Abstract
Background
Predicting clinical outcomes represents a major challenge in Crohn's disease (CD).
Radiomics provides a method to extract quantitative features from medical images and
may successfully predict clinical course.
Aims
The aim of this pilot study is to evaluate the use of radiomics to predict 10-year
surgery for CD patients.
Methods
We selected a cohort of CD patients with CT scan enterographies and a 10-year follow
up. The R library Moddicom was used to extract radiomic features from each lesion
of CD, segmented in the CT scans. A logistic regression model based on selected radiomic
features was developed to predict 10-year surgery. The model was evaluated by computing
the area under the curve (AUC) of the receiver operating characteristic curve, sensitivity,
specificity, positive and negative predictive values (PPV, NPV).
Results
We enroled 30 patients, with 44 CT scans and 93 lesions. We extracted 217 radiomic
features from each lesion. The developed model was based on two radiomic features
and presented an AUC (95% CI) of 0.83 (0.73–0.91) in predicting 10-year surgery. Sensitivity,
specificity, PPV, NPV of the radiomic model were equal to 0.72, 0.90, 0.79, 0.86,
respectively.
Conclusion
Radiomics could be a helpful tool to identify patients with high risk for surgery
and needing a stricter monitoring.
Keywords
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Article info
Publication history
Published online: November 24, 2022
Accepted:
November 7,
2022
Received:
June 15,
2022
Publication stage
In Press Corrected ProofIdentification
Copyright
© 2022 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.
