Enhancing Fraction in Glioma and Its Relationship to the Tumoral Vascular Microenvironment: A Dynamic Contrast-Enhanced MR Imaging Study

Mills, Samantha J.; Soh, Calvin; O’Connor, James P.B.; Rose, Christopher; Buonaccorsi, Giovanni A.; Cheung, Susan; Zhao, Sixiang; Parker, Geoffrey; Jackson, Alan

doi:10.3174/ajnr.a1925

Cited by 27 publications

(14 citation statements)

References 24 publications

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“…8,[10][11][12][13]15,18,28 Using ROC curve analyses, Jia et al 8 showed that K trans and Ve were significantly lower in low-grade gliomas than in high-grade gliomas, with cutoff values of K trans and Ve of 0.035 minutes Ϫ1 and 0.13, respectively. Awasthi et al 10 presented a discriminant function for differentiating low-and high-grade gliomas and a correlation with immunohistochemical markers by using relative CBV, elimination rate of contrast agent or Kep, and Ve derived from DCE MR imaging.…”

Section: Discussionmentioning

confidence: 99%

Glioma: Application of Histogram Analysis of Pharmacokinetic Parameters from T1-Weighted Dynamic Contrast-Enhanced MR Imaging to Tumor Grading

Jung¹,

Yeom²,

Kim³

et al. 2014

American Journal of Neuroradiology

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BACKGROUND AND PURPOSE:The usefulness of pharmacokinetic parameters for glioma grading has been reported based on the perfusion data from parts of entire-tumor volumes. However, the perfusion values may not reflect the entire-tumor characteristics. Our aim was to investigate the feasibility of glioma grading by using histogram analyses of pharmacokinetic parameters including the volume transfer constant, extravascular extracellular space volume per unit volume of tissue, and blood plasma volume per unit volume of tissue from T1-weighted dynamic contrast-enhanced perfusion MR imaging.

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Section: Discussionmentioning

confidence: 99%

Glioma: Application of Histogram Analysis of Pharmacokinetic Parameters from T1-Weighted Dynamic Contrast-Enhanced MR Imaging to Tumor Grading

Jung¹,

Yeom²,

Kim³

et al. 2014

American Journal of Neuroradiology

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“…A study of DCE-MRI derived EnF in glioma has shown the use of thresholding allows the distinction between histological grade of tumour [3]. In the unthresholded form, EnF IAUC60>0 correlated with v p in low grade tumours and K trans in GBM [2]. These latter studies have all required a DCE-MRI acquisition in order to derive EnF, thus limiting the translation …”

Section: Discussionmentioning

confidence: 99%

“…EnF is a relatively recently described parameter [2,3,20,21]. A CT variant of this measure has shown potential in predicting disease free survival and time to progression in patients with ovarian carcinoma [1].…”

Section: Discussionmentioning

confidence: 99%

“…The application of a thresholding technique to EnF allows for the distinction between low and high grade glioma [3]. EnF has been shown to correlate with the established DCE-MRI derived parameters v p (in low grade glioma) and K trans (in glioblastoma multiforme, GBM) [2]. The present technique for measuring EnF requires a DCE-MRI acquisition, calculation of pixel by pixel contrast concentration time course curves providing parametric maps of IAUC 60 .…”

Section: Introductionmentioning

confidence: 99%

“…An MRI based measure of EnF has been shown to provide clinical information in glioma [2,3]. The commonest approach to calculating EnF from MRI is to use the initial area under the concentration time curve (IAUC 60 ) derived from dynamic contrast enhanced MRI (DCE-MRI) and to measure the proportion of voxels within a tumour with a measurable IAUC (> 0 mMol.s) [2,3]. The application of a thresholding technique to EnF allows for the distinction between low and high grade glioma [3].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Survival and Enhancing Fraction (enf) in Glioblastoma Multiforme (GBM)

Mills¹,

Thompson²,

Buonaccorsi³

et al. 2017

Radiol Diagn Imaging

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Assessment of therapeutic response and treatment planning for brain tumors using metabolic and physiological MRI

Nelson¹

2011

NMR in Biomedicine

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MRI is routinely used for diagnosis, treatment planning and assessment of response to therapy for patients with glioma. Gliomas are spatially heterogeneous and infiltrative lesions that are quite variable in terms of their response to therapy. Patients classified as having low-grade histology have a median overall survival of 7 years or more, but need to be monitored carefully to make sure that their tumor does not upgrade to a more malignant phenotype. Patients with the most aggressive grade IV histology have a median overall survival of 12–15 months and often undergo multiple surgeries and adjuvant therapies in an attempt to control their disease. Despite improvements in the spatial resolution and sensitivity of anatomic images, there remain considerable ambiguities in the interpretation of changes in the size of the gadolinium-enhancing lesion on T1-weighted images as a measure of treatment response, and in differentiating between treatment effects and infiltrating tumor within the larger T2 lesion. The planning of focal therapies, such as surgery, radiation and targeted drug delivery, as well as a more reliable assessment of the response to therapy, would benefit considerably from the integration of metabolic and physiological imaging techniques into routine clinical MR examinations. Advanced methods that have been shown to provide valuable data for patients with glioma are diffusion, perfusion and spectroscopic imaging. Multiparametric examinations that include the acquisition of such data are able to assess tumor cellularity, hypoxia, disruption of normal tissue architecture, changes in vascular density and vessel permeability, in addition to the standard measures of changes in the volume of enhancing and nonenhancing anatomic lesions. This is particularly critical for the interpretation of the results of Phase I and Phase II clinical trials of novel therapies, which are increasingly including agents that are designed to have anti-angiogenic and anti-proliferative properties as opposed to having a direct effect on tumor cell viability.

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Enhancing Fraction in Glioma and Its Relationship to the Tumoral Vascular Microenvironment: A Dynamic Contrast-Enhanced MR Imaging Study

Abstract: BACKGROUND AND PURPOSE: EnF is a newly described measure of proportional tumor enhancement derived from DCE-MR imaging. The aim of this study was to assess the relationship between EnF and the more established DCE-MR imaging parameters: K trans , v e , and v p .

Cited by 27 publications

References 24 publications

Glioma: Application of Histogram Analysis of Pharmacokinetic Parameters from T1-Weighted Dynamic Contrast-Enhanced MR Imaging to Tumor Grading

Glioma: Application of Histogram Analysis of Pharmacokinetic Parameters from T1-Weighted Dynamic Contrast-Enhanced MR Imaging to Tumor Grading

Survival and Enhancing Fraction (enf) in Glioblastoma Multiforme (GBM)

Assessment of therapeutic response and treatment planning for brain tumors using metabolic and physiological MRI

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