AIMC Topic: Radiomics

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A radiomics model combining machine learning and neural networks for high-accuracy prediction of cervical lymph node metastasis on ultrasound of head and neck squamous cell carcinoma.

Oral surgery, oral medicine, oral pathology and oral radiology Jan 24, 2025
OBJECTIVE: This study aimed to develop an ultrasound image-based radiomics model for diagnosing cervical lymph node (LN) metastasis in patients with head and neck squamous cell carcinoma (HNSCC) that shows higher accuracy than previous models.
Lymphatic Metastasis Humans Lymph Nodes Radiomics Neural Networks, Computer Squamous Cell Carcinoma of Head and Neck Machine Learning Male Head and Neck Neoplasms Female Middle Aged Neck Ultrasonography
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Performance of Radiomics-based machine learning and deep learning-based methods in the prediction of tumor grade in meningioma: a systematic review and meta-analysis.

Neurosurgical review Jan 24, 2025
Currently, the World Health Organization (WHO) grade of meningiomas is determined based on the biopsy results. Therefore, accurate non-invasive preoperative grading could significantly improve treatment planning and patient outcomes. Considering rece...
Meningioma Humans Meningeal Neoplasms Machine Learning Radiomics Deep Learning Neoplasm Grading
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Delta-Radiomics Using Machine Learning Classifiers With Auxiliary Data Sets to Predict Disease Progression During Magnetic Resonance-Guided Radiotherapy in Adrenal Metastases.

JCO clinical cancer informatics Jan 24, 2025
PURPOSE: Adaptive radiotherapy accounts for interfractional anatomic changes. We hypothesize that changes in the gross tumor volumes identified during daily scans could be analyzed using delta-radiomics to predict disease progression events. We evalu...
Middle Aged Disease Progression ROC Curve Lung Neoplasms Magnetic Resonance Imaging Humans Machine Learning Adrenal Gland Neoplasms Pancreatic Neoplasms Aged Prognosis Radiotherapy, Image-Guided Female Adult Radiomics Male
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CT-based machine learning radiomics predicts Ki-67 expression level and its relationship with overall survival in resectable pancreatic ductal adenocarcinoma.

Abdominal radiology (New York) Jan 22, 2025
BACKGROUND: The prognostic prediction of pancreatic ductal adenocarcinoma (PDAC) remains challenging. This study aimed to develop a radiomics model to predict Ki-67 expression status in PDAC patients using radiomics features from dual-phase enhanced ...
Humans Machine Learning Prognosis Male Middle Aged Retrospective Studies Aged, 80 and over Ki-67 Antigen Nomograms Adult Tomography, X-Ray Computed Pancreatic Neoplasms Predictive Value of Tests Survival Rate Female Radiomics Carcinoma, Pancreatic Ductal Aged
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Radiomics for prediction of perineural invasion in colorectal cancer: a systematic review and meta-analysis.

Abdominal radiology (New York) Jan 22, 2025
BACKGROUND: Perineural invasion (PNI) in colorectal cancer (CRC) is a significant prognostic factor associated with poor outcomes. Radiomics, which involves extracting quantitative features from medical imaging, has emerged as a potential tool for pr...
Colorectal Neoplasms Radiomics Neoplasm Invasiveness Peripheral Nerves Humans Sensitivity and Specificity
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Multi-parametric MRI combined with radiomics for the diagnosis and grading of endometrial fibrosis.

Abdominal radiology (New York) Jan 22, 2025
PURPOSE: To evaluate the application of multi-parametric MRI (MP-MRI) combined with radiomics in diagnosing and grading endometrial fibrosis (EF).
Humans Machine Learning Prospective Studies Female Adult Image Interpretation, Computer-Assisted Magnetic Resonance Imaging Sensitivity and Specificity Multiparametric Magnetic Resonance Imaging Fibrosis Radiomics Uterine Diseases Middle Aged Endometrium
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Comparative analysis of deep learning and radiomic signatures for overall survival prediction in recurrent high-grade glioma treated with immunotherapy.

Cancer imaging : the official publication of the International Cancer Imaging Society Jan 21, 2025
BACKGROUND: Radiomic analysis of quantitative features extracted from segmented medical images can be used for predictive modeling of prognosis in brain tumor patients. Manual segmentation of the tumor components is time-consuming and poses significa...
Adult Radiomics Brain Neoplasms Male Immunotherapy Glioma Magnetic Resonance Imaging Middle Aged Deep Learning Prognosis Neoplasm Grading Retrospective Studies Humans Neoplasm Recurrence, Local Female Neural Networks, Computer Aged
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Deep learning-based CT radiomics predicts prognosis of unresectable hepatocellular carcinoma treated with TACE-HAIC combined with PD-1 inhibitors and tyrosine kinase inhibitors.

BMC gastroenterology Jan 21, 2025
OBJECTIVE: To develop and validate a computed tomography (CT)-based deep learning radiomics model to predict treatment response and progression-free survival (PFS) in patients with unresectable hepatocellular carcinoma (uHCC) treated with transarteri...
Combined Modality Therapy Chemoembolization, Therapeutic Adult Protein Kinase Inhibitors Radiomics Retrospective Studies Tyrosine Kinase Inhibitors Humans Carcinoma, Hepatocellular Male Tomography, X-Ray Computed Deep Learning Prognosis Middle Aged Immune Checkpoint Inhibitors Female Liver Neoplasms Antineoplastic Combined Chemotherapy Protocols Aged
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CT-based Machine Learning Radiomics Modeling: Survival Prediction and Mechanism Exploration in Ovarian Cancer Patients.

Academic radiology Jan 17, 2025
RATIONALE AND OBJECTIVES: To create a radiomics model based on computed tomography (CT) to predict overall survival in ovarian cancer patients. To combine Rad-score with genomic data to explore the association between gene expression and Rad-score.
Tomography, X-Ray Computed Female Aged Adult Ovarian Neoplasms Humans Radiomics Machine Learning Middle Aged Prognosis Retrospective Studies
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Development of a clinical prediction model for benign and malignant pulmonary nodules with a CTR ≥ 50% utilizing artificial intelligence-driven radiomics analysis.

BMC medical imaging Jan 17, 2025
OBJECTIVE: In clinical practice, diagnosing the benignity and malignancy of solid-component-predominant pulmonary nodules is challenging, especially when 3D consolidation-to-tumor ratio (CTR) ≥ 50%, as malignant ones are more invasive. This study aim...
Adult Radiomics Male Middle Aged Retrospective Studies Tomography, X-Ray Computed Female Aged Solitary Pulmonary Nodule Diagnosis, Differential ROC Curve Lung Neoplasms Logistic Models Multiple Pulmonary Nodules Humans Artificial Intelligence
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