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    Decoding the interdependence of multiparametric magnetic resonance imaging to reveal patient subgroups correlated with survivals

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    Authors
    Li, C
    Wang, S
    Liu, P
    Torheim, Turid
    Boonzaier, NR
    van Dijken, BR
    Schonlieb, CB
    Markowetz, F
    Price, SJ
    Affiliation
    Cambridge Brain Tumor Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
    Issue Date
    2019
    
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    Abstract
    Glioblastoma is highly heterogeneous in microstructure and vasculature, creating various tumor microenvironments among patients, which may lead to different phenotypes. The purpose was to interrogate the interdependence of microstructure and vasculature using perfusion and diffusion imaging and to investigate the utility of this approach in tumor invasiveness assessment. A total of 115 primary glioblastoma patients were prospectively recruited for preoperative magnetic resonance imaging (MRI) and surgery. Apparent diffusion coefficient (ADC) was calculated from diffusion imaging, and relative cerebral blood volume (rCBV) was calculated from perfusion imaging. The empirical copula transform was applied to ADC and rCBV voxels in the contrast-enhancing tumor region to obtain their joint distribution, which was discretized to extract second-order features for an unsupervised hierarchical clustering. The lactate levels of patient subgroups, measured by MR spectroscopy, were compared. Survivals were analyzed using Kaplan-Meier and multivariate Cox regression analyses. The results showed that three patient subgroups were identified by the unsupervised clustering. These subtypes showed no significant differences in clinical characteristics but were significantly different in lactate level and patient survivals. Specifically, the subtype demonstrating high interdependence of ADC and rCBV displayed a higher lactate level than the other two subtypes (P?=?.016 and P?=?.044, respectively). Both subtypes of low and high interdependence showed worse progression-free survival than the intermediate (P?=?.046 and P?=?.009 respectively). Our results suggest that the interdependence between perfusion and diffusion imaging may be useful in stratifying patients and evaluating tumor invasiveness, providing overall measure of tumor microenvironment using multiparametric MRI.
    Citation
    Li C, Wang S, Liu P, Torheim T, Boonzaier NR, van Dijken BR, et al. Decoding the interdependence of multiparametric magnetic resonance imaging to reveal patient subgroups correlated with survivals. Neoplasia. 2019 May;21(5):442-9.
    Journal
    Neoplasia
    URI
    http://hdl.handle.net/10541/621873
    DOI
    10.1016/j.neo.2019.03.005
    PubMed ID
    30943446
    Additional Links
    https://dx.doi.org/10.1016/j.neo.2019.03.005
    Type
    Article
    Language
    en
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.neo.2019.03.005
    Scopus Count
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    All Paterson Institute for Cancer Research

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