Multiparametric Characterization of Grade 2 Glioma Subtypes Using Magnetic Resonance Spectroscopic, Perfusion, and Diffusion Imaging

Bian, Wei; Khayal, Inas S.; Lupo, Janine M.; McGue, Colleen; Lamborn, Kathleen R.; Chang, Susan M.; Nelson, Sarah J.

doi:10.1593/tlo.09178

Cited by 31 publications

(22 citation statements)

References 42 publications

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“…Similarly, Lev et al [21] observed a higher maximum rCBV in oligodendrogliomas compared with astrocytomas in a similar sized cohort of patients (N = 30; 8 oligodendrogliomas; 4 WHO II and 4 WHO III) even after leakage correction; however, the relatively low number of patients and use of maximum rCBV measurements likely biased their results toward more corticallybased lesions or tumors near vascular structures. Lastly, our current results demonstrated no difference in median ADC between histologic subtypes, which corroborate the findings by Fellah et al [22], but are inconsistent with the findings from Bian et al [34], who found a lower ADC in oligodendrogliomas compared with astrocytomas. Some of the differences may have stemmed from our smaller sample size in grade II gliomas and the differences in criteria used for distinguishing oligoastrocytomas from oligodendrogliomas and astrocytomas.…”

Section: Discussionsupporting

confidence: 51%

Perfusion and diffusion MRI signatures in histologic and genetic subtypes of WHO grade II–III diffuse gliomas

et al. 2017

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Section: Discussionsupporting

confidence: 51%

Perfusion and diffusion MRI signatures in histologic and genetic subtypes of WHO grade II–III diffuse gliomas

et al. 2017

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“…With its ability to probe tissue cellularity, the use of diffusion imaging with apparent diffusion coefficient (ADC) was also attempted to distinguish low-from high-grade brain tumors (9-13). However, its clinical acceptance is limited because of substantial overlap of ADC values among different tumor grades for both adult and pediatric patients (1,(14)(15)(16)(17)(18)(19)(20)(21)(22)(23). In addition, in some common locations (eg, the brain stem) of pediatric brain tumors, tumor grading D = 38.6 msec; duration of each diffusion gradient, d = 32.2 msec; field of view, 22 cm; section thickness, 5 mm; matrix size, 128 3 128; and imaging time, 3 minutes.…”

Section: Fundingmentioning

confidence: 99%

Differentiation of Low- and High-Grade Pediatric Brain Tumors with Highb-Value Diffusion-weighted MR Imaging and a Fractional Order Calculus Model

Sui¹,

Wang

Liu

et al. 2015

Radiology

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).q RSNA, 2015 Purpose:To demonstrate that a new set of parameters (D, b, and m) from a fractional order calculus (FROC) diffusion model can be used to improve the accuracy of MR imaging for differentiating among low-and high-grade pediatric brain tumors. Materials and Methods:The institutional review board of the performing hospital approved this study, and written informed consent was obtained from the legal guardians of pediatric patients. Multi-b-value diffusion-weighted magnetic resonance (MR) imaging was performed in 67 pediatric patients with brain tumors. Diffusion coefficient D, fractional order parameter b (which correlates with tissue heterogeneity), and a microstructural quantity m were calculated by fitting the multi-b-value diffusion-weighted images to an FROC model. D, b, and m values were measured in solid tumor regions, as well as in normal-appearing gray matter as a control. These values were compared between the lowand high-grade tumor groups by using the Mann-Whitney U test. The performance of FROC parameters for differentiating among patient groups was evaluated with receiver operating characteristic (ROC) analysis. Results:None of the FROC parameters exhibited significant differences in normal-appearing gray matter (P  .24), but all showed a significant difference (P , . Conclusion:The FROC parameters can be used to differentiate between low-and high-grade pediatric brain tumor groups. The combination of FROC parameters or individual parameters may serve as in vivo, noninvasive, and quantitative imaging markers for classifying pediatric brain tumors.q RSNA, 2015

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“…Despite the potential, several studies indicate that ADC values overlap considerably among different tumor grades in both adult 15–17 and pediatric patients 14, 18–20 . The ADC values of tumor tissues are obtained by characterizing the diffusion MRI signals with a mono-exponential function, also known as a Gaussian diffusion model, which assumes that the diffusion process within a voxel is homogeneous 21 .…”

Section: Introductionmentioning

confidence: 99%

Differentiation of Low- and High-Grade Gliomas Using High b-Value Diffusion Imaging with a Non-Gaussian Diffusion Model

Sui

Xiong

Jiang

et al. 2016

AJNR Am J Neuroradiol

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Background and Purpose Imaging-based tumor grading is highly desirable, but faces challenges in sensitivity, specificity, or diagnostic accuracy. A recently proposed diffusion imaging method using a fractional order calculus (FROC) model offers a set of new parameters to probe not only the diffusion process itself, but also intra-voxel tissue structures, providing new opportunities for non-invasive tumor grading. This study aims at demonstrating the feasibility of using the FROC model to differentiate low- from high-grade gliomas in adult patients and illustrating its improved performance over a conventional diffusion imaging method employing ADC (or D). Materials and Methods With approval from the institutional review board (IRB) and written informed consents from all participating patients, 54 adult patients (18–70 years old) with histology-proven gliomas were enrolled and divided into a low-grade (n = 24) and a high-grade group (n = 30). Multi-b-value diffusion MRI was acquired with 17 b-values (0–4000s/mm2) and analyzed using a FROC model. Mean values and standard deviations of three FROC parameters (D, β, and μ) were calculated from the normal contralateral thalamus (NCTH; as control) and the tumors, respectively. Based on these values, the low- and high-grade glioma groups were compared using a Mann-Whitney U-test. Receiver operating characteristic (ROC) analysis was performed to assess the performance of individual parameters as well as the combination of multiple parameters for low- versus high-grade differentiation. Results Each of the three FROC parameters exhibited a statistically higher value (p ≤ 0.011) in the low-grade than in the high-grade gliomas, whereas there was no difference in the NCTH (p ≥ 0.706). The ROC analysis showed that β (AUC = 0.853) produced a higher AUC than D (0.781) or μ (0.703), and offered a sensitivity of 87.5%, specificity of 76.7%, and diagnostic accuracy of 82.1%. Conclusion The study has demonstrated the feasibility of using a non-Gaussian FROC diffusion model to differentiate low- and high-grade gliomas. While all three FROC parameters showed statistically significant differences between the two groups, β exhibited better performance than the other two parameters, including ADC (or D).

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Multiparametric Characterization of Grade 2 Glioma Subtypes Using Magnetic Resonance Spectroscopic, Perfusion, and Diffusion Imaging

Cited by 31 publications

References 42 publications

Perfusion and diffusion MRI signatures in histologic and genetic subtypes of WHO grade II–III diffuse gliomas

Perfusion and diffusion MRI signatures in histologic and genetic subtypes of WHO grade II–III diffuse gliomas

Differentiation of Low- and High-Grade Pediatric Brain Tumors with Highb-Value Diffusion-weighted MR Imaging and a Fractional Order Calculus Model

Differentiation of Low- and High-Grade Gliomas Using High b-Value Diffusion Imaging with a Non-Gaussian Diffusion Model

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