The impact of Alzheimer's disease risk factors on the pupillary light response.

Alzheimer's disease (AD) is the leading cause of dementia, and its prevalence is increasing and is expected to continue to increase over the next few decades. Because of this, there is an urgent requirement to determine a way to diagnose the disease, and to target interventions to delay and ideally stop the onset of symptoms, specifically those impacting cognition and daily livelihood. The pupillary light response (PLR) is controlled by the sympathetic and parasympathetic branches of the autonomic nervous system, and impairments to the pupillary light response (PLR) have been related to AD. However, most of these studies that assess the PLR occur in patients who have already been diagnosed with AD, rather than those who are at a higher risk for the disease but without a diagnosis. Determining whether the PLR is similarly impaired in subjects before an AD diagnosis is made and before cognitive symptoms of the disease begin, is an important step before using the PLR as a diagnostic tool. Specifically, identifying whether the PLR is impaired in specific at-risk groups, considering both genetic and non-genetic risk factors, is imperative. It is possible that the PLR may be impaired in association with some risk factors but not others, potentially indicating different pathways to neurodegeneration that could be distinguished using PLR. In this work, we review the most common genetic and lifestyle-based risk factors for AD and identify established relationships between these risk factors and the PLR. The evidence here shows that many AD risk factors, including traumatic brain injury, ocular and intracranial hypertension, alcohol consumption, depression, and diabetes, are directly related to changes in the PLR. Other risk factors currently lack sufficient literature to make any conclusions relating directly to the PLR but have shown links to impairments in the parasympathetic nervous system; further research should be conducted in these risk factors and their relation to the PLR.

Modelling spatiotemporal dynamics of cerebral blood flow using multiple-timepoint arterial spin labelling MRI.

Introduction: Cerebral blood flow (CBF) is an important physiological parameter that can be quantified non-invasively using arterial spin labelling (ASL) imaging. Although most ASL studies are based on single-timepoint strategies, multi-timepoint approaches (multiple-PLD) in combination with appropriate model fitting strategies may be beneficial not only to improve CBF quantification but also to retrieve other physiological information of interest. Methods: In this work, we tested several kinetic models for the fitting of multiple-PLD pCASL data in a group of 10 healthy subjects. In particular, we extended the standard kinetic model by incorporating dispersion effects and the macrovascular contribution and assessed their individual and combined effect on CBF quantification. These assessments were performed using two pseudo-continuous ASL (pCASL) datasets acquired in the same subjects but during two conditions mimicking different CBF dynamics: normocapnia and hypercapnia (achieved through a CO2 stimulus). Results: All kinetic models quantified and highlighted the different CBF spatiotemporal dynamics between the two conditions. Hypercapnia led to an increase in CBF whilst decreasing arterial transit time (ATT) and arterial blood volume (aBV). When comparing the different kinetic models, the incorporation of dispersion effects yielded a significant decrease in CBF (∼10-22%) and ATT (∼17-26%), whilst aBV (∼44-74%) increased, and this was observed in both conditions. The extended model that includes dispersion effects and the macrovascular component has been shown to provide the best fit to both datasets. Conclusion: Our results support the use of extended models that include the macrovascular component and dispersion effects when modelling multiple-PLD pCASL data.

A systematic review of the association between dementia risk factors and cerebrovascular reactivity.

Cumulative evidence suggests that impaired cerebrovascular reactivity (CVR), a regulatory response critical for maintaining neuronal health, is amongst the earliest pathological changes in dementia. However, we know little about how CVR is affected by dementia risk, prior to disease onset. Understanding this relationship would improve our knowledge of disease pathways and help inform preventative interventions. This systematic review investigates 59 studies examining how CVR (measured by magnetic resonance imaging) is affected by modifiable, non-modifiable, and clinical risk factors for dementia. We report that non-modifiable risk (older age and apolipoprotein ε4), some modifiable factors (diabetes, traumatic brain injury, hypertension) and some clinical factors (stroke, carotid artery occlusion, stenosis) were consistently associated with reduced CVR. We also note a lack of conclusive evidence on how other behavioural factors such as physical inactivity, obesity, or depression, affect CVR. This review explores the biological mechanisms underpinning these brain-behaviour associations, highlights evident gaps in the literature, and identifies the risk factors that could be managed to preserve CVR in an effort to prevent dementia.

Estimation of field inhomogeneity map following magnitude-based ambiguity-resolved water-fat separation.

Magnitude-based PDFF (Proton Density Fat Fraction) and R2∗ mapping with resolved water-fat ambiguity is extended to calculate field inhomogeneity (field map) using the phase images. The estimation is formulated in matrix form, resolving the field map in a least-squares sense. PDFF and R2∗ from magnitude fitting may be updated using the estimated field maps. The limits of quantification of our voxel-independent implementation were assessed. Bland-Altman was used to compare PDFF and field maps from our method against a reference complex-based method on 152 UK Biobank subjects (1.5 T Siemens). A separate acquisition (3 T Siemens) presenting field inhomogeneities was also used. The proposed field mapping was accurate beyond double the complex-based limit range. High agreement was obtained between the proposed method and the reference in UK. Robust field mapping was observed at 3 T, for inhomogeneities over 400 Hz including rapid variation across edges. Field mapping following unambiguous magnitude-based water-fat separation was demonstrated in-vivo and showed potential at 3 T.

Vascular smooth muscle cell dysfunction in neurodegeneration.

Vascular smooth muscle cells (VSMCs) are the key moderators of cerebrovascular dynamics in response to the brain's oxygen and nutrient demands. Crucially, VSMCs may provide a sensitive biomarker for neurodegenerative pathologies where vasculature is compromised. An increasing body of research suggests that VSMCs have remarkable plasticity and their pathophysiology may play a key role in the complex process of neurodegeneration. Furthermore, extrinsic risk factors, including environmental conditions and traumatic events can impact vascular function through changes in VSMC morphology. VSMC dysfunction can be characterised at the molecular level both preclinically, and clinically ex vivo. However the identification of VSMC dysfunction in living individuals is important to understand changes in vascular function at the onset and progression of neurological disorders such as dementia, Alzheimer's disease, and Parkinson's disease. A promising technique to identify changes in the state of cerebral smooth muscle is cerebrovascular reactivity (CVR) which reflects the intrinsic dynamic response of blood vessels in the brain to vasoactive stimuli in order to modulate regional cerebral blood flow (CBF). In this work, we review the role of VSMCs in the most common neurodegenerative disorders and identify physiological systems that may contribute to VSMC dysfunction. The evidence collected here identifies VSMC dysfunction as a strong candidate for novel therapeutics to combat the development and progression of neurodegeneration, and highlights the need for more research on the role of VSMCs and cerebrovascular dynamics in healthy and diseased states.

Determination of oxygen relaxivity in oxygen nanobubbles at 3 and 7 Tesla.

OBJECTIVE: Oxygen-loaded nanobubbles have shown potential for reducing tumour hypoxia and improving treatment outcomes, however, it remains difficult to noninvasively measure the changes in partial pressure of oxygen (PO2) in vivo. The linear relationship between PO2 and longitudinal relaxation rate (R1) has been used to noninvasively infer PO2 in vitreous and cerebrospinal fluid, and therefore, this experiment aimed to investigate whether R1 is a suitable measurement to study oxygen delivery from such oxygen carriers. METHODS: T1 mapping was used to measure R1 in phantoms containing nanobubbles with varied PO2 to measure the relaxivity of oxygen (r1Ox) in the phantoms at 7 and 3 T. These measurements were used to estimate the limit of detection (LOD) in two experimental settings: preclinical 7 T and clinical 3 T MRI. RESULTS: The r1Ox in the nanobubble solution was 0.00057 and 0.000235 s-1/mmHg, corresponding to a LOD of 111 and 103 mmHg with 95% confidence at 7 and 3 T, respectively. CONCLUSION: This suggests that T1 mapping could provide a noninvasive method of measuring a > 100 mmHg oxygen delivery from therapeutic nanobubbles.

Pancreas MRI Segmentation Into Head, Body, and Tail Enables Regional Quantitative Analysis of Heterogeneous Disease.

BACKGROUND: Quantitative imaging studies of the pancreas have often targeted the three main anatomical segments, head, body, and tail, using manual region of interest strategies to assess geographic heterogeneity. Existing automated analyses have implemented whole-organ segmentation, providing overall quantification but failing to address spatial heterogeneity. PURPOSE: To develop and validate an automated method for pancreas segmentation into head, body, and tail subregions in abdominal MRI. STUDY TYPE: Retrospective. SUBJECTS: One hundred and fifty nominally healthy subjects from UK Biobank (100 subjects for method development and 50 subjects for validation). A separate 390 UK Biobank triples of subjects including type 2 diabetes mellitus (T2DM) subjects and matched nondiabetics. FIELD STRENGTH/SEQUENCE: A 1.5 T, three-dimensional two-point Dixon sequence (for segmentation and volume assessment) and a two-dimensional axial multiecho gradient-recalled echo sequence. ASSESSMENT: Pancreas segments were annotated by four raters on the validation cohort. Intrarater agreement and interrater agreement were reported using Dice overlap (Dice similarity coefficient [DSC]). A segmentation method based on template registration was developed and evaluated against annotations. Results on regional pancreatic fat assessment are also presented, by intersecting the three-dimensional parts segmentation with one available proton density fat fraction (PDFF) image. STATISTICAL TEST: Wilcoxon signed rank test and Mann-Whitney U-test for comparisons. DSC and volume differences for evaluation. A P value < 0.05 was considered statistically significant. RESULTS: Good intrarater (DSC mean, head: 0.982, body: 0.940, tail: 0.961) agreement and interrater (DSC mean, head: 0.968, body: 0.905, tail: 0.943) agreement were observed. No differences (DSC, head: P = 0.4358, body: P = 0.0992, tail: P = 0.1080) were observed between the manual annotations and our method's segmentations (DSC mean, head: 0.965, body: 0.893, tail: 0.934). Pancreatic body PDFF was different between T2DM and nondiabetics matched by body mass index. DATA CONCLUSION: The developed segmentation's performance was no different from manual annotations. Application on type 2 diabetes subjects showed potential for assessing pancreatic disease heterogeneity. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY STAGE: 3.

A General Model to Calculate the Spin-Lattice Relaxation Rate (R1) of Blood, Accounting for Hematocrit, Oxygen Saturation, Oxygen Partial Pressure, and Magnetic Field Strength Under Hyperoxic Conditions.

BACKGROUND: Under normal physiological conditions, the spin-lattice relaxation rate (R1) in blood is influenced by many factors, including hematocrit, field strength, and the paramagnetic effects of deoxyhemoglobin and dissolved oxygen. In addition, techniques such as oxygen-enhanced magnetic resonance imaging (MRI) require high fractions of inspired oxygen to induce hyperoxia, which complicates the R1 signal further. A quantitative model relating total blood oxygen content to R1 could help explain these effects. PURPOSE: To propose and assess a general model to estimate the R1 of blood, accounting for hematocrit, SO2 , PO2 , and B0 under both normal physiological and hyperoxic conditions. STUDY TYPE: Mathematical modeling. POPULATION: One hundred and twenty-six published values of R1 from phantoms and animal models. FIELD STRENGTH/SEQUENCE: 5-8.45 T. ASSESSMENT: We propose a two-compartment nonlinear model to calculate R1 as a function of hematocrit, PO2 , and B0. The Akaike Information Criterion (AIC) was used to select the best-performing model with the fewest parameters. A previous model of R1 as a function of hematocrit, SO2 , and B0 has been proposed by Hales et al, and our work builds upon this work to make the model applicable under hyperoxic conditions (SO2  > 0.99). Models were assessed using the AIC, mean squared error (MSE), coefficient of determination (R2 ), and Bland-Altman analysis. The effect of volume fraction constants WRBC and Wplasma was assessed by the SD of resulting R1. The range of the model was determined by the maximum and minimum B0, hematocrit, SO2 , and PO2 of the literature data points. STATISTICAL TESTS: Bland-Altman, AIC, MSE, coefficient of determination (R2 ), SD. RESULTS: The model estimates agreed well with the literature values of R1 of blood (R2  = 0.93, MSE = 0.0013 s-2 ), and its performance was consistent across the range of parameters: B0 = 1.5-8.45 T, SO2  = 0.40-1, PO2  = 30-700 mmHg. DATA CONCLUSION: Using the results from this model, we have quantified and explained the contradictory decrease in R1 reported in oxygen-enhanced MRI and oxygen-delivery experiments. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 1.

Cerebrovascular Reactivity Mapping Without Gas Challenges: A Methodological Guide.

Cerebrovascular reactivity (CVR) is defined as the ability of vessels to alter their caliber in response to vasoactive factors, by means of dilating or constricting, in order to increase or decrease regional cerebral blood flow (CBF). Importantly, CVR may provide a sensitive biomarker for pathologies where vasculature is compromised. Furthermore, the spatiotemporal dynamics of CVR observed in healthy subjects, reflecting regional differences in cerebral vascular tone and response, may also be important in functional MRI studies based on neurovascular coupling mechanisms. Assessment of CVR is usually based on the use of a vasoactive stimulus combined with a CBF measurement technique. Although transcranial Doppler ultrasound has been frequently used to obtain global flow velocity measurements, MRI techniques are being increasingly employed for obtaining CBF maps. For the vasoactive stimulus, vasodilatory hypercapnia is usually induced through the manipulation of respiratory gases, including the inhalation of increased concentrations of carbon dioxide. However, most of these methods require an additional apparatus and complex setups, which not only may not be well-tolerated by some populations but are also not widely available. For these reasons, strategies based on voluntary breathing fluctuations without the need for external gas challenges have been proposed. These include the task-based methodologies of breath holding and paced deep breathing, as well as a new generation of methods based on spontaneous breathing fluctuations during resting-state. Despite the multitude of alternatives to gas challenges, existing literature lacks definitive conclusions regarding the best practices for the vasoactive modulation and associated analysis protocols. In this work, we perform an extensive review of CVR mapping techniques based on MRI and CO2 variations without gas challenges, focusing on the methodological aspects of the breathing protocols and corresponding data analysis. Finally, we outline a set of practical guidelines based on generally accepted practices and available data, extending previous reports and encouraging the wider application of CVR mapping methodologies in both clinical and academic MRI settings.

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.

Rapid cerebrovascular reactivity mapping: Enabling vascular reactivity information to be routinely acquired.

Cerebrovascular reactivity mapping (CVR), using magnetic resonance imaging (MRI) and carbon dioxide as a stimulus, provides useful information on how cerebral blood vessels react under stress. This information has proven to be useful in the study of vascular disorders, dementia and healthy ageing. However, clinical adoption of this form of CVR mapping has been hindered by relatively long scan durations of 7-12 min. By replacing the conventional block presentation of carbon dioxide enriched air with a sinusoidally modulated stimulus, the aim of this study was to investigate whether more clinically acceptable scan durations are possible. Firstly, the conventional block protocol was compared with a sinusoidal protocol of the same duration of 7 min. Estimates of the magnitude of the CVR signal (CVR magnitude) were found to be in good agreement between the stimulus protocols, but estimates of the relative timing of the CVR response (CVR phase) were not. Secondly, data from the sinusoidal protocol was reanalysed using decreasing amounts of data in the range 1-6 min. The CVR magnitude was found to tolerate this reduction in scan duration better than CVR phase. However, these analyses indicate that scan durations in the range of 3-5 min produce robust data.

Investigating the dependence of the calibration parameter M on echo time.

PURPOSE: The calculation of the calibration parameter M, which represents the maximum theoretically possible blood oxygen level dependent (BOLD) signal increase, is an essential intermediate step in any calibrated fMRI experiment. To better compare M values obtained across different studies, it is common to scale M values from their original BOLD echo time (TE) to a different echo time according to the theory that M is directly proportional to TE. To the best of our knowledge, this relationship has never been directly tested. THEORY AND METHODS: A pseudocontinuous arterial spin labeling sequence with five readouts (TE ranging from 20 to 78 ms) was implemented to test the relationship between M and TE, both with and without the application of flow crushing gradients. RESULTS: Both M and the BOLD signal were found to be linear functions of TE, but with a nonzero intercept. This intercept was reduced when crusher gradients were added, suggesting that the deviation from theory is a result of nonnegligible intravascular signal. CONCLUSION: The linear scaling method introduces some error when comparing M values acquired with different BOLD echo times. However, this error is small compared with other considerations, and would generally not preclude the continued use of this scaling method.

Sources of systematic error in calibrated BOLD based mapping of baseline oxygen extraction fraction.

Recently a new class of calibrated blood oxygen level dependent (BOLD) functional magnetic resonance imaging (MRI) methods were introduced to quantitatively measure the baseline oxygen extraction fraction (OEF). These methods rely on two respiratory challenges and a mathematical model of the resultant changes in the BOLD functional MRI signal to estimate the OEF. However, this mathematical model does not include all of the effects that contribute to the BOLD signal, it relies on several physiological assumptions and it may be affected by intersubject physiological variability. The aim of this study was to investigate these sources of systematic error and their effect on estimating the OEF. This was achieved through simulation using a detailed model of the BOLD signal. Large ranges for intersubject variability in baseline physiological parameters such as haematocrit and cerebral blood volume were considered. Despite this the uncertainty in the relationship between the measured BOLD signals and the OEF was relatively low. Investigations of the physiological assumptions that underlie the mathematical model revealed that OEF measurements are likely to be overestimated if oxygen metabolism changes during hypercapnia or cerebral blood flow changes under hyperoxia. Hypoxic hypoxia was predicted to result in an underestimation of the OEF, whilst anaemic hypoxia was found to have only a minimal effect.

Investigating the field-dependence of the Davis model: Calibrated fMRI at 1.5, 3 and 7T.

Gas calibrated fMRI in its most common form uses hypercapnia in conjunction with the Davis model to quantify relative changes in the cerebral rate of oxygen consumption (CMRO2) in response to a functional stimulus. It is most commonly carried out at 3T but, as 7T research scanners are becoming more widespread and the majority of clinical scanners are still 1.5T systems, it is important to investigate whether the model used remains accurate across this range of field strengths. Ten subjects were scanned at 1.5, 3 and 7T whilst performing a bilateral finger-tapping task as part of a calibrated fMRI protocol, and the results were compared to a detailed signal model. Simulations predicted an increase in value and variation in the calibration parameter M with field strength. Two methods of defining experimental regions of interest (ROIs) were investigated, based on (a) BOLD signal and (b) BOLD responses within grey matter only. M values from the latter ROI were in closer agreement with theoretical predictions; however, reassuringly, ROI choice had less impact on CMRO2 than on M estimates. Relative changes in CMRO2 during motor tasks at 3 and 7T were in good agreement but were over-estimated at 1.5T as a result of the lower signal to noise ratio. This result is encouraging for future studies at 7T, but also highlights the impact of imaging and analysis choices (such as ASL sequence and ROI definition) on the calibration parameter M and on the calculation of CMRO2.

Reduced cerebrovascular reactivity in young adults carrying the APOE ε4 allele.

BACKGROUND: Functional magnetic resonance imaging (MRI) studies have shown that APOE ε2- and ε4-carriers have similar patterns of blood-oxygenation-level-dependent (BOLD) activation suggesting that we need to look beyond the BOLD signal to link APOE's effect on the brain to Alzheimer's disease (AD)-risk. METHODS: We evaluated APOE-related differences in BOLD activation in response to a memory task, cerebrovascular reactivity using a CO2-inhalation challenge (CO2-CVR), and the potential contribution of CO2-CVR to the BOLD signal. RESULTS: APOE ε4-carriers had the highest task-related hippocampal BOLD signal relative to non-carriers. The largest differences in CO2-CVR were between ε2- and ε4-carriers, with the latter having the lowest values. Genotype differences in CO2-CVR accounted for ∼70% of hippocampal BOLD differences between groups. CONCLUSION: Because CO2-CVR gauges vascular health, the differential effect of APOE in young adults may reflect a vascular contribution to the vulnerability of ε4-carriers to late-life pathology. Studies confirming our findings are warranted.

MRI measurement of oxygen extraction fraction, mean vessel size and cerebral blood volume using serial hyperoxia and hypercapnia.

Functional magnetic resonance imaging measures signal increases arising from a variety of interrelated effects and physiological sources. Recently there has been some success in disentangling this signal in order to quantify baseline physiological parameters, including the resting oxygen extraction fraction (OEF), cerebral blood volume (CBV) and mean vessel size. However, due to the complicated nature of the signal, each of these methods relies on certain physiological assumptions to derive a solution. In this work we present a framework for the simultaneous, voxelwise measurement of these three parameters. The proposed method removes the assumption of a fixed vessel size from the quantification of OEF and CBV, while simultaneously removing the need for an assumed OEF in the calculation of vessel size. The new framework is explored through simulations and validated with a pilot study in healthy volunteers. The MRI protocol uses a combined hyperoxia and hypercapnia paradigm with a modified spin labelling sequence collecting multi-slice gradient echo and spin echo data.

The influence of noise on BOLD-mediated vessel size imaging analysis methods.

Vessel size imaging (VSI) is a magnetic resonance imaging (MRI) technique that aims to provide quantitative measurements of tissue microvasculature. An emerging variation of this technique uses the blood oxygenation level-dependent (BOLD) effect as the source of the imaging contrast. Gas challenges have the advantage over contrast injection techniques in that they are noninvasive and easily repeatable because of the fast washout of the contrast. However, initial results from BOLD-VSI studies are somewhat contradictory, with substantially different estimates of the mean vessel radius. Owing to BOLD-VSI being an emerging technique, there is not yet a standard processing methodology, and different techniques have been used to calculate the mean vessel radius and reject uncertain estimates. In addition, the acquisition methodology and signal modeling vary from group to group. Owing to these differences, it is difficult to determine the source of this variation. Here we use computer modeling to assess the impact of noise on the accuracy and precision of different BOLD-VSI calculations. Our results show both potential overestimates and underestimates of the mean vessel radius, which is confirmed with a validation study at 3T.

Comparison of CO2 in air versus carbogen for the measurement of cerebrovascular reactivity with magnetic resonance imaging.

Measurement of cerebrovascular reactivity (CVR) can give valuable information about existing pathology and the risk of adverse events, such as stroke. A common method of obtaining regional CVR values is by measuring the blood flow response to carbon dioxide (CO2)-enriched air using arterial spin labeling (ASL) or blood oxygen level-dependent (BOLD) imaging. Recently, several studies have used carbogen gas (containing only CO2 and oxygen) as an alternative stimulus. A direct comparison was performed between CVR values acquired by ASL and BOLD imaging using stimuli of (1) 5% CO2 in air and (2) 5% CO2 in oxygen (carbogen-5). Although BOLD and ASL CVR values are shown to be correlated for CO2 in air (mean response 0.11±0.03% BOLD, 4.46±1.80% ASL, n=16 hemispheres), this correlation disappears during a carbogen stimulus (0.36±0.06% BOLD, 4.97±1.30% ASL). It is concluded that BOLD imaging should generally not be used in conjunction with a carbogen stimulus when measuring CVR, and that care must be taken when interpreting CVR as measured by ASL, as values obtained from different stimuli (CO2 in air versus carbogen) are not directly comparable.

An analysis of the use of hyperoxia for measuring venous cerebral blood volume: comparison of the existing method with a new analysis approach.

Hyperoxia is known to cause an increase in the blood oxygenation level dependent (BOLD) signal that is primarily localised to the venous vasculature. This contrast mechanism has been proposed as a way to measure venous cerebral blood volume (CBVv) without the need for more invasive contrast media. In the existing method the analysis modelled the data as a dynamic contrast agent experiment, with the assumption that the BOLD signal of tissue was dominated by intravascular signal. The effects on the accuracy of the method due to extravascular BOLD signal changes, as well as signal modulation by intersubject differences in baseline physiology, such as haematocrit and oxygen extraction fraction, have so far been unexplored. In this study the effect of extravascular signal and intersubject physiological variability was investigated by simulating the hyperoxia CBVv experiment using a detailed BOLD signal model. This analysis revealed substantial uncertainty in the measurement of CBVv using the existing analysis based on dynamic contrast agent experiments. Instead, the modelling showed a simple and direct relationship between the BOLD signal change and CBVv, and an alternative analysis method with much reduced uncertainty was proposed based on this finding. Both methods were tested experimentally, with the new method producing results that are consistent with the limited literature in this area.

The effect of basal vasodilation on hypercapnic and hypocapnic reactivity measured using magnetic resonance imaging.

Cerebrovascular reactivity to vasodilatory hypercapnic and vasoconstrictive hypocapnic challenges is known to be altered in several hemodynamic disorders, which is often attributable to changes in smooth muscle-mediated vascular compliance. Recently, attenuated reactivity to hypercapnia but enhanced reactivity to hypocapnia was observed in patients with chronic stroke. We hypothesize that the latter observation could be explained by a change in the basal vascular tone. In particular, reduced cerebral perfusion pressure, as is prevalent in these patients, may cause vasodilation through autoregulatory mechanisms, and this compensatory baseline condition may alter reactivity to vasoconstrictive hypocapnic challenges. To test this hypothesis, a predilated vascular condition was created in young, healthy subjects (n=11; age=23 to 36 years) using inhalation of 4% CO(2). Using blood oxygenation level-dependent functional magnetic resonance imaging at 3 T, breath holding and cued deep breathing respiratory challenges were administered to assess hypercapnia and hypocapnia reactivity, respectively. During the predilated condition, vasoconstrictive reactivity to hypocapnia was significantly (21.1%, P=0.016) enhanced throughout the gray matter, whereas there was no significant change (6.4%, P=0.459) in hypercapnic vasodilatory reactivity. This suggests that baseline vasodilation may explain the enhanced hypocapnia reactivity observed in some stroke patients, and that hypocapnia challenges may help identify the level of vascular compliance in patients with reduced cerebral perfusion pressure.