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Diffusion Weighted Imaging in High-grade Gliomas: A Histogram-based Analysis of Apparent Diffusion Coefficient Profile

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Journal PLoS One
Date 2021 Apr 15
PMID 33857203
Citations 7
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Abstract

Purpose: Glioblastoma and anaplastic astrocytoma represent the most commonly encountered high-grade-glioma (HGG) in adults. Although both neoplasms are very distinct entities in context of epidemiology, clinical course and prognosis, their appearance in conventional magnetic resonance imaging (MRI) is very similar. In search for additional information aiding the distinction of potentially confusable neoplasms, histogram analysis of apparent diffusion coefficient (ADC) maps recently proved to be auxiliary in a number of entities. Therefore, our present exploratory retrospective study investigated whether ADC histogram profile parameters differ significantly between anaplastic astrocytoma and glioblastoma, reflect the proliferation index Ki-67, or are associated with the prognostic relevant MGMT (methylguanine-DNA methyl-transferase) promotor methylation status.

Methods: Pre-surgical ADC volumes of 56 HGG patients were analyzed by histogram-profiling. Association between extracted histogram parameters and neuropathology including WHO-grade, Ki-67 expression and MGMT promotor methylation status was investigated due to comparative and correlative statistics.

Results: Grade IV gliomas were more heterogeneous than grade III tumors. More specifically, ADCmin and the lowest percentile ADCp10 were significantly lower, whereas ADCmax, ADC standard deviation and Skewness were significantly higher in the glioblastoma group. ADCmin, ADCmax, ADC standard deviation, Kurtosis and Entropy of ADC histogram were significantly correlated with Ki-67 expression. No significant difference could be revealed by comparison of ADC histogram parameters between MGMT promotor methylated and unmethylated HGG.

Conclusions: ADC histogram parameters differ significantly between glioblastoma and anaplastic astrocytoma and show distinct associations with the proliferative activity in both HGG. Our results suggest ADC histogram profiling as promising biomarker for differentiation of both, however, further studies with prospective multicenter design are wanted to confirm and further elaborate this hypothesis.

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References
1.
Han Y, Yan L, Wang X, Sun Y, Zhang X, Liu Z . Structural and advanced imaging in predicting MGMT promoter methylation of primary glioblastoma: a region of interest based analysis. BMC Cancer. 2018; 18(1):215. PMC: 5822523. DOI: 10.1186/s12885-018-4114-2. View

2.
Lemee J, Clavreul A, Menei P . Intratumoral heterogeneity in glioblastoma: don't forget the peritumoral brain zone. Neuro Oncol. 2015; 17(10):1322-32. PMC: 4578587. DOI: 10.1093/neuonc/nov119. View

3.
Gihr G, Horvath-Rizea D, Kohlhof-Meinecke P, Ganslandt O, Henkes H, Richter C . Histogram Profiling of Postcontrast T1-Weighted MRI Gives Valuable Insights into Tumor Biology and Enables Prediction of Growth Kinetics and Prognosis in Meningiomas. Transl Oncol. 2018; 11(4):957-961. PMC: 6008484. DOI: 10.1016/j.tranon.2018.05.009. View

4.
Cui Y, Ma L, Chen X, Zhang Z, Jiang H, Lin S . Lower apparent diffusion coefficients indicate distinct prognosis in low-grade and high-grade glioma. J Neurooncol. 2014; 119(2):377-85. DOI: 10.1007/s11060-014-1490-6. View

5.
Gihr G, Horvath-Rizea D, Garnov N, Kohlhof-Meinecke P, Ganslandt O, Henkes H . Diffusion Profiling via a Histogram Approach Distinguishes Low-grade from High-grade Meningiomas, Can Reflect the Respective Proliferative Potential and Progesterone Receptor Status. Mol Imaging Biol. 2018; 20(4):632-640. DOI: 10.1007/s11307-018-1166-2. View