AIMC Topic: Radiomics
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MRI-based radiomics model for the preoperative prediction of classification in children with venous malformations.
Clinical radiology
May 22, 2025
AIM: This study aimed to explore the efficacy of MRI-based radiomics models, employing various machine learning techniques, in the preoperative prediction of the digital subtraction angiography (DSA) classification of venous malformations (VMs).
The value of radiomics features of white matter hyperintensities in diagnosing cognitive frailty: a study based on T2-FLAIR imaging.
BMC medical imaging
May 22, 2025
BACKGROUND: White matter hyperintensities (WMHs) are closely associated with cognitive frailty (CF). This study aims to explore the potential diagnostic value of WMHs for CF based on radiomics approaches, thereby providing a novel methodology for the...
Non-invasive prediction of DCE-MRI radiomics model on CCR5 in breast cancer based on a machine learning algorithm.
Cancer biomarkers : section A of Disease markers
May 21, 2025
BackgroundNon-invasive methods with universal prognostic guidance for detecting breast cancer (BC) survival biomarkers need to be further explored.ObjectiveThis study aimed to investigate C-C motif chemokine receptor type 5 (CCR5) prognosis value in ...
Morphometric and radiomics analysis toward the prediction of epilepsy associated with supratentorial low-grade glioma in children.
Cancer imaging : the official publication of the International Cancer Imaging Society
May 19, 2025
OBJECTIVES: Understanding the impact of epilepsy on pediatric brain tumors is crucial to diagnostic precision and optimal treatment selection. This study investigated MRI radiomics features, tumor location, voxel-based morphometry (VBM) for gray matt...
Preoperative DBT-based radiomics for predicting axillary lymph node metastasis in breast cancer: a multi-center study.
BMC medical imaging
May 19, 2025
BACKGROUND: In the prognosis of breast cancer, the status of axillary lymph nodes (ALN) is critically important. While traditional axillary lymph node dissection (ALND) provides comprehensive information, it is associated with high risks. Sentinel ly...
Radiomic analysis based on machine learning of multi-sequences MR to assess early treatment response in locally advanced nasopharyngeal carcinoma.
Science progress
May 8, 2025
ObjectiveThe prediction of early response in locally advanced nasopharyngeal carcinoma (LA-NPC) after concurrent chemoradiotherapy (CCRT) is important for determining the need for timely consolidation therapy. We developed a radiomic analysis of mult...
Stacking classifiers based on integrated machine learning model: fusion of CT radiomics and clinical biomarkers to predict lymph node metastasis in locally advanced gastric cancer patients after neoadjuvant chemotherapy.
BMC cancer
May 6, 2025
BACKGROUND: The early prediction of lymph node positivity (LN+) after neoadjuvant chemotherapy (NAC) is crucial for optimizing individualized treatment strategies. This study aimed to integrate radiomic features and clinical biomarkers through machin...
Prediction of EGFR Mutations in Lung Adenocarcinoma via CT Images: A Comparative Study of Intratumoral and Peritumoral Radiomics, Deep Learning, and Fusion Models.
Academic radiology
May 5, 2025
RATIONALE AND OBJECTIVES: This study aims to analyze the intratumoral and peritumoral characteristics of lung adenocarcinoma patients on the basis of chest CT images via radiomic and deep learning methods and to develop and validate a multimodel fusi...
The Application Status of Radiomics-Based Machine Learning in Intrahepatic Cholangiocarcinoma: Systematic Review and Meta-Analysis.
Journal of medical Internet research
May 5, 2025
BACKGROUND: Over the past few years, radiomics for the detection of intrahepatic cholangiocarcinoma (ICC) has been extensively studied. However, systematic evidence is lacking in the use of radiomics in this domain, which hinders its further developm...
Radiomic study of common sellar region lesions differentiation in magnetic resonance imaging based on multi-classification machine learning model.
BMC medical imaging
May 3, 2025
OBJECTIVE: Pituitary adenomas (PAs), craniopharyngiomas (CRs), Rathke's cleft cysts (RCCs), and tuberculum sellar meningiomas (TSMs) are common sellar region lesions with similar imaging characteristics, making differential diagnosis challenging. Thi...
Radiomics
Male
Middle Aged
Adolescent
Support Vector Machine
Magnetic Resonance Imaging
Pituitary Neoplasms
Adenoma
Diagnosis, Differential
Retrospective Studies
Female
Central Nervous System Cysts
Aged
Young Adult
Adult
Meningioma
Humans
Meningeal Neoplasms
Machine Learning
Sella Turcica
Craniopharyngioma
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