Expanding the spectrum of low-grade sinonasal adenocarcinoma with biphasic seromucinous differentiation and activating HRAS/AKT1 mutations.

AIMS: Low-grade non-intestinal-type sinonasal adenocarcinoma (LGSNAC) is a rare heterogeneous and poorly characterised group of tumours, distinct from intestinal- and salivary-type neoplasms. Therefore, further characterisation is needed for clearer biological understanding and classification. METHODS AND RESULTS: Clinical, histological and molecular characterisation of four cases of biphasic, low-grade adenocarcinomas of the sinonasal tract was performed. All patients were male, aged between 48 and 78 years, who presented with polypoid masses in the nasal cavity. Microscopically, virtually all tumours were dominated by tubulo-glandular biphasic patterns, microcystic, focal (micro)papillary, oncocytic or basaloid features. Immunohistochemical staining confirmed biphasic differentiation with an outer layer of myoepithelial cells. Molecular profiling revealed HRAS (p.G13R, p.Q61R) mutations, and concomitant AKT1 (p.E17K, p.Q79R) mutations in two cases. Two cases showed potential in-situ/precursor lesions adjacent to the tumour. Follow-up periods ranged from 1 to 30 months, with one case relapsing locally after 12 and > 20 years. CONCLUSION: This study further corroborates a distinct biphasic low-grade neoplasm of the sinonasal tract with seromucinous differentiation. Although morphological and molecular features overlap with salivary gland epithelial-myoepithelial carcinoma, several arguments favour categorising these tumours within the spectrum of LGSNAC.

Changes in tumor-to-blood ratio as a prognostic marker for progression-free survival and overall survival in neuroendocrine tumor patients undergoing PRRT.

BACKGROUND: Historically, patient selection for peptide receptor radionuclide therapy (PRRT) has been performed by virtue of somatostatin receptor scintigraphy (SRS). In recent years, somatostatin receptor positron emission tomography (SSTR-PET) has gradually replaced SRS because of its improved diagnostic capacity, creating an unmet need for SSTR-PET-based selection criteria for PRRT. Tumor-to-blood ratio (TBR) measurements have shown high correlation with the net influx rate Ki, reflecting the tumor somatostatin receptor expression, to a higher degree than standardized uptake value (SUV) measurements. TBR may therefore predict treatment response to PRRT. In addition, changes in semiquantitative SSTR-PET parameters have been shown to predate morphological changes, making them a suitable metric for response assessment. METHODS: The institutional database of the Department of Nuclear Medicine (University Hospital Essen) was searched for NET patients undergoing ≥ 2 PRRT cycles with available baseline and follow-up SSTR-PET. Two blinded independent readers reported the occurrence of new lesions quantified tumor uptake of up to nine lesions per patient using SUV and TBR. The association between baseline TBR and changes in uptake/occurrence of new lesions with progression-free survival (PFS) and overall survival (OS) was tested by use of a Cox regression model and log-rank test. RESULTS: Patients with baseline TBR in the 1st quartile had a shorter PFS (14.4 months) than those in the 3rd (23.7 months; p = 0.03) and 4th (24.1 months; p = 0.02) quartile. Similarly, these patients had significantly shorter OS (32.5 months) than those with baseline TBR in the 2nd (41.8 months; p = 0.03), 3rd (69.2 months; p < 0.01), and 4th (42.7 months; p = 0.03) quartile. Baseline to follow-up increases in TBR were independently associated with shorter PFS when accounting for prognostic markers, e.g., RECIST response (hazard ratio = 2.91 [95%CI = 1.54-5.50]; p = 0.01). This was confirmed with regard to OS (hazard ratio = 1.64 [95%CI = 1.03-2.62]; p = 0.04). Changes in SUVmean were not associated with PFS or OS. CONCLUSIONS: Baseline TBR as well as changes in TBR were significantly associated with PFS and OS and may improve patient selection and morphological response assessment. Future trials need to assess the role of TBR for therapy monitoring also during PRRT and prospectively explore TBR as a predictive marker for patient selection.

Sedation-free pediatric [18F]FDG imaging on totalbody PET/CT with the assistance of artificial intelligence.

PURPOSE: While sedation is routinely used in pediatric PET examinations to preserve diagnostic quality, it may result in side effects and may affect the radiotracer's biodistribution. This study aims to investigate the feasibility of sedation-free pediatric PET imaging using ultra-fast total-body (TB) PET scanners and deep learning (DL)-based attenuation and scatter correction (ASC). METHODS: This retrospective study included TB PET (uExplorer) imaging of 35 sedated pediatric patients under four years old to determine the minimum effective scanning time. A DL-based ASC method was applied to enhance PET quantification. Both quantitative and qualitative assessments were conducted to evaluate the image quality of ultra-fast DL-ASC PET. Five non-sedated pediatric patients were subsequently used to validate the proposed approach. RESULTS: Comparisons between standard 300-second and ultra-fast 15-second imaging, CT-ASC and DL-ASC ultra-fast 15-second images, as well as DL-ASC ultra-fast 15-second images in non-sedated and sedated patients, showed no significant differences in qualitative scoring, lesion detectability, and quantitative Standard Uptake Value (SUV) (P = ns). CONCLUSIONS: This study demonstrates that pediatric PET imaging can be effectively performed without sedation by combining ultra-fast imaging techniques with a DL-based ASC. This advancement in sedation-free ultra-fast PET imaging holds potential for broader clinical adoption.

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.

Multicenter development of a PET-based risk assessment tool for product-specific outcome prediction in large B-cell lymphoma patients undergoing CAR T-cell therapy.

PURPOSE: The emergence of chimeric antigen receptor (CAR) T-cell therapy fundamentally changed the management of individuals with relapsed and refractory large B-cell lymphoma (LBCL). However, real-world data have shown divergent outcomes for the approved products. The present study therefore set out to evaluate potential risk factors in a larger cohort. METHODS: Our analysis set included 88 patients, treated in four German university hospitals and one Italian center, who had undergone 2-[18F]fluoro-2-deoxy-D-glucose positron emission tomography (PET) before CAR T-cell therapy with tisagenlecleucel or axicabtagene ciloleucel. We first determined the predictive value of conventional risk factors, treatment lines, and response to bridging therapy for progression-free survival (PFS) through forward selection based on Cox regression. In a second step, the additive potential of two common PET parameters was assessed. Their optimal dichotomizing thresholds were calculated individually for each CAR T-cell product. RESULTS: Extra-nodal involvement emerged as the most relevant of the conventional tumor and patient characteristics. Moreover, we found that inclusion of metabolic tumor volume (MTV) further improves outcome prediction. The hazard ratio for a PFS event was 1.68 per unit increase of our proposed risk score (95% confidence interval [1.20, 2.35], P = 0.003), which comprised both extra-nodal disease and lymphoma burden. While the most suitable MTV cut-off among patients receiving tisagenlecleucel was 11 mL, a markedly higher threshold of 259 mL showed optimal predictive performance in those undergoing axicabtagene ciloleucel treatment. CONCLUSION: Our analysis demonstrates that the presence of more than one extra-nodal lesion and higher MTV in LBCL are associated with inferior outcome after CAR T-cell treatment. Based on an assessment tool including these two factors, patients can be assigned to one of three risk groups. Importantly, as shown by our study, metabolic tumor burden might facilitate CAR T-cell product selection and reflect the individual need for bridging therapy.

Epstein Barr virus-directed T-cell therapy for refractory EBV-PTLD in a toddler post Orthotopic heart transplantation.

Epstein-Barr Virus (EBV) is a ubiquitous herpes type virus that is associated with post-transplant lymphoproliferative disorder (PTLD). Usual management includes reduction or cessation of immunosuppression and in some cases chemotherapy including rituximab. However, limited therapies are available if PTLD is refractory to rituximab. Several clinical trials have investigated the use of EBV-directed T cells in rituximab-refractory patients; however, data regarding response is scarce and inconclusive. Herein, we describe a patient with EBV-PTLD refractory to rituximab after orthotopic heart transplantation (OHT) requiring EBV-directed T-cell therapy. This article aims to highlight the unique and aggressive clinical presentation and progression of PTLD with utilization of EBV-directed T-cell therapy for management and associated pitfalls.

A Prognostic Risk Score for Prostate Cancer Based on PSMA PET-derived Organ-specific Tumor Volumes.

Background Prostate-specific membrane antigen (PSMA) PET has high specificity in localizing primary tumors and metastases in patients with prostate cancer, but the individual overall survival probability is still difficult to estimate. Purpose To develop a prognostic risk score using PSMA PET-derived organ-specific total tumor volumes for predicting overall survival in patients with prostate cancer. Materials and Methods Men with prostate cancer who underwent PSMA PET/CT from January 2014 to December 2018 were evaluated retrospectively. All patients from center A were split into training (80%) and internal validation (20%) cohorts. Randomly selected patients from center B were used for external validation. Organ-specific tumor volumes were automatically quantified from PSMA PET scans by a neural network. A prognostic score was selected using multivariable Cox regression guided by the Akaike information criterion (AIC). The final prognostic risk score fitted on the training set was applied to both validation cohorts. Results A total of 1348 men (mean age, 70 years ± 8 [SD]) were included, with 918 patients in the training cohort, 230 in the internal validation cohort, and 200 in the external validation cohort. The median follow-up time was 55.7 months (IQR, 46.7-65.1 months; >4 years; 429 deaths occurred). A body weight-adjusted prognostic risk score integrating total, bone, and visceral tumor volumes obtained high C index values in the internal (0.82) and external (0.74) validation cohorts, as well as in patients with castration-resistant (0.75) and hormone-sensitive (0.68) disease. The fit of the statistical model for the prognostic score was improved compared with a model containing total tumor volume only (AIC, 3324 vs 3351; likelihood ratio test, P < .001). Calibration plots ascertained good model fit. Conclusion The newly developed risk score that included prostate-specific membrane antigen PET-derived organ-specific tumor volumes had good model fit for predicting overall survival in both internal and external validation cohorts. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Civelek in this issue.

Evaluation of thresholding methods for the quantification of [68Ga]Ga-PSMA-11 PET molecular tumor volume and their effect on survival prediction in patients with advanced prostate cancer undergoing [177Lu]Lu-PSMA-617 radioligand therapy.

PURPOSE: The aim of this study was to systematically evaluate the effect of thresholding algorithms used in computer vision for the quantification of prostate-specific membrane antigen positron emission tomography (PET) derived tumor volume (PSMA-TV) in patients with advanced prostate cancer. The results were validated with respect to the prognostication of overall survival in patients with advanced-stage prostate cancer. MATERIALS AND METHODS: A total of 78 patients who underwent [177Lu]Lu-PSMA-617 radionuclide therapy from January 2018 to December 2020 were retrospectively included in this study. [68Ga]Ga-PSMA-11 PET images, acquired prior to radionuclide therapy, were used for the analysis of thresholding algorithms. All PET images were first analyzed semi-automatically using a pre-evaluated, proprietary software solution as the baseline method. Subsequently, five histogram-based thresholding methods and two local adaptive thresholding methods that are well established in computer vision were applied to quantify molecular tumor volume. The resulting whole-body molecular tumor volumes were validated with respect to the prognostication of overall patient survival as well as their statistical correlation to the baseline methods and their performance on standardized phantom scans. RESULTS: The whole-body PSMA-TVs, quantified using different thresholding methods, demonstrate a high positive correlation with the baseline methods. We observed the highest correlation with generalized histogram thresholding (GHT) (Pearson r (r), p value (p): r = 0.977, p < 0.001) and Sauvola thresholding (r = 0.974, p < 0.001) and the lowest correlation with Multiotsu (r = 0.877, p < 0.001) and Yen thresholding methods (r = 0.878, p < 0.001). The median survival time of all patients was 9.87 months (95% CI [9.3 to 10.13]). Stratification by median whole-body PSMA-TV resulted in a median survival time from 11.8 to 13.5 months for the patient group with lower tumor burden and 6.5 to 6.6 months for the patient group with higher tumor burden. The patient group with lower tumor burden had significantly higher probability of survival (p < 0.00625) in eight out of nine thresholding methods (Fig. 2); those methods were SUVmax50 (p = 0.0038), SUV ≥3 (p = 0.0034), Multiotsu (p = 0.0015), Yen (p = 0.0015), Niblack (p = 0.001), Sauvola (p = 0.0001), Otsu (p = 0.0053), and Li thresholding (p = 0.0053). CONCLUSION: Thresholding methods commonly used in computer vision are promising tools for the semiautomatic quantification of whole-body PSMA-TV in [68Ga]Ga-PSMA-11-PET. The proposed algorithm-driven thresholding strategy is less arbitrary and less prone to biases than thresholding with predefined values, potentially improving the application of whole-body PSMA-TV as an imaging biomarker.

First experiences with dynamic renal [68Ga]Ga-DOTA PET/CT: a comparison to renal scintigraphy and compartmental modelling to non-invasively estimate the glomerular filtration rate.

PURPOSE: The determination of the glomerular filtration rate (GFR) is decisive for a variety of clinical issues, for example, to monitor the renal function in radionuclide therapy patients. Renal scintigraphy using glomerularly filtered tracers allows combined acquisition of renograms and GFR estimation but requires repeated blood sampling for several hours. In contrast, dynamic PET imaging using the glomerularly filtered tracer [68Ga]Ga-DOTA bears the potential to non-invasively estimate the GFR by compartmental kinetic modelling. Here, we report the, to our knowledge, first comparison of human renal dynamic [68Ga]Ga-DOTA PET imaging in comparison to renal scintigraphy and compare PET-derived to serum creatinine-derived GFR measurements. METHODS: Dynamic [68Ga]Ga-DOTA PET data were acquired for 30 min immediately after tracer injection in 12 patients. PET and renal scintigraphy images were visually interpreted in a consensus read by three nuclear medicine physicians. The functional renal cortex was segmented to obtain time-activity curves. The arterial input function was estimated from the PET signal in the abdominal aorta. Single-compartmental tracer kinetic modelling was performed to calculate the GFR using complete 30-min (GFRPET-30) and reduced 15-min PET data sets (GFRPET-15) to evaluate whether a shorter acquisition time is sufficient for an accurate GFR estimation. A modified approach excluding minutes 2 to 10 was applied to reduce urinary spill-over effects. Serum creatinine-derived GFRCKD (CKD-EPI-formula) was used as reference standard. RESULTS: PET image interpretation revealed the same findings as conventional scintigraphy (2/12 patients with both- and 1/12 patients with right-sided urinary obstruction). Model fit functions were substantially improved for the modified approach to exclude spill-over. Depending on the modelling approach, GFRCKD and both GFRPET-30 and GFRPET-15 were well correlated with interclass correlation coefficients (ICCs) from 0.74 to 0.80 and Pearson's correlation coefficients (PCCs) from 0.74 to 0.81. For a subgroup of patients with undisturbed urinary efflux (n = 9), correlations were good to excellent (ICCs from 0.82 to 0.95 and PCCs from 0.83 to 0.95). Overall, GFRPET-30 and GFRPET-15 were excellently correlated (ICCs from 0.96 to 0.99 and PCCs from 0.96 to 0.99). CONCLUSION: Renal [68Ga]Ga-DOTA PET can be a suitable alternative to conventional scintigraphy. Visual assessment of PET images and conventional renograms revealed comparable results. GFR values derived by non-invasive single-compartmental-modelling of PET data show a good correlation to serum creatinine-derived GFR values. In patients with undisturbed urinary efflux, the correlation was excellent. Dynamic PET data acquisition for 15 min is sufficient for visual evaluation and GFR derivation.

Artificial intelligence guided enhancement of digital PET: scans as fast as CT?

PURPOSE: Both digital positron emission tomography (PET) detector technologies and artificial intelligence based image post-reconstruction methods allow to reduce the PET acquisition time while maintaining diagnostic quality. The aim of this study was to acquire ultra-low-count fluorodeoxyglucose (FDG) ExtremePET images on a digital PET/computed tomography (CT) scanner at an acquisition time comparable to a CT scan and to generate synthetic full-dose PET images using an artificial neural network. METHODS: This is a prospective, single-arm, single-center phase I/II imaging study. A total of 587 patients were included. For each patient, a standard and an ultra-low-count FDG PET/CT scan (whole-body acquisition time about 30 s) were acquired. A modified pix2pixHD deep-learning network was trained employing 387 data sets as training and 200 as test cohort. Three models (PET-only and PET/CT with or without group convolution) were compared. Detectability and quantification were evaluated. RESULTS: The PET/CT input model with group convolution performed best regarding lesion signal recovery and was selected for detailed evaluation. Synthetic PET images were of high visual image quality; mean absolute lesion SUVmax (maximum standardized uptake value) difference was 1.5. Patient-based sensitivity and specificity for lesion detection were 79% and 100%, respectively. Not-detected lesions were of lower tracer uptake and lesion volume. In a matched-pair comparison, patient-based (lesion-based) detection rate was 89% (78%) for PERCIST (PET response criteria in solid tumors)-measurable and 36% (22%) for non PERCIST-measurable lesions. CONCLUSION: Lesion detectability and lesion quantification were promising in the context of extremely fast acquisition times. Possible application scenarios might include re-staging of late-stage cancer patients, in whom assessment of total tumor burden can be of higher relevance than detailed evaluation of small and low-uptake lesions.

Phantom-based acquisition time and image reconstruction parameter optimisation for oncologic FDG PET/CT examinations using a digital system.

BACKGROUND: New-generation silicon-photomultiplier (SiPM)-based PET/CT systems exhibit an improved lesion detectability and image quality due to a higher detector sensitivity. Consequently, the acquisition time can be reduced while maintaining diagnostic quality. The aim of this study was to determine the lowest 18F-FDG PET acquisition time without loss of diagnostic information and to optimise image reconstruction parameters (image reconstruction algorithm, number of iterations, voxel size, Gaussian filter) by phantom imaging. Moreover, patient data are evaluated to confirm the phantom results. METHODS: Three phantoms were used: a soft-tissue tumour phantom, a bone-lung tumour phantom, and a resolution phantom. Phantom conditions (lesion sizes from 6.5 mm to 28.8 mm in diameter, lesion activity concentration of 15 kBq/mL, and signal-to-background ratio of 5:1) were derived from patient data. PET data were acquired on an SiPM-based Biograph Vision PET/CT system for 10 min in list-mode format and resampled into time frames from 30 to 300 s in 30-s increments to simulate different acquisition times. Different image reconstructions with varying iterations, voxel sizes, and Gaussian filters were probed. Contrast-to-noise-ratio (CNR), maximum, and peak signal were evaluated using the 10-min acquisition time image as reference. A threshold CNR value ≥ 5 and a maximum (peak) deviation of ± 20% were considered acceptable. 20 patient data sets were evaluated regarding lesion quantification as well as agreement and correlation between reduced and full acquisition time standard uptake values (assessed by Pearson correlation coefficient, intraclass correlation coefficient, Bland-Altman analyses, and Krippendorff's alpha). RESULTS: An acquisition time of 60 s per bed position yielded acceptable detectability and quantification results for clinically relevant phantom lesions ≥ 9.7 mm in diameter using OSEM-TOF or OSEM-TOF+PSF image reconstruction, a 4-mm Gaussian filter, and a 1.65 × 1.65 x 2.00-mm3 or 3.30 × 3.30 x 3.00-mm3 voxel size. Correlation and agreement of patient lesion quantification between full and reduced acquisition times were excellent. CONCLUSION: A threefold reduction in acquisition time is possible. Patients might benefit from more comfortable examinations or reduced radiation exposure, if instead of the acquisition time the applied activity is reduced.

Vesseg: An Open-Source Tool for Deep Learning-Based Atherosclerotic Plaque Quantification in Histopathology Images-Brief Report.

Objective: Manual plaque segmentation in microscopy images is a time-consuming process in atherosclerosis research and potentially subject to unacceptable user-to-user variability and observer bias. We address this by releasing Vesseg a tool that includes state-of-the-art deep learning models for atherosclerotic plaque segmentation. Approach and Results: Vesseg is a containerized, extensible, open-source, and user-oriented tool. It includes 2 models, trained and tested on 1089 hematoxylin-eosin stained mouse model atherosclerotic brachiocephalic artery sections. The models were compared to 3 human raters. Vesseg can be accessed at https://vesseg .online or downloaded. The models show mean Soerensen-Dice scores of 0.91+/-0.15 for plaque and 0.97+/-0.08 for lumen pixels. The mean accuracy is 0.98+/-0.05. Vesseg is already in active use, generating time savings of >10 minutes per slide. Conclusions: Vesseg brings state-of-the-art deep learning methods to atherosclerosis research, providing drastic time savings, while allowing for continuous improvement of models and the underlying pipeline.

Shining Damaged Hearts: Immunotherapy-Related Cardiotoxicity in the Spotlight of Nuclear Cardiology.

The emerging use of immunotherapies in cancer treatment increases the risk of immunotherapy-related cardiotoxicity. In contrast to conventional chemotherapy, these novel therapies have expanded the forms and presentations of cardiovascular damage to a broad spectrum from asymptomatic changes to fulminant short- and long-term complications in terms of cardiomyopathy, arrythmia, and vascular disease. In cancer patients and, particularly, cancer patients undergoing (immune-)therapy, cardio-oncological monitoring is a complex interplay between pretherapeutic risk assessment, identification of impending cardiotoxicity, and post-therapeutic surveillance. For these purposes, the cardio-oncologist can revert to a broad spectrum of nuclear cardiological diagnostic workup. The most promising commonly used nuclear medicine imaging techniques in relation to immunotherapy will be discussed in this review article with a special focus on the continuous development of highly specific molecular markers and steadily improving methods of image generation. The review closes with an outlook on possible new developments of molecular imaging and advanced image evaluation techniques in this exciting and increasingly growing field of immunotherapy-related cardiotoxicity.

Radiation dose aspects and establishment of diagnostic reference levels for90Y radioembolisation during angiographic procedure.

90Y radioembolisation (RE) is an angiographic procedure used in patients with both primary and secondary hepatic malignancies. Local tumour control can be achieved by short range tumour irradiation by the regional intra-arterial administration of glass or resin microspheres loaded with 90yttrium that accumulate in the tumorous tissue. The aim of this study was to investigate the radiation exposure of RE and to establish a local diagnostic reference level (DRL). In this retrospective study, dose data from 397 procedures in 306 patients (mean age 67.4 ± 10.6 years, 82 female) who underwent RE between 06/2017 and 01/2022 using one of two different angiography systems were analysed. DRL was set as the 75th percentile of the dose distribution. In the overall population, dose area product (DAP) (median (interquartile range, IQR)) was 26 Gy cm2(IQR 12-50) with a median fluoroscopy time (FT) of 4.5 min (IQR 2.9-8.0). FT and DAP increased significantly with the number of infusion positions (median, IQR): one position 23 Gy cm2(12-46), two positions 33 Gy cm2(14-60), three positions 50 Gy cm2(24-82) (p< 0.0001). Local DRL is 47 Gy cm2for RE and 111 Gy cm2for RE with additional embolisation. Radiation exposure and FT are significantly higher with increasing number of infusion positions as well as additional embolisation. Our established DRLs for RE may serve as a benchmark for dose optimisation.

Imaging and liquid biopsy in the prediction and evaluation of response to PRRT in neuroendocrine tumors: implications for patient management.

PURPOSE: The aim of this narrative review is to give an overview on current and emerging imaging methods and liquid biopsy for prediction and evaluation of response to PRRT. Current limitations and new perspectives, including artificial intelligence, are discussed. METHODS: A literature review of PubMed/Medline was performed with representative keywords. The search included articles published online through August 31, 2020. All searches were restricted to English language manuscripts. RESULTS: Peptide radio receptor therapy (PRRT) is a prospectively evaluated and approved therapy option in neuroendocrine tumors (NETs). Different ligands targeting the somatostatin receptor (SSTR) are used as theranostic pairs for imaging NET and for PRRT. Response assessment in prospective trials often relies on the morphological RECIST 1.1 criteria, based on lesion size in CT or MRI. The role of SSTR-PET and quantitative uptake parameters and volumetric data is still not defined. Monoanalyte tumor marker chromogranin A has a limited value for response assessment after PRRT. New emerging liquid biopsy techniques are offering prediction of response to PRRT and prognostic value. CONCLUSIONS: New response criteria for NET patients undergoing PRRT will comprise multiparametric hybrid imaging and blood-based multianalyte markers. This represents tumor biology and heterogeneity.

Just another "Clever Hans"? Neural networks and FDG PET-CT to predict the outcome of patients with breast cancer.

BACKGROUND: Manual quantification of the metabolic tumor volume (MTV) from whole-body 18F-FDG PET/CT is time consuming and therefore usually not applied in clinical routine. It has been shown that neural networks might assist nuclear medicine physicians in such quantification tasks. However, little is known if such neural networks have to be designed for a specific type of cancer or whether they can be applied to various cancers. Therefore, the aim of this study was to evaluate the accuracy of a neural network in a cancer that was not used for its training. METHODS: Fifty consecutive breast cancer patients that underwent 18F-FDG PET/CT were included in this retrospective analysis. The PET-Assisted Reporting System (PARS) prototype that uses a neural network trained on lymphoma and lung cancer 18F-FDG PET/CT data had to detect pathological foci and determine their anatomical location. Consensus reads of two nuclear medicine physicians together with follow-up data served as diagnostic reference standard; 1072 18F-FDG avid foci were manually segmented. The accuracy of the neural network was evaluated with regard to lesion detection, anatomical position determination, and total tumor volume quantification. RESULTS: If PERCIST measurable foci were regarded, the neural network displayed high per patient sensitivity and specificity in detecting suspicious 18F-FDG foci (92%; CI = 79-97% and 98%; CI = 94-99%). If all FDG-avid foci were regarded, the sensitivity degraded (39%; CI = 30-50%). The localization accuracy was high for body part (98%; CI = 95-99%), region (88%; CI = 84-90%), and subregion (79%; CI = 74-84%). There was a high correlation of AI derived and manually segmented MTV (R2 = 0.91; p < 0.001). AI-derived whole-body MTV (HR = 1.275; CI = 1.208-1.713; p < 0.001) was a significant prognosticator for overall survival. AI-derived lymph node MTV (HR = 1.190; CI = 1.022-1.384; p = 0.025) and liver MTV (HR = 1.149; CI = 1.001-1.318; p = 0.048) were predictive for overall survival in a multivariate analysis. CONCLUSION: Although trained on lymphoma and lung cancer, PARS showed good accuracy in the detection of PERCIST measurable lesions. Therefore, the neural network seems not prone to the clever Hans effect. However, the network has poor accuracy if all manually segmented lesions were used as reference standard. Both the whole body and organ-wise MTV were significant prognosticators of overall survival in advanced breast cancer.

PSMA PET total tumor volume predicts outcome of patients with advanced prostate cancer receiving [177Lu]Lu-PSMA-617 radioligand therapy in a bicentric analysis.

INTRODUCTION: [177Lu]Lu-PSMA-617 (Lu-PSMA) radioligand therapy is an emerging treatment option for patients with end-stage prostate cancer. However, response to Lu-PSMA therapy is only achieved in approximately half of patients. It is clinically important to identify patients at risk of poor outcome. Therefore, the aim of this study was to evaluate pretherapeutic PSMA PET derived total tumor volume and related metrics as prognosticators of overall survival in patients receiving Lu-PSMA therapy. METHODS: A total number of 110 patients form the Departments of Nuclear Medicine Münster and Essen were included in this retrospective analysis. Baseline PSMA PET-CT was available for all patients. Employing a previously published approach, all tumor lesions were semi-automatically delineated in PSMA PET-CT acquisitions. Total lesion number, total tumor volume (PSMA-TV), total lesion uptake (PSMA-TLU = PSMA-TV * SUVmean), and total lesion quotient (PSMA-TLQ = PSMA-TV / SUVmean) were quantified for each patient. Log2 transformation was used for regressions. RESULTS: Lesion number, PSMA-TV, and PSMA-TLQ were prognosticators of overall survival (HR = 1.255, p = 0.009; HR = 1.299, p = 0.005; HR = 1.326, p = 0.002). In a stepwise backward Cox regression including lesion number, PSMA-TV, PSA, LDH, and PSMA-TLQ, only the latter two remained independent and statistically significant negative prognosticators of overall survival (HR = 1.632, p = 0.011; HR = 1.239, p = 0.024). PSMA-TLQ and LDH were significant negative prognosticators in multivariate Cox regression in contrast to PSA value. CONCLUSION: PSMA-TV was a statistically significant negative prognosticator of overall survival in patients receiving Lu-PSMA therapy. PSMA-TLQ was an independent and superior prognosticator of overall survival compared with PSMA-TV.

The impact of the extent of the bone involvement on overall survival and toxicity in mCRPC patients receiving [177Lu]Lu-PSMA-617: a WARMTH multicentre study.

INTRODUCTION: Prostate-specific membrane antigen (PSMA)-based radioligand therapy (RLT) showed in a multicentre WARMTH (World Association of Radiopharmaceutical and Molecular Therapy) study that the presence of bone metastases is a negative prognosticator for the survival. The current multicentre retrospective analysis aims to evaluate the response rate to RLT, the overall survival (OS) of patients and the safety of the treatment according to the extent of bone involvement. METHODS: The study included patients with progressive metastatic castration-resistant prostate cancer (mCRPC), who underwent RLT with [177Lu]Lu-PSMA-617 and a follow-up of at least 6 months. Tumour burden in the bone was classified prior to RLT as follows: less than 6 lesions, 6-20 lesions, more than 20 lesions and diffuse involvement. The response rate was evaluated using changes of the prostate-specific antigen (PSA) after the first treatment cycle. Overall survival was calculated from the date of the first treatment. Haematological adverse events were classified according to Common Terminology Criteria for Adverse Events (CTCAE), version 5.0. RESULTS: A total of 319 males were included in the analysis. The extent of bone metastases and PSA response did not correlate significantly. Any PSA decline was observed in 73% patients; 44% showed a decline of ≥50%. The median OS of patient in the different subgroups was 18 months (less than 6 lesions), 13 months (6-20 lesions), 11 months (more than 20 lesions) and 8 months (diffuse involvement), respectively (p < 0.0001). Patients with prior Ra-223-therapy showed longer OS in all subgroups, especially in the subgroups with 6-20 lesions (OS: 16 vs. 12 months; p = 0.038) as well as diffuse involvement (OS: 11 vs. 7 months; p = 0.034). Significant negative prognosticators of OS were the existence of liver metastases in all subgroups and prior chemotherapy in patients with <6 bone lesions. Anaemia and thrombocytopenia correlated positively with the extent of bone metastases: p < 0.0001 and 0.005, respectively. No patient showed a high grade leukopenia. CONCLUSION: The extent of bone involvement correlated negatively with the OS after RLT; however, it showed no relevant correlation with the PSA response rate. Prior therapy with Ra-223 may have a positive impact on OS. Haematotoxicity was higher in patients with more than 20 bone lesions; nevertheless, the majority of these patients did not show a relevant haematotoxicity.

Prior therapies as prognostic factors of overall survival in metastatic castration-resistant prostate cancer patients treated with [177Lu]Lu-PSMA-617. A WARMTH multicenter study (the 617 trial).

INTRODUCTION: The impact of prior therapies, especially chemotherapy, on overall survival (OS) in patients with castration-resistant prostate cancer (CRPC) receiving [177Lu]Lu-PSMA-617 therapy has been the subject of controversy. Therefore, WARMTH decided to plan a multicenter retrospective analysis (the "617 trial") to evaluate response rate and OS as well as the impact of prior therapies on OS in more than 300 patients treated with 177Lu-PSMA-617. MATERIALS AND METHODS: The data of 631 metastatic CRPC (mCRPC) patients from 11 different clinics were evaluated. According to the inclusion and exclusion criteria, all patients had to have received at least abiraterone or enzalutamide prior to [177Lu]Lu-PSMA-617 therapy. The patients were divided into three groups: patients who had received prior chemotherapy, patients who avoided chemotherapy, and patients for whom a chemotherapy was contraindicated. RESULTS: The analysis included the data of 416 patients, with a median age of 71.9 years. At the time of analysis, 87 patients (20,9%) were still alive. A total of 53.6% of patients had received both abiraterone and enzalutamide; 75.5% and 26.4% had a history of chemotherapy with docetaxel and cabazitaxel, respectively. A total of 20.4% had had Ra-223. The median OS was 11.1 months. Prior chemotherapy, the existence of bone and liver metastases, as well as Eastern Cooperative Oncology Group (ECOG) status, were significant prognosticators of worse overall survival in both univariate and multivariate analyses. Patients without any prior chemotherapy showed a significantly longer OS (14.6 months). The median OS in patients who received one or two lines of chemotherapy with docetaxel or docetaxel followed by cabazitaxel, respectively, was 10.9 months and 8.9 months. There was no difference in OS between patients who had not received chemotherapy and patients for whom chemotherapy was contraindicated. The other prior therapies did not have any significant impact on OS. CONCLUSION: In the present multicenter analysis, chemotherapy-naïve mCRPC patients receiving [177Lu]Lu-PSMA-617 therapy had a significantly longer OS than patients with a history of chemotherapy. This remained independent in the multivariate analysis besides presence of bone and liver metastases as negative prognosticators for survival, whereas an ECOG of 0-1 is associated with a longer OS.

Prospective comparison of the diagnostic accuracy of 18F-FDG PET/MRI, MRI, CT, and bone scintigraphy for the detection of bone metastases in the initial staging of primary breast cancer patients.

OBJECTIVES: To compare the diagnostic performance of [18F]FDG PET/MRI, MRI, CT, and bone scintigraphy for the detection of bone metastases in the initial staging of primary breast cancer patients. MATERIAL AND METHODS: A cohort of 154 therapy-naive patients with newly diagnosed, histopathologically proven breast cancer was enrolled in this study prospectively. All patients underwent a whole-body [18F]FDG PET/MRI, computed tomography (CT) scan, and a bone scintigraphy prior to therapy. All datasets were evaluated regarding the presence of bone metastases. McNemar χ2 test was performed to compare sensitivity and specificity between the modalities. RESULTS: Forty-one bone metastases were present in 7/154 patients (4.5%). Both [18F]FDG PET/MRI and MRI alone were able to detect all of the patients with histopathologically proven bone metastases (sensitivity 100%; specificity 100%) and did not miss any of the 41 malignant lesions (sensitivity 100%). CT detected 5/7 patients (sensitivity 71.4%; specificity 98.6%) and 23/41 lesions (sensitivity 56.1%). Bone scintigraphy detected only 2/7 patients (sensitivity 28.6%) and 15/41 lesions (sensitivity 36.6%). Furthermore, CT and scintigraphy led to false-positive findings of bone metastases in 2 patients and in 1 patient, respectively. The sensitivity of PET/MRI and MRI alone was significantly better compared with CT (p < 0.01, difference 43.9%) and bone scintigraphy (p < 0.01, difference 63.4%). CONCLUSION: [18F]FDG PET/MRI and MRI are significantly better than CT or bone scintigraphy for the detection of bone metastases in patients with newly diagnosed breast cancer. Both CT and bone scintigraphy show a substantially limited sensitivity in detection of bone metastases. KEY POINTS: • [18F]FDG PET/MRI and MRI alone are significantly superior to CT and bone scintigraphy for the detection of bone metastases in patients with newly diagnosed breast cancer. • Radiation-free whole-body MRI might serve as modality of choice in detection of bone metastases in breast cancer patients.