This article describes a novel Multifunctional and Transparent Urinary System Model (MTUSM),which can be applied to anatomy teaching, operational training of clinical skills as well as simulated experiments in vitro. This model covers kidneys, ureters, bladder, prostate, male and female urethra, bracket and pedestal,etc. Based on human anatomy structure and parameters, MTUSM consists of two transparent layers i.e. transparent organic glass external layer,which constraints the internal layer and maintains shape of the model, and transparent silica gel internal layer, which possesses perfect elasticity and deformability. It is obvious that this model is preferable in simulating the structure of human urinary system by applying hierarchical fabrication. Meanwhile, the transparent design, which makes the inner structure, internal operations and experiments visual,facilitates teaching instruction and understanding. With the advantages of simple making, high-findelity, unique structure and multiple functions, this model will have a broad application prospect and great practical value.
Three dimensional (3D) bioprinting is a new biological tissue engineering technology in recent years. The development of 3D bioprinting is conducive to solving the current problems of clinical tissue and organ repairing. This article provides a review about the clinical and research status of 3D bioprinting and urinary system reconstruction. Furthermore, the feasibility and clinical value of 3D bioprinting in urinary system reconstruction will be also discussed.
With the rapid development of artificial intelligence technology, researchers have applied it to the diagnosis of various tumors in the urinary system in recent years, and have obtained many valuable research results. The article sorted the research status of artificial intelligence technology in the fields of renal tumors, bladder tumors and prostate tumors from three aspects: the number of papers, image data, and clinical tasks. The purpose is to summarize and analyze the research status and find new valuable research ideas in the future. The results show that the artificial intelligence model based on medical data such as digital imaging and pathological images is effective in completing basic diagnosis of urinary system tumors, image segmentation of tumor infiltration areas or specific organs, gene mutation prediction and prognostic effect prediction, but most of the models for the requirement of clinical application still need to be improved. On the one hand, it is necessary to further improve the detection, classification, segmentation and other performance of the core algorithm. On the other hand, it is necessary to integrate more standardized medical databases to effectively improve the diagnostic accuracy of artificial intelligence models and make it play greater clinical value.
Objective To investigate the clinical application value of GeneXpert Mycobacterium tuberculosis (MTB)/ rifampin (RIF) in urine samples for tuberculosis diagnosis. Methods The patients with clinically highly suspected tuberculosis admitted to West China Hospital of Sichuan University between January 1, 2018 and June 1, 2023 were selected retrospectively. The diagnostic efficacy of urine GeneXpert MTB/RIF detection, such as sensitivity, specificity, positive predictive value, and negative predictive value, were retrospectively analyzed to evaluate its clinical value in the diagnosis of tuberculosis. Correlation analysis was further conducted to explore the correlation between positive levels of GeneXpert MTB/RIF in urine samples and laboratory test indicators. Results A total of 400 patients were included. Among them, 163 cases were in the clinical tuberculosis group and 237 cases were in the clinical non tuberculosis group. In the clinical tuberculosis group, 112 cases were urogenital tuberculosis patients and 51 cases were non-urogenital tuberculosis patients. The sensitivity, specificity, positive predictive value, and negative predictive value of urine GeneXpert MTB/RIF in the diagnosis of tuberculosis were 55.2%, 97.5%, 93.8% and 76.0%, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value of urine GeneXpert MTB/RIF in the diagnosis of urogenital tuberculosis were 65.2%, 92.0%, 76.0% and 87.2%, respectively, and the diagnostic sensitivity was further improved. Correlation analysis showed that the positive degree of urine GeneXpert MTB/RIF was correlated with the levels of hemoglobin, serum total protein, blood serum albumin, and other indicators. Conclusions Urine GeneXpert MTB/RIF detection offers high sensitivity and specificity in the diagnosis of tuberculosis, especially in urogenital tuberculosis, which is helpful for the early and rapid diagnosis of tuberculosis patients. The positive degree reported by the GeneXpert MTB/RIF in urine may indicate disease severity.