A novel vascular model yields increased MR perfusion metrics compared to conventional dynamic susceptibility contrast algorithms in untreated glioblastoma

Reis J, Stahl R, Müller KJ, Karschnia P, Teske N, Neubauer A, Von Baumgarten L, Thon N, Ringel F, Liebig T, Albert NL, Harter PN, Forbrig R (2025)

Publication Type: Journal article

Publication year: 2025

Journal

Neuro-Oncology Advances Oxford University Press

Book Volume: 7

Article Number: vdaf212

Journal Issue: 1

DOI: 10.1093/noajnl/vdaf212

Abstract

Background Malignant gliomas are heterogeneous brain tumors with extensive neovascularization. Conventional gradient-echo dynamic susceptibility contrast (GRE-DSC) perfusion MRI may underestimate microvascular alterations. We hypothesized that a novel vascular model (NVM), based on Bayesian voxel-wise transit time distribution analysis, could yield higher perfusion metrics in untreated isocitrate dehydrogenase (IDH)-wild-type glioblastoma compared to standard vendor GRE-DSC algorithms. Methods In this retrospective, single-center study, 89 patients with neuropathologically confirmed glioblastoma underwent pretherapeutic GRE-DSC perfusion MRI at 1.5 or 3.0 T. Perfusion maps were generated using both the NVM and default vendor algorithms. Using co-registered T1-post-contrast and T2/FLAIR images, two neuroradiologists independently assessed perfusion conspicuity of color-coded maps for each algorithm and manually performed region-of-interest analyses within visually identified tumor hotspots for quantification. Relative values of cerebral blood flow (rCBF), cerebral blood volume (rCBV), and mean transit time (rMTT) were normalized to contralateral normal-appearing white matter. Nonparametric tests evaluated group differences. Results The NVM yielded enhanced hotspot delineation and significantly higher median normalized perfusion values than vendor algorithms (all P<.001), with excellent inter-rater reliability (Cohen’s κ and intraclass correlation coefficients ≥0.86). At 3.0 T, NVM-derived rCBV was significantly higher than at 1.5 T (P=.008). Conclusions NVM post-processing yielded higher normalized CBF, CBV, and MTT values within tumor hotspots than vendor pipelines, suggesting that Bayesian model-based perfusion analysis may enhance the detection of microvascular changes in glioblastoma. As validation against a gold standard is missing, prospective multicenter studies are warranted to confirm our findings, particularly with regard to treatment monitoring and clinical decision-making.

Authors with CRIS profile

Philipp Karschnia Department of Neurosurgery Nico Teske Department of Neurosurgery

Involved external institutions

Klinikum der Universität München (LMU Klinikum) DE Germany (DE) Deutsches Krebsforschungszentrum (DKFZ) DE Germany (DE) Universitätsklinikum Knappschaftskrankenhaus Bochum DE Germany (DE) Ludwig-Maximilians-Universität (LMU) DE Germany (DE)

How to cite

APA:

Reis, J., Stahl, R., Müller, K.J., Karschnia, P., Teske, N., Neubauer, A.,... Forbrig, R. (2025). A novel vascular model yields increased MR perfusion metrics compared to conventional dynamic susceptibility contrast algorithms in untreated glioblastoma. Neuro-Oncology Advances, 7(1). https://doi.org/10.1093/noajnl/vdaf212

MLA:

Reis, Jonas, et al. "A novel vascular model yields increased MR perfusion metrics compared to conventional dynamic susceptibility contrast algorithms in untreated glioblastoma." Neuro-Oncology Advances 7.1 (2025).

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