Feasibility of NIRS in the Neurointensive Care Unit: A Pilot Study in Stroke Using Physiological Oscillations

Abstract

Introduction Near-infrared spectroscopy (NIRS) is a non-invasive, real-time bedside modality sensitive to changes in cerebral perfusion and oxygenation and is highly sensitive to physiological oscillations at different frequencies. However, the clinical feasibility of NIRS remains limited, partly due to concerns regarding NIRS signal quantification, which relies on mostly arbitrary assumptions on hemoglobin concentrations and tissue layers. In this pilot study comparing stroke patients to healthy controls, we explored the utility of the interhemispheric correlation coefficient (IHCC) during physiological oscillations in detecting asymmetry in hemispheric microvascular hemodynamics. Methods Using bi-hemispheric continuous-wave NIRS, 12 patients with hemispheric strokes and 9 controls were measured prospectively. NIRS signal was band-pass filtered to isolate cardiac (0.7–3 Hz) and respiratory (0.15–0.7 Hz) oscillations. IHCCs were calculated in both oscillation frequency bands. Using Fisher’s Z-transform for non-Gaussian distributions, the IHCC during cardiac and respiratory oscillations were compared between both groups. Results Nine patients and nine controls had data of sufficient quality to be included in the analysis. The IHCCs during cardiac and respiratory oscillations were significantly different between patients versus controls (cardiac 0.79 ± 0.18 vs. 0.94 ± 0.07, P = 0.025; respiratory 0.24 ± 0.28 vs. 0.59 ± 0.3; P = 0.016). Conclusions Computing the IHCC during physiological cardiac and respiratory oscillations may be a new NIRS analysis technique to quantify asymmetric microvascular hemodynamics in stroke patients in the neurocritical care unit. It allows each subject to serve as their own control obviating the need for arbitrary assumptions on absolute hemoglobin concentration. Future clinical applications may include rapid identification of patients with ischemic brain injury in the pre-hospital setting. This promising new analysis technique warrants further validation.

Transcranial Direct Current Stimulation in Stroke Rehabilitation: A Review of Recent Advancements

“…Using data from diffusion magnetic resonance imaging, Crofts and Higham [152] compared connectivity between 56 brain areas in stroke patients and healthy controls and showed decreased communication among a number of brain regions in stroke patients. Similar results were obtained using near-infrared spectroscopy [153], showing that the interhemispheric correlation coefficient was reduced in stroke patients. Consistent with these results is the reduction in interhemispheric functional connectivity in a rat model of stroke using low-frequency BOLD fluctuations in MRI [154].…”

Detection of cerebral ischemia using the power spectrum of the pulse wave measured by near-infrared spectroscopy

“…42 Asymmetry in cerebral hemodynamics between hemispheres due to cardiac oscillations could be detected by continuous-wave NIRS. 43 We compared the mean pulse-wave power on the ipsilateral side that included the ischemic region with the mean pulse-wave power from a symmetrical region on the contralateral side of the head. This was done to reduce the influence of differences in optical path lengths at different recording sites.…”

Motion artifacts in functional near-infrared spectroscopy: A comparison of motion correction techniques applied to real cognitive data

“…fNIRS is becoming more and more common in the study of infants (Lloyd-Fox et al, 2010; Taga et al, 2011; Wilcox et al, 2010), cognition (Cutini et al, 2012a; Köchel et al, 2011; Tupak et al, 2012), motor tasks (Brigadoi et al, 2012; Perrey, 2008) and in studies with difficult and hard-to-test populations, e.g. stroke patients (Lin et al, 2012; Muehlschlegel et al, 2009; Obrig and Steinbrink, 2011). Although the improvement in fNIRS technology has been significant in recent years, effectively coupling the sources and the detectors to the head can be problematic and motion artifacts are often a significant component of the measured fNIRS signal.…”