Choice architecture in cascade genetic testing (CHARGE study) for hereditary cancer: Design of a hybrid type I randomized feasibility trial.

Background: Although cascade testing affords disease-free relatives the opportunity for genetically targeted primary disease prevention and is endorsed by multiple guidelines, utilization studies reveal that rates remain low. Lack of family communication and high testing costs are two of the most commonly documented barriers to testing. We leverage two well-known choice-architecture tools from psychology and behavioral science - default effect and zero price effect - to address these barriers and improve cascade testing rates in hereditary cancer.

Free-breathing single-beat exercise cardiovascular magnetic resonance with generative artificial intelligence for evaluation of volumetric and functional cardiac indices: A reproducibility study.

Background: Exercise cardiovascular magnetic resonance (Ex-CMR) can reveal pathophysiologies not evident at rest by quantifying biventricular volume and function during or immediately after exercise. However, achieving reproducible Ex-CMR measurements is challenging due to limited spatial and temporal resolution. This study aimed to develop and evaluate a free-breathing, high-spatiotemporal-resolution single-beat Ex-CMR cine enhanced by generative artificial intelligence.

Population and pan-genomic analyses of identify geographic distinctions in accessory gene content and novel loci associated with AMR.

is a common representative of the normal skin microbiota of dogs and cats but is also a causative agent of a variety of infections. Although primarily a canine/feline bacterium, recent studies suggest an expanded host range including humans. This paper details population genomic analyses of the largest yet assembled and sequenced collection of isolates from across the USA and Canada and assesses these isolates within a larger global population genetic context.

Free-breathing, Highly Accelerated, Single-beat, Multisection Cardiac Cine MRI with Generative Artificial Intelligence.

Purpose To develop and evaluate a free-breathing, highly accelerated, multisection, single-beat cine sequence for cardiac MRI. Materials and Methods This prospective study, conducted from July 2022 to December 2023, included participants with various cardiac conditions as well as healthy participants who were imaged using a 3-T MRI system. A single-beat sequence was implemented, collecting data for each section in one heartbeat.

Radiomic Cardiac MRI Signatures for Predicting Ventricular Arrhythmias in Patients With Nonischemic Dilated Cardiomyopathy.

Background: Risk stratification in patients with nonischemic dilated cardiomyopathy (DCM) remains challenging. Although late gadolinium enhancement (LGE) cardiovascular magnetic resonance is recognized as a major risk factor for ventricular tachycardia/ventricular fibrillation (VT/VF), the prognostic value of LGE radiomics is unknown.

Objectives: The purpose of this study was to investigate if radiomic analysis of LGE images can improve arrhythmia risk stratification in patients with DCM beyond current clinical and imaging markers.

Shared decision making in routine oncology appointments with Black patients with lung cancer.

Purpose: Poor clinician-patient communication may contribute to racialized inequities in cancer symptom burden. Shared decision-making (SDM) enhances clinician-patient communication, and could contribute to health equity for Black patients with cancer. However, research on SDM is limited for Black patients with cancer.

Clinical and Investigative Approach to Recurrent Acute Pancreatitis.

Recurrent acute pancreatitis (RAP) is a complex syndrome that presents variably, with many cases remaining idiopathic after thorough diagnostics. For evaluating structural etiologies, endoscopic ultrasound and MR cholangiopancreatography are preferred over endoscopic retrograde cholangiopancreatography (ERCP) given their more favorable risk profile and sensitivity. The diagnostic work-up remains paramount since treatment should focus on addressing underlying causes such as early cholecystectomy for gallstone pancreatitis.

Association of Epicardial Adipose Tissue and Ventricular Arrhythmias in Patients With Nonischemic Cardiomyopathy.

Background: Risk stratification for sudden cardiac death (SCD) in patients with nonischemic cardiomyopathy (NICM) remains challenging.

Objectives: This study aimed to investigate the impact of epicardial adipose tissue (EAT) on SCD in NICM patients.

Methods: Our study cohort included 173 consecutive patients (age 53 ± 14 years, 73% men) scheduled for primary prevention implantable cardioverter-defibrillators (ICDs) implantation who underwent preimplant cardiovascular magnetic resonance.

Understanding Variation in Bra Cup Sizing Among Leading Manufacturers: A Current Guide for Patients and Surgeons.

Background: Brassiere (bra) size is commonly used when patients and plastic surgeons discuss breast procedures. Variations in sizing between manufacturers can affect patient-surgeon communication and postoperative satisfaction. This study quantifies bra cup volume across alphanumeric sizes and manufacturers to describe variance and improve preoperative communication for shared decision-making.

Accelerated phase-contrast magnetic resonance imaging with use of resolution enhancement generative adversarial neural network.

Background: Cardiovascular magnetic resonance (CMR) phase contrast is used to quantify blood flow. We sought to develop a complex-difference reconstruction for inline super-resolution of phase-contrast flow (CRISPFlow) to accelerate phase-contrast imaging.

Methods: CRISPFlow was built on the super-resolution generative adversarial network.

Late gadolinium enhancement cardiovascular magnetic resonance with generative artificial intelligence.

Background: Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging enables imaging of scar/fibrosis and is a cornerstone of most CMR imaging protocols. CMR imaging can benefit from image acceleration; however, image acceleration in LGE remains challenging due to its limited signal-to-noise ratio. In this study, we sought to evaluate a rapid two-dimensional (2D) LGE imaging protocol using a generative artificial intelligence (AI) algorithm with inline reconstruction.

Accelerated cardiac cine with spatio-coil regularized deep learning reconstruction.

Purpose: To develop an iterative deep learning (DL) reconstruction with spatio-coil regularization and multichannel k-space data consistency for accelerated cine imaging.

Methods: This study proposes a Spatio-Coil Regularized DL (SCR-DL) approach for iterative deep learning reconstruction incorporating multicoil information in data consistency and regularizer. SCR-DL uses shift-invariant convolutional kernels to interpolate missing k-space lines and reconstruct individual coil images, followed by a regularizer that operates simultaneously across spatial and coil dimensions using learned image priors.

Strategies for Identifying and Recruiting Women at High Risk for Breast Cancer for Research Outside of Clinical Settings: Observational Study.

Background: Research is needed to understand and address barriers to risk management for women at high (≥20% lifetime) risk for breast cancer, but recruiting this population for research studies is challenging.

Objective: This paper compares a variety of recruitment strategies used for a cross-sectional, observational study of high-risk women.

Methods: Eligible participants were assigned female at birth, aged 25-85 years, English-speaking, living in the United States, and at high risk for breast cancer as defined by the American College of Radiology.

Barriers and facilitators to breast cancer screening among high-risk women: a qualitative study.

Purpose: Women with greater than 20-25% lifetime breast cancer risk are recommended to have breast cancer screening with annual mammogram and supplemental breast MRI. However, few women follow these screening recommendations. The objective of this study was to identify barriers and facilitators of screening among women at high risk for breast cancer, guided by the Health Services Utilization Model (HSUM).

Obesity-Related Differences in Pathomechanism and Outcomes in Patients With HFpEF: A CMR Study.

Background: Clinical significance of an integrated evaluation of epicardial adipose tissue (EAT) and the right ventricle (RV) in heart failure with preserved ejection fraction (HFpEF) is unknown.

Objectives: The authors investigated the potential of EAT and RV quantification for obesity-related pathophysiology and risk stratification in obese HFpEF patients using cardiovascular magnetic resonance (CMR).

Methods: A total of 150 patients (obese, body mass index ≥30 kg/m; n = 73, nonobese, body mass index <30 kg/m; n = 77) with a clinical diagnosis of HFpEF undergoing CMR were retrospectively identified.

Accelerating the design of lattice structures using machine learning.

Lattices remain an attractive class of structures due to their design versatility; however, rapidly designing lattice structures with tailored or optimal mechanical properties remains a significant challenge. With each added design variable, the design space quickly becomes intractable. To address this challenge, research efforts have sought to combine computational approaches with machine learning (ML)-based approaches to reduce the computational cost of the design process and accelerate mechanical design.

Sustainability of a Pediatric Neurointensive Care Unit Model Within a Mixed Pediatric Intensive Care Unit and Its Effect on Nursing Sentiment.

BACKGROUND: Pediatric neurocritical care (PNCC) and pediatric neurointensive care units (neuro-PICU) are growing fields. Although some institutions have established independent neuro-PICUs meeting most Neurocritical Care Society (NCS) standards for neurocritical care units, many centers lack the resources to do so. We describe an alternative neuro-PICU model as a designated unit within a mixed pediatric intensive care unit (PICU) and its effects on nursing sentiment.

Iterative Development of an Interactive Website to Support Shared Decision-Making in Metastatic Breast Cancer.

Recent treatment advances have resulted in significantly increased survival times following metastatic breast cancer (MBC) diagnosis. Novel treatment approaches-and their related side effects-have changed the landscape of MBC treatment decision-making. We developed a prototype of an online educational tool to prepare patients with MBC for shared decision-making with their oncologists.

Deformation-encoding Deep Learning Transformer for High-Frame-Rate Cardiac Cine MRI.

Purpose To develop a deep learning model for increasing cardiac cine frame rate while maintaining spatial resolution and scan time. Materials and Methods A transformer-based model was trained and tested on a retrospective sample of cine images from 5840 patients (mean age, 55 years ± 19 [SD]; 3527 male patients) referred for clinical cardiac MRI from 2003 to 2021 at nine centers; images were acquired using 1.5- and 3-T scanners from three vendors.

Patterns and Predictors of Referral for Screening Breast MRI: A Mixed-Methods Study.

Women with ≥20% lifetime breast cancer risk can receive supplemental breast cancer screening with MRI. We examined factors associated with recommendation for screening breast MRI among primary care providers (PCPs), gynecologists (GYNs), and radiologists. We conducted a sequential mixed-methods study.

Cardiovascular magnetic resonance characterization of myocardial tissue injury in a miniature swine model of cancer therapy-related cardiovascular toxicity.

Background: Left ventricular ejection fraction (LVEF) is the most commonly clinically used imaging parameter for assessing cancer therapy-related cardiac dysfunction (CTRCD). However, LVEF declines may occur late, after substantial injury. This study sought to investigate cardiovascular magnetic resonance (CMR) imaging markers of subclinical cardiac injury in a miniature swine model.

MRI Assessment of Myocardial Deformation for Risk Stratification of Major Arrhythmic Events in Patients With Non-Ischemic Cardiomyopathy Eligible for Primary Prevention Implantable Cardioverter Defibrillators.

Background: Implantable cardioverter-defibrillator (ICD) intervention is an established prophylactic measure. Identifying high-benefit patients poses challenges.

Purpose: To assess the prognostic value of cardiac magnetic resonance imaging (MRI) parameters including myocardial deformation for risk stratification of ICD intervention in non-ischemic cardiomyopathy (NICM) while accounting for competing mortality risk.

Highly accelerated free-breathing real-time myocardial tagging for exercise cardiovascular magnetic resonance.

Background: Exercise cardiovascular magnetic resonance (Ex-CMR) myocardial tagging would enable quantification of myocardial deformation after exercise. However, current electrocardiogram (ECG)-segmented sequences are limited for Ex-CMR.

Methods: We developed a highly accelerated balanced steady-state free-precession real-time tagging technique for 3 T.

Gadolinium-Free Cardiac MRI Myocardial Scar Detection by 4D Convolution Factorization.

Gadolinium-based contrast agents are commonly used in cardiac magnetic resonance (CMR) imaging to characterize myocardial scar tissue. Recent works using deep learning have shown the promise of contrast-free short-axis cine images to detect scars based on wall motion abnormalities (WMA) in ischemic patients. However, WMA can occur in patients without a scar.