Automated Integration of AI Results into Radiology Reports Using Common Data Elements.

Integration of artificial intelligence (AI) into radiology practice can create opportunities to improve diagnostic accuracy, workflow efficiency, and patient outcomes. Integration demands the ability to seamlessly incorporate AI-derived measurements into radiology reports. Common data elements (CDEs) define standardized, interoperable units of information.

The landscape of plasma proteomic links to human organ imaging.

Plasma protein levels provide important insights into human disease, yet a comprehensive assessment of plasma proteomics across organs is lacking. Using large-scale multimodal data from the UK Biobank, we integrated plasma proteomics with organ imaging to map their phenotypic and genetic links, analyzing 2,923 proteins and 1,051 imaging traits across multiple organs. We uncovered 5,067 phenotypic protein-imaging associations, identifying both organ-specific and organ-shared proteomic relations, along with their enriched protein-protein interaction networks and biological pathways.

Quantification of NAD T and T Relaxation Times Using Downfield H MRS at 7 T in Human Brain In Vivo.

The purpose of this study was to measure T and T relaxation times of NAD proton resonances in the downfield H MRS spectrum in human brain at 7 T in vivo and to assess the propagation of relaxation time uncertainty in NAD quantification. Downfield spectra from eight healthy volunteers were acquired at multiple echo times to measure T relaxation times, and saturation recovery data were acquired to measure T relaxation times. The downfield acquisition used a spectrally selective 90° sinc pulse for excitation centered at 9.

Demographic-Based Personalized Left Ventricular Hypertrophy Thresholds for Hypertrophic Cardiomyopathy Diagnosis.

Background: Hypertrophic cardiomyopathy (HCM) is a leading cause of sudden cardiac death. Current diagnosis emphasizes the detection of left ventricular hypertrophy (LVH) using a fixed threshold of ≥15-mm maximum wall thickness (MWT). This study proposes a method that considers individual demographics to adjust LVH thresholds as an alternative to a 1-size-fits-all approach.

Automated Characterization of Abdominal MRI Exams Using Deep Learning.

Advances in magnetic resonance imaging (MRI) have revolutionized disease detection and treatment planning. However, as the volume and complexity of MRI data grow with increasing heterogeneity between institutions in imaging protocol, scanner technology, and data labeling, there is a need for a standardized methodology to efficiently identify, characterize, and label MRI sequences. Such a methodology is crucial for advancing research efforts that incorporate MRI data from diverse populations to develop robust machine learning models.

Denoising diffusion model for increased performance of detecting structural heart disease.

Recent advancements in generative artificial intelligence have shown promise in producing realistic images from complex data distributions. We developed a denoising diffusion probabilistic model trained on the CheXchoNet dataset, encoding the joint distribution of demographic data and echocardiogram measurements. We generated a synthetic dataset skewed towards younger patients with a higher prevalence of structural left ventricle disease.

Mapping rare protein-coding variants on multi-organ imaging traits.

Human organ structure and function are important endophenotypes for clinical outcomes. Genome-wide association studies (GWAS) have identified numerous common variants associated with phenotypes derived from magnetic resonance imaging (MRI) of the brain and body. However, the role of rare protein-coding variations affecting organ size and function is largely unknown.

Optimization of H-MRS methods for large-volume acquisition of low-concentration downfield resonances at 3 T and 7 T.

Purpose: This goal of this study was to optimize spectrally selective H-MRS methods for large-volume acquisition of low-concentration metabolites with downfield resonances at 7 T and 3 T, with particular attention paid to detection of nicotinamide adenine dinucleotide (NAD) and tryptophan.

Methods: Spectrally selective excitation was used to avoid magnetization-transfer effects with water, and various sinc pulses were compared with a band-selective, uniform response, pure-phase (E-BURP) pulse. Localization using a single-slice selective pulse was compared with voxel-based localization that used three orthogonal refocusing pulses, and low bandwidth refocusing pulses were used to take advantage of the chemical shift displacement of water.

Protein-truncating variant in APOL3 increases chronic kidney disease risk in epistasis with APOL1 risk alleles.

BACKGROUNDTwo coding alleles within the APOL1 gene, G1 and G2, found almost exclusively in individuals genetically similar to West African populations, contribute substantially to the pathogenesis of chronic kidney disease (CKD). The APOL gene cluster on chromosome 22 contains a total of 6 APOL genes that have arisen as a result of gene duplication.METHODSUsing a genome-first approach in the Penn Medicine BioBank, we identified 62 protein-altering variants in the 6 APOL genes with a minor allele frequency of >0.

A Cloud-Based System for Automated AI Image Analysis and Reporting.

Although numerous AI algorithms have been published, the relatively small number of algorithms used clinically is partly due to the difficulty of implementing AI seamlessly into the clinical workflow for radiologists and for their healthcare enterprise. The authors developed an AI orchestrator to facilitate the deployment and use of AI tools in a large multi-site university healthcare system and used it to conduct opportunistic screening for hepatic steatosis. During the 60-day study period, 991 abdominal CTs were processed at multiple different physical locations with an average turnaround time of 2.

Acute nicotinamide riboside supplementation increases human cerebral NAD levels in vivo.

Purpose: The purpose of this study was to determine the effect of acute nicotinamide riboside (NR) supplementation on cerebral nicotinamide adenine dinucleotide (NAD) levels in the human brain in vivo by means of downfield proton MRS (DF H MRS).

Methods: DF H MRS was performed on 10 healthy volunteers in a 7.0 T MRI scanner with spectrally selective excitation and spatially selective localization to determine cerebral NAD levels on two back-to-back days: once after an overnight fast (baseline) and once 4 h after oral ingestion of nicotinamide riboside (900 mg).

SynthA1c: Towards Clinically Interpretable Patient Representations for Diabetes Risk Stratification.

Early diagnosis of Type 2 Diabetes Mellitus (T2DM) is crucial to enable timely therapeutic interventions and lifestyle modifications. As the time available for clinical office visits shortens and medical imaging data become more widely available, patient image data could be used to opportunistically identify patients for additional T2DM diagnostic workup by physicians. We investigated whether image-derived phenotypic data could be leveraged in tabular learning classifier models to predict T2DM risk in an automated fashion to flag high-risk patients the need for additional blood laboratory measurements.

CT imaging-derived phenotypes for abdominal muscle and their association with age and sex in a medical biobank.

The study of muscle mass as an imaging-derived phenotype (IDP) may yield new insights into determining the normal and pathologic variations in muscle mass in the population. This can be done by determining 3D abdominal muscle mass from 12 distinct abdominal muscle regions and groups using computed tomography (CT) in a racially diverse medical biobank. To develop a fully automatic technique for assessment of CT abdominal muscle IDPs and preliminarily determine abdominal muscle IDP variations with age and sex in a clinically and racially diverse medical biobank.

Thoracic Aortic Three-Dimensional Geometry.

Background: Aortic structure impacts cardiovascular health through multiple mechanisms. Aortic structural degeneration occurs with aging, increasing left ventricular afterload and promoting increased arterial pulsatility and target organ damage. Despite the impact of aortic structure on cardiovascular health, three-dimensional (3D) aortic geometry has not been comprehensively characterized in large populations.

Optimization of H MR spectroscopy methods for large volume acquisition of low concentration downfield resonances at 3T and 7T.

Purpose: This goal of this study was to optimize spectrally selective H MRS methods for large volume acquisition of low concentration metabolites with downfield resonances at 7T and 3T, with particular attention paid to detection of nicotinamide adenine dinucleotide (NAD) and tryptophan.

Methods: Spectrally selective excitation was used to avoid magnetization transfer effects with water, and various sinc pulses were compared to a pure-phase E-BURP pulse. Localization using a single slice selective pulse was compared to voxel-based localization that used three orthogonal refocusing pulses, and low bandwidth refocusing pulses were used to take advantage of the chemical shift displacement of water.

Quantification of NAD T and T relaxation times using downfield H MRS at 7 T in human brain in vivo.

Introduction: The purpose of this study was to use a single-slice spectrally-selective sequence to measure T and T relaxation times of NAD proton resonances in the downfield H MRS spectrum in human brain at 7 T in vivo and assess the propagation of relaxation time uncertainty in NAD quantification.

Methods: Downfield spectra from 7 healthy volunteers were acquired at multiple echo times in all subjects to measure T relaxation, and saturation recovery data were to measure T relaxation. The downfield acquisition used a spectrally-selective 90° sinc pulse for excitation centered at 9.

Strategies for Implementing Machine Learning Algorithms in the Clinical Practice of Radiology.

Despite recent advancements in machine learning (ML) applications in health care, there have been few benefits and improvements to clinical medicine in the hospital setting. To facilitate clinical adaptation of methods in ML, this review proposes a standardized framework for the step-by-step implementation of artificial intelligence into the clinical practice of radiology that focuses on three key components: problem identification, stakeholder alignment, and pipeline integration. A review of the recent literature and empirical evidence in radiologic imaging applications justifies this approach and offers a discussion on structuring implementation efforts to help other hospital practices leverage ML to improve patient care.

Clinical correlates of CT imaging-derived phenotypes among lean and overweight patients with hepatic steatosis.

The objective of this study is to define CT imaging derived phenotypes for patients with hepatic steatosis, a common metabolic liver condition, and determine its association with patient data from a medical biobank. There is a need to further characterize hepatic steatosis in lean patients, as its epidemiology may differ from that in overweight patients. A deep learning method determined the spleen-hepatic attenuation difference (SHAD) in Hounsfield Units (HU) on abdominal CT scans as a quantitative measure of hepatic steatosis.

Relationships between body fat distribution and metabolic syndrome traits and outcomes: A mendelian randomization study.

Background: Obesity is a complex, multifactorial disease associated with substantial morbidity and mortality worldwide. Although it is frequently assessed using BMI, many epidemiological studies have shown links between body fat distribution and obesity-related outcomes. This study examined the relationships between body fat distribution and metabolic syndrome traits using Mendelian Randomization (MR).

Noninvasive Assessment of Lipomatous Metaplasia as a Substrate for Ventricular Tachycardia in Chronic Infarct.

Myocardial lipomatous metaplasia (LM) has been increasingly reported in patients with prior myocardial infarction. Cardiac magnetic resonance and cardiac contrast-enhanced computed tomography have been used to noninvasively detect and quantify myocardial LM in postinfarct patients, and may provide useful information for understanding cardiac mechanics, arrhythmia susceptibility, and prognosis. This review aims to summarize the advantages and disadvantages, clinical applications, and imaging features of different cardiac magnetic resonance sequences and cardiac contrast-enhanced computed tomography for LM detection and quantification.

Magnetic resonance myocardial T1ρ mapping : Technical overview, challenges, emerging developments, and clinical applications.

The potential of cardiac magnetic resonance to improve cardiovascular care and patient management is considerable. Myocardial T1-rho (T1ρ) mapping, in particular, has emerged as a promising biomarker for quantifying myocardial injuries without exogenous contrast agents. Its potential as a contrast-agent-free ("needle-free") and cost-effective diagnostic marker promises high impact both in terms of clinical outcomes and patient comfort.

Identification of new resonances in downfield H MRS of human calf muscle in vivo: Potentially metabolite precursors for skeletal muscle NAD.

Purpose: The purpose of this study was to identify and characterize newly discovered resonances appearing in the downfield proton MR spectrum (DF H MRS) of the human calf muscle in vivo at 7T.

Methods: Downfield H MRS was performed on the calf muscle of five healthy volunteers at 7T. A spectrally selective 90° E-BURP RF pulse with an excitation center frequency at 10.