Beyond Prostate Imaging Reporting and Data System: Combining Magnetic Resonance Imaging Prostate Imaging Reporting and Data System and Prostate-Specific Membrane Antigen-Positron Emission Tomography/Computed Tomography PRIMARY Score in a Composite (P) Score for More Accurate Diagnosis of Clinically Significant Prostate Cancer.

PURPOSE: The Prostate Imaging Reporting and Data System (PI-RADS) score is standard of care for clinically significant prostate cancer (csPCa) diagnosis. The PRIMARY score (prostate-specific membrane antigen [PSMA]-positron emission tomography [PET]/CT) also has high diagnostic accuracy for csPCa. This study aimed to develop an easily calculated combined (P) score for csPCa detection (International Society of Urological Pathology [ISUP] ≥2) incorporating separately read PI-RADS and PRIMARY scores, with external validation. MATERIALS AND METHODS: Two datasets of men with suspected PCa, no prior biopsy, recent MRI and 68Ga-PSMA-11-PET/CT, and subsequent transperineal biopsy were evaluated. The development sample (n = 291, 56% csPCa) a prospective trial and the validation sample (n = 227, 67% csPCa) a multicenter retrospective database. Primary outcome was detection of csPCa (ISUP ≥2), with ISUP ≥ 3 cancer detection a secondary outcome. Score performance was evaluated by area under the curve, sensitivity, specificity, and decision curve analysis. RESULTS: The 5-point combined (P) score was developed in a prospective dataset. In the validation dataset, csPCa was identified in 0%, 20%, 52%, 96%, and 100% for P score 1 to 5. The area under the curve was 0.93 (95% CI: 0.90-0.96), higher than PI-RADS 0.89 (95% CI: 0.85-0.93, P = .039) and PRIMARY score alone 0.84 (95% CI: 0.79-0.89, P < .001). Splitting scores at 1/2 (negative) vs 3/4/5 (positive), P score sensitivity was 94% (95% CI: 89-97) compared to PI-RADS 89% (95% CI: 83-93) and PRIMARY score 86% (95% CI: 79-91). For ISUP ≥ 3, P score sensitivity was 99% (95% CI: 95-100) vs 94% (95% CI: 88-98) and 92% (95% CI: 85-97) for PI-RADS and PRIMARY scores respectively. A maximum standardized uptake value > 12 (P score 5) was ISUP ≥ 2 in all cases with 93% ISUP ≥ 3. CONCLUSIONS: The P score is easily calculated and improves accuracy for csPCa over both PI-RADS and PRIMARY scores. It should be considered when PSMA-PET is undertaken for diagnosis.

Pre-therapy PET-based voxel-wise dosimetry prediction by characterizing intra-organ heterogeneity in PSMA-directed radiopharmaceutical theranostics.

BACKGROUND AND OBJECTIVE: Treatment planning through the diagnostic dimension of theranostics provides insights into predicting the absorbed dose of RPT, with the potential to individualize radiation doses for enhancing treatment efficacy. However, existing studies focusing on dose prediction from diagnostic data often rely on organ-level estimations, overlooking intra-organ variations. This study aims to characterize the intra-organ theranostic heterogeneity and utilize artificial intelligence techniques to localize them, i.e. to predict voxel-wise absorbed dose map based on pre-therapy PET. METHODS: 23 patients with metastatic castration-resistant prostate cancer treated with [177Lu]Lu-PSMA I&T RPT were retrospectively included. 48 treatment cycles with pre-treatment PET imaging and at least 3 post-therapeutic SPECT/CT imaging were selected. The distribution of PET tracer and RPT dose was compared for kidney, liver and spleen, characterizing intra-organ heterogeneity differences. Pharmacokinetic simulations were performed to enhance the understanding of the correlation. Two strategies were explored for pre-therapy voxel-wise dosimetry prediction: (1) organ-dose guided direct projection; (2) deep learning (DL)-based distribution prediction. Physical metrics, dose volume histogram (DVH) analysis, and identity plots were applied to investigate the predicted absorbed dose map. RESULTS: Inconsistent intra-organ patterns emerged between PET imaging and dose map, with moderate correlations existing in the kidney (r = 0.77), liver (r = 0.5), and spleen (r = 0.58) (P < 0.025). Simulation results indicated the intra-organ pharmacokinetic heterogeneity might explain this inconsistency. The DL-based method achieved a lower average voxel-wise normalized root mean squared error of 0.79 ± 0.27%, regarding to ground-truth dose map, outperforming the organ-dose guided projection (1.11 ± 0.57%) (P < 0.05). DVH analysis demonstrated good prediction accuracy (R2 = 0.92 for kidney). The DL model improved the mean slope of fitting lines in identity plots (199% for liver), when compared to the theoretical optimal results of the organ-dose approach. CONCLUSION: Our results demonstrated the intra-organ heterogeneity of pharmacokinetics may complicate pre-therapy dosimetry prediction. DL has the potential to bridge this gap for pre-therapy prediction of voxel-wise heterogeneous dose map.

Response Evaluation Criteria in PSMA PET/CT (RECIP 1.0) in Metastatic Castration-resistant Prostate Cancer.

Background Response Evaluation Criteria in Prostate-specific Membrane Antigen (PSMA) PET/CT (RECIP 1.0) initially integrated software-based quantitative assessment of PSMA-positive total tumor volume (TTV). Clinical implementation of such software is not expected soon, limiting the use of RECIP in practice. Purpose To assess the agreement of RECIP determined using tumor segmentation software (quantitative RECIP) with RECIP determined by qualitative reads by nuclear medicine physicians (visual RECIP) for response evaluation in metastatic castration-resistant prostate cancer. Materials and Methods This multicenter retrospective study at three academic centers included men who received lutetium 177 (177Lu) PSMA treatment between December 2014 and July 2019. PSMA PET/CT images at baseline and 12 weeks were assessed qualitatively by five readers for changes in TTV and for new lesions. Quantitative changes in TTV were also measured using tumor segmentation software. The status of new lesions was combined with qualitative changes in TTV to determine visual RECIP and with quantitative changes in TTV to determine quantitative RECIP. The primary outcomes were the agreement between visual and quantitative RECIP and the interreader reliability of visual RECIP according to the Fleiss κ. The secondary outcome was the association of visual RECIP with overall survival according to Cox regression. Results A total of 124 men (median age, 73 years [IQR, 67-76 years]) were included. Forty (32%) and 84 (68%) men had quantitative RECIP progressive disease (PD) and non-PD, respectively. Agreement between visual versus quantitative RECIP was excellent (κ = 0.89; 118 of 124 men [95%]). Agreement among readers in classifying visual RECIP PD versus non-PD was excellent (κ = 0.81; 103 of 124 men [83%]). RECIP PD was associated with significantly shorter overall survival compared with non-PD (hazard ratio, 2.6 [95% CI: 1.7, 3.8]; P < .001). Conclusion Qualitatively assessed RECIP demonstrated excellent agreement with quantitative RECIP and excellent interreader reliability and can be readily implemented in clinical practice for response evaluation in men with metastatic castration-resistant prostate cancer undergoing 177Lu-PSMA therapy. © RSNA, 2023 Supplemental material is available for this article.

Adoption of Lutetium-177 PSMA radioligand therapy for metastatic castration resistant prostate cancer: a total population analysis in Germany from 2016 to 2020.

PURPOSE: This study is to investigate the adoption and current trends of Lutetium-177 PSMA RLT for mCRPC in Germany. METHODS: We analyzed data from the reimbursement.INFO tool based on German hospitals' quality reports for Lutetium-177 PSMA RLT from 2016 to 2020 and from the nationwide German hospital billing database (Destatis) for general therapy with open radionuclides in combination with prostate cancer from 2006 to 2020. For validation of these billing data, we included the 177Lu-PSMA RLT cycles from two participating institutions from 2016 to 2020. For detection of trends over time we applied linear regression models. RESULTS: General therapy with open radionuclides increased from 2006 to 2020. We identified a total of 12,553 177Lu-PSMA RLT cycles. The number of 177Lu-PSMA RLTs steadily increased from a total of 1026 therapies in 2016 to 3328 therapies in 2020 (+ 576 RLT/year; p < 0.005). In 2016, 25 departments of nuclear medicine offered this treatment, which increased to 44 nuclear medicine departments in 2020. In 2016, 16% of nuclear medicine departments (4/25) performed more than 100 177Lu-PSMA RLTs, which increased to 36% (16/44) in 2020 (p < 0.005). In 2016, 88% (22/25) of 177Lu-PSMA RLTs were performed at a university hospital, which decreased to 70% (31/44) in 2020. The proportion of patients older than 65 years receiving 177Lu-PSMA RLT increased from 78% in 2016 to 81% in 2020. CONCLUSION: Treatment of mCRPC with 177Lu-PSMA RLT has been rapidly increasing in Germany in the recent years providing an additional therapy option. This development is remarkable, because of outstanding formal EMA approval.

Development and external validation of a multivariable [68Ga]Ga-PSMA-11 PET-based prediction model for lymph node involvement in men with intermediate or high-risk prostate cancer.

PURPOSE: To develop and evaluate a lymph node invasion (LNI) prediction model for men staged with [68Ga]Ga-PSMA-11 PET. METHODS: A consecutive sample of intermediate to high-risk prostate cancer (PCa) patients undergoing [68Ga]Ga-PSMA-11 PET, extended pelvic lymph node dissection (ePLND), and radical prostatectomy (RP) at two tertiary referral centers were retrospectively identified. The training cohort comprised 173 patients (treated between 2013 and 2017), the validation cohort 90 patients (treated between 2016 and 2019). Three models for LNI prediction were developed and evaluated using cross-validation. Optimal risk-threshold was determined during model development. The best performing model was evaluated and compared to available conventional and multiparametric magnetic resonance imaging (mpMRI)-based prediction models using area under the receiver operating characteristic curves (AUC), calibration plots, and decision curve analysis (DCA). RESULTS: A combined model including prostate-specific antigen, biopsy Gleason grade group, [68Ga]Ga Ga-PSMA-11 positive volume of the primary tumor, and the assessment of the [68Ga]Ga-PSMA-11 report N-status yielded an AUC of 0.923 (95% CI 0.863-0.984) in the external validation. Using a cutoff of ≥ 17%, 44 (50%) ePLNDs would be spared and LNI missed in one patient (4.8%). Compared to conventional and MRI-based models, the proposed model showed similar calibration, higher AUC (0.923 (95% CI 0.863-0.984) vs. 0.700 (95% CI 0.548-0.852)-0.824 (95% CI 0.710-0.938)) and higher net benefit at DCA. CONCLUSIONS: Our results indicate that information from [68Ga]Ga-PSMA-11 may improve LNI prediction in intermediate to high-risk PCa patients undergoing primary staging especially when combined with clinical parameters. For better LNI prediction, future research should investigate the combination of information from both PSMA PET and mpMRI for LNI prediction in PCa patients before RP.

PSMA PET/CT: joint EANM procedure guideline/SNMMI procedure standard for prostate cancer imaging 2.0.

Here we aim to provide updated guidance and standards for the indication, acquisition, and interpretation of PSMA PET/CT for prostate cancer imaging. Procedures and characteristics are reported for a variety of available PSMA small radioligands. Different scenarios for the clinical use of PSMA-ligand PET/CT are discussed. This document provides clinicians and technicians with the best available evidence, to support the implementation of PSMA PET/CT imaging in research and routine practice.

Joint EANM/SNMMI procedure guideline for the use of 177Lu-labeled PSMA-targeted radioligand-therapy (177Lu-PSMA-RLT).

Prostate-specific membrane antigen (PSMA) is expressed by the majority of clinically significant prostate adenocarcinomas, and patients with target-positive disease can easily be identified by PSMA PET imaging. Promising results with PSMA-targeted radiopharmaceutical therapy have already been obtained in early-phase studies using various combinations of targeting molecules and radiolabels. Definitive evidence of the safety and efficacy of [177Lu]Lu-PSMA-617 in combination with standard-of-care has been demonstrated in patients with metastatic castration-resistant prostate cancer, whose disease had progressed after or during at least one taxane regimen and at least one novel androgen-axis drug. Preliminary data suggest that 177Lu-PSMA-radioligand therapy (RLT) also has high potential in additional clinical situations. Hence, the radiopharmaceuticals [177Lu]Lu-PSMA-617 and [177Lu]Lu-PSMA-I&T are currently being evaluated in ongoing phase 3 trials. The purpose of this guideline is to assist nuclear medicine personnel, to select patients with highest potential to benefit from 177Lu-PSMA-RLT, to perform the procedure in accordance with current best practice, and to prepare for possible side effects and their clinical management. We also provide expert advice, to identify those clinical situations which may justify the off-label use of [177Lu]Lu-PSMA-617 or other emerging ligands on an individual patient basis.

Development of PSMA-PET-guided CT-based radiomic signature to predict biochemical recurrence after salvage radiotherapy.

PURPOSE: To develop a CT-based radiomic signature to predict biochemical recurrence (BCR) in prostate cancer patients after sRT guided by positron-emission tomography targeting prostate-specific membrane antigen (PSMA-PET). MATERIAL AND METHODS: Consecutive patients, who underwent 68Ga-PSMA11-PET/CT-guided sRT from three high-volume centers in Germany, were included in this retrospective multicenter study. Patients had PET-positive local recurrences and were treated with intensity-modulated sRT. Radiomic features were extracted from volumes of interests on CT guided by focal PSMA-PET uptakes. After preprocessing, clinical, radiomics, and combined clinical-radiomic models were developed combining different feature reduction techniques and Cox proportional hazard models within a nested cross validation approach. RESULTS: Among 99 patients, median interval until BCR was the radiomic models outperformed clinical models and combined clinical-radiomic models for prediction of BCR with a C-index of 0.71 compared to 0.53 and 0.63 in the test sets, respectively. In contrast to the other models, the radiomic model achieved significantly improved patient stratification in Kaplan-Meier analysis. The radiomic and clinical-radiomic model achieved a significantly better time-dependent net reclassification improvement index (0.392 and 0.762, respectively) compared to the clinical model. Decision curve analysis demonstrated a clinical net benefit for both models. Mean intensity was the most predictive radiomic feature. CONCLUSION: This is the first study to develop a PSMA-PET-guided CT-based radiomic model to predict BCR after sRT. The radiomic models outperformed clinical models and might contribute to guide personalized treatment decisions.

Safety and efficiency of repeat salvage lymph node dissection for recurrence of prostate cancer using PSMA-radioguided surgery (RGS) after prior salvage lymph node dissection with or without initial RGS support.

BACKGROUND AND OBJECTIVE: Metastasis-directed therapy is a feasible option for low PSA, recurrent locoregional metastatic prostate cancer. After initial salvage surgery, patients with good response might consider a repeat salvage surgery in case of recurrent, isolated, and PSMA-positive metastases. This analysis aimed to evaluate the oncological outcome and safety of repeat PSMA-targeted radioguided surgery (RGS) after either prior RGS or "standard" salvage lymph node dissection (SLND). MATERIALS AND METHODS: We identified 37 patients undergoing repeat RGS after prior SLND (n = 21) (SLND-RGS) or prior RGS (n = 16) (RGS-RGS) between 2014 and 2021 after initial radical prostatectomy with or without pelvic radiation therapy at two German tertiary referral centers. Kaplan-Meier analyses and uni-/multivariable Cox regression models were used to investigate factors associated with biochemical recurrence-free survival (BRFS) and treatment-free survival (TFS) after repeat salvage surgery. RESULTS AND LIMITATIONS: Complete Biochemical Response (cBR, PSA < 0.2 ng/ml) was observed in 20/32 patients (5 NA). Median overall BRFS [95% confidence interval (CI)] after repeat salvage surgery was 10.8 months (mo) (5.3-22). On multivariable regression, only age (HR 1.09, 95% CI 1.01-1.17) and preoperative PSA (HR 1.23, 95% CI 1.01-1.50) were associated with shorter BRFS, although PSA (HR 1.16, 95% CI 0.99-1.36) did not achieve significant predictor status in univariable analysis before (p value = 0.07). Overall, one year after second salvage surgery, 89% of the patients (number at risk: 19) did not receive additional treatment and median TFS was not reached. Clavien-Dindo grade > 3a complications were observed in 8% (3/37 patients). Limitations are the retrospective evaluation, heterogeneous SLND procedures, lack of long-term follow-up data, and small cohort size. CONCLUSION: In this study, repeat RGS was safe and provided clinically meaningful biochemical recurrence- and treatment-free intervals for selected cases. Patients having low preoperative PSA seemed to benefit most of repeat RGS, irrespective of prior SLND or RGS or the time from initial RP/first salvage surgery.

Comparative Analysis of Morphological and Functional Effects of 225Ac- and 177Lu-PSMA Radioligand Therapies (RLTs) on Salivary Glands.

Most Prostate Specific Membrane Antigens (PSMAs) targeting small molecules accumulate in the salivary glands (SGs), raising concerns about SG toxicity, especially after repeated therapies or therapy with 225Ac-labeled ligands. SG toxicity is assessed clinically by the severity of patient-reported xerostomia, but this parameter can be challenging to objectively quantify. Therefore, we explored the feasibility of using SG volume as a biomarker for toxicity. In 21 patients with late-stage metastatic resistant prostate cancer (mCRPC), the PSMA volume and ligand uptake of SG were analyzed retrospectively before and after two cycles of 177Lu-PSMA (LuPSMA; cohort A) and before and after one cycle of 225Ac-PSMA-617 (AcPSMA, cohort B). Mean Volume-SG in cohort A was 59 ± 13 vs. 54 ± 16 mL (-10%, p = 0.4), and in cohort B, it was 50 ± 13 vs. 40 ± 11 mL (-20%, p = 0.007), respectively. A statistically significant decrease in the activity concentration in the SG was only observed in group B (SUVmean: 9.2 ± 2.8 vs. 5.3 ± 1.8, p < 0.0001; vs. A: SUVmean: 11.2 ± 3.3 vs. 11.1 ± 3.5, p = 0.8). SG volume and PSMA-ligand uptake are promising markers to monitor the SG toxicity after a PSMA RLT.

Application of machine learning to pretherapeutically estimate dosimetry in men with advanced prostate cancer treated with 177Lu-PSMA I&T therapy.

PURPOSE: Although treatment planning and individualized dose application for emerging prostate-specific membrane antigen (PSMA)-targeted radioligand therapy (RLT) are generally recommended, it is still difficult to implement in practice at the moment. In this study, we aimed to prove the concept of pretherapeutic prediction of dosimetry based on imaging and laboratory measurements before the RLT treatment. METHODS: Twenty-three patients with metastatic castration-resistant prostate cancer (mCRPC) treated with 177Lu-PSMA I&T RLT were included retrospectively. They had available pre-therapy 68 Ga-PSMA-HEBD-CC PET/CT and at least 3 planar and 1 SPECT/CT imaging for dosimetry. Overall, 43 cycles of 177Lu-PSMA I&T RLT were applied. Organ-based standard uptake values (SUVs) were obtained from pre-therapy PET/CT scans. Patient dosimetry was calculated for the kidney, liver, spleen, and salivary glands using Hermes Hybrid Dosimetry 4.0 from the planar and SPECT/CT images. Machine learning methods were explored for dose prediction from organ SUVs and laboratory measurements. The uncertainty of these dose predictions was compared with the population-based dosimetry estimates. Mean absolute percentage error (MAPE) was used to assess the prediction uncertainty of estimated dosimetry. RESULTS: An optimal machine learning method achieved a dosimetry prediction MAPE of 15.8 ± 13.2% for the kidney, 29.6% ± 13.7% for the liver, 23.8% ± 13.1% for the salivary glands, and 32.1 ± 31.4% for the spleen. In contrast, the prediction based on literature population mean has significantly larger MAPE (p < 0.01), 25.5 ± 17.3% for the kidney, 139.1% ± 111.5% for the liver, 67.0 ± 58.3% for the salivary glands, and 54.1 ± 215.3% for the spleen. CONCLUSION: The preliminary results confirmed the feasibility of pretherapeutic estimation of treatment dosimetry and its added value to empirical population-based estimation. The exploration of dose prediction may support the implementation of treatment planning for RLT.

Measuring response in metastatic castration-resistant prostate cancer using PSMA PET/CT: comparison of RECIST 1.1, aPCWG3, aPERCIST, PPP, and RECIP 1.0 criteria.

PURPOSE: To compare the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, the adapted Prostate Cancer Working Group Criteria 3 (aPCWG3), the adapted Positron Emission Tomography Response Criteria in Solid Tumors (aPERCIST), the PSMA PET Progression (PPP), and the Response Evaluation Criteria In PSMA-Imaging (RECIP) 1.0 for response evaluation using prostate-specific membrane antigen (PSMA)-PET/CT in men with metastatic castration-resistant prostate cancer (mCRPC) treated with 177Lu-PSMA radioligand therapy. METHODS: A total of 124 patients were included in this multicenter retrospective study. All patients received 177Lu-PSMA and underwent PSMA-PET/CT scans at baseline (bPET) and at 12 weeks (iPET). Imaging responses according to RECIST 1.1, aPCWG3, aPERCIST, PPP, and RECIP 1.0 were interpreted by consensus among three blinded readers. Changes in total tumor burden were obtained using the semi-automatic qPSMA software. The response according to each criterion was classified to progressive disease (PD) vs no-PD. Primary outcome measure was the prognostic value (by Cox regression analysis) for overall survival (OS). Secondary outcome measure was the inter-reader reliability (by Cohen's κ coefficient). RESULTS: A total of 43 (35%) of patients had non-measurable disease according to RECIST 1.1. Sixteen (13%), 66 (52%), 72 (58%), 69 (56%), and 39 (32%) of 124 patients had PD according to RECIST 1.1, aPCWG3, aPERCIST, PPP, and RECIP, respectively. PD vs no-PD had significantly higher risk of death according to aPCWG3 (HR = 2.37; 95%CI, 1.62-3.48; p < 0.001), aPERCIST (HR = 2.48; 95%CI, 1.68-3.66; p < 0.001), PPP (HR = 2.72; 95%CI, 1.85-4.01; p < 0.001), RECIP 1.0 (HR = 4.33; 95%CI, 2.80-6.70; p < 0.001), but not according to RECIST 1.1 (HR = 1.29; 95%CI, 0.73-2.27; p = 0.38). The κ index of RECIST 1.1, aPCWG3, aPERCIST 1.0, PPP, and RECIP 1.0 for identifying PD vs no-PD were 0.50 (95%CI, 0.32-0.76), 0.72 (95%CI, 0.63-0.82), 0.68 (95%CI, 0.63-0.73), 0.73 (95%CI, 0.63-0.83), and 0.83 (95%CI, 0.77-0.88), respectively. CONCLUSION: PSMA-PET-specific criteria for early response evaluation in men with mCRPC treated with 177Lu-PSMA achieved higher prognostic values and inter-reader reliabilities in comparison to conventional CT assessment or to criteria adapted to PSMA-PET from other imaging modalities. RECIP 1.0 identified the fewest patients with PD and achieved the highest risk of death for PD vs. no-PD, suggesting that other classification methods tend to overcall progression. Prospective validation of our findings on an independent patient cohort is warranted.

Whole-body uptake classification and prostate cancer staging in 68Ga-PSMA-11 PET/CT using dual-tracer learning.

PURPOSE: In PSMA-ligand PET/CT imaging, standardized evaluation frameworks and image-derived parameters are increasingly used to support prostate cancer staging. Clinical applicability remains challenging wherever manual measurements of numerous suspected lesions are required. Deep learning methods are promising for automated image analysis, typically requiring extensive expert-annotated image datasets to reach sufficient accuracy. We developed a deep learning method to support image-based staging, investigating the use of training information from two radiotracers. METHODS: In 173 subjects imaged with 68Ga-PSMA-11 PET/CT, divided into development (121) and test (52) sets, we trained and evaluated a convolutional neural network to both classify sites of elevated tracer uptake as nonsuspicious or suspicious for cancer and assign them an anatomical location. We evaluated training strategies to leverage information from a larger dataset of 18F-FDG PET/CT images and expert annotations, including transfer learning and combined training encoding the tracer type as input to the network. We assessed the agreement between the N and M stage assigned based on the network annotations and expert annotations, according to the PROMISE miTNM framework. RESULTS: In the development set, including 18F-FDG training data improved classification performance in four-fold cross validation. In the test set, compared to expert assessment, training with 18F-FDG data and the development set yielded 80.4% average precision [confidence interval (CI): 71.1-87.8] for identification of suspicious uptake sites, 77% (CI: 70.0-83.4) accuracy for anatomical location classification of suspicious findings, 81% agreement for identification of regional lymph node involvement, and 77% agreement for identification of metastatic stage. CONCLUSION: The evaluated algorithm showed good agreement with expert assessment for identification and anatomical location classification of suspicious uptake sites in whole-body 68Ga-PSMA-11 PET/CT. With restricted PSMA-ligand data available, the use of training examples from a different radiotracer improved performance. The investigated methods are promising for enabling efficient assessment of cancer stage and tumor burden.

The added value of PSMA PET/MR radiomics for prostate cancer staging.

PURPOSE: To evaluate the performance of combined PET and multiparametric MRI (mpMRI) radiomics for the group-wise prediction of postsurgical Gleason scores (psGSs) in primary prostate cancer (PCa) patients. METHODS: Patients with PCa, who underwent [68 Ga]Ga-PSMA-11 PET/MRI followed by radical prostatectomy, were included in this retrospective analysis (n = 101). Patients were grouped by psGS in three categories: ISUP grades 1-3, ISUP grade 4, and ISUP grade 5. mpMRI images included T1-weighted, T2-weighted, and apparent diffusion coefficient (ADC) map. Whole-prostate segmentations were performed on each modality, and image biomarker standardization initiative (IBSI)-compliant radiomic features were extracted. Nine support vector machine (SVM) models were trained: four single-modality radiomic models (PET, T1w, T2w, ADC); three PET + MRI double-modality models (PET + T1w, PET + T2w, PET + ADC), and two baseline models (one with patient data, one image-based) for comparison. A sixfold stratified cross-validation was performed, and balanced accuracies (bAcc) of the predictions of the best-performing models were reported and compared through Student's t-tests. The predictions of the best-performing model were compared against biopsy GS (bGS). RESULTS: All radiomic models outperformed the baseline models. The best-performing (mean ± stdv [%]) single-modality model was the ADC model (76 ± 6%), although not significantly better (p > 0.05) than other single-modality models (T1w: 72 ± 3%, T2w: 73 ± 2%; PET: 75 ± 5%). The overall best-performing model combined PET + ADC radiomics (82 ± 5%). It significantly outperformed most other double-modality (PET + T1w: 74 ± 5%, p = 0.026; PET + T2w: 71 ± 4%, p = 0.003) and single-modality models (PET: p = 0.042; T1w: p = 0.002; T2w: p = 0.003), except the ADC-only model (p = 0.138). In this initial cohort, the PET + ADC model outperformed bGS overall (82.5% vs 72.4%) in the prediction of psGS. CONCLUSION: All single- and double-modality models outperformed the baseline models, showing their potential in the prediction of GS, even with an unbalanced cohort. The best-performing model included PET + ADC radiomics, suggesting a complementary value of PSMA-PET and ADC radiomics.

The maximum standardized uptake value in patients with recurrent or persistent prostate cancer after radical prostatectomy and PSMA-PET-guided salvage radiotherapy-a multicenter retrospective analysis.

PURPOSE: This study aims to evaluate the association of the maximum standardized uptake value (SUVmax) in positron-emission tomography targeting prostate-specific membrane antigen (PSMA-PET) prior to salvage radiotherapy (sRT) on biochemical recurrence free survival (BRFS) in a large multicenter cohort. METHODS: Patients who underwent 68 Ga-PSMA11-PET prior to sRT were enrolled in four high-volume centers in this retrospective multicenter study. Only patients with PET-positive local recurrence (LR) and/or nodal recurrence (NR) within the pelvis were included. Patients were treated with intensity-modulated-sRT to the prostatic fossa and elective lymphatics in case of nodal disease. Dose escalation was delivered to PET-positive LR and NR. Androgen deprivation therapy was administered at the discretion of the treating physician. LR and NR were manually delineated and SUVmax was extracted for LR and NR. Cox-regression was performed to analyze the impact of clinical parameters and the SUVmax-derived values on BRFS. RESULTS: Two hundred thirty-five patients with a median follow-up (FU) of 24 months were included in the final cohort. Two-year and 4-year BRFS for all patients were 68% and 56%. The presence of LR was associated with favorable BRFS (p = 0.016). Presence of NR was associated with unfavorable BRFS (p = 0.007). While there was a trend for SUVmax values ≥ median (p = 0.071), SUVmax values ≥ 75% quartile in LR were significantly associated with unfavorable BRFS (p = 0.022, HR: 2.1, 95%CI 1.1-4.6). SUVmax value in NR was not significantly associated with BRFS. SUVmax in LR stayed significant in multivariate analysis (p = 0.030). Sensitivity analysis with patients for who had a FU of > 12 months (n = 197) confirmed these results. CONCLUSION: The non-invasive biomarker SUVmax can prognosticate outcome in patients undergoing sRT and recurrence confined to the prostatic fossa in PSMA-PET. Its addition might contribute to improve risk stratification of patients with recurrent PCa and to guide personalized treatment decisions in terms of treatment intensification or de-intensification. This article is part of the Topical Collection on Oncology-Genitourinary.

Nomograms to predict outcomes after 177Lu-PSMA therapy in men with metastatic castration-resistant prostate cancer: an international, multicentre, retrospective study.

BACKGROUND: Lutetium-177 (177Lu) prostate-specific membrane antigen (177Lu-PSMA) is a novel targeted treatment for patients with metastatic castration-resistant prostate cancer (mCRPC). Predictors of outcomes after 177Lu-PSMA to enhance its clinical implementation are yet to be identified. We aimed to develop nomograms to predict outcomes after 177Lu-PSMA in patients with mCRPC. METHODS: In this multicentre, retrospective study, we screened patients with mCRPC who had received 177Lu-PSMA between Dec 10, 2014, and July 19, 2019, as part of the previous phase 2 trials (NCT03042312, ACTRN12615000912583) or compassionate access programmes at six hospitals and academic centres in Germany, the USA, and Australia. Eligible patients had received intravenous 6·0-8·5 GBq 177Lu-PSMA once every 6-8 weeks, for a maximum of four to six cycles, and had available baseline [68Ga]Ga-PSMA-11 PET/CT scan, clinical data, and survival outcomes. Putative predictors included 18 pretherapeutic clinicopathological and [68Ga]Ga-PSMA-11 PET/CT variables. Data were collected locally and centralised. Primary outcomes for the nomograms were overall survival and prostate-specific antigen (PSA)-progression-free survival. Nomograms for each outcome were computed from Cox regression models with LASSO penalty for variable selection. Model performance was measured by examining discrimination (Harrell's C-index), calibration (calibration plots), and utility (patient stratification into low-risk vs high-risk groups). Models were validated internally using bootstrapping and externally by calculating their performance on a validation cohort. FINDINGS: Between April 23, 2019, and Jan 13, 2020, 414 patients were screened; 270 (65%) of whom were eligible and were divided into development (n=196) and validation (n=74) cohorts. The median duration of follow-up was 21·5 months (IQR 13·3-30·7). Predictors included in the nomograms were time since initial diagnosis of prostate cancer, chemotherapy status, baseline haemoglobin concentration, and [68Ga]Ga-PSMA-11 PET/CT parameters (molecular imaging TNM classification and tumour burden). The C-index of the overall survival model was 0·71 (95% CI 0·69-0·73). Similar C-indices were achieved at internal validation (0·71 [0·69-0·73]) and external validation (0·72 [0·68-0·76]). The C-index of the PSA-progression-free survival model was 0·70 (95% CI 0·68-0·72). Similar C-indices were achieved at internal validation (0·70 [0·68-0·72]) and external validation (0·71 [0·68-0·74]). Both models were adequately calibrated and their predictions correlated with the observed outcome. Compared with high-risk patients, low-risk patients had significantly longer overall survival in the validation cohort (24·9 months [95% CI 16·8-27·3] vs 7·4 months [4·0-10·8]; p<0·0001) and PSA-progression-free survival (6·6 months [6·0-7·1] vs 2·5 months [1·2-3·8]; p=0·022). INTERPRETATION: These externally validated nomograms that are predictive of outcomes after 177Lu-PSMA in patients with mCRPC might help in clinical trial design and individual clinical decision making, particularly at institutions where 177Lu-PSMA is introduced as a novel therapeutic option. FUNDING: Prostate Cancer Foundation.

Regional Lymph Node Metastasis on Prostate Specific Membrane Antigen Positron Emission Tomography Correlates with Decreased Biochemical Recurrence-Free and Therapy-Free Survival after Radical Prostatectomy: A Retrospective Single-Center Single-Arm Observational Study.

PURPOSE: We sought to address the impact of preoperative prostate specific membrane antigen (PSMA) positron emission tomography (PET) findings prior to radical prostatectomy and pelvic lymph node dissection on biochemical recurrence and time to adjuvant or salvage treatment. MATERIALS AND METHODS: Between 2013 and 2017, 64 intermediate and 166 high risk (230) prostate cancer patients received 68Ga-PSMA-11 PET followed by radical prostatectomy and pelvic lymph node dissection. Biochemical recurrence-free and therapy-free survivalwere determined. For all time-to-event analyses, univariable and multivariable Cox proportional hazards models and univariable Kaplan-Meier analyses were applied, with a significance threshold of p <0.05. RESULTS: The overall sensitivity, specificity, positive predictive value and negative predictive value of PSMA PET for pN1 disease was 48.5%, 95.7%, 82.1% and 82.2%, respectively. Median followup was 30.2 months. Biochemical recurrence occurred in 50.4% (116) of patients and adjuvant or salvage treatment was performed in 46.5% (107). Worst biochemical recurrence-free and therapy-free survival was observed in pN1 patients who also exhibited PSMA PET positive lymph node, followed by pN1 patients without PSMA PET positive lymph node and patients without evidence of lymph node metastasis on histology and PSMA PET (median biochemical recurrence-free survival 1.7 vs. 7.5 vs. >36 months, median therapy-free survival 2.6 vs. 8.9 vs. >36 months). CONCLUSIONS: Patients with positive lymph node on PSMA PET prior to radical prostatectomy have to expect early biochemical recurrence and adjuvant/salvage therapy, despite thorough pelvic lymph node dissection. Therefore, results from PSMA PET can be used for patients' consultation and more stringent followup as well as for planning of neoadjuvant/adjuvant therapy.

Value of PET imaging for radiation therapy.

This comprehensive review written by experts in their field gives an overview on the current status of incorporating positron emission tomography (PET) into radiation treatment planning. Moreover, it highlights ongoing studies for treatment individualisation and per-treatment tumour response monitoring for various primary tumours. Novel tracers and image analysis methods are discussed. The authors believe this contribution to be of crucial value for experts in the field as well as for policy makers deciding on the reimbursement of this powerful imaging modality.

Almost 10 years of PET/MR attenuation correction: the effect on lesion quantification with PSMA: clinical evaluation on 200 prostate cancer patients.

PURPOSE: After a decade of PET/MR, the case of attenuation correction (AC) remains open. The initial four-compartment (air, water, fat, soft tissue) Dixon-based AC scheme has since been expanded with several features, the latest being MR field-of-view extension and a bone atlas. As this potentially changes quantification, we evaluated the impact of these features in PET AC in prostate cancer patients. METHODS: Two hundred prostate cancer patients were examined with either 18F- or 68Ga-prostate-specific membrane antigen (PSMA) PET/MR. Qualitative and quantitative analysis (SUVmean, SUVmax, correlation, and statistical significance) was performed on images reconstructed using different AC schemes: Dixon, Dixon+MLAA, Dixon+HUGE, and Dixon+HUGE+bones for 18F-PSMA data; Dixon and Dixon+bones for 68Ga-PSMA data. Uptakes were compared using linear regression against standard Dixon. RESULTS: High correlation and no visually perceivable differences between all evaluated methods (r > 0.996) were found. The mean relative difference in lesion uptake of 18F-PSMA and 68Ga-PSMA remained, respectively, within 4% and 3% in soft tissue, and within 10% and 9% in bones for all evaluated methods. Bone registration errors were detected, causing mean uptake change of 5% in affected lesions. CONCLUSIONS: Based on these results and the encountered bone atlas registration inaccuracy, we deduce that including bones and extending the MR field-of-view did not introduce clinically significant differences in PSMA diagnostic accuracy and tracer uptake quantification in prostate cancer pelvic lesions, facilitating the analysis of serial studies respectively. However, in the absence of ground truth data, we advise against atlas-based methods when comparing serial scans for bone lesions.

Performance of [68Ga]Ga-PSMA-11 PET/CT in patients with recurrent prostate cancer after prostatectomy-a multi-centre evaluation of 2533 patients.

PURPOSE: To evaluate the performance of [68Ga]Ga-PSMA-11 PET/CT in the diagnosis of recurrent prostate cancer (PC) after prostatectomy in a large multicentre cohort. METHODS: The centres, which contributed to this study, were the departments of nuclear medicine of Heidelberg (Germany), Technical University of Munich (Germany) and Albert Einstein Hospital of São Paulo (Brazil). A total of 2533 patients who were scanned with [68Ga]Ga-PSMA-11 PET/CT at 1 h p.i. due to recurrent PC after prostatectomy were included in this retrospective analysis. Exclusion criteria were as follows: patients with untreated primary tumour, previous chemotherapy or Xofigo®; those previously treated with exclusively external beam radiation therapy or HIFU; those referred for PSMA-therapy; and those treated with ADT (including first- and second-generation ADT) within the last 6 months. Potential influences of different factors such as PSA level, PSA doubling-time (PSADT), PSA velocity (PSAVel), Gleason Score (GSC, including the separate analysis of 7a and 7b), age and amount of injected tracer were evaluated in a multivariable analysis. RESULTS: The rate of pathologic PET/CT-scans was 43% for PSA ≤ 0.2 ng/ml, 58% for PSA > 0.2 to ≤ 0.5, 72% for PSA > 0.5 to ≤ 1.0 and increased to a maximum of 93% for PSA > 10 ng/ml. A pathological PET/CT was significantly (p = 0.001) associated with PSA level and higher GSC. Amount of injected tracer, age, PSADT and PSAVel were not associated with a higher probability of a pathological scan. CONCLUSION: [68Ga]Ga-PSMA-11 PET/CT at 1 h p.i. confirmed its high performance in the largest patient cohort yet analysed. Tumour detection showed a clear association with higher PSA and higher GSC. No association was found between a pathological [68Ga]Ga-PSMA-11 PET/CT and age, amount of injected tracer, PSADT or PSAVel.