Radiology

Role of Low-Field Magnetic Resonance Imaging in the Lungs: Opportunities and Challenges.

Clinical utilization of lung MRI has not kept pace with MRI of other body regions. This is due to a combination of technical and perceptual factors related to lung imaging. With increasing access to and application of low-field MRI, there are unique opportunities for lung imaging. This review will first explain the role of conventional lung MRI, next delineate the opportunities afforded by low-fie...

DSHARP: Deep Incompressible Motion Estimation with Sinusoidal-transformed Harmonic Phase for Tagged MRI.

Tagged magnetic resonance imaging (tMRI) is a valuable tool for visualizing and quantifying tissue deformation in vivo. Its use is often hampered, however, by tag fading, long computation times, and the challenge of ensuring diffeomorphic, incompressible motion fields. In this paper, we describe a novel integration of the harmonic phase (HARP) approach to tMRI analysis with an unsupervised deep le...

Toward protocol simplification: Deep learning-based image synthesis in three-phase CT urography.

OBJECTIVE: The purpose of this study was to develop and evaluate a method for synthesizing 3D urothelial phase images in CTU examinations from the dua...

Image-derived input functions for [18F]LW223 and [18F]SynVesT-1 PET in the rodent determined using an autoencoder (IDIF-AE).

Objective.Quantitative analysis of dynamic positron emission tomography (PET) scans requires knowledge of the arterial input function (AIF). Existing ...

Influence of scintillation light confinement on depth-of-interaction measurement performance in a single-Ended readout PET detector.

Continuous depth-of-interaction (cDOI) detectors enable single-ended readout in positron emission tomography (PET) by encoding the interaction depth i...

Machine Learning Integration of Ultrasound Habitat Radiomics for Predicting Axillary Metastasis in Clinically Node-negative Triple-negative Breast Cancer.

OBJECTIVE: To develop and validate habitat radiomics as a biomarker for predicting axillary lymph node metastasis (ALNM) in clinically node-negative (...

Adaptive patch sampling and location-aware reasoning for whole body PET-CT multi-organ segmentation.

Patch-wise learning is a common strategy for training neural networks on large-scale dense prediction problems, yet existing approaches assume uniform...

NucVerse3D: generalizable 3D nuclear instance segmentation across heterogeneous microscopy modalities.

Accurate three-dimensional (3D) nuclear instance segmentation is a prerequisite for quantitative phenotyping in volumetric microscopy, yet remains cha...

Artificial intelligence iterative imaging reconstruction with low-dose CT scans for hepatic metastases.

Contrast-enhanced CT is commonly used in the evaluation of hepatic metastatic lesions. This prospective study aimed to assess the capability of artifi...

Osteoarthritis phenotypes: advancing precision medicine through clinical, structural, and molecular stratification.

PURPOSE: Osteoarthritis (OA) is now understood as a heterogeneous syndrome driven by diverse biological, biomechanical, metabolic, genetic, and molecu...

Interpretable machine learning model integrating MRI-derived paraspinal muscle parameters for predicting new vertebral compression fractures after vertebral augmentation.

OBJECTIVES: To develop and validate interpretable machine learning (ML) models incorporating MRI-derived paraspinal muscle parameters to predict new v...

MRI- and report-based multimodal model with SHAP-based explanation for preoperative prediction of deep stromal invasion in early-stage cervical cancer.

OBJECTIVES: Depth of stromal invasion (DSI) is a key prognostic factor significantly influencing treatment decisions in early-stage cervical cancer (E...

Digital Twins as the Implementation Layer of Precision Medicine in Pediatric Neurosurgery.

Pediatric neurosurgery increasingly utilizes precision medicine, but practitioners encounter challenges in translating complex data into individualize...

Distinct 3-Dimensional Anatomic Patterns Including Flatter Surfaces and Greater Sagittal Inclinations of Intra-articular Structures Are Reliably Identified Through an Artificial Intelligence-Based Pipeline in Anterior Cruciate Ligament-Injured Knees.

PURPOSE: To evaluate whether an automated AI-based pipeline can identify 3-dimensional (3D) anatomic patterns associated with anterior cruciate ligame...

Machine Learning Models of Phase Contrast Images Predict Efficiency of Human Pluripotent Stem Cell Differentiation to Cardiomyocytes.

Terminal cell types derived from human pluripotent stem cells (hPSCs) are at the forefront of emerging cell and gene therapy products. hPSC-derived ca...

GRACE-MORE: A Motion-Resolved Golden-Angle Radial CEST MRI Technique for Free-Breathing Abdominal Imaging.

PURPOSE: To develop a motion-resolved acquisition and reconstruction framework for motion-robust and spectrally reliable abdominal CEST imaging under ...

Development and Validation of a Diffusion-weighted Imaging-only Deep Learning Model for the Detection of Supratentorial Acute Ischemic Infarcts: A Retrospective Diagnostic Accuracy Study.

BACKGROUND: Acute ischemic stroke is a leading cause of death and long-term disability worldwide, with a disproportionately increasing burden in low- ...

Efficacy of short-course bevacizumab for brain tumor radiation necrosis with a volumetric analysis.

PURPOSE: Radiation necrosis (RN) is a challenging complication of cranial irradiation, often requiring corticosteroids for management. This study eval...

Diagnostic value of cytokine detection in children with Mycoplasma pneumoniae pneumonia complicated by bacterial or viral co-infections.

BACKGROUND: To evaluate the diagnostic value of cytokine levels in paediatric patients with Mycoplasma pneumoniae pneumonia (MPP) complicated by bacte...

The role of MRCP in characterizing ductal communication and high-risk features in pancreatic cystic lesions.

Pancreatic cystic lesions are increasingly detected due to the widespread use of high-resolution cross-sectional imaging, particularly MRI and CT. The...