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Abstract Purpose To evaluate the difference in the diagnostic efficacy of 18F-PSMA-1007 PET/CT and pelvic MRI in primary prostate cancer, as well as the correlation between the two methods and histopathological parameters and serum PSA levels. Methods A total of 41 patients with suspected prostate cancer who underwent 18F-PSMA-1007 PET/CT imaging in our department from 2018 to 2023 were retrospectively collected. All patients underwent 18F-PSMA-1007 PET/CT and MRI scans. The sensitivity, PPV and diagnostic accuracy of MRI and 18F-PSMA-1007 PET/CT in the diagnosis of prostate cancer were calculated after comparing the results of MRI and 18F-PSMA-1007 PET/CT with biopsy. The Spearman test was used to calculate the correlation between 18F-PSMA-1007 PET/CT, MRI parameters, histopathological indicators, and serum PSA levels. Results Compared with histopathological results, the sensitivity, PPV and diagnostic accuracy of 18F-PSMA-1007 PET/CT in the diagnosis of prostate cancer were 95.1%, 100.0% and 95.1%, respectively. The sensitivity, PPV and diagnostic accuracy of MRI in the diagnosis of prostate cancer were 82.9%, 100.0% and 82.9%, respectively. There was a mild to moderately positive correlation between Gleason (Gs) score, Ki-67 index, serum PSA level and 18F-PSMA-1007 PET/CT parameters (p 0.05). Conclusion Compared with MRI, 18F-PSMA-1007 PET/CT has higher sensitivity and diagnostic accuracy in the detection of malignant prostate tumors. In addition, the Ki-67 index and AMACR (P504S) expression were only correlated with 18F-PSMA-1007 PET/CT parameters. Gs score and serum PSA level were correlated with 18F-PSMA-1007 PET/CT and MRI parameters. 18F-PSMA-1007 PET/CT examination can provide certain reference values for the clinical diagnosis, evaluation, and treatment of malignant prostate tumors.

Abstract Purpose To investigate the prognosis value of a combined model based on 18F-fluoro-deoxyglucose positron emission tomography-computed tomography (18F-FDG PET-CT) baseline and interim parameters in patients with diffuse large B-cell lymphoma (DLBCL). Methods We retrospectively analyzed the PET metabolic parameters and clinical data of 154 DLBCL patients between December 2015 and October 2020. All of these patients underwent 18F-FDG PET/CT scan before treatment and after three or four courses of chemotherapy. The optimal cut-off values for quantitative variables were determined by the receiver operating characteristic (ROC) curve. The baseline and interim PET/CT parameters, which respectively included maximum standardized uptake value (SUVmax0), total metabolic tumor volume (TMTV0), standardized total metabolic tumor volume (STMTV0), and the distance between the two furthest lesions (Dmax) and total tumor lesion glycolysis (TTLG1), SUVmax1, TMTV1, and the rate of change of SUVmax (%ΔSUVmax), and clinical characteristics were analyzed by chi-squared test, Kaplan-Meier survival curve, and Cox regression analysis. Results Of 154 patients, 35 exhibited disease progression or recurrence. ROC analysis revealed that baseline 18F-FDG PET/CT metabolic parameters, including maximum standardized uptake value (SUVmax0), total metabolic tumor volume (TMTV0), standardized total metabolic tumor volume (STMTV0), and the distance between the two furthest lesions (Dmax), along with interim 18F-FDG PET/CT metabolic parameters such as total tumor lesion glycolysis (TTLG1), SUVmax1, TMTV1, and the rate of change of SUVmax (%ΔSUVmax), were predictive of relapse or progression in DLBCL patients (P

18F-PSMA-1007 PET/CT imaging is increasingly used for the diagnosis, staging, and efficacy assessment of patients with prostate cancer. Compared with other PSMA tracers, 18F-PSMA-1007 is mainly cleared by the liver and bile and has lower urinary clearance, thus allowing a better assessment of the lesions around the bladder. However, there were some patients who showed an obvious concentration of the 18F-PSMA-1007 in the bladder, which may affect the observation of peripheral lesions, but the mechanism of this change is unknown. The aim of this study was to explore the cause of bladder 18F-PSMA-1007 concentration by assessing the clinical and imaging characteristics of 18F-PSMA-1007 PET/CT scans. A total of 284 patients were included in this retrospective study, and their clinical characteristics such as age, height, weight, Gleason score, metastases, different treatment methods, the level of liver and kidney function, PSA level, and imaging characteristics such as 18F-PSMA-1007 injected activity, the interval between injection to scan, physiological distribution (parotid gland, kidney, liver, spleen, intestine, obturator internus), pathological distribution (prostate lesions, metastases) were collected, and were compared after subgrouping using bladder urine SUVmax. This study showed that the distribution of bladder 18F-PSMA-1007 was not correlated with the above clinical and imaging characteristics, so further studies are needed to find the explanations, and thus to improve the disease assessment of this type of prostate cancer patients.

Machine translation (MT) systems such as Google Translate, Bing or Youdao are increasingly present in everyday life. Anecdotal evidence suggests that language students might use them to produce written work in the target language (TL) and thus possibly get around a potentially difficult writing task. The crucial question to ask would be whether it is possible to differentiate the output of MT from learner language. This paper seeks to address this question by comparing the lexical features of these two types of discourse in the Chinese context. In particular, it examines the use of English translation equivalents of polysemous Chinese words in two parallel corpora: A Chinese webpage corpus translated into English using Bing and Youdao on the one hand and a Chinese learner writing corpus on the other. While the comparison yields similar error rates, it also establishes that human learners and translation engines have difficulties with different sets of words. Word frequency also plays a significant role in differentiating between the two sets of output. The paper concludes with the finding that MT output is sufficiently different from learner language in terms of lexis. The findings could be used to create an algorithm for the detection of ethics code violation through the use of MT engines in written assignments.