Literature DB >> 18079184

Apparent diffusion coefficient and cerebral blood volume in brain gliomas: relation to tumor cell density and tumor microvessel density based on stereotactic biopsies.

N Sadeghi1, N D'Haene, C Decaestecker, M Levivier, T Metens, C Maris, D Wikler, D Baleriaux, I Salmon, S Goldman.   

Abstract

BACKGROUND AND
PURPOSE: MR imaging-based apparent diffusion coefficient (ADC) and regional cerebral blood volume (rCBV) measurements have been related respectively to both cell and microvessel density in brain tumors. However, because of the high degree of heterogeneity in gliomas, a direct correlation between these MR imaging-based measurements and histopathologic features is required. The purpose of this study was to correlate regionally ADC and rCBV values with both cell and microvessel density in gliomas, by using coregistered MR imaging and stereotactic biopsies.
MATERIALS AND METHODS: Eighteen patients (9 men, 9 women; age range, 19-78 years) with gliomas underwent diffusion-weighted and dynamic susceptibility contrast-enhanced MR imaging before biopsy. Eighty-one biopsy samples were obtained and categorized as peritumoral, infiltrated tissue, or bulk tumor, with quantification of cell and microvessel density. ADC and rCBV values were measured at biopsy sites and were normalized to contralateral white matter on corresponding maps coregistered with a 3D MR imaging dataset. ADC and rCBV ratios were compared with quantitative histologic features by using the Spearman correlation test.
RESULTS: The highest correlations were found within bulk tumor samples between rCBV and cell density (r=0.57, P < .001) and rCBV and microvessel density (r=0.46, P < .01). An inverse correlation was found between ADC and microvessel density within bulk tumor (r=-0.36, P < .05), whereas no significant correlation was found between ADC and cell density.
CONCLUSION: rCBV regionally correlates with both cell and microvessel density within gliomas, whereas no regional correlation was found between ADC and cell density.

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Year:  2007        PMID: 18079184      PMCID: PMC8118877          DOI: 10.3174/ajnr.A0851

Source DB:  PubMed          Journal:  AJNR Am J Neuroradiol        ISSN: 0195-6108            Impact factor:   3.825


  36 in total

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8.  A prognostic model based on preoperative MRI predicts overall survival in patients with diffuse gliomas.

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9.  Radiomics in peritumoral non-enhancing regions: fractional anisotropy and cerebral blood volume improve prediction of local progression and overall survival in patients with glioblastoma.

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