Examination of the predictive factors of the response to whole brain radiotherapy for brain metastases from lung cancer using MRI

Previous studies have been conducted on the prognostic factors for overall survival in patients with brain metastases (BMs) following whole brain radiotherapy (WBRT). However, there have been a small number of studies regarding the prognostic factors for the response of tumor to WBRT. The aim of the present study was to identify the predictive factors for the response to WBRT from the point of view of reduction of tumor using magnetic resonance imaging. A retrospective analysis of 62 patients with BMs from primary lung cancer treated with WBRT was under-taken. The effects of the following factors on the response to WBRT were evaluated: Age; sex; performance status; lactate dehydrogenase; pathology; existence of extracranial metastases; activity of extracranial disease; chemo-history; chest radiotherapy history; treatment term; γ-knife radiotherapy; diffusion weighted image signal intensity; tumor diameter; extent of edema and the edema/tumor (E/T) ratio. The association between the reduction of tumors and clinical factors was evaluated using logistic regression analysis. P<0.05 was considered to indicate a statistically significant difference. The overall response ratio of this cohort was 54.8%. In the univariate analysis, the response of tumors was associated with the presence of small cell lung carcinoma (SCLC; P=0.0007), an E/T ratio of ≥1.5 (P=0.048), and a median tumor diameter of <20 mm (P=0.014). In the multivariate analysis, the presence of SCLC [P=0.001; odds ratio (OR), 17.152), an E/T ratio of ≥1.5 (P=0.019; OR, 9.526), and the presence of extracranial metastases (P=0.031; OR, 4.875) were revealed to be independent predictive factors for the reduction of tumor. The following 3 factors were significantly associated with the response of tumors to WBRT: The presence of SCLC; an E/T ratio of ≥1.5; and the presence of extracranial metastases. The E/T ratio is a novel index that provides a simple and easy predictive method for use in a clinical setting.