Comparison of the Diagnostic Accuracy of DSC- and Dynamic Contrast-Enhanced MRI in the Preoperative Grading of Astrocytomas

Abstract

BACKGROUND AND PURPOSE: Dynamic contrast-enhanced MR imaging parameters can be biased by poor measurement of the vascular input function. We have compared the diagnostic accuracy of dynamic contrast-enhanced MR imaging by using a phase-derived vascular input function and "bookend" T1 measurements with DSC MR imaging for preoperative grading of astrocytomas.

Correlation of Tumor Immunohistochemistry with Dynamic Contrast-Enhanced and DSC-MRI Parameters in Patients with Gliomas

“…These patients were part of a diagnostic accuracy study on DCE-and DSC-MR imaging for glioma grading, which has been published previously. 11 Eleven patients were excluded due to the absence of a histopathologic diagnosis or the presence of an alternate histopathologic diagnosis: no biopsy (n ϭ 2), inconclusive biopsy (n ϭ 1), metastatic disease (n ϭ 2), lymphomas (n ϭ 2), glioneuronal tumors (n ϭ 2), meningioma (n ϭ 1), and neurosarcoidosis (n ϭ 1). Nine patients with gliomas were excluded for technical reasons: inadequate bolus injection of contrast (n ϭ 4), hemorrhage within the glioblastoma causing extensive susceptibility artifacts (n ϭ 3), dynamic acquisition not centered over the tumor (n ϭ 1), and inadequate VIF for the DCE acquisition (n ϭ 1).…”

“…This step was performed off-line by using in-house software written in IDL (Exelis Visual Information Solutions, Boulder, Colorado) and has been described in previous articles. 10,11 The gadolinium-versus-time curve was imported as the VIF in a kinetic modeling-analysis software (nordicICE software, Version 2; NordicNeuroLab, Bergen, Norway) for a voxel-by-voxel estimation of plasma volume obtained from phase-derived vascular input function and bookend T1 mapping (Vp_⌽) and volume transfer constant obtained from phase-derived vascular input function and bookend T1 mapping (K trans _⌽). Postprocessing parameters were the following: noise level ϭ 0, spatial smoothing ϭ off, vascular deconvolution ϭ on, normalize kinetic parameters ϭ on, autodetect VIF-tissue delay ϭ on, hematocrit correction factor ϭ 0.45.…”

“…[8][9][10][11] MR imaging signal data are complex numbers, composed of magnitude and phase. The magnitude is the strength of the signal and is affected by T1, T2, proton density, inflow, and magnetic field inhomogeneity.…”

3D Pseudocontinuous Arterial Spin-Labeling MR Imaging in the Preoperative Evaluation of Gliomas

“…4,5 Dynamic susceptibility contrast perfusion imaging is the reference standard for evaluating tumor perfusion. 6,7 However, this technique relies on the intravenous application of a contrast medium, which is not suitable for patients who are allergic to this medium or who have renal failure.…”

Addition of Amide Proton Transfer Imaging to FDG-PET/CT Improves Diagnostic Accuracy in Glioma Grading: A Preliminary Study Using the Continuous Net Reclassification Analysis

“…Several researchers have argued that multiparametric MR imaging methods have the potential to improve the diagnostic performance of preoperative glioma grading. [30][31][32] Furthermore, Yoon et al 1 reported that adding FDG-PET to multiparametric MR imaging, including DWI, PWI, and MR spectroscopy, can improve the diagnostic accuracy of glioma grading. However, few studies have examined glioma grading with multiparametric imaging that included APT imaging and PWI or DWI.…”