Comparing multi-texture fibrosis analysis versus binary opacity-based abnormality detection for quantitative assessment of idiopathic pulmonary fibrosis.

Automated tools for quantification of idiopathic pulmonary fibrosis (IPF) can aid in ensuring reproducibility, however their complexity and costs can differ substantially. In this retrospective study, two automated tools were compared in 45 patients with biopsy proven (12/45) and imaging-based (33/45) IPF diagnosis (mean age 74 ± 9 years, 37 male) for quantification of pulmonary fibrosis in CT. First, a tool that identifies multiple characteristic lung texture features was applied to measure multi-texture fibrotic lung (MTFL) by combining the amount of ground glass, reticulation, and honeycombing.

Deep learning for opportunistic, end-to-end automated assessment of epicardial adipose tissue in pre-interventional, ECG-gated spiral computed tomography.

Objectives: Recently, epicardial adipose tissue (EAT) assessed by CT was identified as an independent mortality predictor in patients with various cardiac diseases. Our goal was to develop a deep learning pipeline for robust automatic EAT assessment in CT.

Methods: Contrast-enhanced ECG-gated cardiac and thoraco-abdominal spiral CT imaging from 1502 patients undergoing transcatheter aortic valve replacement (TAVR) was included.

Deep Learning Virtual Contrast-Enhanced T1 Mapping for Contrast-Free Myocardial Extracellular Volume Assessment.

Background: The acquisition of contrast-enhanced T1 maps to calculate extracellular volume (ECV) requires contrast agent administration and is time consuming. This study investigates generative adversarial networks for contrast-free, virtual extracellular volume (vECV) by generating virtual contrast-enhanced T1 maps.

Methods And Results: This retrospective study includes 2518 registered native and contrast-enhanced T1 maps from 1000 patients who underwent cardiovascular magnetic resonance at 1.

Elasticity Mapping of Colloidal Glasses Reveals the Interplay between Mesoscopic Order and Granular Mechanics.

Colloidal glasses (CGs) made of polymer (polymethylmethacrylate) nanoparticles are promising metamaterials for light and sound manipulation, but fabrication imperfections and fragility can limit their functionality and applications. Here, the vibrational mechanical modes of nanoparticles are probed to evaluate the nanomechanical and morphological properties of various CGs architectures. Utilizing the scanning micro-Brillouin light scattering (µ-BLS), the effective elastic constants and nanoparticles' sizes is determined as a function of position in a remote and non-destructive manner.

Primary Care Telehealth Initiation and Engagement Among Veterans at High Risk, 2019-2022.

Importance: During the COVID-19 pandemic, the Veterans Health Administration (VHA) expanded telehealth infrastructure. Understanding telehealth initiation and sustained engagement could inform future resource allocation for high-need populations.

Objective: To describe and examine primary care use, including initiation, use, and engagement factors, of telehealth modalities (telephone, video visits, and secure messaging) from 2020 to 2022.

Reducing Central Nervous System-Active Medications to Prevent Falls and Injuries Among Older Adults: A Cluster Randomized Clinical Trial.

Importance: High-risk medications that contribute to adverse health outcomes are frequently prescribed to older adults. Deprescribing interventions reduce their use, but studies are often not designed to examine effects on patient-relevant health outcomes.

Objective: To test the effect of a health system-embedded deprescribing intervention targeting older adults and their primary care clinicians for reducing the use of central nervous system-active drugs and preventing medically treated falls.

Health Expenditures After Bariatric Surgery: A Retrospective Cohort Study.

Objective: To compare expenditures between surgical and matched nonsurgical patients in a retrospective cohort study.

Background: Bariatric surgery leads to substantial improvements in weight and weight-related conditions, but prior literature on postsurgical health expenditures is equivocal.

Methods: In a retrospective study, total outpatient, inpatient, and medication expenditures 3 years before and 5.

Bariatric Surgery and the Long-Term Risk of Venous Thromboembolism: A Population-Based Cohort Study.

Purpose: Bariatric surgery is associated with a greater venous thromboembolism (VTE) risk in the weeks following surgery, but the long-term risk of VTE is incompletely characterized. We evaluated bariatric surgery in relation to long-term VTE risk.

Materials And Methods: This population-based retrospective matched cohort study within three United States-based integrated health care systems included adults with body mass index (BMI) ≥ 35 kg/m who underwent bariatric surgery between January 2005 and September 2015 (n = 30,171), matched to nonsurgical patients on site, age, sex, BMI, diabetes, insulin use, race/ethnicity, comorbidity score, and health care utilization (n = 218,961).

Residential Density Is Associated With BMI Trajectories in Children and Adolescents: Findings From the Moving to Health Study.

Introduction: This study investigates the associations between built environment features and 3-year BMI trajectories in children and adolescents.

Methods: This retrospective cohort study utilized electronic health records of individuals aged 5-18 years living in King County, Washington, from 2005 to 2017. Built environment features such as residential density; counts of supermarkets, fast-food restaurants, and parks; and park area were measured using SmartMaps at 1,600-meter buffers.

Neighborhood built and food environment in relation to glycemic control in people with type 2 diabetes in the moving to health study.

Objective: To examine whether built environment and food metrics are associated with glycemic control in people with type 2 diabetes.

Research Design And Methods: We included 14,985 patients with type 2 diabetes using electronic health records from Kaiser Permanente Washington. Patient addresses were geocoded with ArcGIS using King County and Esri reference data.

CT-derived Epicardial Adipose Tissue Inflammation Predicts Outcome in Patients Undergoing Transcatheter Aortic Valve Replacement.

Purpose: Inflammatory changes in epicardial (EAT) and pericardial adipose tissue (PAT) are associated with increased overall cardiovascular risk. Using routine, preinterventional cardiac CT data, we examined the predictive value of quantity and quality of EAT and PAT for outcome after transcatheter aortic valve replacement (TAVR).

Materials And Methods: Cardiac CT data of 1197 patients who underwent TAVR at the in-house heart center between 2011 and 2020 were retrospectively analyzed.

Nucleolar protein TAAP1/ confers pro-survival signaling in non-small cell lung cancer.

Tumor cells subvert immune surveillance or lytic stress by harnessing inhibitory signals. Hence, bispecific antibodies have been developed to direct CTLs to the tumor site and foster immune-dependent cytotoxicity. Although applied with success, T cell-based immunotherapies are not universally effective partially because of the expression of pro-survival factors by tumor cells protecting them from apoptosis.

Opportunistic CT-derived analysis of fat and muscle tissue composition predicts mortality in patients with cardiogenic shock.

Prognosis estimation in patients with cardiogenic shock (CS) is important to guide clinical decision making. Aim of this study was to investigate the predictive value of opportunistic CT-derived body composition analysis in CS patients. Amount and density of fat and muscle tissue of 152 CS patients were quantified from single-slice CT images at the level of the intervertebral disc space L3/L4.

Evaluation of Algorithms Using Automated Health Plan Data to Identify Breast Cancer Recurrences.

Background: We updated algorithms to identify breast cancer recurrences from administrative data, extending previously developed methods.

Methods: In this validation study, we evaluated pairs of breast cancer recurrence algorithms (vs. individual algorithms) to identify recurrences.

Development of image-based decision support systems utilizing information extracted from radiological free-text report databases with text-based transformers.

Objectives: To investigate the potential and limitations of utilizing transformer-based report annotation for on-site development of image-based diagnostic decision support systems (DDSS).

Methods: The study included 88,353 chest X-rays from 19,581 intensive care unit (ICU) patients. To label the presence of six typical findings in 17,041 images, the corresponding free-text reports of the attending radiologists were assessed by medical research assistants ("gold labels").

Direct deep learning-based survival prediction from pre-interventional CT prior to transcatheter aortic valve replacement.

Purpose: To investigate survival prediction in patients undergoing transcatheter aortic valve replacement (TAVR) using deep learning (DL) methods applied directly to pre-interventional CT images and to compare performance with survival models based on scalar markers of body composition.

Method: This retrospective single-center study included 760 patients undergoing TAVR (mean age 81 ± 6 years; 389 female). As a baseline, a Cox proportional hazards model (CPHM) was trained to predict survival on sex, age, and the CT body composition markers fatty muscle fraction (FMF), skeletal muscle radiodensity (SMRD), and skeletal muscle area (SMA) derived from paraspinal muscle segmentation of a single slice at L3/L4 level.

Deep learning-based assessment of CT markers of sarcopenia and myosteatosis for outcome assessment in patients with advanced pancreatic cancer after high-intensity focused ultrasound treatment.

Objectives: To evaluate the prognostic value of CT-based markers of sarcopenia and myosteatosis in comparison to the Eastern Cooperative Oncology Group (ECOG) score for survival of patients with advanced pancreatic cancer treated with high-intensity focused ultrasound (HIFU).

Materials And Methods: For 142 retrospective patients, the skeletal muscle index (SMI), skeletal muscle radiodensity (SMRD), fatty muscle fraction (FMF), and intermuscular fat fraction (IMFF) were determined on superior mesenteric artery level in pre-interventional CT. Each marker was tested for associations with sex, age, body mass index (BMI), and ECOG.

Establishment and Molecular Characterization of an In Vitro Model for PARPi-Resistant Ovarian Cancer.

Overcoming PARPi resistance is a high clinical priority. We established and characterized comparative in vitro models of acquired PARPi resistance, derived from either a -proficient or -deficient isogenic background by long-term exposure to olaparib. While parental cell lines already exhibited a certain level of intrinsic activity of multidrug resistance (MDR) proteins, resulting PARPi-resistant cells from both models further converted toward MDR.

Peripheral polyneuropathy in children and young adults with ataxia-telangiectasia.

Background And Purpose: Ataxia-telangiectasia (A-T) is a rare, autosomal recessive, multisystem disorder that leads to progressive neurodegeneration with cerebellar ataxia and peripheral polyneuropathy. Cerebellar neurodegeneration is well described in A-T. However, peripheral nervous system involvement is an underdiagnosed but important additional target for supportive and systemic therapies.

A health-system-embedded deprescribing intervention targeting patients and providers to prevent falls in older adults (STOP-FALLS trial): study protocol for a pragmatic cluster-randomized controlled trial.

Background: Central nervous system (CNS) active medications have been consistently linked to falls in older people. However, few randomized trials have evaluated whether CNS-active medication reduction reduces falls and fall-related injuries. The objective of the Reducing CNS-active Medications to Prevent Falls and Injuries in Older Adults (STOP-FALLS) trial is to test the effectiveness of a health-system-embedded deprescribing intervention focused on CNS-active medications on the incidence of medically treated falls among community-dwelling older adults.

Remission and Relapse of Hypertension After Bariatric Surgery: A Retrospective Study on Long-Term Outcomes.

Unlabelled: To compare hypertension remission and relapse after bariatric surgery compared with usual care.

Background: The effect of Roux-en-Y gastric bypass and sleeve gastrectomy on hypertension remission and relapse has not been studied in large, multicenter studies over long periods and using clinical blood pressure (BP) measurements.

Methods: This retrospective cohort study was set in Kaiser Permanente Washington, Northern California, and Southern California.

Transformer-based structuring of free-text radiology report databases.

Objectives: To provide insights for on-site development of transformer-based structuring of free-text report databases by investigating different labeling and pre-training strategies.

Methods: A total of 93,368 German chest X-ray reports from 20,912 intensive care unit (ICU) patients were included. Two labeling strategies were investigated to tag six findings of the attending radiologist.

Deep learning enables automated MRI-based estimation of uterine volume also in patients with uterine fibroids undergoing high-intensity focused ultrasound therapy.

Background: High-intensity focused ultrasound (HIFU) is used for the treatment of symptomatic leiomyomas. We aim to automate uterine volumetry for tracking changes after therapy with a 3D deep learning approach.

Methods: A 3D nnU-Net model in the default setting and in a modified version including convolutional block attention modules (CBAMs) was developed on 3D T2-weighted MRI scans.

Deep learning for standardized, MRI-based quantification of subcutaneous and subfascial tissue volume for patients with lipedema and lymphedema.

Objectives: To contribute to a more in-depth assessment of shape, volume, and asymmetry of the lower extremities in patients with lipedema or lymphedema utilizing volume information from MR imaging.

Methods: A deep learning (DL) pipeline was developed including (i) localization of anatomical landmarks (femoral heads, symphysis, knees, ankles) and (ii) quality-assured tissue segmentation to enable standardized quantification of subcutaneous (SCT) and subfascial tissue (SFT) volumes. The retrospectively derived dataset for method development consisted of 45 patients (42 female, 44.

Flonicamid metabolite 4-trifluoromethylnicotinamide is a chordotonal organ modulator insecticide.

Background: The selective aphicide flonicamid is known to cause symptoms in aphids that are like those of chordotonal organ TRPV channel modulator insecticides such as pymetrozine, pyrifluquinazon and afidopyropen. Flonicamid is classified by the Insecticide Resistance Action Committee as a chordotonal organ modulator with an undefined target site. However, although it has been shown not to act on TRPV channels, flonicamid's action on chordotonal organs has not been documented in the literature.