In this pilot study, we observed that IHCCs of CW-NIRS at both cardiac and respiratory oscillation frequencies were significantly different between stroke patients and healthy controls. The strength of the study is the application of a novel analysis technique using IHCC that allows each subject to serve as their own control obviating the need for controversial assumptions on absolute baseline hemoglobin concentration and anatomic variations.
Three different NIRS techniques currently exist, each based on a specific illumination type [23
]: (1) the CW modality is based on constant illumination of the medium, and simply measures the attenuation of light through the head; (2) frequency-domain (FD) devices illuminate the head with intensity-modulated light, and measure both the attenuation and the phase shift of the emerging light; (3) the time-domain (TD) technology is based on short pulses of light, and the time-resolved detection of the shape of the pulse after propagation through the head. In ascending order, CW, FD, and TD-NIRS involve increased cost and technological complexity, but also offer more detailed information about the studied medium. In particular, FD and TD technologies enable the absolute characterization of the optical properties of the head, from which one can retrieve absolute values of cerebral blood volume and oxygenation. This feature is not available with CW systems, which only enable relative measurements of hemoglobin variations. On the other hand, CW devices provide very high temporal resolution (as fast as a few tens of milliseconds), and offer the advantages of low-cost and portability.
In this study, we propose a different approach by taking advantage of the temporal features of the CW signal: rather than measuring the absolute values of hemoglobin concentrations or the amplitude of the concentration oscillations, our analysis focuses on the temporal characteristics of the oscillations. Measuring NIRS signals at the 4 cm light detector distance limits, but does not entirely eliminate signals from the superficial scalp layers. Despite the contribution from the scalp to these signals, we detected a temporal asymmetry during physiological oscillations in stroke patients, hence demonstrating that these signals most likely arise from cerebral structures.
We did not investigate the cause of the reduced IHCCs during these physiological oscillations, but a plausible hypothesis is that this finding is due to a disruption in dynamic cerebral autoregulation (DCA). This is in concordance with other studies examining DCA. In the healthy state, DCA is elicited during fast, short changes in systemic blood pressure or other hemodynamic parameters. These can be induced by a rapid-step decrease in arterial blood pressure, and have traditionally been studied on a macrovascular level using transcranial Doppler [25
]. Several investigators have shown that spontaneous blood pressure oscillations or changes in intrathoracic pressure can be used to study DCA [26
]. CW-NIRS can assess DCA on a microvascular level and supplements TCD [18
]. Other investigators have confirmed that CW-NIRS can non-invasively detect spontaneous oscillations in cerebral blood volume [16
] and CW-NIRS is recently emerging as a new modality to assess dynamic autoregulation [20
]. The interesting observation in our study was that the difference in the IHCC was larger during the lower frequency oscillations. One explanation could be that cardiac oscillations may be too fast to detect the autoregulatory response. Alternatively, it may be that the respiration-induced fluctuations in end-tidal carbon dioxide (CO2
) concentrations produced different degrees of vasodilation on the normal versus injured hemispheres and thereby desynchronized the two hemispheres to a larger degree.
The differences in the IHCCs during physiological oscillations seen in our study could potentially be explained by differences in the degree of carotid disease given that 44% of our patients had high-degree ipsilateral carotid disease. A previous study has shown that perturbations in NIRS patterns may predict misery perfusion in patients with symptomatic carotid disease compared to preserved cerebral perfusion in patients with asymptomatic disease [8
]. In a different study of patients with critically stenosed or occluded carotid arteries using TCD and CW-NIRS combined, the authors concluded that carotid disease may lead to perturbations of DCA [18
]. Yet, neuroimaging was not performed in these patients, and therefore it is not known whether prior strokes were present and might be contributing to the DCA perturbation.
One of the main limitations of this pilot study is the small sample size which may increase the risk of both type 1 and type 2 error, and does not allow for statistical adjustment of covariates such as the presence or degree of carotid stenosis. Furthermore, although there was no difference in the mean age, the stroke and control patients were not age or disease-matched, and therefore we cannot exclude that age or co-morbid conditions were effect modifiers. Another limitation of the present study is the lack of knowledge about the origin of the blood flow detected by NIRS. While we believe that we are measuring signals derived from the underlying brain with little contribution from the skull based on the characteristic physiological oscillations observed in the NIRS signal, therefore suggesting either residual or collateral flow, we are unable to differentiate between the two with the data currently collected. Therefore, we cannot correlate the origin of the blood flow to the observed asymmetry in the IHC. Further investigation will be required in order to answer this question, notably by correlating perfusion maps from CT perfusion or MR perfusion to the CW-NIRS oscillations. Finally, 25% of the stroke subjects in this pilot study had to be removed from the analysis because the data did not meet the quality criteria, which in all three cases was due to excessive motion artifacts. Further technical improvement in the probe design and stabilization when attached to the scalp is required to enable good contact of the probe with the scalp during several minutes of recording in intensive care unit patients who are agitated, while still maintaining acceptable levels of patient comfort.
In conclusion, our results suggest that CW-NIRS during physiological cardiac and respiratory oscillations may detect asymmetry in microvascular hemodynamics between hemispheres in stroke patients. Calculating the IHCC may be a useful quantification technique of CW-NIRS signals, obviating the need for assumptions on absolute hemoglobin values or extracranial tissues. Further prospective study involving larger numbers of patients and comparing patients with and without carotid disease as well as comparing the effects of deep and cortical strokes is warranted. This technique could be extended to simultaneous measurements over different territories of the head, in particular for patients where the extent of the injury is unknown.
The results could be applied during non-invasive optical monitoring not just of stroke patients but other patients at risk for primary or secondary brain injury. Conventional bedside monitoring techniques for these patients are mostly invasive and only measure surrogate markers such as intracranial pressure or point source oxygenation. They might be supplemented by CW-NIRS with IHCC calculation as a biomarker of regional microperfusion, once this technique has been further validated and proven to provide robust data with negligible artifact. In addition, if this technique could reliably identify patients with ischemic brain injury in the pre-hospital setting, it could potentially be useful in the selected triage of patients for thrombolytic or neuroprotective strategies.