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RationaleThe development of consensus guidelines for interpretation of Prostate-Specific Membrane Antigen (PSMA)-Positron Emission Tomography (PET) is needed to provide more consistent reports in clinical practice. The standardization of PSMA-PET interpretation may also contribute to increasing the data reproducibility within clinical trials. Finally, guidelines in PSMA-PET interpretation are needed to communicate the exact location of findings to referring physicians, to support clinician therapeutic management decisions.MethodsA panel of worldwide experts in PSMA-PET was established. Panelists were selected based on their expertise and publication record in the diagnosis or treatment of PCa, in their involvement in clinical guidelines and according to their expertise in the clinical application of radiolabeled PSMA inhibitors. Panelists were actively involved in all stages of a modified, nonanonymous, Delphi consensus process.ResultsAccording to the findings obtained by modified Delphi consensus process, panelist recommendations were implemented in a structured report for PSMA-PET.ConclusionsThe E-PSMA standardized reporting guidelines, a document supported by the European Association of Nuclear Medicine (EANM), provide consensus statements among a panel of experts in PSMA-PET imaging, to develop a structured report for PSMA-PET in prostate cancer and to harmonize diagnostic interpretation criteria.

PurposeFAPI ligands (fibroblast activation protein inhibitor), a novel class of radiotracers for PET/CT imaging, demonstrated in previous studies rapid and high tumor uptake. The purpose of this study is the head-to-head intra-individual comparison of 68Ga-FAPI versus standard-of-care 18F-FDG in PET/CT in organ biodistribution and tumor uptake in patients with various cancers.Material and MethodsThis international retrospective multicenter analysis included PET/CT data from 71 patients from 6 centers who underwent both 68Ga-FAPI and 18F-FDG PET/CT within a median time interval of 10 days (range 1–89 days). Volumes of interest (VOIs) were manually drawn in normal organs and tumor lesions to quantify tracer uptake by SUVmax and SUVmean. Furthermore, tumor-to-background ratios (TBR) were generated (SUVmax tumor/ SUVmax organ).ResultsA total of 71 patients were studied of, which 28 were female and 43 male (median age 60). In 41 of 71 patients, the primary tumor was present. Forty-three of 71 patients exhibited 162 metastatic lesions. 68Ga-FAPI uptake in primary tumors and metastases was comparable to 18F-FDG in most cases. The SUVmax was significantly lower for 68Ga-FAPI than 18F-FDG in background tissues such as the brain, oral mucosa, myocardium, blood pool, liver, pancreas, and colon. Thus, 68Ga-FAPI TBRs were significantly higher than 18F-FDG TBRs in some sites, including liver and bone metastases.ConclusionQuantitative tumor uptake is comparable between 68Ga-FAPI and 18F-FDG, but lower background uptake in most normal organs results in equal or higher TBRs for 68Ga-FAPI. Thus, 68Ga-FAPI PET/CT may yield improved diagnostic information in various cancers and especially in tumor locations with high physiological 18F-FDG uptake.

Purpose The aim of our study was to compare the diagnostic performance of 68 Ga-PSMA PET and 99m Tc bone scintigraphy (BS) for the detection of bone metastases in prostate cancer (PC) patients. Methods One hundred twenty-six patients who received planar BS and PSMA PET within three months and without change of therapy were extracted from our database. Bone lesions were categorized into benign, metastatic, or equivocal by two experienced observers. A best valuable comparator (BVC) was defined based on BS, PET, additional imaging, and follow-up data. The cohort was further divided into clinical subgroups (primary staging, biochemical recurrence, and metastatic castration-resistant prostate cancer [mCRPC]). Additionally, subgroups of patients with less than 30 days delay between the two imaging procedures and with additional single-photon emission computed tomography (SPECT) were analyzed. Results A total of 75 of 126 patients were diagnosed with bone metastases. Sensitivities and specificities regarding overall bone involvement were 98.7–100 % and 88.2–100 % for PET, and 86.7–89.3 % and 60.8–96.1 % ( p  < 0.001) for BS, with ranges representing results for ‘optimistic’ or ‘pessimistic’ classification of equivocal lesions. Out of 1115 examined bone regions, 410 showed metastases. Region-based analysis revealed a sensitivity and specificity of 98.8–99.0 % and 98.9–100 % for PET, and 82.4–86.6 % and 91.6–97.9 % ( p  < 0.001) for BS, respectively. PSMA PET also performed better in all subgroups, except patient-based analysis in mCRPC. Conclusion Ga-PSMA PET outperforms planar BS for the detection of affected bone regions as well as determination of overall bone involvement in PC patients. Our results indicate that BS in patients who have received PSMA PET for staging only rarely offers additional information; however, prospective studies, including a standardized integrated x-ray computed tomography (SPECT/CT) protocol, should be performed in order to confirm the presented results.

PurposeThis study proposes an automated prostate cancer (PC) lesion characterization method based on the deep neural network to determine tumor burden on 68Ga-PSMA-11 PET/CT to potentially facilitate the optimization of PSMA-directed radionuclide therapy.MethodsWe collected 68Ga-PSMA-11 PET/CT images from 193 patients with metastatic PC at three medical centers. For proof-of-concept, we focused on the detection of pelvis bone and lymph node lesions. A deep neural network (triple-combining 2.5D U-Net) was developed for the automated characterization of these lesions. The proposed method simultaneously extracts features from axial, coronal, and sagittal planes, which mimics the workflow of physicians and reduces computational and memory requirements.ResultsAmong all the labeled lesions, the network achieved 99% precision, 99% recall, and an F1 score of 99% on bone lesion detection and 94%, precision 89% recall, and an F1 score of 92% on lymph node lesion detection. The segmentation accuracy is lower than the detection. The performance of the network was correlated with the amount of training data.ConclusionWe developed a deep neural network to characterize automatically the PC lesions on 68Ga-PSMA-11 PET/CT. The preliminary test within the pelvic area confirms the potential of deep learning methods. Increasing the amount of training data should further enhance the performance of the proposed method and may ultimately allow whole-body assessments.

National Comprehensive Cancer Network guidelines consider 18F-fluciclovine PET-CT for prostate cancer biochemical recurrence localisation after radical prostatectomy, whereas European Association of Urology guidelines recommend prostate-specific membrane antigen (PSMA) PET-CT. To the best of our knowledge, no prospective head-to-head comparison between these tests has been done so far. The aim of this study was to compare prospectively paired 18F-fluciclovine and PSMA PET-CT scans for localising biochemical recurrence of prostate cancer after radical prostatectomy in patients with low prostate-specific antigen (PSA) concentrations (<2·0 ng/mL). This was a prospective, single-centre, open-label, single-arm comparative study done at University of California Los Angeles (Los Angeles, CA, USA). Patients older than 18 years of age with prostate cancer biochemical recurrence after radical prostatectomy and PSA levels ranging from 0·2 to 2·0 ng/mL without any prior salvage therapy and with a Karnofsky performance status of at least 50 were eligible. Patients underwent 18F-fluciclovine (reference test) and PSMA (index test) PET-CT scans within 15 days. Detection rate of biochemical recurrence at the patient level and by anatomical region was the primary endpoint. A statistical power analysis demonstrated that a sample size of 50 patients was needed to show a 22% difference in detection rates in favour of PSMA (test for superiority). Each PET scan was interpreted by three independent masked readers and a consensus majority interpretation was generated (two vs one) to determine positive findings. This study is registered with ClinicalTrials.gov, number NCT03515577, and is complete. Between Feb 26, 2018, and Sept 20, 2018, 143 patients were screened for eligibility, of whom 50 patients were enrolled into the study. Median follow-up was 8 months (IQR 7–9). The primary endpoint was met; detection rates were significantly lower with 18F-fluciclovine PET-CT (13 [26%; 95% CI 15–40] of 50) than with PSMA PET-CT (28 [56%; 41–70] of 50), with an odds ratio (OR) of 4·8 (95% CI 1·6–19·2; p=0·0026) at the patient level; in the subanalysis of the pelvic nodes region (four [8%; 2–19] with 18F-fluciclovine vs 15 [30%; 18–45] with PSMA PET-CT; OR 12·0 [1·8–513·0], p=0·0034); and in the subanalysis of any extrapelvic lesions (none [0%; 0–6] vs eight [16%; 7–29]; OR non-estimable [95% CI non-estimable], p=0·0078). With higher detection rates, PSMA should be the PET tracer of choice when PET-CT imaging is considered for subsequent treatment management decisions in patients with prostate cancer and biochemical recurrence after radical prostatectomy and low PSA concentrations (≤2·0 ng/mL). Further research is needed to investigate whether higher detection rates translate into improved oncological outcomes. None.

The aim of this guideline is to provide standards for the recommendation, performance, interpretation and reporting of 68 Ga-PSMA PET/CT for prostate cancer imaging. These recommendations will help to improve accuracy, precision, and repeatability of 68 Ga-PSMA PET/CT for prostate cancer essentially needed for implementation of this modality in science and routine clinical practice.

PurposeTo 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.MethodsThe 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.ResultsThe 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.

Background The rapidly expanding clinical adaptation of prostate-specific membrane antigen (PSMA)-targeted PET imaging in the evaluation of patients with prostate cancer has placed an increasing onus on understanding both the potential pearls of interpretation as well as limitations of this new technique. As with any new molecular imaging modality, accurate characterization of abnormalities on PSMA-targeted PET imaging can be accomplished only if one is aware of the normal distribution pattern, physiological variants of radiotracer uptake, and potential sources of false-positive and false-negative imaging findings. In recent years, a growing number of reports have come to light describing incidental non-prostatic benign or malignant pathologies with high uptake on PSMA-targeted PET imaging. In this review, we have summarized the published literature regarding the potential pearls and technical and interpretive pitfalls of this imaging modality. Knowledge of these limitations can increase the confidence of interpreting physicians and thus improve patient care. Conclusions As PSMA-targeted PET is expected to be evaluated in larger prospective trials, the dissemination of potential diagnostic pitfalls and the biologic underpinning of those findings will be of increased importance.

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.