Evidence map›Paper›PMID 40478773›Full record

ArticleRheumatology (Oxford, England)2025

MRI-based patient-specific nomogram for diagnostic risk stratification of patients with early knee OA.

Zhijian Yang, Huiwen Lu, Zhaowei Lin, Weiwen Zhu, Haopeng Guo, Chao Xie

Abstract read
In one paragraph

Article in Rheumatology (Oxford, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Zhijian YangDepartment of Joint Surgery, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, P. R. China.
Huiwen LuDepartment of Traditional Chinese Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, P. R. China.
Zhaowei LinDepartment of Joint and Orthopedics, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, P. R. China.
Weiwen ZhuGuangdong Provincial Key Laboratory of Orthopedics and Traumatology, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, P. R. China.
Haopeng GuoDepartment of Joint and Orthopedics, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, P. R. China.
Chao XieDepartment of Joint and Orthopedics, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, P. R. China.ORCID 0000-0001-6479-9825

Funding

Medical Scientific Research Foundation of Guangdong Province of China A2023083Presidential Foundation of Zhujiang Hospital yzjj2023qn03
6 · The paper itself

Abstract

objectivesThis study is to develop a risk stratification nomogram for early-stage OA based on MRI, especially with potential sequences of MRI called T1rho and T2 mapping.

methodsCartilages diagnosed with early-stage OA or normal were collected and allocated into training or validation cohorts after the MRI. Eleven predictors were determined as candidate predictors for OA-anatomical signature-nomogram (OA-ASN). The performance of OA-ASN was evaluated using the concordance index (C-index), the area under the receiver operating characteristic curve (AUC), calibration plots, decision curve analysis (DCA) and clinical impact curve (CIC).

resultsA total of 199 patients were evaluated. Of these, 79 (39.7%) had early OA. Infrapatellar fat pad (IPFP), T1 rho and T2 mapping were independently associated with early-stage OA at multivariable analysis. The nomogram incorporating these variables displayed excellent discrimination (C-index, 0.975; 95% CI: 0.951, 0.999) in the training sample (n = 115) and bootstrap validation (C-index, 0.96), while C-index was 0.904 (95% CI: 0.840, 0.959) in the validation cohort (n = 84). The calibration plots showed favourable consistency between the prediction of the nomogram and actual observations in both the training and validation cohorts. The DCA and CIC showed that the nomogram was clinically useful.

conclusionsA smaller volume of IPFP, T1ρ value >33 and T2 mapping >35.04 were significantly associated with OA. The OA-ASN demonstrated excellent predictive outcomes with easy-accessible and simple observational screening methods based on physiological MRI, which can provide individual treatment strategies.

Indexed as

Magnetic Resonance ImagingNomogramsOsteoarthritis, KneeAdultAgedFemaleHumansMaleMiddle AgedRisk AssessmentROC Curvecartilageearly-stage OAMRInomogramphysiological biomarkers

Identifiers

PMID40478773
PMCPMC12494199

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