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The aim of this study was to investigate whether the favorable characteristics of novel digital PET/CT (dPET) scanners compared to analog systems (aPET) could translate into an improved disease localization in prostate cancer (PCa) patients with early biochemical recurrence/persistence (BCR/BCP). A retrospective analysis was conducted on 440 consecutive analog (n = 311) or digital (n = 129) 68Ga-PSMA-11 PET/CT scans performed in hormone-sensitive ADT-free PCa patients with early-BCR/BCP (PSA at PET ≤ 2.0 ng/mL), previously treated with radical intent (radical-prostatectomy/radiotherapy). dPET showed a higher positivity rate compared to aPET (48.8% [63/129] vs. 37.3% [116/311], p = 0.03), despite the slightly lower median PSA value of the dPET cohort (0.33 [IQR: 0.26–0.61] vs. 0.55 [IQR: 0.40–0.85] ng/mL, p < 0.01). dPET detection rate was higher in both PSA ranges 0.2–0.5 ng/mL (39.0% [32/82] vs. 25.2% [34/135], p = 0.03) and 0.5–1.0 ng/mL (63.2% [24/38] vs. 40.8% [53/130], p = 0.02), but not for PSA ≥ 1.0 ng/mL. dPET detected a higher per patient median number of pathologic findings (PSMA-RADS ≥ 3) and multi-metastatic cases (>3 lesions) among N1/M1-positive scans (21.7% [10/46] vs. 8.6% [9/105], p = 0.03). Moreover, the proportion of uncertain findings among pathological lesions was significantly lower for dPET than aPET (24.4% [39/160] vs. 38.5% [60/156], p = 0.008). Overall, 68Ga-PSMA-11 dPET showed a better performance compared to aPET, resulting in a higher scan-positivity rate, a higher number of detected pathological lesions, and a lower rate of uncertain findings. [ABSTRACT FROM AUTHOR]

High-resolution intraoperative PET/CT specimen imaging, coupled with prostate-specific membrane antigen (PSMA) molecular targeting, holds great potential for the rapid ex vivo identification of disease localizations in high-risk prostate cancer patients undergoing surgery. However, the accurate analysis of radiotracer uptake would require time-consuming manual volumetric segmentation of 3D images. The aim of this study was to test the feasibility of using machine learning to perform automatic nodal segmentation of intraoperative 68Ga-PSMA-11 PET/CT specimen images. Six (n = 6) lymph-nodal specimens were imaged in the operating room after an e.v. injection of 2.1 MBq/kg of 68Ga-PSMA-11. A machine learning-based approach for automatic lymph-nodal segmentation was developed using only open-source Python libraries (Scikit-learn, SciPy, Scikit-image). The implementation of a k-means clustering algorithm (n = 3 clusters) allowed to identify lymph-nodal structures by leveraging differences in tissue density. Refinement of the segmentation masks was performed using morphological operations and 2D/3D-features filtering. Compared to manual segmentation (ITK-SNAP v4.0.1), the automatic segmentation model showed promising results in terms of weighted average precision (97–99%), recall (68–81%), Dice coefficient (80–88%) and Jaccard index (67–79%). Finally, the ML-based segmentation masks allowed to automatically compute semi-quantitative PET metrics (i.e., SUVmax), thus holding promise for facilitating the semi-quantitative analysis of PET/CT images in the operating room. [ABSTRACT FROM AUTHOR]

The NETTER-1 study has proven peptide receptor radionuclide therapy (PRRT) to be one of the most effective therapeutic options for metastatic neuroendocrine tumors (NETs), improving progression-free survival and overall survival. However, PRRT response assessment is challenging and no consensus on methods and timing has yet been reached among experts in the field. This issue is owed to the suboptimal sensitivity and specificity of clinical biomarkers, limitations of morphological response criteria in slowly growing tumors and necrotic changes after therapy, a lack of standardized parameters and timing of functional imaging and the heterogeneity of PRRT protocols in the literature. The aim of this article is to review the most relevant current approaches for PRRT efficacy prediction and response assessment criteria in order to provide an overview of suitable tools for safe and efficacious PRRT. [ABSTRACT FROM AUTHOR]