Lina Xu, Keno Bressem, Lisa Adams, Denis Poddubnyy, Fabian Proft
{"title":"人工智能在风湿病成像评估中的应用:放射组学和计算机视觉的应用现状、未来前景和潜在挑战","authors":"Lina Xu, Keno Bressem, Lisa Adams, Denis Poddubnyy, Fabian Proft","doi":"10.1093/rap/rkae147","DOIUrl":null,"url":null,"abstract":"<p><p>Inflammatory rheumatic diseases, a diverse group of immune-mediated conditions, are characterized by chronic inflammation that can lead to irreversible damage to joints, bones and organs, posing a significant global health challenge. If left untreated, these conditions can severely deteriorate patients' quality of life, underscoring the importance of timely and accurate diagnosis and appropriate management. Artificial intelligence (AI), including radiomics and computer vision, presents promising advancements in improving the early diagnosis and monitoring of these diseases through the analysis of various imaging modalities such as X-rays, CT scans, MRIs and ultrasounds. This review examines the current state of AI applications in the imaging analysis of inflammatory rheumatic diseases, including RA, SpA, SS, SSc and GCA. AI has demonstrated encouraging results, achieving high sensitivity, specificity and accuracy, often on par with or exceeding expert performance. The review also highlights future opportunities for improving the diagnosis and management of rheumatic diseases, as well as the challenges associated with their clinical implementation.</p>","PeriodicalId":21350,"journal":{"name":"Rheumatology Advances in Practice","volume":"9 2","pages":"rkae147"},"PeriodicalIF":2.1000,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12007601/pdf/","citationCount":"0","resultStr":"{\"title\":\"AI for imaging evaluation in rheumatology: applications of radiomics and computer vision-current status, future prospects and potential challenges.\",\"authors\":\"Lina Xu, Keno Bressem, Lisa Adams, Denis Poddubnyy, Fabian Proft\",\"doi\":\"10.1093/rap/rkae147\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Inflammatory rheumatic diseases, a diverse group of immune-mediated conditions, are characterized by chronic inflammation that can lead to irreversible damage to joints, bones and organs, posing a significant global health challenge. If left untreated, these conditions can severely deteriorate patients' quality of life, underscoring the importance of timely and accurate diagnosis and appropriate management. Artificial intelligence (AI), including radiomics and computer vision, presents promising advancements in improving the early diagnosis and monitoring of these diseases through the analysis of various imaging modalities such as X-rays, CT scans, MRIs and ultrasounds. This review examines the current state of AI applications in the imaging analysis of inflammatory rheumatic diseases, including RA, SpA, SS, SSc and GCA. AI has demonstrated encouraging results, achieving high sensitivity, specificity and accuracy, often on par with or exceeding expert performance. The review also highlights future opportunities for improving the diagnosis and management of rheumatic diseases, as well as the challenges associated with their clinical implementation.</p>\",\"PeriodicalId\":21350,\"journal\":{\"name\":\"Rheumatology Advances in Practice\",\"volume\":\"9 2\",\"pages\":\"rkae147\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2025-04-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12007601/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Rheumatology Advances in Practice\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/rap/rkae147\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q3\",\"JCRName\":\"RHEUMATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Rheumatology Advances in Practice","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/rap/rkae147","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"RHEUMATOLOGY","Score":null,"Total":0}
AI for imaging evaluation in rheumatology: applications of radiomics and computer vision-current status, future prospects and potential challenges.
Inflammatory rheumatic diseases, a diverse group of immune-mediated conditions, are characterized by chronic inflammation that can lead to irreversible damage to joints, bones and organs, posing a significant global health challenge. If left untreated, these conditions can severely deteriorate patients' quality of life, underscoring the importance of timely and accurate diagnosis and appropriate management. Artificial intelligence (AI), including radiomics and computer vision, presents promising advancements in improving the early diagnosis and monitoring of these diseases through the analysis of various imaging modalities such as X-rays, CT scans, MRIs and ultrasounds. This review examines the current state of AI applications in the imaging analysis of inflammatory rheumatic diseases, including RA, SpA, SS, SSc and GCA. AI has demonstrated encouraging results, achieving high sensitivity, specificity and accuracy, often on par with or exceeding expert performance. The review also highlights future opportunities for improving the diagnosis and management of rheumatic diseases, as well as the challenges associated with their clinical implementation.