Header

UZH-Logo

Maintenance Infos

Feasibility of glioblastoma tissue response mapping with physiologic BOLD imaging using precise oxygen and carbon dioxide challenge


Stumpo, Vittorio; Sebök, Martina; van Niftrik, Christiaan Hendrik Bas; Seystahl, Katharina; Hainc, Nicolin; Kulcsar, Zsolt; Weller, Michael; Regli, Luca; Fierstra, Jorn (2022). Feasibility of glioblastoma tissue response mapping with physiologic BOLD imaging using precise oxygen and carbon dioxide challenge. Magma, 35(1):29-44.

Abstract

Objectives: Innovative physiologic MRI development focuses on depiction of heterogenous vascular and metabolic features in glioblastoma. For this feasibility study, we employed blood oxygenation level-dependent (BOLD) MRI with standardized and precise carbon dioxide (CO2) and oxygen (O2) modulation to investigate specific tumor tissue response patterns in patients with newly diagnosed glioblastoma.

Materials and methods: Seven newly diagnosed untreated patients with suspected glioblastoma were prospectively included to undergo a BOLD study with combined CO2 and O2 standardized protocol. %BOLD signal change/mmHg during hypercapnic, hypoxic, and hyperoxic stimulus was calculated in the whole brain, tumor lesion and segmented volumes of interest (VOI) [contrast-enhancing (CE) - tumor, necrosis and edema] to analyze their tissue response patterns.

Results: Quantification of BOLD signal change after gas challenges can be used to identify specific responses to standardized stimuli in glioblastoma patients. Integration of this approach with automatic VOI segmentation grants improved characterization of tumor subzones and edema. Magnitude of BOLD signal change during the 3 stimuli can be visualized at voxel precision through color-coded maps overlayed onto whole brain and identified VOIs.

Conclusions: Our preliminary investigation shows good feasibility of BOLD with standardized and precise CO2 and O2 modulation as an emerging physiologic imaging technique to detail specific glioblastoma characteristics. The unique tissue response patterns generated can be further investigated to better detail glioblastoma lesions and gauge treatment response.

Keywords: BOLD; Carbon dioxide; Cerebrovascular reactivity; Glioblastoma; Hypercapnia; Hyperoxia; Hypoxia; Oxygen.

Abstract

Objectives: Innovative physiologic MRI development focuses on depiction of heterogenous vascular and metabolic features in glioblastoma. For this feasibility study, we employed blood oxygenation level-dependent (BOLD) MRI with standardized and precise carbon dioxide (CO2) and oxygen (O2) modulation to investigate specific tumor tissue response patterns in patients with newly diagnosed glioblastoma.

Materials and methods: Seven newly diagnosed untreated patients with suspected glioblastoma were prospectively included to undergo a BOLD study with combined CO2 and O2 standardized protocol. %BOLD signal change/mmHg during hypercapnic, hypoxic, and hyperoxic stimulus was calculated in the whole brain, tumor lesion and segmented volumes of interest (VOI) [contrast-enhancing (CE) - tumor, necrosis and edema] to analyze their tissue response patterns.

Results: Quantification of BOLD signal change after gas challenges can be used to identify specific responses to standardized stimuli in glioblastoma patients. Integration of this approach with automatic VOI segmentation grants improved characterization of tumor subzones and edema. Magnitude of BOLD signal change during the 3 stimuli can be visualized at voxel precision through color-coded maps overlayed onto whole brain and identified VOIs.

Conclusions: Our preliminary investigation shows good feasibility of BOLD with standardized and precise CO2 and O2 modulation as an emerging physiologic imaging technique to detail specific glioblastoma characteristics. The unique tissue response patterns generated can be further investigated to better detail glioblastoma lesions and gauge treatment response.

Keywords: BOLD; Carbon dioxide; Cerebrovascular reactivity; Glioblastoma; Hypercapnia; Hyperoxia; Hypoxia; Oxygen.

Statistics

Citations

Dimensions.ai Metrics
2 citations in Web of Science®
1 citation in Scopus®
Google Scholar™

Altmetrics

Downloads

21 downloads since deposited on 09 Dec 2021
20 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Neurology
04 Faculty of Medicine > University Hospital Zurich > Clinic for Neuroradiology
04 Faculty of Medicine > University Hospital Zurich > Clinic for Neurosurgery
Dewey Decimal Classification:610 Medicine & health
Uncontrolled Keywords:Radiology Nuclear Medicine and imaging, Radiological and Ultrasound Technology, Biophysics
Language:English
Date:1 February 2022
Deposited On:09 Dec 2021 04:35
Last Modified:07 Dec 2022 01:00
Publisher:Springer
ISSN:0968-5243
OA Status:Green
Publisher DOI:https://doi.org/10.1007/s10334-021-00980-7
PubMed ID:34874499
  • Content: Accepted Version