A machine learning-based radiomics approach for differentiating patellofemoral osteoarthritis from non-patellofemoral osteoarthritis using Q-Dixon MRI

A machine learning-based radiomics approach for differentiating patellofemoral osteoarthritis from non-patellofemoral osteoarthritis using Q-Dixon MRI

This prospective diagnostic study aimed to assess the utility of machine learning-based quadriceps fat pad (QFP) radiomics in distinguishing patellofemoral osteoarthritis (PFOA) from non-PFOA using Q-Dixon MRI in patients presenting with anterior knee pain. This diagnostic accuracy study retrospecti...

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Bibliographic Details
Main Authors: Liangjing Lyu, Jing Ren, Wenjie Lu, Jingyu Zhong, Yang Song, Yongliang Li, Weiwu Yao
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-01-01
Series:Frontiers in Sports and Active Living
Subjects:
anterior knee pain
patellofemoral osteoarthritis
Q-Dixon MRI
radiomics
machine learning
fat fraction
Online Access:https://www.frontiersin.org/articles/10.3389/fspor.2025.1535519/full
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https://www.frontiersin.org/articles/10.3389/fspor.2025.1535519/full

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