Differential cardiac impacts of hematological malignancies and solid tumors: a histopathological and biomarker study.

Background: Cancer patients are known to be associated with increased risk of cardiovascular disease. However, no studies have examined the differential impact of hematologic malignancies (HMs) and solid tumors (STs) on cardiac morphology at the tissue level.

Objective: We aimed to examine histopathological features alongside cardiovascular biomarkers in patients with HMs and STs who underwent post-mortem evaluation.

Lightweight preprocessing and template matching facilitate streamlined ischemic myocardial scar classification.

Purpose: Ischemic myocardial scarring (IMS) is a common outcome of coronary artery disease that potentially leads to lethal arrythmias and heart failure. Late-gadolinium-enhanced cardiac magnetic resonance (CMR) imaging scans have served as the diagnostic bedrock for IMS, with recent advancements in machine learning enabling enhanced scar classification. However, the trade-off for these improvements is intensive computational and time demands.

iPad Annotation of 3D Surgical Models Using Procreate®: Novel Documentation of Supplemental Margins.

We present a novel, efficient approach to demonstrating supplemental margins during oncologic resection. Surgeons and pathologists annotated 10 virtual models of surgical defects and resection specimens in 3D using an iPad-based application, Procreate®. Incorporating this method into the surgical workflow can improve interdepartmental communication and provide visual documentation of surgical steps taken to address at-risk margins.

Functional loss of tumor suppressor genes detected by loss of heterozygosity, but not driver mutations, predicts aggressive lymph node status in papillary thyroid carcinoma.

Background: Recognizing aggressive tumor biology is essential to optimizing patient management for papillary thyroid carcinomas (PTC). Aggressive lymph node (ALN) status is one feature that influences decision-making. We evaluated genomic deletions in regions of tumor suppressor genes, detected by loss of heterozygosity (LOH) analysis, to understand causal alterations linked to thyroid cancer aggressiveness and to serve as a molecular diagnostic biomarker for ALN status.

Intraoperative three-dimensional scanning of head and neck surgical defects: Enhanced communication and documentation of harvested supplemental margins.

Background: We have demonstrated the effectiveness of 3D resection specimen scanning for communicating margin results. We now address the corresponding surgical defect by debuting 3D defect models, which allow for accurate annotations of harvested supplemental margins.

Methods: Surgical defects were rendered into 3D models, which were annotated to document the precise location of harvested supplemental margins.

Frozen Section Timeout: Pilot Study to Reconcile Margins Using 3D Resected Specimen and Defect Scans.

Objective: Opportunities exist to improve intraoperative communication and documentation of resection margin details. We instituted a "frozen section timeout" that centers around visualization of the paired resection specimen and surgical defect-facilitating effective, bidirectional exchange of information.

Methods: We designed an interactive form for use during the "frozen section timeout" including annotated 3D virtual models of the resected specimen and surgical defect, plus a "line-item" table for primary and supplemental margin results.

Pelvic Floor Pressures Differ Based on Location in the Pelvis and Body Position: A Cadaver Mode.

Background: The pelvic floor is a bowl-shaped complex of multiple muscles and fascia, which functions to support the pelvic organs, and it aids in controlling continence. In pelvic floor disease, this complex becomes weakened or damaged leading to urinary, fecal incontinence, and pelvic organ prolapse. It is unclear whether the position of the body impacts the forces on the pelvic floor.

The role of anatomical context in soft-tissue multi-organ segmentation of cadaveric non-contrast-enhanced whole body CT.

Background: Cadaveric computed tomography (CT) image segmentation is a difficult task to solve, especially when applied to whole-body image volumes. Traditional algorithms require preprocessing using registration, or highly conserved organ morphologies. These requirements cannot be fulfilled by cadaveric specimens, so deep learning must be used to overcome this limitation.

Advancing Osteoporosis Evaluation Procedures: Detailed Computational Analysis of Regional Structural Vulnerabilities in Osteoporotic Bone.

Osteoporotic fractures of the femur are associated with poor healing, disability, reduced quality of life, and high mortality rates within 1 year. Moreover, osteoporotic fractures of the femur are still considered to be an unsolved problem in orthopedic surgery. In order to more effectively identify osteoporosis-related fracture risk and develop advanced treatment approaches for femur fractures, it is necessary to acquire a greater understanding of how osteoporosis alters the diaphyseal structure and biomechanical characteristics.

Developing Patient-Specific Statistical Reconstructions of Healthy Anatomical Structures to Improve Patient Outcomes.

There are still numerous problems with modern joint replacement prostheses, which negatively influence patient health and recovery. For example, it is especially important to avoid failures and complications following hip arthroplasty because the loss of hip joint function is commonly associated with increased demand on the healthcare system, reoperation, loss of independence, physical disability, and death. The current study uses hip arthroplasty as a model system to present a new strategy of computationally generating patient-specific statistical reconstructions of complete healthy anatomical structures from computed tomography (CT) scans of damaged anatomical structures.

Histology segmentation using active learning on regions of interest in oral cavity squamous cell carcinoma.

In digital pathology, deep learning has been shown to have a wide range of applications, from cancer grading to segmenting structures like glomeruli. One of the main hurdles for digital pathology to be truly effective is the size of the dataset needed for generalization to address the spectrum of possible morphologies. Small datasets limit classifiers' ability to generalize.

Tall cell variant papillary thyroid carcinoma impacts disease-free survival at the 10 % cut-point on multivariate analysis.

Introduction: The diagnosis of tall cell variant papillary thyroid carcinoma (TCV-PTC) corresponds to the feature of "aggressive histology" within the framework of the American Thyroid Association (ATA) Risk of Recurrence (ROR) guidelines. Using the current World Health Organization (WHO) definition for TCV-PTC (tall cells with height at least twice the width, distribution ≥ 30 %), we examined the impact of this diagnosis on disease-free survival (DFS).

Methods: The study cohort consisted of 347 patients treated for primary papillary thyroid carcinoma (PTC).

Enhancing biomedical data validity with standardized segmentation finite element analysis.

Finite element analysis is a powerful computational technique for augmenting biomedical research, prosthetics design, and preoperative surgical assessment. However, the validity of biomechanical data obtained from finite element analysis is dependent on the quality of the preceding data processing. Until now, little information was available about the effect of the segmentation process on finite element models and biomechanical data.

miR-486 is essential for muscle function and suppresses a dystrophic transcriptome.

miR-486 is a muscle-enriched microRNA, or "myomiR," that has reduced expression correlated with Duchenne muscular dystrophy (DMD). To determine the function of miR-486 in normal and dystrophin-deficient muscles and elucidate miR-486 target transcripts in skeletal muscle, we characterized knockout mice ( KO). KO mice developed disrupted myofiber architecture, decreased myofiber size, decreased locomotor activity, increased cardiac fibrosis, and metabolic defects were exacerbated in KO: (DKO) mice.

Sleep and occupational well-being in active duty special operations soldiers: A replication and expansion.

Objective: To assess the relationship between sleep quality and occupational well-being in active duty military Service Members.

Design: Longitudinal prospective analysis.

Setting: An annual military training event.

Prevalence of Eosinophilic Granulomatosis With Polyangiitis and Associated Health Care Utilization Among Patients With Concomitant Asthma in US Commercial Claims Database.

Objective: To estimate the prevalence and associated disease burden of eosinophilic granulomatosis with polyangiitis (EGPA) in patients with asthma from a US claims database.

Methods: Two cohorts were defined using enrollees (aged ≥18 years) from the Optum deidentified Clinformatics Datamart claims database 2010-2014, based on validated EGPA case definitions with varying specificity: EGPA 1 (main cohort; more specific; patients with 2 codes [in any combination] within 12 months of each other for eosinophilia, vasculitis, or mononeuritis multiplex) and EGPA 2 (sensitivity analysis cohort; less specific; patients with 2 codes of above conditions and/or neurologic symptoms within 12 months of each other). Patients had 3 or more asthma medications in the 12-month baseline before index date (date of the second code).

Extraskeletal Osteochondroma of the Great Toe in a Teenager.

Osteochondromas are common, benign surface tumors of bone, composed of the cartilage-capped bone confluent with the medullary canal of the metaphyseal bone. Extraskeletal osteochondromas have the same gross appearance and histologic characteristics as a typical osteochondroma but do not have any boney attachment to the surrounding osseous structures. They are rare and most frequently reported in the middle-age and older adults.

Disrupting the spatio-temporal symmetry of the electron dynamics in atmospheric pressure plasmas by voltage waveform tailoring.

Single frequency, geometrically symmetric Radio-Frequency (rf) driven atmospheric pressure plasmas exhibit temporally and spatially symmetric patterns of electron heating, and consequently, charged particle densities and fluxes. Using a combination of phase-resolved optical emission spectroscopy and kinetic plasma simulations, we demonstrate that tailored voltage waveforms consisting of multiple rf harmonics induce targeted disruption of these symmetries. This confines the electron heating to small regions of time and space and enables the electron energy distribution function to be tailored.

Anti-IL-5 treatments in patients with severe asthma by blood eosinophil thresholds: Indirect treatment comparison.

Background: Three anti-IL-5 pathway-directed therapies are approved for use in patients with severe eosinophilic asthma (SEA); however, no head-to-head comparison data are available.

Objective: We sought to compare the efficacy of licensed doses of mepolizumab, benralizumab, and reslizumab in patients with SEA, according to baseline blood eosinophil counts.

Methods: This indirect treatment comparison (ITC) used data from a Cochrane review and independent searches.

Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer.

Background: Gene-expression companion diagnostic tests, such as the Oncotype DX test, assess the risk of early stage Estrogen receptor (ER) positive (+) breast cancers, and guide clinicians in the decision of whether or not to use chemotherapy. However, these tests are typically expensive, time consuming, and tissue-destructive.

Methods: In this paper, we evaluate the ability of computer-extracted nuclear morphology features from routine hematoxylin and eosin (H&E) stained images of 178 early stage ER+ breast cancer patients to predict corresponding risk categories derived using the Oncotype DX test.

A resolution adaptive deep hierarchical (RADHicaL) learning scheme applied to nuclear segmentation of digital pathology images.

Deep learning (DL) has recently been successfully applied to a number of image analysis problems. However, DL approaches tend to be inefficient for segmentation on large image data, such as high-resolution digital pathology slide images. For example, typical breast biopsy images scanned at 40× magnification contain billions of pixels, of which usually only a small percentage belong to the class of interest.

Developing the Quantitative Histopathology Image Ontology (QHIO): A case study using the hot spot detection problem.

Interoperability across data sets is a key challenge for quantitative histopathological imaging. There is a need for an ontology that can support effective merging of pathological image data with associated clinical and demographic data. To foster organized, cross-disciplinary, information-driven collaborations in the pathological imaging field, we propose to develop an ontology to represent imaging data and methods used in pathological imaging and analysis, and call it Quantitative Histopathological Imaging Ontology - QHIO.

Mentor's brain functional connectivity network during robotic assisted surgery mentorship.

In many complicated cognitive-motor tasks mentoring is inevitable during the learning process. Although mentors are expert in doing the task, trainee's operation might be new for a mentor. This makes mentoring a very difficult task which demands not only the knowledge and experience of a mentor, but also his/her ability to follow trainee's movements and patiently advise him/her during the operation.

Avascular Necrosis of Trochlea After Supracondylar Humerus Fractures in Children.

Avascular necrosis (AVN) is a rare but important complication after supracondylar humerus fractures. Posttraumatic humerus deformity was first reported in 1948 and sporadically thereafter. AVN deformity has been classified as type A (AVN of the lateral ossification center) and type B (AVN of the entire medial crista and a metaphyseal portion).

Content-based image retrieval of digitized histopathology in boosted spectrally embedded spaces.

Context: Content-based image retrieval (CBIR) systems allow for retrieval of images from within a database that are similar in visual content to a query image. This is useful for digital pathology, where text-based descriptors alone might be inadequate to accurately describe image content. By representing images via a set of quantitative image descriptors, the similarity between a query image with respect to archived, annotated images in a database can be computed and the most similar images retrieved.