Rationale and Objectives
To use radiomics to detect the subtle changes of cartilage and subchondral bone in
chronic lateral ankle instability (CLAI) patients based on MRI PD-FS images.
Materials and Methods
A total of 215 CLAI patients and 186 healthy controls were included and randomly split
into a training set (n=281, patients/controls=151/130) and an independent test set (n=120, patients/controls=64/56). They underwent ankle MRI examinations. On sagittal
PD-FS images, eight cartilage regions and their corresponding subchondral bone regions
were drawn. Radiomics models of cartilage, subchondral bone and combined cartilage
and subchondral bone were built to differentiate CLAI patients from controls. A receiver
operating characteristic curve (ROC) was used to assess the model's performance.
Results
In the test dataset, the cartilage model yielded an area under the curve (AUC) of
0.0.912 (95% confidence interval (CI): 0.858-0.965, p<0.001), a sensitivity of 0.859, a specificity of 0.893, a negative predictive value
(NPV) of 0.848, and a positive predictive value (PPV) of 0.902. The subchondral bone
model yielded an AUC of 0.837 (95% CI: 0.766-0.907, p<0.001), a sensitivity of 0.875, a specificity of 0.714, an NPV of 0.833, and a PPV
of 0.778. For the combined model, the AUC was 0.921 (95% CI: 0.863-0.972, p<0.001), sensitivity was 0.844, specificity was 0.911, NPV was 0.836, and PPV was
0.915, whose AUC was higher than those of both the cartilage model and the subchondral
bone model.
Conclusion
The combined radiomics model achieved satisfying performance in detecting potential
early architectural changes in cartilage and subchondral bone for CLAI patients.
Keywords
Abbreviations:
CLAI (chronic lateral ankle instability), PD-FS (proton density with fat-suppression), ROC (Receiver operating characteristic curve), AUC (area under curve), CI (confidence interval), NPV (negative predictive value), PPV (positive predictive value), ATFL (anterior talofibular ligament), CFL (calcaneofibular ligament), OA (osteoarthritis), T1WI (T1-weighted imaging), T2WI (T2-weighted imaging), BMI (body mass index), OCL (osteochondral lesion), pSTJ (posterior subtalar joints), C-S (cartilage and subchondral), SMOTE (Synthetic Minority Oversampling Technique), PCC (Pearson Correlation Coefficient), RFE (Recursive Feature Elimination), SVM (support vector machine)To read this article in full you will need to make a payment
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Article info
Publication history
Published online: December 02, 2022
Accepted:
November 13,
2022
Received in revised form:
November 8,
2022
Received:
July 31,
2022
Publication stage
In Press Corrected ProofIdentification
Copyright
© 2022 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.