Predicting the early response to neoadjuvant chemotherapy in high-grade serous ovarian cancer by intratumoral habitat heterogeneity based on 18F-FDG PET/CT. - Liu, Zhuonan; Mouni, Dhirendra; Zhang, Shimin; Du, Tianming; Li, Chen; Grzegorzek, Marcin; Sun, Hongzan (European Journal of Nuclear Medicine & Molecular Imaging, 2026)
Objective: To explore the predictive value of intratumoral habitat heterogeneity for the early therapeutic response to neoadjuvant chemotherapy (NACT) in patients with high-grade serous ovarian cancer (HGSOC). Materials and methods: A total of 258 patients with HGSOC receiving [18F]fluorodeoxyglucose ([18F]FDG) PET/CT followed by NACT were enrolled and classified into a response group and a non-response group according to RECIST 1.1. The primary tumor lesion was automatically segmented by the nnU-Net. Habitat subregions of the tumor were segmented by the best method in K-means, DBSCAN, and Otsu. Heterogeneity features were extracted based on radiomics and selected by recursive feature elimination to develop the subregion model, the traditional model, and the union model. The performance of the models was evaluated by the receiver operating characteristic curve and DeLong test, and Pearson correlation analysis was used to explore the relationships between radiomics features and pathological parameters. Results: The automatic segmentation model had a Dice coefficient of 0.82 and showed excellent performance in the validation cohort. The predictive efficacy of the subregion model in the test dataset was significantly better than that of the traditional model [Area Under the Curve (AUC): 0.83 vs. 0.71, P = 0.007. There was no statistically significant difference between the union model and the subregion model (AUC: 0.89 vs. 0.83, P = 0.077). Radiomics features involved in the modeling were significantly correlated with Ki67 before NACT (pre-Ki67) and the change value of Ki67 before NACT-after IDS(ΔKi67) respectively (P < 0.05). Conclusion: The PET/CT radiomics model based on habitat analysis can effectively predict the early response to NACT in patients with HGSOC, which can be explained by the tumor proliferative activity and provide reliable imaging biomarkers for individualized treatment decisions.