Multimodal Techniques Integration in Brain Tumor
Application of hyperspectral imaging in detecting intracranial gliomas: An experimental study in mice
Chuhua Fu, Zhao Li, Haifeng Wang, Lixian Huang, Tu'nan Chen, Liang Tan, Dayong Zhang, Hua Feng, Fei Li
Published 2018-04-28
Cite as Chin J Neurosurg, 2018, 34(4): 359-364. DOI: 10.3760/cma.j.issn.1001-2346.2018.04.008
Abstract
ObjectiveTo provide experimental foundation for application of hyperspectral imaging (HSI) in precise resection of the glioma and detection of its area and boundary in the mouse brain by HSI.
MethodsGL261 cells were implanted into the brain of C57 mice to generate the glioma. The images of 13 animal brains with gliomas (10 in vitro and 3 in vivo) were obtained by hyperspectral imaging and operating microscope. The spectrum of glioma and normal brain were extracted. The accuracy of HSI images were compared with that of 7.0-T MRI images.
ResultsThe HSI spectrum of tumor mass was significant different from normal brain tissue in the whole range of 460-700 nm. However, the HSI spectrum of infiltrating tumor margin (ITM) showed differences from internal capsule and corpus callosum in 460-600 nm, but no differences from dentate gyrus in the 460-700 nm range. Compared with the cortex and thalamus, the HSI spectral reflectance of ITM was lower in 500-600 nm range, but higher in 650-700 nm range. The mass and the boundary of gliomas could be clearly figured out in the HSI R700/R545 images. Based on the tumor areas calculated by hematoxylin-eosin staining (HE) staining, the accuracies of Red Green Blue (RGB) images, MRI T2, and HSI R700/R545 images were 81.9%±4.5%, 84.4%±4.7% and 92.4%±2.5%, respectively.
ConclusionHSI can be used to identify the mass and boundary of mice gliomas accurately and serve as a potential real-time and label free imaging tool during precise glioma resection.
Key words:
Glioma; Magnetic resonance imaging; Neuronavigation; Hyperspectral imaging; Mice
Contributor Information
Chuhua Fu
Department of Neurosurgery, the First Affiliated Hospital of the Army Medical University, Chongqing 400038, China
Zhao Li
Haifeng Wang
Lixian Huang
Tu'nan Chen
Liang Tan
Dayong Zhang
Hua Feng
Fei Li