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Jang J, Choi KS, Lee J, Lee H, Hwang I, Park JH, Chung JW, Choi SH, Kim H. Unsupervised Deep Learning for Blood-Brain Barrier Leakage Detection in Diffuse Glioma Using Dynamic Contrast-enhanced MRI. Radiol Artif Intell 2025; 7:e240507. [PMID: 40172325 DOI: 10.1148/ryai.240507] [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] [Indexed: 04/04/2025]
Abstract
Purpose To develop an unsupervised deep learning framework for generalizable blood-brain barrier leakage detection using dynamic contrast-enhanced MRI, without requiring pharmacokinetic models and arterial input function estimation. Materials and Methods This retrospective study included data from patients who underwent dynamic contrast-enhanced MRI between April 2010 and December 2020. An autoencoder-based anomaly detection approach identified one-dimensional voxel-wise time-series abnormal signals through reconstruction residuals, separating them into residual leakage signals (RLSs) and residual vascular signals. The RLS maps were evaluated and compared with the volume transfer constant (Ktrans) using the structural similarity index and correlation coefficient. Generalizability was tested on subsampled data, and isocitrate dehydrogenase (IDH) status classification performance was assessed using area under the receiver operating characteristic curve (AUC). Results A total of 274 patients (mean age, 54.4 years ± 14.6 [SD]; 164 male) were included in the study. RLS showed high structural similarity (structural similarity index, 0.91 ± 0.02) and correlation (r = 0.56; P < .001) with Ktrans. On subsampled data, RLS maps showed better correlation with RLS values from the original data (0.89 vs 0.72; P < .001), higher peak signal-to-noise ratio (33.09 dB vs 28.94 dB; P < .001), and higher structural similarity index (0.92 vs 0.87; P < .001) compared with Ktrans maps. RLS maps also outperformed Ktrans maps in predicting IDH mutation status (AUC, 0.87 [95% CI: 0.83, 0.91] vs 0.81 [95% CI: 0.76, 0.85]; P = .02). Conclusion The unsupervised framework effectively detected blood-brain barrier leakage without pharmacokinetic models and arterial input function. Keywords: Dynamic Contrast-enhanced MRI, Unsupervised Learning, Feature Detection, Blood-Brain Barrier Leakage Detection Supplemental material is available for this article. © RSNA, 2025 See also commentary by Júdice de Mattos Farina and Kuriki in this issue.
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Affiliation(s)
- Joon Jang
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Kyu Sung Choi
- Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongnogu, Seoul 03080, Republic of Korea
- Artificial Intelligence Collaborative Network, Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Junhyeok Lee
- Interdisciplinary Programs in Cancer Biology Major, Seoul National University Graduate School, Seoul, Republic of Korea
| | - Hyochul Lee
- Interdisciplinary Programs in Cancer Biology Major, Seoul National University Graduate School, Seoul, Republic of Korea
| | - Inpyeong Hwang
- Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongnogu, Seoul 03080, Republic of Korea
- Artificial Intelligence Collaborative Network, Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jung Hyun Park
- Department of Radiology, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, Republic of Korea
| | - Jin Wook Chung
- Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongnogu, Seoul 03080, Republic of Korea
- Artificial Intelligence Collaborative Network, Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
- Institute of Innovate Biomedical Technology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Seung Hong Choi
- Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongnogu, Seoul 03080, Republic of Korea
- Artificial Intelligence Collaborative Network, Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
- Center for Nanoparticle Research, Institute for Basic Science, Seoul, Republic of Korea
| | - Hyeonjin Kim
- Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongnogu, Seoul 03080, Republic of Korea
- Department of Medical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
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Kuo DP, Chen YC, Cheng SJ, Hsieh KLC, Ou CY, Li YT, Chen CY. Ischemia-reperfusion injury in a salvaged penumbra: Longitudinal high-tesla perfusion magnetic resonance imaging in a rat model. Magn Reson Imaging 2024; 112:47-53. [PMID: 38909765 DOI: 10.1016/j.mri.2024.06.003] [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: 04/18/2024] [Revised: 05/23/2024] [Accepted: 06/20/2024] [Indexed: 06/25/2024]
Abstract
INTRODUCTION Although ischemia-reperfusion (I/R) injury varies between cortical and subcortical regions, its effects on specific regions remain unclear. In this study, we used various magnetic resonance imaging (MRI) techniques to examine the spatiotemporal dynamics of I/R injury within the salvaged ischemic penumbra (IP) and reperfused ischemic core (IC) of a rodent model, with the aim of enhancing therapeutic strategies by elucidating these dynamics. MATERIALS AND METHODS A total of 17 Sprague-Dawley rats were subjected to 1 h of transient middle cerebral artery occlusion with a suture model. MRI, including diffusion tensor imaging (DTI), T2-weighted imaging, perfusion-weighted imaging, and T1 mapping, was conducted at multiple time points for up to 5 days during the I/R phases. The spatiotemporal dynamics of blood-brain barrier (BBB) modifications were characterized through changes in T1 within the IP and IC regions and compared with mean diffusivity (MD), T2, and cerebral blood flow. RESULTS During the I/R phases, the MD of the IC initially decreased, normalized after recanalization, decreased again at 24 h, and peaked on day 5. By contrast, the IP remained relatively stable. Both the IP and IC exhibited hyperperfusion, with the IP reaching its peak at 24 h, followed by resolution, whereas hyperperfusion was maintained in the IC until day 5. Despite hyperperfusion, the IP maintained an intact BBB, whereas the IC experienced persistent BBB leakage. At 24 h, the IC exhibited an increase in the T2 signal, corresponding to regions exhibiting BBB disruption at 5 days. CONCLUSIONS Hyperperfusion and BBB impairment have distinct patterns in the IP and IC. Quantitative T1 mapping may serve as a supplementary tool for the early detection of malignant hyperemia accompanied by BBB leakage, aiding in precise interventions after recanalization. These findings underscore the value of MRI markers in monitoring ischemia-specific regions and customizing therapeutic strategies to improve patient outcomes.
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Affiliation(s)
- Duen-Pang Kuo
- Department of Medical Imaging, Taipei Medical University Hospital, Taipei, Taiwan; Translational Imaging Research Center, Taipei Medical University Hospital, Taipei, Taiwan; Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Yung-Chieh Chen
- Department of Medical Imaging, Taipei Medical University Hospital, Taipei, Taiwan; Translational Imaging Research Center, Taipei Medical University Hospital, Taipei, Taiwan; Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Sho-Jen Cheng
- Department of Medical Imaging, Taipei Medical University Hospital, Taipei, Taiwan; Translational Imaging Research Center, Taipei Medical University Hospital, Taipei, Taiwan
| | - Kevin Li-Chun Hsieh
- Department of Medical Imaging, Taipei Medical University Hospital, Taipei, Taiwan; Translational Imaging Research Center, Taipei Medical University Hospital, Taipei, Taiwan; Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Chen-Yin Ou
- Translational Imaging Research Center, Taipei Medical University Hospital, Taipei, Taiwan
| | - Yi-Tien Li
- Translational Imaging Research Center, Taipei Medical University Hospital, Taipei, Taiwan; Research Center for Neuroscience, Taipei Medical University, Taipei, Taiwan; Ph.D. Program in Medical Neuroscience, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan.
| | - Cheng-Yu Chen
- Department of Medical Imaging, Taipei Medical University Hospital, Taipei, Taiwan; Translational Imaging Research Center, Taipei Medical University Hospital, Taipei, Taiwan; Research Center for Artificial Intelligence in Medicine, Taipei Medical University, Taipei, Taiwan; Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan; Department of Radiology, National Defense Medical Center, Taipei, Taiwan
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Liang Y, Jiang Y, Liu J, Li X, Cheng X, Bao L, Zhou H, Guo Z. Blood-Brain Barrier Disruption and Imaging Assessment in Stroke. Transl Stroke Res 2024:10.1007/s12975-024-01300-6. [PMID: 39322815 DOI: 10.1007/s12975-024-01300-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2024] [Revised: 08/20/2024] [Accepted: 09/19/2024] [Indexed: 09/27/2024]
Abstract
Disruption of the blood-brain barrier (BBB) is an important pathological hallmark of ischemic stroke. Blood-brain barrier disruption (BBBD) is a consequence of ischemia and may also exacerbate damage to brain parenchyma. Therefore, maintaining BBB integrity is critical for the central nervous system (CNS) homeostasis. This review offers a concise overview of BBB structure and function, along with the mechanisms underlying its impairment following a stroke. In addition, we review the recent imaging techniques employed to study blood-brain barrier permeability (BBBP) in the context of ischemic brain injury with the goal of providing imaging guidance for stroke diagnosis and treatment from the perspective of the BBBD. This knowledge is vital for developing strategies to safeguard the BBB during cerebral ischemia.
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Affiliation(s)
- Yuchen Liang
- Department of Radiology, the First Hospital of Jilin University, Changchun, China
| | - Yueluan Jiang
- MR Research and Collaboration Team, Diagnostic Imaging, Siemens Healthineers Ltd., Beijing, China
| | - Jiaxin Liu
- Department of Radiology, the First Hospital of Jilin University, Changchun, China
| | - Xuewei Li
- Department of Radiology, the First Hospital of Jilin University, Changchun, China
| | - Xinyue Cheng
- Department of Radiology, the First Hospital of Jilin University, Changchun, China
| | - Lei Bao
- Department of Radiology, the First Hospital of Jilin University, Changchun, China
| | - Hongwei Zhou
- Department of Radiology, the First Hospital of Jilin University, Changchun, China.
| | - Zhenni Guo
- Department of Neurology, Stroke Center, the First Hospital of Jilin University, Changchun, China.
- Department of Neurology, Neuroscience Research Center, the First Hospital of Jilin University, Changchun, China.
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Ru X, Zhao S, Chen W, Wu J, Yu R, Wang D, Dong M, Wu Q, Peng D, Song Y. A weakly supervised deep learning model integrating noncontrasted computed tomography images and clinical factors facilitates haemorrhagic transformation prediction after intravenous thrombolysis in acute ischaemic stroke patients. Biomed Eng Online 2023; 22:129. [PMID: 38115029 PMCID: PMC10731772 DOI: 10.1186/s12938-023-01193-w] [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: 01/28/2023] [Accepted: 12/09/2023] [Indexed: 12/21/2023] Open
Abstract
BACKGROUND Haemorrhage transformation (HT) is a serious complication of intravenous thrombolysis (IVT) in acute ischaemic stroke (AIS). Accurate and timely prediction of the risk of HT before IVT may change the treatment decision and improve clinical prognosis. We aimed to develop a deep learning method for predicting HT after IVT for AIS using noncontrast computed tomography (NCCT) images. METHODS We retrospectively collected data from 828 AIS patients undergoing recombinant tissue plasminogen activator (rt-PA) treatment within a 4.5-h time window (n = 665) or of undergoing urokinase treatment within a 6-h time window (n = 163) and divided them into the HT group (n = 69) and non-HT group (n = 759). HT was defined based on the criteria of the European Cooperative Acute Stroke Study-II trial. To address the problems of indiscernible features and imbalanced data, a weakly supervised deep learning (WSDL) model for HT prediction was constructed based on multiple instance learning and active learning using admission NCCT images and clinical information in addition to conventional deep learning models. Threefold cross-validation and transfer learning were performed to confirm the robustness of the network. Of note, the predictive value of the commonly used scales in clinics associated with NCCT images (i.e., the HAT and SEDAN score) was also analysed and compared to measure the feasibility of our proposed DL algorithms. RESULTS Compared to the conventional DL and ML models, the WSDL model had the highest AUC of 0.799 (95% CI 0.712-0.883). Significant differences were observed between the WSDL model and five ML models (P < 0.05). The prediction performance of the WSDL model outperforms the HAT and SEDAN scores at the optimal operating point (threshold = 1.5). Further subgroup analysis showed that the WSDL model performed better for symptomatic intracranial haemorrhage (AUC = 0.833, F1 score = 0.909). CONCLUSIONS Our WSDL model based on NCCT images had relatively good performance for predicting HT in AIS and may be suitable for assisting in clinical treatment decision-making.
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Affiliation(s)
- Xiaoshuang Ru
- Department of Radiology, Central Hospital of Dalian University of Technology, No. 826 Xinan Rd, Shahekou District, Dalian, 116033, Liaoning Province, China
| | - Shilong Zhao
- Department of Radiology, Affliated ZhongShan Hospital of Dalian University, No. 6 Jiefang Rd, Zhongshan District, Dalian, 116001, Liaoning Province, China
| | - Weidao Chen
- InferVision Medical Technology Company Ltd, 25F, Building E, Yuanyang International Center, Chaoyang District, Beijing, 100025, China
| | - Jiangfen Wu
- InferVision Medical Technology Company Ltd, 25F, Building E, Yuanyang International Center, Chaoyang District, Beijing, 100025, China
| | - Ruize Yu
- InferVision Medical Technology Company Ltd, 25F, Building E, Yuanyang International Center, Chaoyang District, Beijing, 100025, China
| | - Dawei Wang
- InferVision Medical Technology Company Ltd, 25F, Building E, Yuanyang International Center, Chaoyang District, Beijing, 100025, China
| | - Mengxing Dong
- InferVision Medical Technology Company Ltd, 25F, Building E, Yuanyang International Center, Chaoyang District, Beijing, 100025, China
| | - Qiong Wu
- Department of Neurology, Central Hospital of Dalian University of Technology, No. 826 Xinan Rd, Shahekou District, Dalian, 116033, Liaoning Province, China
| | - Daoyong Peng
- Department of Neurology, Central Hospital of Dalian University of Technology, No. 826 Xinan Rd, Shahekou District, Dalian, 116033, Liaoning Province, China
| | - Yang Song
- Department of Radiology, Central Hospital of Dalian University of Technology, No. 826 Xinan Rd, Shahekou District, Dalian, 116033, Liaoning Province, China.
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Uchida Y, Kan H, Sakurai K, Oishi K, Matsukawa N. Contributions of blood-brain barrier imaging to neurovascular unit pathophysiology of Alzheimer's disease and related dementias. Front Aging Neurosci 2023; 15:1111448. [PMID: 36861122 PMCID: PMC9969807 DOI: 10.3389/fnagi.2023.1111448] [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: 11/29/2022] [Accepted: 01/26/2023] [Indexed: 02/11/2023] Open
Abstract
The blood-brain barrier (BBB) plays important roles in the maintenance of brain homeostasis. Its main role includes three kinds of functions: (1) to protect the central nervous system from blood-borne toxins and pathogens; (2) to regulate the exchange of substances between the brain parenchyma and capillaries; and (3) to clear metabolic waste and other neurotoxic compounds from the central nervous system into meningeal lymphatics and systemic circulation. Physiologically, the BBB belongs to the glymphatic system and the intramural periarterial drainage pathway, both of which are involved in clearing interstitial solutes such as β-amyloid proteins. Thus, the BBB is believed to contribute to preventing the onset and progression for Alzheimer's disease. Measurements of BBB function are essential toward a better understanding of Alzheimer's pathophysiology to establish novel imaging biomarkers and open new avenues of interventions for Alzheimer's disease and related dementias. The visualization techniques for capillary, cerebrospinal, and interstitial fluid dynamics around the neurovascular unit in living human brains have been enthusiastically developed. The purpose of this review is to summarize recent BBB imaging developments using advanced magnetic resonance imaging technologies in relation to Alzheimer's disease and related dementias. First, we give an overview of the relationship between Alzheimer's pathophysiology and BBB dysfunction. Second, we provide a brief description about the principles of non-contrast agent-based and contrast agent-based BBB imaging methodologies. Third, we summarize previous studies that have reported the findings of each BBB imaging method in individuals with the Alzheimer's disease continuum. Fourth, we introduce a wide range of Alzheimer's pathophysiology in relation to BBB imaging technologies to advance our understanding of the fluid dynamics around the BBB in both clinical and preclinical settings. Finally, we discuss the challenges of BBB imaging techniques and suggest future directions toward clinically useful imaging biomarkers for Alzheimer's disease and related dementias.
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Affiliation(s)
- Yuto Uchida
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States,*Correspondence: Yuto Uchida, ; Noriyuki Matsukawa,
| | - Hirohito Kan
- Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Keita Sakurai
- Department of Radiology, National Center for Geriatrics and Gerontology, Ōbu, Aichi, Japan
| | - Kenichi Oishi
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Noriyuki Matsukawa
- Department of Neurology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan,*Correspondence: Yuto Uchida, ; Noriyuki Matsukawa,
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MRI-guided thrombolysis for lenticulostriate artery stroke within 12 h of symptom onset. Sci Rep 2022; 12:7445. [PMID: 35523924 PMCID: PMC9076823 DOI: 10.1038/s41598-022-11459-3] [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: 08/25/2021] [Accepted: 04/01/2022] [Indexed: 11/23/2022] Open
Abstract
Stroke thrombolysis treatment is generally administered within 4.5 h, but a greater time window may be permitted depending upon the ischemic penumbra on neuroimaging. This observational cohort study investigated the outcomes of thrombolysis given within 12 h after symptom onset of lenticulostriate artery stroke. The population comprised 160 patients. Thrombolysis was administered via tissue plasminogen activator, alteplase (TPA). Thrombolysis was indicated by a mismatch between diffusion-weighted imaging (DWI) and T2-weighted imaging (T2WI), that is, an acute ischemic lesion on DWI without a corresponding lesion on T2WI. Demographics and medical history were compared with the modified Rankin scale (mRS) score, to reflect outcome. Patients with a favorable clinical outcome (mRS 0–1) had significantly lower hypertension, baseline NIH Stroke Scale (NIHSS) score, and admission systolic/diastolic blood pressure compared with patients with mRS 2–6. Lower admission systolic blood pressure and NIHSS score were significantly associated with favorable outcome. In patients either with IV-TPA within 4.5 h, or between 4.5 and 12 h, lower admission systolic blood pressure and/or NIHSS score similarly independently predict favorable outcome. However, in all groups, the onset-to-treatment time did not significantly influence the outcomes. We conclude that in our cohort higher admission systolic blood pressure and higher baseline NIHSS and not time were associated with poor outcome in patients with magnetic resonance-guided thrombolysis within 12 h of isolated lenticulostriate artery stroke, therefore loosening the traditionally perceived dependency of outcome on time.
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Hong L, Hsu TM, Zhang Y, Cheng X. Neuroimaging Prediction of Hemorrhagic Transformation for Acute Ischemic Stroke. Cerebrovasc Dis 2022; 51:542-552. [PMID: 35026765 DOI: 10.1159/000521150] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 11/20/2021] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Hemorrhagic transformation (HT) is a common complication of acute ischemic stroke, often resulting from reperfusion therapy. Early prediction of HT can enable stroke neurologists to undertake measures to avoid clinical deterioration and make optimal treatment strategies. Moreover, the trend of extending the time window for reperfusion therapy (both for intravenous thrombolysis and endovascular treatment) further requires more precise detection of HT tendency. SUMMARY In this review, we summarized and discussed the neuroimaging markers of HT prediction of acute ischemic stroke patients, mainly focusing on neuroimaging markers of ischemic degree and neuroimaging markers of blood-brain barrier permeability. This review is aimed to provide a concise introduction of HT prediction and to elicit possibilities of future research combining advanced technology to improve the accessibility and accuracy of HT prediction under emergent clinical settings. Key Messages: Substantial studies have utilized neuroimaging, blood biomarkers, and clinical variables to predict HT occurrence. Although huge progress has been made, more individualized and precise HT prediction using simple and robust imaging predictors combining stroke onset time should be the future goal of development.
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Affiliation(s)
- Lan Hong
- Department of Neurology, National Center for Neurological Disorders, National Clinical Research Centre for Aging and Medicine, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai, China,
| | - Tzu-Ming Hsu
- Shanghai Medical College, Fudan University, Shanghai, China
| | - Yiran Zhang
- Department of Neurology, National Center for Neurological Disorders, National Clinical Research Centre for Aging and Medicine, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai, China
| | - Xin Cheng
- Department of Neurology, National Center for Neurological Disorders, National Clinical Research Centre for Aging and Medicine, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai, China
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Arba F, Rinaldi C, Caimano D, Vit F, Busto G, Fainardi E. Blood-Brain Barrier Disruption and Hemorrhagic Transformation in Acute Ischemic Stroke: Systematic Review and Meta-Analysis. Front Neurol 2021; 11:594613. [PMID: 33551955 PMCID: PMC7859439 DOI: 10.3389/fneur.2020.594613] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Accepted: 12/07/2020] [Indexed: 01/17/2023] Open
Abstract
Introduction: Hemorrhagic transformation (HT) is a complication of reperfusion therapy for acute ischemic stroke. Blood–brain barrier (BBB) disruption is a crucial step toward HT; however, in clinical studies, there is still uncertainty about this relation. Hence, we conducted a systematic review and meta-analysis to summarize the current evidence. Methods: We performed systematic review and meta-analysis of observational studies from January 1990 to March 2020 about the relation between BBB disruption and HT in patients with acute ischemic stroke with both computed tomography (CT) and magnetic resonance (MR) assessment of BBB. The outcome of interest was HT at follow-up imaging evaluation (within 48 h from symptom onset). We pooled data from available univariate odds ratios (ORs) in random-effects models with DerSimonian–Laird weights and extracted cumulative ORs. Results: We included 30 eligible studies (14 with CT and 16 with MR), N = 2,609 patients, with 88% and 70% of patients included in CT and MR studies treated with acute stroke therapy, respectively. The majority of studies were retrospective and had high or unclear risk of bias. BBB disruption was measured with consistent methodology in CT studies, whereas in MR studies, there was more variability. All CT studies provided a BBB disruption cutoff predictive of HT. Four CT and 10 MR studies were included in the quantitative analysis. We found that BBB disruption was associated with HT with both CT (OR = 3.42; 95%CI = 1.62–7.23) and MR (OR = 9.34; 95%CI = 3.16–27.59). There was a likely publication bias particularly for MR studies. Conclusion: Our results confirm that BBB disruption is associated with HT in both CT and MR studies. Compared with MR, CT has been more uniformly applied in the literature and has resulted in more consistent results. However, more efforts are needed for harmonization of protocols and methodology for implementation of BBB disruption as a neuroradiological marker in clinical practice.
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Affiliation(s)
| | - Chiara Rinaldi
- NEUROFARBA Department, University of Florence, Florence, Italy
| | - Danilo Caimano
- NEUROFARBA Department, University of Florence, Florence, Italy
| | - Federica Vit
- NEUROFARBA Department, University of Florence, Florence, Italy
| | | | - Enrico Fainardi
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
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Abstract
The blood-brain barrier (BBB) is the interface between the blood and brain tissue, which regulates the maintenance of homeostasis within the brain. Impaired BBB integrity is increasingly associated with various neurological diseases. To gain a better understanding of the underlying processes involved in BBB breakdown, magnetic resonance imaging (MRI) techniques are highly suitable for noninvasive BBB assessment. Commonly used MRI techniques to assess BBB integrity are dynamic contrast-enhanced and dynamic susceptibility contrast MRI, both relying on leakage of gadolinium-based contrast agents. A number of conceptually different methods exist that target other aspects of the BBB. These alternative techniques make use of endogenous markers, such as water and glucose, as contrast media. A comprehensive overview of currently available MRI techniques to assess the BBB condition is provided from a scientific point of view, including potential applications in disease. Improvements that are required to make these techniques clinically more easily applicable will also be discussed.
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Yoen H, Yoo RE, Choi SH, Kim E, Oh BM, Yang D, Hwang I, Kang KM, Yun TJ, Kim JH, Sohn CH. Blood-Brain Barrier Disruption in Mild Traumatic Brain Injury Patients with Post-Concussion Syndrome: Evaluation with Region-Based Quantification of Dynamic Contrast-Enhanced MR Imaging Parameters Using Automatic Whole-Brain Segmentation. Korean J Radiol 2020; 22:118-130. [PMID: 32783413 PMCID: PMC7772380 DOI: 10.3348/kjr.2020.0016] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Revised: 05/05/2020] [Accepted: 05/24/2020] [Indexed: 12/29/2022] Open
Abstract
Objective This study aimed to investigate the blood-brain barrier (BBB) disruption in mild traumatic brain injury (mTBI) patients with post-concussion syndrome (PCS) using dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging and automatic whole brain segmentation. Materials and Methods Forty-two consecutive mTBI patients with PCS who had undergone post-traumatic MR imaging, including DCE MR imaging, between October 2016 and April 2018, and 29 controls with DCE MR imaging were included in this retrospective study. After performing three-dimensional T1-based brain segmentation with FreeSurfer software (Laboratory for Computational Neuroimaging), the mean Ktrans and vp from DCE MR imaging (derived using the Patlak model and extended Tofts and Kermode model) were analyzed in the bilateral cerebral/cerebellar cortex, bilateral cerebral/cerebellar white matter (WM), and brainstem. Ktrans values of the mTBI patients and controls were calculated using both models to identify the model that better reflected the increased permeability owing to mTBI (tendency toward higher Ktrans values in mTBI patients than in controls). The Mann-Whitney U test and Spearman rank correlation test were performed to compare the mean Ktrans and vp between the two groups and correlate Ktrans and vp with neuropsychological tests for mTBI patients. Results Increased permeability owing to mTBI was observed in the Patlak model but not in the extended Tofts and Kermode model. In the Patlak model, the mean Ktrans in the bilateral cerebral cortex was significantly higher in mTBI patients than in controls (p = 0.042). The mean vp values in the bilateral cerebellar WM and brainstem were significantly lower in mTBI patients than in controls (p = 0.009 and p = 0.011, respectively). The mean Ktrans of the bilateral cerebral cortex was significantly higher in patients with atypical performance in the auditory continuous performance test (commission errors) than in average or good performers (p = 0.041). Conclusion BBB disruption, as reflected by the increased Ktrans and decreased vp values from the Patlak model, was observed throughout the bilateral cerebral cortex, bilateral cerebellar WM, and brainstem in mTBI patients with PCS.
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Affiliation(s)
- Heera Yoen
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Roh Eul Yoo
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.
| | - Seung Hong Choi
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.,Center for Nanoparticle Research, Institute for Basic Science (IBS), Seoul National University, Seoul, Korea.,School of Chemical and Biological Engineering, Seoul National University, Seoul, Korea
| | - Eunkyung Kim
- Department of Rehabilitation Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Byung Mo Oh
- Department of Rehabilitation Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.,Department of Rehabilitation Medicine, Seoul National University College of Medicine, Seoul, Korea.,National Traffic Injury Rehabilitation Hospital, Yangpyeong, Korea.,Neuroscience Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Dongjin Yang
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Inpyeong Hwang
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Koung Mi Kang
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Tae Jin Yun
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Ji Hoon Kim
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Chul Ho Sohn
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
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Elsaid N, Mustafa W, Saied A. Radiological predictors of hemorrhagic transformation after acute ischemic stroke: An evidence-based analysis. Neuroradiol J 2020; 33:118-133. [PMID: 31971093 PMCID: PMC7140299 DOI: 10.1177/1971400919900275] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Hemorrhagic transformation (HT) is one of the most common adverse events related to acute ischemic stroke (AIS) that affects the treatment plan and clinical outcome. Identification of a sensitive radiological marker may influence the controversial thrombolytic decision in the setting of AIS and may at a minimum indicate more intensive monitoring or further prophylactic interventions. In this article we summarize possible radiological biomarkers and the role of different radiological modalities including computed tomography (CT), magnetic resonance imaging, angiography, and ultrasound in predicting HT. Different radiological indices of early ischemic changes, large ischemic lesion volume, severe blood flow restriction, blood-brain barrier disruption, poor collaterals and high blood flow velocities have been reported to be associated with higher risk of HT. The current levels of evidence of the available studies highlight the role of the different CT perfusion parameters in predicting HT. Further large standardized studies are recommended to compare the sensitivity and specificity of the different radiological markers combined and delineate the most reliable predictor.
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Affiliation(s)
- Nada Elsaid
- Department of Neurology, University of Mansoura
Faculty of Medicine, Egypt
| | - Wessam Mustafa
- Department of Neurology, University of Mansoura
Faculty of Medicine, Egypt
| | - Ahmed Saied
- Department of Neurology, University of Mansoura
Faculty of Medicine, Egypt
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12
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Smith EE, Biessels GJ, De Guio F, de Leeuw FE, Duchesne S, Düring M, Frayne R, Ikram MA, Jouvent E, MacIntosh BJ, Thrippleton MJ, Vernooij MW, Adams H, Backes WH, Ballerini L, Black SE, Chen C, Corriveau R, DeCarli C, Greenberg SM, Gurol ME, Ingrisch M, Job D, Lam BY, Launer LJ, Linn J, McCreary CR, Mok VC, Pantoni L, Pike GB, Ramirez J, Reijmer YD, Romero JR, Ropele S, Rost NS, Sachdev PS, Scott CJ, Seshadri S, Sharma M, Sourbron S, Steketee RM, Swartz RH, van Oostenbrugge R, van Osch M, van Rooden S, Viswanathan A, Werring D, Dichgans M, Wardlaw JM. Harmonizing brain magnetic resonance imaging methods for vascular contributions to neurodegeneration. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2019; 11:191-204. [PMID: 30859119 PMCID: PMC6396326 DOI: 10.1016/j.dadm.2019.01.002] [Citation(s) in RCA: 62] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
INTRODUCTION Many consequences of cerebrovascular disease are identifiable by magnetic resonance imaging (MRI), but variation in methods limits multicenter studies and pooling of data. The European Union Joint Program on Neurodegenerative Diseases (EU JPND) funded the HARmoNizing Brain Imaging MEthodS for VaScular Contributions to Neurodegeneration (HARNESS) initiative, with a focus on cerebral small vessel disease. METHODS Surveys, teleconferences, and an in-person workshop were used to identify gaps in knowledge and to develop tools for harmonizing imaging and analysis. RESULTS A framework for neuroimaging biomarker development was developed based on validating repeatability and reproducibility, biological principles, and feasibility of implementation. The status of current MRI biomarkers was reviewed. A website was created at www.harness-neuroimaging.org with acquisition protocols, a software database, rating scales and case report forms, and a deidentified MRI repository. CONCLUSIONS The HARNESS initiative provides resources to reduce variability in measurement in MRI studies of cerebral small vessel disease.
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Affiliation(s)
- Eric E. Smith
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, University of Calgary, Alberta, Canada
| | - Geert Jan Biessels
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, Netherlands
| | - François De Guio
- Department of Neurology, Lariboisière Hospital, University Paris Diderot, Paris, France
| | - Frank Erik de Leeuw
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Donders Center for Medical Neuroscience, Radboud University Medical Center, Nijmegen, Netherlands
| | - Simon Duchesne
- CERVO Research Center, Quebec Mental Health Institute, Québec, Canada
- Radiology Department, Université Laval, Québec, Canada
| | - Marco Düring
- Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig-Maximilians-Universität LMU, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE, Munich), Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Richard Frayne
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, University of Calgary, Alberta, Canada
- Seaman Family MR Centre, Foothills Medical Centre, Calgary, Alberta, Canada
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Eric Jouvent
- Department of Neurology, Lariboisière Hospital, University Paris Diderot, Paris, France
| | - Bradley J. MacIntosh
- Heart and Stroke Foundation Canadian Partnership for Stroke Recovery, Department of Medical Biophysics, Sunnybrook Research Institute, University of Toronto, Ontario, Canada
| | - Michael J. Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Meike W. Vernooij
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Hieab Adams
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Walter H. Backes
- Department of Radiology & Nuclear Medicine, School for Mental Health & Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Lucia Ballerini
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Sandra E. Black
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
- Heart and Stroke Foundation Canadian Partnership for Stroke Recovery, Toronto, Ontario, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Christopher Chen
- Memory Aging and Cognition Centre, Department of Pharmacology, National University of Singapore, Singapore
| | - Rod Corriveau
- National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Charles DeCarli
- Department of Neurology and Center for Neuroscience, University of California at Davis, Davis, CA, USA
| | - Steven M. Greenberg
- J. Philip Kistler Stroke Research Center, Stroke Service and Memory Disorders Unit, Massachusetts General Hospital, Boston, MA, USA
| | - M. Edip Gurol
- J. Philip Kistler Stroke Research Center, Stroke Service and Memory Disorders Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Michael Ingrisch
- Department of Radiology, Ludwig-Maximilians-University Hospital Munich, Munich, Germany
| | - Dominic Job
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Bonnie Y.K. Lam
- Therese Pei Fong Chow Research Centre for Prevention of Dementia, Gerald Choa Neuroscience Centre, Lui Che Woo Institute of Innovative Medicine, Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong
| | - Lenore J. Launer
- National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Jennifer Linn
- Institute of Neuroradiology, University Hospital Carl Gustav Carus, Dresden, Germany
| | - Cheryl R. McCreary
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada
- Seaman Family MR Centre, Foothills Medical Centre, Calgary, Alberta, Canada
| | - Vincent C.T. Mok
- Therese Pei Fong Chow Research Centre for Prevention of Dementia, Gerald Choa Neuroscience Centre, Lui Che Woo Institute of Innovative Medicine, Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong
| | - Leonardo Pantoni
- Luigi Sacco Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - G. Bruce Pike
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, University of Calgary, Alberta, Canada
| | - Joel Ramirez
- Heart and Stroke Foundation Canadian Partnership for Stroke Recovery, Department of Medical Biophysics, Sunnybrook Research Institute, University of Toronto, Ontario, Canada
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Yael D. Reijmer
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, Netherlands
| | - Jose Rafael Romero
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Natalia S. Rost
- J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Perminder S. Sachdev
- Centre for Healthy Brain Ageing, University of New South Wales, Sydney, Australia
| | - Christopher J.M. Scott
- Heart and Stroke Foundation Canadian Partnership for Stroke Recovery, Department of Medical Biophysics, Sunnybrook Research Institute, University of Toronto, Ontario, Canada
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Mukul Sharma
- Population Health Research Institute, Hamilton, Ontario, Canada
- Department of Medicine (Neurology) McMaster University, Hamilton, Ontario, Canada
| | - Steven Sourbron
- Imaging Biomarkers Group, Department of Biomedical Imaging Sciences, University of Leeds, Leeds, UK
| | - Rebecca M.E. Steketee
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Richard H. Swartz
- Department of Medicine (Neurology), University of Toronto, Toronto, Canada
- Hurvitz Brain Sciences Program, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Robert van Oostenbrugge
- Department of Neurology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Matthias van Osch
- C.J. Gorter Center for high field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Sanneke van Rooden
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Anand Viswanathan
- J. Philip Kistler Stroke Research Center, Stroke Service and Memory Disorders Unit, Massachusetts General Hospital, Boston, MA, USA
| | - David Werring
- University College London Queen Square institute of Neurology, London, UK
| | - Martin Dichgans
- Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig-Maximilians-Universität LMU, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE, Munich), Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Joanna M. Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
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13
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Thrippleton MJ, Backes WH, Sourbron S, Ingrisch M, van Osch MJP, Dichgans M, Fazekas F, Ropele S, Frayne R, van Oostenbrugge RJ, Smith EE, Wardlaw JM. Quantifying blood-brain barrier leakage in small vessel disease: Review and consensus recommendations. Alzheimers Dement 2019; 15:840-858. [PMID: 31031101 PMCID: PMC6565805 DOI: 10.1016/j.jalz.2019.01.013] [Citation(s) in RCA: 173] [Impact Index Per Article: 28.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2018] [Revised: 11/22/2018] [Accepted: 01/18/2019] [Indexed: 12/12/2022]
Abstract
Cerebral small vessel disease (cSVD) comprises pathological processes of the small vessels in the brain that may manifest clinically as stroke, cognitive impairment, dementia, or gait disturbance. It is generally accepted that endothelial dysfunction, including blood-brain barrier (BBB) failure, is pivotal in the pathophysiology. Recent years have seen increasing use of imaging, primarily dynamic contrast-enhanced magnetic resonance imaging, to assess BBB leakage, but there is considerable variability in the approaches and findings reported in the literature. Although dynamic contrast-enhanced magnetic resonance imaging is well established, challenges emerge in cSVD because of the subtle nature of BBB impairment. The purpose of this work, authored by members of the HARNESS Initiative, is to provide an in-depth review and position statement on magnetic resonance imaging measurement of subtle BBB leakage in clinical research studies, with aspects requiring further research identified. We further aim to provide information and consensus recommendations for new investigators wishing to study BBB failure in cSVD and dementia.
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Affiliation(s)
- Michael J Thrippleton
- Centre for Clinical Brain Science, University of Edinburgh, Edinburgh, UK; Dementia Research Institute, University of Edinburgh, Edinburgh, UK; Edinburgh Imaging, University of Edinburgh, Edinburgh, UK.
| | - Walter H Backes
- Department of Radiology & Nuclear Medicine, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Steven Sourbron
- Leeds Imaging Biomarkers group, Department of Biomedical Imaging Sciences, University of Leeds, Leeds, UK
| | - Michael Ingrisch
- Department of Radiology, Ludwig-Maximilians-University Hospital Munich, Munich, Germany
| | - Matthias J P van Osch
- Department of Radiology, C. J. Gorter Center for High Field MRI, Leiden University Medical Center, Leiden, The Netherlands
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-University München & Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Franz Fazekas
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Richard Frayne
- Department of Radiology, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada; Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada; Seaman Family MR Research Centre, Foothills Medical Centre, Calgary, Alberta, Canada
| | - Robert J van Oostenbrugge
- Department of Neurology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Eric E Smith
- Department of Radiology, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada; Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Joanna M Wardlaw
- Centre for Clinical Brain Science, University of Edinburgh, Edinburgh, UK; Dementia Research Institute, University of Edinburgh, Edinburgh, UK; Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
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14
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Liu HS, Chiang SW, Chung HW, Tsai PH, Hsu FT, Cho NY, Wang CY, Chou MC, Chen CY. Histogram analysis of T2*-based pharmacokinetic imaging in cerebral glioma grading. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2018; 155:19-27. [PMID: 29512499 DOI: 10.1016/j.cmpb.2017.11.011] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2017] [Revised: 10/09/2017] [Accepted: 11/14/2017] [Indexed: 06/08/2023]
Abstract
BACKGROUND AND OBJECTIVE To investigate the feasibility of histogram analysis of the T2*-based permeability parameter volume transfer constant (Ktrans) for glioma grading and to explore the diagnostic performance of the histogram analysis of Ktrans and blood plasma volume (vp). METHODS We recruited 31 and 11 patients with high- and low-grade gliomas, respectively. The histogram parameters of Ktrans and vp, derived from the first-pass pharmacokinetic modeling based on the T2* dynamic susceptibility-weighted contrast-enhanced perfusion-weighted magnetic resonance imaging (T2* DSC-PW-MRI) from the entire tumor volume, were evaluated for differentiating glioma grades. RESULTS Histogram parameters of Ktrans and vp showed significant differences between high- and low-grade gliomas and exhibited significant correlations with tumor grades. The mean Ktrans derived from the T2* DSC-PW-MRI had the highest sensitivity and specificity for differentiating high-grade gliomas from low-grade gliomas compared with other histogram parameters of Ktrans and vp. CONCLUSIONS Histogram analysis of T2*-based pharmacokinetic imaging is useful for cerebral glioma grading. The histogram parameters of the entire tumor Ktrans measurement can provide increased accuracy with additional information regarding microvascular permeability changes for identifying high-grade brain tumors.
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Affiliation(s)
- Hua-Shan Liu
- School of Biomedical Engineering, College of Biomedical Engineering, Taipei Medical University, Taipei, Taiwan; International Ph.D. Program in Biomedical Engineering, College of Biomedical Engineering, Taipei Medical University, Taipei, Taiwan; Research Center of Translational Imaging, College of Medicine, Taipei Medical University, Taipei, Taiwan; Radiogenomic Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan
| | - Shih-Wei Chiang
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan; Department of Radiology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Hsiao-Wen Chung
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan; Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan
| | - Ping-Huei Tsai
- Research Center of Translational Imaging, College of Medicine, Taipei Medical University, Taipei, Taiwan; Radiogenomic Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan; Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan; Department of Medical Imaging, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan; Department of Medical Research, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan
| | - Fei-Ting Hsu
- Research Center of Translational Imaging, College of Medicine, Taipei Medical University, Taipei, Taiwan; Radiogenomic Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan; Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan; Department of Medical Imaging, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan
| | - Nai-Yu Cho
- Department of Radiology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Chao-Ying Wang
- Department and Graduate Institute of Biology and Anatomy, National Defense Medical Center, Taipei, Taiwan
| | - Ming-Chung Chou
- Department of Medical Imaging and Radiological Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan; Department of Healthcare Administration and Medical Informatics, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Cheng-Yu Chen
- Research Center of Translational Imaging, College of Medicine, Taipei Medical University, Taipei, Taiwan; Radiogenomic Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan; Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan; Department of Medical Imaging, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan; Department of Medical Research, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan.
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15
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Walczak P, Wojtkiewicz J, Nowakowski A, Habich A, Holak P, Xu J, Adamiak Z, Chehade M, Pearl MS, Gailloud P, Lukomska B, Maksymowicz W, Bulte JW, Janowski M. Real-time MRI for precise and predictable intra-arterial stem cell delivery to the central nervous system. J Cereb Blood Flow Metab 2017; 37:2346-2358. [PMID: 27618834 PMCID: PMC5531335 DOI: 10.1177/0271678x16665853] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Stem cell therapy for neurological disorders reached a pivotal point when the efficacy of several cell types was demonstrated in small animal models. Translation of stem cell therapy is contingent upon overcoming the challenge of effective cell delivery to the human brain, which has a volume ∼1000 times larger than that of the mouse. Intra-arterial injection can achieve a broad, global, but also on-demand spatially targeted biodistribution; however, its utility has been limited by unpredictable cell destination and homing as dictated by the vascular territory, as well as by safety concerns. We show here that high-speed MRI can be used to visualize the intravascular distribution of a superparamagnetic iron oxide contrast agent and can thus be used to accurately predict the distribution of intra-arterial administered stem cells. Moreover, high-speed MRI enables the real-time visualization of cell homing, providing the opportunity for immediate intervention in the case of undesired biodistribution.
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Affiliation(s)
- Piotr Walczak
- 1 Division of MR Research, The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,2 Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,3 Department of Radiology, Faculty of Medical Sciences, University of Warmia and Mazury, Olsztyn, Poland
| | - Joanna Wojtkiewicz
- 4 Department of Pathophysiology, Faculty of Medical Sciences, University of Warmia and Mazury, Olsztyn, Poland
| | - Adam Nowakowski
- 5 NeuroRepair Dept, Mossakowski Medical Research Centre, Polish Academy of Sciences, Warsaw, Poland
| | - Aleksandra Habich
- 4 Department of Pathophysiology, Faculty of Medical Sciences, University of Warmia and Mazury, Olsztyn, Poland
| | - Piotr Holak
- 6 Department of Surgery and Radiology, Faculty of Veterinary Medicine, University of Warmia and Mazury, Olsztyn, Poland
| | - Jiadi Xu
- 7 F.M. Kirby Research Centre, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Zbigniew Adamiak
- 6 Department of Surgery and Radiology, Faculty of Veterinary Medicine, University of Warmia and Mazury, Olsztyn, Poland
| | - Moussa Chehade
- 1 Division of MR Research, The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Monica S Pearl
- 8 Division of Interventional Neuroradiology, The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Philippe Gailloud
- 8 Division of Interventional Neuroradiology, The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Barbara Lukomska
- 5 NeuroRepair Dept, Mossakowski Medical Research Centre, Polish Academy of Sciences, Warsaw, Poland
| | - Wojciech Maksymowicz
- 9 Department of Neurology and Neurosurgery, Faculty of Medical Sciences, University of Warmia and Mazury, Olsztyn, Poland
| | - Jeff Wm Bulte
- 1 Division of MR Research, The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,2 Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,10 Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,11 Department of Chemical & Biomolecular Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,12 Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Miroslaw Janowski
- 1 Division of MR Research, The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,2 Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,5 NeuroRepair Dept, Mossakowski Medical Research Centre, Polish Academy of Sciences, Warsaw, Poland.,13 Department of Neurosurgery, Mossakowski Medical Research Centre, Polish Academy of Sciences, Warsaw, Poland
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16
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17
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Correction of T1 Effects in Calculation of Relative Recirculation in Ischemic Stroke Patients. J Med Biol Eng 2016. [DOI: 10.1007/s40846-016-0167-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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18
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Vincent N, Stier N, Yu S, Liebeskind DS, Wang DJ, Scalzo F. Detection of Hyperperfusion on Arterial Spin Labeling using Deep Learning. PROCEEDINGS. IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE 2015; 2015:1322-1327. [PMID: 28936367 PMCID: PMC5604473 DOI: 10.1109/bibm.2015.7359870] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Hyperperfusion detected on arterial spin labeling (ASL) images acquired after acute stroke onset has been shown to correlate with development of subsequent intracerebral hemorrhage. We present in this study a quantitative hyperperfusion detection model that can provide an objective decision support for the interpretation of ASL cerebral blood flow (CBF) maps and rapidly delineate hyperperfusion regions. The detection problem is solved using Deep Learning such that the model relates ASL image patches to the corresponding label (normal or hyperperfused). Our method takes into account the regional intensity values of contralateral hemisphere during the labeling of a pixel. Each input vector is associated to a label corresponding to the presence of hyperperfusion that was manually established by a clinical researcher in Neurology. When compared to the manually established hyperperfusion, the predicted maps reached an accuracy of 97.45 ± 2.49% after crossvalidation. Pattern recognition based on deep learning can provide an accurate and objective measure of hyperperfusion on ASL CBF images and could therefore improve the detection of hemorrhagic transformation in acute stroke patients.
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Affiliation(s)
- Nicholas Vincent
- Neurovascular Imaging Research Core, Department of Neurology, University of California, Los Angeles (UCLA)
| | - Noah Stier
- Neurovascular Imaging Research Core, Department of Neurology, University of California, Los Angeles (UCLA)
| | - Songlin Yu
- Neurovascular Imaging Research Core, Department of Neurology, University of California, Los Angeles (UCLA)
| | - David S Liebeskind
- Neurovascular Imaging Research Core, Department of Neurology, University of California, Los Angeles (UCLA)
| | - Danny Jj Wang
- Neurovascular Imaging Research Core, Department of Neurology, University of California, Los Angeles (UCLA)
| | - Fabien Scalzo
- Neurovascular Imaging Research Core, Department of Neurology, University of California, Los Angeles (UCLA)
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19
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Heye AK, Thrippleton MJ, Armitage PA, Valdés Hernández MDC, Makin SD, Glatz A, Sakka E, Wardlaw JM. Tracer kinetic modelling for DCE-MRI quantification of subtle blood-brain barrier permeability. Neuroimage 2015; 125:446-455. [PMID: 26477653 PMCID: PMC4692516 DOI: 10.1016/j.neuroimage.2015.10.018] [Citation(s) in RCA: 127] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2015] [Revised: 09/17/2015] [Accepted: 10/07/2015] [Indexed: 01/07/2023] Open
Abstract
There is evidence that subtle breakdown of the blood–brain barrier (BBB) is a pathophysiological component of several diseases, including cerebral small vessel disease and some dementias. Dynamic contrast-enhanced MRI (DCE-MRI) combined with tracer kinetic modelling is widely used for assessing permeability and perfusion in brain tumours and body tissues where contrast agents readily accumulate in the extracellular space. However, in diseases where leakage is subtle, the optimal approach for measuring BBB integrity is likely to differ since the magnitude and rate of enhancement caused by leakage are extremely low; several methods have been reported in the literature, yielding a wide range of parameters even in healthy subjects. We hypothesised that the Patlak model is a suitable approach for measuring low-level BBB permeability with low temporal resolution and high spatial resolution and brain coverage, and that normal levels of scanner instability would influence permeability measurements. DCE-MRI was performed in a cohort of mild stroke patients (n = 201) with a range of cerebral small vessel disease severity. We fitted these data to a set of nested tracer kinetic models, ranking their performance according to the Akaike information criterion. To assess the influence of scanner drift, we scanned 15 healthy volunteers that underwent a “sham” DCE-MRI procedure without administration of contrast agent. Numerical simulations were performed to investigate model validity and the effect of scanner drift. The Patlak model was found to be most appropriate for fitting low-permeability data, and the simulations showed vp and KTrans estimates to be reasonably robust to the model assumptions. However, signal drift (measured at approximately 0.1% per minute and comparable to literature reports in other settings) led to systematic errors in calculated tracer kinetic parameters, particularly at low permeabilities. Our findings justify the growing use of the Patlak model in low-permeability states, which has the potential to provide valuable information regarding BBB integrity in a range of diseases. However, absolute values of the resulting tracer kinetic parameters should be interpreted with extreme caution, and the size and influence of signal drift should be measured where possible. We performed DCE-MRI in 201 patients with a range of small vessel disease severity. We tested tracer kinetic model performance via simulations and statistical analysis. The Patlak model was optimal for assessing leakage in normal tissues and lesions. Scanner drift leads to substantial errors in measured tracer kinetic parameters. DCE-MRI measurements of subtle leakage should be interpreted with caution.
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Affiliation(s)
- Anna K Heye
- Neuroimaging Sciences, University of Edinburgh, Chancellors Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK.
| | - Michael J Thrippleton
- Neuroimaging Sciences, University of Edinburgh, Chancellors Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK.
| | - Paul A Armitage
- Neuroimaging Sciences, University of Edinburgh, Chancellors Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; Department of Cardiovascular Science, University of Sheffield, Medical School, Beech Hill Road, Sheffield S10 2RX UK.
| | - Maria Del C Valdés Hernández
- Neuroimaging Sciences, University of Edinburgh, Chancellors Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK.
| | - Stephen D Makin
- Neuroimaging Sciences, University of Edinburgh, Chancellors Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK.
| | - Andreas Glatz
- Neuroimaging Sciences, University of Edinburgh, Chancellors Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK.
| | - Eleni Sakka
- Neuroimaging Sciences, University of Edinburgh, Chancellors Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK.
| | - Joanna M Wardlaw
- Neuroimaging Sciences, University of Edinburgh, Chancellors Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK.
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20
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Choi HS, Ahn SS, Shin NY, Kim J, Kim JH, Lee JE, Lee HY, Heo JH, Lee SK. Permeability Parameters Measured with Dynamic Contrast-Enhanced MRI: Correlation with the Extravasation of Evans Blue in a Rat Model of Transient Cerebral Ischemia. Korean J Radiol 2015; 16:791-7. [PMID: 26175578 PMCID: PMC4499543 DOI: 10.3348/kjr.2015.16.4.791] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2014] [Accepted: 03/16/2015] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE The purpose of this study was to correlate permeability parameters measured with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) using a clinical 3-tesla scanner with extravasation of Evans blue in a rat model with transient cerebral ischemia. MATERIALS AND METHODS Sprague-Dawley rats (n = 13) with transient middle cerebral artery occlusion were imaged using a 3-tesla MRI with an 8-channel wrist coil. DCE-MRI was performed 12 hours, 18 hours, and 36 hours after reperfusion. Permeability parameters (K(trans), ve, and vp) from DCE-MRI were calculated. Evans blue was injected after DCE-MRI and extravasation of Evans blue was correlated as a reference with the integrity of the blood-brain barrier. Correlation analysis was performed between permeability parameters and the extravasation of Evans blue. RESULTS All permeability parameters (K(trans), ve, and vp) showed a linear correlation with extravasation of Evans blue. Among them, K(trans) showed highest values of both the correlation coefficient and the coefficient of determination (0.687 and 0.473 respectively, p < 0.001). CONCLUSION Permeability parameters obtained by DCE-MRI at 3-T are well-correlated with Evans blue extravasation, and K(trans) shows the strongest correlation among the tested parameters.
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Affiliation(s)
- Hyun Seok Choi
- Department of Radiology, College of Medicine, The Catholic University of Korea, Seoul 137-701, Korea
| | - Sung Soo Ahn
- Department of Radiology, College of Medicine, Yonsei University, Seoul 120-752, Korea
| | - Na-Young Shin
- Department of Radiology, College of Medicine, Yonsei University, Seoul 120-752, Korea
| | - Jinna Kim
- Department of Radiology, College of Medicine, Yonsei University, Seoul 120-752, Korea
| | - Jae Hyung Kim
- Department of Radiology, College of Medicine, Seoul National University, Seoul 110-744, Korea
| | - Jong Eun Lee
- Department of Anatomy, College of Medicine, Yonsei University, Seoul 120-752, Korea
| | - Hye Yeon Lee
- Department of Radiology, College of Medicine, The Catholic University of Korea, Seoul 137-701, Korea
| | - Ji Hoe Heo
- Department of Neurology, College of Medicine, Yonsei University, Seoul 120-752, Korea
| | - Seung-Koo Lee
- Department of Radiology, College of Medicine, Yonsei University, Seoul 120-752, Korea
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21
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Ibatullin MM, Kalinin MN, Curado AT, Khasanova DR. [Neurovisualisation predictors of malignant cerebral infarction and hemorrhagic transformation]. Zh Nevrol Psikhiatr Im S S Korsakova 2015; 115:3-11. [PMID: 26120991 DOI: 10.17116/jnevro2015115323-11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Neuroimaging plays a central role in the assessment of patients with acute ischemic stroke. Within a few minutes, modern multimodal imaging protocols can provide one with comprehensive information about prognosis, management, and outcome of the disease, and may detect changes in the intracranial structures reflecting severity of the ischemic injury depicted by four Ps: parenchyma (of the brain), pipes (i.e., the cerebral blood vessels), penumbra, and permeability (of the blood brain barrier). In this article, we have reviewed neuroradiological predictors of malignant middle cerebral artery infarction and hemorrhagic transformation in light of the aforementioned four Ps.
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Affiliation(s)
| | | | - A T Curado
- Interregional Clinical Diagnostic Center, Kazan
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22
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Horsch AD, Dankbaar JW, van Seeters T, Niesten JM, Luitse MJA, Vos PC, van der Schaaf IC, Biessels GJ, van der Graaf Y, Kappelle LJ, Mali WPTM, Velthuis BK. Relation between stroke severity, patient characteristics and CT-perfusion derived blood-brain barrier permeability measurements in acute ischemic stroke. Clin Neuroradiol 2015; 26:415-421. [PMID: 25722019 PMCID: PMC5131081 DOI: 10.1007/s00062-015-0375-1] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2014] [Accepted: 01/22/2015] [Indexed: 11/28/2022]
Abstract
Purpose Increased blood-brain barrier permeability (BBBP) can result from ischemia. In this study the relation between stroke severity, patient characteristics and admission BBBP values measured with CT-perfusion (CTP) was investigated in acute ischemic stroke patients. Methods From prospective data of the Dutch Acute Stroke Study 149 patients with a middle cerebral artery stroke and extended CTP were selected. BBBP values were measured in the penumbra and infarct core as defined by CTP thresholds, and in the contra-lateral hemisphere. The relation between stroke (severity) variables and patient characteristics, including early CT signs, dense vessel sign (DVS), time to scan and National Institute of Health Stroke Score (NIHSS), and BBBP parameters in penumbra and infarct core was quantified with regression analysis. Results Early CT signs were related to higher BBBP values in the infarct core (B = 0.710), higher ipsi- to contra-lateral BBBP ratios (B = 0.326) and higher extraction ratios in the infarct core (B = 16.938). Females were found to have lower BBBP values in penumbra and infarct core (B = − 0.446 and − 0.776 respectively) and lower extraction ratios in the infarct core (B = − 10.463). If a DVS was present the ipsi- to contra-lateral BBBP ratios were lower (B = − 0.304). There was no relation between NIHSS or time to scan and BBBP values. Conclusion Early CT signs are related to higher BBBP values in the infarct core, suggesting that only severe ischemic damage alters BBBP within the first hours after symptom onset.
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Affiliation(s)
- Alexander D Horsch
- Department of Radiology, University Medical Center Utrecht, Heidelberglaan 100, HP E01.132, 3584, Utrecht, CX, The Netherlands.
- Department of Radiology, Rijnstate Hospital, Arnhem, The Netherlands.
| | - Jan Willem Dankbaar
- Department of Radiology, University Medical Center Utrecht, Heidelberglaan 100, HP E01.132, 3584, Utrecht, CX, The Netherlands
| | - Tom van Seeters
- Department of Radiology, University Medical Center Utrecht, Heidelberglaan 100, HP E01.132, 3584, Utrecht, CX, The Netherlands
| | - Joris M Niesten
- Department of Radiology, University Medical Center Utrecht, Heidelberglaan 100, HP E01.132, 3584, Utrecht, CX, The Netherlands
| | - Merel J A Luitse
- Department of Neurology, Utrecht Stroke Center, University Medical Center, Utrecht, The Netherlands
| | - Pieter C Vos
- Department of Radiology, University Medical Center Utrecht, Heidelberglaan 100, HP E01.132, 3584, Utrecht, CX, The Netherlands
| | - Irene C van der Schaaf
- Department of Radiology, University Medical Center Utrecht, Heidelberglaan 100, HP E01.132, 3584, Utrecht, CX, The Netherlands
| | - Geert-Jan Biessels
- Department of Neurology, Utrecht Stroke Center, University Medical Center, Utrecht, The Netherlands
| | | | - L Jaap Kappelle
- Department of Neurology, Utrecht Stroke Center, University Medical Center, Utrecht, The Netherlands
| | - Willem P Th M Mali
- Department of Radiology, University Medical Center Utrecht, Heidelberglaan 100, HP E01.132, 3584, Utrecht, CX, The Netherlands
| | - Birgitta K Velthuis
- Department of Radiology, University Medical Center Utrecht, Heidelberglaan 100, HP E01.132, 3584, Utrecht, CX, The Netherlands
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Heye AK, Culling RD, Valdés Hernández MDC, Thrippleton MJ, Wardlaw JM. Assessment of blood-brain barrier disruption using dynamic contrast-enhanced MRI. A systematic review. NEUROIMAGE-CLINICAL 2014; 6:262-74. [PMID: 25379439 PMCID: PMC4215461 DOI: 10.1016/j.nicl.2014.09.002] [Citation(s) in RCA: 282] [Impact Index Per Article: 25.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/18/2014] [Revised: 09/04/2014] [Accepted: 09/05/2014] [Indexed: 01/31/2023]
Abstract
There is increasing recognition of the importance of blood-brain barrier (BBB) disruption in aging, dementia, stroke and multiple sclerosis in addition to more commonly-studied pathologies such as tumors. Dynamic contrast-enhanced MRI (DCE-MRI) is a method for studying BBB disruption in vivo. We review pathologies studied, scanning protocols and data analysis procedures to determine the range of available methods and their suitability to different pathologies. We systematically review the existing literature up to February 2014, seeking studies that assessed BBB integrity using T1-weighted DCE-MRI techniques in animals and humans in normal or abnormal brain tissues. The literature search provided 70 studies that were eligible for inclusion, involving 417 animals and 1564 human subjects in total. The pathologies most studied are intracranial neoplasms and acute ischemic strokes. There are large variations in the type of DCE-MRI sequence, the imaging protocols and the contrast agents used. Moreover, studies use a variety of different methods for data analysis, mainly based on model-free measurements and on the Patlak and Tofts models. Consequently, estimated K (Trans) values varied widely. In conclusion, DCE-MRI is shown to provide valuable information in a large variety of applications, ranging from common applications, such as grading of primary brain tumors, to more recent applications, such as assessment of subtle BBB dysfunction in Alzheimer's disease. Further research is required in order to establish consensus-based recommendations for data acquisition and analysis and, hence, improve inter-study comparability and promote wider use of DCE-MRI.
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Affiliation(s)
- Anna K Heye
- Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Ross D Culling
- College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK
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24
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Leigh R, Jen SS, Hillis AE, Krakauer JW, Barker PB. Pretreatment blood-brain barrier damage and post-treatment intracranial hemorrhage in patients receiving intravenous tissue-type plasminogen activator. Stroke 2014; 45:2030-5. [PMID: 24876245 DOI: 10.1161/strokeaha.114.005249] [Citation(s) in RCA: 65] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE Early blood-brain barrier damage after acute ischemic stroke has previously been qualitatively linked to subsequent intracranial hemorrhage (ICH). In this quantitative study, it was investigated whether the amount of blood-brain barrier damage evident on pre-tissue-type plasminogen activator MRI scans was related to the degree of post-tissue-type plasminogen activator ICH in patients with acute ischemic stroke. METHODS Analysis was performed on a database of patients with acute ischemic stroke provided by the Stroke Imaging Repository (STIR) and Virtual International Stroke Trials Archive (VISTA) Imaging Investigators. Patients with perfusion-weighted imaging lesions>10 mL and negative gradient-recalled echo imaging before intravenous tissue-type plasminogen activator were included. Postprocessing of the perfusion-weighted imaging source images was performed to estimate changes in blood-brain barrier permeability within the perfusion deficit relative to the unaffected hemisphere. Follow-up gradient-recalled echo images were reviewed for evidence of ICH and divided into 3 groups according to European Cooperative Acute Stroke Study (ECASS) criteria: no hemorrhage, hemorrhagic infarction, and parenchymal hematoma. RESULTS Seventy-five patients from the database met the inclusion criteria, 28 of whom experienced ICH, of which 19 were classified as hemorrhagic infarction and 9 were classified as parenchymal hematoma. The mean permeability (±SDs), expressed as an index of contrast leakage, was 17.0±8.8% in the no hemorrhage group, 19.4±4.0% in the hemorrhagic infarction group, and 24.6±4.5% in the parenchymal hematoma group. Permeability was significantly correlated with ICH grade in univariate (P=0.007) and multivariate (P=0.008) linear regression modeling. CONCLUSIONS A perfusion-weighted imaging-derived index of blood-brain barrier damage measured before intravenous tissue-type plasminogen activator is given is associated with the severity of ICH after treatment in patients with acute ischemic stroke.
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Affiliation(s)
- Richard Leigh
- From the Departments of Neurology and Radiology (R.L.), Neurology, Physical Medicine and Rehabilitation and Cognitive Science (A.E.H.), Neurology and Neuroscience (J.W.K.), and Radiology (P.B.B.), Johns Hopkins University, Baltimore, MD; and Department of Radiology, Emory University, Atlanta, GA (S.S.J.).
| | - Shyian S Jen
- From the Departments of Neurology and Radiology (R.L.), Neurology, Physical Medicine and Rehabilitation and Cognitive Science (A.E.H.), Neurology and Neuroscience (J.W.K.), and Radiology (P.B.B.), Johns Hopkins University, Baltimore, MD; and Department of Radiology, Emory University, Atlanta, GA (S.S.J.)
| | - Argye E Hillis
- From the Departments of Neurology and Radiology (R.L.), Neurology, Physical Medicine and Rehabilitation and Cognitive Science (A.E.H.), Neurology and Neuroscience (J.W.K.), and Radiology (P.B.B.), Johns Hopkins University, Baltimore, MD; and Department of Radiology, Emory University, Atlanta, GA (S.S.J.)
| | - John W Krakauer
- From the Departments of Neurology and Radiology (R.L.), Neurology, Physical Medicine and Rehabilitation and Cognitive Science (A.E.H.), Neurology and Neuroscience (J.W.K.), and Radiology (P.B.B.), Johns Hopkins University, Baltimore, MD; and Department of Radiology, Emory University, Atlanta, GA (S.S.J.)
| | - Peter B Barker
- From the Departments of Neurology and Radiology (R.L.), Neurology, Physical Medicine and Rehabilitation and Cognitive Science (A.E.H.), Neurology and Neuroscience (J.W.K.), and Radiology (P.B.B.), Johns Hopkins University, Baltimore, MD; and Department of Radiology, Emory University, Atlanta, GA (S.S.J.)
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25
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Liu HS, Chung HW, Chou MC, Liou M, Wang CY, Kao HW, Chiang SW, Juan CJ, Huang GS, Chen CY. Effects of microvascular permeability changes on contrast-enhanced T1 and pharmacokinetic MR imagings after ischemia. Stroke 2013; 44:1872-7. [PMID: 23743977 DOI: 10.1161/strokeaha.113.001558] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND AND PURPOSE Brain enhancement on contrast-enhanced T1-weighted imaging (CET1-WI) after ischemic stroke is generally accepted as an indicator of the blood-brain barrier disruption. However, this phenomenon usually starts to become visible at the subacute phase. The purpose of this study was to evaluate the time-course profiles of K(trans), cerebral blood volume (vp), and CET1-WI with early detection of blood-brain barrier changes on K(trans) maps and their role for prediction of subsequent hemorrhagic transformation in acute middle cerebral arterial infarct. METHODS Twenty-six patients with acute middle cerebral arterial stroke and early spontaneous reperfusion, whose MR images were obtained at predetermined stroke stages, were included. T2*-based MR perfusion-weighted images were acquired using the first-pass pharmacokinetic model to derive K(trans) and vp. Parenchymal enhancement observed on maps of K(trans), vp, and CET1-WI at each stage was compared. Association among these measurements and hemorrhagic transformation was analyzed. RESULTS K(trans) map showed significantly higher parenchymal enhancement in ischemic parenchyma as compared with that of vp map and CET1-WI at early stroke stages (P<0.05). The increased K(trans) at acute stage was not associated with parenchymal enhancement in CET1-WI at the same stage. Parenchymal enhancement in CET1-WI started to occur at the late subacute stage and tended to be luxury reperfusion-dependent. Patients with hemorrhagic transformation showed higher mean K(trans) values as compared with patients without hemorrhagic transformation (P=0.02). CONCLUSIONS Postischemic brain enhancement on routine CET1-WI seems to be closely related to the luxury reperfusion at the late subacute stage and is not dependent on microvascular permeability changes at the acute stage.
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Affiliation(s)
- Hua-Shan Liu
- Department of Radiology, Tri-Service General Hospital, Taipei, Taiwan
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26
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Jain AR, Jain M, Kanthala AR, Damania D, Stead LG, Wang HZ, Jahromi BS. Association of CT perfusion parameters with hemorrhagic transformation in acute ischemic stroke. AJNR Am J Neuroradiol 2013; 34:1895-900. [PMID: 23598828 DOI: 10.3174/ajnr.a3502] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Prediction of hemorrhagic transformation in acute ischemic stroke could help determine treatment and prognostication. With increasing numbers of patients with acute ischemic stroke undergoing multimodal CT imaging, we examined whether CT perfusion could predict hemorrhagic transformation in acute ischemic stroke. MATERIALS AND METHODS Patients with acute ischemic stroke who underwent CTP scanning within 12 hours of symptom onset were examined. Patients with and without hemorrhagic transformation were defined as cases and controls, respectively, and were matched as to IV rtPA administration and presentation NIHSS score (± 2). Relative mean transit time, relative CBF, and relative CBV values were calculated from CTP maps and normalized to the contralateral side. Receiver operating characteristic analysis curves were created, and threshold values for significant CTP parameters were obtained to predict hemorrhagic transformation. RESULTS Of 83 patients with acute ischemic stroke, 16 developed hemorrhagic transformation (19.28%). By matching, 38 controls were found for only 14 patients with hemorrhagic transformation. Among the matched patients with hemorrhagic transformation, 13 developed hemorrhagic infarction (6 hemorrhagic infarction 1 and 7 hemorrhagic infarction 2) and 1 developed parenchymal hematoma 2. There was no significant difference between cases and controls with respect to age, sex, time to presentation from symptom onset, and comorbidities. Cases had significantly lower median rCBV (8% lower) compared with controls (11% higher) (P = .009; odds ratio, 1.14 for a 0.1-U decrease in rCBV). There was no difference in median total volume of ischemia, rMTT, and rCBF among cases and controls. The area under the receiver operating characteristic was computed to be 0.83 (standard error, 0.08), with a cutoff point for rCBV of 1.09. CONCLUSIONS Of the examined CTP parameters, only lower rCBV was found to be significantly associated with a relatively higher chance of hemorrhagic transformation.
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Scalzo F, Alger JR, Hu X, Saver JL, Dani KA, Muir KW, Demchuk AM, Coutts SB, Luby M, Warach S, Liebeskind DS. Multi-center prediction of hemorrhagic transformation in acute ischemic stroke using permeability imaging features. Magn Reson Imaging 2013; 31:961-9. [PMID: 23587928 DOI: 10.1016/j.mri.2013.03.013] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2012] [Revised: 02/01/2013] [Accepted: 03/09/2013] [Indexed: 10/27/2022]
Abstract
Permeability images derived from magnetic resonance (MR) perfusion images are sensitive to blood-brain barrier derangement of the brain tissue and have been shown to correlate with subsequent development of hemorrhagic transformation (HT) in acute ischemic stroke. This paper presents a multi-center retrospective study that evaluates the predictive power in terms of HT of six permeability MRI measures including contrast slope (CS), final contrast (FC), maximum peak bolus concentration (MPB), peak bolus area (PB), relative recirculation (rR), and percentage recovery (%R). Dynamic T2*-weighted perfusion MR images were collected from 263 acute ischemic stroke patients from four medical centers. An essential aspect of this study is to exploit a classifier-based framework to automatically identify predictive patterns in the overall intensity distribution of the permeability maps. The model is based on normalized intensity histograms that are used as input features to the predictive model. Linear and nonlinear predictive models are evaluated using a cross-validation to measure generalization power on new patients and a comparative analysis is provided for the different types of parameters. Results demonstrate that perfusion imaging in acute ischemic stroke can predict HT with an average accuracy of more than 85% using a predictive model based on a nonlinear regression model. Results also indicate that the permeability feature based on the percentage of recovery performs significantly better than the other features. This novel model may be used to refine treatment decisions in acute stroke.
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Affiliation(s)
- Fabien Scalzo
- Department of Neurology, University of California, LA, USA.
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28
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Weiser RE, Sheth KN. Clinical Predictors and Management of Hemorrhagic Transformation. Curr Treat Options Neurol 2013; 15:125-49. [DOI: 10.1007/s11940-012-0217-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
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29
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El-Koussy M, Schenk P, Kiefer C, Osman OM, Mordasini P, Ozdoba C, Schroth G, Gönner F. Susceptibility-weighted imaging of the brain: does gadolinium administration matter? Eur J Radiol 2011; 81:272-6. [PMID: 21216124 DOI: 10.1016/j.ejrad.2010.12.021] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2010] [Revised: 11/23/2010] [Accepted: 12/02/2010] [Indexed: 11/15/2022]
Abstract
OBJECTIVE Susceptibility-weighted MR imaging (SWI) is usually obtained without administration of intravenous gadolinium (Gd). However, it is occasionally necessary to perform SWI after Gd is injected. The effects of Gd on SWI have not been systematically examined. The aim of this prospective study was to investigate whether performing SWI after Gd would influence the diagnostic image quality, parenchymal signal and vascular enhancement. An additional aim is to suggest potential future applications for Gd-enhanced SWI. METHODS SWI was performed in 31 subjects before and after Gd administration. 17 cases were examined in a 1.5T scanner and the remaining 14 were scanned at 3T. The pre- and post-Gd images were analysed for signal changes in the cerebral grey matter (GM), white matter (WM) as well as for enhancement in the superficial and deep venous system. The visibility of the veins was graded on subtraction maps. RESULTS The Gd-enhanced images showed no image quality degradation and no significant signal intensity change in the GM and WM as compared to the pre-Gd images (p>0.05). After Gd-administration significant enhancement of the venous sinuses was noticed (p<0.005), while the deep and cortical veins were poorly enhanced as confirmed by the calculated subtraction maps. The results showed no significant difference at variable MRI field strengths. CONCLUSION It is possible to perform SWI after Gd injection without information loss or signal change in the parenchyma. The most significant difference is the enhancement of the cerebral venous sinuses. Potential future applications are discussed.
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Affiliation(s)
- Marwan El-Koussy
- Institute of Diagnostic and Interventional Neuroradiology, University Bern, Inselspital, Freiburgstrasse 4, 3010 Bern, Switzerland.
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