BOLD contrast in cerebral diffuse glioma imaging: biological foundations and clinical applications—A narrative review

Authors:
Publisher website
Google Scholar
Abstract
Background: Diffuse cerebral gliomas are among the most common malignant brain tumors in adults. Blood oxygen level-dependent (BOLD)–MRI has been widely investigated for assessing functional, vascular, and metabolic alterations in this patient population. However, a comprehensive overview of its biological underpinnings, clinical applications, and emerging translational approaches is lacking. Methods: In the present study we conducted a narrative review on the role of BOLD–MRI in diffuse glioma imaging, from historical and clinical applications to recent translational studies including approaches to detect vascular and metabolic alterations as well as its expanding potential to enhance tumor infiltration assessment and treatment surveillance. Results: Task-based and resting-state BOLD–MRI enable localization of eloquent cortical areas and assessment of functional reorganization, though their accuracy is challenged by neurovascular uncoupling and patient-related variability. Combination with vasoactive stimuli allows cerebrovascular reactivity mapping to uncover vascular dysfunction propagating beyond visible tumor margins, correlating with tumor grade and hemodynamic impairment. Quantitative and calibrated BOLD approaches as well as oxygen modulation during BOLD sequence acquisition provide noninvasive biomarkers of tissue hypoxia, oxygen metabolism, and tumor aggressiveness. Conclusions: Despite extensive research, BOLD contrast holds unexploited potential for enhancing glioma diagnosis and management by capturing critical vascular and metabolic alterations. Although challenges remain pertaining to accuracy and standardization, emerging techniques offer substantial potential for the assessment of tumor infiltration extent and therapy surveillance. Advancing clinical integration will require robust standardization, large-scale validation, and correlation with clinical, molecular, and histopathological data.
Funding Information
  • Swiss Cancer Research Foundation (KFS-3975-08-2016-R)
  • Universität Zürich (FK-23-048)
  • Deutsche Forschungsgemeinschaft (572737263)

This publication has 142 references indexed in Scilit: