The Role of Preload and Leakage Correction in Gadolinium-Based Cerebral Blood Volume Estimation Determined by Comparison with MION as a Criterion Standard

Abstract

BACKGROUND AND PURPOSE Contrast extravasation in DSC-MRI potentiates inaccurate and imprecise estimates of glioma rCBV. We tested assertions that preload and postprocessing algorithms minimize this error by comparing Gd-rCBV using permutations of these 2 techniques with criterion standard rCBV using MION, an intravascular agent. MATERIALS AND METHODS We imaged 7 Fisher rats with 9L gliosarcomas, by using 3T gradient-echo DSC-MRI with MION (2.0 mg Fe/kg) and staged injection of Gd-diethylene triamine pentaacetic acid: a 0.1-mmol/kg bolus provided no preload (P−) data and served as preload (P+) for a subsequent 0.2-mmol/kg bolus. We computed MION-rCBV (steady-state ΔR2*, tumor versus normal brain) and Gd-rCBV ΔR2* [t] integration) without (C−) and with (C+) postprocessing correction, thereby testing 4 correction permutations: P−C−, P−C+, P+C−, and P+C+. We tested whether each permutation reduced bias and variance of the Gd/MION rCBV differences by using generalized estimating equations and Fmax statistics (P < .05 significant). RESULTS Gd-rCBV progressively better approximated MION-rCBV with increasing leakage correction. There was no statistically significant bias for the mean percentage deviation of Gd-rCBV from MION-rCBV for any correction permutation, but there was significantly reduced variance by using P+C− (22-fold), P−C+ (32-fold), and P+C+ (267-fold) compared with P−C−. P+C+ provided significant additional variance reduction compared with P+C− (12-fold) and P−C+ (8-fold). Linear regression of Gd-rCBV versus MION-rCBV revealed P+C+ to have the closest slope and intercept compared with the ideal, substantially better than P+C−. CONCLUSIONS Preload and postprocessing correction significantly reduced the variance of Gd-rCBV estimates, and bias reduction approached significance. Postprocessing correction provide significant benefit beyond preload alone.

Correlation of 3D Arterial Spin Labeling and Multi-Parametric Dynamic Susceptibility Contrast Perfusion MRI in Brain Tumors

“…The physiologic and experimental mechanisms of the parameter should be defined well in future studies. In this work, we did not use a pre -dose of contrast agent or leakage correction to compensate T1 leakage effect of Gd when obtains DSC MRI parameters, which is possible to affect the estimation accuracy (1).…”

“…It relies on the first passage of contrast agent through the brain tissue (1) and allows estimation of multiple perfusion parameters, such as relative cerebral blood volume (rCBV), relative cerebral blood flow (rCBF), mean transit time (MTT), and time to maximum (Tmax) of the residue function with deconvolution. Of these DSC parameters, rCBV and rCBF are commonly used for brain tumor perfusion, including grading (2, 3), diagnosing (3 -5), monitoring treatment (6), differentiating tumor recurrence from radiation necrosis (1, 7) etc.…”

Comparison of the Diagnostic Accuracy of DSC- and Dynamic Contrast-Enhanced MRI in the Preoperative Grading of Astrocytomas

“…In clinical practice, DSC imaging remains the most commonly used perfusion technique and provides semiquantitative measurements such as relative CBV (rCBV), which can be influenced by the presence of susceptibility artifacts and contrast leakage from tumor vessels. 5,6 Dynamic contrast-enhanced (DCE)-MR imaging is an alternate technique that can potentially provide absolute values of plasma volume (Vp) and a measurement of vascular permeability referred to as the volume transfer constant (K trans ). This technique generally involves additional measurements and postprocessing steps.…”

Evaluation of Microvascular Permeability with Dynamic Contrast-Enhanced MRI for the Differentiation of Primary CNS Lymphoma and Glioblastoma: Radiologic-Pathologic Correlation

“…This model is based on the assumption that in brain tumors with substantial BBB breakdown, contrast agent extravasates into the extravascular extracellular space, thereby reducing the T2* DSC-PWI signal-intensity loss by signal-intensity increase in regions where T1 effects are significant. 21,22 In such instances, CBV will be underestimated. Therefore Boxerman et al 21,22 and Weisskoff et al 23 proposed a mathematic leakage-correction model in which linear fitting is used to determine the voxelwise deviation from nonleaky reference tissue and, by removing the leakage term, allowing generation of both corrected CBV maps and first-order estimates of vascular permeability.…”