Lung adenocarcinoma: Assessment of epidermal growth factor receptor mutation status based on extended models of diffusion‐weighted image. Issue 1 (5th January 2017)

• Record Type: Journal Article
• Authors: Yuan, Mei; Pu, Xue‐Hui; Xu, Xiao‐Quan; Zhang, Yu‐Dong; Zhong, Yan; Li, Hai; Wu, Jiang‐Fen; Yu, Tong‐Fu
• Is Part Of: Journal of magnetic resonance imaging. Volume 46:Issue 1(2017)
• Page Start: 281
• Page End: 289
• Publication Date: 2017-01-05
• Subjects: adenocarcinoma of lung -- diffusion magnetic resonance imaging -- receptor -- epidermal growth factor -- diffusion -- mutations; Magnetic resonance imaging -- Periodicals; 616
• DOI: 10.1002/jmri.25572
• Languages: English
• ISSNs: 1053-1807

Abstract

Abstract : Purpose: To evaluate the diagnostic performance of extended models of diffusion‐weighted (DW) imaging to help differentiate the epidermal growth factor receptor (EGFR) mutation status in stage IIIA‐IV lung adenocarcinoma. Materials and Methods: This retrospective study had institutional research board approval and was HIPAA compliant. Preoperative extended DW imaging including intravoxel incoherent motion (IVIM) and diffusional kurtosis imaging (DKI) 3 Tesla MRI were retrospectively evaluated in 53 patients with pathologically confirmed non‐early stage (IIIA‐IV) lung adenocarcinoma. EGFR mutationsat exons 18–21 were determined by using polymerase chain reaction‐based ARMS. Quantitative parameters (mean, kurtosis, skewness, 10 th and 90 th percentiles) of IVIM (true‐diffusion coefficient D, pseudo‐diffusion coefficient D*, and perfusion fraction f) and DKI (kurtosis value Kapp, kurtosis corrected diffusion coefficient Dapp) were calculated by outlining entire‐volume histogram analysis. Receiver operating characteristic analysis was constructed to determine the diagnostic performance of each parameter. Multivariate logistic regression was used to differentiate the probability of EGFR mutation status. Results: Twenty‐four of 53 patients with lung adenocarcinoma were EGFR mutations, which occurred most often in acinar (10 of 13 [76.9%]) and papillary predominant tumors (9 of 13 [69.2%]). Patients with EGFR mutation showed significant higher 10 th percentile of D, lower D* value in terms of kurtosis, and lower Kapp value in terms of mean, skewness, 10 th and 90 th percentiles (all P values < 0.05). The 90 th Kapp showed significantly higher sensitivity (97%; P < 0.05) and Az (0.817; P < 0.05) value. Multivariate logistic regression showed 90 th Kapp was a independent factor for determining EGFR mutation with odds ratio ‐1.657. Conclusion: Multiple IVIM and DKI parameters, especially the histogram 90 th Kapp value, helped differentiate EGFR mutation status in stage IIIA‐IV lung adenocarcinoma. Level of Evidence: 3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:281–289