The Comparisons of Cerebral Hemodynamics Induced by Obstructive Sleep Apnea with Arousal and Periodic Limb Movement with Arousal: A Pilot NIRS Study

Cumulative brain desaturation: Time to consider brain derived parameters to measure daytime sleepiness in obstructive sleep apnea

OBJECTIVE

/Background: The change in cerebral hemodynamics induced by sleep apneas and hypopneas may contribute to the daytime sleepiness in patients with obstructive sleep apnea (OSA). However, previous studies failed to discovery their relationship. We propose and test a new parameter, the cumulative brain oxygen desaturation, which may contribute to OSA patient's daytime sleepiness.

PATIENTS/METHODS

22 patients with severe OSA (apnea-hypopnea index (AHI) at diagnosis [mean ± standard deviation, std.]: 52.1 ± 21.6/h, median: 45.1/h, interquartile range: 34.4-60.2/h) were monitored by polysomnography during routine continuous positive airway pressure titration. The reductions of brain tissue oxygen saturation (StO2) in all respiratory events at baseline sleep were measured by frequency-domain near-infrared spectroscopy (NIRS). The cumulative brain desaturation was calculated as AHI times the mean StO2 desaturation (i.e., AHI×ΔStO2‾). Similarly, cumulative peripheral desaturation was also calculated, i.e., AHI×ΔSpO2‾ where ΔSpO2‾ was the mean reduction of peripheral arterial oxygen saturation (SpO2). The correlations between Epworth sleepiness scale (ESS) and AHI, ΔStO2‾, AHI×ΔStO2‾, and AHI×ΔSpO2‾ were tested, respectively. Linear regression was applied to predict ESS using AHI×ΔStO2‾ and AHI×ΔSpO2‾, with age and BMI as covariates.

RESULTS

ESS significantly correlates to the cumulative brain desaturation (Pearson's correlation coefficient: 0.68, p = 0.00056), not the other parameters. Regression analysis only finds significant association between ESS and the cumulative cerebral desaturation (p = 0.00195) but not the cumulative peripheral desaturation (p = 0.71).

CONCLUSIONS

The cumulative brain oxygen desaturation, which comprehensively combines total sleep time, the frequency of apnea and hypopnea events, and the severity of cerebral oxygen desaturation, is a new indicator for daytime sleepiness in severe OSA.

Quantitative Changes in Muscular and Capillary Oxygen Desaturation Measured by Optical Sensors during Continuous Positive Airway Pressure Titration for Obstructive Sleep Apnea

Obstructive sleep apnea (OSA) is a common sleep disorder, and continuous positive airway pressure (CPAP) is the most effective treatment. Poor adherence is one of the major challenges in CPAP therapy. The recent boom of wearable optical sensors measuring oxygen saturation makes at-home multiple-night CPAP titrations possible, which may essentially improve the adherence of CPAP therapy by optimizing its pressure in a real-life setting economically. We tested whether the oxygen desaturations (ODs) measured in the arm muscle (arm_OD) by gold-standard frequency-domain multi-distance near-infrared spectroscopy (FDMD-NIRS) change quantitatively with titrated CPAP pressures in OSA patients together with polysomnography. We found that the arm_OD (2.08 ± 1.23%, mean ± standard deviation) was significantly smaller (p-value < 0.0001) than the fingertip OD (finger_OD) (4.46 ± 2.37%) measured by a polysomnography pulse oximeter. Linear mixed-effects models suggested that CPAP pressure was a significant predictor for finger_OD but not for arm_OD. Since FDMD-NIRS measures a mixture of arterial and venous OD, whereas a fingertip pulse oximeter measures arterial OD, our results of no association between arm_OD and finger_OD indicate that the arm_OD mainly represented venous desaturation. Arm_OD measured by optical sensors used for wearables may not be a suitable indicator of the CPAP titration effectiveness.

Predictors of changes in cerebral perfusion and oxygenation during obstructive sleep apnea

Obstructive sleep apnea syndrome (OSAS) is a common sleep disorder. Severe OSAS defined as apnea-hypopnea index (AHI) ≥ 30/h is a risk factor for developing cerebro-cardiovascular diseases. The mechanisms of how repetitive sleep apneas/hypopneas damage cerebral hemodynamics are still not well understood. In this study, changes in blood volume (BV) and oxygen saturation (StO2) in the left forehead of 29 newly diagnosed severe OSAS patients were measured by frequency-domain near-infrared spectroscopy during an incremental continuous positive airway pressure (CPAP) titration protocol together with polysomnography. The coefficients of variation of BV (CV-BV) and the decreases of StO2 (de-StO2) of more than 2000 respiratory events were predicted using linear mixed-effect models, respectively. We found that longer events and apneas rather than hypopneas induce larger changes in CV-BV and stronger cerebral desaturation. Respiratory events occurring during higher baseline StO2 before their onsets, during rapid-eye-movement sleep and those associated with higher heart rate induce smaller changes in CV-BV and de-StO2. The stepwise increased CPAP pressures can attenuate these changes. These results suggest that in severe OSAS the length and the type of respiratory event rather than widely used AHI may be better parameters to indicate the severity of cerebral hemodynamic changes.

The Challenges and Pitfalls of Detecting Sleep Hypopnea Using a Wearable Optical Sensor: Comparative Study

Background

Obstructive sleep apnea (OSA) is the most prevalent respiratory sleep disorder occurring in 9% to 38% of the general population. About 90% of patients with suspected OSA remain undiagnosed due to the lack of sleep laboratories or specialists and the high cost of gold-standard in-lab polysomnography diagnosis, leading to a decreased quality of life and increased health care burden in cardio- and cerebrovascular diseases. Wearable sleep trackers like smartwatches and armbands are booming, creating a hope for cost-efficient at-home OSA diagnosis and assessment of treatment (eg, continuous positive airway pressure [CPAP] therapy) effectiveness. However, such wearables are currently still not available and cannot be used to detect sleep hypopnea. Sleep hypopnea is defined by ≥30% drop in breathing and an at least 3% drop in peripheral capillary oxygen saturation (Spo₂) measured at the fingertip. Whether the conventional measures of oxygen desaturation (OD) at the fingertip and at the arm or wrist are identical is essentially unknown.

Objective

We aimed to compare event-by-event arm OD (arm_OD) with fingertip OD (finger_OD) in sleep hypopneas during both naïve sleep and CPAP therapy.

Methods

Thirty patients with OSA underwent an incremental, stepwise CPAP titration protocol during all-night in-lab video-polysomnography monitoring (ie, 1-h baseline sleep without CPAP followed by stepwise increments of 1 cmH₂O pressure per hour starting from 5 to 8 cmH₂O depending on the individual). Arm_OD of the left biceps muscle and finger_OD of the left index fingertip in sleep hypopneas were simultaneously measured by frequency-domain near-infrared spectroscopy and video-polysomnography photoplethysmography, respectively. Bland-Altman plots were used to illustrate the agreements between arm_OD and finger_OD during baseline sleep and under CPAP. We used t tests to determine whether these measurements significantly differed.

Results

In total, 534 obstructive apneas and 2185 hypopneas were recorded. Of the 2185 hypopneas, 668 (30.57%) were collected during baseline sleep and 1517 (69.43%), during CPAP sleep. The mean difference between finger_OD and arm_OD was 2.86% (95% CI 2.67%-3.06%, t₆₆₇=28.28; P<.001; 95% limits of agreement [LoA] –2.27%, 8.00%) during baseline sleep and 1.83% (95% CI 1.72%-1.94%, t₁₅₁₆=31.99; P<.001; 95% LoA –2.54%, 6.19%) during CPAP. Using the standard criterion of 3% saturation drop, arm_OD only recognized 16.32% (109/668) and 14.90% (226/1517) of hypopneas at baseline and during CPAP, respectively.

Conclusions

arm_OD is 2% to 3% lower than standard finger_OD in sleep hypopnea, probably because the measured arm_OD originates physiologically from arterioles, venules, and capillaries; thus, the venous blood adversely affects its value. Our findings demonstrate that the standard criterion of ≥3% OD drop at the arm or wrist is not suitable to define hypopnea because it could provide large false-negative results in diagnosing OSA and assessing CPAP treatment effectiveness.

A Review of Cerebral Hemodynamics During Sleep Using Near-Infrared Spectroscopy

Investigating cerebral hemodynamic changes during regular sleep cycles and sleep disorders is fundamental to understanding the nature of physiological and pathological mechanisms in the regulation of cerebral oxygenation during sleep. Although sleep neuroimaging methods have been studied and have been well-reviewed, they have limitations in terms of technique and experimental design. Neurologists are convinced that Near-infrared spectroscopy (NIRS) provides essential information and can be used to assist the assessment of cerebral hemodynamics, and numerous studies regarding sleep have been carried out based on NIRS. Thus, a brief historical overview of the sleep studies using NIRS will be helpful for the biomedical students, academicians, and engineers to better understand NIRS from various perspectives. In this study, the existing literature on sleep studies is reviewed, and an overview of the NIRS applications is synthesized and provided. The paper first reviews the application scenarios, as well as the patterns of fluctuation of NIRS, which includes the investigation in regular sleep and sleep-disordered breathing. Various factors such as different sleep stages, populations, and degrees of severity were considered. Furthermore, the experimental design and signal processing, as well as the regulation mechanisms involved in regular and pathological sleep, are investigated and discussed. The strengths and weaknesses of the existing NIRS applications are addressed and presented, which can direct further NIRS analysis and utilization.

Depression is differently associated with sleep measurement in obstructive sleep apnea, restless leg syndrome and periodic limb movement disorder

Depression causes sleep disturbance and is associated with various sleep-related disorders. However, how depression affects the symptomatic presentation of different sleep-related disorders is unclear. In this study, we investigated the sleep parameters of different sleep-related disorders between depressive and non-depressive patients. A total of 785 patients underwent polysomnography in a mental hospital from Jan 2012 to Jun 2013. We first analyzed variables between the depressive and non-depressive groups. The patients were then divided into four groups: obstructive sleep apnea (OSA, n = 339), restless leg syndrome (RLS, n = 51), periodic limb movement disorder (PLMD, n = 58) and comorbid group (OSA and RLS, n = 46). We next compared sleep measures between the depressive and non-depressive subjects within each groups. The patients with OSA and depression were significantly associated with a higher periodic limb movement index. Significantly more patients with RLS patients and depression had initial insomnia complaints. However, significantly more patients with PLMD and depression middle insomnia. Compared with non-depressive population, depressive patients had higher comorbidity with RLS and PLMD. Depression may have different association with the sleep parameters in different sleep-related disorders. Further investigations are needed to investigate how these findings may affect patients' awareness and clinicians' diagnosis and management of sleep-related disorders.

Motion artifact detection and correction in functional near-infrared spectroscopy: a new hybrid method based on spline interpolation method and Savitzky-Golay filtering

Motion artifact contamination in near-infrared spectroscopy (NIRS) data has become an important challenge in realizing the full potential of NIRS for real-life applications. Various motion correction algorithms have been used to alleviate the effect of motion artifacts on the estimation of the hemodynamic response function. While smoothing methods, such as wavelet filtering, are excellent in removing motion-induced sharp spikes, the baseline shifts in the signal remain after this type of filtering. Methods, such as spline interpolation, on the other hand, can properly correct baseline shifts; however, they leave residual high-frequency spikes. We propose a hybrid method that takes advantage of different correction algorithms. This method first identifies the baseline shifts and corrects them using a spline interpolation method or targeted principal component analysis. The remaining spikes, on the other hand, are corrected by smoothing methods: Savitzky-Golay (SG) filtering or robust locally weighted regression and smoothing. We have compared our new approach with the existing correction algorithms in terms of hemodynamic response function estimation using the following metrics: mean-squared error, peak-to-peak error ([Formula: see text]), Pearson's correlation ([Formula: see text]), and the area under the receiver operator characteristic curve. We found that spline-SG hybrid method provides reasonable improvements in all these metrics with a relatively short computational time. The dataset and the code used in this study are made available online for the use of all interested researchers.

Cerebral blood volume and oxygen supply uniformly increase following various intrathoracic pressure strains

Intrathoracic pressure (ITP) swings challenge many physiological systems. The responses of cerebral hemodynamics to different ITP swings are still less well-known due to the complexity of cerebral circulation and methodological limitation. Using frequency-domain near-infrared spectroscopy and echocardiography, we measured changes in cerebral, muscular and cardiac hemodynamics in five graded respiratory maneuvers (RM), breath holding, moderate and strong Valsalva maneuvers (mVM/sVM) with 20 and 40 cmH2O increments in ITP, moderate and strong Mueller maneuvers (mMM/sMM) with 20 and 40 cmH2O decrements in ITP controlled by esophageal manometry. We found cerebral blood volume (CBV) maintains relative constant during the strains while it increases during the recoveries together with increased oxygen supply. By contrast changes in muscular blood volume (MBV) are mainly controlled by systemic changes. The graded changes of ITP during the maneuvers predict the changes of MBV but not CBV. Changes in left ventricular stroke volume and heart rate correlate to MBV but not to CBV. These results suggest the increased CBV after the ITP strains is brain specific, suggesting cerebral vasodilatation. Within the strains, cerebral oxygen saturation only decreases in sVM, indicating strong increment rather than decrement in ITP may be more challenging for the brain.