Perfusion imaging of brain tumors using arterial spin-labeling: Correlation with histopathologic vascular density

Tomoyuki Noguchi, T. Yoshiura, A. Hiwatashi, O. Togao, K. Yamashita, E. Nagao, T. Shono, M. Mizoguchi, S. Nagata, T. Sasaki, S. O. Suzuki, T. Iwaki, K. Kobayashi, F. Mihara, H. Honda

Research output: Contribution to journalArticlepeer-review

155 Citations (Scopus)

Abstract

BACKGROUND AND PURPOSE: We investigated the relationship between tumor blood-flow measurement based on perfusion imaging by arterial spin-labeling (ASL-PI) and histopathologic findings in brain tumors. MATERIALS AND METHODS: We used ASL-PI to examine 35 patients with brain tumors, including 11 gliomas, 9 meningiomas, 9 schwannomas, 1 diffuse large B-cell lymphoma, 4 hemangioblastomas, and 1 metastatic brain tumor. As an index of tumor perfusion, the relative signal intensity (SI) of each tumor (%Signal intensity) was determined as a percentage of the maximal SI within the tumor per averaged SI within normal cerebral gray matter on ASL-PI. Relative vascular attenuation (%Vessel) was determined as the total microvessel area per the entire tissue area on CD-34-immunostained histopathologic specimens. MIB1 indices of gliomas were also calculated. The differences in %Signal intensity among different histopathologic types and between high- and low-grade gliomas were compared. In addition, the correlations between %Signal intensity and %Vessel or MIB1 index were evaluated in gliomas. RESULTS: Statistically significant differences in %Signal intensity were observed between hemangioblastomas versus gliomas (P < .005), meningiomas (P < .05), and schwannomas (P < .005). Among gliomas, %Signal intensity was significantly higher for high-grade than for low-grade tumors (P < .05). Correlation analyses revealed significant positive correlations between %Signal intensity and %Vessel in 35 patients, including all 6 histopathologic types (rs = 0.782, P < .00005) and in gliomas (rs = 0.773, P < .05). In addition, in gliomas, %Signal intensity and MIB1 index were significantly positively correlated (rs = 0.700, P < .05). CONCLUSION: ASL-PI may predict histopathologic vascular densities of brain tumors and may be useful in distinguishing between high- and low-grade gliomas and in differentiating hemangioblastomas from other brain tumors.

Original languageEnglish
Pages (from-to)688-693
Number of pages6
JournalAmerican Journal of Neuroradiology
Volume29
Issue number4
DOIs
Publication statusPublished - Apr 2008

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging
  • Clinical Neurology

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