Heterogeneity Diffusion Imaging of gliomas: Initial experience and validation.

<h4>Objectives</h4>Primary 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 (H...

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Main Authors: Qing Wang, Gloria J Guzmán Pérez-Carrillo, Maria Rosana Ponisio, Pamela LaMontagne, Sonika Dahiya, Daniel S Marcus, Mikhail Milchenko, Joshua Shimony, Jingxia Liu, Gengsheng Chen, Amber Salter, Parinaz Massoumzadeh, Michelle M Miller-Thomas, Keith M Rich, Jonathan McConathy, Tammie L S Benzinger, Yong Wang
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0225093
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spelling doaj-d5c24f2c95604db298f893f453a463532021-03-04T11:20:57ZengPublic Library of Science (PLoS)PLoS ONE1932-62032019-01-011411e022509310.1371/journal.pone.0225093Heterogeneity Diffusion Imaging of gliomas: Initial experience and validation.Qing WangGloria J Guzmán Pérez-CarrilloMaria Rosana PonisioPamela LaMontagneSonika DahiyaDaniel S MarcusMikhail MilchenkoJoshua ShimonyJingxia LiuGengsheng ChenAmber SalterParinaz MassoumzadehMichelle M Miller-ThomasKeith M RichJonathan McConathyTammie L S BenzingerYong Wang<h4>Objectives</h4>Primary 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.<h4>Methods</h4>Seven 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.<h4>Results</h4>The 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.<h4>Conclusions</h4>Conventional 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.https://doi.org/10.1371/journal.pone.0225093
collection DOAJ
language English
format Article
sources DOAJ
author Qing Wang
Gloria J Guzmán Pérez-Carrillo
Maria Rosana Ponisio
Pamela LaMontagne
Sonika Dahiya
Daniel S Marcus
Mikhail Milchenko
Joshua Shimony
Jingxia Liu
Gengsheng Chen
Amber Salter
Parinaz Massoumzadeh
Michelle M Miller-Thomas
Keith M Rich
Jonathan McConathy
Tammie L S Benzinger
Yong Wang
spellingShingle Qing Wang
Gloria J Guzmán Pérez-Carrillo
Maria Rosana Ponisio
Pamela LaMontagne
Sonika Dahiya
Daniel S Marcus
Mikhail Milchenko
Joshua Shimony
Jingxia Liu
Gengsheng Chen
Amber Salter
Parinaz Massoumzadeh
Michelle M Miller-Thomas
Keith M Rich
Jonathan McConathy
Tammie L S Benzinger
Yong Wang
Heterogeneity Diffusion Imaging of gliomas: Initial experience and validation.
PLoS ONE
author_facet Qing Wang
Gloria J Guzmán Pérez-Carrillo
Maria Rosana Ponisio
Pamela LaMontagne
Sonika Dahiya
Daniel S Marcus
Mikhail Milchenko
Joshua Shimony
Jingxia Liu
Gengsheng Chen
Amber Salter
Parinaz Massoumzadeh
Michelle M Miller-Thomas
Keith M Rich
Jonathan McConathy
Tammie L S Benzinger
Yong Wang
author_sort Qing Wang
title Heterogeneity Diffusion Imaging of gliomas: Initial experience and validation.
title_short Heterogeneity Diffusion Imaging of gliomas: Initial experience and validation.
title_full Heterogeneity Diffusion Imaging of gliomas: Initial experience and validation.
title_fullStr Heterogeneity Diffusion Imaging of gliomas: Initial experience and validation.
title_full_unstemmed Heterogeneity Diffusion Imaging of gliomas: Initial experience and validation.
title_sort heterogeneity diffusion imaging of gliomas: initial experience and validation.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2019-01-01
description <h4>Objectives</h4>Primary 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.<h4>Methods</h4>Seven 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.<h4>Results</h4>The 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.<h4>Conclusions</h4>Conventional 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.
url https://doi.org/10.1371/journal.pone.0225093
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