AIMC Topic: Radiomics
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Computed tomography-based radiomics predicts prognostic and treatment-related levels of immune infiltration in the immune microenvironment of clear cell renal cell carcinoma.
BMC medical imaging
Jul 1, 2025
OBJECTIVES: The composition of the tumour microenvironment is very complex, and measuring the extent of immune cell infiltration can provide an important guide to clinically significant treatments for cancer, such as immune checkpoint inhibition ther...
Radiomics and machine learning for osteoporosis detection using abdominal computed tomography: a retrospective multicenter study.
BMC medical imaging
Jul 1, 2025
OBJECTIVE: This study aimed to develop and validate a predictive model to detect osteoporosis using radiomic features and machine learning (ML) approaches from lumbar spine computed tomography (CT) images during an abdominal CT examination.
Multimodal deep learning-based radiomics for meningioma consistency prediction: integrating T1 and T2 MRI in a multi-center study.
BMC medical imaging
Jul 1, 2025
BACKGROUND: Meningioma consistency critically impacts surgical planning, as soft tumors are easier to resect than hard tumors. Current assessments of tumor consistency using MRI are subjective and lack quantitative accuracy. Integrating deep learning...
Muscle-Driven prognostication in gastric cancer: A multicenter deep learning framework integrating Iliopsoas and erector spinae radiomics for 5-Year survival prediction.
Scientific reports
Jul 1, 2025
This study developed a 5-year survival prediction model for gastric cancer patients by combining radiomics and deep learning, focusing on CT-based 2D and 3D features of the iliopsoas and erector spinae muscles. Retrospective data from 705 patients ac...
Radiomics analysis based on dynamic contrast-enhanced MRI for predicting early recurrence after hepatectomy in hepatocellular carcinoma patients.
Scientific reports
Jul 1, 2025
This study aimed to develop a machine learning model based on Magnetic Resonance Imaging (MRI) radiomics for predicting early recurrence after curative surgery in patients with hepatocellular carcinoma (HCC).A retrospective analysis was conducted on ...
Automated classification of chondroid tumor using 3D U-Net and radiomics with deep features.
Scientific reports
Jul 1, 2025
Classifying chondroid tumors is an essential step for effective treatment planning. Recently, with the advances in computer-aided diagnosis and the increasing availability of medical imaging data, automated tumor classification using deep learning sh...
Prediction of axillary lymph node metastasis in triple negative breast cancer using MRI radiomics and clinical features.
Scientific reports
Jul 1, 2025
To develop and validate a machine learning-based prediction model to predict axillary lymph node (ALN) metastasis in triple negative breast cancer (TNBC) patients using magnetic resonance imaging (MRI) and clinical characteristics. This retrospective...
Radiomic 'Stress Test': exploration of a deep learning radiomic model in a high-risk prospective lung nodule cohort.
BMJ open respiratory research
Jun 27, 2025
BACKGROUND: Indeterminate pulmonary nodules (IPNs) are commonly biopsied to ascertain a diagnosis of lung cancer, but many are ultimately benign. The Lung Cancer Prediction (LCP) score is a commercially available deep learning radiomic model with str...
Comprehensive predictive modeling in subarachnoid hemorrhage: integrating radiomics and clinical variables.
Neurosurgical review
Jun 24, 2025
Subarachnoid hemorrhage (SAH) is a severe condition with high morbidity and long-term neurological consequences. Radiomics, by extracting quantitative features from Computed Tomograhpy (CT) scans, may reveal imaging biomarkers predictive of outcomes....
Impact of Field-of-view Zooming and Segmentation Batches on Radiomics Features Reproducibility and Machine Learning Performance in Thyroid Scintigraphy.
Clinical nuclear medicine
Jun 17, 2025
BACKGROUND: Thyroid diseases are the second most common hormonal disorders, necessitating accurate diagnostics. Advances in artificial intelligence and radiomics have enhanced diagnostic precision by analyzing quantitative imaging features. However, ...
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