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

IF 2.8
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 ,&nbsp;Lawrence Lo ,&nbsp;Meera Sury ,&nbsp;Sara M. Bahouth ,&nbsp;Ming Yin ,&nbsp;Lena F. Schaefer ,&nbsp;Jamie E. Collins ,&nbsp;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 ,&nbsp;Lawrence Lo ,&nbsp;Meera Sury ,&nbsp;Sara M. Bahouth ,&nbsp;Ming Yin ,&nbsp;Lena F. Schaefer ,&nbsp;Jamie E. Collins ,&nbsp;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}
引用次数: 0

摘要

目的利用基于软件的磁共振成像(MRI)测量膝关节骨关节炎(KOA)的多种特征来预测KOA患者的放射学和疼痛进展,并与主要使用半定量(SQ)评分的研究进行比较。设计数据来自美国国立卫生研究院骨关节炎生物标志物联盟基金会(FNIH)巢式病例对照研究(600名受试者根据膝关节疼痛和/或放射学进展分为病例组和对照组)。MRI骨关节炎软件评分(MOSS)用于定量评估股骨内侧软骨、骨髓病变、骨赘体积、积液-滑膜炎体积,并使用具有不同专业水平的读者在基线和24个月时测量Hoffa滑膜炎。检查基线和基线至24个月变化与进展状态之间的关系,并使用10倍交叉验证计算的c统计量(AUC)评估判别能力。结果预测疼痛/影像学进展的auc值在0.690 ~ 0.726之间,单独预测影像学进展的auc值在0.709 ~ 0.804之间。骨髓病变和骨赘体积在所有分析中都起作用。除了涉及疼痛进展的横截面分析外,股骨内侧软骨在所有情况下都很重要。与独立出版物的结果比较表明,MOSS与主要使用SQ评分的已发表模型提供了类似的歧视。结论:我们发现了高度的歧视,特别是在放射学进展分析中。使用快速自动化软件和具有不同先前经验的读者使MOSS成为丰富未来临床试验和其他大型KOA研究的有用工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Osteoarthritis and cartilage open
Osteoarthritis and cartilage open Orthopedics, Sports Medicine and Rehabilitation
CiteScore
3.30
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信