Inter-Observer Agreement between Low-Dose and Standard-Dose CT with Soft and Sharp Convolution Kernels in COVID-19 Pneumonia.

Computed tomography (CT) has been an essential diagnostic tool during the COVID-19 pandemic. The study aimed to develop an optimal CT protocol in terms of safety and reliability. For this, we assessed the inter-observer agreement between CT and low-dose CT (LDCT) with soft and sharp kernels using a semi-quantitative severity scale in a prospective study (Moscow, Russia).

Outstanding negative prediction performance of solid pulmonary nodule volume AI for ultra-LDCT baseline lung cancer screening risk stratification.

Objective: To evaluate performance of AI as a standalone reader in ultra-low-dose CT lung cancer baseline screening, and compare it to that of experienced radiologists.

Methods: 283 participants who underwent a baseline ultra-LDCT scan in Moscow Lung Cancer Screening, between February 2017-2018, and had at least one solid lung nodule, were included. Volumetric nodule measurements were performed by five experienced blinded radiologists, and independently assessed using an AI lung cancer screening prototype (AVIEW LCS, v1.

Methodology for Conducting Post-Marketing Surveillance of Software as a Medical Device Based on Artificial Intelligence Technologies.

Unlabelled: was to develop a methodology for conducting post-registration clinical monitoring of software as a medical device based on artificial intelligence technologies (SaMD-AI).

Materials And Methods: The methodology of post-registration clinical monitoring is based on the requirements of regulatory legal acts issued by the Board of the Eurasian Economic Commission. To comply with these requirements, the monitoring involves submission of the review of adverse events reports, the review of developers' routine reports on the safety and efficiency of SaMD-AI, and the assessment of the system for collecting and analyzing developers' post-registration data on the safety and efficiency of medical devices.

Text Analysis of Radiology Reports with Signs of Intracranial Hemorrhage on Brain CT Scans Using the Decision Tree Algorithm.

Unlabelled: is to create, train, and test the algorithm for the analysis of brain CT text reports using a decision tree model to solve the task of simple binary classification of presence/absence of intracranial hemorrhage (ICH) signs.

Materials And Methods: The initial data is a download from the Unified Radiological Information Service of the Unified Medical Information and Analytical System (URIS UMIAS) containing 34,188 studies obtained by a non-contrast CT of the brain in 56 inpatient medical settings. Data analysis and preprocessing were carried out using NLTK (Natural Language Toolkit, version 3.

Sample Size Calculation for Clinical Trials of Medical Decision Support Systems with Binary Outcome.

Currently, software products for use in medicine are actively developed. Among them, the dominant share belongs to clinical decision support systems (CDSS), which can be intelligent (based on mathematical models obtained by machine learning methods or other artificial intelligence technologies) or non-intelligent. For the state registration of CDSSs as software medical products, clinical trials are required, and the protocol of trial is developed jointly by the developer and an authorized medical organization.

[Adrenal imaging: anatomy and pathology (literature review)].

This literature review focuses on the normal adrenal gland anatomy and typical imaging features necessary to evaluate benign and malignant lesions. In particular, adenoma, pheochromocytoma, metastases and adrenocortical carcinoma were discussed as some of the most common lesions. For this purpose, a review of relevant local and international literature sources up to January 2021 was conducted.

A phantom study to optimise the automatic tube current modulation for chest CT in COVID-19.

On March 11, 2020, the World Health Organization declared the coronavirus disease 2019 (COVID-19) pandemic. The expert organisations recommend more cautious use of thoracic computed tomography (CT), opting for low-dose protocols. We aimed at determining a threshold value of automatic tube current modulation noise index below which there is a chance to miss an onset of ground-glass opacities (GGO) in COVID-19.

A simplified cluster model and a tool adapted for collaborative labeling of lung cancer CT scans.

Background And Objective: Lung cancer is the most common type of cancer with a high mortality rate. Early detection using medical imaging is critically important for the long-term survival of the patients. Computer-aided diagnosis (CAD) tools can potentially reduce the number of incorrect interpretations of medical image data by radiologists.

CT-Based COVID-19 triage: Deep multitask learning improves joint identification and severity quantification.

The current COVID-19 pandemic overloads healthcare systems, including radiology departments. Though several deep learning approaches were developed to assist in CT analysis, nobody considered study triage directly as a computer science problem. We describe two basic setups: Identification of COVID-19 to prioritize studies of potentially infected patients to isolate them as early as possible; Severity quantification to highlight patients with severe COVID-19, thus direct them to a hospital or provide emergency medical care.

Chest MRI of patients with COVID-19.

During the pandemic of novel coronavirus infection (COVID-19), computed tomography (CT) showed its effectiveness in diagnosis of coronavirus infection. However, ionizing radiation during CT studies causes concern for patients who require dynamic observation, as well as for examination of children and young people. For this retrospective study, we included 15 suspected for COVID-19 patients who were hospitalized in April 2020, Russia.

Differences in Temporal Volume between Males and Females and the Influence of Age and BMI: A Cross-Sectional CT-Imaging Study.

Background:  The temple has been identified as one of the most compelling facial regions in which to seek aesthetic improvement-both locally and in the entire face-when injecting soft tissue fillers.

Objective:  The objective of this study is to identify influences of age, gender, and body mass index (BMI) on temporal parameters to better understand clinical observations and to identify optimal treatment strategies for treating temporal hollowing.

Methods:  The sample consisted of 28 male and 30 female individuals with a median age of 53 (34) years and a median BMI of 27.

[Artificial intelligence for diagnosis of vertebral compression fractures using a morphometric analysis model, based on convolutional neural networks].

Background: Pathological low-energy (LE) vertebral compression fractures (VFs) are common complications of osteoporosis and predictors of subsequent LE fractures. In 84% of cases, VFs are not reported on chest CT (CCT), which calls for the development of an artificial intelligence-based (AI) assistant that would help radiology specialists to improve the diagnosis of osteoporosis complications and prevent new LE fractures.

Aims: To develop an AI model for automated diagnosis of compression fractures of the thoracic spine based on chest CT images.

Metamaterial inspired wireless coil for clinical breast imaging.

In this work, we propose an application of a metamaterial inspired volumetric wireless coil (WLC) based on coupled split-loop resonators for targeted breast MRI at 1.5 T. Due to strong electromagnetic coupling with the body coil, the metamaterial inspired WLC locally focuses radiofrequency (RF) magnetic flux in the target region, thus improving both transmit and receive performance of the external body coil.

[Epicardial fat Tissue Volumetry: Comparison of Semi-Automatic Measurement and the Machine Learning Algorithm].

Aim        To compare assessments of epicardial adipose tissue (EAT) volumes obtained with a semi-automatic, physician-performed analysis and an automatic analysis using a machine-learning algorithm by data of low-dose (LDCT) and standard computed tomography (CT) of chest organs.Material and methods        This analytical, retrospective, transversal study randomly included 100 patients from a database of a united radiological informational service (URIS). The patients underwent LDCT as a part of the project "Low-dose chest computed tomography as a screening method for detection of lung cancer and other diseases of chest organs" (n=50) and chest CT according to a standard protocol (n=50) in outpatient clinics of Moscow.

Ceramic resonators for targeted clinical magnetic resonance imaging of the breast.

Currently, human magnetic resonance (MR) examinations are becoming highly specialized with a pre-defined and often relatively small target in the body. Conventionally, clinical MR equipment is designed to be universal that compromises its efficiency for small targets. Here, we present a concept for targeted clinical magnetic resonance imaging (MRI), which can be directly integrated into the existing clinical MR systems, and demonstrate its feasibility for breast imaging.

The Course of the Angular Artery in the Midface: Implications for Surgical and Minimally Invasive Procedures.

Background: Previous anatomic studies have provided valuable information on the 2-dimensional course of the angular segment of the facial artery in the midface and its arterial connections. The third dimension (ie, the depth of the artery) is less well characterized.

Objectives: The objective of the present study was to describe the 3-dimensional pathway of the angular segment of the facial artery and its relationship to the muscles of facial expression.

Three-Dimensional Description of the Angular Artery in the Nasolabial Fold.

Background: Due to its arterial vasculature, the nasolabial sulcus is one of the most challenging facial regions to treat when trying to ameliorate the signs of facial aging.

Objectives: The aim of the present study was to provide data on the 3-dimensional course of the angular artery within the nasolabial sulcus in relation to age, gender, and body mass index to increase safety during minimally invasive treatments.

Methods: Thee hundred nasolabial sulci from 75 males and 75 females of Russian Caucasian ethnic background (mean [standard deviation] age, 45.