AIMC Topic: Radiomics

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Deep learning radiomic nomogram outperforms the clinical model in distinguishing intracranial solitary fibrous tumors from angiomatous meningiomas and can predict patient prognosis.

European radiology Oct 16, 2024
OBJECTIVES: To evaluate the value of a magnetic resonance imaging (MRI)-based deep learning radiomic nomogram (DLRN) for distinguishing intracranial solitary fibrous tumors (ISFTs) from angiomatous meningioma (AMs) and predicting overall survival (OS...
Retrospective Studies Female Aged Adult Radiomics Humans Prognosis Meningeal Neoplasms Solitary Fibrous Tumors Brain Neoplasms Male Middle Aged Nomograms Deep Learning Magnetic Resonance Imaging Diagnosis, Differential Meningioma
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Multiparametric MRI Radiomics With Machine Learning for Differentiating HER2-Zero, -Low, and -Positive Breast Cancer: Model Development, Testing, and Interpretability Analysis.

AJR. American journal of roentgenology Oct 16, 2024
MRI radiomics has been explored for three-tiered classification of HER2 expression levels (i.e., HER2-zero, HER2-low, or HER2-positive) in patients with breast cancer, although an understanding of how such models reach their predictions is lacking. ...
Receptor, ErbB-2 Multiparametric Magnetic Resonance Imaging Middle Aged Magnetic Resonance Imaging Breast Image Interpretation, Computer-Assisted Humans Machine Learning Retrospective Studies Adult Breast Neoplasms Female Radiomics Aged
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A Machine Learning Model Based on Global Mammographic Radiomic Features Can Predict Which Normal Mammographic Cases Radiology Trainees Find Most Difficult.

Journal of imaging informatics in medicine Oct 15, 2024
This study aims to investigate whether global mammographic radiomic features (GMRFs) can distinguish hardest- from easiest-to-interpret normal cases for radiology trainees (RTs). Data from 137 RTs were analysed, with each interpreting seven education...
Mammography Radiology Radiographic Image Interpretation, Computer-Assisted Breast Neoplasms Humans Female Radiomics Machine Learning Adult Clinical Competence
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Using Machine Learning on MRI Radiomics to Diagnose Parotid Tumours Before Comparing Performance with Radiologists: A Pilot Study.

Journal of imaging informatics in medicine Oct 10, 2024
The parotid glands are the largest of the major salivary glands. They can harbour both benign and malignant tumours. Preoperative work-up relies on MR images and fine needle aspiration biopsy, but these diagnostic tools have low sensitivity and speci...
Machine Learning Algorithms Female Aged Adult Humans Pilot Projects Magnetic Resonance Imaging Radiologists Parotid Gland Parotid Neoplasms Sensitivity and Specificity Radiomics Male Middle Aged
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Graph neural networks in multi-stained pathological imaging: extended comparative analysis of Radiomic features.

International journal of computer assisted radiology and surgery Oct 7, 2024
PURPOSE: This study investigates the application of Radiomic features within graph neural networks (GNNs) for the classification of multiple-epitope-ligand cartography (MELC) pathology samples. It aims to enhance the diagnosis of often misdiagnosed s...
Humans Neural Networks, Computer Radiomics Skin Diseases Image Interpretation, Computer-Assisted Graph Neural Networks
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Machine learning based classification of spontaneous intracranial hemorrhages using radiomics features.

Neuroradiology Oct 5, 2024
PURPOSE: To assess the efficacy of radiomics features extracted from non-contrast computed tomography (NCCT) scans in differentiating multiple etiologies of spontaneous intracerebral hemorrhage (ICH).
Middle Aged Diagnosis, Differential Radiographic Image Interpretation, Computer-Assisted Intracranial Hemorrhages Retrospective Studies Tomography, X-Ray Computed Female Aged Sensitivity and Specificity Radiomics Male Aged, 80 and over Adult Humans Machine Learning
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Computed Tomography-Based Radiomics with Machine Learning Outperforms Radiologist Assessment in Estimating Colorectal Liver Metastases Pathologic Response After Chemotherapy.

Annals of surgical oncology Oct 5, 2024
OBJECTIVES: This study was designed to assess computed tomography (CT)-based radiomics of colorectal liver metastases (CRLM), extracted from posttreatment scans in estimating pathologic treatment response to neoadjuvant therapy, and to compare treatm...
Neoadjuvant Therapy Follow-Up Studies Radiologists Response Evaluation Criteria in Solid Tumors Male Middle Aged Liver Neoplasms Antineoplastic Combined Chemotherapy Protocols Aged Adult Colorectal Neoplasms Machine Learning Radiomics Humans Prognosis Retrospective Studies Tomography, X-Ray Computed Female
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Machine learning and radiomics for ventricular tachyarrhythmia prediction in hypertrophic cardiomyopathy: insights from an MRI-based analysis.

Acta radiologica (Stockholm, Sweden : 1987) Oct 1, 2024
BACKGROUND: Myocardial fibrosis is often detected in patients with hypertrophic cardiomyopathy (HCM), which causes left ventricular (LV) dysfunction and tachyarrhythmias.
Retrospective Studies Female Adult Humans Machine Learning Magnetic Resonance Imaging, Cine Magnetic Resonance Imaging Radiomics Predictive Value of Tests Cardiomyopathy, Hypertrophic Male Tachycardia, Ventricular Middle Aged Contrast Media
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Machine learning models based on CT radiomics features for distinguishing benign and malignant vertebral compression fractures in patients with malignant tumors.

Acta radiologica (Stockholm, Sweden : 1987) Oct 1, 2024
BACKGROUND: Radiomics has become an important tool for distinguishing benign and malignant vertebral compression fractures (VCFs). It is more clinically significant to concentrate on patients who have malignant tumors and differentiate between benign...
Radiomics Male Middle Aged Diagnosis, Differential Machine Learning Spinal Neoplasms Female Retrospective Studies Spinal Fractures Aged Tomography, X-Ray Computed Fractures, Compression Aged, 80 and over Humans Adult
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Personalized prediction of immunotherapy response in lung cancer patients using advanced radiomics and deep learning.

Cancer imaging : the official publication of the International Cancer Imaging Society Sep 30, 2024
BACKGROUND: Lung cancer (LC) is a leading cause of cancer-related mortality, and immunotherapy (IO) has shown promise in treating advanced-stage LC. However, identifying patients likely to benefit from IO and monitoring treatment response remains cha...
Middle Aged Female Progression-Free Survival Humans Deep Learning Aged Lung Neoplasms Precision Medicine Radiomics Immunotherapy Retrospective Studies Male Tomography, X-Ray Computed
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