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Differentiation of progressive disease from pseudoprogression using MRI histogram analysis in patients with treated glioblastoma

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Abstract

Purpose

Conventional magnetic resonance imaging (MRI) technics are insufficient in the differentiation of tumor progression from post-treatment changes in patients with treated glioblastoma. Previous studies have suggested that histogram analysis is a useful tool in the assessment of treatment response in different cancer types. The aim of the study was to to evaluate the effectiveness of MRI histogram analysis in the differentiation of tumor progression from pseudoprogression in patients with treated glioblastoma.

Methods

Forty-six patients with glioblastoma who newly developed enhancing lesions following chemoradiation treatment were included in this retrospective study. Histogram analysis was performed from new enhancing lesions on T1-weighted contrast-enhanced MRI. Histogram analysis findings of patients with progression (23) and pseudoprogression (23) were compared.

Results

Mean, minimum, median, maximum, standard deviation, variance, entropy, skewness, uniformity values were found to be significantly higher in progressive disease (p < 0.05). A receiver-operating characteristic (ROC) curve analysis was performed for mean value, and area under the curve (AUC) was found as 0.975. When the threshold value was selected as 528.86, two groups could be differentiated with 95.7% sensitivity and 87.0% specificity.

Conclusion

MRI histogram analysis can be used for the differentiation of progressive disease from pseudoprogression.

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Authors and Affiliations

  1. Department of Radiology, Elazığ Fethi Sekin City Hospital, University of Health Sciences, Elazığ, Turkey

    Mustafa Yildirim

  2. Department of Radiology, Faculty of Medicine, Fırat University, Elazığ, Turkey

    Murat Baykara

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  1. Mustafa Yildirim
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  2. Murat Baykara
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Correspondence to Mustafa Yildirim.

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Yildirim, M., Baykara, M. Differentiation of progressive disease from pseudoprogression using MRI histogram analysis in patients with treated glioblastoma. Acta Neurol Belg 122, 363–368 (2022). https://doi.org/10.1007/s13760-021-01607-3

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