Activation of the sigma-1 receptor (Sig-1R) improves functional recovery in models of experimental stroke and is known to modulate microglia function. The present study was conducted to investigate if Sig-1R activation after experimental stroke affects mediators of the inflammatory response in the ischemic hemisphere. Male Wistar rats were subjected to transient occlusion of the middle cerebral artery (MCAO) and injected with the specific Sig-1R agonist 1-(3,4-dimethoxyphenethyl)-4-(3-phenylpropyl)piperazine dihydrochloride (SA4503) or saline for 5 days starting on day 2 after MCAO. Treatment did not affect the increased levels of the pro-inflammatory cytokines interleukin 1 beta (IL-1β), tumor necrosis factor alpha (TNF-α), interferon gamma (IFN-γ), interleukin 4 (IL-4), interleukin 5 (IL-5), and interleukin 13 (IL-13) in the infarct core and peri-infarct area after MCAO. In addition, treatment with SA4503 did not affect elevated levels of nitrite, TNF-α and IL-1β observed in primary cultures of microglia exposed to combined Hypoxia/Aglycemia, while the unspecific sigma receptor ligand 1,3-di-o-tolylguanidine (DTG) significantly decreased the production of nitrite and levels of TNF-α. Analysis of the ischemic hemisphere also revealed increased levels of ionized calcium binding adaptor molecule 1 (Iba1) levels in the infarct core of SA4503 treated animals. However, no difference in Iba1 immunoreactivity was detected in the infarct core. Also, levels of the proliferation marker proliferating cell nuclear antigen (PCNA) and OX-42 were not increased in the infarct core in rats treated with SA4503. Together, our results suggest that sigma-1 receptor activation affects Iba1 expression in microglia/macrophages of the ischemic hemisphere after experimental stroke but does not affect post-stroke inflammatory mediators.
Here, we aimed to develop and validate a fully automated artificial intelligence (AI)-based method for the detection and quantification of suspected prostate tumour/local recurrence, lymph node metastases, and bone metastases from [18F]PSMA-1007 positron emission tomography-computed tomography (PET-CT) images. Images from 660 patients were included. Segmentations by one expert reader were ground truth. A convolutional neural network (CNN) was developed and trained on a training set, and the performance was tested on a separate test set of 120 patients. The AI method was compared with manual segmentations performed by several nuclear medicine physicians. Assessment of tumour burden (total lesion volume (TLV) and total lesion uptake (TLU)) was performed. The sensitivity of the AI method was, on average, 79% for detecting prostate tumour/recurrence, 79% for lymph node metastases, and 62% for bone metastases. On average, nuclear medicine physicians’ corresponding sensitivities were 78%, 78%, and 59%, respectively. The correlations of TLV and TLU between AI and nuclear medicine physicians were all statistically significant and ranged from R = 0.53 to R = 0.83. In conclusion, the development of an AI-based method for prostate cancer detection with sensitivity on par with nuclear medicine physicians was possible. The developed AI tool is freely available for researchers.
Background Scintigraphy with technetium‐99m‐labelled dimercaptosuccinic acid ([99mTc]Tc‐DMSA) is widely used for renal cortical imaging. Uptake of [99mTc]Tc‐DMSA has been shown to correlate with glomerular filtration rate (GFR). Prostate‐specific membrane antigen (PSMA) radiopharmaceuticals used for positron emission tomography (PET) show high renal uptake and are being investigated for renal imaging. [68Ga]Ga‐PSMA‐11 PET parameters have been shown to correlate with estimated GFR (eGFR). The aim of this study was to investigate the relationship between renal [18F]PSMA‐1007 uptake and eGFR. Methods Hundred and eighty‐five patients underwent PET imaging at 1 and 2 h after injection of 4.0 ± 0.2 MBq [18F]PSMA‐1007. Serum creatinine levels were measured and GFR estimated using the Chronic Kidney Disease Epidemiology Collaboration (CKD‐EPI) and Modification of Diet in Renal Disease (MDRD) equations. Fifteen patients were excluded due to missing or incorrect data. Thus, data from 170 patients were analyzed. Kidneys were segmented in the PET images using a convolutional neural network with manual correction. For each kidney, mean standardized uptake value (SUVmean) and segmentation volume in millilitres were measured. Linear regression analyses were performed with eGFR as the outcome variable. Results Variation in the eGFR values was explained to a significant degree by SUVmean and renal segmentation volume in both the 1 and 2 h images. This correlation was stronger for CKD‐EPI eGFR (1 h R2 = 0.64; 2 h R2 = 0.64) than for MDRD eGFR (1 h R2 = 0.47; 2 h R2 = 0.45). Conclusion Renal [18F]PSMA‐1007 uptake parameters correlate with eGFR and are indicative of renal cortical function.
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