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Hangartner K, Bajka A, Wiest MRJ, Sidhu S, Toro MD, Maloca PM, Zweifel SA. Assessment of Retinal Vessel Tortuosity Index in Patients with Fabry Disease Using Optical Coherence Tomography Angiography (OCTA). Diagnostics (Basel) 2023; 13:2496. [PMID: 37568859 PMCID: PMC10417007 DOI: 10.3390/diagnostics13152496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Revised: 07/16/2023] [Accepted: 07/25/2023] [Indexed: 08/13/2023] Open
Abstract
Vessel tortuosity (VT) is a parameter used to assess retinal involvement in patients affected by systemic diseases such as Fabry disease (FD). In this study, we assessed a retinal VT index (VTI) using optical coherence tomography angiography (OCTA) in a group of patients with FD (FD cohort) compared to a healthy control group (HC cohort). This is a single-center, retrospective study analysis of all consecutive patients with genetically tested and confirmed FD who underwent regular ophthalmological visits from December 2017 to January 2020 at the Department of Ophthalmology at the University Hospital of Zurich, Switzerland. VTI was calculated for each OCTA image and the results were compared between FD and HC cohort. A total of 56 participants, 32 (male:female ratio 12:20) in the FD cohort and 24 (male:female ratio 13:11) in the HC cohort. Classic onset was determined in 18 patients. Overall, mean VTI (±SD) was 0.21 (±0.07). Male patients with classic-onset FD had a significantly higher mean VTI (0.33, SD ± 0.35) compared to all other subgroups (p-value < 0.05). Further investigations of retinal VTI in patients with FD could be helpful to use OCTA as a noninvasive screening and follow-up modality to assess disease progression in affected patients.
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Affiliation(s)
- Kevin Hangartner
- Faculty of Human Medicine, University of Zurich, 8032 Zurich, Switzerland
| | - Anahita Bajka
- Faculty of Human Medicine, University of Zurich, 8032 Zurich, Switzerland
- Department of Ophthalmology, University Hospital of Zurich, University of Zurich, 8091 Zurich, Switzerland
| | - Maximilian R. J. Wiest
- Faculty of Human Medicine, University of Zurich, 8032 Zurich, Switzerland
- Department of Ophthalmology, University Hospital of Zurich, University of Zurich, 8091 Zurich, Switzerland
| | - Sophia Sidhu
- Faculty of Medicine, University of California San Diego, 5998 Alcala Park, San Diego, CA 92110, USA
| | - Mario D. Toro
- Department of Ophthalmology, University Hospital of Zurich, University of Zurich, 8091 Zurich, Switzerland
- Chair and Department of General and Pediatric Ophthalmology, Medical University of Lublin, 20079 Lublin, Poland
- Eye Clinic, Department of Public Health, University Federico II, 80131 Naples, Italy
| | - Peter M. Maloca
- Institute of Molecular and Clinical Ophthalmology Basel (IOB), 4031 Basel, Switzerland
- Department of Ophthalmology, University Hospital Basel, 4031 Basel, Switzerland
- Moorfields Eye Hospital NHS Foundation Trust, London EC1V 2PD, UK
| | - Sandrine A. Zweifel
- Faculty of Human Medicine, University of Zurich, 8032 Zurich, Switzerland
- Department of Ophthalmology, University Hospital of Zurich, University of Zurich, 8091 Zurich, Switzerland
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Shi XH, Dong L, Zhang RH, Zhou DJ, Ling SG, Shao L, Yan YN, Wang YX, Wei WB. Relationships between quantitative retinal microvascular characteristics and cognitive function based on automated artificial intelligence measurements. Front Cell Dev Biol 2023; 11:1174984. [PMID: 37416799 PMCID: PMC10322221 DOI: 10.3389/fcell.2023.1174984] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 06/09/2023] [Indexed: 07/08/2023] Open
Abstract
Introduction: The purpose of this study is to assess the relationship between retinal vascular characteristics and cognitive function using artificial intelligence techniques to obtain fully automated quantitative measurements of retinal vascular morphological parameters. Methods: A deep learning-based semantic segmentation network ResNet101-UNet was used to construct a vascular segmentation model for fully automated quantitative measurement of retinal vascular parameters on fundus photographs. Retinal photographs centered on the optic disc of 3107 participants (aged 50-93 years) from the Beijing Eye Study 2011, a population-based cross-sectional study, were analyzed. The main parameters included the retinal vascular branching angle, vascular fractal dimension, vascular diameter, vascular tortuosity, and vascular density. Cognitive function was assessed using the Mini-Mental State Examination (MMSE). Results: The results showed that the mean MMSE score was 26.34 ± 3.64 (median: 27; range: 2-30). Among the participants, 414 (13.3%) were classified as having cognitive impairment (MMSE score < 24), 296 (9.5%) were classified as mild cognitive impairment (MMSE: 19-23), 98 (3.2%) were classified as moderate cognitive impairment (MMSE: 10-18), and 20 (0.6%) were classified as severe cognitive impairment (MMSE < 10). Compared with the normal cognitive function group, the retinal venular average diameter was significantly larger (p = 0.013), and the retinal vascular fractal dimension and vascular density were significantly smaller (both p < 0.001) in the mild cognitive impairment group. The retinal arteriole-to-venular ratio (p = 0.003) and vascular fractal dimension (p = 0.033) were significantly decreased in the severe cognitive impairment group compared to the mild cognitive impairment group. In the multivariate analysis, better cognition (i.e., higher MMSE score) was significantly associated with higher retinal vascular fractal dimension (b = 0.134, p = 0.043) and higher retinal vascular density (b = 0.152, p = 0.023) after adjustment for age, best corrected visual acuity (BCVA) (logMAR) and education level. Discussion: In conclusion, our findings derived from an artificial intelligence-based fully automated retinal vascular parameter measurement method showed that several retinal vascular morphological parameters were correlated with cognitive impairment. The decrease in retinal vascular fractal dimension and decreased vascular density may serve as candidate biomarkers for early identification of cognitive impairment. The observed reduction in the retinal arteriole-to-venular ratio occurs in the late stages of cognitive impairment.
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Affiliation(s)
- Xu Han Shi
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Beijing Ophthalmology and Visual Sciences Key Lab, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Li Dong
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Beijing Ophthalmology and Visual Sciences Key Lab, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Rui Heng Zhang
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Beijing Ophthalmology and Visual Sciences Key Lab, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Deng Ji Zhou
- EVision Technology (Beijing) Co., Ltd., Beijing, China
| | | | - Lei Shao
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Beijing Ophthalmology and Visual Sciences Key Lab, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Yan Ni Yan
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Beijing Ophthalmology and Visual Sciences Key Lab, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Ya Xing Wang
- Beijing Ophthalmology and Visual Science Key Laboratory, Beijing Tongren Eye Center, Beijing Tongren Hospital, Beijing Institute of Ophthalmology, Capital Medical University, Beijing, China
| | - Wen Bin Wei
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Beijing Ophthalmology and Visual Sciences Key Lab, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
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Momin SZ, Le JT, Miranda RC. Vascular Contributions to the Neurobiological Effects of Prenatal Alcohol Exposure. ADVANCES IN DRUG AND ALCOHOL RESEARCH 2023; 3:10924. [PMID: 37205306 PMCID: PMC10191416 DOI: 10.3389/adar.2023.10924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Fetal alcohol spectrum disorders (FASD) are often characterized as a cluster of brain-based disabilities. Though cardiovascular effects of prenatal alcohol exposure (PAE) have been documented, the vascular deficits due to PAE are less understood, but may contribute substantially to the severity of neurobehavioral presentation and health outcomes in persons with FASD. Methods We conducted a systematic review of research articles curated in PubMed to assess the strength of the research on vascular effects of PAE. 40 pertinent papers were selected, covering studies in both human populations and animal models. Results Studies in human populations identified cardiac defects, and defects in vasculature, including increased tortuosity, defects in basement membranes, capillary basal hyperplasia, endarteritis, and disorganized and diminished cerebral vasculature due to PAE. Preclinical studies showed that PAE rapidly and persistently results in vasodilation of large afferent cerebral arteries, but to vasoconstriction of smaller cerebral arteries and microvasculature. Moreover, PAE continues to affect cerebral blood flow into middle-age. Human and animal studies also indicate that ocular vascular parameters may have diagnostic and predictive value. A number of intervening mechanisms were identified, including increased autophagy, inflammation and deficits in mitochondria. Studies in animals identified persistent changes in blood flow and vascular density associated with endocannabinoid, prostacyclin and nitric oxide signaling, as well as calcium mobilization. Conclusion Although the brain has been a particular focus of studies on PAE, the cardiovascular system is equally affected. Studies in human populations, though constrained by small sample sizes, did link pathology in major blood vessels and tissue vasculature, including brain vasculature, to PAE. Animal studies highlighted molecular mechanisms that may be useful therapeutic targets. Collectively, these studies suggest that vascular pathology is a possible contributing factor to neurobehavioral and health problems across a lifespan in persons with a diagnosis of FASD. Furthermore, ocular vasculature may serve as a biomarker for neurovascular health in FASD.
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Affiliation(s)
| | | | - Rajesh C. Miranda
- Corresponding author to whom correspondence should be addressed: Rajesh C. Miranda, PhD, , Texas A&M University Health Science Center, School of Medicine, Department of Neuroscience & Experimental Therapeutics, Medical Research and Education Building, 8447 Riverside Parkway, Bryan, TX 77807-3260, Phone: 979-436-0332, Fax: 979-436-0086
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Tao W, Kwapong WR, Xie J, Wang Z, Guo X, Liu J, Ye C, Wu B, Zhao Y, Liu M. Retinal microvasculature and imaging markers of brain frailty in normal aging adults. Front Aging Neurosci 2022; 14:945964. [PMID: 36072485 PMCID: PMC9441884 DOI: 10.3389/fnagi.2022.945964] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 07/22/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundThe retina and brain share a similar embryologic origin, blood barriers, and microvasculature features. Thus, retinal imaging has been of interest in the aging population to help in the early detection of brain disorders. Imaging evaluation of brain frailty, including brain atrophy and markers of cerebral small vessel disease (CSVD), could reflect brain health in normal aging, but is costly and time-consuming. In this study, we aimed to evaluate the retinal microvasculature and its association with radiological indicators of brain frailty in normal aging adults.MethodsSwept-source optical coherence tomography angiography (SS-OCTA) and 3T-MRI brain scanning were performed on normal aging adults (aged ≥ 50 years). Using a deep learning algorithm, microvascular tortuosity (VT) and fractal dimension parameter (Dbox) were used to evaluate the superficial vascular complex (SVC) and deep vascular complex (DVC) of the retina. MRI markers of brain frailty include brain volumetric measures and CSVD markers that were assessed.ResultsOf the 139 normal aging individuals included, the mean age was 59.43 ± 7.31 years, and 64.0% (n = 89) of the participants were females. After adjustment of age, sex, and vascular risk factors, Dbox in the DVC showed a significant association with the presence of lacunes (β = 0.58, p = 0.007), while VT in the SVC significantly correlated with the score of cerebral deep white matter hyperintensity (β = 0.31, p = 0.027). No correlations were found between brain volumes and retinal microvasculature changes (P > 0.05).ConclusionOur report suggests that imaging of the retinal microvasculature may give clues to brain frailty in the aging population.
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Affiliation(s)
- Wendan Tao
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | | | - Jianyang Xie
- Cixi Institute of Biomedical Engineering, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China
| | - Zetao Wang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Xiaonan Guo
- School of Information Science and Engineering, Yanshan University, Qinhuangdao, China
| | - Junfeng Liu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Chen Ye
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Bo Wu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Yitian Zhao
- The Affiliated People’s Hospital of Ningbo University, Ningbo, China
- Cixi Institute of Biomedical Engineering, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China
- Yitian Zhao,
| | - Ming Liu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
- *Correspondence: Ming Liu,
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Qu Y, Lee JJW, Zhuo Y, Liu S, Thomas RL, Owens DR, Zee BCY. Risk Assessment of CHD Using Retinal Images with Machine Learning Approaches for People with Cardiometabolic Disorders. J Clin Med 2022; 11:2687. [PMID: 35628812 PMCID: PMC9143834 DOI: 10.3390/jcm11102687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 05/05/2022] [Accepted: 05/06/2022] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Coronary heart disease (CHD) is the leading cause of death worldwide, constituting a growing health and social burden. People with cardiometabolic disorders are more likely to develop CHD. Retinal image analysis is a novel and noninvasive method to assess microvascular function. We aim to investigate whether retinal images can be used for CHD risk estimation for people with cardiometabolic disorders. METHODS We have conducted a case-control study at Shenzhen Traditional Chinese Medicine Hospital, where 188 CHD patients and 128 controls with cardiometabolic disorders were recruited. Retinal images were captured within two weeks of admission. The retinal characteristics were estimated by the automatic retinal imaging analysis (ARIA) algorithm. Risk estimation models were established for CHD patients using machine learning approaches. We divided CHD patients into a diabetes group and a non-diabetes group for sensitivity analysis. A ten-fold cross-validation method was used to validate the results. RESULTS The sensitivity and specificity were 81.3% and 88.3%, respectively, with an accuracy of 85.4% for CHD risk estimation. The risk estimation model for CHD with diabetes performed better than the model for CHD without diabetes. CONCLUSIONS The ARIA algorithm can be used as a risk assessment tool for CHD for people with cardiometabolic disorders.
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Affiliation(s)
- Yimin Qu
- Division of Biostatistics, The Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China; (Y.Q.); (J.J.-W.L.)
| | - Jack Jock-Wai Lee
- Division of Biostatistics, The Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China; (Y.Q.); (J.J.-W.L.)
| | - Yuanyuan Zhuo
- Department of Acupuncture and Moxibustion, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen 518005, China;
| | - Shukai Liu
- Department of Cardiovascular Disease, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen 518005, China;
| | - Rebecca L. Thomas
- Diabetes Research Group, Swansea University, Swansea SA2 8PP, UK; (R.L.T.); (D.R.O.)
| | - David R. Owens
- Diabetes Research Group, Swansea University, Swansea SA2 8PP, UK; (R.L.T.); (D.R.O.)
| | - Benny Chung-Ying Zee
- Division of Biostatistics, The Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China; (Y.Q.); (J.J.-W.L.)
- Clinical Trials and Biostatistics Lab, CUHK Shenzhen Research Institute, Shenzhen 518057, China
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