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A new era of precision diagnostics and therapy for patients with neuroendocrine neoplasms began with the approval of somatostatin receptor (SSTR) radiopharmaceuticals for positron emission tomography (PET) imaging followed by peptide receptor radionuclide therapy (PRRT). With the transition from SSTR-based gamma scintigraphy to PET, the higher sensitivity of the latter raised questions regarding the direct application of the planar scintigraphy-based Krenning score for PRRT eligibility. Also, to date, the role of SSTR-PET in response assessment and predicting outcome remains under evaluation. In this comprehensive review article, we discuss the current role of SSTR-PET in all aspects of neuroendocrine neoplasms including its relation to conventional imaging, selection of patients for PRRT, and the current understanding of SSTR-PET based response assessment. We also provide a standardized reporting template for SSTR-PET with a brief discussion.Positron emission tomography and magnetic resonance imaging (PET/MRI) scanners cannot be qualified in the manner adopted for hybrid PET and computed tomography (CT) devices. The main hurdle with qualification in PET/MRI is that attenuation correction (AC) cannot be adequately measured in conventional PET phantoms due to the difficulty in converting the MRI images of the physical structures (e.g., plastic) into electron density maps. Over the last decade, a plethora of novel MR-based algorithms have been developed to more accurately derive the attenuation properties of the human head, including the skull. Although very promising, none of these techniques has yet emerged as an optimal and universally adopted strategy for AC in PET/MRI. In this work, we propose a path for PET/MRI qualification for multicenter brain imaging studies. Specifically, our solution is to separate the head attenuation correction from the other factors that affect PET data quantification and use a patient as a phantom to assess the former. The emission data collected on the integrated PET/MRI scanner to be qualified should be reconstructed using both MR- and CT-based AC methods and whole-brain qualitative and quantitative (both voxel-wise and regional) analyses should be performed. The MR-based approach will be considered satisfactory if the PET quantification bias is within the acceptance criteria specified herein. We have implemented this approach successfully across two PET/MRI scanner manufacturers at two sites.INTRODUCTION Intravenous 177Lu-(HA-)DOTATATE has shown promising results for the treatment of surgery- and radiotherapy-refractory meningiomas. We aimed to investigate the added value of intra-arterial administration. METHODS Patients underwent at least one intravenous 177Lu-HA-DOTATATE treatment first and subsequent intra-arterial cycles. In(tra)-patient comparison was based on post-treatment 177Lu-HA-DOTATATE imaging 24 hours post-injection. Technical success rates and adverse events were recorded. RESULTS Four patients provided informed consent. Technical success rate was 100% and no angiography related or unexpected adverse events occurred. Intra-patient comparison showed an increased target lesion accumulation on both planar imaging (mean +220%) and SPECT/CT (mean +398%) after intra-arterial administration compared to intravenous. No unexpected adverse events during follow-up occurred. see more CONCLUSION Intra-arterial PRRT significantly increases tracer accumulation, and is a safe and promising improvement for salvage meningioma patients. Future prospective studies on intra-arterial PRRT are needed to determine gain on efficacy and survival.Attenuation correction (AC) remains a challenge in pelvis PET/MR imaging. In addition to the segmentation/model-based approaches, deep learning methods have shown promise in synthesizing accurate pelvis attenuation maps (μ-maps). However, these methods often misclassify air pockets in the digestive tract, which can introduce bias in the reconstructed PET images. The aims of this work were to develop deep learning-based methods to automatically segment air pockets and generate pseudo-CT images from CAIPIRINHA-accelerated MR Dixon images. Methods A convolutional neural network (CNN) was trained to segment air pockets using 3D CAIPIRINHA-accelerated MR Dixon datasets from 35 subjects and was evaluated against semi-automated segmentations. A separate CNN was trained to synthesize pseudo-CT μ-maps from the Dixon images. Its accuracy was evaluated by comparing the deep learning-, model- and CT-based μ-maps using data from 30 of the subjects. Finally, the impact of different μ-maps and air pocket segmentation methods on the PET quantification was investigated. Results Air pockets segmented using the CNN agreed well with semi-automated segmentations, with a mean Dice similarity coefficient of 0.75. Volumetric similarity score between two segmentations was 0.85 ± 0.14. The mean absolute relative change (RCs) with respect to the CT-based μ-maps were 2.6% and 5.1% in the whole pelvis for the deep learning and model-based μ-maps, respectively. The average RC between PET images reconstructed with deep learning and CT-based μ-maps was 2.6%. Conclusion We presented a deep learning-based method to automatically segment air pockets from CAIPIRINHA-accelerated Dixon images with comparable accuracy to semi-automatic segmentations. We also showed that the μ-maps synthesized using a deep learning-based method from CAIPIRINHA-accelerated Dixon images are more accurate than those generated with the model-based approach available on integrated PET/MRI scanner.Purpose We aimed to investigate the diagnostic and prognostic value of 68Ga-pentixafor positron emission tomography (PET)/computed tomography (CT) imaging in non-cancer patients with suspected adrenal masses. Methods Sixty-four patients who had benign adrenal masses on CT were retrospectively included in our study. All patients underwent 68Ga-pentixafor PET/CT scans, and 56 of these patients subsequently underwent adrenalectomy. The subtypes of 81 adrenal tumors including 14 nonfunctioning adrenal nodules, 4 cortisol-producing adenomas, 41 aldosterone-producing adenomas, 5 suspected unilateral adrenal hyperplasia, 15 idiopathic aldosterone hyperplasia and 2 pheochromocytomas, were determined by histology or follow-up evaluations. The functional lateralization diagnosis efficiency was calculated by visual analysis. Semi-quantitative parameters of these lesions including maximum standardized uptake value (SUVmax), the ratio of lesional SUVmax to normal liver SUVmean (LLR), and the ratio of lesional SUVmax to contralateral adrenal tissue SUVmean (LCR) have also been calculated.
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