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Lee S, Lim JS, Cheong EN, Lee Y, Kim JW, Kim YE, Jo S, Kim HJ, Shim WH, Lee JH. Relationship between disproportionately enlarged subarachnoid-space hydrocephalus and white matter tract integrity in normal pressure hydrocephalus. Sci Rep 2023; 13:21328. [PMID: 38044360 PMCID: PMC10694135 DOI: 10.1038/s41598-023-48940-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Accepted: 12/01/2023] [Indexed: 12/05/2023] Open
Abstract
Normal pressure hydrocephalus (NPH) patients had altered white matter tract integrities on diffusion tensor imaging (DTI). Previous studies suggested disproportionately enlarged subarachnoid space hydrocephalus (DESH) as a prognostic sign of NPH. We examined DTI indices in NPH subgroups by DESH severity and clinical symptoms. This retrospective case-control study included 33 NPH patients and 33 age-, sex-, and education-matched controls. The NPH grading scales (0-12) were used to rate neurological symptoms. Patients with NPH were categorized into two subgroups, high-DESH and low-DESH groups, by the average value of the DESH scale. DTI indices, including fractional anisotropy, were compared across 14 regions of interest (ROIs). The high-DESH group had increased axial diffusivity in the lateral side of corona radiata (1.43 ± 0.25 vs. 1.72 ± 0.25, p = 0.04), and showed decreased fractional anisotropy and increased mean, and radial diffusivity in the anterior and lateral sides of corona radiata and the periventricular white matter surrounding the anterior horn of lateral ventricle. In patients with a high NPH grading scale, fractional anisotropy in the white matter surrounding the anterior horn of the lateral ventricle was significantly reduced (0.36 ± 0.08 vs. 0.26 ± 0.06, p = 0.03). These data show that DESH may be a biomarker for DTI-detected microstructural alterations and clinical symptom severity.
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Affiliation(s)
- Sunju Lee
- Department of Neurology, Seosan Jungang General Hospital, Seosan-si, Chungcheongnam-do, Republic of Korea
| | - Jae-Sung Lim
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Sonpa-gu, Seoul, 05505, Republic of Korea
| | - E-Nae Cheong
- Department of Medical Science and Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Yoojin Lee
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Sonpa-gu, Seoul, 05505, Republic of Korea
| | - Jae Woo Kim
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Sonpa-gu, Seoul, 05505, Republic of Korea
| | - Ye Eun Kim
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Sonpa-gu, Seoul, 05505, Republic of Korea
| | - Sungyang Jo
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Sonpa-gu, Seoul, 05505, Republic of Korea
| | - Hyung-Ji Kim
- Department of Neurology, Uijeongbu Eulji Medical Center, Eulji University School of Medicine, Uijeongbu, Republic of Korea
| | - Woo Hyun Shim
- Department of Medical Science and Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
- Department of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Jae-Hong Lee
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Sonpa-gu, Seoul, 05505, Republic of Korea.
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Yun SY, Choi KS, Suh CH, Kim SC, Heo H, Shim WH, Jo S, Chung SJ, Lim JS, Lee JH, Kim D, Kim SO, Jung W, Kim HS, Kim SJ, Kim JH. Risk estimation for idiopathic normal-pressure hydrocephalus: development and validation of a brain morphometry-based nomogram. Eur Radiol 2023; 33:6145-6156. [PMID: 37059905 DOI: 10.1007/s00330-023-09612-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 02/10/2023] [Accepted: 03/09/2023] [Indexed: 04/16/2023]
Abstract
OBJECTIVES To develop and validate a nomogram based on MRI features for predicting iNPH. METHODS Patients aged ≥ 60 years (clinically diagnosed with iNPH, Parkinson's disease, or Alzheimer's disease or healthy controls) who underwent MRI including three-dimensional T1-weighted volumetric MRI were retrospectively identified from two tertiary referral hospitals (one hospital for derivation set and the other for validation set). Clinical and imaging features for iNPH were assessed. Deep learning-based brain segmentation software was used for 3D volumetry. A prediction model was developed using logistic regression and transformed into a nomogram. The performance of the nomogram was assessed with respect to discrimination and calibration abilities. The nomogram was internally and externally validated. RESULTS A total of 452 patients (mean age ± SD, 73.2 ± 6.5 years; 200 men) were evaluated as the derivation set. One hundred eleven and 341 patients were categorized into the iNPH and non-iNPH groups, respectively. In multivariable analysis, high-convexity tightness (odds ratio [OR], 35.1; 95% CI: 4.5, 275.5), callosal angle < 90° (OR, 12.5; 95% CI: 3.1, 50.0), and normalized lateral ventricle volume (OR, 4.2; 95% CI: 2.7, 6.7) were associated with iNPH. The nomogram combining these three variables showed an area under the curve of 0.995 (95% CI: 0.991, 0.999) in the study sample, 0.994 (95% CI: 0.990, 0.998) in the internal validation sample, and 0.969 (95% CI: 0.940, 0.997) in the external validation sample. CONCLUSION A brain morphometry-based nomogram including high-convexity tightness, callosal angle < 90°, and normalized lateral ventricle volume can help accurately estimate the probability of iNPH. KEY POINTS • The nomogram with MRI findings (high-convexity tightness, callosal angle, and normalized lateral ventricle volume) helped in predicting the probability of idiopathic normal-pressure hydrocephalus. • The nomogram may facilitate the prediction of idiopathic normal-pressure hydrocephalus and consequently avoid unnecessary invasive procedures such as the cerebrospinal fluid tap test, drainage test, and cerebrospinal fluid shunt surgery.
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Affiliation(s)
- Su Young Yun
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
- Department of Radiology, Busan Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea
| | - Kyu Sung Choi
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Chong Hyun Suh
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
| | - Soo Chin Kim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Hwon Heo
- Department of Convergence Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Woo Hyun Shim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Sungyang Jo
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Sun Ju Chung
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Jae-Sung Lim
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Jae-Hong Lee
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Donghyun Kim
- Department of Radiology, Busan Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea
| | - Seon-Ok Kim
- Department of Clinical Epidemiology and Biostatistics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | | | - Ho Sung Kim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Sang Joon Kim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Ji-Hoon Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
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Thavarajasingam SG, El-Khatib M, Vemulapalli K, Iradukunda HAS, K. SV, Borchert R, Russo S, Eide PK. Radiological predictors of shunt response in the diagnosis and treatment of idiopathic normal pressure hydrocephalus: a systematic review and meta-analysis. Acta Neurochir (Wien) 2023; 165:369-419. [PMID: 36435931 PMCID: PMC9922237 DOI: 10.1007/s00701-022-05402-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 10/24/2022] [Indexed: 11/28/2022]
Abstract
BACKGROUND Patients with the dementia subtype idiopathic normal pressure hydrocephalus (iNPH) may improve clinically following cerebrospinal fluid (CSF) diversion (shunt) surgery, though the predictors of shunt response remain debated. Currently, radiological features play an important role in the diagnosis of iNPH, but it is not well established which radiological markers most precisely predict shunt responsive iNPH. OBJECTIVE To conduct a systematic review and meta-analysis to identify radiological predictors of shunt responsiveness, evaluate their diagnostic effectiveness, and recommend the most predictive radiological features. METHODS Embase, MEDLINE, Scopus, PubMed, Google Scholar, and JSTOR were searched for original studies investigating radiological predictors of shunt response in iNPH patients. Included studies were assessed using the ROBINS-1 tool, and eligible studies were evaluated using a univariate meta-analysis. RESULTS Overall, 301 full-text papers were screened, of which 28 studies were included, and 26 different radiological features were identified, 5 of these met the inclusion criteria for the meta-analysis: disproportionately enlarged subarachnoid space (DESH), callosal angle, periventricular white matter changes, cerebral blood flow (CBF), and computerized tomography cisternography. The meta-analysis showed that only callosal angle and periventricular white matter changes significantly differentiated iNPH shunt responders from non-responders, though both markers had a low diagnostic odds ratio (DOR) of 1.88 and 1.01 respectively. None of the other radiological markers differentiated shunt responsive from shunt non-responsive iNPH. CONCLUSION Callosal angle and periventricular changes are the only diagnostically effective radiological predictors of shunt responsive iNPH patients. However, due to the DORs approximating 1, they are insufficient as sole predictors and are advised to be used only in combination with other diagnostic tests of shunt response. Future research must evaluate the combined use of multiple radiological predictors, as it may yield beneficial additive effects that may allow for more robust radiological shunt response prediction.
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Affiliation(s)
| | | | | | | | | | - Robin Borchert
- Department of Clinical Neurosciences, Cambridge University Hospital NHS Trust, Cambridge, UK
| | - Salvatore Russo
- Department of Neurosurgery, Imperial College Healthcare NHS Trust, London, UK
| | - Per K. Eide
- Department of Neurosurgery, Oslo University Hospital – Rikshospitalet, Oslo, Norway ,Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
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Chen J, He W, Zhang X, Lv M, Zhou X, Yang X, Wei H, Ma H, Li H, Xia J. Value of MRI-based semi-quantitative structural neuroimaging in predicting the prognosis of patients with idiopathic normal pressure hydrocephalus after shunt surgery. Eur Radiol 2022; 32:7800-7810. [PMID: 35501572 PMCID: PMC9668801 DOI: 10.1007/s00330-022-08733-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Revised: 02/19/2022] [Accepted: 03/11/2022] [Indexed: 02/05/2023]
Abstract
OBJECTIVES To explore the value of structural neuroimaging in predicting the prognosis of shunt surgery for idiopathic normal-pressure hydrocephalus (iNPH) using two different standard semi-quantitative imaging scales. METHODS A total of 47 patients with iNPH who underwent shunt surgery at our hospital between 2018 and 2020 were included in this study. The modified Rankin Scale (mRS) and iNPH grading scale (iNPHGS) were used to evaluate and quantify the clinical symptoms before and after shunt surgery. The disproportionately enlarged subarachnoid space hydrocephalus (DESH) and iNPH Radscale scores were used to evaluate the preoperative MR images. The primary endpoint was improvement in the mRS score a year after surgery, and the secondary endpoint was the iNPHGS after 1 year. The preoperative imaging features of the improved and non-improved groups were compared. RESULTS The rates of the primary and secondary outcomes were 59.6% and 61.7%, respectively, 1 year after surgery. There were no significant differences in preoperative DESH score, iNPH Radscale, Evans' index (EI), or callosal angle (CA) between the improved and non-improved groups. Significant correlations were observed between the severity of gait disorder and EI and the CA. CONCLUSIONS The value of structural neuroimaging in predicting the prognosis of shunt surgery is limited, and screening for shunt surgery candidates should not rely only on preoperative imaging findings. KEY POINTS • Early shunt surgery can significantly improve the clinical symptoms and prognosis of patients with idiopathic normal-pressure hydrocephalus (iNPH). • Structural imaging findings have limited predictiveness for the prognosis of patients with iNPH after shunt surgery. • Patients should not be selected for shunt surgery based on only structural imaging findings.
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Affiliation(s)
- Jiakuan Chen
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Shenzhen University, Shenzhen Second People's Hospital, 3002 SunGang Road West, Shenzhen, 518035, Guangdong Province, China
- Guangzhou Medical University, Guangzhou, China
| | - Wenjie He
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Shenzhen University, Shenzhen Second People's Hospital, 3002 SunGang Road West, Shenzhen, 518035, Guangdong Province, China
| | - Xiejun Zhang
- Department of Neurosurgery, The First Affiliated Hospital of Shenzhen University, Shenzhen University, Shenzhen Second People's Hospital, 3002 SunGang Road West, Shenzhen, 518035, Guangdong Province, China
| | - Minrui Lv
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Shenzhen University, Shenzhen Second People's Hospital, 3002 SunGang Road West, Shenzhen, 518035, Guangdong Province, China
| | - Xi Zhou
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Shenzhen University, Shenzhen Second People's Hospital, 3002 SunGang Road West, Shenzhen, 518035, Guangdong Province, China
| | - Xiaolin Yang
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Shenzhen University, Shenzhen Second People's Hospital, 3002 SunGang Road West, Shenzhen, 518035, Guangdong Province, China
- Guangdong Medical University, Zhanjiang, China
| | - Haihua Wei
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Shenzhen University, Shenzhen Second People's Hospital, 3002 SunGang Road West, Shenzhen, 518035, Guangdong Province, China
- Guangdong Medical University, Zhanjiang, China
| | - Haiqin Ma
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Shenzhen University, Shenzhen Second People's Hospital, 3002 SunGang Road West, Shenzhen, 518035, Guangdong Province, China
- Shantou University Medical College, Shantou, China
| | - Hongbing Li
- Department of Radiology, Fuyong People's Hospital, Baoan District, Shenzhen, 518103, Guangdong Province, China.
| | - Jun Xia
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Shenzhen University, Shenzhen Second People's Hospital, 3002 SunGang Road West, Shenzhen, 518035, Guangdong Province, China.
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Carlsen JF, Munch TN, Hansen AE, Hasselbalch SG, Rykkje AM. Can preoperative brain imaging features predict shunt response in idiopathic normal pressure hydrocephalus? A PRISMA review. Neuroradiology. [DOI: 10.1007/s00234-022-03021-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 07/13/2022] [Indexed: 10/16/2022]
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Sohn G, Bae MJ, Park J, Kim SE. Semi-quantitative analysis of periventricular gray-white matter ratio on CT in patients with idiopathic normal pressure hydrocephalus. J Clin Neurosci 2022; 101:16-20. [DOI: 10.1016/j.jocn.2022.04.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 04/24/2022] [Accepted: 04/26/2022] [Indexed: 11/25/2022]
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Jeong SY, Suh CH, Park HY, Heo H, Shim WH, Kim SJ. [Brain MRI-Based Artificial Intelligence Software in Patients with Neurodegenerative Diseases: Current Status]. Taehan Yongsang Uihakhoe Chi 2022; 83:473-485. [PMID: 36238504 PMCID: PMC9514516 DOI: 10.3348/jksr.2022.0048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 05/05/2022] [Accepted: 05/15/2022] [Indexed: 11/28/2022]
Abstract
The incidence of neurodegenerative diseases in the older population has increased in recent years. A considerable number of studies have been performed to characterize these diseases. Imaging analysis is an important biomarker for the diagnosis of neurodegenerative disease. Objective and reliable assessment and precise detection are important for the early diagnosis of neurodegenerative diseases. Artificial intelligence (AI) using brain MRI applied to the study of neurodegenerative diseases could promote early diagnosis and optimal decisions for treatment plans. MRI-based AI software have been developed and studied worldwide. Representatively, there are MRI-based volumetry and segmentation software. In this review, we present the development process of brain volumetry analysis software in neurodegenerative diseases, currently used and developed AI software for neurodegenerative disease in the Republic of Korea, probable uses of AI in the future, and AI software limitations.
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