Purpose: Superficial temporal artery (STA)—middle cerebral artery (MCA) bypass is an important technique for cerebrovascular reconstruction. Intraoperative hemodynamic imaging is needed to perform cerebrovascular reconstruction safely and effectively. Optical intrinsic signal (OIS) imaging is commonly used for assessing cerebral hemodynamics in experimental studies, because it can provide high-resolution mapping images. However, OIS is not used clinically due to algorithm, instrumentation and spectral resolution limitations. We tested the feasibility of a hyperspectral camera (HSC) for assessment of cortical hemodynamics with spectral imaging of the cerebral cortex in rats and in vivo humans.
Methods: A hyperspectral camera (HSC) was tested in a rat model of cerebral ischemia (middle cerebral artery occlusion) and during human revascularization surgery (STA–MCA anastomosis). Changes in cortical oxygen saturation were derived from spectral imaging data (400–800 nm) collected by exposing the cortex to Xenon light. Reflected light was sampled using the HSC. The system was then tested intraoperatively during superficial temporal artery to middle cerebral artery anastomosis procedures. Comparison with single-photon emission computed tomography (SPECT) imaging data was done.
Results: During middle cerebral artery occlusion in rats, the HSC technique showed a significant decrease in cortical oxygen saturation in the ischemic hemisphere. In clinical cases, the cortical oxygen saturation was increased after STA–MCA anastomosis, which agreed with the SPECT imaging data.
Conclusion: Continuous collection of imaging spectroscopic data is feasible and may provide reliable quantification of the hemodynamic responses in the brain. The HSC system may be useful for monitoring intraoperative changes in cortical surface hemodynamics during revascularization procedures in humans.
|Number of pages||14|
|Journal||International Journal of Computer Assisted Radiology and Surgery|
|Publication status||Published - Nov 2014|
All Science Journal Classification (ASJC) codes
- Biomedical Engineering
- Radiology Nuclear Medicine and imaging
- Computer Vision and Pattern Recognition
- Health Informatics
- Computer Science Applications
- Computer Graphics and Computer-Aided Design