Digital Diagnostics

Serous adenocarcinoma of the fallopian tubes is an extremely rare and difficult to diagnose form of the female genital tract malignancies. This pathology is often asymptomatic or accompanied by a nonspecific clinical picture, including serosanguineous vaginal discharge, colicky pain in the lower abdomen and pelvis, and adnexal mass. These symptoms are known in the literature as the Lacko triad and are considered pathognomonic for fallopian tube cancer. However, all of these symptoms occur in less than 15% of patients. The low frequency of occurrence and the absence of pathognomonic clinical picture lead to a high number of diagnostic errors, or to the diagnosis of the disease already in a neglected stage, which significantly worsens the prognosis for the patient. The exact diagnosis at the preoperative stage is established in only 4% of cases. This clinical observation describes a case of serous adenocarcinoma of the fallopian tube with all manifestations of the Lacko triad and MR imaging, which allowed us to suspect the presence of serous adenocarcinoma in the patient at the preoperative stage.

Oleg I. Mynko

Anna P. Gonchar

Valentin A. Valentin

Evgeniya A. Kulikova

Andrey L. Yudin

Elena A. Yumatova

Magnetic resonance imaging in the diagnosis of serous adenocarcinoma of fallopian tubes - description of a clinical observation.

磁共振成像在输卵管浆液性腺癌诊断中的应用——一项临床观察的描述。

Background. Recently, the term 'dosiomics' has gained popularity in the literature as a new direction in radiomics. Dosiomics is a texture analysis method that focuses on radiation dose distribution plans in radiation therapy. Most of the published research in the field of dosiomics is focused on predicting radiation-induced lung injury. Aim. To identify predictors of radiation-induced lung injury using texture analysis of CT images. Materials and methods. The study used data from 36 patients with breast cancer who underwent postoperative conformal radiotherapy. The patients were retrospectively divided into two groups: 13 patients with minimal postradiation lung changes and 23 patients with radiation-induced pulmonary fibrosis. CT scans of 36 patients during radiotherapy planning, along with radiation dose distribution maps, were uploaded to 3D Slicer software. Radiomic and dosimic features were extracted from the regions of interest in the chest soft tissue and lung regions on the irradiated side, where doses exceeded 10Gy and 3Gy. Results. In the lung region with a dose of more than 3 Gy, statistically significant differences were found for 3 radiomic features and 1 dosiomic features. Statistically significant differences were found in 12 radiomic and 1 dosiomic features in the area of the lung with a dose of more than 10Gy. In the area of soft tissues of the thorax statistically significant differences were found for 18 radiomic and 4 dosiomic features. Conclusion. The study suggests a correlation between radiation dose and radiomic and dosiomic features in the lung and soft tissues of the thorax. Several radiomic and dosiomics features where found that were statistically different in breast cancer patients with minimal post-radiation changes and those with radiation-induced pulmonary fibrosis. The identified biomarkers, based on texture analysis, may be used in the prediction of radiation-induced lung injury and identification of patients at higher risk of developing it.

Nikolay V. Nudnov

Vladimir M. Sotnikov

Mikhail E. Ivannikov

Elina S-A. Shakhvalieva

Aleksandr A. Borisov

Vasiliy V. Ledenev

Aleksei Yu. Smyslov

Alina V. Anan'ina

Applying radiomics and dosiomics to identify predictors of radiation-induced lung injury.

应用放射组学和剂量组学识别放射性肺损伤预测因子。

Data processing methods using neural networks are gaining increasing popularity in a variety of medical diagnostic problems. Most often, such methods are used in the study of medical images of human organs using CT scan and magnetic resonance imaging, ultrasound and other non-invasive research methods. Diagnosing pathology in this case is the problem of segmenting a medical image, that is, searching for groups (regions) of pixels that characterize certain objects in them. One of the most successful methods for solving this problem is the U-Net neural network architecture developed in 2015. This review examines various modifications of the classic U-Net architecture. The reviewed papers are divided into several key areas: modifications of the encoder and decoder, the use of attention blocks, combination with elements of other architectures, methods for introducing additional features, transfer learning and approaches for processing small sets of real data. Various training sets are considered, for which the best values of various metrics achieved in the literature are given (similarity coefficient Dice, intersection over union IoU, overall accuracy and some others). A summary table is provided indicating the types of images analyzed and the pathologies detected on them. Promising directions for further modifications to improve the quality of solving segmentation problems are outlined. This review can be useful for determining a set of tools for identifying various diseases, primarily cancers. The presented algorithms can be a basis of professional intelligent medical assistants.

Anastasia M. Dostovalova

Andrey K. Gorshenin

Julia V. Starichkova

Kirill M. Arzamasov

COMPARATIVE ANALYSIS OF MODIFICATIONS OF U-NET NEURAL NETWORK ARCHITECTURES IN THE PROBLEM OF MEDICAL IMAGE SEGMENTATION

医学图像分割问题中U-Net神经网络架构修改的比较分析

Background. Radiomics is promising tool contributing to the diagnosis and treatment of neuroendocrine neoplasms of various localizations. This method is often used for differential diagnosis of gastrointestinal neoplasms from other neoplasms of this localization.Aim. To demonstrate difficulties in imaging of gastrointestinal neuroendocrine tumors, as well as possibilities of radiomics in differential diagnosis.Materials and methods. Data of 12 patients with morphologically confirmed gastric neoplasms (6 - with neuroendocrine tumor, 6 - with adenocarcinoma) and data of 22 patients with morphologically confirmed pancreatic neoplasms (11 - with neuroendocrine tumor, 11 - with adenocarcinoma) who underwent CT examination of abdominal cavity organs with intravenous contrast before treatment at the Russian Scientific Center of Roentgenoradiology were used in this study. Radiomic features were extracted from the area of manually segmented gastric and pancreatic tumors in the native phase of the CT scans. Processing of the features and statistical analysis were performed using Microsoft Office Excel and free open-source software development environment for the R programming language - R-Studio.Results. Typical and atypical imaging features of gastric and pancreatic neuroendocrine tumors, peculiarities of contrast, localization and structure of neoplasms were demonstrated on the examples of CT scans. There were 15 radiomic features that were statistically significantly different in patients with neuroendocrine tumors and gastric adenocarcinomas. In the group of patients with neuroendocrine tumors and pancreatic adenocarcinomas, statistically significant differences were observed in 14 radiomic features.Conclusion. Neuroendocrine tumors of the stomach and pancreas are rare neoplasms that are not only clinically silent in most cases, but also difficult to visualize due to their small size and poor contrast characteristics. Texture analysis is a promising tool for the differential diagnosis of gastrointestinal neoplasms from other neoplasms of this localization, especially considering the difficulties of biopsy.

David G. Karelidze

Neuroendocrine tumors of the stomach and pancreas. Possibilities of application of radiomics. Problems and solutions.

胃和胰腺神经内分泌肿瘤。放射组学应用的可能性、问题与解决方案。

The differential diagnosis of "intracardiac mass" in the region of the mitral annulus, detected by echocardiography, can be challenging. A multimodal approach is usually required to clear up. Sometimes the nature of detected mass may be due to subvalvular mitral annular calcification. The presented series of case reports emphasizes the importance and clinical significance of computed tomography in identifying and characterization subvalvular mitral annular calcification with ambiguous results of other diagnostic methods, in particular echocardiography.

Maria V. Onoyko

Elena A. Mershina

Amalia A. Arakelyants

Valentin E. Sinitsyn

The role of computed tomography in differential diagnosis of "intracardiac mass" in the mitral valve region (a series of case reports)

计算机断层扫描在二尖瓣区域“心内肿块”鉴别诊断中的作用（一系列病例报告）

BACKGROUND: Size and localization, as well as clear differentiation between intact tissue and infarcted area, are important for clinical diagnosis and precision medicine. This work is based on the study of radiomics features capable of differentiating areas of infarcted and distant tissue from the infarct area using data from non-contrast cine cardiac MRI imaging. AIM: Evaluation of the possibilities and informativeness of radiomics analysis in detection of postinfarction areas of the left ventricular myocardium in patients with ischemic cardiomyopathy by contrast-free cine cardiac MRI images. MATHERIALS AND METHODS: The results of contrast enhancement cardiac MRI with of 33 patients undergoing surgical treatment for ischemic cardiomyopathy were analyzed. Texture analysis was performed on 66 sections of cine cardiac MRI images, and 105 texture characteristics were determined for each of them. Cardiac MRI was performed according to the standard technique on a Vantage Titan (Toshiba) 1.5 T. Texture analysis was performed using 3D slicer-version 5.2.2 software, SlicerRadiomics RESULTS: Collinearity diagrams of the features were constructed. We also identified the features with zero importance and established the importance of the features using the gradient boosting algorithm. In addition, the cumulative importance of the features as a function of their total number was estimated. Using the method of identifying features with low importance, we identified the parameters with the lowest importance that do not affect the indicated total level. Using the method of identifying features with a single value, we did not find features with a single unique value. In addition, ROC curve for Lasso logistic regression (Se =57.14% Sp=71.43%, AUC=0.76) was generated based on the results of the analysis. The main result of this study is the identification of radiomics features able to characterize the areas corresponding to postinfarction cardiosclerosis and intact LV wall on the basis of cine cardiac MRI images. CONCLUSION: This study has shown that the use of radiomics analysis on contrast-free cine cardiac MRI images is a promising approach to identify areas corresponding to myocardial infarction and intact wall and could potentially be used as to identify areas of postinfarction cardiosclerosis in patients with ischemic cardiomyopathy without the use of contrast agents.

Aleksandra S. Maksimova

Denis S. Samatov

Boris S. Merzlikin

Tatiana A. Shelkovnikova

Artem I. Listratov

Konstantin V. Zavadovsky

RADIOMICS APPLICATIONS IN NON-CONTRAST CINE CARDIAC MAGNETIC RESONANCE IMAGING IN THE DETECTION OF LEFT VENTRICULAR POSTINFARCTION CARDIOSCLEROSIS

非对比剂心脏磁共振成像中放射组学在检测左心室梗死后心肌硬化中的应用

涉及主题	医学内科学生物放射科病理计算机科学物理外科疾病
出版信息	出版商: Eco-Vector LLC，出版周期: ，期刊类型: journal，开源期刊: 是
基本数据	创刊年份: 2020，原创研究文献占比: 0.00%，自引率:N.A.， Gold OA占比: 0.00%
平均审稿周期	网友分享经验：5 Weeks

Digital Diagnostics

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Magnetic resonance imaging in the diagnosis of serous adenocarcinoma of fallopian tubes - description of a clinical observation.

Applying radiomics and dosiomics to identify predictors of radiation-induced lung injury.

COMPARATIVE ANALYSIS OF MODIFICATIONS OF U-NET NEURAL NETWORK ARCHITECTURES IN THE PROBLEM OF MEDICAL IMAGE SEGMENTATION

Neuroendocrine tumors of the stomach and pancreas. Possibilities of application of radiomics. Problems and solutions.

The role of computed tomography in differential diagnosis of "intracardiac mass" in the mitral valve region (a series of case reports)

COMPARATIVE ANALYSIS OF MODIFICATIONS OF U-NET NEURAL NETWORK ARCHITECTURES IN THE PROBLEM OF MEDICAL IMAGE SEGMENTATION

Magnetic resonance imaging in the diagnosis of serous adenocarcinoma of fallopian tubes - description of a clinical observation.

Applying radiomics and dosiomics to identify predictors of radiation-induced lung injury.

RADIOMICS APPLICATIONS IN NON-CONTRAST CINE CARDIAC MAGNETIC RESONANCE IMAGING IN THE DETECTION OF LEFT VENTRICULAR POSTINFARCTION CARDIOSCLEROSIS

Neuroendocrine tumors of the stomach and pancreas. Possibilities of application of radiomics. Problems and solutions.

ISSN	2712-8490, 2712-8962
h-index	6