DIFFERENTIATION OF ACTIVE TUMOR FROM EDEMATOUS REGIONS OF GLIOBLASTOMAMULTIFORM TUMOR IN DIFFUSION MR IMAGES USING HETEROGENEITY ANALYSIS METHOD

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SALIGHEH RAD HAMIDREZA; FATHI KAZEROONI ANAHITA; NABIL MAHNAZ; ALVIRI MOHAMMADREZA; HADAVAND MEHRDAD; MOHSENI MEYSAM

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Journal: TEHRAN UNIVERSITY MEDICAL JOURNAL (TUMJ) Year:2018 | Volume:76 | Issue:3 Page(s): 178-184

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Title

DIFFERENTIATION OF ACTIVE TUMOR FROM EDEMATOUS REGIONS OF GLIOBLASTOMAMULTIFORM TUMOR IN DIFFUSION MR IMAGES USING HETEROGENEITY ANALYSIS METHOD

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Keywords

DIFFUSION MAGNETIC RESONANCE IMAGINGQ1

EDEMAQ2

GLIOBLASTOMAQ1

MAGNETIC RESONANCEIMAGINGQ2

TUMORQ2

Abstract

Background: Due to intrinsic heterogeneity of cellular distribution and density withindiffusion weighted images (DWI) of GLIOBLASTOMA multiform (GBM) TUMORs, differentiationof active TUMOR and peri-tumoral EDEMA regions within these TUMORs is challenging. The aim of this paper was to take advantage of the differences among heterogeneityof active TUMOR and EDEMAtous regions within the GLIOBLASTOMA multiform TUMORs inorder to discriminate these regions from each other. Methods: The dataset of this retrospective study was selected from a database whichwas collected at the medical imaging center, Imam Khomeini Hospital, Tehran Universityof Medical Sciences, Iran. The quantification was performed as a part of a researchstudy being supported by the Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Iran, between May and September 2017. Twentypatients with histopathologically-confirmed GBM TUMORs who had been imaged on a3T MRI scanner prior to their surgery, were included. Conventional and diffusionweighted MR images had been carried out on the patients. The regions of interest includingthe regions of active TUMOR and EDEMA were identified on MR images by anexpert and overlaid on ADC-maps of the same patients. Histogram analysis was performedon each of these regions and 14 characteristic features were calculated and thebest feature combination for discrimination of active TUMOR from EDEMA was obtained. Results: It was shown that by combining 8 out of 14 histogram features, including median, normalized mean, standard deviation, skewness, energy, 25th, 75th, and 95th percentiles, differentiation with accuracy of 96. 4% and diagnostic performance of 100%can be achieved. Furthermore, by combining mean, energy, and 75th percentile featuresof histograms, the active TUMOR region can be discriminated from the EDEMAtous regionby 92. 7% of accuracy and 98. 9% of diagnostic performance. Conclusion: The present study confirms that the heterogeneity of cellular distributioncan be a predictive biomarker for differentiation of EDEMAtous regions from active TUMORpart of GBM TUMORs.

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APA: Copy

SALIGHEH RAD, HAMIDREZA, FATHI KAZEROONI, ANAHITA, NABIL, MAHNAZ, ALVIRI, MOHAMMADREZA, HADAVAND, MEHRDAD, & MOHSENI, MEYSAM. (2018). DIFFERENTIATION OF ACTIVE TUMOR FROM EDEMATOUS REGIONS OF GLIOBLASTOMAMULTIFORM TUMOR IN DIFFUSION MR IMAGES USING HETEROGENEITY ANALYSIS METHOD. TEHRAN UNIVERSITY MEDICAL JOURNAL (TUMJ), 76(3 ), 178-184. SID. https://sid.ir/paper/38532/en

Vancouver: Copy

SALIGHEH RAD HAMIDREZA, FATHI KAZEROONI ANAHITA, NABIL MAHNAZ, ALVIRI MOHAMMADREZA, HADAVAND MEHRDAD, MOHSENI MEYSAM. DIFFERENTIATION OF ACTIVE TUMOR FROM EDEMATOUS REGIONS OF GLIOBLASTOMAMULTIFORM TUMOR IN DIFFUSION MR IMAGES USING HETEROGENEITY ANALYSIS METHOD. TEHRAN UNIVERSITY MEDICAL JOURNAL (TUMJ)[Internet]. 2018;76(3 ):178-184. Available from: https://sid.ir/paper/38532/en

IEEE: Copy

HAMIDREZA SALIGHEH RAD, ANAHITA FATHI KAZEROONI, MAHNAZ NABIL, MOHAMMADREZA ALVIRI, MEHRDAD HADAVAND, and MEYSAM MOHSENI, “DIFFERENTIATION OF ACTIVE TUMOR FROM EDEMATOUS REGIONS OF GLIOBLASTOMAMULTIFORM TUMOR IN DIFFUSION MR IMAGES USING HETEROGENEITY ANALYSIS METHOD,” TEHRAN UNIVERSITY MEDICAL JOURNAL (TUMJ), vol. 76, no. 3 , pp. 178–184, 2018, [Online]. Available: https://sid.ir/paper/38532/en

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