This study aimed to compare Intravoxel Incoherent Motion (IVIM) to more established measures of perfusion; Arterial Spin Labelling (ASL), Dynamic Contrast Enhanced (DCE) and Dynamic Contrast Susceptibility (DSC) imaging, both in tumours and white matter, with the link between IVIM and tracer kinetics proposed for over 20 years¹. This study may be of interest to neuroradiologists and clinical scientists.

Whole brain multiparametric MR data sets were acquired from 11 patients with suspected malignant brain pathologies following consent using a 3.0T system and eight channel phased array head coil. Morphological imaging was acquired along with:

ASL (pCASL) – pulse label delay 2025ms, 10 arms, 1024 arm length, 3 NEX, 5 mm slice thickness, 32 locations

IVIM - 15 b-values (0, 10, 20, 30, 40, 50, 60, 75, 100, 150, 200, 350, 500, 750, 1000 mm^-2s), 3 directions, 128x128 matrix, 240mm FOV, 2.5mm slice thickness, 56 slices

T₁ DCE – 6s temporal resolution, 60 phases, 192x96 matrix, 240mm FOV, 20° flip angle, 5.0mm slice thickness overlapped to 2.5mm thick reconstructed images, 44 slices, scan time 6.17. Pre-contrast volumes of 3, 5, 7, 10, 20 and 30° flip angles were used to calculate tissue T1 relaxation times, ¾ dose of gadolinium contrast agent

T₂* DSC – GRE-EPI, 2s temporal resolution, 50 phases, 128x128 matrix, 240mm FOV, 5.0mm slice thickness, 29 slices, ¾ dose of gadolinium contrast agent.

Data was processed using in-house software, except ASL the scanner calculated. Motion correction and registration was implemented using FSL². IVIM parameters were flow fraction (f), perfusion fraction (D*) and blood flow (fD*). Pharmacokinetic modelling using a two compartment Tofts-Kety model was used to generate K^trans, v_e and v_b. DSC-MRI was processed using a contrast agent extravasation correction model³, generating the T₂* leakage parameter K₂, with the subsequently corrected cerebral blood volume normalised to global white matter (rCBV). All parametric maps were spatially registered prior to sampling.

Pre- and post-contrast T₁ volume subtraction maps were used to contour enhancing lesions, whist T₂ FLAIR hyperintensity was used for non-enhancing lesions. White matter was sampled on a single representative slice (Figure 1). Mean and 95th percentile measurements were obtained for both tissue groups with cross-modal comparisons made using Pearson’s test.

In the 11 patients, 6 cases of glioblastoma multiforme (WHO IV) were diagnosed along with 1 anaplastic meningioma (WHO III), 1 anaplastic ependymoma (WHO III), 2 diffuse astrocytomas (WHO II) and 1 case of demyelination. Mean±standard deviations in normal white matter for f, D*, fD*, CBF, K^trans, v_e, v_b, rCBV and K₂ were: 0.08±0.01, 7.96±0.85x10^-3mm²s^-1, 0.65±0.08x10^-3mm²s^-1, 29.65±6.70ml100g^-1min^-1, 0.03±0.01min^-1, 0.05±0.02, 0.03±0.01, 1.34±0.10 and 0.37±0.12 respectively. Correlations between perfusion measures are shown for mean (Figure 2) and 95^th percentile values (Figure 3). Correlation coefficients and p-values for both figures are shown in Figure 4.To the author’s knowledge, this is the first brain study to acquire all 4 techniques in a single examination. IVIM values for white matter were comparable to Wu et al.⁴ with f and D* reported as 0.07±0.01 and 7.9±0.9x10^-3mm²s^-1. Bisdas et al.⁵ also reported similar white matter values for f, D*, fD*, 0.07±0.02, 5.35±2.29x10^-3mm²s^-1 and 0.48±0.19x10^-3mm²s^-1 respectively. Federau et al.⁶ reported f as 0.061±0.011 in white matter, was able to observe a correlation between rCBV and f in gliomas, which we also found. Significant correlations of note include CBF vs. fD*, v_b vs. rCBV and K^trans vs. K₂. The significant correlation between f and K^trans has previously been described in prostate⁷ and is a potentially useful finding. Promising correlations can be seen between IVIM, and ASL, DCE and DSC parameters. The ability of IVIM to simultaneously measure diffusion is an added benefit. Encouragingly, spatial registration of all 4 different methods yields acceptable agreement given technical differences.