Article

CT delta-radiomics for identification of advanced EGFR-Mutated lung adenocarcinoma Sensitive to Therapies Targeting EGFR Pathway

2022-06-22

Abstract excerpt

<h4>Purpose: </h4> In this study, a non-invasive radiomics method was used to extract a large amount of valuable information from patient CT images (including pre-treatment and follow-up images), and the image features were effectively combined with treatment effect evaluation, aiming to solve the problem of lung adenocarcinoma in patients with EGFR mutation positive. The early efficacy evaluation of cancer EGFR-T...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: e0f6ac0d-3e8d-58f8-97ff-e7af032ed3a1
DOI: 10.21203/rs.3.rs-1746619/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

CT delta-radiomics for identification of advanced EGFR-Mutated lung adenocarcinoma Sensitive to Therapies Targeting EGFR PathwayDOI 10.21203/rs.3.rs-1746619/v1Read

The Potential of Radiomics Nomogram in Non-invasively Prediction of Epidermal Growth Factor Receptor Mutation Status and Subtypes in Lung AdenocarcinomaSemantic proximity Read

Radiomics Analysis to Enhance Precise Identification of Epidermal Growth Factor Receptor Mutation Based on Positron Emission Tomography Images of Lung Cancer Patients.Semantic proximity Read

Accurate prediction of epidermal growth factor receptor mutation status in early-stage lung adenocarcinoma, using radiomics and clinical features.Semantic proximity Read

Radiomics combined with clinical characteristics predicted the progression-free survival time in first-line targeted therapy for advanced non-small cell lung cancer with EGFR mutationSemantic proximity Read

Integrated CT-derived radiomics for predicting ctDNA status and prognosis in resectable non-small cell lung cancerSemantic proximity Read

A novel radiomic nomogram for predicting epidermal growth factor receptor mutation in peripheral lung adenocarcinoma.Semantic proximity Read

[The value of CT radiomics in the prediction of EGFR mutation in lung cancer].Semantic proximity Read

Using Multi-phase CT Radiomics Features to Predict EGFR Mutation Status in Lung Adenocarcinoma Patients.Semantic proximity Read

Prediction of EGFR Mutation Status in Non-small Cell Lung Cancer Based on Multiparametric MRI RadiomicsSemantic proximity Read

Application value of CT radiomic nomogram in predicting T790M mutation of lung adenocarcinoma.Semantic proximity Read

Machine learning models predict overall survival and progression free survival of non-surgical esophageal cancer patients with chemoradiotherapy based on CT image radiomics signaturesSemantic proximity Read