Prostate-specific membrane antigen (PSMA) is highly expressed on most prostate cancer (PCa) cells, and several PSMA ligands for PET imaging are now available worldwide. 68 Ga-PSMA-11 has already received U.S. Food and Drug Administration approval, and use of PSMA PET is currently suggested by several international guidelines for investigating PCa in different clinical settings. In primary PCa, PSMA PET has been shown to be superior to cross-sectional imaging for the detection of pelvic lymph nodes and distant metastases with subsequent clinical management changes. Additionally, it might also have a role in intraprostatic tumor localization, especially when combined with multiparametric MRI. In a setting of PCa recurrence, higher detection rates have been observed than for any other available imaging techniques, especially at low prostate-specific antigen values. Furthermore, PSMA PET consistently led to a shift in clinical management, thus increasing the proportion of radiotherapy, surgery, or other focal therapies at the expense of systemic options or no treatment. In oligometastatic disease after radical surgery, PSMA PET may be relevant in guiding a metastasis-directed therapy approach, as preliminary data seem to suggest a benefit in terms of progression-free survival after treatment of PSMA PET-positive lesions. As a staging and gatekeeping technique, PSMA PET represents a reliable wholebody imaging procedure in combination with second-line therapy of castration-resistant PCa, as well as being pivotal when assessing patients eligible for radioligand therapy such as 177 Lu-PSMA. This critical review aims at providing a comprehensive overview of the latest literature on the current or emerging main indications, as well as a general outlook on the recommended interpretation criteria for PSMA PET imaging.

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Background: According to published data, radiomics features differ between lesions of refractory/relapsing HL patients from those of long-term responders. However, several methodological aspects have not been elucidated yet. Purpose: The study aimed at setting up a methodological framework in radiomics applications in Hodgkin's lymphoma (HL), especially at (a) developing a novel feature selection approach, (b) evaluating radiomic intra-patient lesions' similarity, and (c) classifying relapsing refractory (R/R) vs non-(R/R) patients. Methods: We retrospectively included 85 patients (male:female = 52:33; median age 35 years, range 19-74). LIFEx (www.lifexsoft.org) was used for [ 18 F]FDG-PET/CT segmentation and feature extraction. Features were a-priori selected if they were highly correlated or uncorrelated to the volume. Principal component analysistransformed features were used to build the fingerprints that were tested to assess lesions' similarity, using the silhouette. For intra-patient similarity analysis, we used patients having multiple lesions only. To classify patients as non-R/R and R/R, the fingerprint considering one single lesion (fingerprint_One) and all lesions (fingerprint_All) was tested using Random Undersampling Boosting of Tree Ensemble (RUBTE). Results: HL fingerprints included up to 15 features. Intra-patient lesion similarity analysis resulted in mean/median silhouette values below 0.5 (low similarity especially in the non-R/R group). In the test set, the fingerprint_One classification accuracy was 62% (78% sensitivity and 53% specificity); the classification by RUBTE using fingerprint_All resulted in 82% accuracy (70% sensitivity and 88% specificity). Conclusions: Lesion similarity analysis was developed, and it allowed to demonstrate that HL lesions were not homogeneous within patients in terms of radiomics signature. Therefore, a random target lesion selection should not be adopted for radiomics applications. Moreover, the classifier to predict R/R vs non-R/R performed the best when all the lesions were used.

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