The Utility and Efficiency Of Diffusion Tensor Imaging Values to Determine Epidermal Growth Factor Receptor Gene Mutation Status in Brain Metastases From Lung Adenocarcinoma: A Preliminary Study

2019 ◽  
Vol 15 ◽  
Author(s):  
Mehmet Ali Gultekin ◽  
Hacı Mehmet Turk ◽  
Ismail Yurtsever ◽  
Bahar Atasoy ◽  
Altay Aliyev ◽  
...  
Keyword(s):  
Brain Metastases ◽  
Lung Adenocarcinoma ◽  
Gene Mutation ◽  
Egfr Mutation ◽  
Wild Type ◽  
Mutation Status ◽  
Egfr Gene ◽  
Group 2 ◽  
Egfr Gene Mutation ◽  
Group 1

Background: We aimed to investigate whether there were any diffusion tensor imaging (DTI) value differences in brain metastases (BM) due to lung adenocarcinoma based on the epidermal growth factor receptor (EGFR) gene mutation status. Material and Methods: 17 patients with 32 solid intracranial metastatic lesions from lung adenocarcinoma were included prospectively. Patients were divided according to the EGFR mutation status as EGFR (+) (group 1, n:8) and EGFR wild type (group 2, n:9). The fractional anisotropy (FA), apparent diffusion coefficient (ADC), normalized ADC (nADC), axial diffusivity (AD), and radial diffusivity (RD) values were measured from the solid component of the metastatic lesions and nADC values were calculated. DTI values were compared between group 1 and group 2. Receiver-operating characteristic analysis was used to obtain cut-off values for the parameters presenting a statistical difference between the EGFR gene mutation positive and wild type group. Results: There were statistically significant differences in measured ADC, nADC, AD, and RD values between group 1 and group 2. The ADC, nADC, AD, and RD values were significantly lower in group 1. There was no significant difference in FA values between two groups. Analysis by the ROC curve method revealed a cut-off value of ≤721 x 10-6 mm2/s for ADC (Sensitivity=72.7, Specificity=85.7); ≤0.820 for nADC (Sensitivity=72.7, Specificity=90.5), ≤886 for AD (Sensitivity=81.8, Specificity=81.0), and ≤588 for RD (Sensitivity=63.6, Specificity=90.5) in differentiating EGFR mutation (+) group from wild type group. Conclusion: Combination of the decreased ADC, nADC, AD, and RD values in BM due to lung adenocarcinoma can be important for predicting the EGFR gene mutation status. DTI features of the brain metastases from lung adenocarcinoma may be utilized to provide insight into the EGFR mutation status and guide the clinicians for initiation of targeted therapy.

scholarly journals Deep CNN Model Using CT Radiomics Feature Mapping Recognizes EGFR Gene Mutation Status of Lung Adenocarcinoma

2021 ◽  
Vol 10 ◽  
Author(s):  
Baihua Zhang ◽  
Shouliang Qi ◽  
Xiaohuan Pan ◽  
Chen Li ◽  
Yudong Yao ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Egfr Mutation ◽  
Ct Images ◽  
Feature Mapping ◽  
Mutation Status ◽  
Egfr Gene ◽  
Non Invasive ◽  
External Test ◽  
Egfr Tki ◽  
Egfr Gene Mutation

To recognize the epidermal growth factor receptor (EGFR) gene mutation status in lung adenocarcinoma (LADC) has become a prerequisite of deciding whether EGFR-tyrosine kinase inhibitor (EGFR-TKI) medicine can be used. Polymerase chain reaction assay or gene sequencing is for measuring EGFR status, however, the tissue samples by surgery or biopsy are required. We propose to develop deep learning models to recognize EGFR status by using radiomics features extracted from non-invasive CT images. Preoperative CT images, EGFR mutation status and clinical data have been collected in a cohort of 709 patients (the primary cohort) and an independent cohort of 205 patients. After 1,037 CT-based radiomics features are extracted from each lesion region, 784 discriminative features are selected for analysis and construct a feature mapping. One Squeeze-and-Excitation (SE) Convolutional Neural Network (SE-CNN) has been designed and trained to recognize EGFR status from the radiomics feature mapping. SE-CNN model is trained and validated by using 638 patients from the primary cohort, tested by using the rest 71 patients (the internal test cohort), and further tested by using the independent 205 patients (the external test cohort). Furthermore, SE-CNN model is compared with machine learning (ML) models using radiomics features, clinical features, and both features. EGFR(-) patients show the smaller age, higher odds of female, larger lesion volumes, and lower odds of subtype of acinar predominant adenocarcinoma (APA), compared with EGFR(+). The most discriminative features are for texture (614, 78.3%) and the features of first order of intensity (158, 20.1%) and the shape features (12, 1.5%) follow. SE-CNN model can recognize EGFR mutation status with an AUC of 0.910 and 0.841 for the internal and external test cohorts, respectively. It outperforms the CNN model without SE, the fine-tuned VGG16 and VGG19, three ML models, and the state-of-art models. Utilizing radiomics feature mapping extracted from non-invasive CT images, SE-CNN can precisely recognize EGFR mutation status of LADC patients. The proposed method combining radiomics features and deep leaning is superior to ML methods and can be expanded to other medical applications. The proposed SE-CNN model may help make decision on usage of EGFR-TKI medicine.

scholarly journals Effect of platinum-based chemotherapy on EGFR gene mutation status in lung adenocarcinoma

Medicine ◽  
2018 ◽  
Vol 97 (4) ◽  
pp. e9602 ◽  
Author(s):  
Yuli Wang ◽  
Xinyu Ma ◽  
Yuan Wei ◽  
Di Ma ◽  
Ping Gong
Keyword(s):  
Lung Adenocarcinoma ◽  
Gene Mutation ◽  
Mutation Status ◽  
Egfr Gene ◽  
Platinum Based Chemotherapy ◽  
Egfr Gene Mutation

scholarly journals Detected EGFR mutation in cerebrospinal fluid of lung adenocarcinoma patients with meningeal metastasis

Open Medicine ◽  
2016 ◽  
Vol 11 (1) ◽  
pp. 93-96 ◽  
Author(s):  
Jiang Rong ◽  
Ma Chunhua ◽  
Lv Yuan ◽  
Mu Ning ◽  
Li Jinduo ◽  
...  
Keyword(s):  
Cerebrospinal Fluid ◽  
Lung Adenocarcinoma ◽  
Gene Mutation ◽  
Direct Sequencing ◽  
Gene Mutations ◽  
Egfr Mutations ◽  
Egfr Gene ◽  
Sequencing Method ◽  
Direct Sequencing Method ◽  
Egfr Gene Mutation

AbstractObjectiveTo discuss the application of ARMS method to detect EGFR gene mutation in cerebrospinal fluid of lung adenocarcinoma patients with meningeal metastasis.Methods5 cases of lung adenocarcinoma were identified with meningeal metastasis that were cleared EGFR gene mutation by gene sequencing method. From each patient 5ml cerebrospinal fluid was obtained by lumbar puncture. ARMS method was used to detect EGFR mutations in cerebrospinal fluid.Results5 samples of cerebrospinal fluid were successfully detected by ARMS method, 3 samples found that EGFR gene mutations, the mutations in line with direct sequencing method.ConclusionARMS method can be used to detect EGFR gene mutations of cerebrospinal fluid samples in lung adenocarcinoma with meningeal metastasis. But cerebrospinal fluid specimens from histological specimens, blood samples need to be confirmed by further comparative study whether there is advantage.

Assessing EGFR gene mutation status in non-small cell lung cancer with imaging features from PET/CT

2019 ◽  
Vol 40 (8) ◽  
pp. 842-849 ◽  
Author(s):  
Mengmeng Jiang ◽  
Yiqian Zhang ◽  
Junshen Xu ◽  
Min Ji ◽  
Yinglong Guo ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Gene Mutation ◽  
Small Cell ◽  
Imaging Features ◽  
Small Cell Lung ◽  
Mutation Status ◽  
Egfr Gene ◽  
Pet Ct ◽  
Egfr Gene Mutation

EGFR gene copy number alterations are not a useful screening tool for predicting EGFR mutation status in lung adenocarcinoma

Pathology ◽  
2014 ◽  
Vol 46 (1) ◽  
pp. 32-36
Author(s):  
Prudence A. Russell ◽  
Y.U. Yong ◽  
D.O. Hongdo ◽  
Timothy D. Clay ◽  
Melissa M. Moore ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Copy Number ◽  
Screening Tool ◽  
Egfr Mutation ◽  
Gene Copy Number ◽  
Gene Copy ◽  
Copy Number Alterations ◽  
Mutation Status ◽  
Egfr Gene

scholarly journals Brain metastases in lung adenocarcinoma: impact of EGFR mutation status on incidence and survival

2014 ◽  
Vol 48 (2) ◽  
pp. 173-183 ◽  
Author(s):  
Karmen Stanic ◽  
Matjaz Zwitter ◽  
Nina Turnsek Hitij ◽  
Izidor Kern ◽  
Aleksander Sadikov ◽  
...  
Keyword(s):  
Brain Metastases ◽  
Lung Adenocarcinoma ◽  
Cumulative Incidence ◽  
Egfr Mutation ◽  
Growth Factor Receptor ◽  
Egfr Mutations ◽  
Mutation Status ◽  
Course Of Disease ◽  
Epidermal Growth ◽  
Egfr Mutant

AbstractBackground. The brain represents a frequent progression site in lung adenocarcinoma. This study was designed to analyse the association between the epidermal growth factor receptor (EGFR) mutation status and the frequency of brain metastases (BM) and survival in routine clinical practice.Patients and methods. We retrospectively analysed the medical records of 629 patients with adenocarcinoma in Slovenia who were tested for EGFR mutations in order to analyse the cumulative incidence of BM, the time from the diagnosis to the development of BM (TDBM), the time from BM to death (TTD) and the median survival.Results. Out of 629 patients, 168 (27%) had BM, 90 patients already at the time of diagnosis. Additional 78 patients developed BM after a median interval of 14.3 months; 25.8 months in EGFR positive and 11.8 months in EGFR negative patients, respectively (p = 0.002). EGFR mutations were present in 47 (28%) patients with BM. The curves for cumulative incidence of BM in EGFR positive and negative patients demonstrate a trend for a higher incidence of BM in EGFR mutant patients at diagnosis (19% vs. 13%, p = 0.078), but no difference later during the course of the disease. The patients with BM at diagnosis had a statistically longer TTD (7.3 months) than patients who developed BM later (3.1 months). The TTD in EGFR positive patients with BM at diagnosis was longer than in EGFR negative patients (12.6 vs. 6.8, p = 0.005), while there was no impact of EGFR status on the TTD of patients who developed BM later.Conclusions. Except for a non-significant increase of frequency of BM at diagnosis in EGFR positive patients, EGFR status had no influence upon the cumulative incidence of BM. EGFR positive patients had a longer time to CNS progression. While EGFR positive patients with BM at diagnosis had a longer survival, EGFR status had no influence on TTD in patients who developed BM later during the course of disease.

LATE-BREAKING ABSTRACT: Treatment efficacy of afatinib vs gefitinib in lung adenocarcinoma with EGFR gene mutation

2016 ◽  
Author(s):  
Marisol Arroyo Hernandez ◽  
Alexander J. Alatorre ◽  
Julio C. Garibay ◽  
José F. Escobar ◽  
Jerónimo Rodríguez
Keyword(s):  
Lung Adenocarcinoma ◽  
Gene Mutation ◽  
Treatment Efficacy ◽  
Egfr Gene ◽  
Egfr Gene Mutation
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