AIMC Topic: Radiomics

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Prediction of early hematoma expansion of spontaneous intracerebral hemorrhage based on deep learning radiomics features of noncontrast computed tomography.

European radiology Nov 8, 2023
OBJECTIVES: Aimed to develop a nomogram model based on deep learning features and radiomics features for the prediction of early hematoma expansion.
Aged Radiomics Male Middle Aged Humans Deep Learning Cerebral Hemorrhage Retrospective Studies Nomograms Tomography, X-Ray Computed Predictive Value of Tests Hematoma Female
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A Machine Learning-Based Unenhanced Radiomics Approach to Distinguishing Between Benign and Malignant Breast Lesions Using T2-Weighted and Diffusion-Weighted MRI.

Journal of magnetic resonance imaging : JMRI Nov 7, 2023
BACKGROUND: Breast MRI has been recommended as supplemental screening tool to mammography and breast ultrasound of breast cancer by international guidelines, but its long examination time and use of contrast material remains concerning.
Female Reproducibility of Results Aged Adult Breast Neoplasms Humans Machine Learning Prospective Studies Retrospective Studies Diagnosis, Differential Area Under Curve Breast Image Interpretation, Computer-Assisted Diffusion Magnetic Resonance Imaging Radiomics Middle Aged Contrast Media Magnetic Resonance Imaging
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Development of an MRI-Based Comprehensive Model Fusing Clinical, Radiomics and Deep Learning Models for Preoperative Histological Stratification in Intracranial Solitary Fibrous Tumor.

Journal of magnetic resonance imaging : JMRI Oct 28, 2023
BACKGROUND: Accurate preoperative histological stratification (HS) of intracranial solitary fibrous tumors (ISFTs) can help predict patient outcomes and develop personalized treatment plans. However, the role of a comprehensive model based on clinica...
Adult Radiomics Brain Neoplasms Male Retrospective Studies Female Aged Young Adult Feasibility Studies Preoperative Period Solitary Fibrous Tumors Middle Aged Deep Learning ROC Curve Magnetic Resonance Imaging Humans
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Magnetic Resonance Deep Learning Radiomic Model Based on Distinct Metastatic Vascular Patterns for Evaluating Recurrence-Free Survival in Hepatocellular Carcinoma.

Journal of magnetic resonance imaging : JMRI Oct 27, 2023
BACKGROUND: The metastatic vascular patterns of hepatocellular carcinoma (HCC) are mainly microvascular invasion (MVI) and vessels encapsulating tumor clusters (VETC). However, most existing VETC-related radiological studies still focus on the predic...
Male Middle Aged Deep Learning Aged, 80 and over Humans Liver Neoplasms China Magnetic Resonance Imaging Young Adult Retrospective Studies Carcinoma, Hepatocellular Neoplasm Recurrence, Local Female Adult Disease-Free Survival Aged Radiomics
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Enhancing radiomics and Deep Learning systems through the standardization of medical imaging workflows.

Scientific data Oct 21, 2023
Recent advances in computer-aided diagnosis, treatment response and prognosis in radiomics and deep learning challenge radiology with requirements for world-wide methodological standards for labeling, preprocessing and image acquisition protocols. Th...
Radiomics Deep Learning Radiography Diagnostic Imaging Workflow Reference Standards
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Radiomics-based Machine Learning to Predict the Recurrence of Hepatocellular Carcinoma: A Systematic Review and Meta-analysis.

Academic radiology Oct 20, 2023
RATIONALE AND OBJECTIVES: Recurrence of hepatocellular carcinoma (HCC) is a major concern in its management. Accurately predicting the risk of recurrence is crucial for determining appropriate treatment strategies and improving patient outcomes. A ce...
Liver Neoplasms Carcinoma, Hepatocellular Contrast Media Predictive Value of Tests Neoplasm Recurrence, Local Humans Machine Learning Sensitivity and Specificity Radiomics
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Editorial for "Assessment of Lymphovascular Invasion in Breast Cancer Using a Combined MRI Morphological Features, Radiomics, and Deep Learning Approach Based on Dynamic Contrast-Enhanced MRI".

Journal of magnetic resonance imaging : JMRI Oct 19, 2023
Neoplasm Invasiveness Breast Radiomics Humans Lymphatic Metastasis Female Deep Learning Contrast Media Magnetic Resonance Imaging Breast Neoplasms
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Assessment of Lymphovascular Invasion in Breast Cancer Using a Combined MRI Morphological Features, Radiomics, and Deep Learning Approach Based on Dynamic Contrast-Enhanced MRI.

Journal of magnetic resonance imaging : JMRI Oct 19, 2023
BACKGROUND: Assessment of lymphovascular invasion (LVI) in breast cancer (BC) primarily relies on preoperative needle biopsy. There is an urgent need to develop a non-invasive assessment method.
Radiomics Cross-Sectional Studies Middle Aged Deep Learning Lymphatic Metastasis Contrast Media Magnetic Resonance Imaging Cohort Studies ROC Curve Female Aged Adult Breast Neoplasms Humans Retrospective Studies Neoplasm Invasiveness Breast
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Multiparametric MRI-based radiomics model for predicting human papillomavirus status in oropharyngeal squamous cell carcinoma: optimization using oversampling and machine learning techniques.

European radiology Oct 18, 2023
OBJECTIVES: To develop and validate a multiparametric MRI-based radiomics model with optimal oversampling and machine learning techniques for predicting human papillomavirus (HPV) status in oropharyngeal squamous cell carcinoma (OPSCC).
Middle Aged Papillomavirus Infections Squamous Cell Carcinoma of Head and Neck Papillomaviridae Human Papillomavirus Viruses Retrospective Studies Oropharyngeal Neoplasms Female Multiparametric Magnetic Resonance Imaging Aged Radiomics Humans Male Machine Learning
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Automated Breast Density Assessment in MRI Using Deep Learning and Radiomics: Strategies for Reducing Inter-Observer Variability.

Journal of magnetic resonance imaging : JMRI Oct 17, 2023
BACKGROUND: Accurate breast density evaluation allows for more precise risk estimation but suffers from high inter-observer variability.
ROC Curve Image Processing, Computer-Assisted Magnetic Resonance Imaging Breast Observer Variation Breast Density Feasibility Studies Image Interpretation, Computer-Assisted Breast Neoplasms Radiomics Middle Aged Deep Learning Female Reproducibility of Results Aged Adult Humans Retrospective Studies
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