Prognostic utility of RECIP 1.0 with manual and AI-based segmentations in biochemically recurrent prostate cancer from [68Ga]Ga-PSMA-11 PET images.

PURPOSE: This study aimed to (i) validate the Response Evaluation Criteria in PSMA (RECIP 1.0) criteria in a cohort of biochemically recurrent (BCR) prostate cancer (PCa) patients and (ii) determine if this classification could be performed fully automatically using a trained artificial intelligence (AI) model. METHODS: One hundred ninety-nine patients were imaged with [68Ga]Ga-PSMA-11 PET/CT once at the time of biochemical recurrence and then a second time a median of 6.0 months later to assess disease progression. Standard-of-care treatments were administered to patients in the interim. Whole-body tumour volume was quantified semi-automatically (TTVman) in all patients and using a novel AI method (TTVAI) in a subset (n = 74, the remainder were used in the training process of the model). Patients were classified as having progressive disease (RECIP-PD), or non-progressive disease (non RECIP-PD). Association of RECIP classifications with patient overall survival (OS) was assessed using the Kaplan-Meier method with the log rank test and univariate Cox regression analysis with derivation of hazard ratios (HRs). Concordance of manual and AI response classifications was evaluated using the Cohen's kappa statistic. RESULTS: Twenty-six patients (26/199 = 13.1%) presented with RECIP-PD according to semi-automated delineations, which was associated with a significantly lower survival probability (log rank p < 0.005) and higher risk of death (HR = 3.78 (1.96-7.28), p < 0.005). Twelve patients (12/74 = 16.2%) presented with RECIP-PD according to AI-based segmentations, which was also associated with a significantly lower survival (log rank p = 0.013) and higher risk of death (HR = 3.75 (1.23-11.47), p = 0.02). Overall, semi-automated and AI-based RECIP classifications were in fair agreement (Cohen's k = 0.31). CONCLUSION: RECIP 1.0 was demonstrated to be prognostic in a BCR PCa population and is robust to two different segmentation methods, including a novel AI-based method. RECIP 1.0 can be used to assess disease progression in PCa patients with less advanced disease. This study was registered with the Australian New Zealand Clinical Trials Registry (ACTRN12615000608561) on 11 June 2015.

Should new organ involvement be included in Response Evaluation Criteria in PSMA Imaging?

PURPOSE: The current study is intended to investigate the effect of new organ involvement on overall survival (OS) and modify the Response Evaluation Criteria in PSMA Imaging (RECIP) by including new organ involvement to RECIP 1.0. MATERIALS AND METHODS: This retrospective study includes 114 patients diagnosed with metastatic castration-resistant prostate cancer (mCRPC) between September 2017 and June 2022 who had received docetaxel treatment and had baseline and post-treatment prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) images. The inclusion criteria were patients with pre- and post-treatment [18F]FDG PET/CT images and whose [18F]FDG PET images were negative. Those whose data were unavailable, who had additional malignancy, or who received abiraterone, enzalutamide, or Lutetium (Lu)-177 treatment were excluded. Age, Gleason score (GS), TPSA (total prostate-specific antigen) levels, surgical history, and OS information were recorded for each patient. RESULTS: The 114 patients herein had a median age of 72.5 (51-91) years and a median GS of 8 (7-10). New lesions were observed in 59 patients (51.7%) and new organ PSMA uptake was observed in 14 patients (12.2%). In the multivariate Cox regression analysis, volume-based treatment response (vTR)-total lesion PSMA (TLP), RECIP PSMA-VOL, modified RECIP (mRECIP) PSMA-VOL, and mRECIP TLP were independent prognostic factors for mortality (p < 0.001, p = 0.006, p = 0.003, and p = 0.003, respectively). The median OS of patients with new organ involvement and new lesion with PSMA uptake was 9.3 months (95% CI 2.1-16.5 months) and 11.8 months (95% CI 7.4-16.2 months), respectively. CONCLUSION: The study concluded that new organ involvement had a shorter OS than new lesion involvement. In the mRECIP that we developed, unlike RECIP, we demonstrated that both PSMA-VOL and TLP value were independent prognostic factors for mortality.

Prognostic Value of Tumor Volume Assessment on PSMA PET After 177Lu-PSMA Radioligand Therapy Evaluated by PSMA PET/CT Consensus Statement and RECIP 1.0.

Quantitative evaluation of prostate-specific membrane antigen (PSMA)-targeting PET/CT remains challenging but is urgently needed for the use of standardized PET-based response criteria, such as the PSMA PET/CT consensus statement or Response Evaluation Criteria in PSMA PET/CT (RECIP 1.0). A recent study evaluated the prognostic value of whole-body tumor volume using a semiautomatic method relying on a 50% threshold of lesion SUVmax (PSMATV50). In the present study, we analyzed the suitability of this approach comparing 18F-PSMA-1007 with 68Ga-PSMA-11 PET/CT scans and the potential of PSMATV50 for the prediction of overall survival (OS) in patients before 177Lu-PSMA radioligand therapy (RLT). Moreover, PSMATV50 was integrated into the PSMA PET/CT consensus statement as well as RECIP 1.0, and the prognostic value of these response classification systems was compared. Methods: This retrospective study included 70 patients with metastatic castration-resistant prostate cancer undergoing PSMA RLT. Thirty-three patients were monitored by 68Ga-PSMA-11 PET/CT, and 37 patients by 18F-PSMA-1007 PET/CT. PET/CT scans before (baseline) and at the end of PSMA RLT after 2-4 cycles (follow-up) were separately analyzed by 2 readers. PSMATV50 at baseline and its change at the time of follow-up (ΔPSMATV50, expressed as a ratio) were correlated with OS using Cox proportional-hazards regression. The results of both subgroups were compared. The integration of ΔPSMATV50 in existing response classification systems was evaluated. To assess and compare the discriminatory strength of these classification systems, Gönen and Heller concordance probability estimates were calculated. Results: PSMATV50 determination was technically feasible in all examinations. A higher PSMATV50 at baseline and a higher ΔPSMATV50 were strongly associated with a shorter OS for both 68Ga-PSMA-11 (PSMATV50: hazard ratio [HR] of 1.29 [95% CI, 1.05-1.55], P = 0.009; ΔPSMATV50: HR of 1.83 [95% CI, 1.08-3.09], P = 0.024) and 18F-PSMA-1007 (PSMATV50: HR of 1.84 [95% CI, 1.13-2.99], P = 0.014; ΔPSMATV50: HR of 1.23 [95% CI, 1.04-1.51], P = 0.03). Response assessment provided high discriminatory power for OS for the PSMA PET/CT consensus statement (concordance probability estimate, 0.73) as well as RECIP 1.0 (concordance probability estimate, 0.74). Conclusion: PSMATV50 and ΔPSMATV50 proved to be predictive of OS not only for 68Ga-PSMA-11 but also for 18F-PSMA-1007 PET/CT scans. Subsequent integration of ΔPSMATV50 into the PSMA PET/CT consensus statement and RECIP 1.0 provided equally high prognostic value for both classification systems.

PET Criteria by Cancer Type from Imaging Interpretation to Treatment Response Assessment: Beyond FDG PET Score.

BACKGROUND: in recent years, the role of positron emission tomography (PET) and PET/computed tomography (PET/CT) has emerged as a reliable diagnostic tool in a wide variety of pathological conditions. This review aims to collect and review PET criteria developed for interpretation and treatment response assessment in cases of non-[18F]fluorodeoxyglucose ([18F]FDG) imaging in oncology. METHODS: A wide literature search of the PubMed/MEDLINE, Scopus and Google Scholar databases was made to find relevant published articles about non-[18F]FDG PET response criteria. RESULTS: The comprehensive computer literature search revealed 183 articles. On reviewing the titles and abstracts, 149 articles were excluded because the reported data were not within the field of interest. Finally, 34 articles were selected and retrieved in full-text versions. CONCLUSIONS: available criteria are a promising tool for the interpretation of non-FDG PET scans, but also to assess the response to therapy and therefore to predict the prognosis. However, oriented clinical trials are needed to clearly evaluate their impact on patient management.