Current State of Community-Driven Radiological AI Deployment in Medical Imaging.

Artificial intelligence (AI) has become commonplace in solving routine everyday tasks. Because of the exponential growth in medical imaging data volume and complexity, the workload on radiologists is steadily increasing. AI has been shown to improve efficiency in medical image generation, processing, and interpretation, and various such AI models have been developed across research laboratories worldwide.

Setting Up the JBrowse 2 Genome Browser.

JBrowse 2 is a modular genome browser that can visualize many common genomic file formats. While JBrowse 2 supports a variety of different usages, it is particularly suited for deployment on websites, such as model organism databases or other web-based genomic data resources. This protocol provides detailed instructions for setting up JBrowse 2 on an Ubuntu Linux web server, loading a reference genome from a FASTA format file, and adding a gene annotation track from a GFF3 format file.

Diffusion tensor transformation for personalizing target volumes in radiation therapy.

Diffusion tensor imaging (DTI) is used in tumor growth models to provide information on the infiltration pathways of tumor cells into the surrounding brain tissue. When a patient-specific DTI is not available, a template image such as a DTI atlas can be transformed to the patient anatomy using image registration. This study investigates a model, the invariance under coordinate transform (ICT), that transforms diffusion tensors from a template image to the patient image, based on the principle that the tumor growth process can be mapped, at any point in time, between the images using the same transformation function that we use to map the anatomy.

Integrating muscle fiber orientation from visible human data into radiotherapy target volumes.

A major challenge in treatment of tumors near skeletal muscle is defining the target volume for suspected tumor invasion into the muscle. This study develops a framework that generates radiation target volumes with muscle fiber orientation directly integrated into their definition. The framework is applied to nineteen sacral tumor patients with suspected infiltration into surrounding muscles.

Warm-up music and low-dose caffeine enhance the activity profile and psychophysiological responses during simulated combat in female taekwondo athletes.

To assess the effects of warm-up music and low dose (3 mg·kg) of caffeine (CAF) on female taekwondo athlete's activity profile and psychophysiological responses during simulated combat. In a double-blinded, randomized, crossover study, 16 female athletes participated in simulated combats under one control and 5 experimental conditions [i.e.

CASCADE: Context-Aware Data-Driven AI for Streamlined Multidisciplinary Tumor Board Recommendations in Oncology.

This study addresses the potential of machine learning in predicting treatment recommendations for patients with hepatocellular carcinoma (HCC). Using an IRB-approved retrospective study of patients discussed at a multidisciplinary tumor board, clinical and imaging variables were extracted and used in a gradient-boosting machine learning algorithm, XGBoost. The algorithm's performance was assessed using confusion matrix metrics and the area under the Receiver Operating Characteristics (ROC) curve.

No code machine learning: validating the approach on use-case for classifying clavicle fractures.

Purpose: We created an infrastructure for no code machine learning (NML) platform for non-programming physicians to create NML model. We tested the platform by creating an NML model for classifying radiographs for the presence and absence of clavicle fractures.

Methods: Our IRB-approved retrospective study included 4135 clavicle radiographs from 2039 patients (mean age 52 ± 20 years, F:M 1022:1017) from 13 hospitals.

Noble Gas Analyses to Distinguish Between Surface and Subsurface Brine Releases at a Legacy Oil Site.

Attributing the sources of legacy contamination, including brines, is important to determine remediation options and to allocate responsibility. To make sound remediation decisions, it is necessary to distinguish subsurface sources, such as leaking oil and gas ("O&G") wells or natural upward fluid migrations, from surface releases. While chemical signatures of surface and subsurface releases may be similar, they are expected to imprint specific dissolved noble gas signatures, caused by the accumulation of terrigenic noble gases in subsurface leaks or re-equilibration of noble gases following surface releases.

Post-Activation Performance Enhancement of Punch Force and Neuromuscular Performance in Amateur Boxing: Toward a More Individualized and "Real-World" Approach.

Finlay, MJ, Greig, M, Bridge, CA, and Page, RM. Post-activation performance enhancement of punch force and neuromuscular performance in amateur boxing: Toward a more individualized and "real-world" approach. J Strength Cond Res 38(6): 1063-1071, 2024-Previous research on post-activation performance enhancement has been applied in several sporting settings, although this is lacking in a boxing setting.

From Machine Learning to Patient Outcomes: A Comprehensive Review of AI in Pancreatic Cancer.

Pancreatic cancer is a highly aggressive and difficult-to-detect cancer with a poor prognosis. Late diagnosis is common due to a lack of early symptoms, specific markers, and the challenging location of the pancreas. Imaging technologies have improved diagnosis, but there is still room for improvement in standardizing guidelines.

Expert-centered Evaluation of Deep Learning Algorithms for Brain Tumor Segmentation.

Purpose To present results from a literature survey on practices in deep learning segmentation algorithm evaluation and perform a study on expert quality perception of brain tumor segmentation. Materials and Methods A total of 180 articles reporting on brain tumor segmentation algorithms were surveyed for the reported quality evaluation. Additionally, ratings of segmentation quality on a four-point scale were collected from medical professionals for 60 brain tumor segmentation cases.

Enrichment of lung cancer computed tomography collections with AI-derived annotations.

Public imaging datasets are critical for the development and evaluation of automated tools in cancer imaging. Unfortunately, many do not include annotations or image-derived features, complicating downstream analysis. Artificial intelligence-based annotation tools have been shown to achieve acceptable performance and can be used to automatically annotate large datasets.

The influence of anisotropy on the clinical target volume of brain tumor patients.

Current radiotherapy guidelines for glioma target volume definition recommend a uniform margin expansion from the gross tumor volume (GTV) to the clinical target volume (CTV), assuming uniform infiltration in the invaded brain tissue. However, glioma cells migrate preferentially along white matter tracts, suggesting that white matter directionality should be considered in an anisotropic CTV expansion. We investigate two models of anisotropic CTV expansion and evaluate their clinical feasibility.

National Cancer Institute Imaging Data Commons: Toward Transparency, Reproducibility, and Scalability in Imaging Artificial Intelligence.

The remarkable advances of artificial intelligence (AI) technology are revolutionizing established approaches to the acquisition, interpretation, and analysis of biomedical imaging data. Development, validation, and continuous refinement of AI tools requires easy access to large high-quality annotated datasets, which are both representative and diverse. The National Cancer Institute (NCI) Imaging Data Commons (IDC) hosts large and diverse publicly available cancer image data collections.

Not without Context-A Multiple Methods Study on Evaluation and Correction of Automated Brain Tumor Segmentations by Experts.

Rationale And Objectives: Brain tumor segmentations are integral to the clinical management of patients with glioblastoma, the deadliest primary brain tumor in adults. The manual delineation of tumors is time-consuming and highly provider-dependent. These two problems must be addressed by introducing automated, deep-learning-based segmentation tools.

Point-of-care AI-assisted stepwise ultrasound pneumothorax diagnosis.

. Ultrasound is extensively utilized as a convenient and cost-effective method in emergency situations. Unfortunately, the limited availability of skilled clinicians in emergency hinders the wider adoption of point-of-care ultrasound.

Test-retest reliability and sensitivity of senior elite amateur boxers maximal punch force, as quantified by a vertically mounted force plate.

An ecologically valid, reliable and sensitive method of quantifying punch force variables would be useful for coaches and practitioners monitoring combat-specific performance. The present study utilised a vertically mounted force plate to quantify the peak punch force and rate of force development (RFD) of amateur boxers. Ten male senior elite amateur boxers performed maximal jab, cross, and hook punches across two separate days.