Purpose: This study investigated whether radiomic features extracted from [¹⁸F]FDG-PET scans acquired before and two weeks after neoadjuvant treatment, and their variation, provided prognostic parameters in locally advanced cervical cancer (LACC) patients treated with neoadjuvant chemo-radiotherapy (CRT) followed by radical surgery. Methods: We retrospectively included LACC patients referred to our Institution from 2010 to 2016. [¹⁸F]FDG-PET/CT was performed before neoadjuvant CRT (baseline) and two weeks after the start of treatment (early). Radiomic features were extracted after semi-automatic delineation of the primary tumour, on baseline and early PET images. Delta radiomics were calculated as the relative differences between baseline and early features. We performed 5-fold cross-validation stratified for recurrence and cancer-specific death, integrating dimensionality reduction of the radiomic features and variable hunting with importance within the folds. After supervised feature selection, radiomic models with the best-performing features for each timepoint, as well as clinical models and combined clinico-radiomic models, were built. Model performances are presented as C-indices, for prediction of recurrence/progression (disease-free survival, DFS) and cancer-specific death (overall survival, OS). Results: 95 patients were included. With a median follow-up of 76.0 months (95% CI: 59.5–82.1), 31.6% of patients had recurrence/progression and 20.0% died of disease. None of the models could predict DFS (C-indices ≤ 0.72). Model performances for OS yielded slightly better results, with mean C-indices of 0.75 for both the radiomic and combined model based on early features, 0.79 and 0.78 for the radiomic and combined model derived from delta features, and 0.76 for the clinical models. Conclusion: [¹⁸F]FDG-PET early and delta radiomic features could not predict DFS in patients with LACC treated with neoadjuvant CRT followed by radical surgery. Although slightly improved performances for the radiomic and combined models were observed in the prediction of OS compared to the clinical model, the added value of these parameters and their inclusion in the clinical practice seems to be limited.

Purpose: This study aims to systematically review and perform a meta-analysis to compare the diagnostic performance of fibroblast activation protein inhibitors (FAPI) radiopharmaceuticals and 2-deoxy-2-[¹⁸F]fluoro-D-glucose ([¹⁸F]FDG) in gynaecological cancers. Methods: A comprehensive search of PubMed/MEDLINE and EMBASE was conducted and updated to October 25, 2024, to identify clinical studies evaluating FAPI and [¹⁸F]FDG PET/CT or PET/MR in patients with gynaecological cancer. Quality was assessed using the QUADAS-2 tool (Quality Assessment of Diagnostic Accuracy Studies). Per-lesion pooled estimates of sensitivity, specificity, positive predictive value, and negative predictive value were calculated with 95% confidence intervals. Results: Ten studies were included for qualitative assessment and five studies focusing on ovarian cancer were included in the meta-analysis. The detection rates of primary cervical cancer ranged from 96 to 100% for both radiopharmaceuticals. For the primary tumour in ovarian cancer, the pooled sensitivities of ⁶⁸Ga-FAPI and [¹⁸F]FDG were 95% and 92%, and the pooled specificities were 81% for both radiopharmaceuticals. Nodal metastases detection was higher with ⁶⁸Ga-FAPI compared with [¹⁸F]FDG in cervical cancer. Similarly, in ovarian cancer the estimated pooled sensitivities of ⁶⁸Ga-FAPI and [¹⁸F]FDG were 97% and 88%, and the pooled specificities were 83% and 41%, respectively. At peritoneal metastases analysis in ovarian cancer, the pooled sensitivities of ⁶⁸Ga-FAPI and [¹⁸F]FDG were 97% and 70%, and the pooled specificities were 93% and 88%, respectively. At the visual assessment of peritoneal cancer scores, such as peritoneal cancer index, ⁶⁸Ga-FAPI detected a greater tumour burden compared with [¹⁸F]FDG. A comparative analysis of the PET semiquantitative parameters was also performed. Conclusion: Despite limited literature data, radiopharmaceuticals based on FAPIs are a promising alternative to [¹⁸F]FDG for imaging gynaecological cancers, in particular for the detection of nodal metastases in cervical and ovarian cancers, as well as for detecting peritoneal metastases in ovarian cancers. Larger prospective studies are needed to confirm these results and promote the inclusion of FAPI radiopharmaceuticals in clinical practice. Clinical trial number: Not applicable.

This study investigated whether radiomic features extracted from pretreatment [18F]FDG PET could improve the prediction of both histopathologic tumor response and survival in patients with locally advanced cervical cancer (LACC) treated with neoadjuvant chemoradiotherapy followed by surgery compared with conventional PET parameters and histopathologic features. Methods: The medical records of all consecutive patients with LACC referred between July 2010 and July 2016 were reviewed. [18F]FDG PET/CT was performed before neoadjuvant chemoradiotherapy. Radiomic features were extracted from the primary tumor volumes delineated semiautomatically on the PET images and reduced by factor analysis. A receiver-operating-characteristic analysis was performed, and conventional and radiomic features were dichotomized with Liu’s method according to pathologic response (pR) and cancer-specific death. According to the study protocol, only areas under the curve of more than 0.70 were selected for further analysis, including logistic regression analysis for response prediction and Cox regression analysis for survival prediction. Results: A total of 195 patients fulfilled the inclusion criteria. At pathologic evaluation after surgery, 131 patients (67.2%) had no or microscopic (≤3 mm) residual tumor (pR0 or pR1, respectively); 64 patients (32.8%) had macroscopic residual tumor (>3 mm, pR2). With a median follow-up of 76.0 mo (95% CI, 70.7–78.7 mo), 31.3% of patients had recurrence or progression and 20.0% died of the disease. Among conventional PET parameters, SUVmean significantly differed between pathologic responders and nonresponders. Among radiomic features, 1 shape and 3 textural features significantly differed between pathologic responders and nonresponders. Three radiomic features significantly differed between presence and absence of recurrence or progression and between presence and absence of cancer-specific death. Areas under the curve were less than 0.70 for all parameters; thus, univariate and multivariate regression analyses were not performed. Conclusion: In a large series of patients with LACC treated with neoadjuvant chemoradiotherapy followed by surgery, PET radiomic features could not predict histopathologic tumor response and survival. It is crucial to further explore the biologic mechanism underlying imaging-derived parameters and plan a large, prospective, multicenter study with standardized protocols for all phases of the process of radiomic analysis to validate radiomics before its use in clinical routine.