Analysis of diffusion tensor imaging metrics for gliomas grading at 3T

Server, Andrés; Graff, Bjørn A.; Josefsen, Roger; Orheim, Tone E. Døli; Schellhorn, Till; Nordhøy, Wibeke; Nakstad, P

doi:10.1016/j.ejrad.2013.12.023

Cited by 48 publications

(58 citation statements)

References 30 publications

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“…Sampling the DTI tensor, the 3D characteristics of diffusion are measured which enables a quantitative statistical analysis for neuro‐oncologic research . There are numerous applications of DWI/DTI in brain tumors: (1) determination of grade and histologic subtype, (2) evaluation of peritumoral edema and assessment of pathways of tumor infiltration, (3) quantitative measurement and monitoring of the response to therapy, and (4) discrimination between necrotic tissue and tumor recurrence (eg, radiation and chemotherapy) …”

Section: Discussionmentioning

confidence: 99%

“…These studies, however, analyzed only ADC/mean diffusivity (MD), not fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD). FA, AD, and RD were previously shown to successfully classify low and high‐grade gliomas . DTI scalars other than ADC may therefore also harbor valuable information for pediatric cerebellar tumors.…”

Section: Introductionmentioning

confidence: 99%

“…FA, AD, and RD were previously shown to successfully classify low and highgrade gliomas. 11 DTI scalars other than ADC may therefore also harbor valuable information for pediatric cerebellar tumors. Thirdly, the focused delineation of the SCT is more prone to inaccuracy than the manual delineation of the entire tumor (ET).…”

Section: Introductionmentioning

confidence: 99%

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Histogram Analysis of Diffusion Tensor Imaging Parameters in Pediatric Cerebellar Tumors

Wagner

Narayan

Bosemani

et al. 2015

Journal of Neuroimaging

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Histogram Analysis of Diffusion Tensor Imaging Parameters in Pediatric Cerebellar Tumors

Wagner

Narayan

Bosemani

et al. 2015

Journal of Neuroimaging

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“…Recent studies have demonstrated the value of metabolic and physiologic MR imaging techniques, such as DWI (19), DTI (20,21), MRS (22,23), DSC MRI (17, 24, 25), and DCE MRI in the assessment of grading gliomas (26,27).…”

Section: Discussionmentioning

confidence: 99%

Diagnostic performance of texture analysis on MRI in grading cerebral gliomas

Skogen

Schulz

Dormagen

et al. 2016

European Journal of Radiology

138

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BACKGROUND AND PURPOSEGrading of cerebral gliomas is important both in treatment decision and assessment of prognosis. The purpose of this study was to determine the diagnostic accuracy of grading cerebral gliomas by assessing the tumor heterogeneity using MRI texture analysis (MRTA). MATERIAL AND METHODS95 patients with gliomas were included, 27 low grade gliomas (LGG) all grade II and 68 high grade gliomas (HGG) (grade III = 34 and grade IV = 34). Preoperative MRI examinations were performed using a 3T scanner and MRTA was done on preoperative contrast-enhanced three-dimensional isotropic spoiled gradient echo images in a representative ROI. The MRTA was assessed using a commercially available research software program (TexRAD) that applies a filtration-histogram technique for characterizing tumor heterogeneity. Filtration step selectively filters and extracts texture features at different anatomical scales varying from 2mm(fine features) to 6mm(coarse features), the statistical parameter standard deviation (SD) was obtained. Receiver operating characteristics (ROC) was performed to assess sensitivity and specificity for differentiating between the different grades and calculating a threshold value to quantify the heterogeneity. RESULTS 2LGG and HGG was best discriminated using SD at fine texture scale, with a sensitivity and specificity of 93% and 81% (AUC 0.910, p<0.0001). The diagnostic ability for MRTA to differentiate between the different sub-groups (grade II -IV) was slightly lower but still significant. CONCLUSIONSMeasuring heterogeneity in gliomas to discriminate HGG from LGG and between different histological sub-types on already obtained images using MRTA can be a useful tool to augment the diagnostic accuracy in grading cerebral gliomas and potentially hasten treatment decision. Abbreviations

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“…The results showed that ADC, RD and AD were useful for differentiation between low-and high-grade gliomas with a diagnostic accuracy of more than 90%. Among them, ADC provided the highest discriminatory power [23].…”

Section: Discussionmentioning

confidence: 99%