An open annotated dataset and baseline machine learning model for segmentation of vertebrae with metastatic bone lesions from CT.

Automatic analysis of pathologic vertebrae from computed tomography (CT) scans could significantly improve the diagnostic management of patients with metastatic spine disease. We provide the first publicly available annotated imaging dataset of cancerous CT spines to help develop artificial intelligence frameworks for automatic vertebrae segmentation and classification. This collection contains a dataset of 55 CT scans collected on patients with various types of primary cancers at two different institutions.

Food Insufficiency Increased After The Expiration Of COVID-19 Emergency Allotments For SNAP Benefits In 2023.

In response to economic distress and food insecurity during the COVID-19 pandemic, Congress expanded the Supplemental Nutrition Assistance Program (SNAP) by introducing emergency allotments to increase monthly benefits, starting in March 2020. In March 2023, emergency allotments expired in the thirty-five states and territories still offering them. We provide some of the first evidence of the impacts of this loss of nutrition support-in some cases, more than $250 a month-for economically disadvantaged households.

Registration of Longitudinal Spine CTs for Monitoring Lesion Growth.

Accurate and reliable registration of longitudinal spine images is essential for assessment of disease progression and surgical outcome. Implementing a fully automatic and robust registration is crucial for clinical use, however, it is challenging due to substantial change in shape and appearance due to lesions. In this paper we present a novel method to automatically align longitudinal spine CTs and accurately assess lesion progression.

The intersection of TB and health financing: defining needs and opportunities.

TB is an airborne public health threat, so the reponse to TB has been defined mainly through the lens of vertical, public-sector national TB programs (NTPs). However, TB exists within a broader health systems and health financing context. Here, we examine the intersection between the particular needs of TB programs and the broader health financing landscape.

TractoSCR: a novel supervised contrastive regression framework for prediction of neurocognitive measures using multi-site harmonized diffusion MRI tractography.

Neuroimaging-based prediction of neurocognitive measures is valuable for studying how the brain's structure relates to cognitive function. However, the accuracy of prediction using popular linear regression models is relatively low. We propose a novel deep regression method, namely , that allows full supervision for contrastive learning in regression tasks using diffusion MRI tractography.

VESCL: an open source 2D vessel contouring library.

Purpose: VESCL (pronounced 'vessel') is a novel vessel contouring library for computer-assisted 2D vessel contouring and segmentation. VESCL facilitates manual vessel segmentation in 2D medical images to generate gold-standard datasets for training, testing, and validating automatic vessel segmentation.

Methods: VESCL is an open-source C++ library designed for easy integration into medical image processing systems.

ReMIND: The Brain Resection Multimodal Imaging Database.

The standard of care for brain tumors is maximal safe surgical resection. Neuronavigation augments the surgeon's ability to achieve this but loses validity as surgery progresses due to brain shift. Moreover, gliomas are often indistinguishable from surrounding healthy brain tissue.

Hyperspectral dark-field microscopy of human breast lumpectomy samples for tumor margin detection in breast-conserving surgery.

Significance: Hyperspectral dark-field microscopy (HSDFM) and data cube analysis algorithms demonstrate successful detection and classification of various tissue types, including carcinoma regions in human post-lumpectomy breast tissues excised during breast-conserving surgeries.

Aim: We expand the application of HSDFM to the classification of tissue types and tumor subtypes in pre-histopathology human breast lumpectomy samples.

Approach: Breast tissues excised during breast-conserving surgeries were imaged by the HSDFM and analyzed.

Surgical pulmonary arterioplasty at bidirectional cavopulmonary anastomosis leads to favorable pulmonary hemodynamics at final stage palliation.

Objective: Pulmonary arterioplasty (PA plasty) at bidirectional cavopulmonary anastomosis (BDCA) is associated with increased morbidity, but outcomes to final stage palliation are unknown. We sought to determine the influence of PA plasty on pulmonary artery growth and hemodyamics at Fontan.

Methods: We retrospectively reviewed clinical data and outcomes for BDCA patients from 2006 to 2018.

A Novel Model for Xenograft Right Ventricle to Pulmonary Artery Conduit.

The last 40 years have shown dramatic improvement in outcomes for neonatal cardiac surgery for a spectrum of congenital heart disease diagnoses. With more patients surviving into adulthood, the long-term impact of initial management strategies of these patients has come into focus. This is particularly true for patients with pediatric heart valve disease.

Unified Brain MR-Ultrasound Synthesis using Multi-Modal Hierarchical Representations.

We introduce MHVAE, a deep hierarchical variational autoencoder (VAE) that synthesizes missing images from various modalities. Extending multi-modal VAEs with a hierarchical latent structure, we introduce a probabilistic formulation for fusing multi-modal images in a common latent representation while having the flexibility to handle incomplete image sets as input. Moreover, adversarial learning is employed to generate sharper images.

Learning Expected Appearances for Intraoperative Registration during Neurosurgery.

We present a novel method for intraoperative patient-to-image registration by learning Expected Appearances. Our method uses preoperative imaging to synthesize patient-specific expected views through a surgical microscope for a predicted range of transformations. Our method estimates the camera pose by minimizing the dissimilarity between the intraoperative 2D view through the optical microscope and the synthesized expected texture.

Hepatic loss protects mice from non-alcoholic fatty liver disease through lipid metabolic rewiring.

Non-alcoholic fatty liver disease (NAFLD) is the most pervasive liver pathology worldwide. Here, we demonstrate that the ubiquitin E3 ligase Huwe1 is vital in NAFLD pathogenesis. Using mass spectrometry and RNA sequencing, we reveal that liver-specific deletion of Huwe1 () in 1-year-old mice (approximately middle age in humans) elicits extensive lipid metabolic reprogramming that involves downregulation of lipogenesis and fatty acid uptake, upregulation of fatty acid β-oxidation, and increased oxidative phosphorylation.

Anatomic considerations in the management of complete atrioventricular canal.

Objective: Patients with complete atrioventricular canal have a variable clinical course prior to repair. Many patients balance their circulations well prior to elective repair. Others manifest clinically significant pulmonary over circulation early in life and require either palliative pulmonary artery banding or complete repair.

Recommendations for centers performing pediatric heart surgery in the United States.

Care and outcomes for the more than 40,000 patients undergoing pediatric and congenital heart surgery in the United States annually are known to vary widely. While consensus recommendations have been published across numerous fields as one mechanism to promote a high level of care delivery across centers, it has been more than two decades since the last pediatric heart surgery recommendations were published in the United States. More recent guidance is lacking, and collaborative efforts involving the many disciplines engaged in caring for these children have not been undertaken to date.

Recommendations for Centers Performing Pediatric Heart Surgery in the United States.

Care and outcomes for the more than 40,000 patients undergoing pediatric and congenital heart surgery in the United States annually are known to vary widely. While consensus recommendations have been published across numerous fields as one mechanism to promote a high level of care delivery across centers, it has been more than two decades since the last pediatric heart surgery recommendations were published in the United States. More recent guidance is lacking, and collaborative efforts involving the many disciplines engaged in caring for these children have not been undertaken to date.

ReMIND: The Brain Resection Multimodal Imaging Database.

The standard of care for brain tumors is maximal safe surgical resection. Neuronavigation augments the surgeon's ability to achieve this but loses validity as surgery progresses due to brain shift. Moreover, gliomas are often indistinguishable from surrounding healthy brain tissue.

Recommendations for Centers Performing Pediatric Heart Surgery in the United States.

Care and outcomes for the more than 40,000 patients undergoing pediatric and congenital heart surgery in the United States annually are known to vary widely. While consensus recommendations have been published across numerous fields as one mechanism to promote a high level of care delivery across centers, it has been more than two decades since the last pediatric heart surgery recommendations were published in the United States. More recent guidance is lacking, and collaborative efforts involving the many disciplines engaged in caring for these children have not been undertaken to date.

The Cost-Effectiveness of the BEAT-TB Regimen for Pre-Extensively Drug-Resistant TB.

Objective: To measure the economic impacts of the longer pre-XDR-TB treatment regimen and the shorter BEAT-TB India regimen.

Methods: In the current study, the economic impacts of the current 18-month pre-XDR-TB treatment regimen and the 6-9 month BEAT-TB regimen were evaluated using an economic model via a decision tree analysis from a societal perspective. The incremental costs and quality-adjusted life years (QALYs) gained from the introduction of the BEAT-TB regimen for pre-XDR-TB patients were estimated.

PRAME expression in cutaneous melanoma does not correlate with disease-specific survival.

Background: Immunohistochemistry-based protein biomarkers can provide useful prognostic information in cutaneous melanoma. The independent prognostic value of Ki-67 has been studied with variable results. PReferentially expressed Antigen in MElanoma (PRAME) immunohistochemistry is a useful new ancillary tool for distinguishing cutaneous nevi from melanoma; however, its prognostic value has not been well studied.

Evaluating Receptor-Specific Fresh Specimen Staining for Tumor Margin Detection in Clinical Breast Specimens.

Purpose: Reliable and rapid identification of tumor in the margins of breast specimens during breast-conserving surgery to reduce repeat surgery rates is an active area of investigation. Dual-stain difference imaging (DDSI) is one of many approaches under evaluation for this application. This technique aims to topically apply fluorescent stain pairs (one targeted to a receptor-of-interest and the other a spectrally distinct isotype), image both stains, and compute a normalized difference image between the two channels.

Deep Learning for Detection and Localization of B-Lines in Lung Ultrasound.

Lung ultrasound (LUS) is an important imaging modality used by emergency physicians to assess pulmonary congestion at the patient bedside. B-line artifacts in LUS videos are key findings associated with pulmonary congestion. Not only can the interpretation of LUS be challenging for novice operators, but visual quantification of B-lines remains subject to observer variability.

Double-Uncertainty Guided Spatial and Temporal Consistency Regularization Weighting for Learning-based Abdominal Registration.

In order to tackle the difficulty associated with the ill-posed nature of the image registration problem, regularization is often used to constrain the solution space. For most learning-based registration approaches, the regularization usually has a fixed weight and only constrains the spatial transformation. Such convention has two limitations: (i) Besides the laborious grid search for the optimal fixed weight, the regularization strength of a specific image pair should be associated with the content of the images, thus the "one value fits all" training scheme is not ideal; (ii) Only spatially regularizing the transformation may neglect some informative clues related to the ill-posedness.

Comparison of pulmonary congestion severity using artificial intelligence-assisted scoring versus clinical experts: A secondary analysis of BLUSHED-AHF.

Aim: Acute decompensated heart failure (ADHF) is the leading cause of cardiovascular hospitalizations in the United States. Detecting B-lines through lung ultrasound (LUS) can enhance clinicians' prognostic and diagnostic capabilities. Artificial intelligence/machine learning (AI/ML)-based automated guidance systems may allow novice users to apply LUS to clinical care.