Data-driven mapping of hypoxia-related tumor heterogeneity using DCE-MRI and OE-MRI.
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ICR Authors
Authors
Featherstone, AK
O'Connor, JPB
Little, RA
Watson, Y
Cheung, S
Babur, M
Williams, KJ
Matthews, JC
Parker, GJM
O'Connor, JPB
Little, RA
Watson, Y
Cheung, S
Babur, M
Williams, KJ
Matthews, JC
Parker, GJM
Document Type
Journal Article
Date
2018-04-01
Date Accepted
2017-07-13
Abstract
PURPOSE: Previous work has shown that combining dynamic contrast-enhanced (DCE)-MRI and oxygen-enhanced (OE)-MRI binary enhancement maps can identify tumor hypoxia. The current work proposes a novel, data-driven method for mapping tissue oxygenation and perfusion heterogeneity, based on clustering DCE/OE-MRI data. METHODS: DCE-MRI and OE-MRI were performed on nine U87 (glioblastoma) and seven Calu6 (non-small cell lung cancer) murine xenograft tumors. Area under the curve and principal component analysis features were calculated and clustered separately using Gaussian mixture modelling. Evaluation metrics were calculated to determine the optimum feature set and cluster number. Outputs were quantitatively compared with a previous non data-driven approach. RESULTS: The optimum method located six robustly identifiable clusters in the data, yielding tumor region maps with spatially contiguous regions in a rim-core structure, suggesting a biological basis. Mean within-cluster enhancement curves showed physiologically distinct, intuitive kinetics of enhancement. Regions of DCE/OE-MRI enhancement mismatch were located, and voxel categorization agreed well with the previous non data-driven approach (Cohen's kappa = 0.61, proportional agreement = 0.75). CONCLUSION: The proposed method locates similar regions to the previous published method of binarization of DCE/OE-MRI enhancement, but renders a finer segmentation of intra-tumoral oxygenation and perfusion. This could aid in understanding the tumor microenvironment and its heterogeneity. Magn Reson Med 79:2236-2245, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Citation
Magnetic resonance in medicine, 2018, 79 (4), pp. 2236 - 2245
Source Title
Publisher
WILEY
ISSN
0740-3194
eISSN
1522-2594
Collections
Research Team
Quantitative Biomedical Imaging