Divergent brain solute clearance in rat models of cerebral amyloid angiopathy and Alzheimer's disease.

Brain waste clearance from the interstitial fluid environment is challenging to measure, which has contributed to controversy regarding the significance of glymphatic transport impairment for neurodegenerative processes. Dynamic contrast enhanced MRI (DCE-MRI) with cerebrospinal fluid administration of Gd-tagged tracers is often used to assess glymphatic system function. We previously quantified glymphatic transport from DCE-MRI data utilizing regularized optimal mass transport (rOMT) analysis, however, information specific to glymphatic clearance was not directly derived.

An effective and open source interactive 3D medical image segmentation solution.

3D medical image segmentation is a key step in numerous clinical applications. Even though many automatic segmentation solutions have been proposed, it is arguably that medical image segmentation is more of a preference than a reference as inter- and intra-variability are widely observed in final segmentation output. Therefore, designing a user oriented and open-source solution for interactive annotation is of great value for the community.

Normal tissue transcriptional signatures for tumor-type-agnostic phenotype prediction.

Cancer transcriptional patterns reflect both unique features and shared hallmarks across diverse cancer types, but whether differences in these patterns are sufficient to characterize the full breadth of tumor phenotype heterogeneity remains an open question. We hypothesized that these shared transcriptomic signatures reflect repurposed versions of functional tasks performed by normal tissues. Starting with normal tissue transcriptomic profiles, we use non-negative matrix factorization to derive six distinct transcriptomic phenotypes, called archetypes, which combine to describe both normal tissue patterns and variations across a broad spectrum of malignancies.

Uncommon and Challenging Phenotypes of High-Risk Human Papillomavirus-Associated Head and Neck Carcinomas Revealed by High-Throughput Studies.

Background: HPV- associated squamous cell carcinoma (SCC) is uncommon in non-oropharynx sites and not well characterized. This study aims to investigate uncommon phenotypes of HPV-associated head and neck carcinoma, the prevalence and morphologic spectrum of HPV-associated SCC in the oral cavity, larynx and hypopharynx.

Method: P16 immunostaining and HPV E6/7 in situ hybridization (ISH) were performed on tissue microarrays comprised of SCCs from different anatomic sites: oropharynx (n = 270), hypopharynx (n = 52), oral cavity (n = 95) and larynx (n = 123).

Morphologic Spectrum of HPV-associated Sinonasal Carcinomas.

Background: High-risk human papillomavirus (HR-HPV) infection has been increasingly recognized as a risk factor for sinonasal tract carcinomas. However the prevalence and prognostic significance of HPV-associated sinonasal carcinomas is not well known due to limited studies and inconsistency in HPV testing modalities in literatures. Morphologically, HPV-associated sinonasal carcinomas encompass a diverse group of tumors.

ACR Appropriateness Criteria® Screening for Abdominal Aortic Aneurysm.

Abdominal aortic aneurysm (AAA) is a significant vascular disease found in 4% to 8% of the screening population. If ruptured, its mortality rate is between 75% and 90%, and it accounts for up to 5% of sudden deaths in the United States. Therefore, screening of AAA while asymptomatic has been a crucial portion of preventive health care worldwide.

ACR Appropriateness Criteria® Pulmonary Arteriovenous Malformation (PAVM): 2023 Update.

Pulmonary arteriovenous malformations (PAVMs) occur in 30% to 50% of patients with hereditary hemorrhagic telangiectasia. Clinical presentations vary from asymptomatic disease to complications resulting from the right to left shunting of blood through the PAVM such as paradoxical stroke, brain abscesses, hypoxemia, and cardiac failure. Radiology plays an important role both in the diagnosis and treatment of PAVM.

Multi-scale geometric network analysis identifies melanoma immunotherapy response gene modules.

Melanoma response to immune-modulating therapy remains incompletely characterized at the molecular level. In this study, we assess melanoma immunotherapy response using a multi-scale network approach to identify gene modules with coordinated gene expression in response to treatment. Using gene expression data of melanoma before and after treatment with nivolumab, we modeled gene expression changes in a correlation network and measured a key network geometric property, dynamic Ollivier-Ricci curvature, to distinguish critical edges within the network and reveal multi-scale treatment-response gene communities.

Unbalanced regularized optimal mass transport with applications to fluid flows in the brain.

As a generalization of the optimal mass transport (OMT) approach of Benamou and Brenier's, the regularized optimal mass transport (rOMT) formulates a transport problem from an initial mass configuration to another with the optimality defined by the total kinetic energy, but subject to an advection-diffusion constraint equation. Both rOMT and the Benamou and Brenier's formulation require the total initial and final masses to be equal; mass is preserved during the entire transport process. However, for many applications, e.

Dynamic network curvature analysis of gene expression reveals novel potential therapeutic targets in sarcoma.

Network properties account for the complex relationship between genes, making it easier to identify complex patterns in their interactions. In this work, we leveraged these network properties for dual purposes. First, we clustered pediatric sarcoma tumors using network information flow as a similarity metric, computed by the Wasserstein distance.

Multi-Scale Geometric Network Analysis Identifies Melanoma Immunotherapy Response Gene Modules.

Melanoma response to immune-modulating therapy remains incompletely characterized at the molecular level. In this study, we assess melanoma immunotherapy response using a multi-scale network approach to identify gene modules with coordinated gene expression in response to treatment. Using gene expression data of melanoma before and after treatment with nivolumab, we modeled gene expression changes in a correlation network and measured a key network geometric property, dynamic Ollivier-Ricci curvature, to distinguish critical edges within the network and reveal multi-scale treatment-response gene communities.

ACR Appropriateness Criteria® Preprocedural Planning for Transcatheter Aortic Valve Replacement: 2023 Update.

This document discusses preprocedural planning for transcatheter aortic valve replacement, evaluating the imaging modalities used in initial imaging for preprocedure planning under two variants 1) Preintervention planning for transcatheter aortic valve replacement: assessment of aortic root; and 2) Preintervention planning for transcatheter aortic valve replacement: assessment of supravalvular aorta and vascular access. US echocardiography transesophageal, MRI heart function and morphology without and with IV contrast, MRI heart function and morphology without IV contrast and CT heart function and morphology with IV contrast are usually appropriate for assessment of aortic root. CTA chest with IV contrast, CTA abdomen and pelvis with IV contrast, CTA chest abdomen pelvis with IV contrast are usually appropriate for assessment of supravalvular aorta and vascular access.

Wasserstein HOG: Local Directionality Extraction via Optimal Transport.

Directionally sensitive radiomic features including the histogram of oriented gradient (HOG) have been shown to provide objective and quantitative measures for predicting disease outcomes in multiple cancers. However, radiomic features are sensitive to imaging variabilities including acquisition differences, imaging artifacts and noise, making them impractical for using in the clinic to inform patient care. We treat the problem of extracting robust local directionality features by mapping via optimal transport a given local image patch to an iso-intense patch of its mean.

Perspectives from two recent medical school graduates on exposure to pathology during undergraduate medical education: A narrative inquiry.

The field of pathology is facing an inflection point where the demand for pathology services is not being met by a corresponding rise in recruitment into the field. Many of the myths about the field of pathology have been dispelled elsewhere, but there have not been many formal accounts of the experience medical students' face when finding their path to pathology. Because of challenges in the visibility of pathology as a specialty and not simply a subject required for United States Medical Licensing Examination Step 1, students tend to fall into one of two categories: early differentiators or late discoverers.

Mapping the Single-cell Differentiation Landscape of Osteosarcoma.

The genetic and intratumoral heterogeneity observed in human osteosarcomas (OS) poses challenges for drug development and the study of cell fate, plasticity, and differentiation, processes linked to tumor grade, cell metastasis, and survival. To pinpoint errors in OS differentiation, we transcriptionally profiled 31,527 cells from a tissue-engineered model that directs MSCs toward adipogenic and osteoblastic fates. Incorporating pre-existing chondrocyte data, we applied trajectory analysis and non-negative matrix factorization (NMF) to generate the first human mesenchymal differentiation atlas.

Fundamentals of blood banking in anesthesiology: A problem-based learning simulation session as an addition to a novel curriculum of transfusion medicine education for anesthesiology residents.

We have previously published a novel transfusion medicine curriculum for first-year anesthesiology residents, making available open access learning materials. We now present a curriculum iteration, by incorporating resident feedback and developing an additional "capstone" session for use at the end of the rotation that integrates several learning points into a practical problem-based simulation. This iteration of the curriculum was piloted with the 2019-2020 PGY-1 anesthesiology residents of the University of Wisconsin Hospitals and Clinics.

Improved prediction of drug-induced liver injury literature using natural language processing and machine learning methods.

Drug-induced liver injury (DILI) is an adverse hepatic drug reaction that can potentially lead to life-threatening liver failure. Previously published work in the scientific literature on DILI has provided valuable insights for the understanding of hepatotoxicity as well as drug development. However, the manual search of scientific literature in PubMed is laborious and time-consuming.

Geometric graph neural networks on multi-omics data to predict cancer survival outcomes.

The advance of sequencing technologies has enabled a thorough molecular characterization of the genome in human cancers. To improve patient prognosis predictions and subsequent treatment strategies, it is imperative to develop advanced computational methods to analyze large-scale, high-dimensional genomic data. However, traditional machine learning methods face a challenge in handling the high-dimensional, low-sample size problem that is shown in most genomic data sets.

Predicting the germline dependence of hematuria risk in prostate cancer radiotherapy patients.

Background And Purpose: Late radiation-induced hematuria can develop in prostate cancer patients undergoing radiotherapy and can negatively impact the quality-of-life of survivors. If a genetic component of risk could be modeled, this could potentially be the basis for modifying treatment for high-risk patients. We therefore investigated whether a previously developed machine learning-based modeling method using genome-wide common single nucleotide polymorphisms (SNPs) can stratify patients in terms of the risk of radiation-induced hematuria.

Continuous positive airway pressure increases CSF flow and glymphatic transport.

Respiration can positively influence cerebrospinal fluid (CSF) flow in the brain, yet its effects on central nervous system (CNS) fluid homeostasis, including waste clearance function via glymphatic and meningeal lymphatic systems, remain unclear. Here, we investigated the effect of supporting respiratory function via continuous positive airway pressure (CPAP) on glymphatic-lymphatic function in spontaneously breathing anesthetized rodents. To do this, we used a systems approach combining engineering, MRI, computational fluid dynamics analysis, and physiological testing.

Functional transcriptional signatures for tumor-type-agnostic phenotype prediction.

Cancer transcriptional patterns exhibit both shared and unique features across diverse cancer types, but whether these patterns are sufficient to characterize the full breadth of tumor phenotype heterogeneity remains an open question. We hypothesized that cancer transcriptional diversity mirrors patterns in normal tissues optimized for distinct functional tasks. Starting with normal tissue transcriptomic profiles, we use non-negative matrix factorization to derive six distinct transcriptomic phenotypes, called archetypes, which combine to describe both normal tissue patterns and variations across a broad spectrum of malignancies.