Introduction: Prostate Specific Membrane Antigen Positron Emission Tomography (PSMA-PET) is routinely used for the staging of patients with prostate cancer, but data on response assessment are sparse and primarily stem from metastatic castration-resistant prostate cancer (mCRPC) patients treated with PSMA radioligand therapy. Still, follow-up PSMA-PET is employed in earlier disease stages in case of clinical suspicion of disease persistence, recurrence or progression to decide if localized or systemic treatment is indicated. Therefore, the prognostic value of PSMA-PET derived tumor volumes in earlier disease stages (i.e., hormone-sensitive prostate cancer (HSPC) and non-[177Lu]Lu-PSMA-617 (LuPSMA) therapy castration resistant prostate cancer (CRPC)) are evaluated in this manuscript. Methods: A total number of 73 patients (6 primary staging, 42 HSPC, 25 CRPC) underwent two (i.e., baseline and follow-up, median interval: 379 days) whole-body [68Ga]Ga-PSMA-11 PET/CT scans between Nov 2014 and Dec 2018. Analysis was restricted to non-LuPSMA therapy patients. PSMA-PETs were retrospectively analyzed and primary tumor, lymph node-, visceral-, and bone metastases were segmented. Body weight-adjusted organ-specific and total tumor volumes (PSMAvol: sum of PET volumes of all lesions) were measured for baseline and follow-up. PSMAvol response was calculated as the absolute difference of whole-body tumor volumes. High metastatic burden (>5 metastases), RECIP 1.0 and PSMA-PET Progression Criteria (PPP) were determined. Survival data were sourced from the cancer registry. Results: The average number of tumor lesions per patient on the initial PET examination was 10.3 (SD 28.4). At baseline, PSMAvol was strongly associated with OS (HR 3.92, p <0.001; n = 73). Likewise, response in PSMAvol was significantly associated with OS (HR 10.48, p < 0.005; n = 73). PPP achieved significance as well (HR 2.19, p <0.05, n = 73). Patients with hormone sensitive disease and poor PSMAvol response (upper quartile of PSMAvol change) in follow-up had shorter outcome (p < 0.05; n = 42). PSMAvol in bones was the most relevant parameter for OS prognostication at baseline and for response assessment (HR 31.11 p < 0.001; HR 32.27, p < 0.001; n = 73). Conclusion: PPP and response in PSMAvol were significantly associated with OS in the present heterogeneous cohort. Bone tumor volume was the relevant miTNM region for OS prognostication. Future prospective evaluation of the performance of organ specific PSMAvol in more homogeneous cohorts seems warranted.

UNASSIGNED: Prostate-specific membrane antigen (PSMA) is a transmembrane protein expressed by normal prostatic tissue. Therefore, molecular imaging targeting PSMA (PSMA-PET) has gained particular interest and diffusion for PCa staging and restaging. Several factors may affect PSMA-PET results, and many tools have been proposed to improve patient selection. Furthermore, PSMA expression is not homogeneous among different tissues and within the prostate itself. The aims of this study were to evaluate immunohistochemistry (IHC) features of prostate biopsy samples and to assess their correlation with whole-mount specimens and PSMA-PET parameters.
UNASSIGNED: We included consecutive high-risk PCa patients who underwent PSMA-PET for staging proposal at our institution from January 2022 to December 2022. The PET parameters selected were SUVmax, total volume (TV), and total lesion activity (TL). Each patient underwent multiparametric MRI (mpMRI) and fusion-targeted prostate biopsy prior to surgery. IHC analyses were performed on the index lesion cores. IHC visual score (VS) (1, 2, 3) and visual pattern (VP) (membranous, cytoplasmic, and combined) and the percentage of PSMA-negative tumor areas (PSMA%neg) within biopsy cores were evaluated.
UNASSIGNED: Forty-three patients who underwent robotic radical prostatectomy after PSMA-PET were available for analyses. Concordance between VS and VP at biopsy and final pathology showed a Cohen\'s kappa coefficient of 0.39 and 0.38, respectively. Patients with PSMA%neg <20% had a higher concordance in VS and VP (Cohen\'s kappa 0.49 and 0.4, respectively). No difference emerged in terms of median PSMA-TV (p = 0.3) and PSMA-TL (p = 0.9) according to VS at biopsy, while median SUVmax was higher in patients with VS 3 (p = 0.04). Higher SUVmax was associated with membranous and combined VP expression (p = 0.008). No difference emerged between patients with PSMA%neg <20% or PSMA%neg >20% on biopsy cores in terms of SUVmax, PSMA-TL, and PSMA-TV (p = 0.5, p = 0.5, and p = 0.9 respectively).
UNASSIGNED: We found a correlation between IHC VS and VP on targeted biopsy cores and SUVmax at PSMA-PET. However, the correlation between the IHC parameters of biopsy cores and final pathology was not as high as expected. Nevertheless, the presence of PSMA%neg <20% seems to have a better concordance in terms of visual score.

Widespread adoption of mpMRI has led to a decrease in the number of patients requiring prostate biopsies. 68Ga-PSMA-11 PET/CT has demonstrated added benefits in identifying csPCa. Integrating the use of these imaging techniques may hold promise for predicting the presence of csPCa without invasive biopsy. A retrospective analysis of 42 consecutive patients who underwent mpMRI, 68Ga-PSMA-11 PET/CT, prostatic biopsy, and radical prostatectomy (RP) was carried out. A lesion-based model (n = 122) using prostatectomy histopathology as reference standard was used to analyze the accuracy of 68Ga-PSMA-11 PET/CT, mpMRI alone, and both in combination to identify ISUP-grade group ≥ 2 lesions. 68Ga-PSMA-11 PET/CT demonstrated greater specificity and positive predictive value (PPV), with values of 73.3% (vs. 40.0%) and 90.1% (vs. 82.2%), while the mpMRI Prostate Imaging Reporting and Data System (PI-RADS) 4-5 had better sensitivity and negative predictive value (NPV): 90.2% (vs. 78.5%) and 57.1% (vs. 52.4%), respectively. When used in combination, the sensitivity, specificity, PPV, and NPV were 74.2%, 83.3%, 93.2%, and 51.0%, respectively. Subgroup analysis of PI-RADS 3, 4, and 5 lesions was carried out. For PI-RADS 3 lesions, 68Ga-PSMA-11 PET/CT demonstrated a NPV of 77.8%. For PI-RADS 4-5 lesions, 68Ga-PSMA-11 PET/CT achieved PPV values of 82.1% and 100%, respectively, with an NPV of 100% in PI-RADS 5 lesions. A combination of 68Ga-PSMA-11 PET/CT and mpMRI improved the radiological diagnosis of csPCa. This suggests that avoidance of prostate biopsy prior to RP may represent a valid option in a selected subgroup of high-risk patients with a high suspicion of csPCa on mpMRI and 68Ga-PSMA-11 PET/CT.

OBJECTIVE: Sequential PET/CT studies oncology patients can undergo during their treatment follow-up course is limited by radiation dosage. We propose an artificial intelligence (AI) tool to produce attenuation-corrected PET (AC-PET) images from non-attenuation-corrected PET (NAC-PET) images to reduce need for low-dose CT scans.
METHODS: A deep learning algorithm based on 2D Pix-2-Pix generative adversarial network (GAN) architecture was developed from paired AC-PET and NAC-PET images. 18F-DCFPyL PSMA PET-CT studies from 302 prostate cancer patients, split into training, validation, and testing cohorts (n = 183, 60, 59, respectively). Models were trained with two normalization strategies: Standard Uptake Value (SUV)-based and SUV-Nyul-based. Scan-level performance was evaluated by normalized mean square error (NMSE), mean absolute error (MAE), structural similarity index (SSIM), and peak signal-to-noise ratio (PSNR). Lesion-level analysis was performed in regions-of-interest prospectively from nuclear medicine physicians. SUV metrics were evaluated using intraclass correlation coefficient (ICC), repeatability coefficient (RC), and linear mixed-effects modeling.
RESULTS: Median NMSE, MAE, SSIM, and PSNR were 13.26%, 3.59%, 0.891, and 26.82, respectively, in the independent test cohort. ICC for SUVmax and SUVmean were 0.88 and 0.89, which indicated a high correlation between original and AI-generated quantitative imaging markers. Lesion location, density (Hounsfield units), and lesion uptake were all shown to impact relative error in generated SUV metrics (all p < 0.05).
CONCLUSIONS: The Pix-2-Pix GAN model for generating AC-PET demonstrates SUV metrics that highly correlate with original images. AI-generated PET images show clinical potential for reducing the need for CT scans for attenuation correction while preserving quantitative markers and image quality.

Early detection of metastatic prostate cancer (mPCa) is crucial. Whilst the prostate-specific membrane antigen (PSMA) PET scan has high diagnostic accuracy, it suffers from inter-reader variability, and the time-consuming reporting process. This systematic review was registered on PROSPERO (ID CRD42023456044) and aims to evaluate AI\'s ability to enhance reporting, diagnostics, and predictive capabilities for mPCa on PSMA PET scans. Inclusion criteria covered studies using AI to evaluate mPCa on PSMA PET, excluding non-PSMA tracers. A search was conducted on Medline, Embase, and Scopus from inception to July 2023. After screening 249 studies, 11 remained eligible for inclusion. Due to the heterogeneity of studies, meta-analysis was precluded. The prediction model risk of bias assessment tool (PROBAST) indicated a low overall risk of bias in ten studies, though only one incorporated clinical parameters (such as age, and Gleason score). AI demonstrated a high accuracy (98%) in identifying lymph node involvement and metastatic disease, albeit with sensitivity variation (62-97%). Advantages included distinguishing bone lesions, estimating tumour burden, predicting treatment response, and automating tasks accurately. In conclusion, AI showcases promising capabilities in enhancing the diagnostic potential of PSMA PET scans for mPCa, addressing current limitations in efficiency and variability.

BACKGROUND: prostate-specific membrane antigen (PSMA) ligand PET has been recently incorporated into international guidelines for several different indications in prostate cancer (PCa) patients. However, there are still some open questions regarding the role of PSMA ligand PET in castration-resistant prostate cancer (CRPC). The aim of this work is to assess the clinical value of PSMA ligand PET/CT in patients with CRPC.
RESULTS: PSMA ligand PET has demonstrated higher detection rates in comparison to conventional imaging and allows for a significant reduction in the number of M0 CRPC patients. However, its real impact on patients\' prognosis is still an open question. Moreover, in CRPC patients, PSMA ligand PET presents some sensitivity and specificity limitations. Due to its heterogeneity, CRPC may present a mosaic of neoplastic clones, some of which could be PSMA-/FDG+, or vice versa. Likewise, unspecific bone uptake (UBU) and second primary neoplasms (SNPs) overexpressing PSMA in the neoangiogenic vessels represent potential specificity issues. Integrated multi-tracer imaging (PSMA ligand and [18F]FDG PET) together with a multidisciplinary discussion could allow for reaching the most accurate evaluation of each patient from a precision medicine point of view.

OBJECTIVE: The increasing use of PSMA-PET/CT for restaging prostate cancer (PCa) leads to a patient shift from a non-metastatic situation based on conventional imaging (CI) to a metastatic situation. Since established therapeutic pathways have been designed according to CI, it is unclear how this should be translated to the PSMA-PET/CT results. This study aimed to investigate whether PSMA-PET/CT and clinical parameters could predict the visibility of PSMA-positive lesions on a bone scan (BS).
METHODS: In four different centers, all PCa patients with BS and PSMA-PET/CT within 6 months without any change in therapy or significant disease progression were retrospectively selected. Up to 10 non-confluent clear bone metastases were selected per PSMA-PET/CT and SUVmax, SUVmean, PSMAtot, PSMAvol, density, diameter on CT, and presence of cortical erosion were collected. Clinical variables (age, PSA, Gleason Score) were also considered. Two experienced double-board physicians decided whether a bone metastasis was visible on the BS, with a consensus readout for discordant findings. For predictive performance, a random forest was fit on all available predictors, and its accuracy was assessed using 10-fold cross-validation performed 10 times.
RESULTS: A total of 43 patients were identified with 222 bone lesions on PSMA-PET/CT. A total of 129 (58.1%) lesions were visible on the BS. In the univariate analysis, all PSMA-PET/CT parameters were significantly associated with the visibility on the BS (p < 0.001). The random forest reached a mean accuracy of 77.6% in a 10-fold cross-validation.
CONCLUSIONS: These preliminary results indicate that there might be a way to predict the BS results based on PSMA-PET/CT, potentially improving the comparability between both examinations and supporting decisions for therapy selection.

Recent studies have outlined the emerging role of 68Ga-PSMA-11 PET/CT in the diagnostic algorithm of clear cell renal cell carcinoma (ccRCC). We report a unique intra-patient comparison of bilateral primary ccRCC imaged with 68Ga-PSMA-11 PET/CT. Although both tumors resulted 68Ga-PSMA-11 avid, we found a remarkable discrepancy in uptake intensity between the high grade and the low grade ccRCC. This case confirms previous evidence reporting that SUVmax on 68Ga-PSMA-11 PET/CT could be used to discriminate aggressive high grade from more indolent low grade ccRCC, due to their different endothelial expression of PSMA.

BACKGROUND: Prostate-specific antigen (PSA) is a reliable biomarker for identification of prostate cancer, although a biopsy is still the gold standard for detecting prostate cancer. Similar to higher PIRADS lesions on MRI, the maximal standard uptake value (SUV max) on PSMA PET is linked to a higher likelihood of prostate cancer. Can an mpMRI in conjunction with PSMA PET Scan accurately predict prostate cancer and further trigger omission of biopsy similar to other solid organ urological malignancies?
METHODS: Ga-68 PSMA PET and mpMRI were performed for each patient who was a part of this retrospective study. The PET-positive lesion\'s maximum standardized uptake value (SUVmax) was recorded. Prostate biopsies were performed on patients who had PSMA PET avid lesions and a PIRADS score of 4 or 5. Robot-assisted radical prostatectomy (RARP) was afterward performed on patients who had cancer on their prostate biopsy. The prostatectomy specimen\'s histopathological information was recorded. Cutoff values and correlations between the variables were determined using the ROC curves and Pearson\'s correlation test.
RESULTS: On the basis of suspicious DRE findings or elevated PSA, 70 men underwent mpMRI and PET scans. PIRADS 4 patients had a median (IQR) SUVmax of 8.75 (11.95); whereas, PIRADS 5 patients had an SUVmax of 24.5 (22). The mean SUVmax for patients whose biopsies revealed no cancer was 6.25 ± 1.41. With an AUC of 0.876 on the ROC curve, it was found that there was a significant positive correlation between the results of the mpMRI and PET scans and those of the histopathological investigation. A SUVmax ≥ 8.25 on PSMA PET for a PIRADS 4/5 lesion on mpMRI will aid in correctly predicting malignancy, with a sensitivity of 82.8% and specificity of 100%.
CONCLUSIONS: The findings of this study were positive and indicated that patients with a high suspicion of prostate cancer on mpMRI and PSMA PET (PIRADS ≥ 4 and SUVmax ≥ 8.25). This study substantiates the fact that a combination of mpMRI and PSMA PET can accurately predict localized prostate cancer.

UNASSIGNED: The absence of prostate cancer on final surgical pathology after biopsy-proven prostate cancer is a rare finding.
UNASSIGNED: Case of pT0 prostate cancer following Gleason Grade Group 4 in 1 out of 12 cores from a transrectal ultrasound-guided biopsy in a man who underwent both magnetic resonance imaging and 18F-PSMA-1007 Positron Emission Tomography prior to radical prostatectomy.
UNASSIGNED: pT0 prostate cancer is rare. The use of novel imaging modalities may help in the workup of prostate cancer.