Dynamic contrast-enhanced MRI perfusion for differentiating between melanoma and lung cancer brain metastases. Academic Article uri icon

Overview

abstract

  • 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 (Ktrans ) 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 Vpmean and Kmeantrans. The Mann-Whitney U test and receiver operating characteristic analysis (ROC) were performed to compare perfusion parameters between the two groups. The Vpmean of melanoma brain metastases (4.35, standard deviation [SD] = 1.31) was significantly higher (P = 0.03) than Vpmean 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 Vpmean (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 Vpmean 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.

publication date

  • March 17, 2017

Research

keywords

  • Brain Neoplasms
  • Carcinoma, Non-Small-Cell Lung
  • Contrast Media
  • Lung Neoplasms
  • Melanoma

Identity

PubMed Central ID

  • PMC5387174

Scopus Document Identifier

  • 85016394579

Digital Object Identifier (DOI)

  • 10.1002/cam4.1046

PubMed ID

  • 28303695

Additional Document Info

volume

  • 6

issue

  • 4