Retinal Vascular Morphology Reflects and Predicts Cerebral Small Vessel Disease: Evidences from Eye–Brain Imaging Analysis
Cerebral small vessel disease (SVD) involves ischemic white matter damage and choroid plexus (CP) dysfunction for cerebrospinal fluid (CSF) production. Given the vascular and CSF links between the eye and brain, this study explored whether retinal vascular morphology can indicate cerebrovascular inj...
Saved in:
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
American Association for the Advancement of Science (AAAS)
2025-01-01
|
| Series: | Research |
| Online Access: | https://spj.science.org/doi/10.34133/research.0633 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850254562622963712 |
|---|---|
| author | Ning Wu Mingze Xu Shuohua Chen Shouling Wu Jing Li Ying Hui Xiaoshuai Li Zhenchang Wang Han Lv |
| author_facet | Ning Wu Mingze Xu Shuohua Chen Shouling Wu Jing Li Ying Hui Xiaoshuai Li Zhenchang Wang Han Lv |
| author_sort | Ning Wu |
| collection | DOAJ |
| description | Cerebral small vessel disease (SVD) involves ischemic white matter damage and choroid plexus (CP) dysfunction for cerebrospinal fluid (CSF) production. Given the vascular and CSF links between the eye and brain, this study explored whether retinal vascular morphology can indicate cerebrovascular injury and CP dysfunction in SVD. We assessed SVD burden using imaging phenotypes like white matter hyperintensities (WMH), perivascular spaces, lacunes, and microbleeds. Cerebrovascular injury was quantified by WMH volume and peak width of skeletonized mean diffusivity (PSMD), while CP volume measured its dysfunction. Retinal vascular markers were derived from fundus images, with associations analyzed using generalized linear models and Pearson correlations. Path analysis quantified contributions of cerebrovascular injury and CP volume to retinal changes. Support vector machine models were developed to predict SVD severity using retinal and demographic data. Among 815 participants, 578 underwent ocular imaging. Increased SVD burden markedly correlated with both cerebral and retinal biomarkers, with retinal alterations equally influenced by cerebrovascular damage and CP enlargement. Machine learning models showed robust predictive power for severe SVD burden (AUC was 0.82), PSMD (0.81), WMH volume (0.77), and CP volume (0.80). These findings suggest that retinal imaging could serve as a cost-effective, noninvasive tool for SVD screening based on vascular and CSF connections. |
| format | Article |
| id | doaj-art-7c1f4eec812044c799ebf493acd719a9 |
| institution | OA Journals |
| issn | 2639-5274 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | American Association for the Advancement of Science (AAAS) |
| record_format | Article |
| series | Research |
| spelling | doaj-art-7c1f4eec812044c799ebf493acd719a92025-08-20T01:57:05ZengAmerican Association for the Advancement of Science (AAAS)Research2639-52742025-01-01810.34133/research.0633Retinal Vascular Morphology Reflects and Predicts Cerebral Small Vessel Disease: Evidences from Eye–Brain Imaging AnalysisNing Wu0Mingze Xu1Shuohua Chen2Shouling Wu3Jing Li4Ying Hui5Xiaoshuai Li6Zhenchang Wang7Han Lv8Department of Medical Imaging, Yanjing Medical College, Capital Medical University, Beijing, China.Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.Department of Cardiology, Kailuan General Hospital, Tangshan, China.Department of Cardiology, Kailuan General Hospital, Tangshan, China.Department of Radiology, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China.Department of Radiology, Kailuan General Hospital, Tangshan, China.Department of Radiology, Capital Medical University Affiliated Beijing Friendship Hospital, Beijing, China.Department of Radiology, Capital Medical University Affiliated Beijing Friendship Hospital, Beijing, China.Department of Radiology, Capital Medical University Affiliated Beijing Friendship Hospital, Beijing, China.Cerebral small vessel disease (SVD) involves ischemic white matter damage and choroid plexus (CP) dysfunction for cerebrospinal fluid (CSF) production. Given the vascular and CSF links between the eye and brain, this study explored whether retinal vascular morphology can indicate cerebrovascular injury and CP dysfunction in SVD. We assessed SVD burden using imaging phenotypes like white matter hyperintensities (WMH), perivascular spaces, lacunes, and microbleeds. Cerebrovascular injury was quantified by WMH volume and peak width of skeletonized mean diffusivity (PSMD), while CP volume measured its dysfunction. Retinal vascular markers were derived from fundus images, with associations analyzed using generalized linear models and Pearson correlations. Path analysis quantified contributions of cerebrovascular injury and CP volume to retinal changes. Support vector machine models were developed to predict SVD severity using retinal and demographic data. Among 815 participants, 578 underwent ocular imaging. Increased SVD burden markedly correlated with both cerebral and retinal biomarkers, with retinal alterations equally influenced by cerebrovascular damage and CP enlargement. Machine learning models showed robust predictive power for severe SVD burden (AUC was 0.82), PSMD (0.81), WMH volume (0.77), and CP volume (0.80). These findings suggest that retinal imaging could serve as a cost-effective, noninvasive tool for SVD screening based on vascular and CSF connections.https://spj.science.org/doi/10.34133/research.0633 |
| spellingShingle | Ning Wu Mingze Xu Shuohua Chen Shouling Wu Jing Li Ying Hui Xiaoshuai Li Zhenchang Wang Han Lv Retinal Vascular Morphology Reflects and Predicts Cerebral Small Vessel Disease: Evidences from Eye–Brain Imaging Analysis Research |
| title | Retinal Vascular Morphology Reflects and Predicts Cerebral Small Vessel Disease: Evidences from Eye–Brain Imaging Analysis |
| title_full | Retinal Vascular Morphology Reflects and Predicts Cerebral Small Vessel Disease: Evidences from Eye–Brain Imaging Analysis |
| title_fullStr | Retinal Vascular Morphology Reflects and Predicts Cerebral Small Vessel Disease: Evidences from Eye–Brain Imaging Analysis |
| title_full_unstemmed | Retinal Vascular Morphology Reflects and Predicts Cerebral Small Vessel Disease: Evidences from Eye–Brain Imaging Analysis |
| title_short | Retinal Vascular Morphology Reflects and Predicts Cerebral Small Vessel Disease: Evidences from Eye–Brain Imaging Analysis |
| title_sort | retinal vascular morphology reflects and predicts cerebral small vessel disease evidences from eye brain imaging analysis |
| url | https://spj.science.org/doi/10.34133/research.0633 |
| work_keys_str_mv | AT ningwu retinalvascularmorphologyreflectsandpredictscerebralsmallvesseldiseaseevidencesfromeyebrainimaginganalysis AT mingzexu retinalvascularmorphologyreflectsandpredictscerebralsmallvesseldiseaseevidencesfromeyebrainimaginganalysis AT shuohuachen retinalvascularmorphologyreflectsandpredictscerebralsmallvesseldiseaseevidencesfromeyebrainimaginganalysis AT shoulingwu retinalvascularmorphologyreflectsandpredictscerebralsmallvesseldiseaseevidencesfromeyebrainimaginganalysis AT jingli retinalvascularmorphologyreflectsandpredictscerebralsmallvesseldiseaseevidencesfromeyebrainimaginganalysis AT yinghui retinalvascularmorphologyreflectsandpredictscerebralsmallvesseldiseaseevidencesfromeyebrainimaginganalysis AT xiaoshuaili retinalvascularmorphologyreflectsandpredictscerebralsmallvesseldiseaseevidencesfromeyebrainimaginganalysis AT zhenchangwang retinalvascularmorphologyreflectsandpredictscerebralsmallvesseldiseaseevidencesfromeyebrainimaginganalysis AT hanlv retinalvascularmorphologyreflectsandpredictscerebralsmallvesseldiseaseevidencesfromeyebrainimaginganalysis |