Impact of preoperative beta-hydroxy-beta-methylbutyrate, arginine, and glutamine supplementation on inflammation in patients with cardiac surgery: A secondary analysis of a randomized controlled trial.

Background: Preoperative physical frailty is a significant predictor of adverse postoperative outcomes in older patients undergoing cardiac surgery. Inflammation plays a crucial role in the development of frailty and contributes to postoperative complications. This study investigated the effects of preoperative beta-hydroxy-beta-methylbutyrate (HMB), arginine, and glutamine supplementation on inflammatory markers, nutritional status, and renal function in older patients undergoing cardiac surgery.

Intra-axial primary brain tumor differentiation: comparing large language models on structured MRI reports vs. radiologists on images.

Objective: Aimed to evaluate the potential of large language models (LLMs) in differentiating intra-axial primary brain tumors using structured magnetic resonance imaging (MRI) reports and compare their performance with radiologists.

Materials And Methods: Structured reports of preoperative MRI findings from 137 surgically confirmed intra-axial primary brain tumors, including Glioblastoma (n = 77), Central Nervous System (CNS) Lymphoma (n = 22), Astrocytoma (n = 9), Oligodendroglioma (n = 9), and others (n = 20), were analyzed by multiple LLMs, including GPT-4, Claude-3-Opus, Claude-3-Sonnet, GPT-3.5, Llama-2-70B, Qwen1.

Synergistic effects of underweight and dementia on in-hospital mortality during acute myocardial infarction.

Aims: Although the impact of underweight and dementia on mortality is clear, no large study has examined the synergistic impact of underweight and dementia on acute myocardial infarction (AMI) in real-world settings. Therefore, this study aimed to investigate the synergistic effects of underweight and dementia on in-hospital mortality in AMI patients using a nationwide administrative database.

Methods And Results: This nationwide retrospective cohort study was performed using the Japanese nationwide administrative data (JROAD-DPC) of 474,979 AMI patients between April 2012 and March 2021.

Impact of super-resolution deep learning-based reconstruction for hippocampal MRI: A volunteer and phantom study.

Background And Purpose: To evaluate the effects of super-resolution deep learning-based reconstruction (SR-DLR) on thin-slice T2-weighted hippocampal MR image quality using 3 T MRI, in both human volunteers and phantoms.

Materials And Methods: Thirteen healthy volunteers underwent hippocampal MRI at standard and high resolutions. Original (standard-resolution; StR) images were reconstructed with and without deep learning-based reconstruction (DLR) (Matrix = 320 × 320), and with SR-DLR (Matrix = 960 × 960).

Phocaeicola dorei and Phocaeicola vulgatus Protect against Atherosclerosis by Regulating Gut Immunity.

Aim: Arteriosclerosis is a condition that leads to coronary artery disease (CAD) and stroke. Basic and clinical studies have suggested a link between the gut microbiota and various diseases, including atherosclerosis. Therefore, we focused on gut microbiota and aimed to develop a probiotic-based treatment for atherosclerosis.

Evaluating the Performance of Reasoning Large Language Models on Japanese Radiology Board Examination Questions.

Rationale And Objectives: This study evaluates the performance, cost, and processing time of OpenAI's reasoning large language models (LLMs) (o1-preview, o1-mini) and their base models (GPT-4o, GPT-4o-mini) on Japanese radiology board examination questions.

Materials And Methods: A total of 210 questions from the 2022-2023 official board examinations of the Japan Radiological Society were presented to each of the four LLMs. Performance was evaluated by calculating the percentage of correctly answered questions within six predefined radiology subspecialties.

Predicting rheumatoid arthritis progression from seronegative undifferentiated arthritis using machine learning: a deep learning model trained on the KURAMA cohort and externally validated with the ANSWER cohort.

Background: Undifferentiated arthritis (UA) often develops into rheumatoid arthritis (RA), but predicting disease progression from seronegative UA remains challenging because seronegative RA often does not meet the classification criteria. This study aims to build a machine learning (ML) model to predict the progression from seronegative UA to RA using clinical and laboratory parameters.

Methods: KURAMA cohort (training dataset) and ANSWER cohort (validation dataset) were utilized.

Body Mass Index Affects Hospital-Associated Disability and Economic Burden in Elective Cardiovascular Surgery - JROAD/JROAD-DPC Database.

Background: Both underweight and overweight are recognized as important factors influencing outcomes in patients undergoing cardiovascular surgery. This study investigated the effects of body mass index (BMI) on hospital-associated disability (HAD) and hospitalization costs in patients undergoing elective cardiovascular surgery (coronary artery bypass grafting, valve surgery, aortic surgery) by analyzing data from the Japanese Registry of All Cardiac and Vascular Diseases - Diagnosis Procedure Combination (JROAD-DPC) database.

Methods And Results: All patients in the JROAD-DPC database were categorized into 5 groups according to the World Health Organization BMI criteria for Asians.

U-shaped relationship between body mass index and intracerebral hemorrhage-related functional decline.

Background: Body mass index (BMI) is associated with the sites of intracerebral hemorrhage (ICH), which affect functional decline. However, the optimal BMI range for minimizing functional decline remains unclear. This study aimed to clarify the relationship between BMI and ICH-related functional decline.

Sucrose-preferring gut microbes prevent host obesity by producing exopolysaccharides.

Commensal bacteria affect host health by producing various metabolites from dietary carbohydrates via bacterial glycometabolism; however, the underlying mechanism of action remains unclear. Here, we identified Streptococcus salivarius as a unique anti-obesity commensal bacterium. We found that S.

Effects of preoperative beta-hydroxy-beta-methylbutyrate, arginine, and glutamine supplementation on cardiac surgery: A randomized controlled trial.

Background & Aims: In older patients undergoing cardiac surgery, physical function is a critical determinant of postoperative outcomes. Beta-hydroxy-beta-methylbutyrate (HMB) supplementation has been shown to promote muscle protein anabolism and inhibit catabolism, thereby preventing muscle weakness. However, its efficacy in older patients undergoing cardiac surgery remains unknown.

Deep Learning Reconstruction for Enhanced Resolution and Image Quality in Breath-Hold MRCP: A Preliminary Study.

Objective: This preliminary study aims to assess the image quality of enhanced-resolution deep learning reconstruction (ER-DLR) in magnetic resonance cholangiopancreatography (MRCP) and compare it with non-ER-DLR MRCP images.

Methods: Our retrospective study incorporated 34 patients diagnosed with biliary and pancreatic disorders. We obtained MRCP images using a single breath-hold MRCP on a 3T MRI system.

Impact of deep learning reconstruction on radiation dose reduction and cancer risk in CT examinations: a real-world clinical analysis.

Purpose: The purpose of this study is to estimate the extent to which the implementation of deep learning reconstruction (DLR) may reduce the risk of radiation-induced cancer from CT examinations, utilizing real-world clinical data.

Methods: We retrospectively analyzed scan data of adult patients who underwent body CT during two periods relative to DLR implementation at our facility: a 12-month pre-DLR phase (n = 5553) using hybrid iterative reconstruction and a 12-month post-DLR phase (n = 5494) with routine CT reconstruction transitioning to DLR. To ensure comparability between two groups, we employed propensity score matching 1:1 based on age, sex, and body mass index.

Performance of Multimodal Large Language Models in Japanese Diagnostic Radiology Board Examinations (2021-2023).

Rationale And Objectives: To evaluate the performance of various multimodal large language models (LLMs) in the Japanese Diagnostic Radiology Board Examinations (JDRBE) both with and without images.

Materials And Methods: Five multimodal LLMs-GPT-4o, Claude 3 Opus, GPT-4 Vision, Gemini Flash 1.5, and Gemini Pro 1.

Super-resolution deep learning reconstruction approach for enhanced visualization in lumbar spine MR bone imaging.

Objectives: This study aims to assess the effectiveness of super-resolution deep-learning-based reconstruction (SR-DLR), which leverages k-space data, on the image quality of lumbar spine magnetic resonance (MR) bone imaging using a 3D multi-echo in-phase sequence.

Materials And Methods: In this retrospective study, 29 patients who underwent lumbar spine MRI, including an MR bone imaging sequence between January and April 2023, were analyzed. Images were reconstructed with and without SR-DLR (Matrix sizes: 960 × 960 and 320 × 320, respectively).

Safety of Janus kinase inhibitors compared to biological DMARDs in patients with rheumatoid arthritis and renal impairment: the ANSWER cohort study.

Data on the safety of Janus kinase inhibitors (JAKis) in patients with renal impairment are lacking. This study aimed to investigate the safety of JAKis compared to biological (b) DMARDs in patients with rheumatoid arthritis (RA) and renal impairment. We used a multi-centre observational registry of patients with RA in Japan (the ANSWER cohort).

BCAA-nitrogen flux in brown fat controls metabolic health independent of thermogenesis.

Brown adipose tissue (BAT) is best known for thermogenesis. Rodent studies demonstrated that enhanced BAT thermogenesis is tightly associated with increased energy expenditure, reduced body weight, and improved glucose homeostasis. However, human BAT is protective against type 2 diabetes, independent of body weight.

Optimizing High-Resolution MR Angiography: The Synergistic Effects of 3D Wheel Sampling and Deep Learning-Based Reconstruction.

Objective: The aim of this study was to assess the utility of the combined use of 3D wheel sampling and deep learning-based reconstruction (DLR) for intracranial high-resolution (HR)-time-of-flight (TOF)-magnetic resonance angiography (MRA) at 3 T.

Methods: This prospective study enrolled 20 patients who underwent head MRI at 3 T, including TOF-MRA. We used 3D wheel sampling called "fast 3D" and DLR for HR-TOF-MRA (spatial resolution, 0.

Gut microbial stability in older Japanese populations: insights from the Mykinso cohort.

Gut microbiota imbalance plays an important role in the pathogenesis of various diseases. Here, we determined microbe-microbe interactions and gut microbiome stability in a Japanese population with varying body mass indices (BMIs) and enterotypes. Using 16S ribosomal RNA gene sequencing, we analyzed gut microbial data from fecal samples obtained from 3,365 older Japanese individuals.

Preliminary assessment of automated radiology report generation with generative pre-trained transformers: comparing results to radiologist-generated reports.

Purpose: In this preliminary study, we aimed to evaluate the potential of the generative pre-trained transformer (GPT) series for generating radiology reports from concise imaging findings and compare its performance with radiologist-generated reports.

Methods: This retrospective study involved 28 patients who underwent computed tomography (CT) scans and had a diagnosed disease with typical imaging findings. Radiology reports were generated using GPT-2, GPT-3.

Update on the Use of Artificial Intelligence in Hepatobiliary MR Imaging.

The application of machine learning (ML) and deep learning (DL) in radiology has expanded exponentially. In recent years, an extremely large number of studies have reported about the hepatobiliary domain. Its applications range from differential diagnosis to the diagnosis of tumor invasion and prediction of treatment response and prognosis.