Journal of Nuclear Medicine最新文献

For patients with advanced-stage metastatic castration-resistant prostate cancer (mCRPC) who do not respond to [¹⁷⁷Lu]Lu-PSMA therapy, there are limited treatment options. Clinical results obtained with [²²⁵Ac]Ac-PSMA are promising. We retrospectively analyzed the outcomes of patients treated with [²²⁵Ac]Ac-PSMA between December 2018 and October 2022. Methods: We evaluated the treatment results of 23 patients (mean age, 70.3 ± 8.8 y) with mCRPC who were refractory to treatment with [¹⁷⁷Lu]Lu-PSMA (2-9 cycles). The safety profile was assessed according to Common Technology Criteria for Adverse Events version 5.0. Treatment efficacy was assessed using prostate-specific membrane antigen PET progression criteria and prostate-specific antigen (PSA) response according to Prostate Cancer Working Group 2 criteria after the first cycle of [²²⁵Ac]Ac-PSMA treatment. Results: All patients received androgen-deprivation therapy, whereas 22 (96%) and 19 (83%) patients received chemotherapy and second-generation antiandrogen therapy, respectively. One patient received 4 cycles, 2 received 3 cycles, 8 received 2 cycles, and 12 received 1 cycle of [²²⁵Ac]Ac-PSMA. The median interval between cycles was 13 wk (range, 8-28 wk). [²²⁵Ac]Ac-PSMA was administered with a mean activity of 7.6 MBq (range, 6.2-10.0 MBq) in each cycle. Patients were at an advanced stage of disease, and tumor burden was very high. Although the best PSA response was observed in 5 patients (26%) after [²²⁵Ac]Ac-PSMA treatment, there was at least some level of decline in PSA observed in 11 patients (58%; n = 19). Treatment response was assessed in patients who underwent [⁶⁸Ga]Ga-PSMA PET/CT imaging. After the first cycle of treatment (n = 18), 50% of patients (n = 9) showed disease progression according to prostate-specific membrane antigen PET progression criteria, and the disease control rate was calculated to be 50%. Median progression-free survival was 3.1 mo, and median overall survival was 7.7 mo. Grade 3 hematologic toxicity occurred in 1 patient, and grade 3 nephrotoxicity was observed in another patient. Parotid SUV_max decreased by 33%, although all patients complained of dry mouth before treatment. Conclusion: We observed that [²²⁵Ac]Ac-PSMA therapy was safe and showed potential even in cases with advanced-stage mCRPC in which all other treatment options were completed.

The deployment of artificial intelligence (AI) has the potential to make nuclear medicine and medical imaging faster, cheaper, and both more effective and more accessible. This is possible, however, only if clinicians and patients feel that these AI medical devices (AIMDs) are trustworthy. Highlighting the need to ensure health justice by fairly distributing benefits and burdens while respecting individual patients' rights, the AI Task Force of the Society of Nuclear Medicine and Molecular Imaging has identified 4 major ethical risks that arise during the deployment of AIMD: autonomy of patients and clinicians, transparency of clinical performance and limitations, fairness toward marginalized populations, and accountability of physicians and developers. We provide preliminary recommendations for governing these ethical risks to realize the promise of AIMD for patients and populations.

Dosimetry after ¹⁷⁷Lu-DOTATATE peptide receptor radionuclide therapy (PRRT) enables estimation of radiation doses absorbed by normal organs and target lesions. This process is time-consuming and requires multiple posttreatment studies on several subsequent days. In a previous study, we described a newly developed multiple-linear-regression model to predict absorbed doses (ADs) from a single-time-point (STP) posttreatment study acquired 168 h after the first infusion and 24 h after the following ones, with similar results to the standard multiple-time-point (MTP) protocol. The present study aimed to validate this model in a large patient cohort and to assess whether STP dosimetry affects patient management decisions compared with our MTP protocol. Methods: Quantitative ¹⁷⁷Lu-DOTATATE SPECT/CT post-PRRT data from 159 consecutive patients (172 therapies, 477 therapy cycles) were retrospectively analyzed. ADs obtained from an STP model were compared with those obtained using an MTP model. We evaluated the impact of the STP model on the decision on whether PRRT should be stopped because of an expected kidney AD exceeding the safety threshold. We hypothesized that patient management based on the STP model does not differ from that based on the MTP model in at least 90% of the cases. Results: There was no difference in management decisions between the MTP and STP models in 170 of 172 therapies (98.8%). A Fisher χ² test for combined probabilities produced a composite P value of 0.0003. Mean cumulative AD relative differences between the STP and MTP models were 0.8% ± 8.0%, -7.7% ± 4.8%, 0.0% ± 11.4%, -2.8% ± 6.3%, and -2.1% ± 18.4% for kidneys, bone marrow, liver, spleen, and tumors, respectively (Pearson r = 0.99 for all), for patients who underwent 4 therapy cycles. Similar results were obtained with fewer therapy cycles. Conclusion: Estimated radiation ADs and patient management decisions were similar with the STP and MTP models. The STP model can simplify the dosimetry process while also reducing scanner and staff time and improving patient comfort.

Upregulation of prostate-specific membrane antigen (PSMA) in neovasculature has been described in glioblastoma multiforme (GBM), whereas vasculature in nonaffected brain shows hardly any expression of PSMA. It is unclear whether PSMA-targeting tracer uptake on PET is based on PSMA-specific binding to neovasculature or aspecific uptake in tumor. Here, we quantified uptake of various PSMA-targeting tracers in GBM and correlated this with PSMA expression in tumor biopsy samples from the same patients. Methods: Fourteen patients diagnosed with de novo (n = 8) or recurrent (n = 6) GBM underwent a preoperative PET scan after injection of 1.5 MBq/kg [⁶⁸Ga]Ga-PSMA-11 (n = 7), 200 MBq of [¹⁸F]DCFpyl (n = 3), or 200 MBq of [¹⁸F]PSMA-1007 (n = 4). Uptake in tumor and tumor-to-background ratios, with contralateral nonaffected brain as background, were determined. In a subset of patients, PSMA expression levels from different regions in the tumor tissue samples (n = 40), determined using immunohistochemistry (n = 35) or RNA sequencing (n = 13), were correlated with tracer uptake on PET. Results: Moderate to high (SUV_max, 1.3-20.0) heterogeneous uptake was found in all tumors irrespective of the tracer type used. Uptake in nonaffected brain was low, resulting in high tumor-to-background ratios (6.1-359.0) calculated by dividing SUV_max of tumor by SUV_max of background. Immunohistochemistry showed variable PSMA expression on endothelial cells of tumor microvasculature, as well as on dispersed individual cells (of unknown origin), and granular staining of the neuropil. No correlation was found between in vivo uptake and PSMA expression levels (for immunohistochemistry, r = -0.173, P = 0.320; for RNA, r = -0.033, P = 0.915). Conclusion: Our results indicate the potential use of various PSMA-targeting tracers in GBM. However, we found no correlation between PSMA expression levels on immunohistochemistry and uptake intensity on PET. Whether this may be explained by methodologic reasons, such as the inability to measure functionally active PSMA with immunohistochemistry, tracer pharmacokinetics, or the contribution of a disturbed blood-brain barrier to tracer retention, should still be investigated.

This study aimed to develop an analytic approach based on [¹⁸F]FDG PET radiomics using stacking ensemble learning to improve the outcome prediction in diffuse large B-cell lymphoma (DLBCL). Methods: In total, 240 DLBCL patients from 2 medical centers were divided into the training set (n = 141), internal testing set (n = 61), and external testing set (n = 38). Radiomics features were extracted from pretreatment [¹⁸F]FDG PET scans at the patient level using 4 semiautomatic segmentation methods (SUV threshold of 2.5, SUV threshold of 4.0 [SUV4.0], 41% of SUV_max, and SUV threshold of mean liver uptake [PERCIST]). All extracted features were harmonized with the ComBat method. The intraclass correlation coefficient was used to evaluate the reliability of radiomics features extracted by different segmentation methods. Features from the most reliable segmentation method were selected by Pearson correlation coefficient analysis and the LASSO (least absolute shrinkage and selection operator) algorithm. A stacking ensemble learning approach was applied to build radiomics-only and combined clinical-radiomics models for prediction of 2-y progression-free survival and overall survival based on 4 machine learning classifiers (support vector machine, random forests, gradient boosting decision tree, and adaptive boosting). Confusion matrix, receiver-operating-characteristic curve analysis, and survival analysis were used to evaluate the model performance. Results: Among 4 semiautomatic segmentation methods, SUV4.0 segmentation yielded the highest interobserver reliability, with 830 (66.7%) selected radiomics features. The combined model constructed by the stacking method achieved the best discrimination performance. For progression-free survival prediction in the external testing set, the areas under the receiver-operating-characteristic curve and accuracy of the stacking-based combined model were 0.771 and 0.789, respectively. For overall survival prediction, the stacking-based combined model achieved an area under the curve of 0.725 and an accuracy of 0.763 in the external testing set. The combined model also demonstrated a more distinct risk stratification than the International Prognostic Index in all sets (log-rank test, all P < 0.05). Conclusion: The combined model that incorporates [¹⁸F]FDG PET radiomics and clinical characteristics based on stacking ensemble learning could enable improved risk stratification in DLBCL.

PET imaging using the somatostatin receptor 2 (SSTR2) antagonist satoreotide trizoxetan (SSO-120, previously OPS-202) could offer accurate tumor detection and screening for SSTR2-antagonist radionuclide therapy in patients with SSTR2-expressing small cell lung cancer (SCLC). The aim of this single-center study was to investigate tumor uptake and detection rates of ⁶⁸Ga-SSO-120 in comparison to ¹⁸F-FDG PET in the initial staging of SCLC patients. Methods: Patients with newly diagnosed SCLC who underwent additional whole-body ⁶⁸Ga-SSO-120 PET/CT during the initial diagnostic workup were retrospectively included. The mean administered activity was 139 MBq, and the mean uptake time was 60 min. Gold-standard staging ¹⁸F-FDG PET/CT was evaluated if available within 2 wk before or after ⁶⁸Ga-SSO-120 PET if morphologic differences in CT images were absent. ⁶⁸Ga-SSO-120- or ¹⁸F-FDG-positive lesions were reported in 7 anatomic regions (primary tumor, thoracic lymph node metastases, and distant metastases including pleural, contralateral pulmonary, liver, bone, and other) according to the TNM classification for lung cancer (eighth edition). Consensus TNM staging (derived from CT, endobronchial ultrasound-guided transbronchial needle aspiration, PET, and brain MRI) by a clinical tumor board served as the reference standard. Results: Thirty-one patients were included, 12 with limited and 19 with extensive disease according to the Veterans Administration Lung Study Group classification. ⁶⁸Ga-SSO-120-positive tumor was detected in all patients (100%) and in 90 of the 217 evaluated regions (41.5%). Thirteen patients (42.0%) had intense average ⁶⁸Ga-SSO-120 uptake (region-based mean SUV_max ≥ 10); 28 patients (90.3%) had average ⁶⁸Ga-SSO-120 uptake greater than liver uptake (region-based mean peak tumor-to-liver ratio > 1). In 25 patients with evaluable ¹⁸F-FDG PET, primary tumor, thoracic lymph node metastases, and distant metastases were detected in 100%, 92%, and 64%, respectively, of all investigated patients by ⁶⁸Ga-SSO-120 and in 100%, 92%, and 56%, respectively, by ¹⁸F-FDG PET. ⁶⁸Ga-SSO-120 PET detected additional contralateral lymph node, liver, and brain metastases in 1, 1, and 2 patients, respectively (no histopathology available), and ¹⁸F-FDG PET detected additional contralateral lymph node metastases in 3 patients (1 confirmed, 1 systematic endobronchial ultrasound-guided transbronchial needle aspiration-negative, and 1 without available histopathology). None of these differences altered Veterans Administration Lung Study Group staging. The region-based monotonic correlation between ⁶⁸Ga-SSO-120 and ¹⁸F-FDG uptake was low (Spearman ρ = 0.26-0.33). Conclusion: ⁶⁸Ga-SSO-120 PET offers high diagnostic precision with compara

CT and bone scintigraphy are not useful for response evaluation of bone metastases to ²²³Ra treatment in metastatic castration-resistant prostate cancer (mCRPC). PET using ⁶⁸Ga prostate-specific membrane antigen 11 (⁶⁸Ga-PSMA) is a promising tool for response evaluation of mCRPC. The aim of this study was to determine the utility of ⁶⁸Ga-PSMA PET/CT for response evaluation of ²²³Ra treatment in patients with mCRPC. Methods: Within this prospective, multicenter, imaging discovery study, 28 patients with mCRPC, eligible for ²²³Ra treatment, were included between 2019 and 2022. Patients received ²²³Ra according to the standard of care. Study procedures included CT, bone scintigraphy, and ⁶⁸Ga-PSMA PET/CT at baseline, after 3 and 6 cycles of ²²³Ra treatment, and on treatment failure. Response to ²²³Ra treatment was visually assessed on all 3 imaging modalities. Total tumor volume within bone (TTV_bone) was determined on ⁶⁸Ga-PSMA PET/CT. Intrapatient heterogeneity in response was studied using a newly developed image-registration tool for sequential images of PET/CT. Results were compared with failure-free survival (good responders vs. poor responders; cutoff, 24 wk) and alkaline phosphatase (ALP) response after 3 cycles. Results: Visual response assessment criteria could not distinguish good responders from poor responders on ⁶⁸Ga-PSMA PET/CT and bone scintigraphy. For ⁶⁸Ga-PSMA PET/CT, TTV_bone at baseline was lower in good responders than in poor responders, whereas TTV_bone increased in both groups during treatment. TTV_bone was higher in patients with new extraosseous metastases during ²²³Ra treatment. Although TTV_bone and ALP correlated at baseline, changes in TTV_bone and ALP on treatment did not. ⁶⁸Ga-PSMA response of TTV_bone showed intrapatient heterogeneity in most patients. Conclusion: mCRPC patients with lower TTV_bone on ⁶⁸Ga-PSMA PET/CT have the best clinical outcome after ²²³Ra treatment. Response is highly heterogeneous in most patients. A decrease in ALP, which occurred in most patients, was not correlated with a decrease in TTV_bone, which might make one question the value of ALP for disease monitoring during ²²³Ra treatment in clinical practice.