Development of a machine learning approach for prediction of red blood cell transfusion in patients undergoing Cesarean section at a single institution.

Despite recent advances in surgical techniques and perinatal management in obstetrics for reducing intraoperative bleeding, blood transfusion may occur during a cesarean section (CS). This study aims to identify machine learning models with an optimal diagnostic performance for intraoperative transfusion prediction in parturients undergoing a CS. Additionally, to address model performance degradation due to data imbalance, this study further investigated the variation in predictive model performance depending on the ratio of event to non-event data (1:1, 1:2, 1:3, and 1:4 model datasets and raw data).

Association Between Taurine Level in the Hippocampus and Major Depressive Disorder in Young Women: A Proton Magnetic Resonance Spectroscopy Study at 7T.

Background: Major depressive disorder (MDD) is characterized by depressed mood or loss of interest or pleasure. Generally, women are twice as likely as men to have depression. Taurine, a type of amino acid, plays critical roles in neuronal generation, differentiation, arborization, and formation of synaptic connections.

Prediction of Decompensation and Death in Advanced Chronic Liver Disease Using Deep Learning Analysis of Gadoxetic Acid-Enhanced MRI.

Objective: This study aimed to evaluate the usefulness of quantitative indices obtained from deep learning analysis of gadoxetic acid-enhanced hepatobiliary phase (HBP) MRI and their longitudinal changes in predicting decompensation and death in patients with advanced chronic liver disease (ACLD).

Materials And Methods: We included patients who underwent baseline and 1-year follow-up MRI from a prospective cohort that underwent gadoxetic acid-enhanced MRI for hepatocellular carcinoma surveillance between November 2011 and August 2012 at a tertiary medical center. Baseline liver condition was categorized as non-ACLD, compensated ACLD, and decompensated ACLD.

Preliminary Study for Quantitative Assessment of Sacroiliitis Activity Using Bone SPECT/CT: Comparison of Diagnostic Performance of Quantitative Parameters.

Purpose: We compared the feasibility of quantitative analysis methods using bone SPECT/CT with those using planar bone scans to assess active sacroiliitis.

Methods: We retrospectively reviewed whole-body bone scans and pelvic bone SPECT/CTs of 8 patients who had clinically confirmed sacroiliitis and enrolled 24 patients without sacroiliitis as references. The volume of interest of each sacroiliac joint, including both the ilium and sacrum, was drawn.

Deep Learning-Based Assessment of Functional Liver Capacity Using Gadoxetic Acid-Enhanced Hepatobiliary Phase MRI.

Objective: We aimed to develop and test a deep learning algorithm (DLA) for fully automated measurement of the volume and signal intensity (SI) of the liver and spleen using gadoxetic acid-enhanced hepatobiliary phase (HBP)-magnetic resonance imaging (MRI) and to evaluate the clinical utility of DLA-assisted assessment of functional liver capacity.

Materials And Methods: The DLA was developed using HBP-MRI data from 1014 patients. Using an independent test dataset (110 internal and 90 external MRI data), the segmentation performance of the DLA was measured using the Dice similarity score (DSS), and the agreement between the DLA and the ground truth for the volume and SI measurements was assessed with a Bland-Altman 95% limit of agreement (LOA).

Prediction of the Acuity of Vertebral Compression Fractures on CT Using Radiologic and Radiomic Features.

Rationale And Objectives: To develop and validate prediction models to differentiate acute and chronic vertebral compression fractures based on radiologic and radiomic features on CT.

Materials And Methods: This study included acute and chronic compression fractures in patients who underwent both spine CT and MRI examinations. For each fractured vertebra, three CT findings ([1] cortical disruption, [2] hypoattenuating cleft or sclerotic line, and [3] relative bone marrow attenuation) were assessed by two radiologists.

Preoperative prediction of postsurgical outcomes in mass-forming intrahepatic cholangiocarcinoma based on clinical, radiologic, and radiomics features.

Objectives: Current prognostic systems for intrahepatic cholangiocarcinoma (IHCC) rely on surgical pathology data and are not applicable to a preoperative setting. We aimed to develop and validate preoperative models to predict postsurgical outcomes in mass-forming IHCC patients based on clinical, radiologic, and radiomics features.

Methods: This multicenter retrospective cohort study included patients who underwent curative-intent resection for mass-forming IHCC.

Combined radiomics-clinical model to predict malignancy of vertebral compression fractures on CT.

Objectives: To develop and validate a combined radiomics-clinical model to predict malignancy of vertebral compression fractures on CT.

Methods: One hundred sixty-five patients with vertebral compression fractures were allocated to training (n = 110 [62 acute benign and 48 malignant fractures]) and validation (n = 55 [30 acute benign and 25 malignant fractures]) cohorts. Radiomics features (n = 144) were extracted from non-contrast-enhanced CT images.

Radiomics and deep learning in liver diseases.

Recently, radiomics and deep learning have gained attention as methods for computerized image analysis. Radiomics and deep learning can perform diagnostic or predictive tasks using high-dimensional image-derived features and have the potential to expand the capabilities of liver imaging beyond the scope of traditional visual image analysis. Recent research has demonstrated the potential of these techniques in various fields of liver imaging, including staging of liver fibrosis, prognostication of malignant liver tumors, automated detection and characterization of liver tumors, automated abdominal organ segmentation, and body composition analysis.

Isotope Effect in the Magneto-Optoelectronic Response of Organic Light-Emitting Diodes Based on Donor-Acceptor Exciplexes.

The isotope effect is studied in the magneto-electroluminescence (MEL) and pulsed electrically detected magnetic resonance of organic light-emitting diodes based on thermally activated delayed fluorescence (TADF) from donor-acceptor exciplexes that are either protonated (H) or deuterated (D). It is found that at ambient temperature, the exchange of H to D has no effect on the spin-dependent current and MEL responses in the devices. However, at cryogenic temperatures, where the reverse intersystem crossing (RISC) from triplet to singlet exciplex diminishes, a pronounced isotope effect is observed.

Radiomics and Deep Learning: Hepatic Applications.

Radiomics and deep learning have recently gained attention in the imaging assessment of various liver diseases. Recent research has demonstrated the potential utility of radiomics and deep learning in staging liver fibroses, detecting portal hypertension, characterizing focal hepatic lesions, prognosticating malignant hepatic tumors, and segmenting the liver and liver tumors. In this review, we outline the basic technical aspects of radiomics and deep learning and summarize recent investigations of the application of these techniques in liver disease.

Gadoxetate-enhanced dynamic contrast-enhanced MRI for evaluation of liver function and liver fibrosis in preclinical trials.

Background: To facilitate translational drug development for liver fibrosis, preclinical trials need to be run in parallel with clinical research. Liver function estimation by gadoxetate-enhanced dynamic contrast-enhanced MRI (DCE-MRI) is being established in clinical research, but still rarely used in preclinical trials. We aimed to evaluate feasibility of DCE-MRI indices as translatable biomarkers in a liver fibrosis animal model.

Netrin-1/DCC-mediated PLCγ1 activation is required for axon guidance and brain structure development.

[Image: see text]

Analysis of quantitative correlations between microaneurysm, ischaemic index and new vessels in ultrawide-field fluorescein angiography images using automated software.

Background/aim: To analyse ultrawide-field fluorescein angiography (UWF-FA) images of diabetic retinopathy using a novel software that automatically calculates microaneurysm (MA) and non-perfusion area.

Methods: Two hundred UWF-FA images of treatment-naïve diabetic retinopathy (38 proliferative diabetic retinopathy and 162 non-proliferative diabetic retinopathy) from 120 patients (mean age 54.22; 80 male) were analysed using novel software to determine the number of MAs, area of capillary non-perfusion (ischaemic index) and number of neovascularisations.

Amide proton transfer-weighted MRI can detect tissue acidosis and monitor recovery in a transient middle cerebral artery occlusion model compared with a permanent occlusion model in rats.

Objectives: To assess whether increases in amide proton transfer (APT)-weighted signal reflect the effects of tissue recovery from acidosis using transient rat middle cerebral artery occlusion (MCAO) models, compared to permanent occlusion models.

Materials And Methods: Twenty-four rats with MCAO (17 transient and seven permanent occlusions) were prepared. APT-weighted signal (APTw), apparent diffusion coefficient (ADC), cerebral blood flow (CBF), and MR spectroscopy were evaluated at three stages in each group (occlusion, reperfusion/1 h post-occlusion, and 3 h post-reperfusion/4 h post-occlusion).

Radiomics Analysis of Gadoxetic Acid-enhanced MRI for Staging Liver Fibrosis.

Purpose To develop and validate a radiomics-based model for staging liver fibrosis by using gadoxetic acid-enhanced hepatobiliary phase MRI. Materials and Methods In this retrospective study, 436 patients (mean age, 51 years; age range, 18-86 years; 319 men [mean age, 51 years; age range, 18-86 years]; 117 women [mean age, 50 years; age range, 18-79 years]) with pathologic analysis-proven liver fibrosis who underwent gadoxetic acid-enhanced MRI from June 2015 to December 2016 were randomized in a three-to-one ratio into development (n = 329) and test (n = 107) cohorts, respectively. In the development cohort, a model was developed to calculate radiomics fibrosis index (RFI) by using logistic regression with elastic net regularization to differentiate stage F3-F4 from stage F0-F2.

Correction to: Contribution of Zinc-Dependent Delayed Calcium Influx via TRPC5 in Oxidative Neuronal Death and its Prevention by Novel TRPC Antagonist.

After the publication of this work errors were noticed in Fig. 3b and 4d.

Netrin-1/DCC-mediated PLCγ1 activation is required for axon guidance and brain structure development.

Coordinated expression of guidance molecules and their signal transduction are critical for correct brain wiring. Previous studies have shown that phospholipase C gamma1 (PLCγ1), a signal transducer of receptor tyrosine kinases, plays a specific role in the regulation of neuronal cell morphology and motility However, several questions remain regarding the extracellular stimulus that triggers PLCγ1 signaling and the exact role PLCγ1 plays in nervous system development. Here, we demonstrate that PLCγ1 mediates axonal guidance through a netrin-1/deleted in colorectal cancer (DCC) complex.

Improved Diagnostic Accuracy of Alzheimer's Disease by Combining Regional Cortical Thickness and Default Mode Network Functional Connectivity: Validated in the Alzheimer's Disease Neuroimaging Initiative Set.

Objective: To identify potential imaging biomarkers of Alzheimer's disease by combining brain cortical thickness (CThk) and functional connectivity and to validate this model's diagnostic accuracy in a validation set.

Materials And Methods: Data from 98 subjects was retrospectively reviewed, including a study set (n = 63) and a validation set from the Alzheimer's Disease Neuroimaging Initiative (n = 35). From each subject, data for CThk and functional connectivity of the default mode network was extracted from structural T1-weighted and resting-state functional magnetic resonance imaging.

Influence of B-Inhomogeneity on Pharmacokinetic Modeling of Dynamic Contrast-Enhanced MRI: A Simulation Study.

Objective: To simulate the B-inhomogeneity-induced variation of pharmacokinetic parameters on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

Materials And Methods: B-inhomogeneity-induced flip angle (FA) variation was estimated in a phantom study. Monte Carlo simulation was performed to assess the FA-deviation-induced measurement error of the pre-contrast R, contrast-enhancement ratio, Gd-concentration, and two-compartment pharmacokinetic parameters (K, v, and v).

Dynamic contrast-enhanced MRI for oncology drug development.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a promising tool for evaluating tumor vascularity, as it can provide vasculature-derived, functional, and quantitative parameters. To implement DCE-MRI parameters as biomarkers for monitoring the effect of antiangiogenic or vascular-disrupting treatment, two crucial elements of surrogate endpoint, ie, validation and qualification, should be satisfied. Although early studies have shown the accuracy and reliability of DCE-MRI parameters for evaluating treatment-driven vascular alterations, there have been an increasing number of studies demonstrating the limitations of DCE-MRI parameters as surrogate endpoints.

Dual MRI T1 and T2(*) contrast with size-controlled iron oxide nanoparticles.

Unlabelled: Contrast-enhancing magnetic resonance mechanism, employing either positive or negative signal changes, has contrast-specific signal characteristics. Although highly sensitive, negative contrast typically decreases the resolution and spatial specificity of MRI, whereas positive contrast lacks a high contrast-to-noise ratio but offers high spatial accuracy. To overcome these individual limitations, dual-contrast acquisitions were performed using iron oxide nanoparticles and a pair of MRI acquisitions.

The rate of resolution of clot burden measured by pulmonary CT angiography in patients with acute pulmonary embolism.

Objective: The purpose of this article is to quantitatively assess the rate of resolution of clot burden detected on pulmonary CT angiography (CTA) in patients with acute pulmonary embolism (PE).

Materials And Methods: We evaluated 111 consecutive patients (55 men and 56 women) in a retrospective cohort who were diagnosed with PE by pulmonary CTA and had at least one follow-up pulmonary CTA within 1 year. Two radiologists in consensus measured the volume of each clot using a semiautomated quantification program.