Development of a Multiparametric Voxel-Based Magnetic Resonance Imaging Biomarker for Early Cancer Therapeutic Response Assessment
Author(s) -
Craig J. Galbán,
Benjamin Lemasson,
Benjamin A. Hoff,
Timothy D. Johnson,
Pia C. Sundgren,
Christina Tsien,
Thomas L. Chenevert,
Brian D. Ross
Publication year - 2015
Publication title -
tomography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.074
H-Index - 9
eISSN - 2379-139X
pISSN - 2379-1381
DOI - 10.18383/j.tom.2015.00124
Subject(s) - imaging biomarker , medicine , magnetic resonance imaging , diffusion mri , temozolomide , biomarker , nuclear medicine , effective diffusion coefficient , glioma , radiation therapy , radiology , biochemistry , chemistry , cancer research
Quantitative magnetic resonance imaging (MRI)-based biomarkers, which capture physiological and functional tumor processes, were evaluated as imaging surrogates of early tumor response following chemoradiotherapy in glioma patients. A multiparametric extension of a voxel-based analysis, referred as the parametric response map (PRM), was applied to quantitative MRI maps to test the predictive potential of this metric for detecting response. Fifty-six subjects with newly diagnosed high-grade gliomas treated with radiation and concurrent temozolomide were enrolled in a single-site prospective institutional review board-approved MRI study. Apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) maps were acquired before therapy and 3 weeks after therapy was initiated. Multiparametric PRM (mPRM) was applied to both physiological MRI maps and evaluated as an imaging biomarker of patient survival. For comparison, single-biomarker PRMs were also evaluated in this study. The simultaneous analysis of ADC and rCBV by the mPRM approach was found to improve the predictive potential for patient survival over single PRM measures. With an array of quantitative imaging parameters being evaluated as biomarkers of therapeutic response, mPRM shows promise as a new methodology for consolidating physiologically distinct imaging parameters into a single interpretable and quantitative metric.
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