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Imaging Biomarkers for Retinal Diseases: Prognostic Tools and Novel Clinical...
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Imaging Biomarkers for Retinal Diseases: Prognostic Tools and Novel Clinical Trial Endpoints for Precision Medicine

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Disease Biomarker".

Deadline for manuscript submissions: closed (31 May 2024) | Viewed by 5765

Special Issue Editor

Prof. Dr. Justis P. Ehlers

E-Mail Website
Guest Editor
Tony and Leona Campane Center for Excellence in Image-Guided Surgery and Advanced Imaging Research, Cole Eye Institute, Cleveland Clinic, OH, USA
Interests: imaging biomarkers; deep learning; retinal diseases; advanced image analysis; intraaoperative OCT; precision medicine

Special Issue Information

Dear Colleagues,

Advancements in imaging technology have transformed the field of retinal diseases through new insights in disease pathogenesis and prognosis. Advancements in image feature extraction and analysis technology, such as machine learning, has enabled the next-generation identification and quantification of imaging biomarkers for macular diseases across multiple imaging modalities. These biomarkers present unique opportunities to enhance personalized medicine in retinal disease management through improved patient education, progression risk prognostication, clinical trial enrichment, and even new potential end points. As new therapies emerge, the enhanced phenotyping of these biomarkers may provide important information regarding precision medicine and decision-making for treatment. This Special Issue of the Journal for Personalized Medicine aims to highlight imaging biomarkers for retinal diseases across various modalities using advanced image analysis techniques. We look forward to receiving manuscripts related to new imaging biomarker discovery, image analysis techniques, and assessments of imaging biomarkers within clinical trial datasets.

Prof. Dr. Justis P. Ehlers
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • age-related macular degeneration
  • diabetic eye disease
  • optical coherence tomography (OCT)
  • fluorescein angiography/ultra-widefield fluorescein angiography (UWFA)
  • fundus autofluorescence OCT angiography
  • retinal disease
  • macular disease

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Published Papers (3 papers)

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Research

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10 pages, 1571 KiB  
Article
Automated Evaluation of Ellipsoid Zone At-Risk Burden for Detection of Hydroxychloroquine Retinopathy
by Katherine E. Talcott, Gagan Kalra, Hasan Cetin, Yavuz Cakir, Jon Whitney, Jordan Budrevich, Jamie L. Reese, Sunil K. Srivastava and Justis P. Ehlers
J. Pers. Med. 2024, 14(5), 448; https://doi.org/10.3390/jpm14050448 - 25 Apr 2024
Viewed by 988
Abstract
Background: Screening for hydroxychloroquine (HCQ) retinopathy is crucial to detecting early disease. A novel machine-learning-based optical coherence tomography (OCT) biomarker, Ellipsoid Zone (EZ) At-Risk, can quantitatively measure EZ alterations and at-risk areas for progressive EZ loss in a fully automated fashion. The purpose [...] Read more.
Background: Screening for hydroxychloroquine (HCQ) retinopathy is crucial to detecting early disease. A novel machine-learning-based optical coherence tomography (OCT) biomarker, Ellipsoid Zone (EZ) At-Risk, can quantitatively measure EZ alterations and at-risk areas for progressive EZ loss in a fully automated fashion. The purpose of this analysis was to compare the EZ At-Risk burden in eyes with HCQ toxicity to eyes without toxicity. Methods: IRB-approved image analysis study of 83 subjects on HCQ and 44 age-matched normal subjects. SD-OCT images were reviewed for evidence of HCQ retinopathy. A ML-based, fully automatic measurement of the percentage of the macular area with EZ At-Risk was performed. Results: The mean age for HCQ subjects was 67.1 ± 13.2 years and 64.2 ± 14.3 years for normal subjects. The mean EZ At-Risk macular burden in the “toxic” group (n = 38) was significantly higher (10.7%) compared to the “non-toxic” group (n = 45; 2.2%; p = 0.023) and the “normal” group (1.4%; p = 0.012). Additionally, the amount of EZ At-Risk burden was significantly correlated with the HCQ dose based on the actual (p = 0.016) and ideal body weight (p = 0.033). Conclusions: The novel biomarker EZ-At Risk was significantly higher in subjects with evidence of HCQ retinopathy as well as significantly associated with HCQ dose. This novel biomarker should be further evaluated as a potential screening tool for subjects on HCQ. Full article
(This article belongs to the Special Issue Imaging Biomarkers for Retinal Diseases: Prognostic Tools and Novel Clinical Trial Endpoints for Precision Medicine)
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13 pages, 4174 KiB  
Article
Optical Identification of Diabetic Retinopathy Using Hyperspectral Imaging
by Ching-Yu Wang, Arvind Mukundan, Yu-Sin Liu, Yu-Ming Tsao, Fen-Chi Lin, Wen-Shuang Fan and Hsiang-Chen Wang
J. Pers. Med. 2023, 13(6), 939; https://doi.org/10.3390/jpm13060939 - 1 Jun 2023
Cited by 6 | Viewed by 1962
Abstract
The severity of diabetic retinopathy (DR) is directly correlated to changes in both the oxygen utilization rate of retinal tissue as well as the blood oxygen saturation of both arteries and veins. Therefore, the current stage of DR in a patient can be [...] Read more.
The severity of diabetic retinopathy (DR) is directly correlated to changes in both the oxygen utilization rate of retinal tissue as well as the blood oxygen saturation of both arteries and veins. Therefore, the current stage of DR in a patient can be identified by analyzing the oxygen content in blood vessels through fundus images. This enables medical professionals to make accurate and prompt judgments regarding the patient’s condition. However, in order to use this method to implement supplementary medical treatment, blood vessels under fundus images need to be determined first, and arteries and veins then need to be differentiated from one another. Therefore, the entire study was split into three sections. After first removing the background from the fundus images using image processing, the blood vessels in the images were then separated from the background. Second, the method of hyperspectral imaging (HSI) was utilized in order to construct the spectral data. The HSI algorithm was utilized in order to perform analysis and simulations on the overall reflection spectrum of the retinal image. Thirdly, principal component analysis (PCA) was performed in order to both simplify the data and acquire the major principal components score plot for retinopathy in arteries and veins at all stages. In the final step, arteries and veins in the original fundus images were separated using the principal components score plots for each stage. As retinopathy progresses, the difference in reflectance between the arteries and veins gradually decreases. This results in a more difficult differentiation of PCA results in later stages, along with decreased precision and sensitivity. As a consequence of this, the precision and sensitivity of the HSI method in DR patients who are in the normal stage and those who are in the proliferative DR (PDR) stage are the highest and lowest, respectively. On the other hand, the indicator values are comparable between the background DR (BDR) and pre-proliferative DR (PPDR) stages due to the fact that both stages exhibit comparable clinical-pathological severity characteristics. The results indicate that the sensitivity values of arteries are 82.4%, 77.5%, 78.1%, and 72.9% in the normal, BDR, PPDR, and PDR, while for veins, these values are 88.5%, 85.4%, 81.4%, and 75.1% in the normal, BDR, PPDR, and PDR, respectively. Full article
(This article belongs to the Special Issue Imaging Biomarkers for Retinal Diseases: Prognostic Tools and Novel Clinical Trial Endpoints for Precision Medicine)
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Review

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22 pages, 16697 KiB  
Review
Retinal Findings and Cardiovascular Risk: Prognostic Conditions, Novel Biomarkers, and Emerging Image Analysis Techniques
by Joseph Colcombe, Rusdeep Mundae, Alexis Kaiser, Jacques Bijon and Yasha Modi
J. Pers. Med. 2023, 13(11), 1564; https://doi.org/10.3390/jpm13111564 - 31 Oct 2023
Cited by 3 | Viewed by 2160
Abstract
Many retinal diseases and imaging findings have pathophysiologic underpinnings in the function of the cardiovascular system. Myriad retinal conditions, new imaging biomarkers, and novel image analysis techniques have been investigated for their association with future cardiovascular risk or utility in cardiovascular risk prognostication. [...] Read more.
Many retinal diseases and imaging findings have pathophysiologic underpinnings in the function of the cardiovascular system. Myriad retinal conditions, new imaging biomarkers, and novel image analysis techniques have been investigated for their association with future cardiovascular risk or utility in cardiovascular risk prognostication. An intensive literature search was performed to identify relevant articles indexed in PubMed, Scopus, and Google Scholar for a targeted narrative review. This review investigates the literature on specific retinal disease states, such as retinal arterial and venous occlusions and cotton wool spots, that portend significantly increased risk of future cardiovascular events, such as stroke or myocardial infarction, and the implications for personalized patient counseling. Furthermore, conditions diagnosed primarily through retinal bioimaging, such as paracentral acute middle maculopathy and the newly discovered entity known as a retinal ischemic perivascular lesion, may be associated with future incident cardiovascular morbidity and are also discussed. As ever-more-sophisticated imaging biomarkers and analysis techniques are developed, the review concludes with a focused analysis of optical coherence tomography and optical coherence tomography angiography biomarkers under investigation for potential value in prognostication and personalized therapy in cardiovascular disease. Full article
(This article belongs to the Special Issue Imaging Biomarkers for Retinal Diseases: Prognostic Tools and Novel Clinical Trial Endpoints for Precision Medicine)
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