Radiology

Reinforcement learning for real-time adaptive radiotherapy.

State-of-the-art radiotherapy machines with integrated magnetic resonance (MR) imaging, known as MR-Linacs, provide the capability to track tumors in real time. This capability aids delivery of precise irradiation in the presence of patient motion, such as breathing, by adjusting the radiation beam. However, current solutions rely solely on geometric tracking without closing the loop by considerin...

Practical Integration of Bedside Real-Time Lung Ultrasound and Electrical Impedance Tomography for Guiding Personalized Perioperative Lung Protective Ventilation in Cardiothoracic and Vascular Anesthesia.

Patients undergoing cardiothoracic and vascular surgery are at uniquely high risk for postoperative pulmonary complications due to the confluence of surgical trauma, one-lung ventilation, cardiopulmonary bypass, and sternotomy. This review evaluates the critical role of real-time bedside imaging-specifically lung ultrasound and electrical impedance tomography-in transitioning from empirical, fixed...

Bridging the Scales via Personalized Cellular Modeling and Deep Phenotyping in Schizophrenia.

IMPORTANCE: While growing evidence implicates synaptic dysfunction as a key pathophysiological mechanism in cognitive impairments in schizophrenia (SC...

Fast 3D whole-body occupational dose estimation in interventional radiology using physics-informed deep learning.

Occupational radiation exposure in interventional radiology is spatially heterogeneous and inadequately captured by conventional point-based dosimetry...

Investigating Phase Separation in Genome Folding via Multiscale Computational Modeling.

The 3D organization of the genome is central to gene regulation, and phase separation has emerged as an important physical principle for this architec...

Deep transfer learning radiomics combined with explainable machine learning for predicting malignancy risk in parotid gland tumors based on ultrasound.

OBJECTIVE: This study aimed to develop and validate an ultrasound (US)-based deep transfer learning radiomics model, integrated with explainable machi...

Emerging perspectives in cardiovascular medicine.

Cardiovascular medicine continues to evolve rapidly through advances in molecular biology, biomarkers, digital technologies, and interventional strate...

ACCURACY AND GENERALIZABILITY OF AN OPEN-SOURCE DEEP LEARNING MODEL FOR FACIAL BONE SEGMENTATION ON CT AND CBCT SCANS: AN EX VIVO STUDY.

AIM: To evaluate the accuracy and generalizability of DentalSegmentator, an open-source deep learning tool, for automated reconstruction of facial ske...

Dental Odontogenic Lesion CBCT and Histopathology Integrated Dataset for Benchmarking Deep Learning Algorithms.

Accurate diagnosis of odontogenic lesions requires pre-operative cone-beam computed tomography (CBCT) and post-operative histopathological confirmatio...

Personalized mapping of body homeostasis using whole-body PET connectomics and routine FDG PET imaging.

BACKGROUND: Immuno-inflammation and systemic alterations are key features of chronic diseases. While PET molecular imaging is widely used in precision...

Simulation of prosthetic vision with the PRIMA system and enhancement of face representation.

OBJECTIVE: Patients implanted with the PRIMA photovoltaic subretinal prosthesis in geographic atrophy report form vision with the average acuity match...

Accelerated Brain Aging in Young Women with Posttraumatic Stress Disorder.

Posttraumatic stress disorder (PTSD) has been associated with structural brain alterations, suggesting accelerated brain aging. Evidence from peripher...

Artificial Intelligence for Colorectal Surgeons - Part I: Foundations, Clinical and Educational Applications.

BACKGROUND: Artificial intelligence (AI) is rapidly transforming colorectal surgery through applications spanning screening to postoperative care. Thi...

Benchmarking Hybrid CNN-Transformer Versus Pure Transformer Architectures for Accelerated Hyperpolarized 129Xe MRI Reconstruction.

BACKGROUND: Hyperpolarized 129Xe MRI faces technical challenges including low signal-to-noise ratio and breath-hold constraints. Current literature fo...

Incremental Prognostic Value of Pericardial Adipose Tissue Radiomic Phenotype Based on Cardiac MRI in Patients With End-Stage Renal Disease.

BACKGROUND: While pericardial adipose tissue (PEAT) volume is linked to cardiac risk, the prognostic value of its radiomic features for major adverse ...

Necessary conditions for valid causal inference from observational data.

Observational studies often guide policy, regulation, litigation, and public health decisions. However, causal claims from such studies can be mislead...

Artificial intelligence and radiomics for pediatric brain tumor classification and molecular characterization: a systematic review.

BACKGROUND: Artificial intelligence (AI) and radiomics are increasingly applied in pediatric neuroradiology to enhance diagnostic precision. However, ...

The Deep Learning Revolution in Neuroimaging: Insights from a Bibliometric Analysis (2014-2024).

This paper presents a bibliometric analysis of the fast-growing area of deep learning in neuroimaging. Using data from the Scopus database, we analyze...

Visual question answering-based image-finding generation for pulmonary nodules on chest CT from structured annotations.

PURPOSE: Interpretation of imaging findings based on morphological characteristics is important for diagnosing pulmonary nodules on chest computed tom...

Measuring the Impact of AI on Report-Drafting Efficiency in Chest Computed Tomography Interpretation: Retrospective Analysis.

BACKGROUND: Artificial intelligence (AI), particularly deep learning, has shown promise in enhancing medical image interpretation and improving radiol...