W S Jung1,2, C H Park1, C-K Hong3, S H Suh1, S J Ahn4. 1. From the Departments of Radiology (W.S.J., C.H.P., S.H.S., S.J.A.). 2. Department of Radiology (W.S.J.), Ajou University School of Medicine, Suwon, Korea. 3. Neurosurgery (C.-K.H.), Gangnam Severance Hospital, Yonsei University, College of Medicine, Seoul, Korea. 4. From the Departments of Radiology (W.S.J., C.H.P., S.H.S., S.J.A.) aahng77@yuhs.ac.
Abstract
BACKGROUND AND PURPOSE: Development of noninvasive imaging biomarkers indicating the histology and the gene mutation status of brain metastasis from lung cancer is important. We aimed to investigate diffusion-weighted imaging parameters as predictors of the histology and gene mutations of brain metastasis from lung cancer. MATERIALS AND METHODS: DWI data for 74 patients with brain metastasis from lung cancer were retrospectively reviewed. The patients were first grouped according to the primary tumor histology (adenocarcinoma, small-cell lung cancer, squamous cell carcinoma), and those with adenocarcinoma were further divided into epidermal growth factor receptor (EFGR) mutation-positive and wild type groups. Sex; age; number, size, and location of brain metastasis; DWI visual scores; the minimum ADC; and the normalized ADC ratio were compared among groups using χ2 and ANOVA. Multiple logistic regression analysis was performed to determine independent predictors of the EGFR mutation. RESULTS: The minimum ADC was lower in the small-cell lung cancer group than in the other 2 groups, though the difference was not significant. Furthermore, minimum ADC and the normalized ADC ratio were significantly lower in the EGFR mutation-positive group than in the wild type group (P = .021 and .014, respectively). Multivariate analysis revealed that minimum ADC and the normalized ADC ratio were independently associated with the EGFR mutation status (P = .028 and .021, respectively). CONCLUSIONS: Our results suggest that DWI parameters (minimum ADC and normalized ADC ratio) for the solid components of brain metastasis from lung cancer are not correlated with their histology, whereas they can predict the EGFR mutation status in brain metastasis from lung adenocarcinoma.
BACKGROUND AND PURPOSE: Development of noninvasive imaging biomarkers indicating the histology and the gene mutation status of brain metastasis from lung cancer is important. We aimed to investigate diffusion-weighted imaging parameters as predictors of the histology and gene mutations of brain metastasis from lung cancer. MATERIALS AND METHODS: DWI data for 74 patients with brain metastasis from lung cancer were retrospectively reviewed. The patients were first grouped according to the primary tumor histology (adenocarcinoma, small-cell lung cancer, squamous cell carcinoma), and those with adenocarcinoma were further divided into epidermal growth factor receptor (EFGR) mutation-positive and wild type groups. Sex; age; number, size, and location of brain metastasis; DWI visual scores; the minimum ADC; and the normalized ADC ratio were compared among groups using χ2 and ANOVA. Multiple logistic regression analysis was performed to determine independent predictors of the EGFR mutation. RESULTS: The minimum ADC was lower in the small-cell lung cancer group than in the other 2 groups, though the difference was not significant. Furthermore, minimum ADC and the normalized ADC ratio were significantly lower in the EGFR mutation-positive group than in the wild type group (P = .021 and .014, respectively). Multivariate analysis revealed that minimum ADC and the normalized ADC ratio were independently associated with the EGFR mutation status (P = .028 and .021, respectively). CONCLUSIONS: Our results suggest that DWI parameters (minimum ADC and normalized ADC ratio) for the solid components of brain metastasis from lung cancer are not correlated with their histology, whereas they can predict the EGFR mutation status in brain metastasis from lung adenocarcinoma.
Authors: Sebastian Johannes Müller; Eya Khadhraoui; Nicole E Neef; Christian Heiner Riedel; Marielle Ernst Journal: BMC Med Imaging Date: 2021-04-15 Impact factor: 1.930
Authors: Jihwan Yoo; Yoon Jin Cha; Hun Ho Park; Mina Park; Bio Joo; Sang Hyun Suh; Sung Jun Ahn Journal: Cancers (Basel) Date: 2022-03-26 Impact factor: 6.639