Correlation of MR perfusion imaging and vessel tortuosity parameters in assessment of intracranial neoplasms

Abstract

Advances in noninvasive imaging techniques such as magnetic resonance perfusion imaging have been found useful in grading cerebral neoplasms and have potential for significant clinical benefit. The purpose of this study was to determine the correlation between tumor vessel tortuosity as measured from vessels extracted from magnetic resonance angiograms (MRA) and perfusion parameters of cerebral blood flow (CBF) and cerebral blood volume (CBV) in intracranial neoplasms. We hypothesized that tumor blood vessel tortuosity measures and perfusion measures would be correlated, since both are increased by tumor angiogenesis. 18 patients with 19 cerebral neoplasms were evaluated with conventional MR imaging and dynamic contrast-enhanced T2-weighted perfusion MR imaging (PWI). Both benign and malignant lesions were included, as were hyper- and hypovascular tumors. Regions of interest were plotted within the tumor area to locate foci of maximum CBV and CBF. CBV and CBF measurements were also recorded in contralateral normal appearing white matter to calculate relative CBV (rCBV) and relative CBF (rCBF). Vessel tortuosity analyses were conducted upon vessels segmented from MRA images of the same patients using two tortuosity descriptors (SOAM and ICM), which have previously been demonstrated to have efficacy in separating benign from malignant disease. Linear regression analyses were conducted to determine if correlations exist between CBV or CBF and the two tortuosity measurements. For the overall set of tumors, no significant correlations were found between flow or volume measures and the tortuosity measures. However, when the 7 glioblastoma multiforme tumors were examined as a subgroup, the following significant correlations were found: rCBV and SOAM (R2=0.799), rCBV and ICM (R2=0.214). Our results demonstrate that MR perfusion imaging data do not correlate significantly with vessel tortuosity parameters as determined from the larger vessels seen by MRA. However, for subgroups of a particular tumor type such as GBM, there may be significant correlations. It appears that perfusion and tortuosity data may provide independently useful data in the assessment of cerebral neoplasms.

Figure 1

Linear correlations between (a) normalized cerebral blood flow (nlCBF) and the vessel tortuosity parameter Sum of Angles Metric (SOAM); (b) nlCBF and the vessel tortuosity parameter Inflection Count Metric (ICM); (c) normalized cerebral blood volume (nlCBV) and SOAM; (d) nlCBV and ICM are shown. Correlation coefficients are given. hypervascularity are present, will also exhibit abnormalities detectable by the ICM. More information on the mathematical definition of these measures is found in (9).