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Diagnostics
Special Issues
Diagnostics for Ocular Diseases: Its Importance in Patient Care
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Diagnostics for Ocular Diseases: Its Importance in Patient Care

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Pathology and Molecular Diagnostics".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 1469

Special Issue Editors

Dr. Ramesh Venkatesh

E-Mail Website
Guest Editor
Department of Retina and Vitreous, Narayana Nethralaya, #121/C, 1st R Block, Chord Road, Rajaji Nagar, 560010 Bengaluru, Karnataka, India
Interests: retinal imaging; retinal vascular occlusion; macular telangiectasia
Dr. Jay Chhablani

E-Mail Website
Guest Editor
UPMC Eye Center, University of Pittsburgh, Pittsburgh, PA 15213, USA
Interests: retinal imaging; central serous chorioretinopathy; optic disc pit
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

On behalf of the Diagnostics Editorial Team, we are delighted to present a Special Issue on the topic of Diagnostics for Ocular Diseases: Its Importance in Patient Care.

This Special Issue aims to evaluate the use of latest ocular imaging modalities in ocular and systemic diseases in order to evaluate the possibility of obtaining new potential diagnostic biomarkers and facilitate multidisciplinary integration between clinical medicine and the field of ocular imaging.

The accepted papers will describe new applications in these areas. This Special Issue accepts high-quality articles containing original research results and case reports as well as review articles.

We are pleased to invite you to submit your work related to this topic. We look forward to receiving your contributions.

Dr. Ramesh Venkatesh
Dr. Jay Chhablani
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

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

  • ocular imaging
  • patient care
  • biomarkers
  • retinal imaging
  • retinal diseases

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Published Papers (2 papers)

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Research

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10 pages, 482 KiB  
Article
Evaluation of Systemic Risk Factors in Patients with Diabetes Mellitus for Detecting Diabetic Retinopathy with Random Forest Classification Model
by Ramesh Venkatesh, Priyanka Gandhi, Ayushi Choudhary, Rupal Kathare, Jay Chhablani, Vishma Prabhu, Snehal Bavaskar, Prathiba Hande, Rohit Shetty, Nikitha Gurram Reddy, Padmaja Kumari Rani and Naresh Kumar Yadav
Diagnostics 2024, 14(16), 1765; https://doi.org/10.3390/diagnostics14161765 - 13 Aug 2024
Viewed by 211
Abstract
Background: This study aims to assess systemic risk factors in diabetes mellitus (DM) patients and predict diabetic retinopathy (DR) using a Random Forest (RF) classification model. Methods: We included DM patients presenting to the retina clinic for first-time DR screening. Data on age, [...] Read more.
Background: This study aims to assess systemic risk factors in diabetes mellitus (DM) patients and predict diabetic retinopathy (DR) using a Random Forest (RF) classification model. Methods: We included DM patients presenting to the retina clinic for first-time DR screening. Data on age, gender, diabetes type, treatment history, DM control status, family history, pregnancy history, and systemic comorbidities were collected. DR and sight-threatening DR (STDR) were diagnosed via a dilated fundus examination. The dataset was split 80:20 into training and testing sets. The RF model was trained to detect DR and STDR separately, and its performance was evaluated using misclassification rates, sensitivity, and specificity. Results: Data from 1416 DM patients were analyzed. The RF model was trained on 1132 (80%) patients. The misclassification rates were 0% for DR and ~20% for STDR in the training set. External testing on 284 (20%) patients showed 100% accuracy, sensitivity, and specificity for DR detection. For STDR, the model achieved 76% (95% CI-70.7%–80.7%) accuracy, 53% (95% CI-39.2%–66.6%) sensitivity, and 80% (95% CI-74.6%–84.7%) specificity. Conclusions: The RF model effectively predicts DR in DM patients using systemic risk factors, potentially reducing unnecessary referrals for DR screening. However, further validation with diverse datasets is necessary to establish its reliability for clinical use. Full article
(This article belongs to the Special Issue Diagnostics for Ocular Diseases: Its Importance in Patient Care)
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<p>Flow chart depicting the process of model training and testing in the study.</p> Full article ">

Other

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11 pages, 2001 KiB  
Case Report
High-Resolution Imaging in Macular Telangiectasia Type 2: Case Series and Literature Review
by Andrada Elena Mirescu, Florian Balta, Ramona Barac, Dan George Deleanu, Ioana Teodora Tofolean, George Balta, Razvan Cojanu and Sanda Jurja
Diagnostics 2024, 14(13), 1351; https://doi.org/10.3390/diagnostics14131351 - 25 Jun 2024
Viewed by 907
Abstract
Background: Macular telangiectasia (MacTel), also known as idiopathic juxtafoveolar telangiectasis (IJFTs), involves telangiectatic changes in the macular capillary network. The most common variant, MacTel type 2, has distinct clinical features and management strategies. Methods: This study offers a comprehensive review of MacTel and [...] Read more.
Background: Macular telangiectasia (MacTel), also known as idiopathic juxtafoveolar telangiectasis (IJFTs), involves telangiectatic changes in the macular capillary network. The most common variant, MacTel type 2, has distinct clinical features and management strategies. Methods: This study offers a comprehensive review of MacTel and focuses on a series of three patients diagnosed with MacTel type 2 in our clinic. A meticulous ophthalmological evaluation, augmented by high-resolution imaging techniques like optical coherence tomography (OCT), OCT angiography (OCT-A), fundus autofluorescence (FAF), fluorescein angiography (FA), and adaptive optics (AOs) imaging, was conducted. Results: The findings revealed normal anterior segment features and a grayish discoloration in the temporal perifoveal area on fundus examination. OCT exhibited hyporeflective cavities in the inner and outer neurosensory retina, along with other changes, while OCT-A identified retinal telangiectatic vessels in the deep capillary plexus. FAF demonstrated increased foveal autofluorescence, while FA initially detected telangiectatic capillaries followed by diffuse perilesional leakage in the later phase. Adaptive optics images showed the cone mosaic pattern. Notably, one patient developed a macular hole as a complication, which was successfully managed surgically. Conclusion: This study underscores the challenges in diagnosing and managing MacTel, emphasizing the importance of a multidisciplinary approach and regular follow-ups for optimal outcomes. Full article
(This article belongs to the Special Issue Diagnostics for Ocular Diseases: Its Importance in Patient Care)
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Figure 1

Figure 1
<p>(<b>a</b>) OCT image of RE; (<b>b</b>) OCT-A image of RE; (<b>c</b>) OCT image of LE; (<b>d</b>) OCT-A image of LE; (<b>e</b>) FAF of RE; (<b>f</b>) FAF of LE; (<b>g</b>) FA—early phases of RE; (<b>h</b>) FA—early phases of LE; (<b>i</b>) FA—late phase of RE (<b>j</b>) FA—late phase of LE; (<b>k</b>) AO image of RE photoreceptors; and (<b>l</b>) AO image of LE photoreceptors. The lines in b and d represents the OCT image slice navigators.</p> Full article ">Figure 2
<p>(<b>a</b>) OCT image of RE; (<b>b</b>) OCT-A image of RE; (<b>c</b>) OCT image of LE; (<b>d</b>) OCT-A image of LE; (<b>e</b>) FAF of RE; (<b>f</b>) FAF of LE; (<b>g</b>) FA—early phase of RE; (<b>h</b>) FA—early phases of LE; (<b>i</b>) FA—late phase of RE (<b>j</b>) FA—late phase of LE; (<b>k</b>) AO image of RE photoreceptors; and (<b>l</b>) AO image of LE photoreceptors. The lines in b and d represents the OCT image slice navigators.</p> Full article ">Figure 3
<p>(<b>a</b>) OCT image of RE; (<b>b</b>) OCT-A image of RE; (<b>c</b>) OCT image of LE; (<b>d</b>) OCT-A image of LE; (<b>e</b>) FAF of RE; (<b>f</b>) FAF of LE; (<b>g</b>) FA—early phases of RE; (<b>h</b>) FA—early phases of LE; (<b>i</b>) FA—late phase of RE (<b>j</b>) FA—late phase of LE; (<b>k</b>) AO image of RE photoreceptors; and (<b>l</b>) AO image of LE photoreceptors. The lines in b and d represents the OCT image slice navigators.</p> Full article ">Figure 4
<p>(<b>a</b>) LE OCT captured one year after the initial visit, showing the progression into a macular hole with a positive “ILM drape” sign; (<b>b</b>) LE OCT captured one month after vitrectomy.</p> Full article ">Figure 5
<p>(<b>a</b>) RE OCT showing the progression into a macular hole with a positive “ILM drape” sign; (<b>b</b>) RE OCT of RE captured one month after vitrectomy.</p> Full article ">
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