Artificial intelligence and different image modalities in Uveal Melanoma diagnosis and prognosis: A narrative review.

Photodiagnosis and photodynamic therapy Pub Date : 2025-02-20 DOI:10.1016/j.pdpdt.2025.104528

Atefeh Tahmasebzadeh, Mahdi Sadeghi, Masood Naseripour, Reza Mirshahi, Reza Ghaderi

{"title":"Artificial intelligence and different image modalities in Uveal Melanoma diagnosis and prognosis: A narrative review.","authors":"Atefeh Tahmasebzadeh, Mahdi Sadeghi, Masood Naseripour, Reza Mirshahi, Reza Ghaderi","doi":"10.1016/j.pdpdt.2025.104528","DOIUrl":null,"url":null,"abstract":"Background: The most widespread primary intraocular tumor in adults is called uveal melanoma (UM), if detected early enough, it can be curable. Various methods are available to treat UM, but the most commonly used and effective approach is plaque radiotherapy using Iodine-125 and Ruthenium-106.Method: The authors performed searches to distinguish relevant studies from 2017 to 2024 by three databases (PubMed, Scopus, and Google Scholar).Results: Imaging technologies such as Ultrasound (US), Fundus Photography (FP), Optical Coherent Tomography (OCT), Fluorescein Angiography (FA), and Magnetic Resonance Images (MRI) play a vital role in the diagnosis and prognosis of UM. The present review assessed the power of different image modalities when integrated with artificial intelligence (AI) to diagnose and prognosis of patients affected by UM.Conclusion: Finally, after reviewing the studies conducted, it was concluded that AI is a developing tool in image analysis and enhances workflows in diagnosis from data and image processing to clinical decisions, improving tailored treatment scenarios, response prediction, and prognostication.","PeriodicalId":94170,"journal":{"name":"Photodiagnosis and photodynamic therapy","volume":" ","pages":"104528"},"PeriodicalIF":0.0000,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Photodiagnosis and photodynamic therapy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.pdpdt.2025.104528","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

Abstract

Background: The most widespread primary intraocular tumor in adults is called uveal melanoma (UM), if detected early enough, it can be curable. Various methods are available to treat UM, but the most commonly used and effective approach is plaque radiotherapy using Iodine-125 and Ruthenium-106.

Method: The authors performed searches to distinguish relevant studies from 2017 to 2024 by three databases (PubMed, Scopus, and Google Scholar).

Results: Imaging technologies such as Ultrasound (US), Fundus Photography (FP), Optical Coherent Tomography (OCT), Fluorescein Angiography (FA), and Magnetic Resonance Images (MRI) play a vital role in the diagnosis and prognosis of UM. The present review assessed the power of different image modalities when integrated with artificial intelligence (AI) to diagnose and prognosis of patients affected by UM.

Conclusion: Finally, after reviewing the studies conducted, it was concluded that AI is a developing tool in image analysis and enhances workflows in diagnosis from data and image processing to clinical decisions, improving tailored treatment scenarios, response prediction, and prognostication.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

求助全文

约1分钟内获得全文去求助

来源期刊

Photodiagnosis and photodynamic therapy

自引率

0.00%

发文量