Tissue-type mapping of gliomas.
Tissue-type mapping of gliomas.
Raschke, F.; Barrick, T. R.; Jones, T.; Yang, G.; Ye, X.; Howe, F. A.
PURPOSE:
To develop a statistical method of combining multimodal MRI (mMRI) of adult glial brain tumours to generate tissue heterogeneity maps that indicate tumour grade and infiltration margins.
MATERIALS AND METHODS:
We performed a retrospective analysis of mMRI from patients with histological diagnosis of glioma (n = 25). 1H Magnetic Resonance Spectroscopic Imaging (MRSI) was used to label regions of "pure" low- or high-grade tumour across image types. Normal brain and oedema characteristics were defined from healthy controls (n = 10) and brain metastasis patients (n = 10) respectively. Probability density distributions (PDD) for each tissue type were extracted from intensity normalised proton density and T2-weighted images, and p and q diffusion maps. Superpixel segmentation and Bayesian inference was used to produce whole-brain tissue-type maps.
RESULTS:
Total lesion volumes derived automatically from tissue-type maps correlated with those from manual delineation (p < 0.001, r = 0.87). Large high-grade volumes were determined in all grade III & IV (n = 16) tumours, in grade II gemistocytic rich astrocytomas (n = 3) and one astrocytoma with a histological diagnosis of grade II. For patients with known outcome (n = 20), patients with survival time < 2 years (3 grade II, 2 grade III and 10 grade IV) had a high-grade volume significantly greater than zero (Wilcoxon signed rank p < 0.0001) and also significantly greater high grade volume than the 5 grade II patients with survival >2 years (Mann Witney p = 0.0001). Regions classified from mMRI as oedema had non-tumour-like 1H MRS characteristics.
CONCLUSIONS:
1H MRSI can label tumour tissue types to enable development of a mMRI tissue type mapping algorithm, with potential to aid management of patients with glial tumours.
Keywords: Glioma; Magnetic resonance spectroscopy (MRS); Multimodal MRI; Nosologic imaging; Pattern recognition
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NeuroImage Clinical 21(2019), 101648
Online First (2018) DOI: 10.1016/j.nicl.2018.101648
Cited 48 times in Scopus
Permalink: https://www.hzdr.de/publications/Publ-28845
Publ.-Id: 28845