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Purpose Performing 2-[18F]FDG PET/CT in addition to a PSMA-ligand PET/CT can assist in the detection of lesions with low PSMA expression and may help in prognostication and identification of patients who likely benefit from PSMA-radioligand therapy (PSMA-RLT). However, the cost and time needed for a separate PET/CT examination might hinder its routine implementation. In this communication, we present our initial experiences with additional low-dose 2-[18F]FDG PET/CT as part of a dual-tracer and same-day imaging protocol which exploits the higher sensitivity exhibited by long-axial field-of-view (LAFOV) and total-body PET/CT systems and demonstrates its feasibility. Methods Fourteen patients referred for evaluation for PSMA-RLT received [68 Ga]Ga-PSMA-11 PET/CT at 1 h p.i. with a standard activity of 150 MBq and an additional low-dose 2-[18F]FDG PET/CT with 40 MBq 1 h thereafter using a long-axial field-of-view PET/CT system in a single sitting and as per institutional protocol. Scans were scrutinized by two experienced nuclear medicine physicians for mismatch findings. Results The combined protocol identified additional lesions with low or absent PSMA-expression but high FDG-avidity in 1/14 (7%) patients. The protocol was easily implemented and well tolerated by all patients. Conclusion Additional low-dose 2-[18F]FDG-PET/CT is feasible as part of a same-day imaging protocol and can help reveal lesions of low PSMA avidity as part of therapy assessment for [177Lu]-PSMA radioligand therapy and demonstrates higher sensitivity compared to [68 Ga]Ga-PSMA-11 PET/CT alone in some patients.

Background Accurate kinetic modeling of 18F-fluorodeoxyglucose ([18F]-FDG) positron emission tomography (PET) data requires accurate knowledge of the available tracer concentration in the plasma during the scan time, known as the arterial input function (AIF). The gold standard method to derive the AIF requires collection of serial arterial blood samples, but the introduction of long axial field of view (LAFOV) PET systems enables the use of non-invasive image-derived input functions (IDIFs) from large blood pools such as the aorta without any need for bed movement. However, such protocols require a prolonged dynamic PET acquisition, which is impractical in a busy clinical setting. Population-based input functions (PBIFs) have previously shown potential in accurate Patlak analysis of [18F]-FDG datasets and can enable the use of shortened dynamic imaging protocols. Here, we exploit the high sensitivity and temporal resolution of a LAFOV PET system and explore the use of PBIF with abbreviated protocols in [18F]-FDG total body kinetic modeling. Methods Dynamic PET data were acquired in 24 oncological subjects for 65 min following the administration of [18F]-FDG. IDIFs were extracted from the descending thoracic aorta, and a PBIF was generated from 16 datasets. Five different scaled PBIFs (sPBIFs) were generated by scaling the PBIF with the AUC of IDIF curve tails using various portions of image data (35–65, 40–65, 45–65, 50–65, and 55–65 min post-injection). The sPBIFs were compared with the IDIFs using the AUCs and Patlak Ki estimates in tumor lesions and cerebral gray matter. Patlak plot start time (t*) was also varied to evaluate the performance of shorter acquisitions on the accuracy of Patlak Ki estimates. Patlak Ki estimates with IDIF and t* = 35 min were used as reference, and mean bias and precision (standard deviation of bias) were calculated to assess the relative performance of different sPBIFs. A comparison of parametric images generated using IDIF and sPBIFs was also performed. Results There was no statistically significant difference between AUCs of the IDIF and sPBIFs (Wilcoxon test: P > 0.05). Excellent agreement was shown between Patlak Ki estimates obtained using sPBIF and IDIF. Using the sPBIF55–65 with the Patlak model, 20 min of PET data (i.e., 45 to 65 min post-injection) achieved Ki estimates in tumor lesions compared to the estimates with the IDIF. Parametric images reconstructed using the IDIF and sPBIFs with and without an abbreviated protocol were visually comparable. Using Patlak Ki generated with an IDIF and 30 min of PET data as reference, Patlak Ki images generated using sPBIF55–65 with 20 min of PET data (t* = 45 min) provided excellent image quality with structural similarity index measure > 0.99 and peak signal-to-noise ratio > 55 dB. Conclusion We demonstrate the feasibility of performing accurate [18F]-FDG Patlak analysis using sPBIFs with only 20 min of PET data from a LAFOV PET scanner.

Background: Accurate kinetic modelling of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) data requires accurate knowledge of the available tracer concentration in the plasma during the scan time, known as the arterial input function (AIF). The gold standard method to derive the AIF requires collection of serial arterial blood samples but the introduction of long axial field of view (LAFOV) PET systems enables use of non-invasive image derived input functions (IDIF) from large blood pools such as the aorta without any need for bed movement. However, such protocols require a prolonged dynamic PET acquisition which is impractical in a busy clinical setting. Population-based input functions (PBIF) have previously shown potential in accurate Patlak analysis of 18F-FDG datasets and can enable the use of shortened dynamic imaging protocols. We not exploit the high sensitivity and temporal resolution of a LAFOV PET system and explore use of PBIF with abbreviated protocols in 18F-FDG total body kinetic modelling. Methods: Dynamic PET data were acquired in 24 oncological subjects for 65 minutes following the administration of 18F-FDG. IDIFs were extracted from the descending thoracic aorta and a PBIF was generated from 16 datasets. Five different scaled PBIFs (sPBIF) were generated by scaling the PBIF with AUC of IDIF curve tails using various portions of image data (35-65, 40-65, 45-65, 50-65 and 55-65 min post injection). The sPBIFs were compared with the IDIFs using the AUCs and Patlak Ki estimates in tumour lesions and cerebral grey matter. Patlak plot start time (t*) was also varied to evaluate the performance of shorter acquisitions on accuracy of Patlak Ki estimates. Patlak Ki estimates with IDIF and t*=35 min was used as reference and mean bias and precision (standard deviation of bias) were calculated to assess relative performance of different sPBIFs. Comparison of parametric images generated using IDIF and sPBIFs was also performed. Results: There was no statistically significant difference between AUCs of the IDIF and sPBIFs (Wilcoxon test: P>0.05). The sPBIF55-65 showed the best performance with 1.5% bias and %6.8 precision in tumour lesions. Using the sPBIF55-65 with Patlak model, 20 minutes of PET data (i.e. 45 to 65 min post injection) achieved i estimates in tumour lesions compared to the estimates with the IDIF. Parametric images reconstructed using the IDIF and sPBIFs with and without an abbreviated protocol were visually comparable. Using Patlak Ki generated with an IDIF and 30 mins of PET data as reference, Patlak Ki images generated using sPBIF55-65 with 20 minutes of PET data (t*=45 min) provided excellent image quality with structural similarity index measure > 0.99 and peak signal-to-noise ratio > 55 dB. Conclusion: We demonstrate the feasibility of performing accurate 18F-FDG Patlak analysis using sPBIFs with only 20 minutes of PET data from a LAFOV PET scanner.

Purpose While acquisition of images in [68 Ga]Ga-PSMA-11 following longer uptake times can improve lesion uptake and contrast, resultant imaging quality and count statistics are limited by the isotope’s half-life (68 min). Here, we present a series of cases demonstrating that when performed using a long axial field-of-view (LAFOV) PET/CT system, late imaging is feasible and can even provide improved image quality compared to regular acquisitions. Methods In this retrospective case series, we report our initial experiences with 10 patients who underwent standard imaging at 1 h p.i. following administration of 192 ± 36 MBq [68 Ga]Ga-PSMA-11 with additional late imaging performed at 4 h p.i. Images were acquired in a single bed position for 6 min at 1 h p.i. and 16 min p.i. at 4 h p.i. using a LAFOV scanner (106 cm axial FOV). Two experienced nuclear medicine physicians reviewed all scans in consensus and evaluated overall image quality (5-point Likert scale), lesion uptake in terms of standardised uptake values (SUV), tumour to background ratio (TBR) and target-lesion signal to background noise (SNR). Results Subjective image quality as rated on a 5-point Likert scale was only modestly lower for late acquisitions (4.2/5 at 4 h p.i.; 5/5 1 h p.i.), TBR was significantly improved (4 h: 3.41 vs 1 h: 1.93, p p = 0.062) at later imaging. Images were obtained with total acquisition times comparable to routine examinations on standard axial FOV scanners. Conclusion Late acquisition in tandem with a LAFOV PET/CT resulted in improvements in TBR and SNR and was associated with only modest impairment in subjective visual imaging quality. These data show that later acquisition times for [68 Ga]Ga-PSMA-11 may be preferable when performed on LAFOV systems.

It is still debating if individualized dose should be applied for the emerging PSMA-targeted radionuclide therapy (RLT). A critical consideration in this debate is the necessity and feasibility of individual estimation of post-therapy dosimetry before the treatment. In this study, we aimed to prove the concept of individual dosimetry prediction based on pre-therapy imaging and laboratory measurements. Methods: 23 patients with metastatic castration-resistant prostate cancer (mCRPC) treated with 177Lu-PSMA-I&T RLT were included retrospectively. Included patients had available pre-therapeutic 68Ga-PSMA-HEBD-CC PET/CT and at least 3 planar and 1 SPECT/CT dosimetry imaging. Overall, 43 cycles of 177Lu-PSMA I&T RLT were applied. Organ-based standard uptake value (SUV) uptake was obtained from pretherapy PET/CT scans. Patient individual dosimetry was calculated for kidney, liver, spleen, and salivary glands using Hermes Hybrid Dosimetry 4.0 from the post-treatment 177Lu-PSMA I&T imaging studies. Machine learning methods were explored for individual dose prediction from PET images. The accuracy of these dose predictions was compared with the accuracy of population-based dosimetry estimates. Mean absolute percentage error was used to assess the prediction error of estimated dosimetry. Results: An optimal machine learning method achieved a dosimetry prediction error of 15.8 ± 13.2% for kidney, 29.6%±13.7% for liver, 23.8%±13.1% for salivary glands and 32.1 ± 31.4% for spleen. In contrast, the prediction based on literature population mean has significantly larger error (p Conclusion: The preliminary results confirmed the feasibility of individual estimation of post-therapy dosimetry before the RLT and its added value to empirical population-based estimation. The exploration of individual dose prediction may support the identification of the role of treatment planning for RLT.

ZusammenfassungDas Prostatakarzinom (PCa) ist der weltweit häufigste maligne Tumor bei Männern. Seit ihrer klinischen Einführung im Jahr 2011 hat sich sowohl die PET/CT als auch die Radioligandentherapie mit PSMA-Liganden zur Diagnostik bzw. Therapie des PCa weltweit rasch ausgebreitet. Obwohl die PSMA-PET/CT als ein signifikanter Durchbruch in der Diagnostik des PCa gilt, stellt die Evaluation und Kontrolle aller Tumorherde inklusive ihrer Volumina und Charakteristiken bei fortgeschrittenem, multimetastatischem PCa nach wie vor eine große Herausforderung dar. Diese gilt es zu bewältigen, um beispielsweise eine Optimierung der Endoradiotherapie mit PSMA-Liganden zu erreichen. In diesem Kontext könnte die künstliche Intelligenz, die in den letzten Jahren signifikante Fortschritte erzielt hat, in der nahen Zukunft eine wichtige Rolle spielen. Die Artificial Intelligence (AI) hat bereits demonstriert, dass sie den menschlichen Fähigkeiten zur Datenverarbeitung überlegen sein kann und bietet damit großes Potenzial zur Verbesserung der Detektion, Quantifizierung und Charakterisierung von PCa-Herden in der PSMA-PET/CT.Die hier vorliegende Schrift befasst sich mit den aktuellen Entwicklungen der künstlichen Intelligenz für den Einsatz in der PSMA-PET/CT und den sich daraus bietenden Möglichkeiten.

Purpose: Uncertain bone lesions (UBL) with intensive radiopharmaceutical avidity are frequently observed in patients undergoing [18F]PSMA-1007 PET/CT for the detection of prostate cancer (PC). Such lesions can pose diagnostic conundrums and risk an incorrect staging. The aim of this short communication is to share the results of PET-guided biopsies of such lesions. Methods: A retrospective analysis revealed 10 patients who were referred to our department for PET-guided biopsy of UBL visible in a previous [18F]PSMA-1007 PET/CT. [18F]-PSMA-1007 PET-guided biopsy was conducted for 11 PSMA-avid bone lesions in these 10 patients. The biopsy materials were analysed for tissue typing and immunohistochemistry (IHC) was performed for prostate-specific-membrane-antigen (PSMA) expression. The scans were analysed by two experienced physicians in a consensus read for clinical characteristics and radiopharmaceutical uptake of lesions. Results: 1/11 (9.1%) of the lesions biopsied was confirmed as bone metastasis of PC with intense PSMA-expression while 10/11 (90.9%) lesions were revealed to be unremarkable bone tissue without evidence of PSMA-expression at IHC. Amongst all bone lesions assessed by biopsy, eight were visually classified as being at high risk of malignancy in the PET/CT (SUVmean 12.0 ± 8.1; SUVmax 18.8 ± 13.1), three as equivocal (SUVmean 4.6 ± 2.1; SUVmax 7.2 ± 3.0) and zero as low risk. No UBL had any CT correlate. Conclusions: In this cohort biopsy revealed that a small but relevant number of UBL are true metastases. For those confirmed as benign, no PSMA-expression at IHC was observed, suggesting a non-PSMA mediated cause for intensive [18F]PSMA-1007-uptake of which the reason remains unclear. Readers must interpret such lesions with caution in order to reduce the risk of erroneous staging and subsequent treatment. PET-guided biopsy, particularly in the absence of morphological changes in the CT, can be a useful method to clarify such lesions.

Uncertain focal bone uptake (UBU) with intensive radiopharmaceutical avidity are frequently observed in patients undergoing [A retrospective analysis revealed 10 patients who were referred to our department for PET-guided biopsy of UBU visible in a previous [One out of 11 (9.1%) of the foci biopsied was confirmed as bone metastasis of PC with intense PSMA-expression, while 10/11 (90.9%) foci were revealed to be unremarkable bone tissue without evidence of PSMA expression at IHC. Amongst all bone foci assessed by biopsy, eight were visually classified as being at high risk of malignancy in the PET/CT (SUVmean 12.0 ± 8.1; SUVmax 18.8 ± 13.1), three as equivocal (SUVmean 4.6 ± 2.1; SUVmax 7.2 ± 3.0) and zero as low risk. No UBU had any CT correlate.This cohort biopsy revealed that a small but relevant number of UBU are true metastases. For those confirmed as benign, no PSMA expression at IHC was observed, suggesting a non-PSMA mediated cause for intensive [

Aim Despite increasing use for the detection of biochemically recurrent prostate cancer (rPC), the diagnostic accuracy of positron emission tomography/computed tomography (PET/CT) with [18F]PSMA-1007 remains only partially investigated. The aim of this study was to determine the sensitivity (SE), specificity (SP), positive predictive value (PPV), and negative predictive value (NPV) for PC-local recurrence and metastases on a per region basis. Materials and methods One hundred seventy-seven consecutive patients undergoing [18F]PSMA-1007 PET/CT for rPC were retrospectively analysed. Six body regions were defined: prostate fossa, pelvic lymph nodes (LN), retroperitoneal LN, supradiaphragmatic LN, bones, and soft tissue. A region was counted positive if at least one PSMA-positive lesion suspicious for PC was observed. Confirmation of a true-positive PSMA-avid lesion was defined as positive by histopathology, fall in serum prostate-specific antigen (PSA) (> 50%) after targeted therapy or confirmatory further CT, MRI, PET/CT, or bone scan imaging. Regions where additional imaging was able to confirm the absence of suspicious PC lesions or regions outside exclusively targeted RT with serum PSA decline (> 50%) were counted as true-negative regions. SE, SP, PPV, and NPV were calculated for all six regions. Results The overall PET-positivity rate was 91%. Conclusive follow-up for affirmation or refutation of a PSMA-positive lesion was available for 81/152 patients on a per region basis. In this subgroup, overall sensitivity, specificity, PPV, and NPV were 95% (CI: 0.90–0.98), 89% (CI: 0.83–0.93), 86% (0.80–0.90), and 96% (CI: 0.92–0.98), respectively. On a per region basis, PPV was 97% (CI: 0.83–0.99) for local recurrence, 93% (CI: 0.78–0.98) for pelvic LN, 87% (CI: 0.62–0.96) for retroperitoneal LN, 82% (CI: 0.52–0.95) for supradiaphragmatic LN, and 79% (0.65–0.89) for bone lesions. The number of solid organ metastases (n = 6) was too small for an accurate statistical analysis. Conclusion The known high PET-positivity rate of [18F]PSMA-1007 PET/CT in rPC was confirmed, with corresponding high (> 90%) sensitivity and NPV on a per region basis. However, overall PPV was limited (86%), particularly for bone lesions (79%), which are a potential diagnostic weaknesses when using this tracer.

During disease progression from primary towards metastatic prostate cancer (PCa), and in particular bone metastases, the tumor microenvironment (TME) evolves in parallel with the cancer clones, altering extracellular matrix composition (ECM), vasculature architecture, and recruiting specialized tumor-supporting cells that favor tumor spread and colonization at distant sites. We introduce the clinical profile of advanced metastatic PCa in terms of common genetic alterations. Findings from recently developed models of PCa metastatic spread are discussed, focusing mainly on the role of the TME (mainly matrix and fibroblast cell types), at distinct stages: premetastatic niche orchestrated by the primary tumor towards the metastatic site and bone metastasis. We report evidence of premetastatic niche formation, such as the mechanisms of distant site conditioning by extracellular vesicles, chemokines and other tumor-derived mechanisms, including altered cancer cell-ECM interactions. Furthermore, evidence supporting the similarities of stroma alterations among the primary PCa and bone metastasis, and contribution of TME to androgen deprivation therapy resistance are also discussed. We summarize the available bone metastasis transgenic mouse models of PCa from a perspective of pro-metastatic TME alterations during disease progression and give an update on the current diagnostic and therapeutic radiological strategies for bone metastasis clinical management.

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 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.

Radiosynoviorthesis (RSO) is an established therapeutic method for the local treatment of pain in aseptic joint inflammation (e.g. arthritis, activated osteoarthritis, synovitis). RSO can be used for the treatment of synovial membrane inflammation of the finger joints such as the thumb's carpometacarpal joint. The beta emitter Erbium-169 (Er-169) is injected into the joint space, which irradiates the inflamed synovialis, thereby leading to fibrosis and obliteration of the pain receptors of the synovial membrane. The chances of success in the treatment of the thumb's carpometacarpal joint by RSO are estimated to be 54-100% within 2-6 weeks after therapy.Die Radiosynoviorthese (RSO) ist ein etabliertes Therapieverfahren zur lokalen Schmerzbehandlung bei aseptischen Gelenkentzündungen (z. B. Arthritis, aktivierte Arthrose, Synovialitis). Sie kann unter anderem bei Entzündungen der Gelenkinnenhaut (Synovialis) von Fingergelenken wie z. B. dem Daumensattelgelenk eingesetzt werden. Dabei wird der Beta-Strahler Erbium-169 (Er-169) in den Gelenkspalt eingebracht, der gezielt die Synovialis bestrahlt und so zu einer Fibrosierung und Verödung der dortigen Schmerzrezeptoren führt. Die Erfolgschancen bei der Behandlung des Daumensattelgelenkes werden auf 54–100 % innerhalb von 2–6 Wochen nach Therapie eingeschätzt. Die RSO bietet so ein erfolgsversprechendes konservatives Behandlungskonzept von entzündeten Gelenken wie dem Daumensattelgelenk.

A Correction to this paper has been published: 10.1007/s00259-021-05300-8

Despite increasing use for the detection of biochemically recurrent prostate cancer (rPC), the diagnostic accuracy of positron emission tomography/computed tomography (PET/CT) with [One hundred seventy-seven consecutive patients undergoing [The overall PET-positivity rate was 91%. Conclusive follow-up for affirmation or refutation of a PSMA-positive lesion was available for 81/152 patients on a per region basis. In this subgroup, overall sensitivity, specificity, PPV, and NPV were 95% (CI: 0.90-0.98), 89% (CI: 0.83-0.93), 86% (0.80-0.90), and 96% (CI: 0.92-0.98), respectively. On a per region basis, PPV was 97% (CI: 0.83-0.99) for local recurrence, 93% (CI: 0.78-0.98) for pelvic LN, 87% (CI: 0.62-0.96) for retroperitoneal LN, 82% (CI: 0.52-0.95) for supradiaphragmatic LN, and 79% (0.65-0.89) for bone lesions. The number of solid organ metastases (n = 6) was too small for an accurate statistical analysis.The known high PET-positivity rate of [

To investigate the kinetics ofTwenty-four oncological patients underwent dynamicWe report estimates of kinetic parameters and metabolic rate of glucose consumption (MRWe performed pharmacokinetic modelling of multiple organs using linear and non-linear models using dynamic total-body

Purpose Many radiotracers are currently available for the detection of recurrent prostate cancer (rPC), yet many have not been compared head-to-head in comparative imaging studies. There is therefore an unmet need for evidence synthesis to guide evidence-based decisions in the selection of radiotracers. The objective of this study was therefore to assess the detection rate of various radiotracers for the rPC. Methods The PUBMED, EMBASE, and the EU and NIH trials databases were searched without date or language restriction for comparative imaging tracers for 13 radiotracers of principal interest. Key search terms included 18F-PSMA-1007, 18F-DCPFyl, 68Ga-PSMA-11, 18F-PSMA-11, 68Ga-PSMA-I&T, 68Ga-THP-PSMA, 64Cu-PSMA-617, 18F-JK-PSMA-7, 18F-Fluciclovine, 18F-FABC, 18F-Choline, 11C-Choline, and 68Ga-RM2. Studies reporting comparative imaging data in humans in rPC were selected. Single armed studies and matched pair analyses were excluded. Twelve studies with eight radiotracers were eligible for inclusion. Two independent reviewers screened all studies (using the PRISMA-NMA statement) for inclusion criteria, extracted data, and assessed risk of bias (using the QUADAS-2 tool). A network meta-analysis was performed using Markov-Chain Monte Carlo Bayesian analysis to obtain estimated detection rate odds ratios for each tracer combination. Results A majority of studies were judged to be at risk of publication bias. With the exception of 18F-PSMA-1007, little difference in terms of detection rate was revealed between the three most commonly used PSMA-radiotracers (68Ga-PSMA-11, 18F-PSMA-1007, 18F-DCFPyl), which in turn showed clear superiority to choline and fluciclovine using the derived network. Conclusion Differences in patient-level detection rates were observed between PSMA- and choline-radiotracers. However, there is currently insufficient evidence to favour one of the four routinely used PSMA-radioligands (PSMA-11, PSMA-1007, PSMA-I&T, and DCFPyl) over another owing to the limited evidence base and risk of publication bias revealed by our systematic review. A further limitation was lack of reporting on diagnostic accuracy, which might favour radiotracers with low specificity in an analysis restricted only to detection rate. The NMA derived can be used to inform the design of future clinical trials and highlight areas where current evidence is weak.

Radioligand therapy (RLT) targeting prostate specific-membrane antigen (PSMA) is an emerging treatment for metastatic castration-resistant prostate cancer (mCRPC). It administrates 225Ac- or 177Lu-labeled ligands for the targeted killing of tumor cells. Differently from X- or γ-ray, for the emitted α or β particles the ionization of the DNA molecule is less dependent on the tissue oxygenation status. Furthermore, the diffusion range of electrons in a tumor is much larger than the volume typically spanned by hypoxic regions. Therefore, hypoxia is less investigated as an influential factor for PSMA-directed RLT, in particular with β emitters. This study proposes an in silico approach to theoretically investigate the influence of tumor hypoxia on the PSMA-directed RLT. Based on mice histology images, the distribution of the radiopharmaceuticals was simulated with an in silico PBPK-based convection–reaction–diffusion model. Three anti-CD31 immunohistochemistry slices were used to simulate the tumor microenvironment. Ten regions of interest with varying hypoxia severity were analyzed. A kernel-based method was developed for dose calculation. The cell survival probability was calculated according to the linear-quadratic model. The statistical analysis performed on all the regions of interest (ROIs) shows more heterogeneous dose distributions obtained with 225Ac compared to 177Lu. The higher homogeneity of 177Lu-PSMA-ligand treatment is due to the larger range covered by the emitted β particles. The dose-to-tissue histogram (DTH) metric shows that in poorly vascularized ROIs only 10% of radiobiological hypoxic tissue receives the target dose using 177Lu-PSMA-ligand treatment. This percentage drops down to 5% using 225Ac. In highly vascularized ROIs, the percentage of hypoxic tissue receiving the target dose increases to more than 85% and 65% for the 177Lu and 225Ac-PSMA-ligands, respectively. The in silico study demonstrated that the reduced vascularization of the tumor strongly influences the dose delivered by PSMA-directed RLT, especially in hypoxic regions and consequently the treatment outcome.

This 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. We 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. Among 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. We 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.

PURPOSE Digital PET/CT scanners represent a significant step forward in molecular imaging. We report here the clinical impact of digital PET in PSMA-PET/CT. METHODS In this retrospective study, 88 consecutive patients who underwent [68Ga]Ga-PSMA-11 PET/CT on a digital PET/CT (dPET/CT) scanner for recurrent prostate cancer (PC) were included in a first cohort. In a second step, 88 individuals who underwent an analogue [68Ga]Ga-PSMA-11 PET/CT (aPET/CT) were selected after they were matched to the first cohort for clinical parameters. Following consensus read by two nuclear medicine physicians, the number and type of PC lesions as well as benign, PSMA-positive lesions were recorded. The results were complemented by extensive [68Ga]Ga phantom measurements to determine imaging characteristics of both scanners. RESULTS dPET/CT revealed a greater number of PC lesions compared to aPET/CT (326 versus 142) as well as a proportional increase in benign causes of tracer-uptake (144 versus 65). A greater number of scans were noted as pathological for PC on dPET/CT (74/88) compared to aPET/CT (64/88, p < 0.05). The PSMA positivity rate for PC was significantly higher in dPET/CT for the lowest PSA values (PSA < 2.0 ng/ml, p < 0.05). CONCLUSION dPET/CT detected more PC lesions compared to aPET/CT. A significantly higher rate of pathological PET/CTs was noted in the group with the lowest PSA values. A higher number of benign PSMA-positive lesions were also noted in dPET/CT. The differences could be plausibly explained by the measured imaging characteristics of the scanners.

Die Positronenemissionstomographie/Computertomographie (PET/CT) mit Liganden des Prostataspezifischen Membranantigens (PSMA) und die PSMA-Therapie haben sich seit ihrer klinischen Einfuhrung in 2011 weltweit rasant ausgebreitet. Aktuelle Erkenntnisse sowohl uber die PSMA-PET/CT als auch uber die PSMA-Therapie werden zusammengefasst. Erkenntnisse aus der Literatur und Erfahrungen der Autoren wurden zusammengetragen. Es zeigt sich eine sehr hohe Sensitivitat und Spezifitat der PSMA-PET/CT sowohl beim Rezidivprostatakarzinom (‑PC) als auch beim Primarstaging des PC mit mittlerem und hohem Risikoprofil. Die Ergebnisse der PSMA-Therapie als Drittlinientherapie bei Patienten mit metastasiertem, kastrationsresistentem PC sind vielversprechend. Die PSMA-PET/CT hat sich mittlerweile als Goldstandard in der Diagnostik des Rezidiv-PC etabliert und ist dabei, dieselbe Rolle auch beim Primarstaging des PC mit mittlerem und hohem Risikoprofil zu ubernehmen. Die PSMA-Therapie wird in einer stets wachsenden Zahl an Zentren als Drittlinientherapie bei metastasiertem, kastrationsresistentem PC routinemasig durchgefuhrt.

PURPOSE Dual-time point PET/CT scanning with [68Ga]Ga-PSMA-11 in the diagnosis of prostate cancer (PC) has been advanced as a method to increase detection of PC lesions, particularly at early stages of biochemical recurrence and as a potential means to aid the discrimination between benign and pathological prostate-specific membrane antigen (PSMA) uptake. However, the assumption that all PC lesions uniformly exhibit increasing tracer uptake at delayed imaging has not yet been investigated, which this present study aims to address. METHODS One hundred consecutive patients with biochemically recurrent PC who received standard and late [68Ga]Ga-PSMA-11 PET/CT (by local protocol at 1.5 h "standard" and 2.5 h p.i. "late") underwent retrospective evaluation. All lesions with a tracer uptake above local background were analysed with regard to their maximum standardised uptake values at standard and late images (SUVmax) and characterised according to their morphological characteristics. RESULTS Seventy-nine of 100 patients had PSMA-positive scans, in whom a total of 185 individual PSMA-positive lesions were identified. These were morphologically characterised as bone lesions (n = 48), solid organ lesions (n = 3), lymph node (LN) lesions (n = 78) and locally recurrent lesions in the prostatic fossa or seminal vesicles (n = 56). The relative uptake between standard and late imaging was considered; all lesions classified as local recurrence presented with increasing (86%) or stable patterns of tracer uptake (14%). In contrast, only 58% of bone lesions exhibited increasing tracer uptake, with 21% exhibiting a stable pattern and 21% exhibiting a decreasing tracer uptake at late imaging. CONCLUSION A heterogeneous pattern of dynamic tracer uptake was observed, with a largely increasing pattern observed for locally recurrent lesions and lymph nodes and a significant proportion of bone lesions exhibiting decreasing tracer uptake. The results are of significance not only in the imaging and identification of PC lesions, but they also have implications for PSMA-directed ligand therapy.

PURPOSE So far, there have been very few studies which provide a direct comparison between MRI and PSMA-ligand PET/CT for the detection of recurrent prostate cancer (rPC). This present study therefore aims to provide further clinical data in order to resolve this urgent clinical question, and thereby strengthen clinical recommendations. METHODS A retrospective analysis was performed for patients who were scanned at our institution with whole-body PSMA-PET/CT (tracer: 68Ga-PSMA-11) between January 2017 and September 2018 in order to detect rPC. Amongst them, 43 underwent an additional pelvic MRI within 2 months. Both modalities were compared as follows: a consensus read of the PET data was performed by two nuclear physicians. All lesions were recorded with respect to their type and localization. The same process was conducted by two radiologists for pelvic MRI. Thereafter, both modalities were directly compared for every patient and lesion. RESULTS Overall, 30/43 patients (69.8%) presented with a pathologic MRI and 38/43 (88.4%) with a pathologic PSMA-PET/CT of the pelvis. MRI detected 53 pelvic rPC lesions (13 of them classified as "uncertain") and PSMA-PET/CT detected 75 pelvic lesions (three classified as "uncertain"). The superiority of PSMA-PET/CT was statistically significant only if uncertain lesions were classified as false-positive. CONCLUSIONS PSMA-PET/CT detected more pelvic lesions characteristic for rPC when compared to MRI. In order to detect rPC, a potential future scenario could be conducting first a PSMA-PET/CT. Combining the advantages of both modalities in hybrid PET/MRI scanners would be an ideal future scenario.

ZusammenfassungDas Prostatakarzinom (PCa) ist der weltweit häufigste maligne Tumor bei Männern. Seit ihrer klinischen Einführung in 2011 hat sich sowohl die PET/CT als auch die Radioligandentherapie mit PSMA-Liganden zur Diagnostik bzw. Therapie des PCa weltweit rasch ausgebreitet. Obwohl die PSMA-PET/CT als ein signifikanter Durchbruch in der Diagnostik des PCa gilt, stellt die Evaluation und Kontrolle aller Tumorherde inklusive ihrer Volumina und Charakteristika bei fortgeschrittener, multimetastatischer PCa nach wie vor eine große Herausforderung dar. Diese gilt es zu bewältigen, um beispielsweise eine Optimierung der Endoradiotherapie mit PSMA-Liganden zu erreichen. In diesem Kontext könnte die künstliche Intelligenz, die in den letzten Jahren signifikante Fortschritte erzielt hat, in der nahen Zukunft eine wichtige Rolle spielen. Die Artificial Intelligence (AI) hat bereits demonstriert, dass sie den menschlichen Fähigkeiten zur Datenverarbeitung überlegen sein kann und bietet damit großes Potential zur Verbesserung der Detektion, Quantifizierung und Charakterisierung von PCa-Herden in der PSMA-PET/CT. Die hier vorliegende Schrift befasst sich mit den aktuellen Entwicklungen der künstlichen Intelligenz für den Einsatz in der PSMA-PET/CT und den sich daraus bietenden Möglichkeiten.

Prostate-specific membrane antigen-PET/computed tomography (PSMA-PET/CT) is the investigation of choice for imaging prostate cancer. Demonstrating high diagnostic accuracy, PSMA-PET/CT detects disease at very early stages of recurrence, where the chances of a definitive cure may be at their greatest. A number of PSMA-radioligands are in established clinical routine, and there are currently only limited data and no single tracer can clearly be advocated over the others at present. Further clinical trial data, comparing and contrasting radiotracers and reporting outcome-based data are necessary to further increase the implementation of this very promising imaging modality.