Radiology

Response to letter to editor "Radiomics-based machine-learning approach to predict response at brachytherapy using pretreatment magnetic resonance imaging in locally advanced cervical cancer".

Enhanced MRI brain tumor segmentation with DNet and hybrid dice-weighted cross-entropy loss.

Localization of brain tumors via magnetic resonance imaging (MRI) is critically important for diagnosis, treatment, and surgical operations. This study proposes DNet, an optimized and highly efficient deep learning framework for the automatic detection and segmentation of brain tumors from MR images. On the basis of the classical UNet structure, DNet reduces the risk of overfitting by balancing th...

Comparative effectiveness of arthroscopic-assisted uniportal surgery versus percutaneous endoscopic decompression in lumbar spinal stenosis.

Single-level lumbar spinal stenosis (LSS) that does not respond to conservative therapy is now of the standard care given due to minimal invasive deco...

Large-scale multi-sequence pretraining for generalizable MRI analysis in versatile clinical applications.

Multi-sequence magnetic resonance imaging (MRI) is essential for clinical diagnosis because it enables comprehensive characterization of complex anato...

DensiThAI: A Multi-View Deep Learning Framework for Breast Density Estimation Using Infrared Images.

Breast tissue density is an established biomarker of breast cancer risk and an important determinant of mammographic sensitivity. Density assessment i...

Automated Deep Learning Segmentation and Quantification of Epicardial Adipose Tissue from Coronary Computed Tomography Angiography: Validation and Clinical Implications.

Epicardial adipose tissue (EAT) sits directly on the heart and, in excess, has been linked to coronary artery disease and adverse cardiac events. Meas...

Predicting the seed microbiome using phylogeny-driven machine learning.

BACKGROUND: The composition of the seed-associated bacterial microbiome can reflect host evolutionary relationships, a pattern consistent with phylosy...

A scoping review on emerging biomarkers in inflammatory bowel disease: Towards precision medicine in diagnosis and therapeutic management.

BACKGROUND: Inflammatory Bowel Diseases (IBD) are chronic conditions presenting significant diagnostic and management challenges. Current invasive met...

Evaluation of deep learning-based reconstruction models on non-TOF BGO PET/CT: impact of acquisition times and BSREM penalization factors on lesion detectability and SNR.

BACKGROUND: New long field-of-view (FOV) PET scanners using bismuth germanate (BGO) detectors without time-of-flight (TOF) capability are now availabl...

Multi-modal Features Analysis and Performance Assessment for Endovascular Surgery Skills.

PURPOSE: Interventional skill and assessment are essential for vascular interventionalists prior to performing clinical procedures. However, tradition...

FUO-PETMamba: a pet maximum-intensity-projection-based artificial intelligence framework for aetiological classification of fever of unknown origin with multicentre validation.

BACKGROUND: Fever of unknown origin (FUO) remains diagnostically challenging because of heterogeneous causes, non-specific clinical manifestations, an...

White Matter Perivascular Space Burden in Children With Autism Spectrum Disorder and Typically Developing Controls: An Automated Quantitative MRI Study.

BACKGROUND: Perivascular spaces (PVS) are compartments involved in brain waste clearance. PVS are commonly observed in typically developing (TD) child...

Pretreatment multiparametric MRI-based habitat radiomics and 2.5D deep learning for predicting early complete response to induction chemoimmunotherapy in locally advanced nasopharyngeal carcinoma.

OBJECTIVE: To develop and externally validate a pretreatment multiparametric MRI-based combined imaging model integrating conventional radiomics, habi...

Application Effectiveness Analysis of Artificial Intelligence-assisted Teaching in Standardized Training for Medical Imaging Residents.

RATIONALE AND OBJECTIVES: This study evaluated the efficacy of a combined artificial intelligence (AI)-assisted and traditional teaching model in enha...

Development and multicohort external validation of a preoperative [18F]PSMA-1007 PET-derived deep learning score and multimodal model for predicting biochemical recurrence-free survival after radical prostatectomy.

PURPOSE: To develop and validate a preoperative [18F]PSMA-1007 PET-derived deep learning score (DLS) and an integrated model combining DLS, D'Amico ri...

Deep learning-based malignancy probability estimation of pulmonary nodules in PET/CT imaging.

OBJECTIVE: The current BTS guidelines recommend evaluation of suspicious pulmonary nodules using [18F]FDG-PET/CT imaging, followed by Herder model ris...

3D and 4D Free-Breathing Abdominal T1-Weighted MRI in Clinical Practice Using Deep Learning Auto-Navigation and Reconstruction.

PURPOSE: To develop and evaluate an automated clinical prototype for a 1-min free-breathing T1-weighted 3D MRI and a 2.25-min 4D MRI utilizing radial ...

Comparison of radiomics handcrafted features and deep features in 18F-FDG PET/CT for differentiating benign and malignant persistent pulmonary ground-glass nodules.

BACKGROUND: The differentiation between benign and malignant persistent pulmonary ground-glass nodules (GGNs) remains challenging, and the relative va...

RadiolGAN: Multicenter Feasibility Study of Synthetic CT From 3D Ultra-Short Echo Time MRI for Enhanced Pulmonary Radiologic Sign Visualization.

BACKGROUND: Chest CT requires breath-holding and ionizing radiation. 3D ultrashort echo time (UTE) MRI allows radiation-free imaging, but the image qu...

Quantitative Investigation of Tibiofemoral Cartilage Early Degeneration After ACL Reconstruction: An Integrated Biomechanical and Longitudinal MRI Analysis.

BACKGROUND: Anterior cruciate ligament reconstruction (ACLR) restores stability but is often followed by early cartilage degeneration. The contributio...