Estimation of urinary stone composition by automated processing of CT images

The objective of this article was developing an automated tool for routine clinical practice to estimate urinary stone composition from CT images based on the density of all constituent voxels. A total of 118 stones for which the composition had been determined by infrared spectroscopy were placed in a helical CT scanner. A standard acquisition, low-dose and high-dose acquisitions were performed. All voxels constituting each stone were automatically selected. A dissimilarity index evaluating variations of density around each voxel was created in order to minimize partial volume effects: stone composition was established on the basis of voxel density of homogeneous zones. Stone composition was determined in 52% of cases. Sensitivities for each compound were: uric acid: 65%, struvite: 19%, cystine: 78%, carbapatite: 33.5%, calcium oxalate dihydrate: 57%, calcium oxalate monohydrate: 66.5%, brushite: 75%. Low-dose acquisition did not lower the performances (P < 0.05). This entirely automated approach eliminates manual intervention on the images by the radiologist while providing identical performances including for low-dose protocols

Transforming urinary stone disease management by artificial intelligence-based methods: A comprehensive review

Objective: To provide a comprehensive review on the existing research and evi-dence regarding artificial intelligence (AI) applications in the assessment and management of urinary stone disease.Methods: A comprehensive literature review was performed using PubMed, Scopus, and Google Scholar databases to identify publications about innovative concepts or supporting applica-tions of AI in the improvement of every medical procedure relating to stone disease. The terms "endourology", "artificial intelligence", "machine learning", and "urolithiasis"were used for searching eligible reports, while review articles, articles referring to automated procedures without AI application, and editorial comments were excluded from the final set of publica-tions. The search was conducted from January 2000 to September 2023 and included manu-scripts in the English language.Results: A total of 69 studies were identified. The main subjects were related to the detection of urinary stones, the prediction of the outcome of conservative or operative management, the optimization of operative procedures, and the elucidation of the relation of urinary stone chemistry with various factors.Conclusion: AI represents a useful tool that provides urologists with numerous amenities, which explains the fact that it has gained ground in the pursuit of stone disease management perfection. The effectiveness of diagnosis and therapy can be increased by using it as an alter-native or adjunct to the already existing data. However, little is known concerning the poten-tial of this vast field. Electronic patient records, containing big data, offer AI the opportunity to develop and analyze more precise and efficient diagnostic and treatment algorithms. Never-theless, the existing applications are not generalizable in real-life practice, and high-quality studies are needed to establish the integration of AI in the management of urinary stone dis-ease.CNN ; CNN

Dual energy imaging for determining urinary calculi composition: A theoretical and experimental study with computed tomography

Urinary calculi is a common problem worldwide and is associated with substantial patient morbidity and healthcare costs. The choice of treatment is dependent on the composition of the stone. Currently that can only be determined once it has been removed which is too late to impact treatment decisions. Considerable investigation into the use of dual-energy CT (DECT) for determining stone composition has lead to mixed results. The varied results may be due to inherent sources of error and it is unclear whether the mixed results with DECT are due to CT artifacts or insufficient fundamental difference in the linear attenuation coefficient between stones of various compositions. This work will develop a fundamental model for dual-energy CT to determine the ability to differentiate between stones of uniform and mixed composition. The model will be tested experimentally to optimize the parameters and determine the appropriate clinical measurement to reflect the results

ROLE OF MACHINE VISION FOR IDENTIFICATION OF KIDNEY STONES USING MULTI FEATURES ANALYSIS

The purpose of this study is to highlight the significance of machine vision for the Classification of kidney stone identification. A novel optimized fused texture features frame work was designed to identify the stones in kidney.&nbsp; A fused 234 texture feature namely (GLCM, RLM and Histogram) feature set was acquired by each region of interest (ROI). It was observed that on each image 8 ROI’s of sizes (16x16, 20x20 and 22x22) were taken. It was difficult to handle a large feature space 280800 (1200x234). Now to overcome this data handling issue we have applied feature optimization technique namely POE+ACC and acquired 30 most optimized features set for each ROI. The optimized fused features data set 3600(1200x30) was used to four machine vision Classifiers that is Random Forest, MLP, j48 and Naïve Bayes. Finally, it was observed that Random Forest provides best results of 90% accuracy on ROI 22x22 among the above discussed deployed Classifier

2016 Advances in Renal Imaging Symposium

The primary objective of the “Advances in Renal Imaging” symposium is to provide a forum for nephrology researchers and imaging scientists to come together and discuss needed kidney imaging biomarkers and explore the development of imaging technologies designed to address specific renal imaging needs. The Symposium includes three sessions of oral presentations with invited speakers addressing the following general themes: 1) Need for advances in renal imaging and the identification of potential imaging biomarker targets; 2) Advances in renal microscopy methods for basic science renal research; 3) Advances in molecular, perfusion, and structural renal imaging.International Society of Nephrology; Indiana CTSI; IUPU

Minimally Invasive Urological Procedures and Related Technological Developments

The landscape of minimally invasive urological intervention is changing. A lot of new innovations and technological developments have happened over the last 3 decades. Laparoscopy and robotic surgery have revolutionised kidney and prostate cancer treatment, with more minimally invasive procedures now being carried out than ever before. At the same time, technological advancements and the use of laser have changed the face of endourology. Several new innovative treatments are now commonplace for benign prostate enlargement (BPE). Management of prostate cancer now involves procedures such as robotic prostatectomy, brachytherapy, radiotherapy, cryotherapy and HIFU. Robotic partial nephrectomy and cryotherapy have changed the face of renal cancer. En-bloc resection of bladder cancer is challenging the traditional management of non-muscle invasive bladder cancer and becoming commonplace, while robotic cystectomy is also gaining popularity for muscle invasive bladder cancer. Newer surgical intervention related to BPE includes laser (holmium, thulium and green light), water-based treatment (Rezum, Aquablation) and other minimally invasive procedures such as prostate artery embolisation (PAE) and Urolift. Endourological procedures have incorporated newer laser types and settings such as moses technology, disposable ureteroscopes (URS) and minimisation of percutaneous nephrolithotomy (PCNL) instruments. All these technological innovations and improvements have led to shorter hospital stay, reduced cost, potential reduction in complications and improvement in the quality of life (QoL)

Electrical Characterization and Detection of Blood Cells and Stones in Urine

Urine contains an immense amount of information related to its physical, chemical, and biological components; hence, it is a promising tool in detecting various diseases. Available methods for detecting hematuria (blood in the urine) are not accurate. Results are influenced by many factors, such as, health and vitals of the patients, settings of the equipment and laboratories, which leads to false positive or false negative outputs. This necessitates the development of new, accurate, and easy-access methods that save time and effort. This study demonstrates a label-free and accurate method for detecting the presence of red and white blood cells (RBCs and WBCs) in urine by measuring the changes in the dielectric properties of urine upon increasing concentrations of both cell types. The current method could detect changes in the electrical properties of fresh urine over a short time interval, making this method suitable for detecting changes that cannot be recognized by conventional methods. Correcting these changes enabled the detection of a minimum cell concentration of 10² RBCs per ml which is not possible by conventional methods used in the labs except for the semi-quantitative method that can detect 50 RBCs per ml, but it is a lengthy and involved procedure, not suitable for high volume labs. This ability to detect a very small amount of both types of cells makes the proposed technique an attractive tool for detecting hematuria, the presence of which is indicative of problems in the excretory system. Furthermore, urolithiasis is also a very common problem worldwide, affecting adults, kids, and even animals. Calcium oxalate is the major constituent of urinary tract stones in individuals, primarily due to the consumption of high oxalate foods. The occurrence of urinary oxalate occurs by endogenous synthesis, especially in the upper urinary tract. In a normal, healthy individual, the excretion of oxalate ranges from 10 to 45 mg/day, depending on the age and gender, but the risk of stone formation starts at 25 mg/day depending on the health history of the individual. This study also addresses the detection of the presence of calcium oxalate in urine following the same label-free approach. This can be done by measuring the changes in the dielectric properties of urine with increasing concentrations of calcium oxalate hydrate (CaC₂O₄.H₂O). The current method could detect dynamic changes in the electrical properties of urine over a time interval in samples containing calcium oxalate hydrate even at a concentration as low as 10 μg/mL of urine, making this method suitable for detecting changes that cannot be recognized by conventional methods. The ability to detect a very small amount of stones makes it an attractive tool for detecting and quantifying stones in kidneys. Using a non-invasive method which also works as a precautionary measure for early detection of some severe ailments, holds a good scope. It forms the basis of the cytological examinations and molecular assays for the diagnosis of several diseases. This method can be considered a point-of-care test because the results can be instantaneously shared with the members of the medical team. Based on these results, it is anticipated that the present approach to be a starting point towards establishing the foundation for label-free electrical-based identification and quantification of an unlimited number of nano-sized particles

Methods and instrumentation for raman characterization of bladder cancer tumor

High incidence and recurrence rates make bladder cancer the most common malignant tumor in the urinary system. Cystoscopy is the gold standard test used for diagnosis, nevertheless small flat tumors might be missed, and the procedure still represents discomfort to patients and high recurrence can result from of urethral injuries. During cystoscopy, suspicious tumors are detected through white light endoscopy and resected tissue is further examined by histopathology. after resection, the pathologist provides information on the differentiation of the cells and the penetration depth of the tumor in the tissue, known as grading and staging of tumor, respectively. During cystoscopy, information on tumor grading and morphological depth characterization can assist onsite diagnosis and significantly reduce the amount of unnecessarily resected tissue. Recently, new developments in optical imaging and spectroscopic approaches have been demonstrated to improve the results of standard techniques by providing real-time detection of macroscopic and microscopic biomedical information. Different applications to detect anomalies in tissues and cells based on the chemical composition and structure at the microscopic level have been successfully tested. There is, nevertheless, the need to cope with the demands for clinical translation. This doctoral thesis presents the investigations, clinical studies and approaches applied to filling the main open research questions when applying Raman spectroscopy as a diagnostic tool for bladder cancer tumor grading and general Raman spectroscopy-based oncological clinical studies