Radiology

Deep learning-based segmentation and quantification of pulmonary masses on apparent diffusion coefficient maps: a multicentre reproducibility study.

OBJECTIVES: To develop and validate a deep learning model for automatic segmentation of pulmonary masses on apparent diffusion coefficient (ADC) maps and to assess repeatability of automated ADC quantification. METHODS: We proposed ADCSegNet, a deep learning model tailored to pulmonary ADC maps, trained and tested on ADC maps from centre 1 (303 MRI examinations) and externally evaluated on dataset...

MRI-based machine learning model to distinguish hippocampal sclerosis (HS) ILAE type 1 and no HS gliosis only in medial temporal lobe epilepsy.

PURPOSE: Despite recent advances in preoperative work-up of drug resistant medial temporal lobe epilepsy (MTLE), predicting post-surgical seizure and memory outcomes remains challenging. Differentiating between "no hippocampal sclerosis Gliosis Only" [i.e. gliosis only; no pyramidal neuronal loss] and "HS ILAE Type 1" is essential as these two are distinct histopathological entities in MTLE with d...

Nanomaterials reshaping cancer radiotherapy: Radiosensitization mechanisms, delivery and theranostic platforms, multimodal synergy, and clinical translation strategies.

Radiotherapy (RT) remains a cornerstone of cancer management but is fundamentally constrained by normal tissue toxicity, intrinsic and acquired radior...

Machine Learning-Assisted Optimization Framework for Single-Element Transcranial Focused Ultrasound Transducer Design for Deep Brain Neuromodulation in Mice.

BACKGROUND: Transcranial focused ultrasound (t-FUS) is an emerging noninvasive neuromodulation technique with high spatial precision and deep brain pe...

High-resolution deep learning DIXON MRI of the sacroiliac joints is non-inferior to standard MRI in patients with suspected axial Spondyloarthritis.

OBJECTIVE: To compare the standard multi-sequence MRI protocol (sMRI) of the sacroiliac joints with a single high-resolution deep learning-reconstruct...

Mucinous vs. non-mucinous pancreatic cysts: diagnostic keys on CT and MRI.

The prevalence of incidentally detected pancreatic cystic lesions has increased substantially with the widespread use of high-resolution CT and MRI. D...

Automated Deep Learning-Based Demyelination Load Segmentation in Metachromatic Leukodystrophy.

PURPOSE: Metachromatic leukodystrophy (MLD) is a rare lysosomal storage disorder characterized by progressive white matter demyelination. Quantificati...

Deep learning-based early prediction of carotid plaque response to lipid-lowering therapy using longitudinal multimodal ultrasound imaging.

OBJECTIVE: This study aimed to develop and validate a deep learning prediction model using longitudinal multimodal ultrasound imaging for early identi...

Use of AI to Predict and Support Medication Adherence in Patients With Breast Cancer: Systematic Review.

BACKGROUND: Oral medications are commonly used in the treatment of breast cancer (BC), despite high rates of nonadherence. As adherence is fundamental...

IPEM Topical Report: A National Survey of MRI Use for External Beam Radiotherapy Treatment Planning in the UK: 2025 IPEM Survey Results.

Magnetic Resonance Imaging (MRI) offers superior soft tissue contrast compared to Computed Tomography (CT), making it highly valuable in external beam...

From pixels to pathology: how artificial intelligence mammographic risk scores capture tumor biology through imaging.

OBJECTIVES: To characterize clinical-pathologic tumor features associated with artificial intelligence (AI)-generated risk scores from prior-year scre...

Impaired regional structure-function coupling as novel neurophenotype: mechanistic insights and diagnostic exploration in treatment-resistant depression.

Treatment‑resistant depression (TRD) is one of the toughest clinical challenges in psychiatry, characterized by high recurrence, heavy disease burden,...

Artificial intelligence-based prediction of radio-cephalic arteriovenous fistula maturation using preoperative duplex examination: a retrospective multicenter cohort study.

Establishing a functional arteriovenous fistula (AVF) is crucial to ensure effective dialysis treatment. However, there are currently no definitive cr...

Therapeutic ultrasound in ophthalmology: a comprehensive review.

BACKGROUND: Therapeutic ultrasound has emerged as a promising noninvasive or minimally invasive modality in ophthalmology, offering novel solutions ac...

Equity, diversity, and inclusion: variations in clinical and academic radiology.

Equity, diversity, and inclusion (EDI) are fundamental to achieving fairness and representation in radiological research and practice. This review aim...

Clinical utility of BOLD-MRI in accurate diagnosis and prognostic evaluation of diabetic nephropathy: a prospective renal biopsy-based cohort study.

OBJECTIVES: To validate blood oxygen level-dependent MRI (BOLD-MRI) for non-invasive discrimination of diabetic nephropathy (DN) vs non-diabetic renal...

An AI Based Screening Tool for Detection of Cerebral Venous Thrombosis on Non-Contrast Brain CT.

While non-contrast computed tomography (NCCT) is the primary ‎imaging modality in emergency settings, it has a low sensitivity for detection of ‎Cereb...

Artificial Intelligence in Health Care: Clinical Opportunities, Validation Trends, and Implementation Challenges (2020-2025).

INTRODUCTION: Artificial intelligence (AI) continues to reshape health care, supported by advances in computing power, affordable data storage, and wi...

ReaderAdaptNet: Modeling Reader Variability in Breast Imaging with Reader-Specific Embeddings.

Inter-reader variability remains a major challenge in breast imaging interpretation, particularly for ordinal classification tasks such as breast dens...

Learning Where to Look: Differentiable Slice Selection and Efficient Channel Attention for FCD-II MRI Classification.

Focal Cortical Dysplasia (FCD) is a major cause of drug-resistant epilepsy both in children and adults. In most such cases, surgery is the most effect...