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Yu Z, Chen Z, Chen C, Huang J, He X, Zhao J, Li W, Zhao C, He J, Dong Y, Liu C, Wei FF. Cerebral small vessel disease and cognitive dysfunction in relation to central systolic blood pressure. Eur J Intern Med 2025:S0953-6205(25)00171-2. [PMID: 40312224 DOI: 10.1016/j.ejim.2025.04.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2025] [Revised: 04/15/2025] [Accepted: 04/22/2025] [Indexed: 05/03/2025]
Abstract
BACKGROUND Higher blood pressure (BP) is closely associated with cerebral small vessel disease (CSVD) and poor cognition. However, little is known about the association of CSVD and cognitive dysfunction with central BP. METHODS In 1447 participants (59.3 % women; mean age, 76.0 years) enrolled in the Atherosclerosis Risk in Communities (ARIC) study, we investigated the associations of MRI-defined CSVD, characterized by log-transformed white matter hyperintensity volumes (log-WMHv), and the presence of lacunar infarct, lobar and subcortical microhemorrhages, and cognitive function determined by the Mini Mental State Examination score with per 1-SD increment in central systolic BP (cSBP) derived by applanation tonometry. The model performance was assessed by the area under the receiver operating characteristic curve (AUC). RESULTS After adjusted for potential confounders, cSBP was associated with log-WMHv (β, 0.031; p = 0.003) and lobar (OR, 1.58; p < 0.001) and subcortical microhemorrhages (OR, 1.20; p = 0.011). Adding cSBP to the base model enhanced the model performance for the risk of lobar microhemorrhages (p = 0.042), while AUC did not statistically increase with the addition of peripheral SBP (p = 0.49). Irrespective of adjustments, the associations of cSBP with CSVD markers and cognitive dysfunction were much stronger for Blacks compared with Whites. Incorporating cSBP into the base model significantly improved AUC from 0.63 to 0.68 (p = 0.042) for subcortical microhemorrhages in Blacks. CONCLUSION cSBP was associated with CSVD and cognition impairment. Our observations highlight that cSBP may help further investigation for the prevention strategies of CSVD.
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Affiliation(s)
- Zhongping Yu
- Department of Cardiology, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China; NHC Key Laboratory of Assisted Circulation and Vascular Diseases, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Zihao Chen
- Department of Cardiology, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China; NHC Key Laboratory of Assisted Circulation and Vascular Diseases, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Chang Chen
- Department of Cardiology, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China; NHC Key Laboratory of Assisted Circulation and Vascular Diseases, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Jiale Huang
- Department of Cardiology, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China; NHC Key Laboratory of Assisted Circulation and Vascular Diseases, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Xin He
- Department of Cardiology, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China; NHC Key Laboratory of Assisted Circulation and Vascular Diseases, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Jingjing Zhao
- Department of Cardiology, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China; NHC Key Laboratory of Assisted Circulation and Vascular Diseases, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Wenqing Li
- Department of Cardiology, Huiya Hospital of the First Affiliated Hospital, Sun Yat-Sen University, Huizhou, Guangdong, China
| | - Cuiping Zhao
- Department of Cardiology, Huiya Hospital of the First Affiliated Hospital, Sun Yat-Sen University, Huizhou, Guangdong, China
| | - Jiangui He
- Department of Cardiology, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China; NHC Key Laboratory of Assisted Circulation and Vascular Diseases, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Yugang Dong
- Department of Cardiology, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China; NHC Key Laboratory of Assisted Circulation and Vascular Diseases, Sun Yat-Sen University, Guangzhou, Guangdong, China; National Guangdong Joint Engineering Laboratory for Diagnosis and Treatment of Vascular Disease, Guangzhou, China
| | - Chen Liu
- Department of Cardiology, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China; NHC Key Laboratory of Assisted Circulation and Vascular Diseases, Sun Yat-Sen University, Guangzhou, Guangdong, China; National Guangdong Joint Engineering Laboratory for Diagnosis and Treatment of Vascular Disease, Guangzhou, China.
| | - Fang-Fei Wei
- Department of Cardiology, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China; NHC Key Laboratory of Assisted Circulation and Vascular Diseases, Sun Yat-Sen University, Guangzhou, Guangdong, China; National Guangdong Joint Engineering Laboratory for Diagnosis and Treatment of Vascular Disease, Guangzhou, China.
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Matsulevits A, Alves P, Atzori M, Beyh A, Corbetta M, Pup FD, Dulyan L, Foulon C, Hope T, Ioannucci S, Jobard G, Lemaître H, Neville D, Nozais V, Rorden C, Saprikis OV, Sibon I, Sperber C, Teghipco A, Thirion B, Tshimanga LF, Umarova R, Vaidelyte EB, van den Hoven E, Rodriguez EV, Zanola A, Tourdias T, de Schotten MT. A global effort to benchmark predictive models and reveal mechanistic diversity in long-term stroke outcomes. RESEARCH SQUARE 2025:rs.3.rs-6254029. [PMID: 40321754 PMCID: PMC12047981 DOI: 10.21203/rs.3.rs-6254029/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/10/2025]
Abstract
Stroke remains a leading cause of mortality and long-term disability worldwide, with variable recovery trajectories posing substantial challenges in anticipating post-event care and rehabilitation planning. To address these challenges, we established the NeuralCup consortium to benchmark predictive models of stroke outcome through a collaborative, data-driven approach. This study presents findings from 15 international teams who used a comprehensive dataset including clinical and imaging data, to identify and compare predictors of motor, cognitive, and emotional outcomes one year post-stroke. Our analyses integrated traditional statistical approaches and novel machine learning algorithms to uncover 'optimal recipes' for predicting each domain. The differences in these 'optimal recipes' reflect distinct brain mechanisms in response to different tasks. Key predictors across all domains included infarct characteristics, T1-weighted MRI sequences, and demographic factors. Additionally, integrating FLAIR imaging and white matter tract analysis significantly improved the prediction of cognitive and motor outcomes, respectively. These findings support a multifaceted approach to stroke outcome prediction, underscoring the potential of collaborative data science to develop personalized care strategies that enhance recovery and quality of life for stroke survivors. To encourage further model development and validation, we provide access to the training dataset at http://neuralcup.bcblab.com.
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Affiliation(s)
- Anna Matsulevits
- Groupe d'Imagerie Neurofonctionnelle Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA, University of Bordeaux, Bordeaux, France ; Brain Connectivity and Behaviour La
| | - Pedro Alves
- Centro de Estudos Egas Moniz, Faculdade de Medicina, Universidade de Lisboa
| | | | | | | | | | | | - Chris Foulon
- UCL Queen Square Institute of Neurology, University College London
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Ryu WS, Schellingerhout D, Park J, Chung J, Jeong SW, Gwak DS, Kim BJ, Kim JT, Hong KS, Lee KB, Park TH, Park SS, Park JM, Kang K, Cho YJ, Park HK, Lee BC, Yu KH, Oh MS, Lee SJ, Kim JG, Cha JK, Kim DH, Lee J, Park MS, Kim D, Bang OY, Kim EY, Sohn CH, Kim H, Bae HJ, Kim DE. Deep learning-based automatic segmentation of cerebral infarcts on diffusion MRI. Sci Rep 2025; 15:13214. [PMID: 40240396 PMCID: PMC12003832 DOI: 10.1038/s41598-025-91032-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2024] [Accepted: 02/18/2025] [Indexed: 04/18/2025] Open
Abstract
We explored effects of (1) training with various sample sizes of multi-site vs. single-site training data, (2) cross-site domain adaptation, and (3) data sources and features on the performance of algorithms segmenting cerebral infarcts on Magnetic Resonance Imaging (MRI). We used 10,820 annotated diffusion-weighted images (DWIs) from 10 university hospitals. Algorithms based on 3D U-net were trained using progressively larger subsamples (ranging from 217 to 8661), while internal testing employed a distinct set of 2159 DWIs. External validation was conducted using three unrelated datasets (n = 2777, 50, and 250). For domain adaptation, we utilized 50 to 1000 subsamples from the 2777-image external target dataset. As the size of the multi-site training data increased from 217 to 1732, the Dice similarity coefficient (DSC) and average Hausdorff distance (AHD) improved from 0.58 to 0.65 and from 16.1 to 3.75 mm, respectively. Further increases in sample size to 4330 and 8661 led to marginal gains in DSC (to 0.68 and 0.70, respectively) and in AHD (to 2.92 and 1.73). Similar outcomes were observed in external testing. Notably, performance was relatively poor for segmenting brainstem or hyperacute (< 3 h) infarcts. Domain adaptation, even with a small subsample (n = 50) of external data, conditioned the algorithm trained with 217 images to perform comparably to an algorithm trained with 8661 images. In conclusion, the use of multi-site data (approximately 2000 DWIs) and domain adaptation significantly enhances the performance and generalizability of deep learning algorithms for infarct segmentation.
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Affiliation(s)
- Wi-Sun Ryu
- Artificial Intelligence Research Center, JLK Inc., Seoul, South Korea
- National Priority Research Center for Stroke and Department of Neurology, Dongguk University Ilsan Hospital, 27, Dongguk-ro, Ilsandong-gu, Goyang, South Korea
| | - Dawid Schellingerhout
- Department of Neuroradiology and Imaging Physics, The University of Texas M.D. Anderson Cancer Center, Houston, USA
| | - Jonghyeok Park
- Artificial Intelligence Research Center, JLK Inc., Seoul, South Korea
| | - Jinyong Chung
- National Priority Research Center for Stroke and Department of Neurology, Dongguk University Ilsan Hospital, 27, Dongguk-ro, Ilsandong-gu, Goyang, South Korea
- Bioimaging Data Curation Center, Seoul, South Korea
| | - Sang-Wuk Jeong
- National Priority Research Center for Stroke and Department of Neurology, Dongguk University Ilsan Hospital, 27, Dongguk-ro, Ilsandong-gu, Goyang, South Korea
| | - Dong-Seok Gwak
- National Priority Research Center for Stroke and Department of Neurology, Dongguk University Ilsan Hospital, 27, Dongguk-ro, Ilsandong-gu, Goyang, South Korea
- Bioimaging Data Curation Center, Seoul, South Korea
| | - Beom Joon Kim
- Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, South Korea
| | - Joon-Tae Kim
- Department of Neurology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, South Korea
| | - Keun-Sik Hong
- Department of Neurology, Inje University Ilsan Paik Hospital, Inje University College of Medicine, Goyang, South Korea
| | - Kyung Bok Lee
- Department of Neurology, Soonchunhyang University Hospital, College of Medical Science, Soon Chun Hyang University, Seoul, South Korea
| | - Tai Hwan Park
- Department of Neurology, Seoul Medical Center, Seoul, South Korea
| | - Sang-Soon Park
- Department of Neurology, Seoul Medical Center, Seoul, South Korea
| | - Jong-Moo Park
- Department of Neurology, Uijeongbu Eulji Medical Center, Eulji University School of Medicine, Uijeongbu, South Korea
| | - Kyusik Kang
- Department of Neurology, Nowon Eulji Medical Center, Eulji University School of Medicine, Seoul, South Korea
| | - Yong-Jin Cho
- Department of Neurology, Inje University Ilsan Paik Hospital, Inje University College of Medicine, Goyang, South Korea
| | - Hong-Kyun Park
- Department of Neurology, Inje University Ilsan Paik Hospital, Inje University College of Medicine, Goyang, South Korea
| | - Byung-Chul Lee
- Department of Neurology, Hallym University Sacred Heart Hospital, College of Medicine, Hallym University, Anyang, South Korea
| | - Kyung-Ho Yu
- Department of Neurology, Hallym University Sacred Heart Hospital, College of Medicine, Hallym University, Anyang, South Korea
| | - Mi Sun Oh
- Department of Neurology, Hallym University Sacred Heart Hospital, College of Medicine, Hallym University, Anyang, South Korea
| | - Soo Joo Lee
- Department of Neurology, Eulji University Hospital, Eulji University School of Medicine, Daejeon, South Korea
| | - Jae Guk Kim
- Department of Neurology, Eulji University Hospital, Eulji University School of Medicine, Daejeon, South Korea
| | - Jae-Kwan Cha
- Department of Neurology, Dong-A University Hospital, Dong-A University College of Medicine, Busan, South Korea
| | - Dae-Hyun Kim
- Department of Neurology, Dong-A University Hospital, Dong-A University College of Medicine, Busan, South Korea
| | - Jun Lee
- Department of Neurology, Yeungnam University Hospital, Daegu, South Korea
| | - Man Seok Park
- Department of Neurology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, South Korea
| | - Dongmin Kim
- Artificial Intelligence Research Center, JLK Inc., Seoul, South Korea
| | - Oh Young Bang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Eung Yeop Kim
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Chul-Ho Sohn
- Department of Radiology, College of Medicine, Seoul National University, Seoul, South Korea
| | - Hosung Kim
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Hee-Joon Bae
- Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, South Korea
| | - Dong-Eog Kim
- National Priority Research Center for Stroke and Department of Neurology, Dongguk University Ilsan Hospital, 27, Dongguk-ro, Ilsandong-gu, Goyang, South Korea.
- Bioimaging Data Curation Center, Seoul, South Korea.
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Peng Y, Luo D, Zeng P, Zeng B, Xiang Y, Wang D, Chai Y, Li Y, Chen X, Luo T. Impact of white matter hyperintensity location on outcome in acute ischemic stroke patients: a lesion-symptom mapping study. Brain Imaging Behav 2025; 19:269-278. [PMID: 39753847 DOI: 10.1007/s11682-024-00962-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/08/2024] [Indexed: 04/09/2025]
Abstract
BACKGROUND Studies on the impact of white matter hyperintensity (WMH) on function outcome have primarily concentrated on WMH volume, overlooking the potential significance of WMH location. This study aimed to investigate the relationship between WMH location and outcome in patients with their first-ever acute ischemic stroke (AIS). METHODS Patients who underwent their first AIS between September 2021 and September 2022 were recruited. Function outcome was assessed using the 90-day modified Rankin Scale (mRS). The association between the location of WMH and functional outcome was examined at the voxel level and subsequently at the region of interest tract-based level. RESULTS A total of 134 patients were included (mean age, 66.28 years ± 12.48; 90 male [67.16%]). The median mRS was 2 (IQR, 1-3). The median total WMH volume was 3.80 cm3 (IQR, 2.07-6.78). WMH volume was significantly correlated with mRS (r = 0.28, p = 0.001). WMH in the splenium of corpus callosum, the left superior corona radiata, the left posterior corona radiata, and the bilateral posterior thalamic radiation were associated with poor mRS. The strategic WMH score (OR, 1.18; 95% CI, 1.06-1.32; p = 0.003), derived from these five specific tracts, was an independent predictor of mRS after accounting for the effects of total WMH volume (OR, 1.02; 95% CI, 0.90-1.16; p = 0.771) and infarct lesion volume (OR, 1.26; 95% CI, 1.08-1.48; p = 0.004). CONCLUSION Our findings indicated that the impact of WMH on function outcome is location-dependent, mainly involving five strategic tracts. Evaluating WMH location may help to more accurately predict the functional outcome of AIS.
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Affiliation(s)
- Yuling Peng
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Dan Luo
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Peng Zeng
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Bang Zeng
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Yayun Xiang
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Dan Wang
- Department of Radiology, Mianyang Central Hospital, Mianyang, 621000, China
| | - Ying Chai
- Department of Radiology, People's Hospital of Shapingba District, Chongqing, 400010, China
| | - Yongmei Li
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Xiaoya Chen
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
| | - Tianyou Luo
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
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Yum KS, Chung JW, Ha SY, Park KY, Shin DI, Park HK, Cho YJ, Hong KS, Kim JG, Lee SJ, Kim JT, Seo WK, Bang OY, Kim GM, Lee M, Kim D, Sunwoo L, Bae HJ, Ryu WS, Kim BJ. A multicenter validation and calibration of automated software package for detecting anterior circulation large vessel occlusion on CT angiography. BMC Neurol 2025; 25:100. [PMID: 40065263 PMCID: PMC11892136 DOI: 10.1186/s12883-025-04107-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2024] [Accepted: 02/25/2025] [Indexed: 03/14/2025] Open
Abstract
PURPOSE To validate JLK-LVO, a software detecting large vessel occlusion (LVO) on computed tomography angiography (CTA), within a multicenter dataset. METHODS From 2021 to 2023, we enrolled patients with ischemic stroke who underwent CTA within 24-hour of onset at six university hospitals for validation and calibration datasets and at another university hospital for an independent dataset for testing model calibration. The diagnostic performance was evaluated using area under the curve (AUC), sensitivity, and specificity across the entire study population and specifically in patients with isolated middle cerebral artery (MCA)-M2 occlusion. We calibrated LVO probabilities using logistic regression and by grouping LVO probabilities based on observed frequency. RESULTS After excluding 168 patients, 796 remained; the mean (SD) age was 68.9 (13.7) years, and 57.7% were men. LVO was present in 193 (24.3%) of patients, and the median interval from last-known-well to CTA was 5.7 h (IQR 2.5-12.1 h). The software achieved an AUC of 0.944 (95% CI 0.926-0.960), with a sensitivity of 89.6% (84.5-93.6%) and a specificity of 90.4% (87.7-92.6%). In isolated MCA-M2 occlusion, the AUROC was 0.880 (95% CI 0.824-0.921). Due to sparse data between 20 and 60% of LVO probabilities, recategorization into unlikely (0-20% LVO scores), less likely (20-60%), possible (60-90%), and suggestive (90-100%) provided a reliable estimation of LVO compared with mathematical calibration. The category of LVO probabilities was associated with follow-up infarct volumes and functional outcome. CONCLUSION In this multicenter study, we proved the clinical efficacy of the software in detecting LVO on CTA.
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Affiliation(s)
- Kyu Sun Yum
- Department of Neurology, College of Medicine, Chungbuk National University Hospital, Chungbuk National University, Cheongju, Republic of Korea
| | - Jong-Won Chung
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University College of Medicine, Seoul, Republic of Korea
| | - Sue Young Ha
- Artificial Intelligence Research Center, JLK Inc, Seoul, Republic of Korea
- Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Kwang-Yeol Park
- Department of Neurology, Chung-Ang University College of Medicine, Chung-Ang University Hospital, Seoul, Republic of Korea
| | - Dong-Ick Shin
- Department of Neurology, College of Medicine, Chungbuk National University Hospital, Chungbuk National University, Cheongju, Republic of Korea
| | - Hong-Kyun Park
- Department of Neurology, Inje University Ilsan Paik Hospital, Inje University College of Medicine, Goyang, Republic of Korea
| | - Yong-Jin Cho
- Department of Neurology, Inje University Ilsan Paik Hospital, Inje University College of Medicine, Goyang, Republic of Korea
| | - Keun-Sik Hong
- Department of Neurology, Inje University Ilsan Paik Hospital, Inje University College of Medicine, Goyang, Republic of Korea
| | - Jae Guk Kim
- Department of Neurology, Daejeon Eulji Medical Center, Eulji University School of Medicine, Daejeon, Republic of Korea
| | - Soo Joo Lee
- Department of Neurology, Daejeon Eulji Medical Center, Eulji University School of Medicine, Daejeon, Republic of Korea
| | - Joon-Tae Kim
- Department of Neurology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, Republic of Korea
| | - Woo-Keun Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University College of Medicine, Seoul, Republic of Korea
| | - Oh Young Bang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University College of Medicine, Seoul, Republic of Korea
| | - Gyeong-Moon Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University College of Medicine, Seoul, Republic of Korea
| | - Myungjae Lee
- Artificial Intelligence Research Center, JLK Inc, Seoul, Republic of Korea
| | - Dongmin Kim
- Artificial Intelligence Research Center, JLK Inc, Seoul, Republic of Korea
| | - Leonard Sunwoo
- Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea
| | - Hee-Joon Bae
- Department of Neurology, Seoul National University College of Medicine, Seongnam, Republic of Korea
- Cerebrovascular Disease Center, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Wi-Sun Ryu
- Artificial Intelligence Research Center, JLK Inc, Seoul, Republic of Korea.
| | - Beom Joon Kim
- Department of Neurology, Seoul National University College of Medicine, Seongnam, Republic of Korea.
- Cerebrovascular Disease Center, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
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Matsulevits A, Alvez P, Atzori M, Beyh A, Corbetta M, Pup FD, Dulyan L, Foulon C, Hope T, Ioannucci S, Jobard G, Lemaitre H, Neville D, Nozais V, Rorden C, Saprikis OV, Sibon I, Sperber C, Teghipco A, Thirion B, Tshimanga LF, Umarova R, Vaidelyte EB, van den Hoven E, Rodriguez EV, Zanola A, Tourdias T, de Schotten MT. A global effort to benchmark predictive models and reveal mechanistic diversity in long-term stroke outcomes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2024.10.17.618691. [PMID: 39464108 PMCID: PMC11507916 DOI: 10.1101/2024.10.17.618691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/29/2024]
Abstract
Stroke remains a leading cause of mortality and long-term disability worldwide, with variable recovery trajectories posing substantial challenges in anticipating post-event care and rehabilitation planning. To address these challenges, we established the NeuralCup consortium to benchmark predictive models of stroke outcome through a collaborative, data-driven approach. This study presents findings from 15 international teams who used a comprehensive dataset including clinical and imaging data, to identify and compare predictors of motor, cognitive, and emotional outcomes one year post-stroke. Our analyses integrated traditional statistical approaches and novel machine learning algorithms to uncover 'optimal recipes' for predicting each domain. The differences in these 'optimal recipes' reflect distinct brain mechanisms in response to different tasks. Key predictors across all domains included infarct characteristics, T1-weighted MRI sequences, and demographic factors. Additionally, integrating FLAIR imaging and white matter tract analysis significantly improved the prediction of cognitive and motor outcomes, respectively. These findings support a multifaceted approach to stroke outcome prediction, underscoring the potential of collaborative data science to develop personalized care strategies that enhance recovery and quality of life for stroke survivors. To encourage further model development and validation, we provide access to the training dataset at http://neuralcup.bcblab.com.
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Kim H, Ryu WS, Schellingerhout D, Park J, Chung J, Jeong SW, Gwak DS, Kim BJ, Kim JT, Hong KS, Lee KB, Park TH, Park JM, Kang K, Cho YJ, Lee BC, Yu KH, Oh MS, Lee SJ, Cha JK, Kim DH, Lee J, Park MS, Bae HJ, Kim DE. Automated Segmentation of MRI White Matter Hyperintensities in 8421 Patients with Acute Ischemic Stroke. AJNR Am J Neuroradiol 2024; 45:1885-1894. [PMID: 39013565 PMCID: PMC11630893 DOI: 10.3174/ajnr.a8418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 07/09/2024] [Indexed: 07/18/2024]
Abstract
BACKGROUND AND PURPOSE To date, only a few small studies have attempted deep learning-based automatic segmentation of white matter hyperintensity (WMH) lesions in patients with cerebral infarction; this issue is complicated because stroke-related lesions can obscure WMH borders. We developed and validated deep learning algorithms to segment WMH lesions accurately in patients with cerebral infarction using multisite data sets involving 8421 patients with acute ischemic stroke. MATERIALS AND METHODS We included 8421 patients with stroke from 9 centers in Korea. 2D UNet and squeeze-and-excitation (SE)-UNet models were trained using 2408 FLAIR MRIs from 3 hospitals and validated using 6013 FLAIR MRIs from 6 hospitals. WMH segmentation performance was assessed by calculating the Dice similarity coefficient (DSC), the correlation coefficient, and the concordance correlation coefficient compared with a human-segmented criterion standard. In addition, we obtained an uncertainty index that represents overall ambiguity in the voxel classification for WMH segmentation in each patient based on the Kullback-Leibler divergence. RESULTS In the training data set, the mean age was 67.4 (SD, 13.0) years, and 60.4% were men. The mean (95% CI) DSCs for UNet in internal testing and external validation were, respectively, 0.659 (0.649-0.669) and 0.710 (0.707-0.714), which were slightly lower than the reliability between humans (DSC = 0.744; 95% CI, 0.738-0.751; P = .031). Compared with the UNet, the SE-UNet demonstrated better performance, achieving a mean DSC of 0.675 (95% CI, 0.666-0.685; P < .001) in the internal testing and 0.722 (95% CI, 0.719-0.726; P < .001) in the external validation; moreover, it achieved high DSC values (ranging from 0.672 to 0.744) across multiple validation data sets. We observed a significant correlation between WMH volumes that were segmented automatically and manually for the UNet (r = 0.917, P < .001), and it was even stronger for the SE-UNet (r = 0.933, P < .001). The SE-UNet also attained a high concordance correlation coefficient (ranging from 0.841 to 0.956) in the external test data sets. In addition, the uncertainty indices in most patients (86%) in the external data sets were <0.35, with an average DSC of 0.744 in these patients. CONCLUSIONS We developed and validated deep learning algorithms to segment WMH in patients with acute cerebral infarction using the largest-ever MRI data sets. In addition, we showed that the uncertainty index can be used to identify cases in which automatic WMH segmentation is less accurate and requires human review.
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Affiliation(s)
- Hosung Kim
- From the USC Stevens Neuroimaging and Informatics Institute (H.K.), Keck School of Medicine of USC, University of Southern California, Los Angeles, California
| | - Wi-Sun Ryu
- Artificial Intelligence Research Center (W.-S.R, J.P.), JLK Inc, Seoul, Republic of Korea
- National Priority Research Center for Stroke and Department of Neurology (W.-S.R, J.C., S.-W.J., D.-S.G., D.-E.K.), Dongguk University Ilsan Hospital, Goyang, Republic of Korea
| | - Dawid Schellingerhout
- Department of Neuroradiology and Imaging Physics (D.S.), The University of Texas M.D. Anderson Cancer Center, Houston, Texas
| | - Jonghyeok Park
- Artificial Intelligence Research Center (W.-S.R, J.P.), JLK Inc, Seoul, Republic of Korea
| | - Jinyong Chung
- National Priority Research Center for Stroke and Department of Neurology (W.-S.R, J.C., S.-W.J., D.-S.G., D.-E.K.), Dongguk University Ilsan Hospital, Goyang, Republic of Korea
- Bioimaging Data Curation Center (J.C., D.-S.G., D.-E.K.), KOREA-BioData Station, Daejeon, Republic of Korea
| | - Sang-Wuk Jeong
- National Priority Research Center for Stroke and Department of Neurology (W.-S.R, J.C., S.-W.J., D.-S.G., D.-E.K.), Dongguk University Ilsan Hospital, Goyang, Republic of Korea
| | - Dong-Seok Gwak
- National Priority Research Center for Stroke and Department of Neurology (W.-S.R, J.C., S.-W.J., D.-S.G., D.-E.K.), Dongguk University Ilsan Hospital, Goyang, Republic of Korea
- Bioimaging Data Curation Center (J.C., D.-S.G., D.-E.K.), KOREA-BioData Station, Daejeon, Republic of Korea
| | - Beom Joon Kim
- Department of Neurology (B.J.K., H.-J.B.), Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Joon-Tae Kim
- Department of Neurology (J.-T.K., M.S.P.,), Chonnam National University Hospital, Gwangju, Republic of Korea
| | - Keun-Sik Hong
- Department of Neurology (K.-S.H., Y,-J.C.), Inje University Ilsan Paik Hospital, Goyang, Republic of Korea
| | - Kyung Bok Lee
- Department of Neurology (K.B.L.), Soonchunhyang University Hospital, Seoul, Republic of Korea
| | - Tai Hwan Park
- Department of Neurology (T.H.P.), Seoul Medical Center, Seoul, Republic of Korea
| | - Jong-Moo Park
- Department of Neurology (J.-M.P.), Uijeongbu Eulji Medical Center, Uijeongbu, Republic of Korea
| | - Kyusik Kang
- Department of Neurology (K.K.), Nowon Eulji Medical Center, Eulji University School of Medicine, Seoul, Republic of Korea
| | - Yong-Jin Cho
- Department of Neurology (K.-S.H., Y,-J.C.), Inje University Ilsan Paik Hospital, Goyang, Republic of Korea
| | - Byung-Chul Lee
- Department of Neurology (B.-C.L., K.-H.Y., M.S.O.), Hallym University Sacred Heart Hospital, Anyang, Republic of Korea
| | - Kyung-Ho Yu
- Department of Neurology (B.-C.L., K.-H.Y., M.S.O.), Hallym University Sacred Heart Hospital, Anyang, Republic of Korea
| | - Mi Sun Oh
- Department of Neurology (B.-C.L., K.-H.Y., M.S.O.), Hallym University Sacred Heart Hospital, Anyang, Republic of Korea
| | - Soo Joo Lee
- Department of Neurology (S.J.L.), Eulji University Hospital, Daejeon, Republic of Korea
| | - Jae-Kwan Cha
- Department of Neurology (J.-K.C., D.-H.K.), Dong-A University Hospital, Busan, Republic of Korea
| | - Dae-Hyun Kim
- Department of Neurology (J.-K.C., D.-H.K.), Dong-A University Hospital, Busan, Republic of Korea
| | - Jun Lee
- Department of Neurology (J.L.), Yeungnam University Hospital, Daegu, Republic of Korea
| | - Man Seok Park
- Department of Neurology (J.-T.K., M.S.P.,), Chonnam National University Hospital, Gwangju, Republic of Korea
| | - Hee-Joon Bae
- Department of Neurology (B.J.K., H.-J.B.), Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Dong-Eog Kim
- National Priority Research Center for Stroke and Department of Neurology (W.-S.R, J.C., S.-W.J., D.-S.G., D.-E.K.), Dongguk University Ilsan Hospital, Goyang, Republic of Korea
- Bioimaging Data Curation Center (J.C., D.-S.G., D.-E.K.), KOREA-BioData Station, Daejeon, Republic of Korea
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Chen JL, Wang R, Ma PQ, Wang YM, Tang QQ. Association between intercellular adhesion molecule-1 to depression and blood-brain barrier penetration in cerebellar vascular disease. World J Psychiatry 2024; 14:1661-1670. [PMID: 39564172 PMCID: PMC11572681 DOI: 10.5498/wjp.v14.i11.1661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2024] [Revised: 09/10/2024] [Accepted: 09/18/2024] [Indexed: 11/07/2024] Open
Abstract
BACKGROUND Cerebral small vessel disease (CSVD) is a prevalent cerebrovascular disease in clinical practice that is often associated with macrovascular disease. A clear understanding of the underlying causes of CSVD remains elusive. AIM To explore the association between intercellular adhesion molecule-1 (ICAM-1) and blood-brain barrier (BBB) penetration in CSVD. METHODS This study included patients admitted to Fuyang People's Hospital and Fuyang Community (Anhui, China) between December 2021 and March 2022. The study population comprised 142 patients, including 80 in the CSVD group and 62 in the control group. Depression was present in 53 out of 80 patients with CSVD. Multisequence magnetic resonance imaging (MRI) and dynamic contrast-enhanced MRI were applied in patients to determine the brain volume, cortical thickness, and cortical area of each brain region. Moreover, neuropsychological tests including the Hamilton depression scale, mini-mental state examination, and Montreal cognitive assessment basic scores were performed. RESULTS The multivariable analysis showed that age [P = 0.011; odds ratio (OR) = 0.930, 95% confidence interval (CI): 0.880-0.983] and ICAM-1 levels (P = 0.023; OR = 1.007, 95%CI: 1.001-1.013) were associated with CSVD. Two regions of interest (ROIs; ROI3 and ROI4) in the white matter showed significant (both P < 0.001; 95%CI: 0.419-0.837 and 0.366-0.878) differences between the two groups, whereas only ROI1 in the gray matter showed significant difference (P = 0.046; 95%CI: 0.007-0.680) between the two groups. ICAM-1 was significantly correlated (all P < 0.05) with cortical thickness in multiple brain regions in the CSVD group. CONCLUSION This study revealed that ICAM-1 levels were independently associated with CSVD. ICAM-1 may be associated with cortical thickness in the brain, predominantly in the white matter, and a significant increase in BBB permeability, proposing the involvement of ICAM-1 in BBB destruction.
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Affiliation(s)
- Ju-Luo Chen
- Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China
- The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, Anhui Province, China
- Department of Neurology, Fuyang People’s Hospital, Fuyang 236000, Anhui Province, China
| | - Rui Wang
- The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, Anhui Province, China
| | - Pei-Qi Ma
- Department of Neurology, Fuyang People’s Hospital, Fuyang 236000, Anhui Province, China
| | - You-Meng Wang
- Department of Neurology, Fuyang People’s Hospital, Fuyang 236000, Anhui Province, China
| | - Qi-Qiang Tang
- Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China
- The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, Anhui Province, China
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Zhang L, Su Y, Wang Q, Wang Y, Guo Y. Predictive Value of White Matter Hyperintensities for Early Neurological Deterioration in Patients with Embolic Stroke of Undetermined Source. Neuropsychiatr Dis Treat 2024; 20:2049-2055. [PMID: 39494382 PMCID: PMC11531716 DOI: 10.2147/ndt.s472626] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2024] [Accepted: 10/10/2024] [Indexed: 11/05/2024] Open
Abstract
Objective To explore the role of white matter hyperintensities (WMH) in predicting early neurological deterioration (END) in patients with embolic stroke of undetermined source (ESUS) without reperfusion therapy. Methods In a retrospective analysis, 111 acute ESUS patients not treated with reperfusion therapy were enrolled. WMH severity was evaluated using the Fazekas scale, with patients categorized into mild (Fazekas score ≤ 2) or moderate-to-severe (Fazekas score ≥ 3) WMH groups. Clinical data were compared between the groups, and END was monitored within 72 hours of hospital admission. The association between WMH and END was assessed using binary logistic regression. Results Patients with moderate-to-severe WMH were significantly older (p = 0.001) and more likely to have a history of stroke (28.6% vs 10.5%, p = 0.017) compared to the mild WMH group. The END group (n=16) presented with higher baseline NIHSS scores and a greater prevalence of moderate-to-severe WMH (p < 0.05). Binary logistic regression identified moderate-to-severe WMH (OR = 4.012, 95% CI: 1.080-14.906, p = 0.038), smoking (OR = 4.368, 95% CI: 1.171-16.293, p = 0.028), and diabetes mellitus (OR = 3.986, 95% CI: 1.007-15.789, p = 0.049) as independent predictors of END in ESUS patients. Conclusion Moderate-to-severe WMH is an independent risk factor for END in ESUS patients not receiving reperfusion therapy, highlighting the importance of considering WMH in the clinical evaluation and management of stroke patients.
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Affiliation(s)
- Lihao Zhang
- Department of Neurology, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, Jiangsu Province, People’s Republic of China
| | - Yan Su
- Department of Radiology, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, Jiangsu Province, People’s Republic of China
| | - Qian Wang
- Department of Neurology, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, Jiangsu Province, People’s Republic of China
| | - Yan Wang
- Department of Neurology, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, Jiangsu Province, People’s Republic of China
| | - Yikun Guo
- Department of Neurology, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, Jiangsu Province, People’s Republic of China
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Wang Y, Li H, Pan Y, Wang M, Liao X, Yang Y, Chen W, Meng X, Wang Y, Wang Y. Cerebral small vessel disease was associated with the prognosis in ischemic stroke with atrial fibrillation. CNS Neurosci Ther 2024; 30:e70052. [PMID: 39428892 PMCID: PMC11491548 DOI: 10.1111/cns.70052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Revised: 08/19/2024] [Accepted: 09/05/2024] [Indexed: 10/22/2024] Open
Abstract
BACKGROUND The purpose of this study was to explore the relationship between atrial fibrillation (AF), cerebral small vessel disease (CSVD), and ischemic stroke. METHODS Data were extracted from China's Third National Stroke Registry (CNSR-III), which registered 15,166 patients in China. A total of 12,180 ischemic stroke patients were included excluding those diagnosed with TIA or without MRI. Logistic regression was to explore the relationship between AF, CSVD, and poor functional outcomes at 12-month follow-up. Cox regression is to explore AF, CSVD, and stroke recurrence as well as all-cause mortality at 12-month follow-up. RESULTS The average age was 62.40 ± 11.22 years old, and 8362 (68.65%) were men at baseline. Patients with AF had an increased risk of stroke recurrence and all-cause mortality at 12-month follow-up. Those with AF and CSVD imaging such as lacunes, white matter hyperintensity (WMH), and the presence of cerebral microbleeds (CMBs) had an increased risk of poor prognosis. And those with both AF and CSVD burden had an increased risk of worse prognosis at 12-month follow-up. CONCLUSION Among Chinese patients with acute ischemic stroke, those with AF were associated with a higher risk of 12-month mortality and stroke recurrence. When AF was combined with some CSVD imaging features such as lacunes, WMH, presence of CMBs or burdens, the 12-month poor prognosis worsened.
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Affiliation(s)
- Yicong Wang
- Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Hang Li
- Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
- Department of GeriatricsAffiliated Dalian Friendship Hospital of Dalian Medical UniversityDalianChina
| | - Yuesong Pan
- Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Mengxing Wang
- Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Xiaoling Liao
- Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Yingying Yang
- Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Weiqi Chen
- Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Xia Meng
- Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Yongjun Wang
- Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
- Advanced Innovation Center for Human Brain Protection, Capital Medical UniversityBeijingChina
- Research Unit of Artificial Intelligence in Cerebrovascular DiseaseChinese Academy of Medical SciencesBeijingChina
- Center for Excellence in Brain Science and Intelligence TechnologyChinese Academy of SciencesShanghaiChina
| | - Yilong Wang
- Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
- Advanced Innovation Center for Human Brain Protection, Capital Medical UniversityBeijingChina
- Chinese Institute for Brain ResearchBeijingChina
- Beijing Key Laboratory of Translational Medicine for Cerebrovascular DiseaseBeijingChina
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Sun Y, Xia W, Wei R, Dai Z, Sun X, Zhu J, Song B, Wang H. Quantitative Analysis of White Matter Hyperintensities as a Predictor of 1-Year Risk for Ischemic Stroke Recurrence. Neurol Ther 2024; 13:1467-1482. [PMID: 39136813 PMCID: PMC11393268 DOI: 10.1007/s40120-024-00652-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Accepted: 07/25/2024] [Indexed: 09/14/2024] Open
Abstract
INTRODUCTION This study evaluates the role of quantitative characteristics of white matter hyperintensities (WMHs) in predicting the 1-year recurrence risk of ischemic stroke. METHODS We conducted a retrospective analysis of 1061 patients with ischemic stroke from January 2018 to April 2021. WMHs were automatically segmented using a cluster-based method to quantify their volume and number of clusters (NoC). Additionally, two radiologists independently rated periventricular and deep WMHs using the Fazekas scale. The cohort was divided into a training set (70%) and a testing set (30%). We employed Cox proportional hazards models to develop predictors based on quantitative WMH characteristics, Fazekas scores, and clinical factors, and compared their performance using the concordance index (C-index). RESULTS A total of 180 quantitative variables related to WMHs were extracted. A higher NoC in deep white matter and brainstem, advanced age (> 90 years old), specific stroke subtypes, and absence of discharge antiplatelets showed stronger associations with the risk of ischemic stroke recurrence within 1 year. The nomogram incorporating quantitative WMHs data showed superior discrimination compared to those based on the Fazekas scale or clinical factors alone, with C-index values of 0.709 versus 0.647 and 0.648, respectively, in the testing set. Notably, a combined model including both WMHs and clinical factors achieved the highest predictive accuracy, with a C-index of 0.735 in the testing set. CONCLUSION Quantitative assessment of WMHs provides a valuable neuro-imaging tool for enhancing the prediction of ischemic stroke recurrence risk.
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Affiliation(s)
- Yi Sun
- Department of Radiology, Minhang Hospital, Fudan University, 170 Xinsong Road, Shanghai, 201199, People's Republic of China
| | - Wenping Xia
- Department of Radiology, Ningbo Yinzhou No. 2 Hospital, Ningbo, China
| | - Ran Wei
- Department of Radiology, Minhang Hospital, Fudan University, 170 Xinsong Road, Shanghai, 201199, People's Republic of China
| | - Zedong Dai
- Department of Radiology, Minhang Hospital, Fudan University, 170 Xinsong Road, Shanghai, 201199, People's Republic of China
| | - Xilin Sun
- Department of Radiology, Minhang Hospital, Fudan University, 170 Xinsong Road, Shanghai, 201199, People's Republic of China
| | - Jie Zhu
- Department of Radiology, Minhang Hospital, Fudan University, 170 Xinsong Road, Shanghai, 201199, People's Republic of China
| | - Bin Song
- Department of Radiology, Minhang Hospital, Fudan University, 170 Xinsong Road, Shanghai, 201199, People's Republic of China.
| | - Hao Wang
- Department of Radiology, Minhang Hospital, Fudan University, 170 Xinsong Road, Shanghai, 201199, People's Republic of China.
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Gwak DS, Ryu WS, Schellingerhout D, Chung J, Kim HR, Jeong SW, Kim BJ, Kim JT, Hong KS, Park JM, Park MS, Choi KH, Park TH, Lee K, Park SS, Kang K, Cho YJ, Park HK, Lee BC, Yu KH, Oh MS, Lee SJ, Kim JG, Cha JK, Kim DH, Lee J, Han MK, Lee JS, Bae HJ, Kim DE. Effects of white matter hyperintensity burden on functional outcome after mild versus moderate-to-severe ischemic stroke. Sci Rep 2024; 14:22567. [PMID: 39343768 PMCID: PMC11439954 DOI: 10.1038/s41598-024-71936-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 09/02/2024] [Indexed: 10/01/2024] Open
Abstract
It is uncertain whether the prognostic power of white matter hyperintensity (WMH) on post-stroke outcomes is modulated as a function of initial neurological severity, a critical determinant of outcome after stroke. This multi-center MRI study tested if higher WMH quintiles were associated with 3-month poor functional outcome (modified Rankin Scale ≥ 3) for mild versus moderate-to-severe ischemic stroke. Mild and moderate-to-severe stroke were defined as admission National Institute of Health Stroke Scale scores of 1-4 and ≥ 5, respectively. Mean age of the enrolled patients (n = 8918) was 67.2 ± 12.6 years and 60.1% male. The association between WMH quintiles and poor functional outcome was modified by stroke severity (p-for-interaction = 0.008). In mild stroke (n = 4994), WMH quintiles associated with the 3-month outcome in a dose-dependent manner for the 2nd to 5th quintile versus the 1st quintile, with adjusted-odds-ratios (aOR [95% confidence interval]) being 1.29 [0.96-1.73], 1.37 [1.02-1.82], 1.60 [1.19-2.13], and 1.89 [1.41-2.53], respectively. In moderate-to-severe stroke (n = 3924), however, there seemed to be a threshold effect: only the highest versus the lowest WMH quintile was significantly associated with poor functional outcome (aOR 1.69 [1.29-2.21]). WMH burden aggravates 3-month functional outcome after mild stroke, but has a lesser modulatory effect for moderate-to-severe stroke, likely due to saturation effects.
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Affiliation(s)
- Dong-Seok Gwak
- Department of Neurology, Dongguk University Ilsan Hospital, 52-6 Dongguk-Ro, Ilsandong-Gu, Goyang-si, Gyeonggi-do, 10326, Republic of Korea
- National Priority Research Center for Stroke, Goyang, Republic of Korea
| | - Wi-Sun Ryu
- Artificial Intelligence Research Center, JLK Inc., Seoul, Republic of Korea
| | - Dawid Schellingerhout
- Departments of Neuroradiology and Imaging Physics (D.S.), University of Texas MD Anderson Cancer Center, Houston, USA
| | - Jinyong Chung
- National Priority Research Center for Stroke, Goyang, Republic of Korea
| | - Hang-Rai Kim
- Department of Neurology, Dongguk University Ilsan Hospital, 52-6 Dongguk-Ro, Ilsandong-Gu, Goyang-si, Gyeonggi-do, 10326, Republic of Korea
- National Priority Research Center for Stroke, Goyang, Republic of Korea
| | - Sang-Wuk Jeong
- Department of Neurology, Dongguk University Ilsan Hospital, 52-6 Dongguk-Ro, Ilsandong-Gu, Goyang-si, Gyeonggi-do, 10326, Republic of Korea
- National Priority Research Center for Stroke, Goyang, Republic of Korea
| | - Beom Joon Kim
- Department of Neurology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Joon-Tae Kim
- Department of Neurology, Chonnam National University Hospital, Gwangju, Republic of Korea
| | - Keun-Sik Hong
- Department of Neurology, Inje University Ilsan Paik Hospital, Goyang, Republic of Korea
| | - Jong-Moo Park
- Department of Neurology, Uijeongbu Eulji Medical Center, Uijeongbu, Republic of Korea
| | - Man-Seok Park
- Department of Neurology, Chonnam National University Hospital, Gwangju, Republic of Korea
| | - Kang-Ho Choi
- Department of Neurology, Chonnam National University Hospital, Gwangju, Republic of Korea
| | - Tai Hwan Park
- Department of Neurology, Seoul Medical Center, Seoul, Republic of Korea
| | - Kyungbok Lee
- Department of Neurology, Soonchunhyang University Seoul Hospital, Seoul, Republic of Korea
| | - Sang-Soon Park
- Department of Neurology, Seoul Medical Center, Seoul, Republic of Korea
| | - Kyusik Kang
- Department of Neurology, Nowon Eulji Medical Center, Seoul, Republic of Korea
| | - Yong-Jin Cho
- Department of Neurology, Inje University Ilsan Paik Hospital, Goyang, Republic of Korea
| | - Hong-Kyun Park
- Department of Neurology, Inje University Ilsan Paik Hospital, Goyang, Republic of Korea
| | - Byung-Chul Lee
- Department of Neurology, Hallym University Sacred Heart Hospital, Anyang, Republic of Korea
| | - Kyung-Ho Yu
- Department of Neurology, Hallym University Sacred Heart Hospital, Anyang, Republic of Korea
| | - Mi-Sun Oh
- Department of Neurology, Hallym University Sacred Heart Hospital, Anyang, Republic of Korea
| | - Soo Joo Lee
- Department of Neurology, Eulji University Hospital, Daejeon, Republic of Korea
| | - Jae Guk Kim
- Department of Neurology, Eulji University Hospital, Daejeon, Republic of Korea
| | - Jae-Kwan Cha
- Department of Neurology, Dong-A University Hospital, Busan, Republic of Korea
| | - Dae-Hyun Kim
- Department of Neurology, Dong-A University Hospital, Busan, Republic of Korea
| | - Jun Lee
- Department of Neurology, Yeungnam University Hospital, Daegu, Republic of Korea
| | - Moon-Ku Han
- Department of Neurology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Ji Sung Lee
- Department of Biostatistics, Asan Medical Center, Seoul, Republic of Korea
| | - Hee-Joon Bae
- Department of Neurology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Dong-Eog Kim
- Department of Neurology, Dongguk University Ilsan Hospital, 52-6 Dongguk-Ro, Ilsandong-Gu, Goyang-si, Gyeonggi-do, 10326, Republic of Korea.
- National Priority Research Center for Stroke, Goyang, Republic of Korea.
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Lim JS, Lee JJ, Kim GH, Kim HR, Shin DW, Lee KJ, Baek MJ, Ko E, Kim BJ, Kim S, Ryu WS, Chung J, Kim DE, Gorelick PB, Woo CW, Bae HJ. Subthreshold amyloid deposition, cerebral small vessel disease, and functional brain network disruption in delayed cognitive decline after stroke. Front Aging Neurosci 2024; 16:1430408. [PMID: 39351012 PMCID: PMC11439663 DOI: 10.3389/fnagi.2024.1430408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2024] [Accepted: 08/30/2024] [Indexed: 10/04/2024] Open
Abstract
Background Although its incidence is relatively low, delayed-onset post-stroke cognitive decline (PSCD) may offer valuable insights into the "vascular contributions to cognitive impairment and dementia," particularly concerning the roles of vascular and neurodegenerative mechanisms. We postulated that the functional segregation observed during post-stroke compensation could be disrupted by underlying amyloid pathology or cerebral small vessel disease (cSVD), leading to delayed-onset PSCD. Methods Using a prospective stroke registry, we identified patients who displayed normal cognitive function at baseline evaluation within a year post-stroke and received at least one subsequent assessment. Patients suspected of pre-stroke cognitive decline were excluded. Decliners [defined by a decrease of ≥3 Mini-Mental State Examination (MMSE) points annually or an absolute drop of ≥5 points between evaluations, confirmed with detailed neuropsychological tests] were compared with age- and stroke severity-matched non-decliners. Index-stroke MRI, resting-state functional MRI, and 18F-florbetaben PET were used to identify cSVD, functional network attributes, and amyloid deposits, respectively. PET data from age-, sex-, education-, and apolipoprotein E-matched stroke-free controls within a community-dwelling cohort were used to benchmark amyloid deposition. Results Among 208 eligible patients, 11 decliners and 10 matched non-decliners were identified over an average follow-up of 5.7 years. No significant differences in cSVD markers were noted between the groups, except for white matter hyperintensities (WMHs), which were strongly linked with MMSE scores among decliners (rho = -0.85, p < 0.01). Only one decliner was amyloid-positive, yet subthreshold PET standardized uptake value ratios (SUVR) in amyloid-negative decliners inversely correlated with final MMSE scores (rho = -0.67, p = 0.04). Decliners exhibited disrupted modular structures and more intermingled canonical networks compared to non-decliners. Notably, the somato-motor network's system segregation corresponded with the decliners' final MMSE (rho = 0.67, p = 0.03) and was associated with WMH volume and amyloid SUVR. Conclusion Disruptions in modular structures, system segregation, and inter-network communication in the brain may be the pathophysiological underpinnings of delayed-onset PSCD. WMHs and subthreshold amyloid deposition could contribute to these disruptions in functional brain networks. Given the limited number of patients and potential residual confounding, our results should be considered hypothesis-generating and need replication in larger cohorts in the future.
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Affiliation(s)
- Jae-Sung Lim
- Department of Neurology, Asan Medical Center, Seoul, Republic of Korea
| | - Jae-Joong Lee
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, Republic of Korea
| | - Geon Ha Kim
- Ewha Womans University Mokdong Hospital, Ewha Womans University College of Medicine, Seoul, Republic of Korea
| | - Hang-Rai Kim
- Dongguk University Ilsan Hospital, Dongguk University College of Medicine, Goyang, Republic of Korea
| | - Dong Woo Shin
- Ewha Womans University Mokdong Hospital, Ewha Womans University College of Medicine, Seoul, Republic of Korea
| | - Keon-Joo Lee
- Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Min Jae Baek
- Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea
| | - Eunvin Ko
- Department of Biostatistics, Korea University, Seoul, Republic of Korea
| | - Beom Joon Kim
- Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea
| | - SangYun Kim
- Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea
| | - Wi-Sun Ryu
- Artificial Intelligence Research Center, JLK Inc., Seoul, Republic of Korea
| | - Jinyong Chung
- Medical Science Research Center, Dongguk University Medical Center, Goyang, Republic of Korea
| | - Dong-Eog Kim
- Dongguk University Ilsan Hospital, Dongguk University College of Medicine, Goyang, Republic of Korea
| | - Philip B. Gorelick
- Division of Stroke and Neurocritical Care, Davee Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
| | - Choong-Wan Woo
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, Republic of Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Republic of Korea
| | - Hee-Joon Bae
- Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea
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Lee M, Suh CH, Sohn JH, Kim C, Han SW, Sung JH, Yu KH, Lim JS, Lee SH. Impact of white matter hyperintensity volumes estimated by automated methods using deep learning on stroke outcomes in small vessel occlusion stroke. Front Aging Neurosci 2024; 16:1399457. [PMID: 38974905 PMCID: PMC11224430 DOI: 10.3389/fnagi.2024.1399457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Accepted: 05/31/2024] [Indexed: 07/09/2024] Open
Abstract
Introduction Although white matter hyperintensity (WMH) shares similar vascular risk and pathology with small vessel occlusion (SVO) stroke, there were few studies to evaluate the impact of the burden of WMH volume on early and delayed stroke outcomes in SVO stroke. Materials and methods Using a multicenter registry database, we enrolled SVO stroke patients between August 2013 and November 2022. The WMH volume was estimated by automated methods using deep learning (VUNO Med-DeepBrain, Seoul, South Korea), which was a commercially available segmentation model. After propensity score matching (PSM), we evaluated the impact of WMH volume on early neurological deterioration (END) and poor functional outcomes at 3-month modified Ranking Scale (mRS), defined as mRS score >2 at 3 months, after an SVO stroke. Results Among 1,718 SVO stroke cases, the prevalence of subjects with severe WMH (Fazekas score ≥ 3) was 68.9%. After PSM, END and poor functional outcomes at 3-month mRS (mRS > 2) were higher in the severe WMH group (END: 6.9 vs. 13.5%, p < 0.001; 3-month mRS > 2: 11.4 vs. 24.7%, p < 0.001). The logistic regression analysis using the PSM cohort showed that total WMH volume increased the risk of END [odd ratio [OR], 95% confidence interval [CI]; 1.01, 1.00-1.02, p = 0.048] and 3-month mRS > 2 (OR, 95% CI; 1.02, 1.01-1.03, p < 0.001). Deep WMH was associated with both END and 3-month mRS > 2, but periventricular WMH was associated with 3-month mRS > 2 only. Conclusion This study used automated methods using a deep learning segmentation model to assess the impact of WMH burden on outcomes in SVO stroke. Our findings emphasize the significance of WMH burden in SVO stroke prognosis, encouraging tailored interventions for better patient care.
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Affiliation(s)
- Minwoo Lee
- Department of Neurology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang, Republic of Korea
| | - Chong Hyun Suh
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Jong-Hee Sohn
- Department of Neurology, Chuncheon Sacred Heart Hospital, Hallym University College of Medicine, Chuncheon, Republic of Korea
- Institute of New Frontier Research Team, Hallym University, Chuncheon, Republic of Korea
| | - Chulho Kim
- Department of Neurology, Chuncheon Sacred Heart Hospital, Hallym University College of Medicine, Chuncheon, Republic of Korea
- Institute of New Frontier Research Team, Hallym University, Chuncheon, Republic of Korea
| | - Sang-Won Han
- Department of Neurology, Chuncheon Sacred Heart Hospital, Hallym University College of Medicine, Chuncheon, Republic of Korea
- Institute of New Frontier Research Team, Hallym University, Chuncheon, Republic of Korea
| | - Joo Hye Sung
- Department of Neurology, Chuncheon Sacred Heart Hospital, Hallym University College of Medicine, Chuncheon, Republic of Korea
- Institute of New Frontier Research Team, Hallym University, Chuncheon, Republic of Korea
| | - Kyung-Ho Yu
- Department of Neurology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang, Republic of Korea
| | - Jae-Sung Lim
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Sang-Hwa Lee
- Department of Neurology, Chuncheon Sacred Heart Hospital, Hallym University College of Medicine, Chuncheon, Republic of Korea
- Institute of New Frontier Research Team, Hallym University, Chuncheon, Republic of Korea
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Hervella P, Sampedro-Viana A, Fernández-Rodicio S, Rodríguez-Yáñez M, López-Dequidt I, Pumar JM, Mosqueira AJ, Bazarra-Barreiros M, Abengoza-Bello MT, Ortega-Espina S, Ouro A, Pérez-Mato M, Campos F, Sobrino T, Castillo J, Alonso-Alonso ML, Iglesias-Rey R. Precision Medicine for Blood Glutamate Grabbing in Ischemic Stroke. Int J Mol Sci 2024; 25:6554. [PMID: 38928260 PMCID: PMC11204254 DOI: 10.3390/ijms25126554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Revised: 06/01/2024] [Accepted: 06/09/2024] [Indexed: 06/28/2024] Open
Abstract
Glutamate grabbers, such as glutamate oxaloacetate transaminase (GOT), have been proposed to prevent excitotoxicity secondary to high glutamate levels in stroke patients. However, the efficacy of blood glutamate grabbing by GOT could be dependent on the extent and severity of the disruption of the blood-brain barrier (BBB). Our purpose was to analyze the relationship between GOT and glutamate concentration with the patient's functional status differentially according to BBB serum markers (soluble tumor necrosis factor-like weak inducer of apoptosis (sTWEAK) and leukoaraiosis based on neuroimaging). This retrospective observational study includes 906 ischemic stroke patients. We studied the presence of leukoaraiosis and the serum levels of glutamate, GOT, and sTWEAK in blood samples. Functional outcome was assessed using the modified Rankin Scale (mRS) at 3 months. A significant negative correlation between GOT and glutamate levels at admission was shown in those patients with sTWEAK levels > 2900 pg/mL (Pearson's correlation coefficient: -0.249; p < 0.0001). This correlation was also observed in patients with and without leukoaraiosis (Pearson's correlation coefficients: -0.299; p < 0.001 vs. -0.116; p = 0.024). The logistic regression model confirmed the association of higher levels of GOT with lower odds of poor outcome at 3 months when sTWEAK levels were >2900 pg/mL (OR: 0.41; CI 95%: 0.28-0.68; p < 0.0001) or with leukoaraiosis (OR: 0.75; CI 95%: 0.69-0.82; p < 0.0001). GOT levels are associated with glutamate levels and functional outcomes at 3 months, but only in those patients with leukoaraiosis and elevated sTWEAK levels. Consequently, therapies targeting glutamate grabbing might be more effective in patients with BBB dysfunction.
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Grants
- SAF2017-84267-R, PDC2021-121455-I00 Spanish Ministry of Science and Innovation
- IN607A2022-03, IN607A2022/07 Xunta de Galicia
- PI17/01103, PI22/00938, PI21/01256/, DTS23/00103, RD16/0019/0001, RD21/0006/0003, CB22/05/00067, CPII17/00027, CPII19/00020, CP22/00061, FI22/00200 Instituto de Salud Carlos III
- EAPA_791/2018_ NEUROATLANTIC, 0624_2IQBIONEURO_6_E INTERREG
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Affiliation(s)
- Pablo Hervella
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain; (P.H.); (A.S.-V.); (S.F.-R.); (J.M.P.); (A.J.M.); (M.B.-B.); (M.T.A.-B.); (S.O.-E.); (J.C.)
| | - Ana Sampedro-Viana
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain; (P.H.); (A.S.-V.); (S.F.-R.); (J.M.P.); (A.J.M.); (M.B.-B.); (M.T.A.-B.); (S.O.-E.); (J.C.)
| | - Sabela Fernández-Rodicio
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain; (P.H.); (A.S.-V.); (S.F.-R.); (J.M.P.); (A.J.M.); (M.B.-B.); (M.T.A.-B.); (S.O.-E.); (J.C.)
| | - Manuel Rodríguez-Yáñez
- Stroke Unit, Department of Neurology, Hospital Clínico Universitario, 15706 Santiago de Compostela, Spain;
| | - Iria López-Dequidt
- Department of Neurology, Hospital Clínico Universitario de Ferrol, 15405 Ferrol, Spain;
| | - José M. Pumar
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain; (P.H.); (A.S.-V.); (S.F.-R.); (J.M.P.); (A.J.M.); (M.B.-B.); (M.T.A.-B.); (S.O.-E.); (J.C.)
- Department of Neuroradiology, Hospital Clínico Universitario, Health Research Institute of Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain
| | - Antonio J. Mosqueira
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain; (P.H.); (A.S.-V.); (S.F.-R.); (J.M.P.); (A.J.M.); (M.B.-B.); (M.T.A.-B.); (S.O.-E.); (J.C.)
- Department of Neuroradiology, Hospital Clínico Universitario, Health Research Institute of Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain
| | - Marcos Bazarra-Barreiros
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain; (P.H.); (A.S.-V.); (S.F.-R.); (J.M.P.); (A.J.M.); (M.B.-B.); (M.T.A.-B.); (S.O.-E.); (J.C.)
| | - María Teresa Abengoza-Bello
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain; (P.H.); (A.S.-V.); (S.F.-R.); (J.M.P.); (A.J.M.); (M.B.-B.); (M.T.A.-B.); (S.O.-E.); (J.C.)
| | - Sara Ortega-Espina
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain; (P.H.); (A.S.-V.); (S.F.-R.); (J.M.P.); (A.J.M.); (M.B.-B.); (M.T.A.-B.); (S.O.-E.); (J.C.)
| | - Alberto Ouro
- NeuroAging Group (NEURAL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain; (A.O.); (T.S.)
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - María Pérez-Mato
- Translational Stroke Laboratory (TREAT), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain; (M.P.-M.); (F.C.)
| | - Francisco Campos
- Translational Stroke Laboratory (TREAT), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain; (M.P.-M.); (F.C.)
| | - Tomás Sobrino
- NeuroAging Group (NEURAL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain; (A.O.); (T.S.)
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - José Castillo
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain; (P.H.); (A.S.-V.); (S.F.-R.); (J.M.P.); (A.J.M.); (M.B.-B.); (M.T.A.-B.); (S.O.-E.); (J.C.)
| | - Maria Luz Alonso-Alonso
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain; (P.H.); (A.S.-V.); (S.F.-R.); (J.M.P.); (A.J.M.); (M.B.-B.); (M.T.A.-B.); (S.O.-E.); (J.C.)
| | - Ramón Iglesias-Rey
- Neuroimaging and Biotechnology Laboratory (NOBEL), Clinical Neurosciences Research Laboratory (LINC), Health Research Institute of Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain; (P.H.); (A.S.-V.); (S.F.-R.); (J.M.P.); (A.J.M.); (M.B.-B.); (M.T.A.-B.); (S.O.-E.); (J.C.)
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16
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He G, Fang H, Xue B, Wei L, Lu H, Deng J, Zhu Y. Impact of leukoaraiosis on the infarct growth rate and clinical outcome in acute large vessel occlusion stroke after endovascular thrombectomy. Eur Stroke J 2024; 9:338-347. [PMID: 38230536 PMCID: PMC11318440 DOI: 10.1177/23969873241226771] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 12/31/2023] [Indexed: 01/18/2024] Open
Abstract
INTRODUCTION As a marker of chronic cerebral small vessel disease, leukoaraiosis (LA) was reported to impact the recruitment of collaterals in acute ischemic stroke (AIS). We intended to explore the impact of LA on the infarct growth rate (IGR) and clinical outcome by impaired collateral development in AIS patients with large vessel occlusion (LVO) who underwent endovascular thrombectomy (EVT). PATIENTS AND METHODS Two hundred thirty-six AIS patients who underwent EVT were retrospectively reviewed. The severity of LA was graded using the Fazekas scale with non-contrast CT. IGR was calculated by the acute core volume on CT perfusion divided by the time from stroke onset to imaging. The collateral status after LVO was assessed using the ASITN/SIR collateral scale. The clinical outcomes after EVT were evaluated using a modified Rankin Scale (mRS). The Alberta stroke program early CT score (ASPECTS), the National Institutes of Health Stroke Scale (NIHSS) score at admission, and the modified treatment in cerebral infarction (mTICI) score after EVT were also included. Correlations between those factors were analyzed. RESULTS Patients with severe LA had significantly larger core volume on CTP (p = 0.022) and lower collateral grade (p < 0.001). Faster IGR was significantly associated with higher LA severity (adjusted odds ratio [aOR]: 1.53; 95% CI: 1.02-2.33; p = 0.046), higher NIHSS (aOR: 1.04; 95% CI: 1.00-1.09; p = 0.032) and impaired collaterals (aOR: 2.26; 95% CI: 1.27-4.03; p = 0.005). In mediation analysis, collaterals explained 33% of the effect of LA on fast IGR. There was correlation between the severity of LA and mRS (p = 0.007). DISCUSSION AND CONCLUSION The increasing severity of LA is associated with impaired collateral status and fast infarct growth. These findings suggest that LA may become a predictive imaging biomarker for the likelihood of progression of tissue injury and clinical outcome after EVT in acute large vessel occlusion stroke.
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Affiliation(s)
- Guangchen He
- Department of Radiology, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hui Fang
- Department of Radiology, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Bo Xue
- Department of Neurology, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Liming Wei
- Department of Radiology, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Haitao Lu
- Department of Radiology, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jiangshan Deng
- Department of Neurology, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yueqi Zhu
- Department of Radiology, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
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17
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Huang WQ, Lin Q, Tzeng CM. Leukoaraiosis: Epidemiology, Imaging, Risk Factors, and Management of Age-Related Cerebral White Matter Hyperintensities. J Stroke 2024; 26:131-163. [PMID: 38836265 PMCID: PMC11164597 DOI: 10.5853/jos.2023.02719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 01/15/2024] [Indexed: 06/06/2024] Open
Abstract
Leukoaraiosis (LA) manifests as cerebral white matter hyperintensities on T2-weighted magnetic resonance imaging scans and corresponds to white matter lesions or abnormalities in brain tissue. Clinically, it is generally detected in the early 40s and is highly prevalent globally in individuals aged >60 years. From the imaging perspective, LA can present as several heterogeneous forms, including punctate and patchy lesions in deep or subcortical white matter; lesions with periventricular caps, a pencil-thin lining, and smooth halo; as well as irregular lesions, which are not always benign. Given its potential of having deleterious effects on normal brain function and the resulting increase in public health burden, considerable effort has been focused on investigating the associations between various risk factors and LA risk, and developing its associated clinical interventions. However, study results have been inconsistent, most likely due to potential differences in study designs, neuroimaging methods, and sample sizes as well as the inherent neuroimaging heterogeneity and multi-factorial nature of LA. In this article, we provided an overview of LA and summarized the current knowledge regarding its epidemiology, neuroimaging classification, pathological characteristics, risk factors, and potential intervention strategies.
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Affiliation(s)
- Wen-Qing Huang
- Department of Central Laboratory, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Qing Lin
- Department of Neurology, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, Fujian, China
- Xiamen Clinical Research Center for Neurological Diseases, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, Fujian, China
- Fujian Provincial Clinical Research Center for Brain Diseases, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, Fujian, China
- The Third Clinical College, Fujian Medical University, Fuzhou, Fujian, China
| | - Chi-Meng Tzeng
- Translational Medicine Research Center, School of Pharmaceutical Sciences, Xiamen University, Xiamen, Fujian, China
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18
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Fu C, Xu J, Chen SL, Chen CB, Liang JJ, Liu Z, Huang C, Wu Z, Ng TK, Zhang M, Liu Q. Profile of Lipoprotein Subclasses in Chinese Primary Open-Angle Glaucoma Patients. Int J Mol Sci 2024; 25:4544. [PMID: 38674129 PMCID: PMC11050298 DOI: 10.3390/ijms25084544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 04/16/2024] [Accepted: 04/17/2024] [Indexed: 04/28/2024] Open
Abstract
To investigate the plasma lipoprotein subclasses in patients with primary open-angle glaucoma (POAG), a total of 20 Chinese POAG patients on intraocular pressure (IOP)-lowering treatment and 20 age-matched control subjects were recruited. Based on the levels of total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C), the study subjects were divided into elevated- and normal-level subgroups. The plasma lipoprotein, lipoprotein subclasses, and oxidized LDL (oxLDL) levels were quantitatively measured. The discrimination potential of the lipoproteins was evaluated using the area under the receiver operating characteristic curve (AUC), and their correlation with clinical parameters was also evaluated. Compared to the control subjects with elevated TC and/or LDL-C levels, the levels of TC, LDL-C, non-high-density lipoprotein cholesterol (non-HDL), LDL subclass LDL3 and small dense LDL (sdLDL), and oxLDL were significantly higher in POAG patients with elevated TC and/or LDL-C levels. No differences in any lipoproteins or the subclasses were found between the POAG patients and control subjects with normal TC and LDL-C levels. Moderate-to-good performance of TC, LDL-C, non-HDL, LDL3, sdLDL, and oxLDL was found in discriminating between the POAG patients and control subjects with elevated TC and/or LDL-C levels (AUC: 0.710-0.950). Significant negative correlations between LDL3 and sdLDL with retinal nerve fiber layer (RNFL) thickness in the superior quadrant and between LDL3 and average RNFL thickness were observed in POAG patients with elevated TC and/or LDL-C levels. This study revealed a significant elevation of plasma lipoproteins, especially the LDL subclasses, in POAG patients with elevated TC and/or LDL-C levels, providing insights on monitoring specific lipoproteins in POAG patients with elevated TC and/or LDL-C.
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Affiliation(s)
- Changzhen Fu
- Joint Shantou International Eye Center of Shantou University and The Chinese University of Hong Kong, Shantou 515041, China; (C.F.); (J.X.); (S.-L.C.); (C.-B.C.); (J.-J.L.); (Z.L.); (C.H.); (Z.W.); (T.K.N.)
| | - Jianming Xu
- Joint Shantou International Eye Center of Shantou University and The Chinese University of Hong Kong, Shantou 515041, China; (C.F.); (J.X.); (S.-L.C.); (C.-B.C.); (J.-J.L.); (Z.L.); (C.H.); (Z.W.); (T.K.N.)
| | - Shao-Lang Chen
- Joint Shantou International Eye Center of Shantou University and The Chinese University of Hong Kong, Shantou 515041, China; (C.F.); (J.X.); (S.-L.C.); (C.-B.C.); (J.-J.L.); (Z.L.); (C.H.); (Z.W.); (T.K.N.)
| | - Chong-Bo Chen
- Joint Shantou International Eye Center of Shantou University and The Chinese University of Hong Kong, Shantou 515041, China; (C.F.); (J.X.); (S.-L.C.); (C.-B.C.); (J.-J.L.); (Z.L.); (C.H.); (Z.W.); (T.K.N.)
| | - Jia-Jian Liang
- Joint Shantou International Eye Center of Shantou University and The Chinese University of Hong Kong, Shantou 515041, China; (C.F.); (J.X.); (S.-L.C.); (C.-B.C.); (J.-J.L.); (Z.L.); (C.H.); (Z.W.); (T.K.N.)
| | - Zibo Liu
- Joint Shantou International Eye Center of Shantou University and The Chinese University of Hong Kong, Shantou 515041, China; (C.F.); (J.X.); (S.-L.C.); (C.-B.C.); (J.-J.L.); (Z.L.); (C.H.); (Z.W.); (T.K.N.)
| | - Chukai Huang
- Joint Shantou International Eye Center of Shantou University and The Chinese University of Hong Kong, Shantou 515041, China; (C.F.); (J.X.); (S.-L.C.); (C.-B.C.); (J.-J.L.); (Z.L.); (C.H.); (Z.W.); (T.K.N.)
| | - Zhenggen Wu
- Joint Shantou International Eye Center of Shantou University and The Chinese University of Hong Kong, Shantou 515041, China; (C.F.); (J.X.); (S.-L.C.); (C.-B.C.); (J.-J.L.); (Z.L.); (C.H.); (Z.W.); (T.K.N.)
| | - Tsz Kin Ng
- Joint Shantou International Eye Center of Shantou University and The Chinese University of Hong Kong, Shantou 515041, China; (C.F.); (J.X.); (S.-L.C.); (C.-B.C.); (J.-J.L.); (Z.L.); (C.H.); (Z.W.); (T.K.N.)
- Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Mingzhi Zhang
- Joint Shantou International Eye Center of Shantou University and The Chinese University of Hong Kong, Shantou 515041, China; (C.F.); (J.X.); (S.-L.C.); (C.-B.C.); (J.-J.L.); (Z.L.); (C.H.); (Z.W.); (T.K.N.)
| | - Qingping Liu
- Joint Shantou International Eye Center of Shantou University and The Chinese University of Hong Kong, Shantou 515041, China; (C.F.); (J.X.); (S.-L.C.); (C.-B.C.); (J.-J.L.); (Z.L.); (C.H.); (Z.W.); (T.K.N.)
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Sperber C, Hakim A, Gallucci L, Arnold M, Umarova RM. Cerebral small vessel disease and stroke: Linked by stroke aetiology, but not stroke lesion location or size. J Stroke Cerebrovasc Dis 2024; 33:107589. [PMID: 38244646 DOI: 10.1016/j.jstrokecerebrovasdis.2024.107589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 01/07/2024] [Accepted: 01/17/2024] [Indexed: 01/22/2024] Open
Abstract
BACKGROUND Cerebral small vessel disease (SVD) has previously been associated with worse stroke outcome, vascular dementia, and specific post-stroke cognitive deficits. The underlying causal mechanisms of these associations are not yet fully understood. We investigated whether a relationship between SVD and certain stroke aetiologies or a specific stroke lesion anatomy provides a potential explanation. METHODS In a retrospective observational study, we examined 859 patients with first-ever, non-SVD anterior circulation ischemic stroke (age = 69.0±15.2). We evaluated MRI imaging markers to assess an SVD burden score and mapped stroke lesions on diffusion-weighted MRI. We investigated the association of SVD burden with i) stroke aetiology, and ii) lesion anatomy using topographical statistical mapping. RESULTS With increasing SVD burden, stroke of cardioembolic aetiology was more frequent (ρ = 0.175; 95 %-CI = 0.103;0.244), whereas cervical artery dissection (ρ = -0.143; 95 %-CI = -0.198;-0.087) and a patent foramen ovale (ρ = -0.165; 95 %-CI = -0.220;-0.104) were less frequent stroke etiologies. However, no significant associations between SVD burden and stroke aetiology remained after additionally controlling for age (all p>0.125). Lesion-symptom-mapping and Bayesian statistics showed that SVD burden was not associated with a specific stroke lesion anatomy or size. CONCLUSIONS In patients with a high burden of SVD, non-SVD stroke is more likely to be caused by cardioembolic aetiology. The common risk factor of advanced age may link both pathologies and explain some of the existing associations between SVD and stroke. The SVD burden is not related to a specific stroke lesion location.
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Affiliation(s)
- Christoph Sperber
- Department of Neurology, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland
| | - Arsany Hakim
- University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland
| | - Laura Gallucci
- Department of Neurology, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland
| | - Marcel Arnold
- Department of Neurology, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland
| | - Roza M Umarova
- Department of Neurology, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland.
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Cougo P, Colares H, Farinhas JG, Hämmerle M, Neves P, Bezerra R, Balduino A, Wu O, Pontes-Neto OM. Subtle white matter intensity changes on fluid-attenuated inversion recovery imaging in patients with ischaemic stroke. Brain Commun 2024; 6:fcae089. [PMID: 38529359 PMCID: PMC10963121 DOI: 10.1093/braincomms/fcae089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 01/12/2024] [Accepted: 03/11/2024] [Indexed: 03/27/2024] Open
Abstract
Leukoaraiosis is a neuroimaging marker of small-vessel disease that is characterized by high signal intensity on fluid-attenuated inversion recovery MRI. There is increasing evidence from pathology and neuroimaging suggesting that the structural abnormalities that characterize leukoaraiosis are actually present within regions of normal-appearing white matter, and that the underlying pathophysiology of white matter damage related to small-vessel disease involves blood-brain barrier damage. In this study, we aim to verify whether leukoaraiosis is associated with elevated signal intensity on fluid-attenuated inversion recovery imaging, a marker of brain tissue free-water accumulation, in normal-appearing white matter. We performed a cross-sectional study of adult patients admitted to our hospital with a diagnosis of acute ischaemic stroke or transient ischaemic attack. Leukoaraiosis was segmented using a semi-automated method involving manual outlining and signal thresholding. White matter regions were segmented based on the probabilistic tissue maps from the International Consortium for Brain Mapping 152 atlas. Also, normal-appearing white matter was further segmented based on voxel distance from leukoaraiosis borders, resulting in five normal-appearing white matter strata at increasing voxel distances from leukoaraiosis. The relationship between mean normalized fluid-attenuated inversion recovery signal intensity on normal-appearing white matter and leukoaraiosis volume was studied in a multivariable statistical analysis using linear mixed modelling, having normal-appearing white matter strata as a clustering variable. One hundred consecutive patients meeting inclusion and exclusion criteria were selected for analysis (53% female, mean age 68 years). Mean normalized fluid-attenuated inversion recovery signal intensity on normal-appearing white matter was higher in the vicinity of leukoaraiosis and progressively lower at increasing distances from leukoaraiosis. In a multivariable analysis, the mean normalized fluid-attenuated inversion recovery signal intensity on normal-appearing white matter was positively associated with leukoaraiosis volume and age (B = 0.025 for each leukoaraiosis quartile increase; 95% confidence interval 0.019-0.030). This association was found similarly across normal-appearing white matter strata. Voxel maps of the mean normalized fluid-attenuated inversion recovery signal intensity on normal-appearing white matter showed an increase in signal intensity that was not adjacent to leukoaraiosis regions. Our results show that normal-appearing white matter exhibits subtle signal intensity changes on fluid-attenuated inversion recovery imaging that are related to leukoaraiosis burden. These results suggest that diffuse free-water accumulation is likely related to the aetiopathogenic processes underlying the development of white matter damage related to small-vessel disease.
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Affiliation(s)
- Pedro Cougo
- Instituto Americas, Neurology Division, Rio de Janeiro 22775-001, Brazil
- Hospital Samaritano Barra, Department of Neurology, Rio de Janeiro 22775-001, Brazil
| | - Heber Colares
- Hospital Samaritano Barra, Department of Radiology, Rio de Janeiro, 22775-001, Brazil
| | - João Gabriel Farinhas
- Instituto Americas, Neurology Division, Rio de Janeiro 22775-001, Brazil
- Hospital Samaritano Barra, Department of Neurology, Rio de Janeiro 22775-001, Brazil
| | - Mariana Hämmerle
- Hospital Samaritano Barra, Department of Neurology, Rio de Janeiro 22775-001, Brazil
| | - Pedro Neves
- Hospital Samaritano Barra, Department of Radiology, Rio de Janeiro, 22775-001, Brazil
| | - Raquel Bezerra
- Hospital Samaritano Barra, Department of Radiology, Rio de Janeiro, 22775-001, Brazil
| | - Alex Balduino
- Instituto Americas, Neurology Division, Rio de Janeiro 22775-001, Brazil
| | - Ona Wu
- Athinoula A. Martinos Centre for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Octavio M Pontes-Neto
- Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto 14040-900, Brazil
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21
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Oliveira LC, Bonkhoff AK, Regenhardt RW, Alhadid K, Tuozzo C, Etherton MR, Rost NS, Schirmer MD. Neuroimaging markers of patient-reported outcome measures in acute ischemic stroke. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.27.23299829. [PMID: 38234738 PMCID: PMC10793527 DOI: 10.1101/2023.12.27.23299829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Objectives To determine the relationship between patient-reported outcome measures (PROMs) and volumetric imaging markers in acute ischemic stroke (AIS). Patients and Methods Patients presenting at Massachusetts General Hospital between February 14, 2017 and February 5, 2020 with a confirmed AIS by MRI were eligible and underwent a telephone interview including PROM-10 questionnaires 3-15 months after stroke. White matter hyperintensity (VWMH) and brain volumes (VBrain) were automatically determined using admission clinical MRI. Stroke lesions were manually segmented and volumes calculated (VLesion). Multivariable and ordinal regression analyses were performed to identify associations between global and PROM-10 subscores with brain volumetrics and clinical variables. Results Utilizing data from 167 patients (mean age: 64.7; 41.9% female), higher VWMH was associated with worse global physical (β=-0.6), global mental (β=-0.65), physical health (OR=0.68), social satisfaction (OR=0.66), fatigue (OR=0.69) and social activities (OR=0.59) scores. Higher VLesion was associated with poorer global mental (β=-0.79), mental health (OR=0.68), physical (OR=0.66) and social activities (OR=0.55), and emotional distress (OR=0.68) scores. Higher VBrain was linked to better global mental (β=0.93), global physical (β=0.79), mental health (OR=1.54) and physical activities (OR=1.72) scores. Conclusions Neuroimaging biomarkers were significantly associated with PROMs, where higher VWMH and VLesion led to worse outcome, while higher VBrain was protective. The inclusion of neuroimaging analyses and PROMs in routine assessment provides enhanced understanding of post-stroke outcomes.
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Affiliation(s)
- Lara C Oliveira
- J Philip Kistler Stroke Research Center. Department of Neurology. Massachusetts General Hospital. Harvard Medical School, Boston, MA, United States of America
| | - Anna K Bonkhoff
- J Philip Kistler Stroke Research Center. Department of Neurology. Massachusetts General Hospital. Harvard Medical School, Boston, MA, United States of America
| | - Robert W Regenhardt
- J Philip Kistler Stroke Research Center. Department of Neurology. Massachusetts General Hospital. Harvard Medical School, Boston, MA, United States of America
| | - Kenda Alhadid
- J Philip Kistler Stroke Research Center. Department of Neurology. Massachusetts General Hospital. Harvard Medical School, Boston, MA, United States of America
| | - Carissa Tuozzo
- J Philip Kistler Stroke Research Center. Department of Neurology. Massachusetts General Hospital. Harvard Medical School, Boston, MA, United States of America
| | - Mark R Etherton
- Biogen Inc. Stroke/Acute Neurology Neurovascular Therapeutics Development Unit. Cambridge, MA. USA
| | - Natalia S Rost
- J Philip Kistler Stroke Research Center. Department of Neurology. Massachusetts General Hospital. Harvard Medical School, Boston, MA, United States of America
| | - Markus D Schirmer
- J Philip Kistler Stroke Research Center. Department of Neurology. Massachusetts General Hospital. Harvard Medical School, Boston, MA, United States of America
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22
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Gunkel S, Schötzau A, Fluri F. Burden of cerebral small vessel disease and changes of diastolic blood pressure affect clinical outcome after acute ischemic stroke. Sci Rep 2023; 13:22070. [PMID: 38086878 PMCID: PMC10716411 DOI: 10.1038/s41598-023-49502-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 12/08/2023] [Indexed: 12/18/2023] Open
Abstract
Elevated and low blood pressure (BP) may lead to poor functional outcome after ischemic stroke, which is conflicting. Hence, there must be another factor-such as cerebral small vessel disease (cSVD) -interacting with BP and thus, affecting outcome. Here, we investigate the relationship between BP and cSVD regarding outcome after stroke. Data of 423/503 stroke patients were prospectively analyzed. Diastolic (DBP) and systolic BP (SBP) were collected on hospital admission (BPad) and over the first 72 h (BP72h). cSVD-burden was determined on MR-scans. Good functional outcome was defined as a modified Rankin Scale score ≤ 2 at hospital discharge and 12 months thereafter. cSVD was a predictor of poor outcome (OR 2.8; p < 0.001). SBPad, DBPad and SBP72h were not significantly associated with outcome at any time. A significant relationship was found between DBP72h, (p < 0.01), cSVD (p = 0.013) and outcome at discharge. At 12 months, we found a relationship between outcome and DBP72h (p = 0.018) and a statistical tendency regarding cSVD (p = 0.08). Changes in DBP72h were significantly related with outcome. There was a U-shaped relationship between DBP72h and outcome at discharge. Our results suggest an individualized stroke care by either lowering or elevating DBP depending on cSVD-burden in order to influence functional outcome.
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Affiliation(s)
- Sarah Gunkel
- Department of Neurology, University Hospital Würzburg, Josef-Schneider Strasse 11, 97080, Würzburg, Germany
| | - Andreas Schötzau
- Eudox Statistics, Basel, Switzerland
- Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Felix Fluri
- Department of Neurology, University Hospital Würzburg, Josef-Schneider Strasse 11, 97080, Würzburg, Germany.
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23
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Lim J, Lee K, Kim BJ, Ryu W, Chung J, Gwak D, Lee JS, Kim S, Ko E, Lee J, Han M, Smith EE, Kim D, Bae H. Nonhypertensive White Matter Hyperintensities in Stroke: Risk Factors, Neuroimaging Characteristics, and Prognosis. J Am Heart Assoc 2023; 12:e030515. [PMID: 38014679 PMCID: PMC10727348 DOI: 10.1161/jaha.123.030515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Accepted: 11/03/2023] [Indexed: 11/29/2023]
Abstract
BACKGROUND This study explored the risk factors, neuroimaging features, and prognostic implications of nonhypertensive white matter hyperintensity (WMH) in patients with acute ischemic stroke and transient ischemic attack. METHODS AND RESULTS We included 2283 patients with hypertension and 1003 without from a pool of 10 602. Associations of moderate-to-severe WMH with known risk factors, functional outcome, and a composite of recurrent stroke, myocardial infarction, and all-cause mortality were evaluated. A subset of 351 patients without hypertension and age- and sex-matched pairs with hypertension and moderate-to-severe WMH was created for a detailed topographic examination of WMH, lacunes, and microbleeds. Approximately 35% of patients without hypertension and 65% of patients with hypertensive stroke exhibited moderate-to-severe WMH. WMH was associated with age, female sex, and previous stroke, irrespective of hypertension. In patients without hypertension, WMH was associated with initial systolic blood pressure and was more common in the anterior temporal region. In patients with hypertension, WMH was associated with small vessel occlusion as a stroke mechanism and was more frequent in the periventricular region near the posterior horn of the lateral ventricle. The higher prevalence of occipital microbleeds in patients without hypertension and deep subcortical lacunes in patients with hypertension were also observed. Associations of moderate-to-severe WMH with 3-month functional outcome and 1-year cumulative incidence of the composite outcome were significant (both P<0.01), although the latter lost significance after adjustments. The associations between WMH and outcomes were consistent across hypertensive status. CONCLUSIONS One-third of patients without hypertension with stroke have moderate-to-severe WMH. The pathogenesis of WMH may differ between patients without and with hypertension, but its impact on outcome appears similar.
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Affiliation(s)
- Jae‐Sung Lim
- Department of Neurology, Asan Medical CenterUniversity of Ulsan College of MedicineSeoulRepublic of Korea
| | - Keon‐Joo Lee
- Department of NeurologyKorea University Guro Hospital, Korea University College of MedicineSeoulRepublic of Korea
| | - Beom Joon Kim
- Department of NeurologySeoul National University Bundang Hospital, Seoul National University College of MedicineSeongnamRepublic of Korea
| | | | - Jinyong Chung
- Medical Science Research CenterDongguk University Medical CenterGoyangRepublic of Korea
| | - Dong‐Seok Gwak
- Department of NeurologyDongguk University Ilsan Hospital, Dongguk University College of MedicineGoyangRepublic of Korea
| | - Ji Sung Lee
- Clinical Research CenterAsan Institute for Life Sciences, Asan Medical CenterSeoulRepublic of Korea
| | - Seong‐Eun Kim
- Department of NeurologySeoul National University Bundang Hospital, Seoul National University College of MedicineSeongnamRepublic of Korea
| | - Eunvin Ko
- Department of BiostatisticsKorea UniversitySeoulRepublic of Korea
| | - Juneyoung Lee
- Department of BiostatisticsKorea UniversitySeoulRepublic of Korea
| | - Moon‐Ku Han
- Department of NeurologySeoul National University Bundang Hospital, Seoul National University College of MedicineSeongnamRepublic of Korea
| | - Eric E. Smith
- Department of Clinical Neuroscience and Hotchkiss Brain Institute, Cumming School of MedicineUniversity of CalgaryCalgaryCanada
| | - Dong‐Eog Kim
- Department of NeurologyDongguk University Ilsan Hospital, Dongguk University College of MedicineGoyangRepublic of Korea
| | - Hee‐Joon Bae
- Department of NeurologySeoul National University Bundang Hospital, Seoul National University College of MedicineSeongnamRepublic of Korea
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24
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Brito AC, Levy DF, Schneck SM, Entrup JL, Onuscheck CF, Casilio M, de Riesthal M, Davis LT, Wilson SM. Leukoaraiosis Is Not Associated With Recovery From Aphasia in the First Year After Stroke. NEUROBIOLOGY OF LANGUAGE (CAMBRIDGE, MASS.) 2023; 4:536-549. [PMID: 37946731 PMCID: PMC10631799 DOI: 10.1162/nol_a_00115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 06/28/2023] [Indexed: 11/12/2023]
Abstract
After a stroke, individuals with aphasia often recover to a certain extent over time. This recovery process may be dependent on the health of surviving brain regions. Leukoaraiosis (white matter hyperintensities on MRI reflecting cerebral small vessel disease) is one indication of compromised brain health and is associated with cognitive and motor impairment. Previous studies have suggested that leukoaraiosis may be a clinically relevant predictor of aphasia outcomes and recovery, although findings have been inconsistent. We investigated the relationship between leukoaraiosis and aphasia in the first year after stroke. We recruited 267 patients with acute left hemispheric stroke and coincident fluid attenuated inversion recovery MRI. Patients were evaluated for aphasia within 5 days of stroke, and 174 patients presented with aphasia acutely. Of these, 84 patients were evaluated at ∼3 months post-stroke or later to assess longer-term speech and language outcomes. Multivariable regression models were fit to the data to identify any relationships between leukoaraiosis and initial aphasia severity, extent of recovery, or longer-term aphasia severity. We found that leukoaraiosis was present to varying degrees in 90% of patients. However, leukoaraiosis did not predict initial aphasia severity, aphasia recovery, or longer-term aphasia severity. The lack of any relationship between leukoaraiosis severity and aphasia recovery may reflect the anatomical distribution of cerebral small vessel disease, which is largely medial to the white matter pathways that are critical for speech and language function.
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Affiliation(s)
| | - Deborah F. Levy
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sarah M. Schneck
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jillian L. Entrup
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Caitlin F. Onuscheck
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Marianne Casilio
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Michael de Riesthal
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - L. Taylor Davis
- Department of Radiology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Stephen M. Wilson
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Radiology, Vanderbilt University Medical Center, Nashville, TN, USA
- School of Health and Rehabilitation Sciences, University of Queensland, Brisbane, Australia
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25
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Dimaras T, Merkouris E, Tsiptsios D, Christidi F, Sousanidou A, Orgianelis I, Polatidou E, Kamenidis I, Karatzetzou S, Gkantzios A, Ntatsis C, Kokkotis C, Retsidou S, Aristidou M, Karageorgopoulou M, Psatha EA, Aggelousis N, Vadikolias K. Leukoaraiosis as a Promising Biomarker of Stroke Recurrence among Stroke Survivors: A Systematic Review. Neurol Int 2023; 15:994-1013. [PMID: 37606397 PMCID: PMC10443317 DOI: 10.3390/neurolint15030064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 08/11/2023] [Accepted: 08/18/2023] [Indexed: 08/23/2023] Open
Abstract
Stroke is the leading cause of functional disability worldwide, with increasing prevalence in adults. Given the considerable negative impact on patients' quality of life and the financial burden on their families and society, it is essential to provide stroke survivors with a timely and reliable prognosis of stroke recurrence. Leukoaraiosis (LA) is a common neuroimaging feature of cerebral small-vessel disease. By researching the literature of two different databases (MEDLINE and Scopus), the present study aims to review all relevant studies from the last decade, dealing with the clinical utility of pre-existing LA as a prognostic factor for stroke recurrence in stroke survivors. Nineteen full-text articles published in English were identified and included in the present review, with data collected from a total of 34,546 stroke patients. A higher rate of extended LA was strongly associated with stroke recurrence in all stroke subtypes, even after adjustment for clinical risk factors. In particular, patients with ischemic stroke or transient ischemic attack with advanced LA had a significantly higher risk of future ischemic stroke, whereas patients with previous intracerebral hemorrhage and severe LA had a more than 2.5-fold increased risk of recurrent ischemic stroke and a more than 30-fold increased risk of hemorrhagic stroke. Finally, in patients receiving anticoagulant treatment for AF, the presence of LA was associated with an increased risk of recurrent ischemic stroke and intracranial hemorrhage. Because of this valuable predictive information, evaluating LA could significantly expand our knowledge of stroke patients and thereby improve overall stroke care.
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Affiliation(s)
- Theofanis Dimaras
- Neurology Department, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (T.D.); (E.M.); (F.C.); (A.S.); (E.P.); (I.K.); (S.K.); (A.G.); (C.N.); (S.R.); (E.A.P.); (K.V.)
| | - Ermis Merkouris
- Neurology Department, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (T.D.); (E.M.); (F.C.); (A.S.); (E.P.); (I.K.); (S.K.); (A.G.); (C.N.); (S.R.); (E.A.P.); (K.V.)
| | - Dimitrios Tsiptsios
- Neurology Department, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (T.D.); (E.M.); (F.C.); (A.S.); (E.P.); (I.K.); (S.K.); (A.G.); (C.N.); (S.R.); (E.A.P.); (K.V.)
| | - Foteini Christidi
- Neurology Department, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (T.D.); (E.M.); (F.C.); (A.S.); (E.P.); (I.K.); (S.K.); (A.G.); (C.N.); (S.R.); (E.A.P.); (K.V.)
| | - Anastasia Sousanidou
- Neurology Department, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (T.D.); (E.M.); (F.C.); (A.S.); (E.P.); (I.K.); (S.K.); (A.G.); (C.N.); (S.R.); (E.A.P.); (K.V.)
| | - Ilias Orgianelis
- Neurology Department, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (T.D.); (E.M.); (F.C.); (A.S.); (E.P.); (I.K.); (S.K.); (A.G.); (C.N.); (S.R.); (E.A.P.); (K.V.)
| | - Efthymia Polatidou
- Neurology Department, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (T.D.); (E.M.); (F.C.); (A.S.); (E.P.); (I.K.); (S.K.); (A.G.); (C.N.); (S.R.); (E.A.P.); (K.V.)
| | - Iordanis Kamenidis
- Neurology Department, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (T.D.); (E.M.); (F.C.); (A.S.); (E.P.); (I.K.); (S.K.); (A.G.); (C.N.); (S.R.); (E.A.P.); (K.V.)
| | - Stella Karatzetzou
- Neurology Department, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (T.D.); (E.M.); (F.C.); (A.S.); (E.P.); (I.K.); (S.K.); (A.G.); (C.N.); (S.R.); (E.A.P.); (K.V.)
| | - Aimilios Gkantzios
- Neurology Department, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (T.D.); (E.M.); (F.C.); (A.S.); (E.P.); (I.K.); (S.K.); (A.G.); (C.N.); (S.R.); (E.A.P.); (K.V.)
| | - Christos Ntatsis
- Neurology Department, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (T.D.); (E.M.); (F.C.); (A.S.); (E.P.); (I.K.); (S.K.); (A.G.); (C.N.); (S.R.); (E.A.P.); (K.V.)
| | - Christos Kokkotis
- Department of Physical Education and Sport Science, Democritus University of Thrace, 69100 Komotini, Greece; (C.K.); (M.A.); (M.K.); (N.A.)
| | - Sofia Retsidou
- Neurology Department, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (T.D.); (E.M.); (F.C.); (A.S.); (E.P.); (I.K.); (S.K.); (A.G.); (C.N.); (S.R.); (E.A.P.); (K.V.)
| | - Maria Aristidou
- Department of Physical Education and Sport Science, Democritus University of Thrace, 69100 Komotini, Greece; (C.K.); (M.A.); (M.K.); (N.A.)
| | - Maria Karageorgopoulou
- Department of Physical Education and Sport Science, Democritus University of Thrace, 69100 Komotini, Greece; (C.K.); (M.A.); (M.K.); (N.A.)
| | - Evlampia A. Psatha
- Neurology Department, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (T.D.); (E.M.); (F.C.); (A.S.); (E.P.); (I.K.); (S.K.); (A.G.); (C.N.); (S.R.); (E.A.P.); (K.V.)
| | - Nikolaos Aggelousis
- Department of Physical Education and Sport Science, Democritus University of Thrace, 69100 Komotini, Greece; (C.K.); (M.A.); (M.K.); (N.A.)
| | - Konstantinos Vadikolias
- Neurology Department, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (T.D.); (E.M.); (F.C.); (A.S.); (E.P.); (I.K.); (S.K.); (A.G.); (C.N.); (S.R.); (E.A.P.); (K.V.)
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26
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Zheng K, Wang Z, Chen X, Chen J, Fu Y, Chen Q. Analysis of Risk Factors for White Matter Hyperintensity in Older Adults without Stroke. Brain Sci 2023; 13:brainsci13050835. [PMID: 37239307 DOI: 10.3390/brainsci13050835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Revised: 05/11/2023] [Accepted: 05/19/2023] [Indexed: 05/28/2023] Open
Abstract
BACKGROUND White matter hyperintensity (WMH) is prevalent in older adults aged 60 and above. A large proportion of people with WMH have not experienced stroke and little has been reported in the literature. METHODS The case data of patients aged ≥60 years without stroke in Wuhan Tongji Hospital from January 2015 to December 2019 were retrospectively analyzed. It was a cross-sectional study. Univariate analysis and logistic regression were used to analyze independent risk factors for WMH. The severity of WMH was assessed using the Fazekas scores. The participants with WMH were divided into periventricular white matter hyperintensity (PWMH) group and deep white matter hyperintensity (DWMH) group, then the risk factors of WMH severity were explored separately. RESULTS Eventually, 655 patients were included; among the patients, 574 (87.6%) were diagnosed with WMH. Binary logistic regression showed that age and hypertension were associated with the prevalence of WMH. Ordinal logistic regression showed that age, homocysteine, and proteinuria were associated with the severity of WMH. Age and proteinuria were associated with the severity of PWMH. Age and proteinuria were associated with the severity of DWMH. CONCLUSIONS The present study showed that in patients aged ≥60 years without stroke, age and hypertension were independent risk factors for the prevalence of WMH; while the increasing of age, homocysteine, and proteinuria were associated with greater WMH burden.
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Affiliation(s)
- Kai Zheng
- Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan 430030, China
| | - Zheng Wang
- Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan 430030, China
| | - Xi Chen
- Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan 430030, China
| | - Jiajie Chen
- Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan 430030, China
| | - Yu Fu
- Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan 430030, China
| | - Qin Chen
- Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan 430030, China
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27
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Li Y, Liu Y, Liu S, Gao M, Wang W, Chen K, Huang L, Liu Y. Diabetic vascular diseases: molecular mechanisms and therapeutic strategies. Signal Transduct Target Ther 2023; 8:152. [PMID: 37037849 PMCID: PMC10086073 DOI: 10.1038/s41392-023-01400-z] [Citation(s) in RCA: 216] [Impact Index Per Article: 108.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Revised: 02/19/2023] [Accepted: 02/28/2023] [Indexed: 04/12/2023] Open
Abstract
Vascular complications of diabetes pose a severe threat to human health. Prevention and treatment protocols based on a single vascular complication are no longer suitable for the long-term management of patients with diabetes. Diabetic panvascular disease (DPD) is a clinical syndrome in which vessels of various sizes, including macrovessels and microvessels in the cardiac, cerebral, renal, ophthalmic, and peripheral systems of patients with diabetes, develop atherosclerosis as a common pathology. Pathological manifestations of DPDs usually manifest macrovascular atherosclerosis, as well as microvascular endothelial function impairment, basement membrane thickening, and microthrombosis. Cardiac, cerebral, and peripheral microangiopathy coexist with microangiopathy, while renal and retinal are predominantly microangiopathic. The following associations exist between DPDs: numerous similar molecular mechanisms, and risk-predictive relationships between diseases. Aggressive glycemic control combined with early comprehensive vascular intervention is the key to prevention and treatment. In addition to the widely recommended metformin, glucagon-like peptide-1 agonist, and sodium-glucose cotransporter-2 inhibitors, for the latest molecular mechanisms, aldose reductase inhibitors, peroxisome proliferator-activated receptor-γ agonizts, glucokinases agonizts, mitochondrial energy modulators, etc. are under active development. DPDs are proposed for patients to obtain more systematic clinical care requires a comprehensive diabetes care center focusing on panvascular diseases. This would leverage the advantages of a cross-disciplinary approach to achieve better integration of the pathogenesis and therapeutic evidence. Such a strategy would confer more clinical benefits to patients and promote the comprehensive development of DPD as a discipline.
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Affiliation(s)
- Yiwen Li
- National Clinical Research Center for Chinese Medicine Cardiology, Xiyuan Hospital, Chinese Academy of Chinese Medical Sciences, Beijing, 100091, China
| | - Yanfei Liu
- National Clinical Research Center for Chinese Medicine Cardiology, Xiyuan Hospital, Chinese Academy of Chinese Medical Sciences, Beijing, 100091, China
- The Second Department of Gerontology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, 100091, China
| | - Shiwei Liu
- Department of Nephrology and Endocrinology, Wangjing Hospital, China Academy of Chinese Medical Sciences, Beijing, 100102, China
| | - Mengqi Gao
- Department of Nephrology and Endocrinology, Wangjing Hospital, China Academy of Chinese Medical Sciences, Beijing, 100102, China
| | - Wenting Wang
- National Clinical Research Center for Chinese Medicine Cardiology, Xiyuan Hospital, Chinese Academy of Chinese Medical Sciences, Beijing, 100091, China
| | - Keji Chen
- National Clinical Research Center for Chinese Medicine Cardiology, Xiyuan Hospital, Chinese Academy of Chinese Medical Sciences, Beijing, 100091, China.
| | - Luqi Huang
- China Center for Evidence-based Medicine of TCM, China Academy of Chinese Medical Sciences, Beijing, 100010, China.
| | - Yue Liu
- National Clinical Research Center for Chinese Medicine Cardiology, Xiyuan Hospital, Chinese Academy of Chinese Medical Sciences, Beijing, 100091, China.
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Wang D, Yan D, Yan M, Li R, Jiang H, Wang J, Yang H. Leukoaraiosis severity is related to increased risk of early neurological deterioration in acute ischemic stroke: a retrospective observational study. Acta Neurol Belg 2023:10.1007/s13760-023-02249-3. [PMID: 37014516 DOI: 10.1007/s13760-023-02249-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Accepted: 03/22/2023] [Indexed: 04/05/2023]
Abstract
OBJECTIVES The relationship between leukoaraiosis and early neurological deterioration in acute cerebral infarction patients remains controversial. We tried to determine whether an association existed between leukoaraiosis and early neurological deterioration in patients with acute ischemic stroke. MATERIALS AND METHODS We retrospectively enrolled acute cerebral infarction patients admitted to our our department within 4.5-72.0 h of symptom onset between January 2016 and March 2022. On the basis of the van Swieten scale, leukoaraiosis was evaluated as supratentorial white matter hypoattenuation on admission head CT and graded as 0 (absent), 1 (mild), 2 (moderate) and 3-4 (severe). Early neurological deterioration was defined as an increase in the National Institute of Health Stroke Scale score by > = 2 points in the total score, or > = 1 point in motor power within the first seven days after admission. RESULTS Among 736 patients, 522 (70.9%) patients had leukoaraiosis, and of these, 332 (63.6%) had mild leukoaraiosis, 41 (7.9%) had moderate leukoaraiosis, and 149 (28.5%) had severe leukoaraiosis. 118 (16.0%) patients experienced early neurological deterioration: 20 of the 214 (9.5%) patients without leukoaraiosis and 98 of the 522 (18.8%) patients with leukoaraiosis. In multiple regression analysis, we found van Swieten scale predicted early neurological deterioration independently (OR = 1.570; 95% CI: 1.226-2.012). CONCLUSIONS Leukoaraiosis is common in acute cerebral infarction patients and leukoaraiosis severity is related to increased risk of early neurological deterioration in the patients.
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Affiliation(s)
- Dan Wang
- Department of Neurology, Hubei NO. 3 People's Hospital of Jianghan University, 26 Zhongshan Road, Qiaokou District, Wuhan, China
| | - Dan Yan
- Department of Neurology, Hubei NO. 3 People's Hospital of Jianghan University, 26 Zhongshan Road, Qiaokou District, Wuhan, China
| | - Mingmin Yan
- Department of Neurology, Hubei NO. 3 People's Hospital of Jianghan University, 26 Zhongshan Road, Qiaokou District, Wuhan, China
| | - Ruifang Li
- Department of Neurology, Hubei NO. 3 People's Hospital of Jianghan University, 26 Zhongshan Road, Qiaokou District, Wuhan, China
| | - Haiwei Jiang
- Department of Neurology, Hubei NO. 3 People's Hospital of Jianghan University, 26 Zhongshan Road, Qiaokou District, Wuhan, China
| | - Juan Wang
- Department of Radiology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China
| | - Hao Yang
- Department of Neurology, Hubei NO. 3 People's Hospital of Jianghan University, 26 Zhongshan Road, Qiaokou District, Wuhan, China.
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Yang M, Liang J, Weng B, Liang J, Lu T, Yang H. Total Cerebral Small Vessel Disease Burden Predicts the Outcome of Acute Stroke Patients after Intra-Arterial Thrombectomy. Cerebrovasc Dis 2023; 52:616-623. [PMID: 36913934 DOI: 10.1159/000528603] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 11/30/2022] [Indexed: 03/14/2023] Open
Abstract
INTRODUCTION Various types of cerebral small vessel diseases (cSVD) markers commonly coexist. The neurological function outcome is affected by their combined effect. To investigate the effect of cSVD on intra-arterial thrombectomy (IAT), our study aimed at developing and testing a model with fusing a combination of multiple cSVD markers as total cSVD burden to predict the outcome of acute ischemic stroke (AIS) patients after IAT treatment. METHODS From October 2018 to March 2021, continuous AIS patients with IAT treatment were enrolled. We calculated the cSVD markers identified by magnetic resonance imaging. The outcomes of all patients were assessed according to the modified Rankin Scale (mRS) score at 90 days after stroke. The relationship between total cSVD burden and outcomes was analyzed by logistics regression analysis. RESULTS A total of 271 AIS patients were included in this study. The proportions of score 0∼4 in the total cSVD burden group (i.e., score 0, 1, 2, 3, and 4 groups) were 9.6%, 19.9%, 23.6%, 32.8%, and 14.0%, respectively. The higher the cSVD score, the more patients with a poor outcome. Heavier total cSVD burden (1.6 [1.01∼2.27]), diabetes mellitus (1.27 [0.28∼2.23]), and higher national institute of health stroke scale (NIHSS) on admission (0.15 [0.07∼0.23]) were associated with poor outcome. In the two Least Absolute Shrinkage and Selection Operator regression models, model 1 using age, duration from onset to reperfusion, Alberta stroke program early CT score (ASPECTS), NIHSS on admission, modified thrombolysis in cerebral infarction (mTICI) and total cSVD burden as variables perform well on predicting short-term outcome in area under curve (AUC) of 0.90. Model 2, including all of the variables above except cSVD, showed less predictive capability than model 1 (AUC 0.90 vs. 0.82, p = 0.045). CONCLUSIONS The total cSVD burden score was independently associated with the clinical outcomes of AIS patients after IAT treatment and it may be a reliable predictor for poor outcomes of AIS patients after IAT treatment.
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Affiliation(s)
- Mengqi Yang
- Department of Neurology and Stroke Center, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, China
| | - Jiahui Liang
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer, Guangzhou, China
| | - Baohui Weng
- Department of Neurology and Stroke Center, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, China
| | - Jinghong Liang
- Department of Neurology and Stroke Center, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, China
| | - Tao Lu
- Department of Neurology and Stroke Center, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, China
| | - Hong Yang
- Department of Neurology and Stroke Center, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, China
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Fu W, Yan L, Hou Z, Yu Y, Zhang W, Cui R, Gao F, Mo D, Lou X, Miao Z, Ma N. Impact of cerebral small vessel disease on symptomatic in-stent restenosis in intracranial atherosclerosis. J Neurosurg 2023; 138:750-759. [PMID: 35962963 DOI: 10.3171/2022.6.jns221103] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 06/09/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Cerebral small vessel disease (CSVD) commonly coexists with intracranial atherosclerotic stenosis (ICAS). In-stent restenosis (ISR) affects the nonprocedural outcome of severe symptomatic ICAS after intracranial stenting. However, only 8%-27% of ISR patients are symptomatic, which highlights the importance of the investigation of risk factors associated with symptomatic ISR (SISR) to improve long-term functional outcome. Whether CSVD is associated with SISR remains unclear. The authors tested the hypothesis that CSVD is associated with SISR in ICAS patients after intracranial stenting. METHODS This retrospective study enrolled 97 patients who were symptomatic due to severe anterior circulation ICAS treated with intracranial stenting. SISR was evaluated with clinical and vascular imaging follow-up. CSVD subtypes, including white matter hyperintensities (WMHs), enlarged perivascular spaces, and chronic lacunar infarctions, were evaluated. Cox regression analysis was used to compare the incidence of SISR between patients with and without CSVD. RESULTS Of the enrolled patients, 58.8% had CSVD. The 1- and 2-year ISR rates were 24.7% and 37.1%, respectively. Of the CSVD subtypes, SISR was associated with deep WMHs (DWMHs; HR 5.39, 95% CI 1.02-28.44). DWMH Fazekas scale grades 2 (HR 85.54, 95% CI 2.42-3018.93) and 3 (HR 66.24, 95% CI 1.87-2352.32) were associated with SISR, but DWMH Fazekas grades 0 and 1 were not. The proportions of SISR in patients with DWMH Fazekas grades 0, 1, 2, and 3 were 16.7%, 33.3%, 50%, and 100%, respectively. CONCLUSIONS Patients with CSVD have a higher risk of SISR than those without CSVD. Of the CSVD subtypes, patients with DWMHs are associated with SISR. The DWMH Fazekas scale score is considered to be a predictor for SISR.
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Affiliation(s)
- Weilun Fu
- 1Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing.,2China National Clinical Research Center for Neurological Diseases, Beijing
| | - Long Yan
- 1Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing.,2China National Clinical Research Center for Neurological Diseases, Beijing
| | - Zhikai Hou
- 1Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing.,2China National Clinical Research Center for Neurological Diseases, Beijing
| | - Ying Yu
- 1Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing.,2China National Clinical Research Center for Neurological Diseases, Beijing
| | - Weiyi Zhang
- 3Department of Neurology, Fuxing Hospital, The Eighth Clinical Medical College, Capital Medical University, Beijing; and
| | - RongRong Cui
- 1Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing.,2China National Clinical Research Center for Neurological Diseases, Beijing
| | - Feng Gao
- 1Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing.,2China National Clinical Research Center for Neurological Diseases, Beijing
| | - Dapeng Mo
- 1Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing.,2China National Clinical Research Center for Neurological Diseases, Beijing
| | - Xin Lou
- 4Department of Radiology, Chinese PLA General Hospital, Beijing, China
| | - Zhongrong Miao
- 1Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing.,2China National Clinical Research Center for Neurological Diseases, Beijing
| | - Ning Ma
- 1Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing.,2China National Clinical Research Center for Neurological Diseases, Beijing
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Wang JL, Cheng XR, Meng ZY, Wang YL. Impact of total cerebral small vessel disease score on ophthalmic artery morphologies and hemodynamics. J Transl Med 2023; 21:65. [PMID: 36726156 PMCID: PMC9890861 DOI: 10.1186/s12967-023-03908-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Accepted: 01/21/2023] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Cerebral small vessel disease (CSVD) is a systemic disease, affecting not only the brain, but also eyes and other organs. The total CSVD score is a tool for comprehensive evaluation of brain lesions in patients with CSVD. The ophthalmic artery (OA) is a direct response to ocular blood flow. However, little is known about the correlation between CSVD and characteristics of OA. We investigated the OA morphologies and hemodynamics in patients with CSVD and the correlation between these changes and the total CSVD score. METHODS This cross-sectional observational study included 34 eyes from 22 patients with CSVD and 10 eyes from 5 healthy controls. The total CSVD score was rated according to the CSVD signs on magnetic resonance imaging. OA morphological characteristics were measured on the basis of 3D OA model reconstruction. OA hemodynamic information was calculated using computational fluid dynamics simulations. RESULTS The total CSVD score negatively correlated with the OA diameter, blood flow velocity, and mass flow ratio (all P < 0.05). After adjusting for potential confounding factors, the total CSVD score was still independently correlated with the OA blood velocity (β = - 0.202, P = 0.005). The total CSVD score was not correlated with OA angle (P > 0.05). The presence of cerebral microbleeds and enlarged perivascular spaces was correlated with the OA diameter (both P < 0.01), while the lacunar infarcts and white matter hyperintensities were correlated with the OA blood velocity (both P < 0.001). CONCLUSIONS The decrease of the blood velocity in the OA was associated with the increase in the total CSVD score. The changes of the OA diameter and velocity were associated with the presence of various CSVD signs. The findings suggest that more studies are needed in the future to evaluate CSVD by observing the morphologies and hemodynamics of OA.
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Affiliation(s)
- Jia-Lin Wang
- Department of Ophthalmology, Beijing Friendship Hospital, Capital Medical University, 95 Yong'an Road, Xicheng District, Beijing, 100050, China.
| | - Xue-Ru Cheng
- Department of Ophthalmology, Beijing Friendship Hospital, Capital Medical University, 95 Yong'an Road, Xicheng District, Beijing, 100050, China
| | - Zhao-Yang Meng
- Department of Ophthalmology, Beijing Friendship Hospital, Capital Medical University, 95 Yong'an Road, Xicheng District, Beijing, 100050, China.
| | - Yan-Ling Wang
- Department of Ophthalmology, Beijing Friendship Hospital, Capital Medical University, 95 Yong'an Road, Xicheng District, Beijing, 100050, China.
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Kim JT, Lee JS, Kim BJ, Park JM, Kang K, Lee SJ, Kim JG, Cha JK, Kim DH, Park TH, Lee KB, Lee J, Hong KS, Cho YJ, Park HK, Lee BC, Yu KH, Oh MS, Kim DE, Ryu WS, Choi JC, Kwon JH, Kim WJ, Shin DI, Yum KS, Sohn SI, Hong JH, Lee SH, Park MS, Choi KH, Lee J, Saver JL, Bae HJ. Frequency, management, and outcomes of early neurologic deterioration due to stroke progression or recurrence. J Stroke Cerebrovasc Dis 2023; 32:106940. [PMID: 36529099 DOI: 10.1016/j.jstrokecerebrovasdis.2022.106940] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 11/23/2022] [Accepted: 12/08/2022] [Indexed: 12/23/2022] Open
Abstract
OBJECTIVE The frequency, management, and outcomes of early neurologic deterioration (END) after ischemic stroke specifically due to stroke progression or stroke recurrence have not been well delineated. MATERIALS AND METHODS In a multicenter, nationwide registry, data on END due to stroke progression or recurrence confirmed by imaging were collected prospectively between January 2019 and July 2020. Patient characteristics, management strategies, and clinical outcomes were analyzed. RESULTS Among 14,828 consecutive ischemic stroke patients, 1717 (11.6%) experienced END, including 1221 (8.2%) with END due to stroke progression (SP) or stroke recurrence (SR). Active management after END was implemented in 64.2% of patients. Active management strategies included volume expansion (29.2%), change in antithrombotic regimen (26.1%), induced hypertension (8.6%), rescue reperfusion therapy (6.8%), intracranial pressure lowering with hyperosmolar agents (1.5%), bypass surgery (0.6%), and hypothermia (0.1%). Active management strategies that varied with patient features included volume expansion and induced hypertension, used more often in large artery atherosclerosis and small vessel occlusion, and rescue endovascular thrombectomy, more common in other (dissection), cardioembolism, and large artery atherosclerosis. Active management was associated with higher rates of freedom from disability (modified Rankin Scale, mRS, 0-1; 24.3% vs. 16.6%) and functional independence (mRS, 0-2; 41.6% vs. 27.7%) at 3 months. CONCLUSION END specifically due to stroke progression or recurrence occurs in 1 in 12 acute ischemic stroke patients. In this observational study, active management, undertaken in two-thirds of patients, was most often hemodynamic or antithrombotic and was associated with improved functional outcomes.
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Affiliation(s)
- Joon-Tae Kim
- Department of Neurology, Chonnam National University Hospital, Chonnam National University Medical School, 42 Jebongro, Dong-gu, Gwangju 61469, Korea.
| | - Ji Sung Lee
- Clinical Research Center, Asan Institute for Life Sciences, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Beom Joon Kim
- Department of Neurology, Seoul National University Bundang Hospital, Cerebrovascular Disease Center, Seongnam-si, Gyeonggi-do, Republic of Korea
| | - Jong-Moo Park
- Department of Neurology, Uijeongbu Eulji Medical Center, Eulji University School of Medicine, Uijeongbu-si, Republic of Korea
| | - Kyusik Kang
- Department of Neurology, Nowon Eulji Medical Center, Eulji University School of Medicine, Seoul, Republic of Korea
| | - Soo Joo Lee
- Department of Neurology, Daejeon Eulji Medical Center, Eulji University School of Medicine, Daejeon, Republic of Korea
| | - Jae Guk Kim
- Department of Neurology, Daejeon Eulji Medical Center, Eulji University School of Medicine, Daejeon, Republic of Korea
| | - Jae-Kwan Cha
- Department of Neurology, Dong-A University Hospital, Busan, Republic of Korea
| | - Dae-Hyun Kim
- Department of Neurology, Dong-A University Hospital, Busan, Republic of Korea
| | - Tai Hwan Park
- Department of Neurology, Seoul Medical Center, Seoul, Republic of Korea
| | - Kyung Bok Lee
- Department of Neurology, Soonchunhyang University Seoul Hospital, Soonchunhyang University College of Medicine, Seoul, Republic of Korea
| | - Jun Lee
- Department of Neurology, Yeungnam University Hospital, Daegu, Republic of Korea
| | - Keun-Sik Hong
- Department of Neurology, Ilsan Paik Hospital, Inje University, Goyang, Republic of Korea
| | - Yong-Jin Cho
- Department of Neurology, Ilsan Paik Hospital, Inje University, Goyang, Republic of Korea
| | - Hong-Kyun Park
- Department of Neurology, Ilsan Paik Hospital, Inje University, Goyang, Republic of Korea
| | - Byung-Chul Lee
- Department of Neurology, Hallym University Sacred Heart Hospital, Anyang, Republic of Korea
| | - Kyung-Ho Yu
- Department of Neurology, Hallym University Sacred Heart Hospital, Anyang, Republic of Korea
| | - Mi Sun Oh
- Department of Neurology, Hallym University Sacred Heart Hospital, Anyang, Republic of Korea
| | - Dong-Eog Kim
- Department of Neurology, Dongguk University Ilsan Hospital, Goyang, Republic of Korea
| | - Wi-Sun Ryu
- Department of Neurology, Dongguk University Ilsan Hospital, Goyang, Republic of Korea; Artificial Intelligence Research Center, JLK Inc., Seoul, Republic of Korea
| | - Jay Chol Choi
- Department of Neurology, Jeju National University Hospital, Jeju National University School of Medicine, Jeju, Republic of Korea
| | - Jee-Hyun Kwon
- Department of Neurology, Ulsan University College of Medicine, Ulsan, Republic of Korea
| | - Wook-Joo Kim
- Department of Neurology, Ulsan University College of Medicine, Ulsan, Republic of Korea
| | - Dong-Ick Shin
- Department of Neurology, Chungbuk National University Hospital, Cheongju, Republic of Korea
| | - Kyu Sun Yum
- Department of Neurology, Chungbuk National University Hospital, Cheongju, Republic of Korea
| | - Sung Il Sohn
- Department of Neurology, Keimyung University Dongsan Medical Center, Daegu, Republic of Korea
| | - Jeong-Ho Hong
- Department of Neurology, Keimyung University Dongsan Medical Center, Daegu, Republic of Korea
| | - Sang-Hwa Lee
- Department of Neurology, Department of Neurology, Hallym University Chuncheon Sacred Heart Hospital, Chuncheon-si, Gangwon-do, Republic of Korea
| | - Man-Seok Park
- Department of Neurology, Chonnam National University Hospital, Chonnam National University Medical School, 42 Jebongro, Dong-gu, Gwangju 61469, Korea
| | - Kang-Ho Choi
- Department of Neurology, Chonnam National University Hospital, Chonnam National University Medical School, 42 Jebongro, Dong-gu, Gwangju 61469, Korea
| | - Juneyoung Lee
- Department of Biostatistics, Korea University College of Medicine, Seoul, Korea
| | - Jeffrey L Saver
- Department of Neurology and Comprehensive Stroke Center, David Geffen School of Medicine, University of California, Los Angeles, CA, United States
| | - Hee-Joon Bae
- Department of Neurology, Seoul National University College of Medicine, Cerebrovascular Disease Center, Seoul National University Bundang Hospital, 82, Gumi-ro 173 beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do 13620, Korea.
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Christidi F, Tsiptsios D, Sousanidou A, Karamanidis S, Kitmeridou S, Karatzetzou S, Aitsidou S, Tsamakis K, Psatha EA, Karavasilis E, Kokkotis C, Aggelousis N, Vadikolias K. The Clinical Utility of Leukoaraiosis as a Prognostic Indicator in Ischemic Stroke Patients. Neurol Int 2022; 14:952-980. [PMID: 36412698 PMCID: PMC9680211 DOI: 10.3390/neurolint14040076] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 11/14/2022] [Accepted: 11/16/2022] [Indexed: 11/19/2022] Open
Abstract
Stroke constitutes a major cause of functional disability with increasing prevalence among adult individuals. Thus, it is of great importance for both clinicians and stroke survivors to be provided with a timely and accurate prognostication of functional outcome. A great number of biomarkers capable of yielding useful information regarding stroke patients' recovery propensity have been evaluated so far with leukoaraiosis being among them. Literature research of two databases (MEDLINE and Scopus) was conducted to identify all relevant studies published between 1 January 2012 and 25 June 2022 that dealt with the clinical utility of a current leukoaraiosis as a prognostic indicator following stroke. Only full-text articles published in English language were included. Forty-nine articles have been traced and are included in the present review. Our findings highlight the prognostic value of leukoaraiosis in an acute stroke setting. The assessment of leukoaraiosis with visual rating scales in CT/MRI imaging appears to be able to reliably provide important insight into the recovery potential of stroke survivors, thus significantly enhancing stroke management. Yielding additional information regarding both short- and long-term functional outcome, motor recovery capacity, hemorrhagic transformation, as well as early neurological deterioration following stroke, leukoaraiosis may serve as a valuable prognostic marker poststroke. Thus, leukoaraiosis represents a powerful prognostic tool, the clinical implementation of which is expected to significantly facilitate the individualized management of stroke patients.
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Affiliation(s)
- Foteini Christidi
- Neurology Department, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece
| | - Dimitrios Tsiptsios
- Neurology Department, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece
- Correspondence:
| | - Anastasia Sousanidou
- Neurology Department, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece
| | - Stefanos Karamanidis
- Neurology Department, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece
| | - Sofia Kitmeridou
- Neurology Department, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece
| | - Stella Karatzetzou
- Neurology Department, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece
| | - Souzana Aitsidou
- Neurology Department, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece
| | - Konstantinos Tsamakis
- Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London SE5 8AF, UK
| | - Evlampia A. Psatha
- Department of Radiology, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece
| | - Efstratios Karavasilis
- Medical Physics Laboratory, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece
| | - Christos Kokkotis
- Department of Physical Education and Sport Science, Democritus University of Thrace, 69100 Komotini, Greece
| | - Nikolaos Aggelousis
- Department of Physical Education and Sport Science, Democritus University of Thrace, 69100 Komotini, Greece
| | - Konstantinos Vadikolias
- Neurology Department, School of Medicine, Democritus University of Thrace, 68100 Alexandroupolis, Greece
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Huang XT, Chen CY, Zhang QF, Lu LH, She YL, Fang XY. Meta-analysis of the efficacy of acupuncture in the treatment of the vascular cognitive impairment associated with cerebral small vessel disease. Explore (NY) 2022:S1550-8307(22)00203-8. [DOI: 10.1016/j.explore.2022.10.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 10/18/2022] [Accepted: 10/25/2022] [Indexed: 11/08/2022]
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Lee M, Kim Y, Oh MS, Yu KH, Lee BC, Kim CH, Mo HJ. Cerebral Small Vessel Disease Burden and Futile Reperfusion after Endovascular Treatment for Patients with Acute Ischemic Stroke. Cerebrovasc Dis 2022; 52:427-434. [PMID: 36273453 DOI: 10.1159/000527020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 09/05/2022] [Indexed: 09/05/2023] Open
Abstract
INTRODUCTION Cerebral small vessel disease (SVD) burden includes increased risk of poor functional outcomes after acute ischemic stroke (AIS). We aimed to investigate the impact of cerebral SVD on 3-month functional outcomes in patients with AIS who received endovascular treatment (EVT) and to determine whether SVD is associated with futile reperfusion (FR). METHODS Using a multicenter stroke registry, we analyzed consecutive patients with AIS with either intracranial and/or extracranial anterior circulation large artery occlusion, who were treated with EVT and achieved successful reperfusion (thrombolysis in cerebral infarction grade 2b-3). The cerebral SVD burden was evaluated using baseline brain magnetic resonance imaging using a modified Fazekas score (mFS). The main outcome variable was FR, defined as poor functional outcomes (modified Rankin scale 3-6) at 3 months after stroke, despite successful recanalization. Secondary outcomes included stroke progression/recurrence and any hemorrhagic transformation. RESULTS Among 10,890 patients with AIS, 577 (5.3%) received EVT within 12 h of onset, including 354 who met study eligibility criteria. FR was observed in 191 patients (53.5%) and was positively associated with SVD burden. After adjustment for covariates including age, sex, stroke etiology, initial stroke severity, collateral status, Alberta stroke program early CT score, initial serum glucose, systemic blood pressure, and vascular risk factors, mFS grade 3 was significantly associated with FR (odds ratio: 3.93, 95% confidence interval: 1.602-9.619; p = 0.003). CONCLUSIONS We demonstrated that cerebral SVD assessed with baseline brain MRI is associated with the futility of successful recanalization after EVT and any hemorrhagic transformation but not with early stroke progression or recurrence. Nevertheless, our findings do not justify withholding EVT in otherwise eligible patients with AIS based on the presence of severe SVD.
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Affiliation(s)
- Minwoo Lee
- Department of Neurology, Hallym University Sacred Heart Hospital, Hallym Neurological Institute, Hallym University College of Medicine, Anyang, Republic of Korea,
- Institute of New Frontier Research Team, Hallym University, Chuncheon, Republic of Korea,
| | - Yerim Kim
- Department of Neurology, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Republic of Korea
| | - Mi Sun Oh
- Department of Neurology, Hallym University Sacred Heart Hospital, Hallym Neurological Institute, Hallym University College of Medicine, Anyang, Republic of Korea
| | - Kyung-Ho Yu
- Department of Neurology, Hallym University Sacred Heart Hospital, Hallym Neurological Institute, Hallym University College of Medicine, Anyang, Republic of Korea
| | - Byung-Chul Lee
- Department of Neurology, Hallym University Sacred Heart Hospital, Hallym Neurological Institute, Hallym University College of Medicine, Anyang, Republic of Korea
| | - Chul-Ho Kim
- Institute of New Frontier Research Team, Hallym University, Chuncheon, Republic of Korea
- Department of Neurology, Chuncheon Sacred Heart Hospital, Hallym University College of Medicine, Chuncheon, Republic of Korea
| | - Hee Jung Mo
- Department of Neurology, Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, Republic of Korea
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Meinel TR, Lerch C, Fischer U, Beyeler M, Mujanovic A, Kurmann C, Siepen B, Scutelnic A, Müller M, Goeldlin M, Belachew NF, Dobrocky T, Gralla J, Seiffge D, Jung S, Arnold M, Wiest R, Meier R, Kaesmacher J. Multivariable Prediction Model for Futile Recanalization Therapies in Patients With Acute Ischemic Stroke. Neurology 2022; 99:e1009-e1018. [PMID: 35803722 PMCID: PMC9519255 DOI: 10.1212/wnl.0000000000200815] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 04/19/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Very poor outcome despite IV thrombolysis (IVT) and mechanical thrombectomy (MT) occurs in approximately 1 of 4 patients with ischemic stroke and is associated with a high logistic and economic burden. We aimed to develop and validate a multivariable prognostic model to identify futile recanalization therapies (FRTs) in patients undergoing those therapies. METHODS Patients from a prospectively collected observational registry of a single academic stroke center treated with MT and/or IVT were included. The data set was split into a training (N = 1,808, 80%) and internal validation (N = 453, 20%) cohort. We used gradient boosted decision tree machine learning models after k-nearest neighbor imputation of 32 variables available at admission to predict FRT defined as modified Rankin scale 5-6 at 3 months. We report feature importance, ability for discrimination, calibration, and decision curve analysis. RESULTS A total of 2,261 patients with a median (interquartile range) age of 75 years (64-83 years), 46% female, median NIH Stroke Scale 9 (4-17), 34% IVT alone, 41% MT alone, and 25% bridging were included. Overall, 539 (24%) had FRT, more often in MT alone (34%) as compared with IVT alone (11%). Feature importance identified clinical variables (stroke severity, age, active cancer, prestroke disability), laboratory values (glucose, C-reactive protein, creatinine), imaging biomarkers (white matter hyperintensities), and onset-to-admission time as the most important predictors. The final model was discriminatory for predicting 3-month FRT (area under the curve 0.87, 95% CI 0.87-0.88) and had good calibration (Brier 0.12, 0.11-0.12). Overall performance was moderate (F1-score 0.63 ± 0.004), and decision curve analyses suggested higher mean net benefit at lower thresholds of treatment (up to 0.8). CONCLUSIONS This FRT prediction model can help inform shared decision making and identify the most relevant features in the emergency setting. Although it might be particularly useful in low resource healthcare settings, incorporation of further multifaceted variables is necessary to further increase the predictive performance.
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Affiliation(s)
- Thomas Raphael Meinel
- From the Department of Neurology (T.M., C.L., M.B., B.S., A.S., M.M., M.G., D.S., S.J., M.A.), University Hospital Bern, Inselspital, University of Bern; Department of Neurology and Stroke Center (U.F.), University Hospital Basel and University of Basel; University Institute of Diagnostic and Interventional Neuroradiology (A.M., C.K., N.F.B., T.D., J.G., R.W., R.M., J.K.), Support Center for Advanced Neuroimaging (R.W., R.M., J.K.), and Department of Diagnostic, Paediatric and Interventional Radiology (J.K.), University Hospital Bern, Inselspital, University of Bern, Switzerland.
| | - Christine Lerch
- From the Department of Neurology (T.M., C.L., M.B., B.S., A.S., M.M., M.G., D.S., S.J., M.A.), University Hospital Bern, Inselspital, University of Bern; Department of Neurology and Stroke Center (U.F.), University Hospital Basel and University of Basel; University Institute of Diagnostic and Interventional Neuroradiology (A.M., C.K., N.F.B., T.D., J.G., R.W., R.M., J.K.), Support Center for Advanced Neuroimaging (R.W., R.M., J.K.), and Department of Diagnostic, Paediatric and Interventional Radiology (J.K.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - Urs Fischer
- From the Department of Neurology (T.M., C.L., M.B., B.S., A.S., M.M., M.G., D.S., S.J., M.A.), University Hospital Bern, Inselspital, University of Bern; Department of Neurology and Stroke Center (U.F.), University Hospital Basel and University of Basel; University Institute of Diagnostic and Interventional Neuroradiology (A.M., C.K., N.F.B., T.D., J.G., R.W., R.M., J.K.), Support Center for Advanced Neuroimaging (R.W., R.M., J.K.), and Department of Diagnostic, Paediatric and Interventional Radiology (J.K.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - Morin Beyeler
- From the Department of Neurology (T.M., C.L., M.B., B.S., A.S., M.M., M.G., D.S., S.J., M.A.), University Hospital Bern, Inselspital, University of Bern; Department of Neurology and Stroke Center (U.F.), University Hospital Basel and University of Basel; University Institute of Diagnostic and Interventional Neuroradiology (A.M., C.K., N.F.B., T.D., J.G., R.W., R.M., J.K.), Support Center for Advanced Neuroimaging (R.W., R.M., J.K.), and Department of Diagnostic, Paediatric and Interventional Radiology (J.K.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - Adnan Mujanovic
- From the Department of Neurology (T.M., C.L., M.B., B.S., A.S., M.M., M.G., D.S., S.J., M.A.), University Hospital Bern, Inselspital, University of Bern; Department of Neurology and Stroke Center (U.F.), University Hospital Basel and University of Basel; University Institute of Diagnostic and Interventional Neuroradiology (A.M., C.K., N.F.B., T.D., J.G., R.W., R.M., J.K.), Support Center for Advanced Neuroimaging (R.W., R.M., J.K.), and Department of Diagnostic, Paediatric and Interventional Radiology (J.K.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - Christoph Kurmann
- From the Department of Neurology (T.M., C.L., M.B., B.S., A.S., M.M., M.G., D.S., S.J., M.A.), University Hospital Bern, Inselspital, University of Bern; Department of Neurology and Stroke Center (U.F.), University Hospital Basel and University of Basel; University Institute of Diagnostic and Interventional Neuroradiology (A.M., C.K., N.F.B., T.D., J.G., R.W., R.M., J.K.), Support Center for Advanced Neuroimaging (R.W., R.M., J.K.), and Department of Diagnostic, Paediatric and Interventional Radiology (J.K.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - Bernhard Siepen
- From the Department of Neurology (T.M., C.L., M.B., B.S., A.S., M.M., M.G., D.S., S.J., M.A.), University Hospital Bern, Inselspital, University of Bern; Department of Neurology and Stroke Center (U.F.), University Hospital Basel and University of Basel; University Institute of Diagnostic and Interventional Neuroradiology (A.M., C.K., N.F.B., T.D., J.G., R.W., R.M., J.K.), Support Center for Advanced Neuroimaging (R.W., R.M., J.K.), and Department of Diagnostic, Paediatric and Interventional Radiology (J.K.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - Adrian Scutelnic
- From the Department of Neurology (T.M., C.L., M.B., B.S., A.S., M.M., M.G., D.S., S.J., M.A.), University Hospital Bern, Inselspital, University of Bern; Department of Neurology and Stroke Center (U.F.), University Hospital Basel and University of Basel; University Institute of Diagnostic and Interventional Neuroradiology (A.M., C.K., N.F.B., T.D., J.G., R.W., R.M., J.K.), Support Center for Advanced Neuroimaging (R.W., R.M., J.K.), and Department of Diagnostic, Paediatric and Interventional Radiology (J.K.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - Madlaine Müller
- From the Department of Neurology (T.M., C.L., M.B., B.S., A.S., M.M., M.G., D.S., S.J., M.A.), University Hospital Bern, Inselspital, University of Bern; Department of Neurology and Stroke Center (U.F.), University Hospital Basel and University of Basel; University Institute of Diagnostic and Interventional Neuroradiology (A.M., C.K., N.F.B., T.D., J.G., R.W., R.M., J.K.), Support Center for Advanced Neuroimaging (R.W., R.M., J.K.), and Department of Diagnostic, Paediatric and Interventional Radiology (J.K.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - Martina Goeldlin
- From the Department of Neurology (T.M., C.L., M.B., B.S., A.S., M.M., M.G., D.S., S.J., M.A.), University Hospital Bern, Inselspital, University of Bern; Department of Neurology and Stroke Center (U.F.), University Hospital Basel and University of Basel; University Institute of Diagnostic and Interventional Neuroradiology (A.M., C.K., N.F.B., T.D., J.G., R.W., R.M., J.K.), Support Center for Advanced Neuroimaging (R.W., R.M., J.K.), and Department of Diagnostic, Paediatric and Interventional Radiology (J.K.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - Nebiyat Filate Belachew
- From the Department of Neurology (T.M., C.L., M.B., B.S., A.S., M.M., M.G., D.S., S.J., M.A.), University Hospital Bern, Inselspital, University of Bern; Department of Neurology and Stroke Center (U.F.), University Hospital Basel and University of Basel; University Institute of Diagnostic and Interventional Neuroradiology (A.M., C.K., N.F.B., T.D., J.G., R.W., R.M., J.K.), Support Center for Advanced Neuroimaging (R.W., R.M., J.K.), and Department of Diagnostic, Paediatric and Interventional Radiology (J.K.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - Tomas Dobrocky
- From the Department of Neurology (T.M., C.L., M.B., B.S., A.S., M.M., M.G., D.S., S.J., M.A.), University Hospital Bern, Inselspital, University of Bern; Department of Neurology and Stroke Center (U.F.), University Hospital Basel and University of Basel; University Institute of Diagnostic and Interventional Neuroradiology (A.M., C.K., N.F.B., T.D., J.G., R.W., R.M., J.K.), Support Center for Advanced Neuroimaging (R.W., R.M., J.K.), and Department of Diagnostic, Paediatric and Interventional Radiology (J.K.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - Jan Gralla
- From the Department of Neurology (T.M., C.L., M.B., B.S., A.S., M.M., M.G., D.S., S.J., M.A.), University Hospital Bern, Inselspital, University of Bern; Department of Neurology and Stroke Center (U.F.), University Hospital Basel and University of Basel; University Institute of Diagnostic and Interventional Neuroradiology (A.M., C.K., N.F.B., T.D., J.G., R.W., R.M., J.K.), Support Center for Advanced Neuroimaging (R.W., R.M., J.K.), and Department of Diagnostic, Paediatric and Interventional Radiology (J.K.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - David Seiffge
- From the Department of Neurology (T.M., C.L., M.B., B.S., A.S., M.M., M.G., D.S., S.J., M.A.), University Hospital Bern, Inselspital, University of Bern; Department of Neurology and Stroke Center (U.F.), University Hospital Basel and University of Basel; University Institute of Diagnostic and Interventional Neuroradiology (A.M., C.K., N.F.B., T.D., J.G., R.W., R.M., J.K.), Support Center for Advanced Neuroimaging (R.W., R.M., J.K.), and Department of Diagnostic, Paediatric and Interventional Radiology (J.K.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - Simon Jung
- From the Department of Neurology (T.M., C.L., M.B., B.S., A.S., M.M., M.G., D.S., S.J., M.A.), University Hospital Bern, Inselspital, University of Bern; Department of Neurology and Stroke Center (U.F.), University Hospital Basel and University of Basel; University Institute of Diagnostic and Interventional Neuroradiology (A.M., C.K., N.F.B., T.D., J.G., R.W., R.M., J.K.), Support Center for Advanced Neuroimaging (R.W., R.M., J.K.), and Department of Diagnostic, Paediatric and Interventional Radiology (J.K.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - Marcel Arnold
- From the Department of Neurology (T.M., C.L., M.B., B.S., A.S., M.M., M.G., D.S., S.J., M.A.), University Hospital Bern, Inselspital, University of Bern; Department of Neurology and Stroke Center (U.F.), University Hospital Basel and University of Basel; University Institute of Diagnostic and Interventional Neuroradiology (A.M., C.K., N.F.B., T.D., J.G., R.W., R.M., J.K.), Support Center for Advanced Neuroimaging (R.W., R.M., J.K.), and Department of Diagnostic, Paediatric and Interventional Radiology (J.K.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - Roland Wiest
- From the Department of Neurology (T.M., C.L., M.B., B.S., A.S., M.M., M.G., D.S., S.J., M.A.), University Hospital Bern, Inselspital, University of Bern; Department of Neurology and Stroke Center (U.F.), University Hospital Basel and University of Basel; University Institute of Diagnostic and Interventional Neuroradiology (A.M., C.K., N.F.B., T.D., J.G., R.W., R.M., J.K.), Support Center for Advanced Neuroimaging (R.W., R.M., J.K.), and Department of Diagnostic, Paediatric and Interventional Radiology (J.K.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - Raphael Meier
- From the Department of Neurology (T.M., C.L., M.B., B.S., A.S., M.M., M.G., D.S., S.J., M.A.), University Hospital Bern, Inselspital, University of Bern; Department of Neurology and Stroke Center (U.F.), University Hospital Basel and University of Basel; University Institute of Diagnostic and Interventional Neuroradiology (A.M., C.K., N.F.B., T.D., J.G., R.W., R.M., J.K.), Support Center for Advanced Neuroimaging (R.W., R.M., J.K.), and Department of Diagnostic, Paediatric and Interventional Radiology (J.K.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - Johannes Kaesmacher
- From the Department of Neurology (T.M., C.L., M.B., B.S., A.S., M.M., M.G., D.S., S.J., M.A.), University Hospital Bern, Inselspital, University of Bern; Department of Neurology and Stroke Center (U.F.), University Hospital Basel and University of Basel; University Institute of Diagnostic and Interventional Neuroradiology (A.M., C.K., N.F.B., T.D., J.G., R.W., R.M., J.K.), Support Center for Advanced Neuroimaging (R.W., R.M., J.K.), and Department of Diagnostic, Paediatric and Interventional Radiology (J.K.), University Hospital Bern, Inselspital, University of Bern, Switzerland
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Bae HJ. David G. Sherman Lecture Award: 15-Year Experience of the Nationwide Multicenter Stroke Registry in Korea. Stroke 2022; 53:2976-2987. [PMID: 35899613 DOI: 10.1161/strokeaha.122.039212] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The expected growth of stroke burden in Korea in early 2000s led to the initiation of a government-funded clinical research project with the goal of development and implementation of national stroke guidelines. The CRCS-K (Clinical Research Collaboration for Stroke in Korea) began as a part of this project. For stroke epidemiology and quality of care research, the CRCS-K developed a multicenter, prospective, stroke registry and began collection of data in 2008. Now, about 100 000 cases have been registered at 17 university hospitals or regional stroke centers and about 200 articles have been published based on the registry experience. The analysis of the 10-year secular trends showed overall improvement of stroke care and outcomes and areas for improvement. This large-scale, high-quality dataset provides opportunities to explore and compare treatment disparities using the comparative effectiveness research methods, design and conduct a registry-based randomized clinical trial, connect the registry data with other data sources including the national claims data and neuroimaging or genetic data, and collaborate with other international researchers. An international stroke registry consortium may be a viable future direction.
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Affiliation(s)
- Hee-Joon Bae
- Department of Neurology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Korea
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Meta-Analysis of Predictive Role of Early Neurological Deterioration after Intravenous Thrombolysis. Emerg Med Int 2022; 2022:2894426. [PMID: 35912390 PMCID: PMC9337960 DOI: 10.1155/2022/2894426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 05/25/2022] [Accepted: 06/02/2022] [Indexed: 11/17/2022] Open
Abstract
With the popularization of intravenous thrombolysis, more and more people use intravenous thrombolysis to treat related diseases, but problems also arise. There are still a considerable number of patients with early disease after thrombolytic therapy not only not significantly improving, but also progressing, that is, early neurological deterioration (END). In view of this problem, the prediction of END after intravenous thrombolysis becomes very important. With the development of medical technology, research on the prediction of END after intravenous thrombolysis has gradually been carried out. Effective prediction is of great significance for the prevention and treatment of END after intravenous thrombolysis. This article aimed to carry out a meta-analysis of the predictive role of END after intravenous thrombolysis. Through an informed analysis of all studies of this type in this field, this article determines a method for predicting END after intravenous thrombolysis. The actual effect of its role is revealed in this paper, and its purpose is to promote the development of this field. This article addresses the same type of study on the predictive role of neurological deterioration after intravenous thrombolysis. The article performs test and meta-analysis of its role by conditionally searching for literature studies. It is explained using the relevant theoretical formulas. The analysis results show that the prediction of END after intravenous thrombolysis in this paper can effectively help make a preliminary judgment on the possible later neurological deterioration. Although there is an error between the predicted curve and the actual curve, the difference between the two is between 1% and 5%. It can basically effectively predict the occurrence of END. Therefore, the prediction of END after intravenous thrombolysis has a very large preventive effect on the END after intravenous thrombolysis.
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Ren B, Tan L, Song Y, Li D, Xue B, Lai X, Gao Y. Cerebral Small Vessel Disease: Neuroimaging Features, Biochemical Markers, Influencing Factors, Pathological Mechanism and Treatment. Front Neurol 2022; 13:843953. [PMID: 35775047 PMCID: PMC9237477 DOI: 10.3389/fneur.2022.843953] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 05/12/2022] [Indexed: 01/15/2023] Open
Abstract
Cerebral small vessel disease (CSVD) is the most common chronic vascular disease involving the whole brain. Great progress has been made in clinical imaging, pathological mechanism, and treatment of CSVD, but many problems remain. Clarifying the current research dilemmas and future development direction of CSVD can provide new ideas for both basic and clinical research. In this review, the risk factors, biological markers, pathological mechanisms, and the treatment of CSVD will be systematically illustrated to provide the current research status of CSVD. The future development direction of CSVD will be elucidated by summarizing the research difficulties.
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Affiliation(s)
- Beida Ren
- Department of Neurology, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China
- Institute for Brain Disorders, Beijing University of Chinese Medicine, Beijing, China
- Chinese Medicine Key Research Room of Brain Disorders Syndrome and Treatment of the National Administration of Traditonal Chinese Medicine, Beijing, China
| | - Ling Tan
- Department of Cardiology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Yuebo Song
- Department of Neurology, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Danxi Li
- Institute for Brain Disorders, Beijing University of Chinese Medicine, Beijing, China
- Chinese Medicine Key Research Room of Brain Disorders Syndrome and Treatment of the National Administration of Traditonal Chinese Medicine, Beijing, China
| | - Bingjie Xue
- Institute for Brain Disorders, Beijing University of Chinese Medicine, Beijing, China
- Chinese Medicine Key Research Room of Brain Disorders Syndrome and Treatment of the National Administration of Traditonal Chinese Medicine, Beijing, China
| | - Xinxing Lai
- Institute for Brain Disorders, Beijing University of Chinese Medicine, Beijing, China
| | - Ying Gao
- Department of Neurology, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China
- Institute for Brain Disorders, Beijing University of Chinese Medicine, Beijing, China
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40
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Guettard YO, Gros A, Fukutomi H, Pillois X, Préau S, Lavie-Badie Y, Marest D, Martins RP, Coupez E, Coudroy R, Seguy B, Boyer A, Tourdias T, Gruson D, Coste P, Souweine B, Nseir S, Toussaint A, Outteryck O, Reignier J, Robert R, Urien JM, Porte L, Robin G, Charbonnier G, Sarton B, Silva S, on behalf of the ICE-COCA investigators. Brain imaging determinants of functional prognosis after severe endocarditis: a multicenter observational study. Neurol Sci 2022; 43:3759-3768. [DOI: 10.1007/s10072-021-05789-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 11/26/2021] [Indexed: 10/19/2022]
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Sun R, Wong WW, Wang J, Wang X, Tong RKY. Functional brain networks assessed with surface electroencephalography for predicting motor recovery in a neural guided intervention for chronic stroke. Brain Commun 2022; 3:fcab214. [PMID: 35350709 PMCID: PMC8936428 DOI: 10.1093/braincomms/fcab214] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 06/04/2021] [Accepted: 07/28/2021] [Indexed: 12/12/2022] Open
Abstract
Predicting whether a chronic stroke patient is likely to benefit from a specific intervention can help patients establish reasonable expectations. It also provides the basis for candidates selecting for the intervention. Recent convergent evidence supports the value of network-based approach for understanding the relationship between dysfunctional neural activity and motor deficits after stroke. In this study, we applied resting-state brain connectivity networks to investigate intervention-specific predictive biomarkers of motor improvement in 22 chronic stroke participants who received either combined action observation with EEG-guided robot-hand training (Neural Guided-Action Observation Group, n = 12, age: 34–68 years) or robot-hand training without action observation and EEG guidance (non-Neural Guided-text group, n = 10, age: 42–57 years). The robot hand in Neural Guided-Action Observation training was activated only when significant mu suppression (8–12 Hz) was detected from participant’s EEG signals in ipsilesional hemisphere while it was randomly activated in non-Neural Guided-text training. Only the Neural Guided-Action Observation group showed a significant long-term improvement in their upper-limb motor functions (P < 0.5). In contrast, no significant training effect on the paretic motor functions was found in the non-Neural Guided-text group (P > 0.5). The results of brain connectivity estimated via EEG coherence showed that the pre-training interhemispheric connectivity of delta, theta, alpha and contralesional connectivity of beta were motor improvement related in the Neural Guided-Action Observation group. They can not only differentiate participants with good and poor recovery (interhemispheric delta: P = 0.047, Hedges’ g = 1.409; interhemispheric theta: P = 0.046, Hedges’ g = 1.333; interhemispheric alpha: P = 0.038, Hedges’ g = 1.536; contralesional beta: P = 0.027, Hedges’ g = 1.613) but also significantly correlated with post-training intervention gains (interhemispheric delta: r = −0.901, P < 0.05; interhemispheric theta: r = −0.702, P < 0.05; interhemispheric alpha: r = −0.641, P < 0.05; contralesional beta: r = −0.729, P < 0.05). In contrast, no EEG coherence was significantly correlated with intervention gains in the non-Neural Guided-text group (all Ps>0.05). Partial least square regression showed that the combination of pre-training interhemispheric and contralesional local connectivity could precisely predict intervention gains in the Neural Guided-Action Observation group with a strong correlation between predicted and observed intervention gains (r = 0.82r=0.82) and between predicted and observed intervention outcomes (r = 0.90r=0.90). In summary, EEG-based resting-state brain connectivity networks may serve clinical decision-making by offering an approach to predicting Neural Guided-Action Observation training-induced motor improvement.
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Affiliation(s)
- Rui Sun
- The Laboratory of Neuroscience for Education, Faculty of Education, the University of Hong Kong, Pokfulam, Hong Kong, China
| | - Wan-Wa Wong
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Jing Wang
- School of Mechanical Engineering, Xi'an Jiaotong University, Shaanxi, China
| | - Xin Wang
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong, China
| | - Raymond K Y Tong
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong, China
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Derraz I, Abdelrady M, Ahmed R, Gaillard N, Morganti R, Cagnazzo F, Dargazanli C, Lefevre PH, Riquelme C, Corti L, Gascou G, Mourand I, Arquizan C, Costalat V. Impact of White Matter Hyperintensity Burden on Outcome in Large-Vessel Occlusion Stroke. Radiology 2022; 304:145-152. [PMID: 35348382 DOI: 10.1148/radiol.210419] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background White matter hyperintensity (WMH) has been linked to poor clinical outcomes after acute ischemic stroke. Purpose To assess whether the WMH burden on pretreatment MRI scans is associated with an increased risk for symptomatic intracranial hemorrhage (sICH) or poor functional outcome in patients with acute ischemic stroke treated with endovascular thrombectomy (EVT). Materials and Methods In this retrospective study, consecutive patients treated with EVT for anterior circulation acute ischemic stroke at a comprehensive stroke center (where MRI was the first-line pretreatment imaging strategy; January 2015 to December 2017) were included and analyzed. WMH volumes were assessed with semiautomated volumetric analysis at fluid-attenuated inversion recovery MRI by readers who were blinded to clinical data. The associations of WMH burden with sICH and 3-month functional outcome (modified Rankin Scale [mRS] score) were assessed. Results A total of 366 patients were included (mean age, 69 years ± 19 [SD]; 188 women [51%]). Median total WMH volume was 3.61 cm3 (IQR, 1.10-10.83 cm3). Patients demonstrated higher mRS scores with increasing WMH volumes (odds ratio [OR], 1.020 [95% CI: 1.003, 1.037] per 1.0-cm3 increase for each mRS point increase; P = .018) after adjustment for patient and clinical variables. There were no significant associations between WMH severity and 90-day mortality (OR, 1.007 [95% CI: 0.990, 1.024]; P = .40) or the occurrence of sICH (OR, 1.001 [95% CI: 0.978, 1.024]; P = .94). Conclusion Higher white matter hyperintensity burden was associated with increased risk for poor 3-month functional outcome after endovascular thrombectomy for large-vessel occlusive stroke. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Mossa-Basha and Zhu in this issue.
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Affiliation(s)
- Imad Derraz
- From the Departments of Neuroradiology (I.D., M.A., R.A., F.C., C.D., P.H.L., C.R., G.G., V.C.) and Neurology (N.G., L.C., I.M., C.A.), Hôpital Gui de Chauliac, Montpellier University Medical Center, 80 Avenue Augustin Fliche, Montpellier 34295, France; and Department of Clinical and Experimental Medicine, Section of Statistics, University of Pisa, Pisa, Italy (R.M.)
| | - Mohamed Abdelrady
- From the Departments of Neuroradiology (I.D., M.A., R.A., F.C., C.D., P.H.L., C.R., G.G., V.C.) and Neurology (N.G., L.C., I.M., C.A.), Hôpital Gui de Chauliac, Montpellier University Medical Center, 80 Avenue Augustin Fliche, Montpellier 34295, France; and Department of Clinical and Experimental Medicine, Section of Statistics, University of Pisa, Pisa, Italy (R.M.)
| | - Raed Ahmed
- From the Departments of Neuroradiology (I.D., M.A., R.A., F.C., C.D., P.H.L., C.R., G.G., V.C.) and Neurology (N.G., L.C., I.M., C.A.), Hôpital Gui de Chauliac, Montpellier University Medical Center, 80 Avenue Augustin Fliche, Montpellier 34295, France; and Department of Clinical and Experimental Medicine, Section of Statistics, University of Pisa, Pisa, Italy (R.M.)
| | - Nicolas Gaillard
- From the Departments of Neuroradiology (I.D., M.A., R.A., F.C., C.D., P.H.L., C.R., G.G., V.C.) and Neurology (N.G., L.C., I.M., C.A.), Hôpital Gui de Chauliac, Montpellier University Medical Center, 80 Avenue Augustin Fliche, Montpellier 34295, France; and Department of Clinical and Experimental Medicine, Section of Statistics, University of Pisa, Pisa, Italy (R.M.)
| | - Riccardo Morganti
- From the Departments of Neuroradiology (I.D., M.A., R.A., F.C., C.D., P.H.L., C.R., G.G., V.C.) and Neurology (N.G., L.C., I.M., C.A.), Hôpital Gui de Chauliac, Montpellier University Medical Center, 80 Avenue Augustin Fliche, Montpellier 34295, France; and Department of Clinical and Experimental Medicine, Section of Statistics, University of Pisa, Pisa, Italy (R.M.)
| | - Federico Cagnazzo
- From the Departments of Neuroradiology (I.D., M.A., R.A., F.C., C.D., P.H.L., C.R., G.G., V.C.) and Neurology (N.G., L.C., I.M., C.A.), Hôpital Gui de Chauliac, Montpellier University Medical Center, 80 Avenue Augustin Fliche, Montpellier 34295, France; and Department of Clinical and Experimental Medicine, Section of Statistics, University of Pisa, Pisa, Italy (R.M.)
| | - Cyril Dargazanli
- From the Departments of Neuroradiology (I.D., M.A., R.A., F.C., C.D., P.H.L., C.R., G.G., V.C.) and Neurology (N.G., L.C., I.M., C.A.), Hôpital Gui de Chauliac, Montpellier University Medical Center, 80 Avenue Augustin Fliche, Montpellier 34295, France; and Department of Clinical and Experimental Medicine, Section of Statistics, University of Pisa, Pisa, Italy (R.M.)
| | - Pierre-Henri Lefevre
- From the Departments of Neuroradiology (I.D., M.A., R.A., F.C., C.D., P.H.L., C.R., G.G., V.C.) and Neurology (N.G., L.C., I.M., C.A.), Hôpital Gui de Chauliac, Montpellier University Medical Center, 80 Avenue Augustin Fliche, Montpellier 34295, France; and Department of Clinical and Experimental Medicine, Section of Statistics, University of Pisa, Pisa, Italy (R.M.)
| | - Carlos Riquelme
- From the Departments of Neuroradiology (I.D., M.A., R.A., F.C., C.D., P.H.L., C.R., G.G., V.C.) and Neurology (N.G., L.C., I.M., C.A.), Hôpital Gui de Chauliac, Montpellier University Medical Center, 80 Avenue Augustin Fliche, Montpellier 34295, France; and Department of Clinical and Experimental Medicine, Section of Statistics, University of Pisa, Pisa, Italy (R.M.)
| | - Lucas Corti
- From the Departments of Neuroradiology (I.D., M.A., R.A., F.C., C.D., P.H.L., C.R., G.G., V.C.) and Neurology (N.G., L.C., I.M., C.A.), Hôpital Gui de Chauliac, Montpellier University Medical Center, 80 Avenue Augustin Fliche, Montpellier 34295, France; and Department of Clinical and Experimental Medicine, Section of Statistics, University of Pisa, Pisa, Italy (R.M.)
| | - Grégory Gascou
- From the Departments of Neuroradiology (I.D., M.A., R.A., F.C., C.D., P.H.L., C.R., G.G., V.C.) and Neurology (N.G., L.C., I.M., C.A.), Hôpital Gui de Chauliac, Montpellier University Medical Center, 80 Avenue Augustin Fliche, Montpellier 34295, France; and Department of Clinical and Experimental Medicine, Section of Statistics, University of Pisa, Pisa, Italy (R.M.)
| | - Isabelle Mourand
- From the Departments of Neuroradiology (I.D., M.A., R.A., F.C., C.D., P.H.L., C.R., G.G., V.C.) and Neurology (N.G., L.C., I.M., C.A.), Hôpital Gui de Chauliac, Montpellier University Medical Center, 80 Avenue Augustin Fliche, Montpellier 34295, France; and Department of Clinical and Experimental Medicine, Section of Statistics, University of Pisa, Pisa, Italy (R.M.)
| | - Caroline Arquizan
- From the Departments of Neuroradiology (I.D., M.A., R.A., F.C., C.D., P.H.L., C.R., G.G., V.C.) and Neurology (N.G., L.C., I.M., C.A.), Hôpital Gui de Chauliac, Montpellier University Medical Center, 80 Avenue Augustin Fliche, Montpellier 34295, France; and Department of Clinical and Experimental Medicine, Section of Statistics, University of Pisa, Pisa, Italy (R.M.)
| | - Vincent Costalat
- From the Departments of Neuroradiology (I.D., M.A., R.A., F.C., C.D., P.H.L., C.R., G.G., V.C.) and Neurology (N.G., L.C., I.M., C.A.), Hôpital Gui de Chauliac, Montpellier University Medical Center, 80 Avenue Augustin Fliche, Montpellier 34295, France; and Department of Clinical and Experimental Medicine, Section of Statistics, University of Pisa, Pisa, Italy (R.M.)
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Cai Y, Chen B, Zeng X, Xie M, Wei X, Cai J. The Triglyceride Glucose Index Is a Risk Factor for Enlarged Perivascular Space. Front Neurol 2022; 13:782286. [PMID: 35185759 PMCID: PMC8854364 DOI: 10.3389/fneur.2022.782286] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 01/03/2022] [Indexed: 01/01/2023] Open
Abstract
The triglyceride glucose (TyG) index is considered a simple surrogate marker for insulin resistance and has been associated with cerebrovascular diseases. However, limited information is available regarding its association with the subclinical cerebral small vessel disease (CSVD). Here, we investigated the association of TyG index with the burden and distribution of enlarged perivascular space (EPVS) in the non-diabetic population. The data of 531 non-diabetic patients from 2017 to 2020 were assessed. Participants were grouped according to the burden of EPVS. TyG index was calculated using the log scale of fasting triglycerides (mg/dl) × fasting glucose (mg/dl)/2. The association of TyG index with EPVS burden and distribution was evaluated. In the multivariable logistic regression analysis, the TyG index was associated with moderate to severe EPVS [odds ratio (OR): 2.077; 95% CI = 1.268–3.403]. The TyG index was significantly associated with an increased risk of moderate to severe EPVS in subgroups of age <65 years, male, diastolic blood pressure (DBP) <90 mmHg, low-density lipoprotein cholesterol (LDL-C) ≥2.85 mmol/L, serum homocysteine <10 μmol/L, and estimated glomerular filtration rate (eGFR) <90 ml/min/1.73 m2, as well as those without smoking. Further analysis of EPVS distribution, the TyG index was found to be associated with moderate to severe EPVS in the centrum semiovale (CSO), not in the basal ganglia (BG). Conclusively, the TyG index was independently and positively associated with moderate to severe CSO EPVS. TyG index may serve as an independent risk factor for CSVD in clinical practice.
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Ryu WS, Hong KS, Jeong SW, Park JE, Kim BJ, Kim JT, Lee KB, Park TH, Park SS, Park JM, Kang K, Cho YJ, Park HK, Lee BC, Yu KH, Oh MS, Lee SJ, Kim JG, Cha JK, Kim DH, Lee J, Han MK, Park MS, Choi KH, Lee J, Saver JL, Lo EH, Bae HJ, Kim DE. Association of ischemic stroke onset time with presenting severity, acute progression, and long-term outcome: A cohort study. PLoS Med 2022; 19:e1003910. [PMID: 35120123 PMCID: PMC8815976 DOI: 10.1371/journal.pmed.1003910] [Citation(s) in RCA: 53] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 01/11/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Preclinical data suggest circadian variation in ischemic stroke progression, with more active cell death and infarct growth in rodent models with inactive phase (daytime) than active phase (nighttime) stroke onset. We aimed to examine the association of stroke onset time with presenting severity, early neurological deterioration (END), and long-term functional outcome in human ischemic stroke. METHODS AND FINDINGS In a Korean nationwide multicenter observational cohort study from May 2011 to July 2020, we assessed circadian effects on initial stroke severity (National Institutes of Health Stroke Scale [NIHSS] score at admission), END, and favorable functional outcome (3-month modified Rankin Scale [mRS] score 0 to 2 versus 3 to 6). We included 17,461 consecutive patients with witnessed ischemic stroke within 6 hours of onset. Stroke onset time was divided into 2 groups (day-onset [06:00 to 18:00] versus night-onset [18:00 to 06:00]) and into 6 groups by 4-hour intervals. We used mixed-effects ordered or logistic regression models while accounting for clustering by hospitals. Mean age was 66.9 (SD 13.4) years, and 6,900 (39.5%) were women. END occurred in 2,219 (12.7%) patients. After adjusting for covariates including age, sex, previous stroke, prestroke mRS score, admission NIHSS score, hypertension, diabetes, hyperlipidemia, smoking, atrial fibrillation, prestroke antiplatelet use, prestroke statin use, revascularization, season of stroke onset, and time from onset to hospital arrival, night-onset stroke was more prone to END (adjusted incidence 14.4% versus 12.8%, p = 0.006) and had a lower likelihood of favorable outcome (adjusted odds ratio, 0.88 [95% CI, 0.79 to 0.98]; p = 0.03) compared with day-onset stroke. When stroke onset times were grouped by 4-hour intervals, a monotonic gradient in presenting NIHSS score was noted, rising from a nadir in 06:00 to 10:00 to a peak in 02:00 to 06:00. The 18:00 to 22:00 and 22:00 to 02:00 onset stroke patients were more likely to experience END than the 06:00 to 10:00 onset stroke patients. At 3 months, there was a monotonic gradient in the rate of favorable functional outcome, falling from a peak at 06:00 to 10:00 to a nadir at 22:00 to 02:00. Study limitations include the lack of information on sleep disorders and patient work/activity schedules. CONCLUSIONS Night-onset strokes, compared with day-onset strokes, are associated with higher presenting neurologic severity, more frequent END, and worse 3-month functional outcome. These findings suggest that circadian time of onset is an important additional variable for inclusion in epidemiologic natural history studies and in treatment trials of neuroprotective and reperfusion agents for acute ischemic stroke.
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Affiliation(s)
- Wi-Sun Ryu
- Department of Neurology, Dongguk University Ilsan Hospital, Goyang, Korea
- National Priority Research Center for Stroke, Goyang, Korea
| | - Keun-Sik Hong
- Department of Neurology, Inje University Ilsan Paik Hospital, Goyang, Korea
| | - Sang-Wuk Jeong
- Department of Neurology, Dongguk University Ilsan Hospital, Goyang, Korea
| | - Jung E. Park
- Department of Neurology, Dongguk University Ilsan Hospital, Goyang, Korea
| | - Beom Joon Kim
- Department of Neurology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Joon-Tae Kim
- Department of Neurology, Chonnam National University Hospital, Gwangju, Korea
| | - Kyung Bok Lee
- Department of Neurology, Soonchunhyang University Hospital, Seoul, Korea
| | - Tai Hwan Park
- Department of Neurology, Seoul Medical Center, Seoul, Korea
| | - Sang-Soon Park
- Department of Neurology, Seoul Medical Center, Seoul, Korea
| | - Jong-Moo Park
- Department of Neurology, Uijeongbu Eulji Medical Center, Uijeongbu, Korea
| | - Kyusik Kang
- Department of Neurology, Nowon Eulji Medical Center, Eulji University School of Medicine, Seoul, Korea
| | - Yong-Jin Cho
- Department of Neurology, Inje University Ilsan Paik Hospital, Goyang, Korea
| | - Hong-Kyun Park
- Department of Neurology, Inje University Ilsan Paik Hospital, Goyang, Korea
| | - Byung-Chul Lee
- Department of Neurology, Hallym University Sacred Heart Hospital, Anyang, Korea
| | - Kyung-Ho Yu
- Department of Neurology, Hallym University Sacred Heart Hospital, Anyang, Korea
| | - Mi Sun Oh
- Department of Neurology, Hallym University Sacred Heart Hospital, Anyang, Korea
| | - Soo Joo Lee
- Department of Neurology, Eulji University Hospital, Daejeon, Korea
| | - Jae Guk Kim
- Department of Neurology, Eulji University Hospital, Daejeon, Korea
| | - Jae-Kwan Cha
- Department of Neurology, Dong-A University Hospital, Busan, Korea
| | - Dae-Hyun Kim
- Department of Neurology, Dong-A University Hospital, Busan, Korea
| | - Jun Lee
- Department of Neurology, Yeungnam University Hospital, Daegu, Korea
| | - Moon-Ku Han
- Department of Neurology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Man Seok Park
- Department of Neurology, Chonnam National University Hospital, Gwangju, Korea
| | - Kang-Ho Choi
- Department of Neurology, Chonnam National University Hospital, Gwangju, Korea
| | - Juneyoung Lee
- Department of Biostatistics, Korea University, Seoul, Korea
| | - Jeffrey L. Saver
- Comprehensive Stroke Center, Department of Neurology, University of California, Los Angeles, California, United States of America
- Consortium International pour la Recherche Circadienne sur l’AVC (CIRCA)
| | - Eng H. Lo
- Consortium International pour la Recherche Circadienne sur l’AVC (CIRCA)
- Neuroprotection Research Laboratory, Departments of Radiology and Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Hee-Joon Bae
- Department of Neurology, Seoul National University Bundang Hospital, Seongnam, Korea
- Consortium International pour la Recherche Circadienne sur l’AVC (CIRCA)
- * E-mail: (H-JB); (D-EK)
| | - Dong-Eog Kim
- Department of Neurology, Dongguk University Ilsan Hospital, Goyang, Korea
- National Priority Research Center for Stroke, Goyang, Korea
- Consortium International pour la Recherche Circadienne sur l’AVC (CIRCA)
- * E-mail: (H-JB); (D-EK)
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Năstase MG, Vlaicu I, Trifu SC, Trifu SC, Department of Psychiatry, Hospital for Psychiatry, Săpunari, Călăraşi County, Romania, Department of Neurosciences, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania. Genetic polymorphism and neuroanatomical changes in schizophrenia. ROMANIAN JOURNAL OF MORPHOLOGY AND EMBRYOLOGY = REVUE ROUMAINE DE MORPHOLOGIE ET EMBRYOLOGIE 2022; 63:307-322. [PMID: 36374137 PMCID: PMC9801677 DOI: 10.47162/rjme.63.2.03] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The article is a review of the latest meta-analyses regarding the genetic spectrum in schizophrenia, discussing the risks given by the disrupted-in-schizophrenia 1 (DISC1), catechol-O-methyltransferase (COMT), monoamine oxidases-A∕B (MAO-A∕B), glutamic acid decarboxylase 67 (GAD67) and neuregulin 1 (NRG1) genes, and dysbindin-1 protein. The DISC1 polymorphism significantly increases the risk of schizophrenia, as well injuries from the prefrontal cortex that affect connectivity. NRG1 is one of the most important proteins involved. Its polymorphism is associated with the reduction of areas in the corpus callosum, right uncinate, inferior lateral fronto-occipital fascicle, right external capsule, fornix, right optic tract, gyrus. NRG1 and the ErbB4 receptor (tyrosine kinase receptor) are closely related to the N-methyl-D-aspartate receptor (NMDAR) (glutamate receptor). COMT is located on chromosome 22 and together with interleukin-10 (IL-10) have an anti-inflammatory and immunosuppressive function that influences the dopaminergic system. MAO gene methylation has been associated with mental disorders. MAO-A is a risk gene in the onset of schizophrenia, more precisely a certain type of single-nucleotide polymorphism (SNP), at the gene level, is associated with schizophrenia. In schizophrenia, we find deficits of the γ-aminobutyric acid (GABA)ergic neurotransmitter, the dysfunctions being found predominantly at the level of the substantia nigra. In schizophrenia, missing an allele at GAD67, caused by a SNP, has been correlated with decreases in parvalbumin (PV), somatostatin receptor (SSR), and GAD ribonucleic acid (RNA). Resulting in the inability to mature PV and SSR neurons, which has been associated with hyperactivity.
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Affiliation(s)
- Mihai Gabriel Năstase
- Department of Neurosciences, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania;
| | - Ilinca Vlaicu
- Department of Psychiatry, Hospital for Psychiatry, Săpunari, Călăraşi County, Romania
| | - Simona Corina Trifu
- Department of Neurosciences, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
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Impact of Encephalomalacia and White Matter Hyperintensities on ASPECTS in Patients With Acute Ischemic Stroke: Comparison of Automated- and Radiologist-Derived Scores. AJR Am J Roentgenol 2021; 218:878-887. [PMID: 34910537 DOI: 10.2214/ajr.21.26819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Background: Automated software-based Alberta Stroke Program Early CT Score (ASPECTS) on unenhanced CT is associated with clinical outcomes after acute stroke. However, encephalomalacia or white matter hyperintensities (WMHs) may result in a falsely low automated ASPECTS if such findings are interpreted as early ischemia. Objective: To assess the impact of encephalomalacia and WMH on automated ASPECTS in patients with acute stroke, in comparison with radiologist-derived ASPECTS and clinical outcomes. Methods: This retrospective three-center study included 459 patients (322 men, 137 women; median age, 65 years) with acute ischemic stroke treated by IV thrombolysis who underwent baseline unenhanced CT within 6 hours after symptom onset and MRI within 24 hours after treatment. ASPECTS was determined by automated software and by three radiologists in consensus. Presence of encephalomalacia and extent of WMHs [categorized using the modified Scheltens scale (mSS)] were also determined using MRI. Kappa coefficients were used to compare ASPECTS between automated and radiologist-consensus methods. Multivariable logistic regression analyses and ROC analyses were performed to explore the predictive utility of baseline ASPECTS for unfavorable clinical outcome (90-day modified Rankin Scale score of 3-6) after thrombolysis. Results: Median automated ASPECTS was 9, and median radiologist-consensus ASPECTS was 10. Agreement between automated and radiologist-consensus ASPECTS, expressed as kappa, was 0.68, though was 0.76 in patients without encephalomalacia and 0.08 in patients with encephalomalacia. In patients without encephalomalacia, agreement decreased as the mSS score increased (e.g., 0.78 in subgroup with mSS score <10 vs 0.19 in subgroup with mSS >20). By anatomic region, agreement was highest for M5 (κ=0.52) and lowest for internal capsule (κ=0.18). In multivariable analyses, both automated (odds ratio=0.69) and radiologist-consensus (odds ratio=0.57) ASPECTS independently predicted unfavorable clinical outcome. For unfavorable outcome, automated ASPECTS had AUC of 0.70, sensitivity of 60.4%, and specificity of 71.0%, while radiologist-consensus ASPECTS had AUC of 0.72, sensitivity of 60.4%, and specificity of 80.5%. Conclusion: Presence of encephalomalacia or extensive WMH results in lower automated ASPECTS than radiologist-consensus ASPECTS, which may impact predictive utility of automated ASPECTS. Clinical Impact: When using automated ASPECTS, radiologists should manually confirm the score in patients with encephalomalacia or extensive leukoencephalopathy.
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Sue K, Usuda D, Moriizumi S, Momose K. Preexisting brain lesions in patients with post stroke pusher behavior and their association with the recovery period: A one year retrospective cohort study in a rehabilitation setting. Neurosci Lett 2021; 769:136323. [PMID: 34742861 DOI: 10.1016/j.neulet.2021.136323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 10/12/2021] [Accepted: 10/28/2021] [Indexed: 11/16/2022]
Abstract
The presence of preexisting brain lesions due to previous stroke and cerebral small vessel disease has been reported to influence stroke related disability or rehabilitation outcomes. However, there is no data about the impact of such lesions on the recovery period after pusher behavior (PB). This retrospective cohort study aimed to determine the influence of preexisting brain lesions on PB recovery time. Nineteen patients who were suffering from PB were included in the study. The presence of preexisting brain lesions, including previous stroke, silent brain infarcts, microbleed, white matter hyperintensity, and enlarged perivascular spaces were assessed using medical history reports, radiological reports, and magnetic resonance imaging data. The lesion score, ranging from 0 to 6, was calculated based on each preexisting brain lesion. The time to recovery from PB was assessed using the Scale for Contraversive Pushing. Based on the median value of the lesion score, we divided patients into those with a lesion score <2 and those with a lesion score ≥2. A Kaplan Meier survival analysis was performed between these two groups. A multivariable Cox proportional hazards analysis was also performed using the side with hemiparesis and the score of preexisting brain lesions as covariates to determine the hazard ratio. The results showed that the group with a lesion score ≥2 had significantly delayed recovery from PB and the hazard ratio of preexisting brain lesions score was 0.458 (95 % confidence interval: 0.221, 0.949), while the side of hemiparesis was not identified a significant covariate. Our results indicated that patients with PB having higher score of preexisting brain abnormalities might require a longer time to recover, and this might be useful in planning inpatient rehabilitation and treatment goals for patients with PB.
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Affiliation(s)
- Keita Sue
- Department of Rehabilitation, Kakeyu-Misayama Rehabilitation Center, Kakeyu Hospital, 1308, Kakeyuonsen, Ueda, Nagano, 386-1701, Japan; Department of Health Sciences, Graduate School of Medicine, Science and Technology, Shinshu University, 3-1-1, Asahi, Matsumoto, Nagano, 390-8621, Japan
| | - Daiki Usuda
- Department of Rehabilitation, Kakeyu-Misayama Rehabilitation Center, Kakeyu Hospital, 1308, Kakeyuonsen, Ueda, Nagano, 386-1701, Japan
| | - Shutaro Moriizumi
- Department of Rehabilitation, Kakeyu-Misayama Rehabilitation Center, Kakeyu Hospital, 1308, Kakeyuonsen, Ueda, Nagano, 386-1701, Japan
| | - Kimito Momose
- Department of Physical Therapy, School of Health Science, Shinshu University, 3-1-1, Asahi, Matsumoto, Nagano, 390-8621, Japan.
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Huo L, Chen P, Wang Z, Li X, Zhou J, Wang C, Xing D, Wang S. Impact of leukoaraiosis severity on the association of outcomes of mechanical thrombectomy for acute ischemic stroke: a systematic review and a meta-analysis. J Neurol 2021; 268:4108-4116. [PMID: 32860084 PMCID: PMC8505273 DOI: 10.1007/s00415-020-10167-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 08/12/2020] [Accepted: 08/12/2020] [Indexed: 01/05/2023]
Abstract
BACKGROUND Leukoaraiosis (LA) severity is associated with poor outcome after mechanical thrombectomy (MT) for acute ischemic stroke (AIS) caused by large vessel occlusion. This meta-analysis aimed to assess the association of LA severity with AIS-related risk factors and outcomes of MT. METHODS PubMed, Web of Science, EMBASE, and Cochrane Collaboration Database was searched for studies on MT for AIS with LA. We conducted a random-effects meta-analysis for the prevalence of stroke risk factors and the MT outcome in the absent to moderate LA and severe LA groups. RESULTS We included seven cohort studies involving 1294 participants (1019 with absent to moderate LA and 275 with severe LA). The absent to moderate LA group had a significantly lower prevalence of coronary artery disease (odds ratio [OR] 0.43; 95% CI 0.29-0.66), atrial fibrillation (OR, 0.26; 95% CI 0.17-0.38), hypertension (OR, 0.39; 95% CI 0.24-0.61), and ischemic stroke (OR, 0.27; 95% CI 0.15-0.50) than the severe LA group. There were no significant between-group differences in symptom onset to recanalization time (364.4 versus 356.2 min, mean difference 19.4; 95% CI - 28.3 to 67.2), final recanalization rate (modified thrombolysis in cerebral infarction score of 2b/3; OR, 0.87; 95% CI 0.55-1.38), and symptomatic intracranial hemorrhage (OR, 0.62; 95% CI 0.34-1.11). The absent to moderate LA group had a higher good functional outcome (modified Rankin Scale score of 0-2 at 90 days; OR, 4.55; 95% CI 3.20-6.47) and a lower mortality rate (179/1019 vs 108/275; OR, 0.28; 95% CI 0.20-0.39). CONCLUSION There are unique differences in the characteristics of risk factors and clinical outcomes of ischemic stroke across patients with LA of different severity. Patients with severe LA are more likely to be associated with risk factors for cerebrovascular disease and have a poor post-MT outcome.
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Affiliation(s)
- Longwen Huo
- Department of Neurology and Neuroscience Center, The First Hospital of Jilin University, Changchun, China
| | - Penghui Chen
- Department of Cardiology, Hunan Provincial People's Hospital, The First Affiliated Hospital of Hunan Normal University, Changsha, China
| | - Zhongxiu Wang
- Department of Neurology and Neuroscience Center, The First Hospital of Jilin University, Changchun, China
| | - Xiandong Li
- Department of Neurology and Neuroscience Center, The First Hospital of Jilin University, Changchun, China
| | - Jie Zhou
- Department of Neurology and Neuroscience Center, The First Hospital of Jilin University, Changchun, China
| | - Chao Wang
- Department of Neurology and Neuroscience Center, The First Hospital of Jilin University, Changchun, China
| | - Dajiang Xing
- Department of Neurology and Neuroscience Center, The First Hospital of Jilin University, Changchun, China
| | - Shouchun Wang
- Department of Neurology and Neuroscience Center, The First Hospital of Jilin University, Changchun, China.
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Ryu WS, Yoon HS, Jeong SW, Kim DE. Hyperintense Vessel Sign in Large-Vessel Occlusion Stroke of Mild-to-Moderate Severity Ineligible for Recanalization. J Clin Neurol 2021; 17:516-523. [PMID: 34595859 PMCID: PMC8490907 DOI: 10.3988/jcn.2021.17.4.516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 06/10/2021] [Accepted: 06/10/2021] [Indexed: 11/17/2022] Open
Abstract
Background and Purpose The impact of fluid-attenuated inversion recovery hyperintense vessels (FHVs) on outcomes in patients ineligible for recanalization therapy with large-vessel occlusion (LVO) is unclear. We investigated the impact of FHVs determined using the FHV–Alberta Stroke Program Early CT Score (ASPECTS) on clinical outcomes in patients with LVO stroke of mild-to-moderate severity ineligible for recanalization therapy. Methods Sixty-eight consecutive patients with M1-middle cerebral artery occlusion who underwent magnetic resonance imaging within 24 hours of symptom onset and were ineligible for recanalization were included. Patients were dichotomized into a severe-FHV group (FHV-ASPECTS ≤4; n=33) and a mild-FHV group (FHV-ASPECTS >4; n=35), and multiple logistic regression analysis was used to examine the relationships of FHV scores with early neurological deterioration (END) and an unfavorable 3-month outcome (modified Rankin Scale score ≥3). Results Mean age was 66.2±13.5 years (mean±SD), and 30 (44%) were female. The severe-FHV group had a larger infarct volume (median, 5.5 mL vs. 3 mL) and more frequently exhibited the susceptibility vessel sign (30% vs. 3%) than the mild-FHV group. Ipsilateral old nonlacunar infarct was more frequent in the mild-FHV group than in the severe-FHV group (37% vs. 15%). The severe-FHV group had a fivefold higher risk of END (odds ratio [OR] 5.02, 95% confidence interval [CI] 1.36–18.45) and unfavorable outcome (OR 5.97, 95% CI 1.18–33.31, p=0.03) compared with the mild-FHV group. Conclusions Greater FHV extent was associated with higher risk of END and unfavorable outcome in patients with LVO stroke of mild-to-moderate severity.
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Affiliation(s)
- Wi Sun Ryu
- Department of Neurology, Dongguk University Ilsan Hospital, Goyang, Korea.
| | - Ho Sang Yoon
- Department of Neurology, Dongguk University Ilsan Hospital, Goyang, Korea
| | - Sang Wuk Jeong
- Department of Neurology, Dongguk University Ilsan Hospital, Goyang, Korea
| | - Dong Eog Kim
- Department of Neurology, Dongguk University Ilsan Hospital, Goyang, Korea
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50
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Ryu WS, Schellingerhout D, Hong KS, Jeong SW, Kim BJ, Kim JT, Lee KB, Park TH, Park SS, Park JM, Kang K, Cho YJ, Park HK, Lee BC, Yu KH, Oh MS, Lee SJ, Kim JG, Cha JK, Kim DH, Lee J, Han MK, Park MS, Choi KH, Nahrendorf M, Lee J, Bae HJ, Kim DE. Relation of Pre-Stroke Aspirin Use With Cerebral Infarct Volume and Functional Outcomes. Ann Neurol 2021; 90:763-776. [PMID: 34536234 PMCID: PMC9292882 DOI: 10.1002/ana.26219] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 09/13/2021] [Accepted: 09/14/2021] [Indexed: 01/13/2023]
Abstract
Objective We investigated (1) the associations of pre‐stroke aspirin use with thrombus burden, infarct volume, hemorrhagic transformation, early neurological deterioration (END), and functional outcome, and (2) whether stroke subtypes modify these associations in first‐ever ischemic stroke. Methods This multicenter magnetic resonance imaging (MRI)‐based study included 5,700 consecutive patients with acute first‐ever ischemic stroke, who did not undergo intravenous thrombolysis or endovascular thrombectomy, from May 2011 through February 2014. Propensity score‐based augmented inverse probability weighting was performed to estimate adjusted effects of pre‐stroke aspirin use. Results The mean age was 67 years (41% women), and 15.9% (n = 907) were taking aspirin before stroke. Pre‐stroke aspirin use (vs nonuse) was significantly related to a reduced infarct volume (by 30%), particularly in large artery atherosclerosis stroke (by 45%). In cardioembolic stroke, pre‐stroke aspirin use was associated with a ~50% lower incidence of END (adjusted difference = −5.4%, 95% confidence interval [CI] = −8.9 to −1.9). Thus, pre‐stroke aspirin use was associated with ~30% higher likelihood of favorable outcome (3‐month modified Rankin Scale score < 3), particularly in large artery atherosclerosis stroke and cardioembolic stroke (adjusted difference = 7.2%, 95% CI = 1.8 to 12.5 and adjusted difference = 6.4%, 95% CI = 1.7 to 11.1, respectively). Pre‐stroke aspirin use (vs nonuse) was associated with 85% less frequent cerebral thrombus‐related susceptibility vessel sign (SVS) in large artery atherosclerosis stroke (adjusted difference = −1.4%, 95% CI = −2.1 to −0.8, p < 0.001) and was associated with ~40% lower SVS volumes, particularly in cardioembolic stroke (adjusted difference = −0.16 cm3, 95% CI = −0.29 to −0.02, p = 0.03). Moreover, pre‐stroke aspirin use was not significantly associated with hemorrhagic transformation (adjusted difference = −1.1%, p = 0.09). Interpretation Pre‐stroke aspirin use associates with improved functional independence in patients with first‐ever ischemic large arterial stroke by reducing infarct volume and/or END, likely by decreasing thrombus burden, without increased risk of hemorrhagic transformation. ANN NEUROL 2021;90:763–776
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Affiliation(s)
- Wi-Sun Ryu
- Department of Neurology, Dongguk University Ilsan Hospital, Goyang, South Korea.,National Priority Research Center for Stroke, Goyang, South Korea
| | - Dawid Schellingerhout
- Departments of Radiology and Cancer Systems Imaging, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Keun-Sik Hong
- Department of Neurology, Inje University Ilsan Paik Hospital, Goyang
| | - Sang-Wuk Jeong
- Department of Neurology, Dongguk University Ilsan Hospital, Goyang, South Korea
| | - Beom Joon Kim
- Department of Neurology, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Joon-Tae Kim
- Department of Neurology, Chonnam National University Hospital, Gwangju, South Korea
| | - Kyung Bok Lee
- Department of Neurology, Soonchunhyang University Hospital, Seoul, South Korea
| | - Tai Hwan Park
- Department of Neurology, Seoul Medical Center, Seoul, South Korea
| | - Sang-Soon Park
- Department of Neurology, Seoul Medical Center, Seoul, South Korea
| | - Jong-Moo Park
- Department of Neurology, Uijeongbu Eulji Medical Center, Eulji University School of Medicine, Uijeongbu, South Korea
| | - Kyusik Kang
- Department of Neurology, Nowon Eulji Medical Center, Eulji University School of Medicine, Daejeon, South Korea
| | - Yong-Jin Cho
- Department of Neurology, Inje University Ilsan Paik Hospital, Goyang
| | - Hong-Kyun Park
- Department of Neurology, Inje University Ilsan Paik Hospital, Goyang
| | - Byung-Chul Lee
- Department of Neurology, Hallym University Sacred Heart Hospital, Anyang, South Korea
| | - Kyung-Ho Yu
- Department of Neurology, Hallym University Sacred Heart Hospital, Anyang, South Korea
| | - Mi Sun Oh
- Department of Neurology, Hallym University Sacred Heart Hospital, Anyang, South Korea
| | - Soo Joo Lee
- Department of Neurology, Daejeon Eulji Medical Center, Eulji University School of Medicine, Daejeon, South Korea
| | - Jae Guk Kim
- Department of Neurology, Daejeon Eulji Medical Center, Eulji University School of Medicine, Daejeon, South Korea
| | - Jae-Kwan Cha
- Department of Neurology, Dong-A University Hospital, Busan, South Korea
| | - Dae-Hyun Kim
- Department of Neurology, Dong-A University Hospital, Busan, South Korea
| | - Jun Lee
- Department of Neurology, Yeungnam University Hospital, Daegu, South Korea
| | - Moon-Ku Han
- Department of Neurology, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Man Seok Park
- Department of Neurology, Chonnam National University Hospital, Gwangju, South Korea
| | - Kang-Ho Choi
- Department of Neurology, Chonnam National University Hospital, Gwangju, South Korea
| | - Matthias Nahrendorf
- Center for Systems Biology and Department of Radiology, Massachusetts General Hospital Research Institute, Harvard Medical School, Boston, MA
| | - Juneyoung Lee
- Department of Biostatistics, Korea University, Seoul, South Korea
| | - Hee-Joon Bae
- Department of Neurology, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Dong-Eog Kim
- Department of Neurology, Dongguk University Ilsan Hospital, Goyang, South Korea.,National Priority Research Center for Stroke, Goyang, South Korea
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