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Abstract Objective Dysphagia is common in individuals who have undergone posterior fossa tumor (PFT) resection and negatively impacts on the individual’s quality of life, nutritional status, and overall health. We aimed to quantitatively synthesize data from studies of the prevalence of dysphagia following PFT resection. Methods PubMed, Web of Science, the Cochrane Library, Embase, China National Knowledge Infrastructure (CNKI), Wanfang database, and VIP database were searched for case-control and cross-sectional studies that evaluated the prevalence of dysphagia after PFT surgery. Meta-analyses were performed to determine the prevalence of dysphagia. Subgroup and meta-regression analyses were performed to determine the sources of heterogeneity among the studies. Results A total of 22 studies were included, involving 20,921 cases. A meta-analysis of the random-effects model showed that the pooled global prevalence of dysphagia following PFT resection was 21.7% (95% confidence interval: 16.9–26.6). The subgroup and meta-regression analyses demonstrated that participant age (P < 0.001), assessment methods (P = 0.004), and geographical region of the study participants (P = 0.001) were sources of heterogeneity among the studies. Conclusions Dysphagia has a high prevalence following PFT resection. Individuals with PFTs who are at a high risk for dysphagia should be identified early through screening. Multidisciplinary diagnosis and treatment of dysphagia are required to improve the outcomes in the early stages after PFT resection.

PurposeTo develop and assess a deep convolutional neural network (DCNN) model for the automatic detection of bone metastases from lung cancer on computed tomography (CT)MethodsIn this retrospective study, CT scans acquired from a single institution from June 2012 to May 2022 were included. In total, 126 patients were assigned to a training cohort (n = 76), a validation cohort (n = 12), and a testing cohort (n = 38). We trained and developed a DCNN model based on positive scans with bone metastases and negative scans without bone metastases to detect and segment the bone metastases of lung cancer on CT. We evaluated the clinical efficacy of the DCNN model in an observer study with five board-certified radiologists and three junior radiologists. The receiver operator characteristic curve was used to assess the sensitivity and false positives of the detection performance; the intersection-over-union and dice coefficient were used to evaluate the segmentation performance of predicted lung cancer bone metastases.ResultsThe DCNN model achieved a detection sensitivity of 0.894, with 5.24 average false positives per case, and a segmentation dice coefficient of 0.856 in the testing cohort. Through the radiologists-DCNN model collaboration, the detection accuracy of the three junior radiologists improved from 0.617 to 0.879 and the sensitivity from 0.680 to 0.902. Furthermore, the mean interpretation time per case of the junior radiologists was reduced by 228 s (p = 0.045).ConclusionsThe proposed DCNN model for automatic lung cancer bone metastases detection can improve diagnostic efficiency and reduce the diagnosis time and workload of junior radiologists.

Abstract Objective Postoperative cerebrospinal fluid (CSF) leakage represents a challenge even for experienced pituitary surgeons. We aimed to quantitatively synthesize data from studies regarding the risk factors for postoperative CSF leakage after transsphenoidal surgery (TSS) for pituitary adenoma (PA). Methods PubMed, Web of Science, The Cochrane Library, Embase, China National Knowledge Infrastructure (CNKI), Wanfang database, and VIP database were searched for case–control and cohort studies, focusing on the risk factors associated with postoperative CSF leakage after TSS for PA. Pooled odds ratios (ORs) and 95% confidence intervals were calculated to determine the risk factors. Results A total of 34 case–control and cohort studies involving a total of 9,144 patients with PA were included in this systematic review. The overall rate of postoperative CSF leakage after TSS for PA was 5.6%. Tumor size, adenoma consistency, revision surgery, and intraoperative CSF leakage were independent risk factors for postoperative CSF leakage (ORs, 3.18–6.33). By contrast, the endoscopic approach showed a slight protective benefit compared with the microscopic approach in TSS (OR, 0.69). Conclusions This review provides a comprehensive overview of the quality of the evidence base, informing clinical staff of the importance of screening risk factors for postoperative CSF leakage after TSS for PA. More attention should be paid to PA patients at high risk for CSF leakage after TSS to reduce complications and improve prognosis.

Coronavirus disease 2019 (COVID-19) made a huge effect globally. With the assistance of mixed reality (MR) technology, complicated clinical works became easier to carry out and the condition had been greatly improved with high-tech advantages such as improved convenience, better understanding and communication, higher security, and medical resource saving. This study aimed to introduce one kind of MR application in the fight against COVID-19 and anticipate more feasible smart health care applications to enhance our strength for the final victory.