1. Lesion-Based Radiomics Signature in Pretherapy 18F-FDG PET Predicts Treatment Response to Ibrutinib in Lymphoma
- Author
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Jorge E. Jimenez, Dong Dai, Guofan Xu, Ruiyang Zhao, Tengfei Li, Tinsu Pan, Linghua Wang, Yingyan Lin, Zhangyang Wang, David Jaffray, John D. Hazle, Homer A. Macapinlac, Jia Wu, and Yang Lu
- Subjects
Lymphoma ,Piperidines ,Fluorodeoxyglucose F18 ,Adenine ,Positron Emission Tomography Computed Tomography ,Humans ,Radiology, Nuclear Medicine and imaging ,General Medicine ,Article ,Retrospective Studies - Abstract
PURPOSE: To develop a pretherapy PET/CT-based prediction model for treatment response to ibrutinib in lymphoma patients. MATERIALS AND METHODS: One hundred sixty-nine lymphoma patients with 2441 lesions were studied retrospectively. All eligible lymphomas on pretherapy (18)F-FDG PET images were contoured and segmented for radiomic analysis. Lesion- and patient-based responsiveness to ibrutinib were determined retrospectively using the Lugano classification. PET radiomic features were extracted. A radiomic model was built to predict ibrutinib response. The prognostic significance of the radiomic model was evaluated independently in a test cohort and compared with conventional PET metrics: maximum standard uptake value (SUV(max)), metabolic tumor volume (MTV), and total lesion glycolysis (TLG). RESULTS: The radiomic model had an area under the receiver operating characteristic curve (ROC AUC) of 0.860 (sensitivity, 92.9%, specificity, 81.4%; P < 0.001) for predicting response to ibrutinib, outperforming the SUV(max) (ROC AUC, 0.519; P = 0.823), MTV (ROC AUC, 0.579; P = 0.412), TLG (ROC AUC, 0.576; P = 0.199), and a composite model built using all three (ROC AUC, 0.562; P = 0.046). The radiomic model increased the probability of accurately predicting ibrutinib-responsive lesions from 84.8% (pretest) to 96.5% (posttest). At the patient level, the model’s performance (ROC AUC = 0.811; P = 0.007) was superior to that of conventional PET metrics. Furthermore, the radiomics model showed robustness when validated in treatment subgroups: first (ROC AUC, 0.916; P < 0.001) versus second or greater (ROC AUC, 0.842; P < 0.001) line of defense and single treatment (ROC AUC, 0.931; P < 0.001) versus multiple treatments (ROC AUC, 0.824; P < 0.001). CONCLUSIONS: We developed and validated a pretherapy PET-based radiomic model to predict response to treatment with ibrutinib in a diverse cohort of lymphoma patients.
- Published
- 2023