Voxelwise optimization of hemodynamic lags to improve regional CVR estimates in breath-hold fMRI

Quantitative mapping of cerebrovascular reactivity amplitude and delay with breath-hold BOLD fMRI when end-tidal CO2 quality is low

Cerebrovascular reactivity (CVR), the ability of cerebral blood vessels to dilate or constrict in order to regulate blood flow, is a clinically useful measure of cerebrovascular health. CVR is often measured using a breath-hold task to modulate blood CO2 levels during an fMRI scan. Measuring end-tidal CO2 (PETCO2) with a nasal cannula during the task allows CVR amplitude to be calculated in standard units (vascular response per unit change in CO2, or %BOLD/mmHg) and CVR delay to be calculated in seconds. The use of standard units allows for normative CVR ranges to be established and for CVR comparisons to be made across subjects and scan sessions. Although breath-holding can be successfully performed by diverse patient populations, obtaining accurate PETCO2 measurements requires additional task compliance; specifically, participants must breathe exclusively through their nose and exhale immediately before and after each breath hold. Meeting these requirements is challenging, even in healthy participants, and this has limited the translational potential of breath-hold fMRI for CVR mapping. Previous work has focused on using alternative regressors such as respiration volume per time (RVT), derived from respiratory belt measurements, to map CVR. Because measuring RVT does not require additional task compliance from participants, it is a more feasible measure than PETCO2. However, using RVT does not produce CVR in standard units. In this work, we explored how to achieve CVR maps, in standard units, when breath-hold task PETCO2 data quality is low. First, we evaluated whether RVT could be scaled to units of mmHg using a subset of PETCO2 data of sufficiently high quality. Second, we explored whether a PETCO2 timeseries predicted from RVT using deep learning allows for more accurate CVR measurements. Using a dense-mapping breath-hold fMRI dataset, we showed that both rescaled RVT and rescaled, predicted PETCO2 can be used to produce maps of CVR amplitude and delay in standard units with strong absolute agreement to ground-truth maps. However, the rescaled, predicted PETCO2 regressor resulted in superior accuracy for both CVR amplitude and delay. In an individual with regions of increased CVR delay due to Moyamoya disease, the predicted PETCO2 regressor also provided greater sensitivity to pathology than RVT. Ultimately, this work will increase the clinical applicability of CVR in populations exhibiting decreased task compliance.

Macrovascular blood flow and microvascular cerebrovascular reactivity are regionally coupled in adolescence

Cerebrovascular imaging assessments are particularly challenging in adolescent cohorts, where not all modalities are appropriate, and rapid brain maturation alters hemodynamics at both macro- and microvascular scales. In a preliminary sample of healthy adolescents (n = 12, 8-25 years), we investigated relationships between 4D flow MRI-derived blood velocity and blood flow in bilateral anterior, middle, and posterior cerebral arteries and BOLD cerebrovascular reactivity (CVR) in associated vascular territories. As hypothesized, higher velocities in large arteries are associated with an earlier response to a vasodilatory stimulus (cerebrovascular reactivity delay) in the downstream territory. Higher blood flow through these arteries is associated with a larger BOLD response to a vasodilatory stimulus (cerebrovascular reactivity amplitude) in the associated territory. These trends are consistent in a case study of adult moyamoya disease. In our small adolescent cohort, macrovascular-microvascular relationships for velocity/delay and flow/CVR change with age, though underlying mechanisms are unclear. Our work emphasizes the need to better characterize this key stage of human brain development, when cerebrovascular hemodynamics are changing, and standard imaging methods offer limited insight into these processes. We provide important normative data for future comparisons in pathology, where combining macro- and microvascular assessments may better help us prevent, stratify, and treat cerebrovascular disease.

Macrovascular blood flow and microvascular cerebrovascular reactivity are regionally coupled in adolescence

Cerebrovascular imaging assessments are particularly challenging in adolescent cohorts, where not all modalities are appropriate, and rapid brain maturation alters hemodynamics at both macro- and microvascular scales. In a preliminary sample of healthy adolescents (n=12, 8-25 years), we investigated relationships between 4D flow MRI-derived blood velocity and blood flow in bilateral anterior, middle, and posterior cerebral arteries and BOLD cerebrovascular reactivity in associated vascular territories. As hypothesized, higher velocities in large arteries are associated with an earlier response to a vasodilatory stimulus (cerebrovascular reactivity delay) in the downstream territory. Higher blood flow through these arteries is associated with a larger BOLD response to a vasodilatory stimulus (cerebrovascular reactivity amplitude) in the associated territory. These trends are consistent in a case study of adult moyamoya disease. In our small adolescent cohort, macrovascular-microvascular relationships for velocity/delay and flow/CVR change with age, though underlying mechanisms are unclear. Our work emphasizes the need to better characterize this key stage of human brain development, when cerebrovascular hemodynamics are changing, and standard imaging methods offer limited insight into these processes. We provide important normative data for future comparisons in pathology, where combining macro- and microvascular assessments may better help us prevent, stratify, and treat cerebrovascular disease.

Delayed cerebrovascular reactivity in individuals with spinal cord injury in the right inferior parietal lobe: a breath-hold functional near-infrared spectroscopy study

Cerebrovascular reactivity (CVR) reflects the ability of blood vessels to dilate or constrict in response to a vasoactive stimulus, and allows researchers to assess the brain's vascular health. Individuals with spinal cord injury (SCI) are at an increased risk for autonomic dysfunction in addition to cognitive impairments, which have been linked to a decline in CVR; however, there is currently a lack of brain-imaging studies that investigate how CVR is altered after SCI. In this study, we used a breath-holding hypercapnic stimulus and functional near-infrared spectroscopy (fNIRS) to investigate CVR alterations in individuals with SCI (n = 20, 14M, 6F, mean age = 46.3 ± 10.2 years) as compared to age- and sex-matched able-bodied (AB) controls (n = 25, 19M, 6F, mean age = 43.2 ± 12.28 years). CVR was evaluated by its amplitude and delay components separately by using principal component analysis and cross-correlation analysis, respectively. We observed significantly delayed CVR in the right inferior parietal lobe in individuals with SCI compared to AB controls (linear mixed-effects model, fixed-effects estimate = 6.565, Satterthwaite's t-test, t = 2.663, p = 0.008), while the amplitude of CVR was not significantly different. The average CVR delay in the SCI group in the right inferior parietal lobe was 14.21 s (sd: 6.60 s), and for the AB group, the average delay in the right inferior parietal lobe was 7.08 s (sd: 7.39 s). CVR delays were also associated with the duration since injury in individuals with SCI, in which a longer duration since injury was associated with a shortened delay in CVR in the right inferior parietal region (Pearson's r-correlation, r = -0.59, p = 0.04). This study shows that fNIRS can be used to quantify changes in CVR in individuals with SCI, and may be further used in rehabilitative settings to monitor the cerebrovascular health of individuals with SCI.

Denoising task-correlated head motion from motor-task fMRI data with multi-echo ICA

Motor-task functional magnetic resonance imaging (fMRI) is crucial in the study of several clinical conditions, including stroke and Parkinson's disease. However, motor-task fMRI is complicated by task-correlated head motion, which can be magnified in clinical populations and confounds motor activation results. One method that may mitigate this issue is multi-echo independent component analysis (ME-ICA), which has been shown to separate the effects of head motion from the desired BOLD signal but has not been tested in motor-task datasets with high amounts of motion. In this study, we collected an fMRI dataset from a healthy population who performed a hand grasp task with and without task-correlated amplified head motion to simulate a motor-impaired population. We analyzed these data using three models: single-echo (SE), multi-echo optimally combined (ME-OC), and ME-ICA. We compared the models' performance in mitigating the effects of head motion on the subject level and group level. On the subject level, ME-ICA better dissociated the effects of head motion from the BOLD signal and reduced noise. Both ME models led to increased t-statistics in brain motor regions. In scans with high levels of motion, ME-ICA additionally mitigated artifacts and increased stability of beta coefficient estimates, compared to SE. On the group level, all three models produced activation clusters in expected motor areas in scans with both low and high motion, indicating that group-level averaging may also sufficiently resolve motion artifacts that vary by subject. These findings demonstrate that ME-ICA is a useful tool for subject-level analysis of motor-task data with high levels of task-correlated head motion. The improvements afforded by ME-ICA are critical to improve reliability of subject-level activation maps for clinical populations in which group-level analysis may not be feasible or appropriate, for example in a chronic stroke cohort with varying stroke location and degree of tissue damage.

Deep-learning-enabled brain hemodynamic mapping using resting-state fMRI

Cerebrovascular disease is a leading cause of death globally. Prevention and early intervention are known to be the most effective forms of its management. Non-invasive imaging methods hold great promises for early stratification, but at present lack the sensitivity for personalized prognosis. Resting-state functional magnetic resonance imaging (rs-fMRI), a powerful tool previously used for mapping neural activity, is available in most hospitals. Here we show that rs-fMRI can be used to map cerebral hemodynamic function and delineate impairment. By exploiting time variations in breathing pattern during rs-fMRI, deep learning enables reproducible mapping of cerebrovascular reactivity (CVR) and bolus arrival time (BAT) of the human brain using resting-state CO2 fluctuations as a natural "contrast media". The deep-learning network is trained with CVR and BAT maps obtained with a reference method of CO2-inhalation MRI, which includes data from young and older healthy subjects and patients with Moyamoya disease and brain tumors. We demonstrate the performance of deep-learning cerebrovascular mapping in the detection of vascular abnormalities, evaluation of revascularization effects, and vascular alterations in normal aging. In addition, cerebrovascular maps obtained with the proposed method exhibit excellent reproducibility in both healthy volunteers and stroke patients. Deep-learning resting-state vascular imaging has the potential to become a useful tool in clinical cerebrovascular imaging.

The many layers of BOLD. The effect of hypercapnic and hyperoxic stimuli on macro- and micro-vascular compartments quantified by CVR, M, and CBV across cortical depth

Ultra-high field functional magnetic resonance imaging (fMRI) offers the spatial resolution to measure neuronal activity at the scale of cortical layers. However, cortical depth dependent vascularization differences, such as a higher prevalence of macro-vascular compartments near the pial surface, have a confounding effect on depth-resolved blood-oxygen-level dependent (BOLD) fMRI signals. In the current study, we use hypercapnic and hyperoxic breathing conditions to quantify the influence of all venous vascular and micro-vascular compartments on laminar BOLD fMRI, as measured with gradient-echo (GE) and spin-echo (SE) scan sequences, respectively. We find that all venous vascular and micro-vascular compartments are capable of comparable theoretical maximum signal intensities, as represented by the M-value parameter. However, the capacity for vessel dilation, as reflected by the cerebrovascular reactivity (CVR), is approximately two and a half times larger for all venous vascular compartments combined compared to the micro-vasculature at superficial layers. Finally, there is roughly a 35% difference in estimates of CBV changes between all venous vascular and micro-vascular compartments, although this relative difference was approximately uniform across cortical depth. Thus, our results suggest that fMRI BOLD signal differences across cortical depth are likely caused by differences in dilation properties between macro- and micro-vascular compartments.

Evaluation of the cerebrovascular reactivity in patients with Moyamoya Angiopathy by use of breath-hold fMRI: investigation of voxel-wise hemodynamic delay correction in comparison to [15O]water PET

PURPOSE

Patients with Moyamoya Angiopathy (MMA) require hemodynamic assessment to evaluate the risk of stroke. Hemodynamic evaluation by use of breath-hold-triggered fMRI (bh-fMRI) was proposed as a readily available alternative to the diagnostic standard [¹⁵O]water PET. Recent studies suggest voxel-wise hemodynamic delay correction in hypercapnia-triggered fMRI. The aim of this study was to evaluate the effect of delay correction of bh-fMRI in patients with MMA and to compare the results with [¹⁵O]water PET.

METHODS

bh-fMRI data sets of 22 patients with MMA were evaluated without and with voxel-wise delay correction within different shift ranges and compared to the corresponding [¹⁵O]water PET data sets. The effects were evaluated combined and in subgroups of data sets with most severely impaired CVR (apparent steal phenomenon), data sets with territorial time delay, and data sets with neither steal phenomenon nor delay between vascular territories.

RESULTS

The study revealed a high mean cross-correlation (r = 0.79, p < 0.001) between bh-fMRI and [¹⁵O]water PET. The correlation was strongly dependent on the choice of the shift range. Overall, no shift range revealed a significantly improved correlation between bh-fMRI and [¹⁵O]water PET compared to the correlation without delay correction. Delay correction within shift ranges with positive high high cutoff revealed a lower agreement between bh-fMRI and PET overall and in all subgroups.

CONCLUSION

Voxel-wise delay correction, in particular with shift ranges with high cutoff, should be used critically as it can lead to false-negative results in regions with impaired CVR and a lower correlation to the diagnostic standard [¹⁵O]water PET.

Lag-Optimized Blood Oxygenation Level Dependent Cerebrovascular Reactivity Estimates Derived From Breathing Task Data Have a Stronger Relationship With Baseline Cerebral Blood Flow

Cerebrovascular reactivity (CVR), an important indicator of cerebrovascular health, is commonly studied with the Blood Oxygenation Level Dependent functional MRI (BOLD-fMRI) response to a vasoactive stimulus. Theoretical and empirical evidence suggests that baseline cerebral blood flow (CBF) modulates BOLD signal amplitude and may influence BOLD-CVR estimates. We address how acquisition and modeling choices affect the relationship between baseline cerebral blood flow (bCBF) and BOLD-CVR: whether BOLD-CVR is modeled with the inclusion of a breathing task, and whether BOLD-CVR amplitudes are optimized for hemodynamic lag effects. We assessed between-subject correlations of average GM values and within-subject spatial correlations across cortical regions. Our results suggest that a breathing task addition to a resting-state acquisition, alongside lag-optimization within BOLD-CVR modeling, can improve BOLD-CVR correlations with bCBF, both between- and within-subjects, likely because these CVR estimates are more physiologically accurate. We report positive correlations between bCBF and BOLD-CVR, both between- and within-subjects. The physiological explanation of this positive correlation is unclear; research with larger samples and tightly controlled vasoactive stimuli is needed. Insights into what drives variability in BOLD-CVR measurements and related measurements of cerebrovascular function are particularly relevant when interpreting results in populations with altered vascular and/or metabolic baselines or impaired cerebrovascular reserve.

ICA-based denoising strategies in breath-hold induced cerebrovascular reactivity mapping with multi echo BOLD fMRI

Performing a BOLD functional MRI (fMRI) acquisition during breath-hold (BH) tasks is a non-invasive, robust method to estimate cerebrovascular reactivity (CVR). However, movement and breathing-related artefacts caused by the BH can substantially hinder CVR estimates due to their high temporal collinearity with the effect of interest, and attention has to be paid when choosing which analysis model should be applied to the data. In this study, we evaluate the performance of multiple analysis strategies based on lagged general linear models applied on multi-echo BOLD fMRI data, acquired in ten subjects performing a BH task during ten sessions, to obtain subject-specific CVR and haemodynamic lag estimates. The evaluated approaches range from conventional regression models, i.e. including drifts and motion timecourses as nuisance regressors, applied on single-echo or optimally-combined data, to more complex models including regressors obtained from multi-echo independent component analysis with different grades of orthogonalization in order to preserve the effect of interest, i.e. the CVR. We compare these models in terms of their ability to make signal intensity changes independent from motion, as well as the reliability as measured by voxelwise intraclass correlation coefficients of both CVR and lag maps over time. Our results reveal that a conservative independent component analysis model applied on the optimally-combined multi-echo fMRI signal offers the largest reduction of motion-related effects in the signal, while yielding reliable CVR amplitude and lag estimates, although a conventional regression model applied on the optimally-combined data results in similar estimates. This work demonstrates the usefulness of multi-echo based fMRI acquisitions and independent component analysis denoising for precision mapping of CVR in single subjects based on BH paradigms, fostering its potential as a clinically-viable neuroimaging tool for individual patients. It also proves that the way in which data-driven regressors should be incorporated in the analysis model is not straight-forward due to their complex interaction with the BH-induced BOLD response.

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.