This study addresses the pressing need for non-invasive, continuous monitoring of cerebral physiologic derangements following traumatic brain injury (TBI). We combine frequency-domain and broadband diffuse optical spectroscopy with diffuse correlation spectroscopy to monitor cerebral oxygen metabolism, cerebral blood volume, and cerebral water content in an established adult swine-model of focal TBI. Cerebral physiology is monitored before and after TBI (up to 14 days post injury). Overall, our results suggest that non-invasive optics can monitor cerebral physiology impairments such as reduced oxygen metabolism, hemorrhage, and edema formation post-TBI.
Bedside tools are needed to alert clinicians to the onset of ischemic stroke. Resting-state hemodynamics with optical intrinsic signal imaging (OIS) were assessed in mice before and after middle cerebral artery (MCA) stroke. OIS analysis included resting-state functional connectivity (FC), low frequency power (LFP, local brain activity), and temporal-shift delay (impaired perfusion). Immediately after stroke, there is a decrease in homotopic connectivity and an absence of LFP in stroke-affected hemisphere; perfusion deficits were more localized. Over 24 hours, LFP and delayed perfusion localized in the core MCA territory (matching TTC staining). Such biomarker development could translate to optical bedside technologies.
SignificanceStatistical inference in functional neuroimaging is complicated by the multiple testing problem and spatial autocorrelation. Common methods in functional magnetic resonance imaging to control the familywise error rate (FWER) include random field theory (RFT) and permutation testing. The ability of these methods to control the FWER in optical neuroimaging has not been evaluated.AimWe attempt to control the FWER in optical intrinsic signal imaging resting-state functional connectivity using both RFT and permutation inference at a nominal value of 0.05. The FWER was derived using a mass empirical analysis of real data in which the null is known to be true.ApproachData from normal mice were repeatedly divided into two groups, and differences between functional connectivity maps were calculated with pixel-wise t-tests. As the null hypothesis was always true, all positives were false positives.ResultsGaussian RFT resulted in a higher than expected FWER with either cluster-based (0.15) or pixel-based (0.62) methods. t-distribution RFT could achieve FWERs of 0.05 (cluster-based or pixel-based). Permutation inference always controlled the FWER.ConclusionsRFT can lead to highly inflated FWERs. Although t-distribution RFT can be accurate, it is sensitive to statistical assumptions. Permutation inference is robust to statistical errors and accurately controls the FWER.
Significance: The critical closing pressure (CrCP) of cerebral circulation, as measured by diffuse correlation spectroscopy (DCS), is a promising biomarker of intracranial hypertension. However, CrCP techniques using DCS have not been assessed in gold standard experiments.Aim: CrCP is typically calculated by examining the variation of cerebral blood flow (CBF) during the cardiac cycle (with normal sinus rhythm). We compare this typical CrCP measurement with a gold standard obtained during the drops in arterial blood pressure (ABP) caused by rapid ventricular pacing (RVP) in patients undergoing invasive electrophysiologic procedures.Approach: Adults receiving electrophysiology procedures with planned ablation were enrolled for DCS CBF monitoring. CrCP was calculated from CBF and ABP data by three methods: (1) linear extrapolation of data during RVP (CrCPRVP; the gold standard); (2) linear extrapolation of data during regular heartbeats (CrCPLinear); and (3) fundamental harmonic Fourier filtering of data during regular heartbeats (CrCPFourier).Results: CBF monitoring was performed prior to and during 55 episodes of RVP in five adults. CrCPRVP and CrCPFourier demonstrated agreement (R = 0.66, slope = 1.05 (95%CI, 0.72 to 1.38). Agreement between CrCPRVP and CrCPLinear was worse; CrCPLinear was 8.2 ± 5.9 mmHg higher than CrCPRVP (mean ± SD; p < 0.001).Conclusions: Our results suggest that DCS-measured CrCP can be accurately acquired during normal sinus rhythm.
Significance: Resting-state functional connectivity imaging in mice with optical intrinsic signal (OIS) imaging could provide a powerful translational tool for developing imaging biomarkers in preclinical disease models. However, statistical interpretation of correlation coefficients is hampered by autocorrelations in the data.
Aim: We sought to better understand temporal and spatial autocorrelations in optical resting-state data. We then adapted statistical methods from functional magnetic resonance imaging to improve statistical inference.
Approach: Resting-state data were obtained from mice using a custom-built OSI system. The autocorrelation time was calculated at each pixel, and z scores for correlation coefficients were calculated using Fisher transforms and variance derived from either Bartlett’s method or xDF. The significance of each correlation coefficient was determined through control of the false discovery rate (FDR).
Results: Autocorrelation was generally even across the cortex and parcellation reduced variance. Correcting variance with Bartlett’s method resulted in a uniform reduction in z scores, with xDF preserving high z scores for highly correlated data. Control of the FDR resulted in reasonable thresholding of the correlation coefficient matrices. The use of Bartlett’s method compared with xDF results in more conservative thresholding and fewer false positives under null hypothesis conditions.
Conclusions: We developed streamlined methods for control of autocorrelation in OIS functional connectivity data in mice, and Bartlett’s method is a reasonable compromise and simplification that allows for accurate autocorrelation correction. These results improve the rigor and reproducibility of functional neuroimaging in mice.
Hydrocephalus is a disorder of cerebral spinal fluid (CSF) physiology that results in increased intracranial pressure (ICP). It is commonly treated via surgical placement of a shunt in the ventricles to divert CSF. Diffuse optical measurements of cerebral perfusion and oxygen extraction were acquired before and after surgical shunt placement in neonates with hydrocephalus. An invasive ICP measurement was made at the time of shunt placement. Shunting increased cerebral perfusion and decreased oxygen extraction only in infants with elevated ICP. This suggests abnormally low perfusion in patients with elevated ICP, and normal perfusion in patients without elevated ICP.
Extracorporeal membrane oxygenation (ECMO) is an important therapy for critically ill children but survivors have neurodevelopmental impairments. Cerebral inflammatory response resulting in brain edema is observed on ECMO. This pathologic response may adversely impact the quantitative accuracy of diffuse optical spectroscopy (DOS) neuromonitoring (including commercial NIRS) which commonly assumes a 75% water fraction. Using fresh brain tissue desiccation, we directly quantified the severity of cerebral edema in pediatric swine following cardiac arrest, CPR and 22-24 hours of ECMO therapy. The fractional error in DOS quantification of cerebral hemodynamics from assuming 75% water fraction was determined to be <5%.
Monitoring critical closing pressure (CrCP) can be a useful and noninvasive measure of intracranial pressure (ICP), especially in patients with high risk factors for brain injury. We monitored five patients undergoing cardiac ablation procedures using diffuse correlation spectroscopy (DCS). We utilized the prolonged diastolic events that occur during this procedure to validate non-invasive measurements of CrCP with DCS. to estimate the gold standard CrCP during long diastolic events induced during the procedure and compared them to estimations from normal pressure and flow waveforms prior to each event.
Evaluation of the brain’s resting-state is an important window into neuronal function, connectivity, and health. Resting-state brain activity is reflected via neurovascular coupling in low frequency (0.01-0.1 Hz) hemodynamics, and low frequency power (LFP) can be a proxy for regional neuronal activity. In this exploratory study, we measured LFP in cerebral blood flow using diffuse correlation spectroscopy (LFP-DCS) during the course of an asphyxial cardiac arrest model in pediatric swine. The data demonstrate that LFP-DCS has distinct temporal information to blood flow index and may provide an additional biomarker to predict successful recovery after neurologic insults.
Advancements in antenatal and neonatal medicine over the last few decades have led to significant improvement in the survival rates of sick newborn infants. However, this improvement in survival has not been matched by a reduction in neurodevelopmental morbidities with increasing recognition of the diverse cognitive and behavioral challenges that preterm infants face in childhood. Conventional neuroimaging modalities, such as cranial ultrasound and magnetic resonance imaging, provide an important definition of neuroanatomy with recognition of brain injury. However, they fail to define the functional integrity of the immature brain, particularly during this critical developmental period. Diffuse optical tomography methods have established success in imaging adult brain function; however, few studies exist to demonstrate their feasibility in the neonatal population. We demonstrate the feasibility of using recently developed high-density diffuse optical tomography (HD-DOT) to map functional activation of the visual cortex in healthy term-born infants. The functional images show high contrast-to-noise ratio obtained in seven neonates. These results illustrate the potential for HD-DOT and provide a foundation for investigations of brain function in more vulnerable newborns, such as preterm infants.
The neurodevelopmental outcome of neonatal intensive care unit (NICU) infants is a major clinical concern with many infants displaying neurobehavioral deficits in childhood. Functional neuroimaging may provide early recognition of neural deficits in high-risk infants. Near-infrared spectroscopy (NIRS) has the advantage of providing functional neuroimaging in infants at the bedside. However, limitations in traditional NIRS have included contamination from superficial vascular dynamics in the scalp. Furthermore, controversy exists over the nature of normal vascular, responses in infants. To address these issues, we extend the use of novel high-density NIRS arrays with multiple source-detector distances and a superficial signal regression technique to infants. Evaluations of healthy term-born infants within the first three days of life are performed without sedation using a visual stimulus. We find that the regression technique significantly improves brain activation signal quality. Furthermore, in six out of eight infants, both oxy- and total hemoglobin increases while deoxyhemoglobin decreases, suggesting that, at term, the neurovascular coupling in the visual cortex is similar to that found in healthy adults. These results demonstrate the feasibility of using high-density NIRS arrays in infants to improve signal quality through superficial signal regression, and provide a foundation for further development of high-density NIRS as a clinical tool.
Despite the unique brain imaging capabilities and advantages of functional near-infrared spectroscopy (fNIRS), including portability and comprehensive hemodynamic measurement, widespread acceptance in the neuroimaging community has been hampered by low spatial resolution and image localization errors. While recent technical developments such as high-density diffuse optical tomography (HD-DOT) have, in principle, been shown to have superior in silico image quality, the majority of optical imaging studies are still conducted with sparse fNIRS arrays, perhaps partially because the performance increases of HD-DOT appear incremental. Without a quantitative comparative analysis between HD-DOT and fNIRS, using both simulation and in vivo neuroimaging, the implications of the new HD-DOT technology have been difficult to judge. We present a quantitative comparison of HD-DOT and two commonly used fNIRS geometries using (1) standard metrics of image quality, (2) simulated brain mapping tasks, and (3) in vivo visual cortex mapping results in adult humans. The results show that better resolution and lower positional errors are achieved with HD-DOT and that these improvements provide a substantial advancement in neuroimaging capability. In particular, we demonstrate that HD-DOT enables detailed phase-encoded retinotopic mapping, while sparse arrays are limited to imaging individual block-design visual stimuli.
The development of diffuse optical tomography (DOT) methods for neuroimaging of humans is challenging due to the
geometry and light level constraints. A high density imaging array system has been developed and used to demonstrate
the possibility of true tomographic reconstruction of cortical activity within the adult subjects which are consistent with
studies using functional MRI and positron-emission tomography. This work demonstrates the benefits of using high
density imaging array by investigating depth related information available from the increased number of tomographic
measurements. Through the use of depth related sensitivity analysis, it is shown that the use of 4th and 5th nearest
neighbor (NN) measurements, the sensitivity of the data to absorption related changes within the brain are improved
dramatically, as compared to 1st, 2nd or 3rd NN measurements. Additionally, it is shown that by the use of 5th NN
measurements, it is possible to recover changes at depths of up to 20 mm within the brain, which is an improvement
over the use of 4th NN.
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