Population Studies and Molecular Mechanisms of Human Radioadaptive Capabilities: Is It Time to Rethink Radiation Safety Standards?

The evolution of man on Earth took place under conditions of constant exposure to background ionizing radiation (IR). From this point of view, it would be reasonable to hypothesize the existence of adaptive mechanisms that enable the human organism to safely interact with IR at levels approximating long-term natural background levels. In some situations, the successful operation of molecular mechanisms of protection against IR is observed at values significantly exceeding the natural background level, for example, in cancer cells.

Effectiveness of Telemedicine in Inflammatory Bowel Disease in Russia: TIGE-Rus (Telemonitoring for IBD Goodness Examination in Russia) Study Protocol of a Randomized Controlled Trial.

: Inflammatory bowel diseases (IBD), associated with a significant burden on patients' lives, are becoming increasingly common. Patients with IBD need continuous treatment and lifelong monitoring, which could be achieved by telemonitoring. Telemonitoring has been shown to be effective in improving outcomes for patients with IBD, and can provide a more convenient and accessible way for patients to receive care.

LPC-SonoNet: A Lightweight Network Based on SonoNet and Light Pyramid Convolution for Fetal Ultrasound Standard Plane Detection.

The detection of fetal ultrasound standard planes (FUSPs) is important for the diagnosis of fetal malformation and the prevention of perinatal death. As a promising deep-learning technique in FUSP detection, SonoNet's network parameters have a large size. In this paper, we introduced a light pyramid convolution (LPC) block into SonoNet and proposed LPC-SonoNet with reduced network parameters for FUSP detection.

Prostate magnetic resonance imaging (MRI) in patients with hip implants-presetting a protocol using a phantom.

Background: Metal structures are a source of artifacts that significantly complicate the interpretation of magnetic resonance imaging (MRI). The use of prostate MRI as a preliminary test in men with a suspicion on prostate cancer leads to an increased use of the test. The aim of this study was to solve a clinically significant problem: to ensure the reduction of artifacts from metal hip implants during prostate MRI.

Development and Validation of a Questionnaire to Assess the Radiologists' Views on the Implementation of Artificial Intelligence in Radiology (ATRAI-14).

: Artificial Intelligence (AI) is becoming an essential part of modern radiology. However, available evidence highlights issues in the real-world applicability of AI tools and mixed radiologists' acceptance. We aimed to develop and validate a questionnaire to evaluate the attitude of radiologists toward radiology AI (ATRAI-14).

Development of fetal magnetic resonance imaging (MRI) phantom.

Background: Anthropomorphic phantoms play an important role in routine clinical practice. They can be used to calibrate magnetic resonance imaging (MRI) scanners, control the diagnostic equipment quality, and reduce the acquisition time. The latter is especially critical for diagnosing fetal anomalies, which requires optimal image quality within the shortest possible time.

Gunshot Wounds to the Head: 29 Cases of Monocenter Children's Trauma Hospital Experience and Predictor Scales in Pediatric Population.

Objectives: Gunshot wounds to the head (GSWTH) in children remain an underexplored area, and all clinical guidelines extrapolated from adult experiences. A key challenge in treating these patients is age stratification, as pediatric survival rates are notably higher than in adults. The objective of the study is to compare 2 groups of patients based on the severity of their condition and to analyze the impact of various factors on the outcomes of these conditions.

Independent evaluation of the accuracy of 5 artificial intelligence software for detecting lung nodules on chest X-rays.

Background: The integration of artificial intelligence (AI) into medicine is growing, with some experts predicting its standalone use soon. However, skepticism remains due to limited positive outcomes from independent validations. This research evaluates AI software's effectiveness in analyzing chest X-rays (CXR) to identify lung nodules, a possible lung cancer indicator.

Development, evaluation and validation of machine learning models to predict hospitalizations of patients with coronary artery disease within the next 12 months.

Background: Improved survival of patients after acute coronary syndromes, population growth, and overall life expectancy rise have led to a significant increase in the proportion of patients with stable coronary artery disease (CAD), creating a significant load on the entire healthcare system. The disease often progresses with the development of many complications while significantly increasing the likelihood of hospitalization. Developing and applying a machine learning model for predicting hospitalizations of patients with CAD to an inpatient medical facility will allow for close monitoring of high-risk patients, early preventive interventions, and optimized medical care.

Clinical application of radiological AI for pulmonary nodule evaluation: Replicability and susceptibility to the population shift caused by the COVID-19 pandemic.

Purpose: replicability and generalizability of medical AI are the recognized challenges that hinder a broad AI deployment in clinical practice. Pulmonary nodes detection and characterization based on chest CT images is one of the demanded use cases for automatization by means of AI, and multiple AI solutions addressing this task are becoming available. Here, we evaluated and compared the performance of several commercially available radiological AI with the same clinical task on the same external datasets acquired before and during the pandemic of COVID-19.

Routine Brain MRI Findings on the Long-Term Effects of COVID-19: A Scoping Review.

Rationale And Objectives: Post-COVID condition (PCC) is associated with long-term neuropsychiatric symptoms. Magnetic resonance imaging (MRI) in PCC examines the brain metabolism, connectivity, and morphometry. Such techniques are not easily available in routine practice.

Approaches to Sampling for Quality Control of Artificial Intelligence in Biomedical Research.

Unlabelled: is to evaluate the efficacy of approaches to sampling during periodic quality control of the artificial intelligence (AI) results in biomedical practice.

Materials And Methods: The approaches to sampling based on point statistical estimation, statistical hypothesis testing, employing ready-made statistical tables, as well as options of the approaches presented in GOST R ISO 2859-1-2007 "Statistical methods. Sampling procedures for inspection by attributes" have been analyzed.

An International Non-Inferiority Study for the Benchmarking of AI for Routine Radiology Cases: Chest X-ray, Fluorography and Mammography.

An international reader study was conducted to gauge an average diagnostic accuracy of radiologists interpreting chest X-ray images, including those from fluorography and mammography, and establish requirements for stand-alone radiological artificial intelligence (AI) models. The retrospective studies in the datasets were labelled as containing or not containing target pathological findings based on a consensus of two experienced radiologists, and the results of a laboratory test and follow-up examination, where applicable. A total of 204 radiologists from 11 countries with various experience performed an assessment of the dataset with a 5-point Likert scale via a web platform.

AI-Based CXR First Reading: Current Limitations to Ensure Practical Value.

We performed a multicenter external evaluation of the practical and clinical efficacy of a commercial AI algorithm for chest X-ray (CXR) analysis (Lunit INSIGHT CXR). A retrospective evaluation was performed with a multi-reader study. For a prospective evaluation, the AI model was run on CXR studies; the results were compared to the reports of 226 radiologists.

Giant and Tunable Excitonic Optical Anisotropy in Single-Crystal Halide Perovskites.

During the last years, giant optical anisotropy has demonstrated its paramount importance for light manipulation. In spite of recent advances in the field, the achievement of continuous tunability of optical anisotropy remains an outstanding challenge. Here, we present a solution to the problem through the chemical alteration of halogen atoms in single-crystal halide perovskites.

A 178-clinical-center experiment of integrating AI solutions for lung pathology diagnosis.

In 2020, an experiment testing AI solutions for lung X-ray analysis on a multi-hospital network was conducted. The multi-hospital network linked 178 Moscow state healthcare centers, where all chest X-rays from the network were redirected to a research facility, analyzed with AI, and returned to the centers. The experiment was formulated as a public competition with monetary awards for participating industrial and research teams.

Diagnostic Accuracy of AI for Opportunistic Screening of Abdominal Aortic Aneurysm in CT: A Systematic Review and Narrative Synthesis.

In this review, we focused on the applicability of artificial intelligence (AI) for opportunistic abdominal aortic aneurysm (AAA) detection in computed tomography (CT). We used the academic search system PubMed as the primary source for the literature search and Google Scholar as a supplementary source of evidence. We searched through 2 February 2022.

Greater volumes of a callosal sub-region terminating in posterior language-related areas predict a stronger degree of language lateralization: A tractography study.

Language lateralization is the most intriguing trait of functional asymmetry for cognitive functions. Nowadays, ontogenetic determinants of this trait are largely unknown, but there are efforts to find its anatomical correlates. In particular, a white matter interhemispheric connection-the corpus callosum-has been proposed as such.

Quadrature transceive wireless coil: Design concept and application for bilateral breast MRI at 1.5 T.

Purpose: Development of a novel quadrature inductively driven transceive wireless coil for breast MRI at 1.5 T.

Methods: A quadrature wireless coil (HHMM-coil) design has been developed as a combination of two linearly polarized coils: a pair of 'metasolenoid' coils (MM-coil) and a pair of Helmholtz-type coils (HH-coil).

Systematic review of the radiomics quality score applications: an EuSoMII Radiomics Auditing Group Initiative.

Objective: The main aim of the present systematic review was a comprehensive overview of the Radiomics Quality Score (RQS)-based systematic reviews to highlight common issues and challenges of radiomics research application and evaluate the relationship between RQS and review features.

Methods: The literature search was performed on multiple medical literature archives according to PRISMA guidelines for systematic reviews that reported radiomic quality assessment through the RQS. Reported scores were converted to a 0-100% scale.

Interpretable vertebral fracture quantification via anchor-free landmarks localization.

Vertebral body compression fractures are early signs of osteoporosis. Though these fractures are visible on Computed Tomography (CT) images, they are frequently missed by radiologists in clinical settings. Prior research on automatic methods of vertebral fracture classification proves its reliable quality; however, existing methods provide hard-to-interpret outputs and sometimes fail to process cases with severe abnormalities such as highly pathological vertebrae or scoliosis.

Changes in software as a medical device based on artificial intelligence technologies.

Purpose: to develop a procedure for registering changes, notifying users about changes made, unifying software as a medical device based on artificial intelligence technologies (SaMD-AI) changes, as well as requirements for testing and inspections-quality control before and after making changes.

Methods: The main types of changes, divided into two groups-major and minor. Major changes imply a subsequent change of a SaMD-AI version to improve efficiency and safety, to change the functionality, and to ensure the processing of new data types.

Volumetric wireless coil for wrist MRI at 1.5 T as a practical alternative to Tx/Rx extremity coil: a comparative study.

This work performs a detailed assessment of radiofrequency (RF) safety and imaging performance of a volumetric wireless coil based on periodically coupled split-loop resonators (SLRs) for 1.5 T wrist MRI versus a commercially available transceive extremity coil. In particular, we evaluated the transmit efficiency and RF safety for three setups: a whole-body birdcage coil, a transceive extremity birdcage coil, and a volumetric wireless coil inductively coupled to the whole-body birdcage coil.

Facilitating standardized COVID-19 suspicion prediction based on computed tomography radiomics in a multi-demographic setting.

Objective: To develop an automatic COVID-19 Reporting and Data System (CO-RADS)-based classification in a multi-demographic setting.

Methods: This multi-institutional review boards-approved retrospective study included 2720 chest CT scans (mean age, 58 years [range 18-100 years]) from Italian and Russian patients. Three board-certified radiologists from three countries assessed randomly selected subcohorts from each population and provided CO-RADS-based annotations.