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Gouravani M, Fekrazad S, Mafhoumi A, Ashouri M, DeBuc DC. Optical coherence tomography measurements in Huntington's disease: a systematic review and meta-analysis. J Neurol 2024:10.1007/s00415-024-12634-4. [PMID: 39187741 DOI: 10.1007/s00415-024-12634-4] [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: 07/07/2024] [Revised: 08/02/2024] [Accepted: 08/09/2024] [Indexed: 08/28/2024]
Abstract
BACKGROUND A connection has been established between ocular structural changes and various neurodegenerative diseases. Several studies utilizing optical coherence tomography (OCT) have detected signs of ocular structural alterations among individuals with Huntington's disease (HD). The inconsistent results reported in the literature regarding alterations in the retina and choroid encouraged us to conduct this systematic review and meta-analysis to accumulate the findings. METHODS A systematic search was carried out in three electronic databases (PubMed, Embase, Scopus) to find studies reporting OCT measurements in HD cases compared with healthy controls (HC). A fixed-effects or random-effects meta-analysis was conducted according to the detected heterogeneity level. Furthermore, subgroup and sensitivity analyses, meta-regression, and quality assessment were performed. RESULTS Eleven studies were included in the systematic review and 9 studies with a total population of 452 participants (241 cases, and 211 HC) underwent meta-analysis. Results of the analysis denoted that subfoveal choroid had a significantly reduced thickness in HD eyes compared to HC (p < 0.0001). Moreover, our analysis indicated that HD cases had a significantly thinner average (p = 0.0130) and temporal peripapillary retinal nerve fiber layer (pRNFL) (p = 0.0012) than HC. However, subjects with pre-HD had insignificant differences in average (p = 0.44) and temporal pRNFL thickness (p = 0.33) with the HC group. CONCLUSION Results of the current systematic review and meta-analysis revealed the significant thinning of average and temporal pRNFL and subfoveal choroid in HD compared to HC. However, OCT currently might be considered insensitive to be applied in the pre-HD population at least until further longitudinal investigations considering variables such as the duration between OCT measurement and disease onset validating OCT as a routine diagnostic tool in HD clinics.
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Affiliation(s)
- Mahdi Gouravani
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Sepehr Fekrazad
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
- International Network for Photomedicine and Photodynamic Therapy (INPMPDT), Universal Scientific Education and Research Network (USERN), Tehran, Iran
| | - Asma Mafhoumi
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Moein Ashouri
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Delia Cabrera DeBuc
- Miller School of Medicine, Bascom Palmer Eye Institute, University of Miami, 900 NW 17 Street, Miami, FL, 33136, USA.
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Bahr T, Vu TA, Tuttle JJ, Iezzi R. Deep Learning and Machine Learning Algorithms for Retinal Image Analysis in Neurodegenerative Disease: Systematic Review of Datasets and Models. Transl Vis Sci Technol 2024; 13:16. [PMID: 38381447 PMCID: PMC10893898 DOI: 10.1167/tvst.13.2.16] [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: 08/30/2023] [Accepted: 11/26/2023] [Indexed: 02/22/2024] Open
Abstract
Purpose Retinal images contain rich biomarker information for neurodegenerative disease. Recently, deep learning models have been used for automated neurodegenerative disease diagnosis and risk prediction using retinal images with good results. Methods In this review, we systematically report studies with datasets of retinal images from patients with neurodegenerative diseases, including Alzheimer's disease, Huntington's disease, Parkinson's disease, amyotrophic lateral sclerosis, and others. We also review and characterize the models in the current literature which have been used for classification, regression, or segmentation problems using retinal images in patients with neurodegenerative diseases. Results Our review found several existing datasets and models with various imaging modalities primarily in patients with Alzheimer's disease, with most datasets on the order of tens to a few hundred images. We found limited data available for the other neurodegenerative diseases. Although cross-sectional imaging data for Alzheimer's disease is becoming more abundant, datasets with longitudinal imaging of any disease are lacking. Conclusions The use of bilateral and multimodal imaging together with metadata seems to improve model performance, thus multimodal bilateral image datasets with patient metadata are needed. We identified several deep learning tools that have been useful in this context including feature extraction algorithms specifically for retinal images, retinal image preprocessing techniques, transfer learning, feature fusion, and attention mapping. Importantly, we also consider the limitations common to these models in real-world clinical applications. Translational Relevance This systematic review evaluates the deep learning models and retinal features relevant in the evaluation of retinal images of patients with neurodegenerative disease.
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Affiliation(s)
- Tyler Bahr
- Mayo Clinic, Department of Ophthalmology, Rochester, MN, USA
| | - Truong A. Vu
- University of the Incarnate Word, School of Osteopathic Medicine, San Antonio, TX, USA
| | - Jared J. Tuttle
- University of Texas Health Science Center at San Antonio, Joe R. and Teresa Lozano Long School of Medicine, San Antonio, TX, USA
| | - Raymond Iezzi
- Mayo Clinic, Department of Ophthalmology, Rochester, MN, USA
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Joseph S, Robbins CB, Haystead A, Hemesath A, Allen A, Kundu A, Ma JP, Scott BL, Moore KPL, Agrawal R, Gunasan V, Stinnett SS, Grewal DS, Fekrat S. Characterizing differences in retinal and choroidal microvasculature and structure in individuals with Huntington's Disease compared to healthy controls: A cross-sectional prospective study. PLoS One 2024; 19:e0296742. [PMID: 38289919 PMCID: PMC10826956 DOI: 10.1371/journal.pone.0296742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 12/18/2023] [Indexed: 02/01/2024] Open
Abstract
OBJECTIVE To characterize retinal and choroidal microvascular and structural changes in patients who are gene positive for mutant huntingtin protein (mHtt) with symptoms of Huntington's Disease (HD). METHODS This study is a cross-sectional comparison of patients who are gene positive for mHtt and exhibit symptoms of HD, either motor manifest or prodromal (HD group), and cognitively normal individuals without a family history of HD (control group). HD patients were diagnosed by Duke movement disorder neurologists based on the Unified Huntington's Disease Rating Scale (UHDRS). Fovea and optic nerve centered OCT and OCTA images were captured using Zeiss Cirrus HD-5000 with AngioPlex. Outcome metrics included central subfield thickness (CST), peripapillary retinal nerve fiber layer (pRNFL) thickness, ganglion cell-inner plexiform layer (GCIPL) thickness, and choroidal vascularity index (CVI) on OCT, and foveal avascular zone (FAZ) area, vessel density (VD), perfusion density (PD), capillary perfusion density (CPD), and capillary flux index (CFI) on OCTA. Generalized estimating equation (GEE) models were used to account for inter-eye correlation. RESULTS Forty-four eyes of 23 patients in the HD group and 77 eyes of 39 patients in the control group were analyzed. Average GCIPL thickness and FAZ area were decreased in the HD group compared to controls (p = 0.001, p < 0.001). No other imaging metrics were significantly different between groups. CONCLUSIONS Patients in the HD group had decreased GCIPL thickness and smaller FAZ area, highlighting the potential use of retinal biomarkers in detecting neurodegenerative changes in HD.
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Affiliation(s)
- Suzanna Joseph
- Department of Ophthalmology, Duke University School of Medicine, Durham, NC, United States of America
- iMIND Research Group, Durham, NC, United States of America
| | - Cason B. Robbins
- Department of Ophthalmology, Duke University School of Medicine, Durham, NC, United States of America
- iMIND Research Group, Durham, NC, United States of America
| | - Alice Haystead
- iMIND Research Group, Durham, NC, United States of America
| | - Angela Hemesath
- Department of Ophthalmology, Duke University School of Medicine, Durham, NC, United States of America
- iMIND Research Group, Durham, NC, United States of America
| | - Ariana Allen
- Department of Ophthalmology, Duke University School of Medicine, Durham, NC, United States of America
- iMIND Research Group, Durham, NC, United States of America
| | - Anita Kundu
- Department of Ophthalmology, Duke University School of Medicine, Durham, NC, United States of America
- iMIND Research Group, Durham, NC, United States of America
| | - Justin P. Ma
- iMIND Research Group, Durham, NC, United States of America
| | - Burton L. Scott
- Department of Neurology, Duke University School of Medicine, Durham, NC, United States of America
| | - Kathryn P. L. Moore
- Department of Neurology, Duke University School of Medicine, Durham, NC, United States of America
| | - Rupesh Agrawal
- National Healthcare Group Eye Institute, Tan Tock Seng Hospital, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Vithiya Gunasan
- National Healthcare Group Eye Institute, Tan Tock Seng Hospital, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Sandra S. Stinnett
- Department of Ophthalmology, Duke University School of Medicine, Durham, NC, United States of America
- iMIND Research Group, Durham, NC, United States of America
| | - Dilraj S. Grewal
- Department of Ophthalmology, Duke University School of Medicine, Durham, NC, United States of America
- iMIND Research Group, Durham, NC, United States of America
| | - Sharon Fekrat
- Department of Ophthalmology, Duke University School of Medicine, Durham, NC, United States of America
- iMIND Research Group, Durham, NC, United States of America
- Department of Neurology, Duke University School of Medicine, Durham, NC, United States of America
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Suh A, Ong J, Kamran SA, Waisberg E, Paladugu P, Zaman N, Sarker P, Tavakkoli A, Lee AG. Retina Oculomics in Neurodegenerative Disease. Ann Biomed Eng 2023; 51:2708-2721. [PMID: 37855949 DOI: 10.1007/s10439-023-03365-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 09/05/2023] [Indexed: 10/20/2023]
Abstract
Ophthalmic biomarkers have long played a critical role in diagnosing and managing ocular diseases. Oculomics has emerged as a field that utilizes ocular imaging biomarkers to provide insights into systemic diseases. Advances in diagnostic and imaging technologies including electroretinography, optical coherence tomography (OCT), confocal scanning laser ophthalmoscopy, fluorescence lifetime imaging ophthalmoscopy, and OCT angiography have revolutionized the ability to understand systemic diseases and even detect them earlier than clinical manifestations for earlier intervention. With the advent of increasingly large ophthalmic imaging datasets, machine learning models can be integrated into these ocular imaging biomarkers to provide further insights and prognostic predictions of neurodegenerative disease. In this manuscript, we review the use of ophthalmic imaging to provide insights into neurodegenerative diseases including Alzheimer Disease, Parkinson Disease, Amyotrophic Lateral Sclerosis, and Huntington Disease. We discuss recent advances in ophthalmic technology including eye-tracking technology and integration of artificial intelligence techniques to further provide insights into these neurodegenerative diseases. Ultimately, oculomics opens the opportunity to detect and monitor systemic diseases at a higher acuity. Thus, earlier detection of systemic diseases may allow for timely intervention for improving the quality of life in patients with neurodegenerative disease.
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Affiliation(s)
- Alex Suh
- Tulane University School of Medicine, New Orleans, LA, USA.
| | - Joshua Ong
- Michigan Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Sharif Amit Kamran
- Human-Machine Perception Laboratory, Department of Computer Science and Engineering, University of Nevada, Reno, Reno, NV, USA
| | - Ethan Waisberg
- University College Dublin School of Medicine, Belfield, Dublin, Ireland
| | - Phani Paladugu
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - Nasif Zaman
- Human-Machine Perception Laboratory, Department of Computer Science and Engineering, University of Nevada, Reno, Reno, NV, USA
| | - Prithul Sarker
- Human-Machine Perception Laboratory, Department of Computer Science and Engineering, University of Nevada, Reno, Reno, NV, USA
| | - Alireza Tavakkoli
- Human-Machine Perception Laboratory, Department of Computer Science and Engineering, University of Nevada, Reno, Reno, NV, USA
| | - Andrew G Lee
- Center for Space Medicine, Baylor College of Medicine, Houston, TX, USA
- Department of Ophthalmology, Blanton Eye Institute, Houston Methodist Hospital, 6560 Fannin St #450, Houston, TX, 77030, USA
- The Houston Methodist Research Institute, Houston Methodist Hospital, Houston, TX, USA
- Departments of Ophthalmology, Neurology and Neurosurgery, Weill Cornell Medicine, New York, NY, USA
- Department of Ophthalmology, University of Texas Medical Branch, Galveston, TX, USA
- University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Texas A&M College of Medicine, Bryan, TX, USA
- Department of Ophthalmology, The University of Iowa Hospitals and Clinics, Iowa City, IA, USA
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Murueta-Goyena A, Del Pino R, Acera M, Teijeira-Portas S, Romero D, Ayala U, Fernández-Valle T, Tijero B, Gabilondo I, Gómez Esteban JC. Retinal thickness as a biomarker of cognitive impairment in manifest Huntington's disease. J Neurol 2023:10.1007/s00415-023-11720-3. [PMID: 37079031 DOI: 10.1007/s00415-023-11720-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Revised: 04/06/2023] [Accepted: 04/07/2023] [Indexed: 04/21/2023]
Abstract
BACKGROUND Cognitive decline has been reported in premanifest and manifest Huntington's disease but reliable biomarkers are lacking. Inner retinal layer thickness seems to be a good biomarker of cognition in other neurodegenerative diseases. OBJECTIVE To explore the relationship between optical coherence tomography-derived metrics and global cognition in Huntington's Disease. METHODS Thirty-six patients with Huntington's disease (16 premanifest and 20 manifest) and 36 controls matched by age, sex, smoking status, and hypertension status underwent macular volumetric and peripapillary optical coherence tomography scans. Disease duration, motor status, global cognition and CAG repeats were recorded in patients. Group differences in imaging parameters and their association with clinical outcomes were analyzed using linear mixed-effect models. RESULTS Premanifest and manifest Huntington's disease patients presented thinner retinal external limiting membrane-Bruch's membrane complex, and manifest patients had thinner temporal peripapillary retinal nerve fiber layer compared to controls. In manifest Huntington's disease, macular thickness was significantly associated with MoCA scores, inner nuclear layer showing the largest regression coefficients. This relationship was consistent after adjusting for age, sex, and education and p-value correction with False Discovery Rate. None of the retinal variables were related to Unified Huntington's Disease Rating Scale score, disease duration, or disease burden. Premanifest patients did not show a significant association between OCT-derived parameters and clinical outcomes in corrected models. CONCLUSIONS In line with other neurodegenerative diseases, OCT is a potential biomarker of cognitive status in manifest HD. Future prospective studies are needed to evaluate OCT as a potential surrogate marker of cognitive decline in HD.
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Affiliation(s)
- Ane Murueta-Goyena
- Neurodegenerative Diseases Group, Biocruces Bizkaia Health Research Institute, Barakaldo, Spain.
- Department of Neurosciences, Faculty of Medicine and Nursery, University of the Basque Country (UPV/EHU), 48930, Leioa, Spain.
| | - Rocío Del Pino
- Neurodegenerative Diseases Group, Biocruces Bizkaia Health Research Institute, Barakaldo, Spain
| | - Marian Acera
- Neurodegenerative Diseases Group, Biocruces Bizkaia Health Research Institute, Barakaldo, Spain
| | - Sara Teijeira-Portas
- Neurodegenerative Diseases Group, Biocruces Bizkaia Health Research Institute, Barakaldo, Spain
| | - David Romero
- Biomedical Engineering Department, Faculty of Engineering, Mondragon University, Mondragon, Spain
| | - Unai Ayala
- Biomedical Engineering Department, Faculty of Engineering, Mondragon University, Mondragon, Spain
| | - Tamara Fernández-Valle
- Neurodegenerative Diseases Group, Biocruces Bizkaia Health Research Institute, Barakaldo, Spain
- Department of Neurosciences, Faculty of Medicine and Nursery, University of the Basque Country (UPV/EHU), 48930, Leioa, Spain
- Neurology Department, Cruces University Hospital, Osakidetza, Barakaldo, Spain
| | - Beatriz Tijero
- Neurodegenerative Diseases Group, Biocruces Bizkaia Health Research Institute, Barakaldo, Spain
- Neurology Department, Cruces University Hospital, Osakidetza, Barakaldo, Spain
| | - Iñigo Gabilondo
- Neurodegenerative Diseases Group, Biocruces Bizkaia Health Research Institute, Barakaldo, Spain
- IKERBASQUE, The Basque Foundation for Science, Bilbao, Spain
| | - Juan Carlos Gómez Esteban
- Neurodegenerative Diseases Group, Biocruces Bizkaia Health Research Institute, Barakaldo, Spain
- Department of Neurosciences, Faculty of Medicine and Nursery, University of the Basque Country (UPV/EHU), 48930, Leioa, Spain
- Neurology Department, Cruces University Hospital, Osakidetza, Barakaldo, Spain
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Yefimova MG. Myelinosome organelles in pathological retinas: ubiquitous presence and dual role in ocular proteostasis maintenance. Neural Regen Res 2022; 18:1009-1016. [PMID: 36254982 PMCID: PMC9827766 DOI: 10.4103/1673-5374.355753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
The timely and efficient elimination of aberrant proteins and damaged organelles, formed in response to various genetic and environmental stressors, is a vital need for all cells of the body. Recent lines of evidence point out several non-classical strategies employed by ocular tissues to cope with aberrant constituents generated in the retina and in the retinal pigmented epithelium cells exposed to various stressors. Along with conventional strategies relying upon the intracellular degradation of aberrant constituents through ubiquitin-proteasome and/or lysosome-dependent autophagy proteolysis, two non-conventional mechanisms also contribute to proteostasis maintenance in ocular tissues. An exosome-mediated clearing and a myelinosome-driven secretion mechanism do not require intracellular degradation but provide the export of aberrant constituents and "waste proteins" outside of the cells. The current review is centered on the non-degradative myelinosome-driven secretion mechanism, which operates in the retina of transgenic Huntington's disease R6/1 model mice. Myelinosome-driven secretion is supported by rare organelles myelinosomes that are detected not only in degenerative Huntington's disease R6/1 retina but also in various pathological states of the retina and of the retinal pigmented epithelium. The intra-retinal traffic and inter-cellular exchange of myelinosomes was discussed in the context of a dual role of the myelinosome-driven secretion mechanism for proteostasis maintenance in different ocular compartments. Special focus was made on the interplay between degradative and non-degradative strategies in ocular pathophysiology, to delineate potential therapeutic approaches to counteract several vision diseases.
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Affiliation(s)
- Marina G. Yefimova
- Sechenov Institute of Evolutionary Physiology and Biochemistry, Russian Academy of Sciences, St-Petersburg, Russia,Laboratoire STIM CNRS ERL 7003, Université de Poitiers, Poitiers, France,Correspondence to: Marina G. Yefimova, .
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