Dynamic Assessment of Cerebral Metabolic Rate of Oxygen (cmro2) With Magnetic Resonance Imaging

The brain is almost entirely dependent on oxidative metabolism to meet its energy requirements. As such, the cerebral metabolic rate of oxygen (CMRO2) is a direct measure of brain energy use. CMRO2 provides insight into brain functional architecture and has demonstrated potential as a clinical tool for assessing many common neurological disorders. Recent developments in magnetic resonance imaging (MRI)-based CMRO2 quantification have shown promise in spatially resolving CMRO2 in clinically feasible scan times. However, brain energy requirements are both spatially heterogeneous and temporally dynamic, responding to rapid changes in oxygen supply and demand in response to physiologic stimuli and neuronal activation. Methods for dynamic quantification of CMRO2 are lacking, and this dissertation aims to address this gap. Given the fundamental tradeoff between spatial and temporal resolution in MRI, we focus initially on the latter. Central to each proposed method is a model-based approach for deriving venous oxygen saturation (Yv) – the critical parameter for CMRO2 quantification – from MRI signal phase using susceptometry-based oximetry (SBO). First, a three-second-temporal-resolution technique for whole-brain quantification of Yv and CMRO2 is presented. This OxFlow method is applied to measure a small but highly significant increase in CMRO2 in response to volitional apnea. Next, OxFlow is combined with a competing approach for Yv quantification based on blood T2 relaxometry (TRUST). The resulting interleaved-TRUST (iTRUST) pulse sequence greatly improves T2-based CMRO2 quantification, while allowing direct, simultaneous comparison of SBO- and T2-based Yv. iTRUST is applied to assess the CMRO2 response to hypercapnia – a topic of great interest in functional neuroimaging – demonstrating significant biases between SBO- and T2-derived Yv and CMRO2. To address the need for dynamic and spatially resolved CMRO2 quantification, we explore blood-oxygen-level-dependent (BOLD) calibration, introducing a new calibration model and hybrid pulse sequence combining OxFlow with standard BOLD/CBF measurement. Preliminary results suggest Ox-BOLD provides improved calibration “M-maps” for converting BOLD signal to CMRO2. Finally, OxFlow is applied clinically to patients with obstructive sleep apnea (OSA). A small clinical pilot study demonstrates OSA-associated reductions in CMRO2 at baseline and in response to apnea, highlighting the potential utility of dynamic CMRO2 quantification in assessing neuropathology

Digging Deeper with Diffuse Correlation Spectroscopy

Patients with neurological diseases are vulnerable to cerebral ischemia, which can lead to brain injury. In the intensive care unit (ICU), neuromonitoring techniques that can detect flow reductions would enable timely administration of therapies aimed at restoring adequate cerebral perfusion, thereby avoiding damage to the brain. However, suitable bedside neuromonitoring methods sensitive to changes of blood flow and/or oxygen metabolism have yet to be established. Near-infrared spectroscopy (NIRS) is a promising technique capable of non-invasively monitoring flow and oxygenation. Specifically, diffuse correlation spectroscopy (DCS) and time-resolved (TR) NIRS can be used to monitor blood flow and tissue oxygenation, respectively, and combined to measuring oxidative metabolism. The work presented in this thesis focused on advancing a DCS/TR-NIRS hybrid system for acquiring these physiological measurements at the bedside. The application of NIRS for neuromonitoring is favourable in the neonatal ICU since the relatively thin scalp and skull of infants has minimal effect on the detected optical signal. Considering this application, the validation of a combined DCS/NIRS method for measuring the cerebral metabolic rate of oxygen (CMRO2) was investigated in Chapter 2. Although perfusion changes measured by DCS have been confirmed by various flow modalities, characterization of photon scattering in the brain is not clearly understood. Chapter 3 presents the first DCS study conducted directly on exposed cortex to confirm that the Brownian motion model is the best flow model for characterizing the DCS signal. Furthermore, a primary limitation of DCS is signal contamination from extracerebral tissues in the adult head, causing CBF to be underestimated. In Chapter 4, a multi-layered model was implemented to separate signal contributions from scalp and brain; derived CBF changes were compared to computed tomography perfusion. Overall, this thesis advances DCS techniques by (i) quantifying cerebral oxygen metabolism, (ii) confirming the more appropriate flow model for analyzing DCS data and (iii) demonstrating the ability of DCS to measure CBF accurately despite the presence of a thick (1-cm) extracerebral layer. Ultimately, the work completed in this thesis should help with the development of a hybrid DCS/NIRS system suitable for monitoring cerebral hemodynamics and energy metabolism in critical-ill patients

Hybrid Optical System for Studying the Dynamic Regulation of Blood Flow/Metabolism in the Adult Brain

Cerebral blood flow (CBF) and oxygen delivery are tightly controlled to meet neuronal energy demands; however, studying dynamic neurovascular coupling in the human brain is challenging due to the lack of methods that can measure rapid changes in CBF and tissue oxygenation. This report presents an in-house-developed hybrid time-resolved near-infrared spectroscopy/diffuse correlation spectroscopy (TR-NIRS/DCS) device and its use to track dynamic CBF and tissue oxygen saturation (StO2) responses simultaneously with sub-second resolution following a vasodilatory stimulus (i.e., a hypercapnic challenge). Cerebrovascular reactivity (CVR) experiments were performed on 10 healthy participants (mean age: 27 years) using a computer-controlled gas delivery system to manipulate breath-to-breath inspired CO2 levels. TR-NIRS and DCS data were acquired continuously at a sampling frequency of 3 Hz to capture dynamic CBF and oxygenation responses. CVR measurements derived from oxyhemoglobin and deoxyhemoglobin concentrations were 3.4 ± 2.6 and 3.0 ± 1.9 %/mmHg, respectively. Their dynamic component, a fitted exponential coefficient that defines the speed of the response as per the hemodynamic response function, was estimated to be 32 ± 16 and 33 ± 28 seconds. The corresponding CVR value and dynamic component derived from CBF was 3.5 ± 3.6 %/mmHg and 33 ± 18 seconds. These experiments demonstrated that the optical system had sufficient temporal resolution to capture the dynamics of the oxygenation and CBF responses to a vasodilatory stimulus

Measuring acute effects of subanesthetic ketamine on cerebrovascular hemodynamics in humans using TD-fNIRS

Quantifying neural activity in natural conditions (i.e. conditions comparable to the standard clinical patient experience) during the administration of psychedelics may further our scientific understanding of the effects and mechanisms of action. This data may facilitate the discovery of novel biomarkers enabling more personalized treatments and improved patient outcomes. In this single-blind, placebo-controlled study with a non-randomized design, we use time-domain functional near-infrared spectroscopy (TD-fNIRS) to measure acute brain dynamics after intramuscular subanesthetic ketamine (0.75 mg/kg) and placebo (saline) administration in healthy participants (n = 15, 8 females, 7 males, age 32.4 ± 7.5 years) in a clinical setting. We found that the ketamine administration caused an altered state of consciousness and changes in systemic physiology (e.g. increase in pulse rate and electrodermal activity). Furthermore, ketamine led to a brain-wide reduction in the fractional amplitude of low frequency fluctuations, and a decrease in the global brain connectivity of the prefrontal region. Lastly, we provide preliminary evidence that a combination of neural and physiological metrics may serve as predictors of subjective mystical experiences and reductions in depressive symptomatology. Overall, our study demonstrated the successful application of fNIRS neuroimaging to study the physiological effects of the psychoactive substance ketamine in humans, and can be regarded as an important step toward larger scale clinical fNIRS studies that can quantify the impact of psychedelics on the brain in standard clinical settings

BrainSignals Revisited: Simplifying a Computational Model of Cerebral Physiology

Multimodal monitoring of brain state is important both for the investigation of healthy cerebral physiology and to inform clinical decision making in conditions of injury and disease. Near-infrared spectroscopy is an instrument modality that allows non-invasive measurement of several physiological variables of clinical interest, notably haemoglobin oxygenation and the redox state of the metabolic enzyme cytochrome c oxidase. Interpreting such measurements requires the integration of multiple signals from different sources to try to understand the physiological states giving rise to them. We have previously published several computational models to assist with such interpretation. Like many models in the realm of Systems Biology, these are complex and dependent on many parameters that can be difficult or impossible to measure precisely. Taking one such model, BrainSignals, as a starting point, we have developed several variant models in which specific regions of complexity are substituted with much simpler linear approximations. We demonstrate that model behaviour can be maintained whilst achieving a significant reduction in complexity, provided that the linearity assumptions hold. The simplified models have been tested for applicability with simulated data and experimental data from healthy adults undergoing a hypercapnia challenge, but relevance to different physiological and pathophysiological conditions will require specific testing. In conditions where the simplified models are applicable, their greater efficiency has potential to allow their use at the bedside to help interpret clinical data in near real-time

Multiparametric measurement of cerebral physiology using calibrated fMRI

The ultimate goal of calibrated fMRI is the quantitative imaging of oxygen metabolism (CMRO2), and this has been the focus of numerous methods and approaches. However, one underappreciated aspect of this quest is that in the drive to measure CMRO2, many other physiological parameters of interest are often acquired along the way. This can significantly increase the value of the dataset, providing greater information that is clinically relevant, or detail that can disambiguate the cause of signal variations. This can also be somewhat of a double-edged sword: calibrated fMRI experiments combine multiple parameters into a physiological model that requires multiple steps, thereby providing more opportunity for error propagation and increasing the noise and error of the final derived values. As with all measurements, there is a trade-off between imaging time, spatial resolution, coverage, and accuracy. In this review, we provide a brief overview of the benefits and pitfalls of extracting multiparametric measurements of cerebral physiology through calibrated fMRI experiments

Effects of training and lung volume levels on voice onset control and cortical activation in singers

Singers need to counteract respiratory elastic recoil at high and low lung volume levels (LVLs) to maintain consistent airflow and pressure while singing. Professionally trained singers modify their vocal and respiratory systems creating a physiologically stable and perceptually pleasing voice quality at varying LVLs. In manuscript 1, we compared non-singers and singers on the initiation of a voiceless plosive followed by a vowel at low (30% vital capacity, VC), intermediate (50%VC), and high (80%VC) LVLs. In manuscript 2, we examined how vocal students (singers in manuscript 1) learn to control their voice onset at varying LVLs before and after a semester of voice training within a university program. Also examined were the effects of training level and LVLs on cortical activation patterns between non-singers and singers (manuscript 1), and within vocal students before and after training (manuscript 2) using fNIRS. Results revealed decreased control of voice onset initially in singers prior to training as compared to non-singers, but significant improvements in initial voice onset control after training, although task difficulty continued to alter voice physiology throughout. Cortical activation patterns did not change with training but continued to show increased activation during the most difficult tasks, which was more pronounced after training. Professionally trained techniques for consistent, coordinated voice initiation were shown to alter voice onset following plosive consonants with training. However, in non-singers and, as performance improved in singers after training, cortical activation remained greatest during the tasks at low LVLs when difficulty was highest

Cerebral near infra-red spectroscopy in traumatic brain injury as a potential independent monitoring modality and alternative to invasive tissue oxygen tension sensors

Background: Traumatic brain injury (TBI) is pathology of growing international importance. Near Infrared spectroscopy (NIRS) represents a non-invasive, cost effective and easily applies cerebral tissue monitoring modality with the potential to direct therapy and guide management decisions. Currently the use of this technology within mainstream TBI care is limited considering its potential inherent advantages. Recent advances in NIRS parameter recovery techniques and data processing potentially offer an improvement on previously evaluated technology. Frequency domain (FD) parameter recovery NIRS is one such advancement now available in clinically viable and commercially available devices. This technology has not yet been evaluated within the context of TBI care. Aims: i) To assess the current evidence within the published literature regarding the use of NIRS within the field of TBI management. ii) To compare the abilities of a frequency domain clinically viable point of care NIRS device to radiological and invasive gold standards in measuring changes in cerebral physiology. Methods: A number of specific original investigations to assess the abilities of clinically viable NIRS technology benefiting from FD parameter recovery for use in the management of TBI patients were undertaken along with a review of the existing literature. Results. NIR.S has demonstrated certain useful abilities in the monitoring of cerebral oxygenation in the care of individuals who have sustained a TBI, however sufficient evidence does not exist to support its independent use in TBI. The FD NIRS device tested demonstrated good correlation with fMRI (Valsalva and Hyperventilation), and equivalent abilities in differentiating activity within superficial extra-cranial and cerebral tissue. Manipulating of blood flow into the overlying extra-cranial tissue did not significantly affect the output parameters seen in these models. However the FD NIRS device tested did not demonstrate sufficient abilities to replace invasive brain tissue oxygen tension measurement in TBI patients. Also, within the context of controlled hypoxia (relevant to TBI) no discernable advantage was observed in utilising a device benefiting from frequency domain parameter recovery. Conclusion: NIRS still remains the best available prospect for a non-invasive monitoring modality to direct therapy and guide management in TBI care. However, further development and translation of the multitude of advancements in NIRS technology achieved recently in the science of biological optics may be required to realise this potential