2016
DOI: 10.3892/ijo.2016.3595
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A 3-dimensional DTI MRI-based model of GBM growth and response to radiation therapy

Abstract: Abstract. Glioblastoma (GBM) is both the most common and the most aggressive intra-axial brain tumor, with a notoriously poor prognosis. To improve this prognosis, it is necessary to understand the dynamics of GBM growth, response to treatment and recurrence. The present study presents a mathematical diffusion-proliferation model of GBM growth and response to radiation therapy based on diffusion tensor (DTI) MRI imaging. This represents an important advance because it allows 3-dimensional tumor modeling in the… Show more

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Cited by 14 publications
(7 citation statements)
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“…DTI data have been used successfully in the context of glioma evaluation in several regards. For example, they have been used to adapt target volume definitions for GBM treatment planning [24][25][26], for modeling of brain tumor growth [27][28][29][30], to detect early malignant transformation of low-grade glioma [31], to differentiate between GBM and brain metastases [32], to use DTI-derived fiber tracking in surgery planning [33], and to detect the infiltration of the corpus callosum [34]. Our inability to properly connect most primary and secondary tumors does not diminish the value of DTI for these applications.…”
Section: Discussionmentioning
confidence: 99%
“…DTI data have been used successfully in the context of glioma evaluation in several regards. For example, they have been used to adapt target volume definitions for GBM treatment planning [24][25][26], for modeling of brain tumor growth [27][28][29][30], to detect early malignant transformation of low-grade glioma [31], to differentiate between GBM and brain metastases [32], to use DTI-derived fiber tracking in surgery planning [33], and to detect the infiltration of the corpus callosum [34]. Our inability to properly connect most primary and secondary tumors does not diminish the value of DTI for these applications.…”
Section: Discussionmentioning
confidence: 99%
“…Each of these greatly complicate the understanding of the progression of an individual cell population, which we provide the fundamental groundwork for in the present work. The most practically useful models will of course need to account for these ongoing treatment factors, one of which – radiation therapy – we have modeled separately elsewhere [24]. Specifically, we note that we have considered D to be time-invariant, and ρ and η to be constant across both time and space.…”
Section: Discussionmentioning
confidence: 99%
“…Some studies have used the whole tensor to predict tumour spread. An article used a 3D-based DTI model that uses the fibre orientation to predict glioma growth [25]. However, this study did not evaluate the model accuracy quantitatively.…”
Section: Dti Modelled Tumoral Invasionmentioning
confidence: 99%