How does obstructive sleep apnea alter cerebral hemodynamics?

Sleep Disordered Breathing and Neurocognitive Disorders

Sleep-disordered breathing (SDB), which includes conditions such as obstructive sleep apnea (OSA) and central sleep apnea (CSA), is an independent risk factor for cerebral small vessel disease (CSVD), stroke, heart failure, arrhythmias, and other cardiovascular disorders. The influence of OSA on brain structure and cognitive function has become an essential focus in the heart-brain axis, given its potential role in developing neurocognitive abnormalities. In this review, we found that OSA plays a significant role in the cardio-neural pathway that leads to the development of cerebral small vessel disease and neurocognitive decline. Although data is still limited on this topic, understanding the critical role of OSA in the heart-brain axis could lead to the utilization of imaging modalities to simultaneously identify early signs of pathology in both organ systems based on the known OSA-driven pathological pathways that result in a disease state in both the cardiovascular and cerebrovascular systems. This narrative review aims to summarize the current link between OSA and neurocognitive disorders, cardio-neural pathophysiology, and the treatment options available for patients with OSA-related neurocognitive disorders.

Comparing the performance potential of speckle contrast optical spectroscopy and diffuse correlation spectroscopy for cerebral blood flow monitoring using Monte Carlo simulations in realistic head geometries

Significance

The non-invasive measurement of cerebral blood flow based on diffuse optical techniques has seen increased interest as a research tool for cerebral perfusion monitoring in critical care and functional brain imaging. Diffuse correlation spectroscopy (DCS) and speckle contrast optical spectroscopy (SCOS) are two such techniques that measure complementary aspects of the fluctuating intensity signal, with DCS quantifying the temporal fluctuations of the signal and SCOS quantifying the spatial blurring of a speckle pattern. With the increasing interest in the use of these techniques, a thorough comparison would inform new adopters of the benefits of each technique.

Aim

We systematically evaluate the performance of DCS and SCOS for the measurement of cerebral blood flow.

Approach

Monte Carlo simulations of dynamic light scattering in an MRI-derived head model were performed. For both DCS and SCOS, estimates of sensitivity to cerebral blood flow changes, coefficient of variation of the measured blood flow, and the contrast-to-noise ratio of the measurement to the cerebral perfusion signal were calculated. By varying complementary aspects of data collection between the two methods, we investigated the performance benefits of different measurement strategies, including altering the number of modes per optical detector, the integration time/fitting time of the speckle measurement, and the laser source delivery strategy.

Results

Through comparison across these metrics with simulated detectors having realistic noise properties, we determine several guiding principles for the optimization of these techniques and report the performance comparison between the two over a range of measurement properties and tissue geometries. We find that SCOS outperforms DCS in terms of contrast-to-noise ratio for the cerebral blood flow signal in the ideal case simulated here but note that SCOS requires careful experimental calibrations to ensure accurate measurements of cerebral blood flow.

Conclusion

We provide design principles by which to evaluate the development of DCS and SCOS systems for their use in the measurement of cerebral blood flow.