In 2025, the Centers for Medicare and Medicaid Services introduced a computed tomography (CT) dose measure for pay-for-performance programs. Hospitals employ diverse scanner fleets, but the impact of scanner technologies on dose benchmarking remains unclear. This study evaluates dose variation across scanner models and its benchmarking implications.

Tuberous sclerosis complex (TSC) is a multisystem genetic disorder. Focusing on central nervous system manifestations, this study developed an imaging-clinical model combining advanced diffusion MRI parameters with neurological clinical features to distinguish TSC1 vs. TSC2 genotypes.

To construct and validate an interpretable machine learning (ML) radiomics model derived from multiparametric magnetic resonance imaging (MRI) images to differentiate between luminal and non-luminal breast cancer (BC) subtypes.

Routine knee MRI protocols for 1.5 T and 3 T scanners, do not include T2*-w gradient echo (T2*W) images, which are useful in several clinical scenarios such as the assessment of cartilage, synovial blooming (deposition of hemosiderin), chondrocalcinosis and the evaluation of the physis in pediatric patients. Herein, we aimed to develop an open-source deep learning model that creates synthetic T2*W images of the knee using fat-suppressed intermediate-weighted images.

Preoperative knowledge of the status of lymphovascular invasion (LVI) status in colorectal cancer (CRC) patients can provide valuable information for choosing appropriate treatment strategies. This study aimed to explore the value of heterogeneity features derived from the habitat analysis of F-fluorodeoxyglucose (FDG) positron emission tomography (PET) images in predicting LVI.

To investigate the magnetic resonance elastography (MRE)-derived pancreatic stiffness for predicting the occurrence of clinically relative postoperative pancreatic fistula (CR-POPF) in patients with partial pancreatectomy, and establish a predictive model for POPF before surgery.

Coronary chronic total occlusion (CTO) and subtotal occlusion (STO) pose diagnostic challenges, differing in treatment strategies. Artificial intelligence and radiomics are promising tools for accurate discrimination. This study aimed to develop deep learning (DL) and radiomics models using coronary computed tomography angiography (CCTA) to differentiate CTO from STO lesions and compare their performance with that of the conventional method.

MRI proton density fat fraction (MRI-PDFF), controlled attenuation parameters (CAP), and attenuation coefficients (AC) are capable of steatosis characterization and may be useful as noninvasive alternatives for diagnosing hepatic steatosis.

Ultrasound (US)-based deep learning (DL) models for grading the severity of carpal tunnel syndrome (CTS) are scarce. We aimed to advance CTS grading by developing a joint-DL model integrating clinical information and multimodal US features.

Wild-type transthyretin amyloid cardiomyopathy (ATTRwt-CM) predominantly affects males; however, female patients can also develop this condition. This study assessed the non-invasive imaging features of ATTRwt-CM in female patients.

Adolescent major depressive disorder (MDD) is a serious mental health condition that has been linked to abnormal functional connectivity (FC) patterns within the brain. However, whether FC could be used as a potential biomarker for diagnosis of adolescent MDD is still unclear. The aim of our study was to investigate the potential diagnostic value of whole-brain FC in adolescent MDD.

The classification of renal cell carcinoma (RCC) histological subtypes plays a crucial role in clinical diagnosis. However, traditional image normalization methods often struggle with discrepancies arising from differences in imaging parameters, scanning devices, and multi-center data, which can impact model robustness and generalizability.

Thermal ablation (TA) has demonstrated promising treatment efficacy and safety in T1N0M0 papillary thyroid carcinoma (PTC). However, the efficacy and safety of TA for T2N0M0 PTC still lack sufficient evidence.

Yttrium-90 (Y-90) radioembolization has emerged as an effective therapeutic modality for patients with liver metastases, despite the absence of Level I evidence. The objective of this study is to evaluate the efficacy of this treatment approach through a meta-analysis of the available literature.

The therapeutic efficacy of irreversible electroporation (IRE) for treating subcapsular hepatocellular carcinoma (HCC) remains under-explored. The current study aimed to compare IRE and radiofrequency ablation (RFA) outcomes in an HCC patient group.