Objective
Metastatic castration-resistant prostate cancer (mCRPC) is a heterogeneous disease with varying survival outcomes. This study investigated whether baseline PSMA PET/CT parameters are associated with survival and treatment response.

Methods
Sixty mCRPC patients underwent [18F]PSMA-1007 PET/CT before treatment with androgen receptor-targeted agents (ARTAs) or chemotherapy. Intensity-based parameters, volumetric parameters, metastatic sites and DmaxVox (distance between the two outermost voxels) from baseline PSMA PET/CT were collected, as well as age, Gleason score and laboratory parameters. Cox regression analysis evaluated their prognostic value for overall survival (OS). Additionally, a preliminary lesion-level analysis was done (n = 241 lesions) with lesion location and twelve radiomic features selected from previous literature. Logistic regression evaluated their association with PSMA PET/CT-based lesion progression after 3–4 months of treatment.

Results
Total tumour volume (PSMA-TV) (HR = 1.41 per doubling [1.17–1.70]), total lesion uptake (TL-PSMA) (HR = 1.40 per doubling [1.16–1.69]) and DmaxVox (HR = 1.31 per 10 cm increase [1.07–1.62]) were prognostic for OS, each independent of baseline PSA level (HR = 0.82 per doubling [0.68–0.98]), haemoglobin level (HR = 0.68 per mmol/L increase [0.49–0.95]) and line of treatment. On lesion-level, location (prostate vs bone OR = 0.23 [0.06–0.83]) and SUVmean (OR = 1.72 per doubling [1.08–2.75]) were independent prognostic markers for lesion progression, morphological and texture-based radiomic features were not.

Conclusion
Baseline PSMA PET/CT scans have prognostic value in mCRPC patients and can potentially aid in treatment decision-making. DmaxVox can serve as a simpler alternative to PSMA-TV when automated segmentation software is not available. When combined with PSMA-TV, lower PSA levels indicated worse OS, which may be a marker of tumour dedifferentiation. Further research is needed to validate these models in larger patient cohorts.

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.

Background: Central necrosis can be detected on [¹⁸F]FDG PET/CT as a region with little to no tracer uptake. Currently, there is no consensus regarding the inclusion of regions of central necrosis during volume of interest (VOI) delineation for radiomic analysis. The aim of this study was to assess how central necrosis affects radiomic analysis in PET. Methods: Forty-three patients, either with non-small cell lung carcinomas (NSCLC, n = 12) or with pheochromocytomas or paragangliomas (PPGL, n = 31), were included retrospectively. VOIs were delineated with and without central necrosis. From all VOIs, 105 radiomic features were extracted. Differences in radiomic features between delineation methods were assessed using a paired t-test with Benjamini-Hochberg multiple testing correction. In the PPGL cohort, performances of the radiomic models to predict the noradrenergic biochemical profile were assessed by comparing the areas under the receiver operating characteristic curve (AUC) for both delineation methods. Results: At least 65% of the features showed significant differences between VOI_vital-tumour and VOI_gross-tumour (65%, 79% and 82% for the NSCLC, PPGL and combined cohort, respectively). The AUCs of the radiomic models were not significantly different between delineation methods. Conclusion: In both tumour types, almost two-third of the features were affected, demonstrating that the impact of whether or not to include central necrosis in the VOI on the radiomic feature values is significant. Nevertheless, predictive performances of both delineation methods were comparable. We recommend that radiomic studies should report whether or not central necrosis was included during delineation.