Prostate-specific membrane antigen (PSMA) targeting positron emission tomography (PET) is emerging to become a reference imaging tool for the staging and restaging of patients with prostate cancer for both clinical routine and trials. The prostate cancer molecular imaging standardized evaluation (PROMISE) criteria have been proposed as a framework for whole-body staging (molecular imaging TNM staging, denoted miTNM staging) to describe the prostate cancer disease extent on PSMA-PET. To create a comprehensive and integrated framework for PSMA-PET image interpretation and reporting. We propose the PROMISE V2 framework, which integrates an updated miTNM system, improved assessment of local disease, and a slightly modified PSMA-expression score for clinical routine. We have added a response monitoring framework defining qualitative and quantitative parameters to be recorded for a longitudinal assessment in clinical trials. We provide a comprehensive literature review on the current use of the PROMISE framework in clinical research and prospective trials. PROMISE variables demonstrate a clear association with survival. PSMA expression assessed by the PSMA-expression score was used in several trials, and a low PSMA-expression score is a negative prognosticator of overall survival after ¹⁷⁷Lu-PSMA radioligand therapy. The proposed imaging parameters recorded for response assessment in clinical trials can be utilized to determine response according to PSMA-PET progression (PPP) or Response Evaluation Criteria in PSMA-PET/Computed Tomography (RECIP) frameworks, but also future response criteria. PROMISE V2 offers standardized reporting of disease extent for clinical routine and research. Parameters recorded within clinical trials facilitate objective response assessment. Prostate-specific membrane antigen (PSMA) targeting positron emission tomography (PET) has become a standard imaging examination for prostate cancer. We propose a comprehensive framework for the analysis and reporting of PSMA-PET findings that will improve the communication between imaging experts and uro-oncologists.

A convolutional neural network−based detection and classification of fluorine 18−fluorodeoxyglucose PET foci in patients with lymphoma and lung cancer is feasible and accurate. Background Fluorine 18 (18F)−fluorodeoxyglucose (FDG) PET/CT is a routine tool for staging patients with lymphoma and lung cancer. Purpose To evaluate configurations of deep convolutional neural ne...

Purpose: The purpose of this guideline is to provide comprehensive information on best practices for robust radiomics analyses for both hand-crafted and deep learning-based approaches. Methods: In a cooperative effort between the EANM and SNMMI, we agreed upon current best practices and recommendations for relevant aspects of radiomics analyses, including study design, quality assurance, data collection, impact of acquisition and reconstruction, detection and segmentation, feature standardization and implementation, as well as appropriate modelling schemes, model evaluation, and interpretation. We also offer an outlook for future perspectives. Conclusion: Radiomics is a very quickly evolving field of research. The present guideline focused on established findings as well as recommendations based on the state of the art. Though this guideline recognizes both hand-crafted and deep learning-based radiomics approaches, it primarily focuses on the former as this field is more mature. This guideline will be updated once more studies and results have contributed to improved consensus regarding the application of deep learning methods for radiomics. Although methodological recommendations in the present document are valid for most medical image modalities, we focus here on nuclear medicine, and specific recommendations when necessary are made for PET/CT, PET/MR, and quantitative SPECT.

PURPOSE: Image analysis is one of the most promising applications of artificial intelligence (AI) in health care, potentially improving prediction, diagnosis, and treatment of diseases. Although scientific advances in this area critically depend on the accessibility of large-volume and high-quality data, sharing data between institutions faces various ethical and legal constraints as well as organizational and technical obstacles. METHODS: The Joint Imaging Platform (JIP) of the German Cancer Consortium (DKTK) addresses these issues by providing federated data analysis technology in a secure and compliant way. Using the JIP, medical image data remain in the originator institutions, but analysis and AI algorithms are shared and jointly used. Common standards and interfaces to local systems ensure permanent data sovereignty of participating institutions. RESULTS: The JIP is established in the radiology and nuclear medicine departments of 10 university hospitals in Germany (DKTK partner sites). In multiple complementary use cases, we show that the platform fulfills all relevant requirements to serve as a foundation for multicenter medical imaging trials and research on large cohorts, including the harmonization and integration of data, interactive analysis, automatic analysis, federated machine learning, and extensibility and maintenance processes, which are elementary for the sustainability of such a platform. CONCLUSION: The results demonstrate the feasibility of using the JIP as a federated data analytics platform in heterogeneous clinical information technology and software landscapes, solving an important bottleneck for the application of AI to large-scale clinical imaging data.

Introduction:¹⁸F-PSMA-1007 PET is used in the management of patients with prostate cancer. However, recent reports indicate a high rate of non-specific bone uptake (NSBU) with ¹⁸F-PSMA-1007, which may lead to false positive diagnosis. NSBU have not been evaluated thoroughly. Here, we evaluate the frequency of NSBU and bone metastases separately for ¹⁸F-PSMA-1007 and ⁶⁸Ga-PSMA-11 in biochemical recurrence (interindividual comparison). Additionally, we investigate NSBU seen in ¹⁸F-PSMA-1007 through follow up examinations (intraindividual comparison) using ⁶⁸Ga-PSMA-11 PET, bone scintigraphy and MRI. Methods: First, all patients (n = 383) who had ⁶⁸Ga-PSMA-11 PET between January 2020 and December 2020 and all patients (n = 409) who had ¹⁸F-PSMA-1007 PET between January 2020 and November 2021 due to biochemical recurrence were included for an interindividual comparison of bone metastases and NSBU rate. In a second approach, we regarded all patients with NSBU in ¹⁸F-PSMA-1007, characterized by focal bone uptake with SUV_max>4 and PSA≤5 ng/ml, who had an additional ⁶⁸Ga-PSMA-11 PET (n = 17) (interindividual comparison). Of these, 12 patients also had bone scintigraphy and wbMRI within a 1–5-week interval. Bone uptake seen on ¹⁸F-PSMA-1007 but not on any of the other four modalities (CT, MRI (n = 1), bone scan and ⁶⁸Ga-PSMA-11 PET) was recorded as false positive. Results: Patients scanned with ¹⁸F-PSMA-1007 PET had a significantly higher rate of NSBU compared with ⁶⁸Ga-PSMA-11 (140 vs. 64; p<0.001); however, the rate of bone metastases was not significantly different (72 vs. 64; P = 0.7). In the intraindividual comparison group, workup by CT, MRI, bone scan and ⁶⁸Ga-PSMA-11 PET resulted in a positive predictive value for ¹⁸F-PSMA-1007 focal bone uptake (mean SUV_max 6.1±2.9) per patient and per lesion of 8.3 % and 3.6 %, respectively. Conclusion: In patients with PSA≤5 ng/mL and SUV>4 at biochemical recurrence, most ¹⁸F-PSMA-1007 focal bone uptake are likely to be false positive and therefore due to NSBU. In case of low clinical likelihood of metastatic disease, ¹⁸F-PSMA-1007 bone uptake without morphologic surrogate should be assessed carefully with regard to localization and clinical context. However, the rate of bone metastases was not higher with ¹⁸F-PSMA-1007 in the clinical routine, indicating that experienced reporting physicians adjust for NSBU findings.

Introduction:¹⁸F-2-Fluoro-2-deoxyglucose (¹⁸F-FDG) in addition to Prostate Specific Membrane Antigen (PSMA) PET has been employed to assess the eligibility for PSMA-targeted therapy by some centers. However, it remains unclear, if both examinations are needed as a part of work-up in the clinical practice, or if PSMA-PET alone, as was done in the positive phase 3 VISION trial, is sufficient to identify suitable candidates. The aim was to re-analyze all patients who received both ¹⁸F-FDG- and PSMA-PET for PSMA-targeted therapy eligibility assessment using the VISION trial criteria. Methods: Eighty-nine men with mCRPC referred to ¹⁷⁷Lu-PSMA therapy from June 2019 until October 2021 who received both ¹⁸F-FDG- and PSMA-PET (using either ⁶⁸Ga-PSMA-11 or ¹⁸F-PSMA-1007) examinations within 2 weeks were included in this analysis. Eligibility status was determined in accordance with either (a) knowledge of both ¹⁸F-FDG- and PSMA-PET (clinical routine) or (b) VISION criteria with PSMA-PET only (study reassessment, done twice with liver only for PSMA-11 and liver/spleen as reference for PSMA-1007). A metastasis seen on ¹⁸F-FDG-PET or CT but not on PSMA-PET was denoted as a mismatch finding and led to exclusion from ¹⁷⁷Lu-PSMA therapy. Based on clinical assessment, 52 patients received ¹⁷⁷Lu-PSMA therapy, 37 did not; all patients were reassessed. Results: Patients treated with ¹⁷⁷Lu-PSMA therapy had significantly longer OS than those not treated (12.4 vs. 6.8 months, p<0.01). PSMA-only analysis (spleen/liver reference) and ¹⁸F-FDG/PSMA mismatch reads had a substantial agreement (Cohen`s κ=0.73). 18% (n = 16/89) of patients had a mismatch finding based on ¹⁸F-FDG/PSMA-PET. With the liver/spleen reference, a minor fraction of patients who had no mismatch finding (and were therefore treated) would have been withheld from therapy by PSMA-only analysis (3%). 3% (n = 3) of all patients had an ¹⁸F-FDG/PSMA mismatch finding not detected by the PSMA-PET only (VISION-like) analysis. For patients not receiving PSMA therapy, the overall survival was not statistically significantly different comparing ¹⁸F-FDG/PSMA mismatch vs. non-mismatch (P = 0.61) patients. Conclusion:¹⁸F-FDG- and PSMA-PET provide complementary information, yet less than 5% of patients had mismatch findings not detected using PSMA-PET only. Based on our data, ¹⁸F- FDG/PSMA mismatch examination and PSMA-only analysis have a substantial level of agreement.