Comparison of clinically available dynamic susceptibility contrast post processing software to differentiate progression from pseudoprogression in post-treatment high grade glioma

Nathalie Nierobisch; Riccardo Ludovichetti; Krishna Kadali; Jorn Fierstra; Martin Hüllner; Lars Michels; Ngwe Rawlings Achangwa; Paula Alcaide-Leon; Michael Weller; Zsolt Kulcsar; Nicolin Hainc

doi:10.1016/j.ejrad.2023.111076

Comparison of clinically available dynamic susceptibility contrast post processing software to differentiate progression from pseudoprogression in post-treatment high grade glioma

Eur J Radiol. 2023 Oct:167:111076. doi: 10.1016/j.ejrad.2023.111076. Epub 2023 Sep 1.

Affiliations

¹ Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland.
² University of Zurich, Switzerland.
³ Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland.
⁴ Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, Switzerland.
⁵ Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and Swiss Federal Institute of Technology Zurich, Zurich, Switzerland.
⁶ Department of Medical Imaging, University of Toronto, Toronto, Canada; Joint Department of Medical Imaging, University Health Network, Toronto, Canada.
⁷ Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland.
⁸ Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland. Electronic address: Nicolin.hainc@usz.ch.

PMID: 37666072
DOI: 10.1016/j.ejrad.2023.111076

Abstract

Introduction: The purpose of this retrospective study was to compare two, widely available software packages for calculation of Dynamic Susceptibility Contrast (DSC) perfusion MRI normalized relative Cerebral Blood Volume (rCBV) values to differentiate tumor progression from pseudoprogression in treated high-grade glioma patients.

Material and methods: rCBV maps processed by Siemens Syngo.via (Siemens Healthineers) and Olea Sphere (Olea Medical) software packages were co-registered to contrast-enhanced T1 (T1-CE). Regions of interest based on T1-CE were transferred to the rCBV maps. rCBV was calculated using mean values and normalized using contralateral normal- appearing white matter. The Wilcoxon test was performed to assess for significant differences, and software-specific optimal rCBV cutoff values were determined using the Youden index. Interrater reliability was evaluated for two raters using the intraclass correlation coefficient.

Results: 41 patients (18 females; median age = 59 years; range 21-77 years) with 49 new or size-increasing post-treatment contrast-enhancing lesions were included (tumor progression = 40 lesions; pseudoprogression = 9 lesions). Optimal rCBV cutoffs of 1.31 (Syngo.via) and 2.40 (Olea) were significantly different, with an AUC of 0.74 and 0.78, respectively. Interrater reliability was 0.85.

Discussion: We demonstrate that different clinically available MRI DSC-perfusion software packages generate significantly different rCBV cutoff values for the differentiation of tumor progression from pseudoprogression in standard-of-care treated high grade gliomas. Physicians may want to determine the unique value of their perfusion software packages on an institutional level in order to maximize diagnostic accuracy when faced with this clinical challenge. Furthermore, combined with implementation of current DSC-perfusion recommendations, multi-center comparability will be improved.

Keywords: Astrocytoma; Glioblastoma; Glioma; Magnetic resonance imaging; Perfusion weighted MRI.

MeSH terms

Female
Glioma* / diagnostic imaging
Humans
Middle Aged
Perfusion
Reproducibility of Results
Retrospective Studies
Software