4.6 Article

Dynamic contrast-enhanced MRI perfusion for differentiating between melanoma and lung cancer brain metastases

期刊

CANCER MEDICINE
卷 6, 期 4, 页码 761-767

出版社

WILEY
DOI: 10.1002/cam4.1046

关键词

Brain tumors; melanoma; neuroimaging; non-small cell lung cancer; perfusion weighted MRI

类别

资金

  1. National Institutes of Health/NCI Cancer Center [P30 CA008748]

向作者/读者索取更多资源

Brain metastases originating from different primary sites overlap in appearance and are difficult to differentiate with conventional MRI. Dynamic contrast-enhanced (DCE)-MRI can assess tumor microvasculature and has demonstrated utility in characterizing primary brain tumors. Our aim was to evaluate the performance of plasma volume (Vp) and volume transfer coefficient (K-trans) derived from DCE-MRI in distinguishing between melanoma and nonsmall cell lung cancer (NSCLC) brain metastases. Forty-seven NSCLC and 23 melanoma brain metastases were retrospectively assessed with DCE-MRI. Regions of interest were manually drawn around the metastases to calculate Vp(mean) and Kmeantrans. The Mann-Whitney U test and receiver operating characteristic analysis (ROC) were performed to compare perfusion parameters between the two groups. The Vp(mean) of melanoma brain metastases (4.35, standard deviation [SD]=1.31) was significantly higher (P=0.03) than Vp(mean) of NSCLC brain metastases (2.27, SD=0.96). The Kmeantrans values were higher in melanoma brain metastases, but the difference between the two groups was not significant (P=0.12). Based on ROC analysis, a cut-off value of 3.02 for Vp(mean) (area under curve=0.659 with SD=0.074) distinguished between melanoma brain metastases and NSCLC brain metastases (P<0.01) with 72% specificity. Our data show the DCE-MRI parameter Vp(mean) can differentiate between melanoma and NSCLC brain metastases. The ability to noninvasively predict tumor histology of brain metastases in patients with multiple malignancies can have important clinical implications.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据