Perfusion Imaging of Brain Tumors Using Arterial Spin-Labeling: Correlation with Histopathologic Vascular Density
Autor: | Satoshi O. Suzuki, Osamu Togao, Shinji Nagata, Masahiro Mizoguchi, Tomoyuki Noguchi, K. Yamashita, A. Hiwatashi, Kouji Kobayashi, Hiroyuki Honda, Toru Iwaki, Takashi Yoshiura, Tomonari Sasaki, Tadahisa Shono, Eiki Nagao, Futoshi Mihara |
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Jazyk: | angličtina |
Rok vydání: | 2008 |
Předmět: |
Adult
Male medicine.medical_specialty Pathology Adolescent Central nervous system Perfusion scanning Correlation Meningeal Neoplasms Medicine Humans Radiology Nuclear Medicine and imaging Child Microvessel Aged Cell Proliferation medicine.diagnostic_test business.industry Brain Neoplasms Microcirculation Brain Magnetic resonance imaging Anatomical pathology Glioma Middle Aged medicine.disease Magnetic Resonance Imaging Lymphoma medicine.anatomical_structure Cerebrovascular Circulation Child Preschool Arterial spin labeling Female Spin Labels Neurology (clinical) business Nuclear medicine Hemangioma Meningioma Neurilemmoma |
Zdroj: | AJNR Am J Neuroradiol |
Popis: | 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. |
Databáze: | OpenAIRE |
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