AIMC Topic: ErbB Receptors

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A deep learning model integrating multisequence MRI to predict EGFR mutation subtype in brain metastases from non-small cell lung cancer.

European radiology experimental Jan 2, 2024
BACKGROUND: To establish a predictive model based on multisequence magnetic resonance imaging (MRI) using deep learning to identify wild-type (WT) epidermal growth factor receptor (EGFR), EGFR exon 19 deletion (19Del), and EGFR exon 21-point mutation...
Humans Retrospective Studies Brain Neoplasms Magnetic Resonance Imaging Mutation ErbB Receptors Deep Learning Lung Neoplasms Carcinoma, Non-Small-Cell Lung
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A multi-task deep learning model for EGFR genotyping prediction and GTV segmentation of brain metastasis.

Journal of translational medicine Nov 7, 2023
BACKGROUND: The precise prediction of epidermal growth factor receptor (EGFR) mutation status and gross tumor volume (GTV) segmentation are crucial goals in computer-aided lung adenocarcinoma brain metastasis diagnosis. However, these two tasks prese...
Humans Brain Neoplasms Deep Learning Image Processing, Computer-Assisted Lung Neoplasms Genotype ErbB Receptors
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A CT-based Deep Learning Radiomics Nomogram for the Prediction of EGFR Mutation Status in Head and Neck Squamous Cell Carcinoma.

Academic radiology Jul 21, 2023
RATIONALE AND OBJECTIVES: Accurately assessing epidermal growth factor receptor (EGFR) mutation status in head and neck squamous cell carcinoma (HNSCC) patients is crucial for prognosis and treatment selection. This study aimed to construct and valid...
Tomography, X-Ray Computed Radiomics Deep Learning Humans Retrospective Studies Mutation ErbB Receptors Nomograms Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms
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High accuracy epidermal growth factor receptor mutation prediction via histopathological deep learning.

BMC pulmonary medicine Jul 5, 2023
BACKGROUND: The detection of epidermal growth factor receptor (EGFR) mutations in patients with non-small cell lung cancer is critical for tyrosine kinase inhibitor therapy. EGFR detection requires tissue samples, which are difficult to obtain in som...
Humans ErbB Receptors Adenocarcinoma Carcinoma, Non-Small-Cell Lung Mutation Deep Learning Lung Neoplasms
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Plasma Exosome Analysis for Protein Mutation Identification Using a Combination of Raman Spectroscopy and Deep Learning.

ACS sensors Jun 6, 2023
Protein mutation detection using liquid biopsy can be simply performed periodically, making it easy to detect the occurrence of newly emerging mutations rapidly. However, it has low diagnostic accuracy since there are more normal proteins than mutate...
Carcinoma, Non-Small-Cell Lung Mutation Exosomes ErbB Receptors Protein Kinase Inhibitors Deep Learning Lung Neoplasms Spectrum Analysis, Raman Humans
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Predicting survival after radiosurgery in patients with lung cancer brain metastases using deep learning of radiomics and EGFR status.

Physical and engineering sciences in medicine Mar 1, 2023
The early prediction of overall survival (OS) in patients with lung cancer brain metastases (BMs) after Gamma Knife radiosurgery (GKRS) can facilitate patient management and outcome improvement. However, the disease progression is influenced by multi...
ErbB Receptors Humans Retrospective Studies Brain Neoplasms Deep Learning Lung Neoplasms Radiosurgery
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A radiomics-based deep learning approach to predict progression free-survival after tyrosine kinase inhibitor therapy in non-small cell lung cancer.

Cancer imaging : the official publication of the International Cancer Imaging Society Jan 20, 2023
BACKGROUND: The epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) are a first-line therapy for non-small cell lung cancer (NSCLC) with EGFR mutations. Approximately half of the patients with EGFR-mutated NSCLC are treated with...
Humans Deep Learning Lung Neoplasms Carcinoma, Non-Small-Cell Lung Mutation Progression-Free Survival ErbB Receptors Disease-Free Survival Protein Kinase Inhibitors Tyrosine Kinase Inhibitors
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Histopathologic Basis for a Chest CT Deep Learning Survival Prediction Model in Patients with Lung Adenocarcinoma.

Radiology Jul 5, 2022
Background A preoperative CT-based deep learning (DL) prediction model was proposed to estimate disease-free survival in patients with resected lung adenocarcinoma. However, the black-box nature of DL hinders interpretation of its results. Purpose To...
Adenocarcinoma Humans Deep Learning ErbB Receptors Aged Retrospective Studies Adenocarcinoma of Lung Lung Neoplasms Male Tomography, X-Ray Computed Middle Aged Female
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Xprediction: Explainable EGFR-TKIs response prediction based on drug sensitivity specific gene networks.

PloS one May 18, 2022
In recent years, drug sensitivity prediction has garnered a great deal of attention due to the growing interest in precision medicine. Several computational methods have been developed for drug sensitivity prediction and the identification of related...
Gene Regulatory Networks Neural Networks, Computer ErbB Receptors Machine Learning Drug Resistance
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Predicting EGFR mutation status by a deep learning approach in patients with non-small cell lung cancer brain metastases.

Journal of neuro-oncology Feb 4, 2022
PURPOSE: Non-small cell lung cancer (NSCLC) tends to metastasize to the brain. Between 10 and 60% of NSCLCs harbor an activating mutation in the epidermal growth-factor receptor (EGFR), which may be targeted with selective EGFR inhibitors. However, d...
Mutation ErbB Receptors Lung Neoplasms Carcinoma, Non-Small-Cell Lung Humans Prospective Studies Retrospective Studies Brain Neoplasms Deep Learning
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