Investigating intracranial tumour growth patterns with multiparametric MRI incorporating Gd-DTPA and USPIO-enhanced imaging.

Abstract

High grade and metastatic brain tumours exhibit considerable spatial variations in proliferation, angiogenesis, invasion, necrosis and oedema. Vascular heterogeneity arising from vascular co-option in regions of invasive growth (in which the blood-brain barrier remains intact) and neoangiogenesis is a major challenge faced in the assessment of brain tumours by conventional MRI. A multiparametric MRI approach, incorporating native measurements and both Gd-DTPA (Magnevist) and ultrasmall superparamagnetic iron oxide (P904)-enhanced imaging, was used in combination with histogram and unsupervised cluster analysis using a k-means algorithm to examine the spatial distribution of vascular parameters, water diffusion characteristics and invasion in intracranially propagated rat RG2 gliomas and human MDA-MB-231 LM2-4 breast adenocarcinomas in mice. Both tumour models presented with higher ΔR1 (the change in transverse relaxation rate R1 induced by Gd-DTPA), fractional blood volume (fBV) and apparent diffusion coefficient than uninvolved regions of the brain. MDA-MB-231 LM2-4 tumours were less densely cellular than RG2 tumours and exhibited substantial local invasion, associated with oedema, whereas invasion in RG2 tumours was minimal. These additional features were reflected in the more heterogeneous appearance of MDA-MB-231 LM2-4 tumours on T2 -weighted images and maps of functional MRI parameters. Unsupervised cluster analysis separated subregions with distinct functional properties; areas with a low fBV and relatively impermeable blood vessels (low ΔR1 ) were predominantly located at the tumour margins, regions of MDA-MB-231 LM2-4 tumours with relatively high levels of water diffusion and low vascular permeability and/or fBV corresponded to histologically identified regions of invasion and oedema, and areas of mismatch between vascular permeability and blood volume were identified. We demonstrate that dual contrast MRI and evaluation of tissue diffusion properties, coupled with cluster analysis, allows for the assessment of heterogeneity within invasive brain tumours and the designation of functionally diverse subregions that may provide more informative predictive biomarkers.