In Frontiers in medicine
PURPOSE : To determine the characteristics influence of key histological on 18F-fluorodeoxyglucose (18F-FDG) and 18F-choline positron emission tomography (PET) positivity in hepatocellular carcinoma (HCC).
MATERIALS AND METHODS : The 18F-FDG/18F-choline PET imaging findings of 103 histologically proven HCCs (from 62 patients, of which 47 underwent hepatectomy and 15 received liver transplantation) were retrospectively examined to assess the following key histological parameters: Grade, capsule, microvascular invasion (mVI), macrovascular invasion (MVI), and necrosis. Using a ratio of 70/30 for training and testing sets, respectively, a penalized classification model (Elastic Net) was trained using 100 repeated cross-validation procedures (10-fold cross-validation for hyperparameter optimization). The contribution of each histological parameter to the PET positivity was determined using the Shapley Additive Explanations method. Receiver operating characteristic curves with and without dimensionality reduction were finally estimated and compared.
RESULTS : Among the five key histological characteristics of HCC (Grade, capsule, mVI, MVI, and necrosis), mVI and tumor Grade (I-III) showed the highest relevance and robustness in explaining HCC uptake of 18F-FDG and 18F-choline. MVI and necrosis status both showed high instability in outcome predictions. Tumor capsule had a minimal influence on the model predictions. On retaining only mVI and Grades I-III for the final analysis, the area under the receiver operating characteristic (ROC) curve values were maintained (0.68 vs. 0.63, 0.65 vs. 0.64, and 0.65 vs. 0.64 for 18F-FDG, 18F-choline, and their combination, respectively).
CONCLUSION : 18F-FDG/18F-choline PET positivity appears driven by both the Grade and mVI components in HCC. Consideration of the tumor microenvironment will likely be necessary to improve our understanding of multitracer PET positivity.
Ghidaglia Jérôme, Laurent Vincent, Sebagh Mylène, Pascale Alina, Durand Emmanuel, Golse Nicolas, Besson Florent L
2023
18F-FDG, 18F-choline, PET/CT, hepatocellular carcinoma, machine learning
