Latest AI and machine learning research in radiology for healthcare professionals.
PURPOSE: Preoperative risk estimation of occult high-volume central lymph node metastasis (CLNM) in clinically node-negative (cN0) papillary thyroid carcinoma (PTC) remains challenging. We aimed to develop and validate a practical multimodal model integrating conventional ultrasound and radiomics for individualized preoperative risk stratification. METHODS: In this retrospective, two-center, multi...
Patients with multiple myeloma are frequently exposed to prolonged, multi-line and multi-drug treatment, factors that may substantially influence overall health, physical reserve, and physiological resilience. Imaging of organs that are captured by whole body scans can be opportunistically interrogated to derive direct, quantitative measures of body composition. Advances and standardisation of who...
Dysregulation of biomolecular condensates is implicated across multiple neurological disorders. However, approaches to systematically identify their m...
OBJECTIVE: In brain radiotherapy, accurate target volume delineation is a key step in treatment planning. However, manual contour delineation can be t...
PURPOSE: The SMART (Stereotactic MR-Guided Adaptive Radiation Therapy) protocol for prostate SBRT has demonstrated favorable clinical outcomes using a...
BACKGROUND: Brain metastasis (BM) is a high-mortality complication occurring in 20-40% of cancer patients. While the Gamma Knife (GK) is a primary tre...
This study evaluated whether a vendor-neutral deep learning reconstruction (DLR) can improve image quality in accelerated T2-weighted imaging (T2WI) o...
To develop a deep learning-based body composition quantification framework from non-contrast CT for urolithiasis classification (calcium, non-calcium,...
BACKGROUND: The evaluation of genetic mutations is crucial for personalized therapy in colorectal cancer (CRC), but the invasive tissue biopsy is subj...
BACKGROUND: Supraspinatus tendon pathologies are common causes of shoulder pain. Magnetic resonance imaging (MRI) is the reference imaging method but ...
OBJECTIVES: We developed a transfer learning-based multimodal fusion deep learning model integrating positron emission tomography/computed tomography ...
BACKGROUND: The writing of study protocols is a labor and time-intensive process. We hypothesized that the writing of some methodological aspects of s...
Chronic obstructive pulmonary disease (COPD) is a heterogeneous syndrome. Spirometry, while diagnostic, inadequately characterizes disease complexity....
BACKGROUND: Since 1992, the incidence of lung cancer has shown an overall downward trend, with survival rates significantly improving in recent years ...
The assessment of response to neoadjuvant systemic therapy (NST) is a critical pillar in defining the multidisciplinary therapeutic strategy in breast...
INTRODUCTION: Assessment of renal tissue and renal tumor stiffness may provide complementary information for tissue characterization; however, convent...
BACKGROUND: Cardiovascular disease (CVD) diagnosis using multimodal health care data remains a major challenge due to the heterogeneity of clinical an...
PURPOSE: To design a deep learning pipeline for automated, time-resolved segmentation of the left atrium (LA) from 4D flow MRI data. METHODS: We studi...
INTRODUCTION: As ultrasound technology has become more advanced and accessible over the years, point-of-care ultrasound (POCUS) is becoming a tool as ...
BACKGROUND: Catheter ablation is an essential tool for ventricular arrhythmia management, yet sustained procedural success is hindered by the limited ...