Despite continued improvements, major vascular and cardiac surgeries involving cardio-pulmonary bypass (CPB) still result in high rates of neurological injury. Pathophysiologic changes during CPB result in pharmacokinetic alterations that complicate the management of anesthesia and significantly alter major organ blood flow. Both anesthetic and analgesic agents target the central nervous system and, in conjunction with potentially impaired cerebral auto-regulation, can result in insufficient delivery of oxygen to the brain. While systemic hemodynamic and respiratory monitoring of the patients has been used for a long time, there is no accepted standard for assessing brain health. A number of cerebral oximeters, based on continuous-wave near-infrared spectroscopy measurements exist on the market. However, despite studies showing some utility in that drops in brain hemoglobin oxygen saturation (SO2) during surgery have been correlated with neurological deficits, they have not been adopted as clinical standards. This is largely because they are based on inexpensive technology and approaches that require many assumptions, making them sensitive to extracerebral contamination and unable to provide a quantitative threshold for guiding clinical interventions. Further, interpretation of SO2 alone is ambiguous, as it reflects the combined influence of multiple systemic and cerebral physiological parameters and clinical conditions, including cerebral blood flow, oxygen consumption, hematocrit, and temperature. In this application, we propose to develop a state-of-the art non-invasive brain health monitoring tool to provide real-time feedback on multiple aspects of the brain functional status. Leveraging the substantial experience of our group in instrumentation development, we will combine frequency domain near-infrared spectroscopy as well as diffuse correlation spectroscopy measurements at multiple distances with intrinsic or ultrasound assisted estimates of tissue layer thicknesses to obtain quantitative measures of perfusion, hemoglobin oxygenation and cerebral oxygen metabolism by means of innovative Monte Carlo based light transport modeling algorithms. We will determine the accuracy and precision of our measurements using both tissue-realistic phantoms and a miniature pig animal model. Next, we will perform validation measurements in healthy human subjects during normoxic, hyperoxic and hypercapnic states while monitoring brain perfusion and regional venous oxygenation using MRI methods. Finally, we will perform a pilot clinical measurements in patients undergoing cardiovascular surgery under cardio-pulmonary bypass. We hypothesize that decreases in brain oxygenation and perfusion during surgery are predictive of neurological injury, development of new ischemic lesions on diffusion weighted MRI and extended hospital stay and superior to current cerebral oximeters. We will demonstrate the feasibility of monitoring cerebral health using our device in the operating room and the collected data will serve as a basis for further hypothesis generation and to plan follow-up, targeted clinical studies. We hope to offer a significant advance in the state-of-the art of non-invasive neuromonitoring tools, and enable a new level of personalized care that can lead to a reduction in negative outcomes resulting from surgical procedures under cardio-pulmonary bypass.

Public Health Relevance

Despite continued improvements, major vascular and cardiac surgeries involving cardio-pulmonary bypass still result in high rates of neurological injury. We propose to develop a state-of-the art non-invasive brain health monitoring tool to provide real-time feedback on multiple aspects of brain function during bypass procedures. In the long term, we hope an effective neuromonitoring tool could be used to provide personalized care and reduce negative outcomes from major cardio-vascular surgery.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS100750-03
Application #
9828111
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Koenig, James I
Project Start
2017-12-01
Project End
2022-11-30
Budget Start
2019-12-01
Budget End
2020-11-30
Support Year
3
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
Cheng, Xiaojun; Tamborini, Davide; Carp, Stefan A et al. (2018) Time domain diffuse correlation spectroscopy: modeling the effects of laser coherence length and instrument response function. Opt Lett 43:2756-2759