New Advances in Diagnostic and Surgical Treatment of Ocular Diseases

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Clinical Medicine, Cell, and Organism Physiology".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 2163

Special Issue Editor


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Guest Editor
Department of Ophthalmology, University of Medicine and Pharmacy “Grigore T. Popa”, 700115 Iasi, Romania
Interests: vitreoretinal surgery; macular diseases; intraocular inflammation; ocular trauma; intravitreal therapies

Special Issue Information

Dear Colleagues,

I am delighted to introduce “New Advances in Diagnostic and Surgical Treatment of Ocular Diseases”, a new Special Issue of the Journal of Personalized Medicine (JPM) dedicated to understanding the innovative diagnosis and management of ocular disease.

With the rapid development of surgical techniques, medical equipment, and biological materials, the field of clinical ophthalmology has altered dramatically in recent decades. Advances in surgical techniques and instruments have improved not only clinical outcomes but also diagnostic accuracy, with new treatment options making surgery safer, faster, and more precise. This Special Issue aims to create a multidisciplinary forum of discussion about the role of diagnostic and surgical procedures in the different subfields of ophthalmology.

The published papers will describe new developments in these areas. We would like to include discussions of topics relevant to the study of innovative diagnostic approaches, surgical procedures, medical equipment, and biological materials of the ocular conditions. These can include, but are not limited to, refractive errors, cataracts, retinal vascular disease, retinal detachment, macular degeneration, glaucoma, and uveitis.

Dr. Ciprian Danielescu
Guest Editor

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. Journal of Personalized Medicine is an international peer-reviewed open access monthly 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 diseases

  • diagnostic approaches
  • surgical procedures
  • medical equipment
  • biological materials

Published Papers (2 papers)

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Review

18 pages, 967 KiB  
Review
Non-Invasive Retinal Vessel Analysis as a Predictor for Cardiovascular Disease
by Raluca Eugenia Iorga, Damiana Costin, Răzvana Sorina Munteanu-Dănulescu, Elena Rezuș and Andreea Dana Moraru
J. Pers. Med. 2024, 14(5), 501; https://doi.org/10.3390/jpm14050501 - 9 May 2024
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Abstract
Cardiovascular disease (CVD) is the most frequent cause of death worldwide. The alterations in the microcirculation may predict the cardiovascular mortality. The retinal vasculature can be used as a model to study vascular alterations associated with cardiovascular disease. In order to quantify microvascular [...] Read more.
Cardiovascular disease (CVD) is the most frequent cause of death worldwide. The alterations in the microcirculation may predict the cardiovascular mortality. The retinal vasculature can be used as a model to study vascular alterations associated with cardiovascular disease. In order to quantify microvascular changes in a non-invasive way, fundus images can be taken and analysed. The central retinal arteriolar (CRAE), the venular (CRVE) diameter and the arteriolar-to-venular diameter ratio (AVR) can be used as biomarkers to predict the cardiovascular mortality. A narrower CRAE, wider CRVE and a lower AVR have been associated with increased cardiovascular events. Dynamic retinal vessel analysis (DRVA) allows the quantification of retinal changes using digital image sequences in response to visual stimulation with flicker light. This article is not just a review of the current literature, it also aims to discuss the methodological benefits and to identify research gaps. It highlights the potential use of microvascular biomarkers for screening and treatment monitoring of cardiovascular disease. Artificial intelligence (AI), such as Quantitative Analysis of Retinal vessel Topology and size (QUARTZ), and SIVA–deep learning system (SIVA-DLS), seems efficient in extracting information from fundus photographs and has the advantage of increasing diagnosis accuracy and improving patient care by complementing the role of physicians. Retinal vascular imaging using AI may help identify the cardiovascular risk, and is an important tool in primary cardiovascular disease prevention. Further research should explore the potential clinical application of retinal microvascular biomarkers, in order to assess systemic vascular health status, and to predict cardiovascular events. Full article
(This article belongs to the Special Issue New Advances in Diagnostic and Surgical Treatment of Ocular Diseases)
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19 pages, 367 KiB  
Review
Automated Retinal Vessel Analysis Based on Fundus Photographs as a Predictor for Non-Ophthalmic Diseases—Evolution and Perspectives
by Ciprian Danielescu, Marius Gabriel Dabija, Alin Horatiu Nedelcu, Vasile Valeriu Lupu, Ancuta Lupu, Ileana Ioniuc, Georgiana-Emmanuela Gîlcă-Blanariu, Vlad-Constantin Donica, Maria-Luciana Anton and Ovidiu Musat
J. Pers. Med. 2024, 14(1), 45; https://doi.org/10.3390/jpm14010045 - 29 Dec 2023
Cited by 1 | Viewed by 1290
Abstract
The study of retinal vessels in relation to cardiovascular risk has a long history. The advent of a dedicated tool based on digital imaging, i.e., the retinal vessel analyzer, and also other software such as Integrative Vessel Analysis (IVAN), Singapore I Vessel Assessment [...] Read more.
The study of retinal vessels in relation to cardiovascular risk has a long history. The advent of a dedicated tool based on digital imaging, i.e., the retinal vessel analyzer, and also other software such as Integrative Vessel Analysis (IVAN), Singapore I Vessel Assessment (SIVA), and Vascular Assessment and Measurement Platform for Images of the Retina (VAMPIRE), has led to the accumulation of a formidable body of evidence regarding the prognostic value of retinal vessel analysis (RVA) for cardiovascular and cerebrovascular disease (including arterial hypertension in children). There is also the potential to monitor the response of retinal vessels to therapies such as physical activity or bariatric surgery. The dynamic vessel analyzer (DVA) remains a unique way of studying neurovascular coupling, helping to understand the pathogenesis of cerebrovascular and neurodegenerative conditions and also being complementary to techniques that measure macrovascular dysfunction. Beyond cardiovascular disease, retinal vessel analysis has shown associations with and prognostic value for neurological conditions, inflammation, kidney function, and respiratory disease. Artificial intelligence (AI) (represented by algorithms such as QUantitative Analysis of Retinal vessel Topology and siZe (QUARTZ), SIVA-DLS (SIVA—deep learning system), and many others) seems efficient in extracting information from fundus photographs, providing prognoses of various general conditions with unprecedented predictive value. The future challenges will be integrating RVA and other qualitative and quantitative risk factors in a unique, comprehensive prediction tool, certainly powered by AI, while building the much-needed acceptance for such an approach inside the medical community and reducing the “black box” effect, possibly by means of saliency maps. Full article
(This article belongs to the Special Issue New Advances in Diagnostic and Surgical Treatment of Ocular Diseases)
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