CT in the diagnosis of nontraumatic acute abdomen
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01.01.2018 |
Arablinskiy A.
Magdebura Y.
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Russian Electronic Journal of Radiology |
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© 2018 Russian Electronic Journal of Radiology. All rights reserved. Purpose. Evaluation of the morbidity structure and demonstration CT-semiotics of the main diseases in patients with nontraumatic acute abdomen. Materials and methods. 905 studies of the abdomen performed in 2016 in the State Clinical Hospital named after S.P. Botkin in patients with acute abdomen. The studies were conducted natively, with contrasting per os, with intravenous enhancement, depending on the expected pathology. Results. The most common causes of acute abdomen were: acute intestinal obstruction (27%), pancreatitis (9%), urolithiasis and its complications (8%), oncology directly and its complications (7%), inflammatory changes in the gallbladder and diliary ducts (4%), inflammatory changes in the kidneys (3%). Also significant weight in the structure of morbidity was perforation of the bowel (2.5%), mesenteric thrombosis (2%), extraorganic inflammatory changes (2%). Only 5% of cases failed to reliably detect signs of a pathological process in the presence of a clinical picture. The main characteristics of the risk group for the emergence of acute abdominal pathology, such as the age of 32-67 years, the male sex, are revealed. A more detailed analysis of risk factors within the statistically most significant nosological groups was also carried out. The diagnostic efficiency index of multislice computed tomography (CT) for the above diseases varied from 95% to 97%, the sensitivity and specificity of the method depending on the disease were 95-97.8% and 93.2-97%, respectively, p> 0.05. Conclusions. CT allows to determine the nature of the disease quite accurately in emergency medical care in patients with nontraumatic urgent abdominal pathology. The identification of a risk group in the structure of acute nontraumatic abdominal pathology facilitates early diagnosis and timely treatment.
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The original technique of the collection and adaptation different types of diagnostic information for congenital urinary malformations in newborns for the Systems of automated analysis of three-dimensional images and surgical navigation
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01.01.2018 |
Nemkovskiy G.
Podurovskaya Y.
Balashov I.
Kozhin P.
Prohin A.
Bychenko V.
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Procedia Computer Science |
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Ссылка
© 2018 The Author(s). The article describes the processes of collecting and adapting the diagnostic information necessary for use in automated analysis of three-dimensional images and surgical navigation. The work is carried out on the basis of the NMRC Obstetrics, Gynecology And Perinatology named after V.I. Kulakov of the Ministry of Health of the Russian Federation with the financial support of the Ministry of Science and Education of the Russian Federation (Agreement dated 03.10.2016 No. 14.607.21.0162, unique identifier RFMEFI60716X0162) The work is devoted to the features of collection, segmentation and description of the results of preoperative radiological diagnostics of newborn patients with congenital urinary malformations such as hydronephrosis (HN), renal duplication with uretherohydronephrosis of the nonfunctional segment (UHN) or multicystic dysplastic kidney (MC). The goal of the work is the development of standards for the collection, classification and segmentation of various diagnostic information of congenital urinary malformations in newborns necessary to use in automated three-dimensional image analysis and surgical navigation. In order to expand the scope of application, it was decided to supplement the data bank with information from the patient's phenotypic chart, compiled by the clinical geneticist when examining the patient. According to the developed and implemented algorithms we collected and segmented 978 series of images belonging to 393 patients with urinary malformations and 452 series of normal urinary System. Available text descriptions of the series are reconstructed to the original developed standard. At present, using this data bank, a subSystem of neural network analysis and reconstruction of diagnostic images of newborn patients is being developed, as well as a surgical navigation System for performing endoscopic surgical manipulations on patients for congenital malformations of the urinal System.
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