Abstract
ObjectivesPrimary brain tumors are composed of tumor cells, neural/glial tissues, edema, and vasculature tissue. Conventional MRI has a limited ability to evaluate heterogeneous tumor pathologies. We developed a novel diffusion MRI-based method—Heterogeneity Diffusion Imaging (HDI)—to simultaneously detect and characterize multiple tumor pathologies and capillary blood perfusion using a single diffusion MRI scan.MethodsSeven adult patients with primary brain tumors underwent standard-of-care MRI protocols and HDI protocol before planned surgical resection and/or stereotactic biopsy. Twelve tumor sampling sites were identified using a neuronavigational system and recorded for imaging data quantification. Metrics from both protocols were compared between World Health Organization (WHO) II and III tumor groups. Cerebral blood volume (CBV) derived from dynamic susceptibility contrast (DSC) perfusion imaging was also compared with the HDI-derived perfusion fraction.ResultsThe conventional apparent diffusion coefficient did not identify differences between WHO II and III tumor groups. HDI-derived slow hindered diffusion fraction was significantly elevated in the WHO III group as compared with the WHO II group. There was a non-significantly increasing trend of HDI-derived tumor cellularity fraction in the WHO III group, and both HDI-derived perfusion fraction and DSC-derived CBV were found to be significantly higher in the WHO III group. Both HDI-derived perfusion fraction and slow hindered diffusion fraction strongly correlated with DSC-derived CBV. Neither HDI-derived cellularity fraction nor HDI-derived fast hindered diffusion fraction correlated with DSC-derived CBV.ConclusionsConventional apparent diffusion coefficient, which measures averaged pathology properties of brain tumors, has compromised accuracy and specificity. HDI holds great promise to accurately separate and quantify the tumor cell fraction, the tumor cell packing density, edema, and capillary blood perfusion, thereby leading to an improved microenvironment characterization of primary brain tumors. Larger studies will further establish HDI’s clinical value and use for facilitating biopsy planning, treatment evaluation, and noninvasive tumor grading.
Highlights
Gliomas account for the majority of primary brain tumors in adults; they represent 26.5% of primary brain tumors and 80.7% of malignant brain tumors [1]
Cerebral blood volume (CBV) derived from dynamic susceptibility contrast (DSC) perfusion imaging was compared with the Heterogeneity Diffusion Imaging (HDI)-derived perfusion fraction
HDI-derived slow hindered diffusion fraction was significantly elevated in the World Health Organization (WHO) III group as compared with the WHO II group
Summary
Gliomas account for the majority of primary brain tumors in adults; they represent 26.5% of primary brain tumors and 80.7% of malignant brain tumors [1]. Malignant gliomas contain heterogeneous pathologies that reflect regional diversity in tumor cell proliferation [2], immune infiltration, tumor vessel density, necrosis, and cystic degeneration. This heterogeneity makes clinical diagnosis and management very challenging. Advanced MRI techniques such as diffusion MRI [3, 4], MR spectroscopy [5, 6] and MR perfusion [7] provide more pathophysiologic information, and they have demonstrated the potential to characterize tumor types and to differentiate recurrent tumor from pseudo progression. Conventional ADC measures average the diffusivity of multiple pathologies coexisting within each tumor voxel, which significantly limits the accuracy and specificity of this method for characterizing neoplastic pathologies
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