Stacy E. Smith , Lawrence Lo , Meera Sury , Sara M. Bahouth , Ming Yin , Lena F. Schaefer , Jamie E. Collins , Jeffrey Duryea
{"title":"在一项病例对照研究中对膝关节骨关节炎的多重mri定量结构测量进行分析——与疼痛和结构进展的关联以及与半定量评分的比较","authors":"Stacy E. Smith , Lawrence Lo , Meera Sury , Sara M. Bahouth , Ming Yin , Lena F. Schaefer , Jamie E. Collins , Jeffrey Duryea","doi":"10.1016/j.ocarto.2025.100638","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><div>To use software-based magnetic resonance imaging (MRI) measures of multiple features of knee osteoarthritis (KOA) to predict radiographic and pain progression in persons with KOA, and compare to a study that used primarily semi-quantitative (SQ) scoring.</div></div><div><h3>Design</h3><div>Data from the Foundation for the National Institutes of Health Osteoarthritis Biomarkers Consortium (FNIH) nested case-control study (600 subjects divided into case and control groups based on knee pain and/or radiographic progression) were used. The MRI Osteoarthritis Software Scoring (MOSS) was used to quantitatively assess medial femoral cartilage, bone marrow lesions, osteophyte volume, effusion-synovitis volume, and a measure of Hoffa's synovitis at baseline and 24-months using readers with diverse levels of expertise. Association between baseline and baseline to 24-month change with progressor status was examined and discriminative ability assessed using the c-statistic (AUC) computed under 10-fold cross validation.</div></div><div><h3>Results</h3><div>AUC values ranged from 0.690 to 0.726 to predict combined pain/radiographic progression and from 0.709 to 0.804 to predict radiographic progression alone. Bone marrow lesions and osteophyte volume played a role in all analyses. Medial femoral cartilage was significant for all but the cross-sectional analysis involving pain progression. Comparison to results from a separate publication showed that MOSS offered similar discrimination to a published model that primarily used SQ scoring.</div></div><div><h3>Conclusions</h3><div>We found a high level of discrimination particularly for radiographic progression analysis. Use of fast automated software and readers with varied prior experience make MOSS a useful tool for enriching future clinical trials and for other large studies of KOA.</div></div>","PeriodicalId":74377,"journal":{"name":"Osteoarthritis and cartilage open","volume":"7 3","pages":"Article 100638"},"PeriodicalIF":2.8000,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of multiple MRI-based quantitative structural measurements of knee osteoarthritis in a case control study – association with pain and structural progression and comparison to semi-quantitative scoring\",\"authors\":\"Stacy E. Smith , Lawrence Lo , Meera Sury , Sara M. Bahouth , Ming Yin , Lena F. Schaefer , Jamie E. Collins , Jeffrey Duryea\",\"doi\":\"10.1016/j.ocarto.2025.100638\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objective</h3><div>To use software-based magnetic resonance imaging (MRI) measures of multiple features of knee osteoarthritis (KOA) to predict radiographic and pain progression in persons with KOA, and compare to a study that used primarily semi-quantitative (SQ) scoring.</div></div><div><h3>Design</h3><div>Data from the Foundation for the National Institutes of Health Osteoarthritis Biomarkers Consortium (FNIH) nested case-control study (600 subjects divided into case and control groups based on knee pain and/or radiographic progression) were used. The MRI Osteoarthritis Software Scoring (MOSS) was used to quantitatively assess medial femoral cartilage, bone marrow lesions, osteophyte volume, effusion-synovitis volume, and a measure of Hoffa's synovitis at baseline and 24-months using readers with diverse levels of expertise. Association between baseline and baseline to 24-month change with progressor status was examined and discriminative ability assessed using the c-statistic (AUC) computed under 10-fold cross validation.</div></div><div><h3>Results</h3><div>AUC values ranged from 0.690 to 0.726 to predict combined pain/radiographic progression and from 0.709 to 0.804 to predict radiographic progression alone. Bone marrow lesions and osteophyte volume played a role in all analyses. Medial femoral cartilage was significant for all but the cross-sectional analysis involving pain progression. Comparison to results from a separate publication showed that MOSS offered similar discrimination to a published model that primarily used SQ scoring.</div></div><div><h3>Conclusions</h3><div>We found a high level of discrimination particularly for radiographic progression analysis. Use of fast automated software and readers with varied prior experience make MOSS a useful tool for enriching future clinical trials and for other large studies of KOA.</div></div>\",\"PeriodicalId\":74377,\"journal\":{\"name\":\"Osteoarthritis and cartilage open\",\"volume\":\"7 3\",\"pages\":\"Article 100638\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2025-06-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Osteoarthritis and cartilage open\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2665913125000743\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Osteoarthritis and cartilage open","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2665913125000743","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of multiple MRI-based quantitative structural measurements of knee osteoarthritis in a case control study – association with pain and structural progression and comparison to semi-quantitative scoring
Objective
To use software-based magnetic resonance imaging (MRI) measures of multiple features of knee osteoarthritis (KOA) to predict radiographic and pain progression in persons with KOA, and compare to a study that used primarily semi-quantitative (SQ) scoring.
Design
Data from the Foundation for the National Institutes of Health Osteoarthritis Biomarkers Consortium (FNIH) nested case-control study (600 subjects divided into case and control groups based on knee pain and/or radiographic progression) were used. The MRI Osteoarthritis Software Scoring (MOSS) was used to quantitatively assess medial femoral cartilage, bone marrow lesions, osteophyte volume, effusion-synovitis volume, and a measure of Hoffa's synovitis at baseline and 24-months using readers with diverse levels of expertise. Association between baseline and baseline to 24-month change with progressor status was examined and discriminative ability assessed using the c-statistic (AUC) computed under 10-fold cross validation.
Results
AUC values ranged from 0.690 to 0.726 to predict combined pain/radiographic progression and from 0.709 to 0.804 to predict radiographic progression alone. Bone marrow lesions and osteophyte volume played a role in all analyses. Medial femoral cartilage was significant for all but the cross-sectional analysis involving pain progression. Comparison to results from a separate publication showed that MOSS offered similar discrimination to a published model that primarily used SQ scoring.
Conclusions
We found a high level of discrimination particularly for radiographic progression analysis. Use of fast automated software and readers with varied prior experience make MOSS a useful tool for enriching future clinical trials and for other large studies of KOA.