Radiology

Demystifying machine learning approaches in digital bone imaging using microCT and HRpQCT.

Micro-computed tomography (microCT) and high-resolution peripheral quantitative computed tomography (HRpQCT) generate three-dimensional digital images capturing bone structure and quality. Radiomic analytical approaches applied to these images extract quantitative measures of bone microarchitecture (e.g., bone volume and density). Automating and interpreting radiomics data using conventional image...

Quantitative Coronary Atherosclerotic Plaque Burden From CCTA and the Benefit From Lipid-Lowering Medication.

BACKGROUND: We hypothesized that quantification of coronary atherosclerotic plaque burden by artificial intelligence-guided quantitative computed tomography can identify patients who derive outcome benefit from lipid-lowering medication (LLM). METHODS: In this observational cohort study, consecutive symptomatic patients undergoing coronary computed tomography angiography for suspected coronary art...

Artificial Intelligence-Aided Lung Ultrasound Detection of Interstitial Lung Disease in Systemic Sclerosis and Inflammatory Myopathy.

BACKGROUND: Lung ultrasound (LUS) is a sensitive, low-cost, and radiation-free modality for ILD detection. We previously developed and validated LUS i...

On optimisation of Paganin's method for propagation-based X-ray phase-contrast imaging and tomography.

Paganin's method for image reconstruction in propagation-based phase-contrast X-ray imaging and tomography has enjoyed broad acceptance in recent year...

Artificial intelligence-based segmentation of perisinusoidal tissue along the superior sagittal sinus in human brain magnetic resonance imaging.

Deep learning reconstruction for 40-keV virtual monoenergetic CT of colon cancer: evaluation of image quality and edge sharpness.

BACKGROUND: Virtual monoenergetic imaging (VMI) at 40 keV improves iodine attenuation in colon cancer CT but is constrained by severe image noise. Dee...

Deep Learning for Content-Based Medical Image Retrieval in Picture Archiving and Communication Systems for Brain Tumor Detection: Algorithm Development and Validation.

BACKGROUND: Advances in medical imaging have led to massive archives, yet navigating these datasets remains challenging due to the limitations of trad...

Organ-Aware Cross-Modality Registration Enables Attenuation Correction Without Repeated CT in Multi-Scan Total-Body PET/CT Imaging.

Multi-Scan Total-Body PET/CT imaging, including dual-time-point and multi-tracer protocols, provides valuable metabolic information for enhanced disea...

Deep Learning Driven Evaluation of MR-guided Focused Ultrasound Ablation.

OBJECTIVE: Magnetic resonance-guided focused ultrasound (MRgFUS) thermal therapy is a promising incisionless procedure for breast cancer treatment. fo...

Anatomy-Guided Self-Supervised Distillation Learning for Medical Image Analysis.

3D medical imaging modalities, including CT and MRI, provide high-resolution views essential for precision medicine. However, the increasing volume an...

Performance of an image-only deep learning breast cancer risk model with the addition of a polygenic risk score.

BACKGROUND: Mammograms contain imaging biomarkers that can predict future breast cancer risk using deep learning (DL) models. We evaluated whether add...

An ethics-informed computable audit framework for monitoring misdiagnosis risk in AI-assisted diagnosis.

Diagnostic AI can misclassify under distribution shift and subgroup imbalance; governance signals are rarely computable at deploy time. We target depl...

AI Models for Surgical Decision Support in Spontaneous Intracerebral Hemorrhage: A Systematic Review in Relation to Trials and Guidelines.

Artificial intelligence (AI) applications for spontaneous intracerebral hemorrhage (ICH) are rapidly expanding, particularly in perioperative imaging ...

Investigation of multimodal deep learning models for predicting ovarian tumor malignancy based on ultrasound images and clinical information - a comprehensive comparative study against readers and O-RADS.

BACKGROUND: As the second deadly cancer affecting women globally, precise and timely classification of ovarian tumors plays an instrumental role in im...

Advances in cataract surgery: is a new era on the horizon?

PURPOSE OF REVIEW: To summarize recent technological, procedural and material advances that are reshaping cataract surgery and to appraise their impli...

A fully automated CT-based pelvimetry pipeline for quantifying mid-pelvic surgical workspace in rectal cancer.

PURPOSE: Pelvimetry may aid preoperative planning in rectal cancer surgery, yet manual measurements are time-consuming and MRI-based methods require d...

A machine learning approach to using ultrasound for body composition and nutritional status assessment in newborns: a pilot study protocol.

BACKGROUND: Accurate assessment of infant body composition, specifically fat and fat-free mass, is crucial for evaluating growth and nutritional statu...

Predictive neuroimaging biomarkers of major depressive disorder treatment response: An umbrella review.

Major depressive disorder (MDD) is a heterogeneous condition with varied responses to pharmacological, psychotherapeutic, and neuromodulation interven...

Would You Like a Side of Artificial Intelligence With Your Mammogram? An Experimental Study of Patient Willingness to Pay for Artificial Intelligence.

BACKGROUND: Some radiology practices ask patients to pay out of pocket for supplemental artificial intelligence (AI) interpretations of screening mamm...

The diagnostic performance of machine learning based detection of urinary tract stones: a systematic review and meta-analysis.

BACKGROUND: Urolithiasis is a prevalent urological condition, and Non-Contrast Computed Tomography (NCCT) is the gold standard for diagnosis. In recen...