Radiology in the Russian Federation in 2016

Тюрин, И. Е.

doi:10.20862/0042-4676-2017-98-4-219-226

Cited by 11 publications

(5 citation statements)

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“…К росту числа КТ-исследований приводит увеличивающееся число выявляемых онкологических заболеваний. Неизбежным результатом КТ является лучевая нагрузка [19]. Первые попытки уменьшения лучевой нагрузки начали предпринимать еще в конце XX века, когда пытались внести изменения в такие параметры сканирования, как коллимация рентгеновского луча, питч, время ротации гентри [20].…”

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Influence of the low-dose CE-MDCT scanning protocol parameters on the results of pancreatic ductal adenocarcinoma radiomic analysis

et al. 2021

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To investigate the dependence of textural parameters of pancreatic ductal adenocarcinoma on using standard and low-dose CT protocols.Materials and methods. The study included 52 consecutive patients with histologically confirmed pancreatic ductal adenocarcinoma who underwent contrast enhanced computed tomography using standard (120 kV) and low-dose (100 kV) scanning protocols. We compared radiomics features of the identical histological tumors in all scanning phases.Results. We calculated 53 radiomics features in all types of pancreatic ductal adenocarcinoma grade differentiation for all scanning phases. We identified that out of 53 features of texture analysis, less than half was statistically different for each scan phase (11 parameters (20.8%) for the unenhanced phase; 18 parameters (34%) for the arterial; 19 parameters (35.8%) for the venous and delayed scanning phases), in all types of tumor differentiation (GLCM_ Contrast, GLCM_Correlation, GLCM_Dissimilarity, GLRLM_SRHGE etc., p < 0.05).The diagnostic accuracy of more than 50% of the radiomics features is preserved when changing kV in the CT scan protocol.Conclusion. The use of a low-dose CT protocol doesn’t affect the diagnostic accuracy of the features of texture analysis in the preoperative assessment of the degree of differentiation of pancreatic ductal adenocarcinoma.

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Section: Discussionunclassified

Influence of the low-dose CE-MDCT scanning protocol parameters on the results of pancreatic ductal adenocarcinoma radiomic analysis

et al. 2021

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“…Активное внедрение методов ЭхоКГ служит одним из условий ранней диагностики клапанного поражения [1]. Так, в 1993 году по данным официальных отчётов в лечебно-профилактических учреждениях РФ ежегодно проводилось около 60 млн лучевых исследований [14], в 2014 году -уже 318 млн исследований с преобладанием ультразвуковых (43%), а в 2016 -326 млн [15]. Кроме того, только за период с 2012 по 2016 гг.…”

Section: обсуждение эпидемиология приобретённых пороков сердцаunclassified

Phenotype of a modern patient with valvular heart diseases: literature review

Dren',

Lyapina,

Pecherina

et al. 2023

CardioSomatics

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In modern conditions, valvular heart diseases (VHD) are one of the most common pathologies among cardiovascular diseases with a dynamic change in the phenotype of patients. An increase in the prevalence of VHD is currently observed due to the active implementation of diagnostic methods in cardiology. Geographical differences in the genesis of the development of valvular heart defects are noted, and the portrait of patients also changes as a result of aging and the addition of comorbid pathology. The purpose of the literature review was to present current trends in changing phenotype of patients with VHD, to study current data on the epidemiology of valve pathology, the contribution of various cardiovascular risk factors and comorbidity of patients on the course of the disease. Current data on the number of surgical interventions performed for VHD based on Russian, European, American, Australian and other studies, data on patient survival and mortality, as well as differences in these indicators in age groups of different countries are presented. The review will be useful for doctors to understand the modern portrait of a patient with VHD, trends in cardiovascular risk factors that influence the course of the disease and prognosis in patients with VHD.

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“…Для выбора подходящей системы медицинским учреждениям необходимо выполнять предварительное тестирование на собственных моделях, эквивалентных исследованиям, которые проводятся в данном учреждении (параметры выполнения рентгенографии, характер и частота выявляемой патологии). О р и г и н а л ь н а я с т а т ь я Ц ифровые рентгенологические исследования легких занимают значимую (более 30%) долю от всех лучевых исследований в Российской Федерации [1,2]. По данным многих авторов, существенную проблему в выявлении патологических изменений на рентгенограммах органов грудной клетки представляют сложность трактовки суммационных изображений и высокие требования к квалификации врачей-рентгенологов [3][4][5].…”

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Evaluation of diagnostic accuracy of the automatic system for the analysis of digital lung X-ray for detection of spherical masses

Gavrilov

Smolnikova

2021

Alʹm. klin. med.

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Rationale: Most data on the effectiveness of systems for the analysis of digital X-ray images have been provided by their developers and require a high-quality validation in databases prepared independently of the developer.Aim: To analyze the information content of automatic identification of spherical lung masses with digital X-ray imaging using one of the widely available diagnostic algorithms on publicly unaccessible reference datasets.Materials and methods: The study was based on the recognition and analysis of digital X-ray images from two publicly inaccessible reference datasets that have the state registration (Russian Federation) with one of the publicly available diagnostic algorithms (FutureMed Analyzer). The study was performed using two models of X-ray screening as examples: Model 1 consisted of 100 X-ray images of the lungs with a normal: abnormal ratio of 94%: 6%; Model 2 consisted of 5150 chest X-ray images with a normal: abnormal ratio of 97%: 3%.Results: According to the results of the analysis of the X-ray images with the diagnostic system, 98% of the images were correctly interpreted with Model 1 and 95% of the images, with Model 2. 83% of the cases from Model 1 and 69% from Model 2% were interpreted as images with lung abnormalities. The percentage of correct answers for differentiation of the chest X-ray images into two categories (normal vs. abnormal) for Model 1 and Model 2 was 95% and 98%, respectively. The sensitivity for detection of abnormal masses ranged from 69% to 83%. The specificity was 99% for the Model 1 chest X-ray images and 96% for the Model 2 chest X-ray images. The underdiagnosis rate was quite low ranging for Model 1 – 17%, and for Model 2 – 31%. The area under the curve for Model 1 was 0.91 and for Model 2 0.85.Conclusion: The diagnostic efficiency of the automatic image analysis based on the convolutional neuronal networks approaches that of the radiologists. This system of automatic identification of abnormalities was unable to solve the most complex problems of detecting low density spherical masses (like "ground glass" area on computed tomography) and that of shadow summation for abnormalities located in such difficult to interpret zones as lung apices, clavicles, ribs, etc. To select a suitable system, medical institutions need to conduct preliminary testing in their own models equivalent to the studies performed in a given institution (parameters for radiography, nature and frequency of abnormalities).

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Radiology in the Russian Federation in 2016

Cited by 11 publications

References 0 publications

Influence of the low-dose CE-MDCT scanning protocol parameters on the results of pancreatic ductal adenocarcinoma radiomic analysis

Influence of the low-dose CE-MDCT scanning protocol parameters on the results of pancreatic ductal adenocarcinoma radiomic analysis

Phenotype of a modern patient with valvular heart diseases: literature review

Evaluation of diagnostic accuracy of the automatic system for the analysis of digital lung X-ray for detection of spherical masses

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