Abstract
BACKGROUND AND PURPOSE: Malignant glioma is a highly infiltrative malignancy that causes variable disruptions to the structure and function of the cerebrovasculature. While many of these structural disruptions have known correlative histopathologic alterations, the mechanisms underlying vascular dysfunction identified by resting-state blood oxygen level–dependent imaging are not yet known. The purpose of this study was to characterize the alterations that correlate with a blood oxygen level–dependent biomarker of vascular dysregulation.
Materials and Methods: Thirty-two stereotactically localized biopsies were obtained from contrast-enhancing (n = 16) and nonenhancing (n = 16) regions during open surgical resection of malignant glioma in 17 patients. Preoperative resting-state blood oxygen level–dependent fMRI was used to evaluate the relationships between radiographic and histopathologic characteristics. Signal intensity for a blood oxygen level–dependent biomarker was compared with scores of tumor infiltration and microvascular proliferation as well as total cell and neuronal density.
Results: Biopsies corresponded to a range of blood oxygen level–dependent signals, ranging from relatively normal (z = −4.79) to markedly abnormal (z = 8.84). Total cell density was directly related to blood oxygen level–dependent signal abnormality (P = .013, R2 = 0.19), while the neuronal labeling index was inversely related to blood oxygen level–dependent signal abnormality (P = .016, R2 = 0.21). The blood oxygen level–dependent signal abnormality was also related to tumor infiltration (P = .014) and microvascular proliferation (P = .045).
Conclusions: The relationship between local, neoplastic characteristics and a blood oxygen level–dependent biomarker of vascular function suggests that local effects of glioma cell infiltration contribute to vascular dysregulation.
ABBREVIATIONS:
- BOLD
- blood oxygen level–dependent
- CE
- contrast-enhancing
- Gd
- gadolinium
- NE
- nonenhancing
Footnotes
Disclosures: Peter D. Chang—RELATED: Provision of Writing Assistance, Medicines, Equipment, or Administrative Support: NVIDIA Corporation, Comments: donation of graphics-processing unit computing hardware for analysis. Peter Canoll—RELATED: Grant: James S. McDonnell Foundation, Comments: This grant supported the collection and analysis of the localized biopsies*. Jack Grinband—RELATED: Grant: American Society of Neuroradiology*. *Money paid to the institution.
Preliminary results from this work were presented at: Eastern-Atlantic Medical Student Research Forum, March 3–5, 2016; Miami, Florida. Further results were previously presented at: Society of Neuro-Oncology Annual Meeting and Education Day, November 17–22, 2016; Scottsdale, Arizona.
This project was funded, in part, by the 2015 Research Scientist Award from the American Society of Neuroradiology (J.G.), the James S. McDonnell Foundation, and the Irving Institute for Clinical and Translational Research: Pilot Research Award (P.C.). Support from NVIDIA included 1 TITAN X Graphic Card (12 GB) to run a deep learning code to perform cell counting (P.D.C.). Dr Chang's salary is supported by the National Institutes of Health (National Institute of Biomedical Imaging and Bioengineering) T32 Training Grant, T32EB001631.
- © 2018 by American Journal of Neuroradiology
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