AIMC Topic: Radiomics

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Comparative analysis of machine learning models for predicting pathological complete response to neoadjuvant chemotherapy in breast cancer: An MRI radiomics approach.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Feb 12, 2025
PURPOSE: The aim of this work is to compare different machine learning models for predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer using radiomics features from dynamic contrast-enhanced magnetic reso...
Image Processing, Computer-Assisted Adult Treatment Outcome Humans Breast Neoplasms Neoadjuvant Therapy Machine Learning Radiomics Magnetic Resonance Imaging Female Middle Aged Aged
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Radiomics integration based on intratumoral and peritumoral computed tomography improves the diagnostic efficiency of invasiveness in patients with pure ground-glass nodules: a machine learning, cross-sectional, bicentric study.

Journal of cardiothoracic surgery Feb 11, 2025
BACKGROUND: Radiomics has shown promise in the diagnosis and prognosis of lung cancer. Here, we investigated the performance of computed tomography-based radiomic features, extracted from gross tumor volume (GTV), peritumoral volume (PTV), and GTV + ...
Middle Aged Lung Neoplasms Neoplasm Invasiveness Adenocarcinoma of Lung Machine Learning Aged Humans Prognosis Radiomics Retrospective Studies Cross-Sectional Studies Tomography, X-Ray Computed Male Female
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Deep Learning Radiomics for Survival Prediction in Non-Small-Cell Lung Cancer Patients from CT Images.

Journal of medical systems Feb 11, 2025
This study aims to apply a multi-modal approach of the deep learning method for survival prediction in patients with non-small-cell lung cancer (NSCLC) using CT-based radiomics. We utilized two public data sets from the Cancer Imaging Archive (TCIA) ...
Humans Neural Networks, Computer Aged Tomography, X-Ray Computed Radiomics Female Lung Neoplasms Male Carcinoma, Non-Small-Cell Lung Middle Aged Proportional Hazards Models Deep Learning
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Prediction of High-risk Capsule Characteristics for Recurrence of Pleomorphic Adenoma in the Parotid Gland Based on Habitat Imaging and Peritumoral Radiomics: A Two-center Study.

Academic radiology Feb 10, 2025
RATIONALE AND OBJECTIVES: This study aims to develop and validate an ultrasoundbased habitat imaging and peritumoral radiomics model for predicting high-risk capsule characteristics for recurrence of pleomorphic adenoma (PA) of the parotid gland whil...
Machine Learning Retrospective Studies Female Risk Factors Aged Humans Ultrasonography Neoplasm Recurrence, Local Adult Parotid Gland Radiomics Parotid Neoplasms Male Adenoma, Pleomorphic Middle Aged
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Ultrasonic-Based Radiomics Signature With Machine Learning for Differentiating Prognostic Subsets of Pediatric Peripheral Neuroblastic Tumors: A Retrospective Study.

Ultrasound in medicine & biology Feb 8, 2025
OBJECTIVE: To construct and select a better model based on ultrasonic-based radiomics features and clinical characteristics for prognostic subsets of pediatric neuroblastic tumors.
Machine Learning Male Humans Ultrasonography Infant Neuroblastoma Prognosis Child, Preschool Child Retrospective Studies Female Radiomics
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A Hybrid Machine Learning CT-Based Radiomics Nomogram for Predicting Cancer-Specific Survival in Curatively Resected Colorectal Cancer.

Academic radiology Feb 7, 2025
RATIONALE AND OBJECTIVES: To develop and validate a computed tomography-based radiomics nomogram for cancer-specific survival (CSS) prediction in curatively resected colorectal cancer (CRC), and its performance was compared with the American Joint Co...
Nomograms Neoplasm Staging Colorectal Neoplasms Radiomics Male Middle Aged Prognosis Tomography, X-Ray Computed Female Aged Humans Machine Learning Prospective Studies
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Integration of radiomic and deep features to reliably differentiate benign renal lesions from renal cell carcinoma.

European journal of radiology Feb 7, 2025
PURPOSE: Accurate differentiation of benign renal lesions from renal cell carcinoma (RCC) is crucial for optimized management, particularly for small renal lesions (≤4 cm in diameter). This study aimed to integrate clinical data, radiomic features, a...
Radiomics Male Humans Middle Aged Aged Radiographic Image Interpretation, Computer-Assisted Aged, 80 and over Retrospective Studies Kidney Neoplasms Deep Learning Adult Tomography, X-Ray Computed Carcinoma, Renal Cell Diagnosis, Differential Sensitivity and Specificity Female Reproducibility of Results
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Machine learning assisted radiomics in predicting postoperative occurrence of deep venous thrombosis in patients with gastric cancer.

BMC cancer Feb 7, 2025
BACKGROUND: Gastric cancer patients are prone to lower extremity deep vein thrombosis (DVT) after surgery, which is an important cause of death in postoperative patients. Therefore, it is particularly important to find a suitable way to predict the r...
Male Middle Aged Postoperative Complications Venous Thrombosis Lower Extremity Aged Adult Stomach Neoplasms Radiomics Gastrectomy Humans Machine Learning Algorithms Retrospective Studies Tomography, X-Ray Computed Female Risk Factors
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Integrating manual annotation with deep transfer learning and radiomics for vertebral fracture analysis.

BMC medical imaging Feb 6, 2025
BACKGROUND: Vertebral compression fractures (VCFs) are prevalent in the elderly, often caused by osteoporosis or trauma. Differentiating acute from chronic VCFs is vital for treatment planning, but MRI, the gold standard, is inaccessible for some. Ho...
Female Aged Aged, 80 and over Radiomics Male Humans Retrospective Studies Tomography, X-Ray Computed Spinal Fractures Fractures, Compression Middle Aged Deep Learning ROC Curve Magnetic Resonance Imaging
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A comparison of different machine learning classifiers in predicting xerostomia and sticky saliva due to head and neck radiotherapy using a multi-objective, multimodal radiomics model.

Biomedical physics & engineering express Feb 6, 2025
. Although radiotherapy techniques are a primary treatment for head and neck cancer (HNC), they are still associated with substantial toxicity and side effects. Machine learning (ML) based radiomics models for predicting toxicity mostly rely on featu...
Bayes Theorem Female Saliva Aged Male Humans Adult Xerostomia Middle Aged Radiomics Machine Learning Head and Neck Neoplasms Tomography, X-Ray Computed Support Vector Machine Magnetic Resonance Imaging
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