Cerebrovascular Reactivity Mapping Research Articles

CVRmap—a complete cerebrovascular reactivity mapping post-processing BIDS toolbox

Cerebrovascular Reactivity (CVR) refers to the ability of cerebral blood vessels to dilate or constrict under the effect of vasoactive substances and can be estimated using functional Magnetic Resonance Imaging (fMRI). Computation of CVR maps is relevant in various brain diseases and requires specialized data processing. We introduce CVRmap, an opensource software that automates the computation of CVR map. The toolbox complies with the Brain Imaging Data Structure (BIDS) standards.

Lower cerebrovascular reactivity in prefrontal cortex and weaker negative functional connectivity between prefrontal cortex and insula contribute to white matter hyperintensity-related anxiety or depression

BackgroundWhite matter hyperintensities (WMHs) are associated with higher anxiety or depression (A/D) incidence. We investigated associations of WMHs with A/D, cerebrovascular reactivity (CVR), and functional connectivity (FC) to identify potential pathomechanisms. MethodsParticipants with WMH (n = 239) and normal controls (NCs, n = 327) were assessed for A/D using the Hamilton Anxiety Rating Scale (HAMA) and Hamilton Depression Rating Scale (HAMD). The CVR and FC maps were constructed from resting-state functional MRI. Two-way analysis of covariance with fixed factors A/D and WMH was performed to identify regional CVR abnormalities. Seed-based FC analyses were then conducted on regions with WMH × A/D interaction effects on CVR. Logistic regression models were constructed to examine the utility of these measurements for identifying WMH-related A/D. ResultsParticipants with WMH related A/D exhibited significantly greater CVR in left insula and lower CVR in right superior frontal gyrus (SFG.R), and HAMA scores were negatively correlated with CVR in SFG.R (r = −0.156, P = 0.016). Insula–SFG.R negative FC was significantly weaker in WMH patients with suspected or definite A/D. A model including CVR plus FC changes identified WMH-associated A/D with highest sensitivity and specificity. In contrast, NCs with A/D exhibited greater CVR in prefrontal cortex and stronger FC within the default mode network (DMN) and between the DMN and executive control network. LimitationsThis cross-sectional study requires validation by longitudinal and laboratory studies. ConclusionsImpaired CVR in SFG.R and weaker negative FC between prefrontal cortex and insula may contribute to WMH-related A/D, providing potential diagnostic imaging markers and therapeutic targets.

Abstract WP127: Diagnostic Value of the Ivy Sign Compared to MR With Cerebrovascular Reactivity in Decompensated Moyamoya Arteriopathy

Introduction: MR cerebrovascular reactivity (CVR) mapping during rapid manipulation of end-tidal pCO2 is used to assess hemodynamic compromise in patients with Moyamoya arteriopathy (MMA). Leptomeningeal ivy sign on MRI FLAIR sequence may indicate regions of decreased perfusion, which would be an inexpensive and easy way to screen for hemodynamic compromise. The purpose of this study was to examine the diagnostic value of the ivy sign compared to MR CVR. Methods: For this retrospective cross-sectional study, we included consecutive patients with uncompensated MMA who were eligible for extracranial-intracranial bypass surgery and completed a preoperative MRI FLAIR with CVR study. Patients with incomplete or artefact degraded imaging were excluded. Two neuroradiologists who were blinded for the CVR result independently assessed the degree of ivy sign on axial 2D FLAIR imaging as grade 0, 1 or 2 in 8 predefined brain regions. Two different readers, blinded for ivy sign, independently assessed the presence or absence of steal in the same regions on MR CVR. Consensus was reached for discordant findings. We assessed interrater agreement using weighted kappa followed by diagnostic accuracy measures for the ivy sign using MR CVR as a reference. Results: We enrolled 73 patients (41/73 (56.1%) female; mean age 43). 47/73 (64%) patients had bilateral MMA with on average 3 brain regions with abnormal CVR. Interrater agreement was good for ivy sign (weighted kappa 0.63 (95%CI 0.54-0.71)) and excellent for CVR (kappa 0.95 (95% CI 0.87-1.00)). For a total of 156/584 (26.7%) brain regions, there was agreement between a positive ivy sign and the presence of steal on CVR and 240/584 (41%) brain regions had no ivy sign and normal CVR. The sensitivity of the ivy sign was 64.5%, specificity 70.2%, positive predictive value 60.5% and negative predictive value 73.6% with an AUC of 0.68 (95% CI 0.64-0.72) Conclusions: In this preselected cohort with high pretest probability for hemodynamic compromise, the diagnostic accuracy of the ivy sign compared to MR CVR was limited and needs to be used with caution to determine haemodynamic status in MMA.

Assessment of Cerebrovascular Reactivity Using CO2-BOLD MRI: A 15-Year, Single Center Experience.

Cerebrovascular reactivity (CVR) is a measure of the change in cerebral blood flow (CBF) in response to a vasoactive challenge. It is a useful indicator of the brain's vascular health. To evaluate the factors that influence successful and unsuccessful CVR examinations using precise arterial and end-tidal partial pressure of CO2 control during blood oxygen level-dependent (BOLD) MRI. Retrospective. Patients that underwent a CVR between October 2005 and May 2021 were studied (total of 1162 CVR examinations). The mean (±SD) age was 46.1 (±18.8) years, and 352 patients (43%) were female. 3 T; T1-weighted images, T2*-weighed two-dimensional gradient-echo sequence with standard echo-planar readout. Measurements were obtained following precise hypercapnic stimuli using BOLD MRI as a surrogate of CBF. Successful CVR examinations were defined as those where: 1) patients were able to complete CVR testing, and 2) a clinically useful CVR map was generated. Unsuccessful examinations were defined as those where patients were not able to complete the CVR examination or the CVR maps were judged to be unreliable due to, for example, excessive head motion, and poor PETCO2 targeting. Successful and unsuccessful CVR examinations between hypercapnic stimuli, and between different patterns of stimulus were compared with Chi-Square tests. Interobserver variability was determined by using the intraclass correlation coefficient (P < 0.05 is significant). In total 1115CVR tests in 662 patients were included in the final analysis. The success rate of generating CVR maps was 90.8% (1012 of 1115). Among the different hypercapnic stimuli, those containing a step plus a ramp protocol was the most successful (95.18%). Among the unsuccessful examinations (9.23%), most were patient related (89.3%), the most common of which was difficulty breathing. CO2-BOLD MRI CVR studies are well tolerated with a high success rate. 4 TECHNICAL EFFICACY: Stage 3.

Progressive Cerebrovascular Reactivity Reduction Occurs in Parkinson's Disease: A Longitudinal Study.

The change of microvascular function over the course of Parkinson's disease (PD) remains unclear. We aimed to ascertain regional cerebrovascular reactivity (CVR) changes in the patients with PD at baseline (V0) and during a 2-year follow-up period (V1). We further investigated whether alterations in CVR were linked to cognitive decline and brain functional connectivity (FC). We recruited 90 PD patients and 51 matched healthy controls (HCs). PD patients underwent clinical evaluations, neuropsychological assessments, and magnetic resonance (MR) scanning at V0 and V1, whereas HCs completed neuropsychological assessments and MR at baseline. The analysis included evaluating CVR and FC maps derived from resting-state functional magnetic resonance imaging and investigating CVR measurement reproducibility. Compared with HCs, CVR reduction in left inferior occipital gyrus and right superior temporal cortex at V0 persisted at V1, with larger clusters. Longitudinal reduction in CVR of the left posterior cingulate cortex correlated with decline in Trail Making Test B performance within PD patients. Reproducibility validation further confirmed these findings. In addition, the results also showed that there was a tendency for FC to be weakened from posterior to anterior with the progression of the disease. Microvascular dysfunction might be involved in disease progression, subsequently weaken brain FC, and partly contribute to executive function deficits in early PD. © 2023 International Parkinson and Movement Disorder Society.

Improved cerebrovascular reactivity mapping using coherence weighted general linear model in the frequency domain

Cerebrovascular reactivity (CVR) is a prognostic indicator of cerebrovascular health. Estimating CVR from endogenous end-tidal carbon dioxide (CO2) fluctuation and MRI signal recorded under resting state can be difficult due to the poor signal-to-noise ratio (SNR) of signals. Thus, we aimed to improve the method of estimating CVR from end-tidal CO2 and MRI signals. We proposed a coherence weighted general linear model (CW-GLM) to estimate CVR from the Fourier coefficients weighted by the signal coherence in frequency domain, which confers two advantages. First, it requires no signal alignment in time domain, which simplifies experimental methods. Second, it limits the GLM analysis within the frequency band where CO2 and MRI signals are highly correlated, which automatically suppresses noise and nuisance signals. We compared the performance of our method with time-domain GLM (TD-GLM) and frequency-domain GLM (FD-GLM) in both synthetic and in-vivo data; wherein we calculated CVR from signals recorded under both resting state and sinusoidal stimulus. In synthetic data, CW-GLM has a remarkable performance on CVR estimation from narrow band signals with a mean-absolute error of 0.7 % (gray matter) and 1.2 % (white matter), which was lower than all the other methods. Meanwhile, CW-GLM maintains a comparable performance on CVR estimation from resting signals, with a mean-absolute error of 4.1 % (gray matter) and 8 % (white matter). The superior performance was maintained across the 36 in-vivo measurements, with CW-GLM exhibiting limits of agreement of -16.7 % – 9.5 % between CVR calculated from the resting and sinusoidal CO2 paradigms which was 12 % – 209 % better than current time-domain methods. Evaluating of the cross-coherence spectrum revealed highest signal coherence within the frequency band from 0.01 Hz to 0.05 Hz, which overlaps with previously recommended frequency band (0.02 Hz to 0.04 Hz) for CVR analysis. Our data demonstrates that CW-GLM can work as a self-adaptive band-pass filter to improve CVR robustness, while also avoiding the need for signal temporal alignment.

Towards high-resolution quantitative assessment of vascular dysfunction

Neurovascular alterations are increasingly recognized as a key feature of many brain diseases. They can manifest as a reduction in resting cerebral blood flow or cerebrovascular reactivity (CVR) in the whole brain or in specific regions, depending on the underlying condition. Neurovascular impairment is observed in hypertension, Alzheimer’s disease, stroke, multiple sclerosis and cerebral small vessel disease. Magnetic resonance imaging (MRI)-derived CVR mapping is a reliable marker of vascular dysfunction and has been performed mainly at standard functional MRI (fMRI) resolutions of 2–3 mm using the blood oxygen level dependent (BOLD) contrast. However, vascular alterations may occur at a finer scale (i.e., in the capillary bed) which would be better characterized with smaller voxel sizes. Capillaries in gray matter deliver oxygen and glucose to neural tissue and are arranged in a mesh structure, with variable density across the cortical depth. Given that the human cortex is, on average, 2.5 mm thick, submillimetric voxel sizes are effective in increasing the spatial specificity of measurements of hemodynamic and metabolic changes. Novel MRI sequences offer the possibility to map physiological parameters at high resolution with relatively simple experimental setups. In particular, pairing the BOLD acquisition with a contrast sensitive to blood volume changes, while administering a mild hypercapnic challenge, allows for simultaneous mapping of CVR, cerebral metabolic rate of oxygen consumption and other relevant parameters at a high resolution and can be performed at the clinical field strength of 3 T. We propose that this approach will help provide crucial insights into vascular impairment.

Detection and Mitigation of Neurovascular Uncoupling in Brain Gliomas.

Functional magnetic resonance imaging (fMRI) with blood oxygen level-dependent (BOLD) technique is useful for preoperative mapping of brain functional networks in tumor patients, providing reliable in vivo detection of eloquent cortex to help reduce the risk of postsurgical morbidity. BOLD task-based fMRI (tb-fMRI) is the most often used noninvasive method that can reliably map cortical networks, including those associated with sensorimotor, language, and visual functions. BOLD resting-state fMRI (rs-fMRI) is emerging as a promising ancillary tool for visualization of diverse functional networks. Although fMRI is a powerful tool that can be used as an adjunct for brain tumor surgery planning, it has some constraints that should be taken into consideration for proper clinical interpretation. BOLD fMRI interpretation may be limited by neurovascular uncoupling (NVU) induced by brain tumors. Cerebrovascular reactivity (CVR) mapping obtained using breath-hold methods is an effective method for evaluating NVU potential.

Convolutional Neural Networks to Assess Steno-Occlusive Disease Using Cerebrovascular Reactivity.

Cerebrovascular Reactivity (CVR) is a provocative test used with Blood oxygenation level-dependent (BOLD) Magnetic Resonance Imaging (MRI) studies, where a vasoactive stimulus is applied and the corresponding changes in the cerebral blood flow (CBF) are measured. The most common clinical application is the assessment of cerebral perfusion insufficiency in patients with steno-occlusive disease (SOD). Globally, millions of people suffer from cerebrovascular diseases, and SOD is the most common cause of ischemic stroke. Therefore, CVR analyses can play a vital role in early diagnosis and guiding clinical treatment. This study develops a convolutional neural network (CNN)-based clinical decision support system to facilitate the screening of SOD patients by discriminating between healthy and unhealthy CVR maps. The networks were trained on a confidential CVR dataset with two classes: 68 healthy control subjects, and 163 SOD patients. This original dataset was distributed in a ratio of 80%-10%-10% for training, validation, and testing, respectively, and image augmentations were applied to the training and validation sets. Additionally, some popular pre-trained networks were imported and customized for the objective classification task to conduct transfer learning experiments. Results indicate that a customized CNN with a double-stacked convolution layer architecture produces the best results, consistent with expert clinical readings.

Dependence of resting-state-based cerebrovascular reactivity (CVR) mapping on spatial resolution.

Cerebrovascular reactivity (CVR) is typically assessed with a carbon dioxide (CO2) stimulus combined with BOLD fMRI. Recently, resting-state (RS) BOLD fMRI has been shown capable of generating CVR maps, providing a potential for broader CVR applications in neuroimaging studies. However, prior RS-CVR studies have primarily been performed at a spatial resolution of 3-4 mm voxel sizes. It remains unknown whether RS-CVR can also be obtained at high-resolution without major degradation in image quality. In this study, we investigated RS-CVR mapping based on resting-state BOLD MRI across a range of spatial resolutions in a group of healthy subjects, in an effort to examine the feasibility of RS-CVR measurement at high resolution. Comparing the results of RS-CVR with the maps obtained by the conventional CO2-inhalation method, our results suggested that good CVR map quality can be obtained at a voxel size as small as 2 mm isotropic. Our results also showed that, RS-CVR maps revealed resolution-dependent sensitivity. However, even at a high resolution of 2 mm isotropic voxel size, the voxel-wise sensitivity is still greater than that of typical task-evoked fMRI. Scan duration affected the sensitivity of RS-CVR mapping, but had no significant effect on its accuracy. These findings suggest that RS-CVR mapping can be applied at a similar resolution as state-of-the-art fMRI studies, which will broaden the use of CVR mapping in basic science and clinical applications including retrospective analysis of previously collected fMRI data.

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.

Cerebrovascular Reactivity Has Negligible Contribution to Hemodynamic Lag After Stroke: Implications for Functional Magnetic Resonance Imaging Studies.

Functional magnetic resonance imaging (fMRI) is ubiquitously used to study poststroke recovery. However, the fMRI-derived hemodynamic responses are vulnerable to vascular insult which can result in reduced magnitude and temporal delays (lag) in the hemodynamic response function (HRF). The cause of HRF lag remains controversial, and a better understanding of it is required to ensure accurate interpretation of poststroke fMRI studies. In this longitudinal study, we investigate the relationship between hemodynamic lag and cerebrovascular reactivity (CVR) following stroke. Voxel-wise lag maps were calculated relative to a mean gray matter reference signal for 27 healthy controls and 59 patients with stroke across 2 time points (≈2 weeks and ≈4 months poststroke) and 2 conditions: resting-state and breath-holding. The breath-holding condition was additionally used to calculate CVR in response to hypercapnia. HRF lag was computed for both conditions across tissue compartments: lesion, perilesional tissue, unaffected tissue of the lesioned hemisphere, and their homolog regions in the unaffected hemisphere. CVR and lag maps were correlated. Group, condition, and time effects were assessed using ANOVA analyses. Compared with the average gray matter signal, a relative hemodynamic lead was observed in the primary sensorimotor cortices in resting-state and bilateral inferior parietal cortices in the breath-holding condition. Whole-brain hemodynamic lag was significantly correlated across conditions irrespective of group, with regional differences across conditions suggestive of a neural network pattern. Patients showed relative lag in the lesioned hemisphere which significantly reduced over time. Breath-hold derived lag and CVR had no significant voxel-wise correlation in controls, or patients within the lesioned hemisphere or the homologous regions of the lesion and perilesional tissue in the right hemisphere (mean r<0.1). The contribution of altered CVR to HRF lag was negligible. We suggest that HRF lag is largely independent of CVR, and could partly reflect intrinsic neural network dynamics among other factors.

Comparing end-tidal CO2, respiration volume per time (RVT), and average gray matter signal for mapping cerebrovascular reactivity amplitude and delay with breath-hold task BOLD fMRI

Cerebrovascular reactivity (CVR), defined as the cerebral blood flow response to a vasoactive stimulus, is an imaging biomarker with demonstrated utility in a range of diseases and in typical development and aging processes. A robust and widely implemented method to map CVR involves using a breath-hold task during a BOLD fMRI scan. Recording end-tidal CO2 (PETCO2) changes during the breath-hold task is recommended to be used as a reference signal for modeling CVR amplitude in standard units (%BOLD/mmHg) and CVR delay in seconds. However, obtaining reliable PETCO2 recordings requires equipment and task compliance that may not be achievable in all settings. To address this challenge, we investigated two alternative reference signals to map CVR amplitude and delay in a lagged general linear model (lagged-GLM) framework: respiration volume per time (RVT) and average gray matter BOLD response (GM-BOLD). In 8 healthy adults with multiple scan sessions, we compare spatial agreement of CVR maps from RVT and GM-BOLD to those generated with PETCO2. We define a threshold to determine whether a PETCO2 recording has “sufficient” quality for CVR mapping and perform these comparisons in 16 datasets with sufficient PETCO2 and 6 datasets with insufficient PETCO2. When PETCO2 quality is sufficient, both RVT and GM-BOLD produce CVR amplitude maps that are nearly identical to those from PETCO2 (after accounting for differences in scale), with the caveat they are not in standard units to facilitate between-group comparisons. CVR delays are comparable to PETCO2 with an RVT regressor but may be underestimated with the average GM-BOLD regressor. Importantly, when PETCO2 quality is insufficient, RVT and GM-BOLD CVR recover reasonable CVR amplitude and delay maps, provided the participant attempted the breath-hold task. Therefore, our framework offers a solution for achieving high quality CVR maps in both retrospective and prospective studies where sufficient PETCO2 recordings are not available and especially in populations where obtaining reliable measurements is a known challenge (e.g., children). Our results have the potential to improve the accessibility of CVR mapping and to increase the prevalence of this promising metric of vascular health.

Effects of candesartan on cerebral microvascular function in mild cognitive impairment: Results of two clinical trials.

Cerebral microvascular dysfunction is commonly seen in Alzheimer's disease (AD) and vascular cognitive impairment (VCI). Cerebrovascular reactivity (CVR) to CO2 reflects cerebral microvascular health and may be modulated by the renin-angiotensin system (RAS). This study aimed to investigate the effects of RAS modulation on CVR in individuals with mild cognitive impairment (MCI) due to underlying vascular or AD etiologies. This study presents findings of candesartan's effects on the secondary outcomes of two double-blind randomized clinical trials of 12-month therapy of candesartan versus lisinopril in VCI (CALIBREX (Candesartan vs Lisinopril Effects on the Brain and Endothelial Function in Executive MCI)) and candesartan versus placebo in prodromal AD (Candesartan's Effects on Alzheimer's Disease and Related Biomarkers (CEDAR)). Primary outcome results of these trials have been reported in previous publications. Participants underwent identical brain blood oxygenation level dependent (BOLD)-CVR in response to a 2-min CO2 challenge at baseline and 12 months. Regions of interest and voxel-wise CVR maps were derived from BOLD signal changes during CO2 challenge. CVR effects were compared between candesartan and lisinopril (CALIBREX) and candesartan and placebo (CEDAR) using mixed-model repeated measures. Data from 102 participants in the CALIBREX study (mean age = 65 years, 45% female, 63% African American) and 59 in the CEDAR study (mean age = 67 years, 32% female, 20% African American) were analyzed. Candesartan was associated with improved whole brain CVR compared to placebo in the CEDAR study (adjusted within-group mean difference for candesartan = 0.27 (95% confidence interval (CI) = 0.006, 0.53) vs placebo = -0.17 (95% CI = 0.42, 0.08), p-value = 0.018), and compared to lisinopril in the CALIBREX study (adjusted within-group mean difference for candesartan = 0.28 (95% CI = 0.10, 0.46) vs lisinopril = -0.08 (95% CI = -0.31, 0.14), p-value = 0.012), independent of blood pressure. In an exploratory meta-analysis of the two trials, improved CVR in the hippocampus was linked to improved attention and working memory (p = 0.044) and a trend for improved executive function (p = 0.087) with candesartan therapy. This study suggests that candesartan is associated with improved microvascular function in MCI, and these findings are independent of its blood pressure effect in these VCI and prodromal AD populations.

Effects of Alzheimer’s Disease Risk Factors on Cerebrovascular Dynamics in Gray Matter

AbstractBackgroundCerebrovascular functional parameters such as cerebral blood flow (CBF), cerebrovascular reactivity (CVR), and arterial transit time (ATT) may play an essential role in understanding the vascular contributions to dementia (VCID). We investigated the relationships between cerebrovascular functional parameters and AD risk factors, including APOE genotype, hypertension, and diabetes.MethodSixty‐five subjects (Table 1) enrolled in the Wake Forest Alzheimer’s Disease Research Center (ADRC) Clinical Core cohort underwent MRI, including pseudo‐continuous ASL (PCASL). CVR maps were obtained under a hypercapnic challenge using a computer‐controlled gas blender. A multi‐TI PCASL sequence was also employed to obtain resting CBF and ATT. Separate linear regression models were tested with response variables of quantitative CBF, CVR and ATT in whole brain gray matter (GM) and AD‐prone GM regions including hippocampus, parahippocampal, entorhinal, inferior parietal lobule, precuneus, and cuneus, adjusted for covariates: age, sex, and years of education. To investigate the effects of a risk factor on the interrelated vascular dynamic parameters, a cerebrovascular composite was created with the implementation of the weighting factors, obtained from covariates adjusted logistic regression, for each AD risk group and mild cognitive impairment (MCI). The factor score p‐values were calculated from two‐sample t‐tests with the cerebrovascular composite.ResultIn both whole brain GM and AD‐prone GM regions, subjects with the risk factors generally had lower resting CBF, but differential relationship with CVR. Subjects with hypertension had significantly higher CVR, while APOE e4 carriers showed significantly lower CVR (Figure 1 and 2). From the cerebrovascular composite analysis, CVR showed higher weights in hypertension and APOE e4 carrier groups in both whole brain GM and AD‐prone GM regions (Table 2) although there still were fractions of linear weights of CBF or ATT, which were not negligible.ConclusionHypertension and APOE e4 carrier showed group differences of CVR in both whole brain GM and AD‐prone GM regions and the directions were opposite, implying their pathophysiological mechanisms may differ. As resting CBF and ATT showed lower weights in the composite than CVR, CVR may be a more sensitive brain perfusion parameter relating VCID.

Effects of Alzheimer’s Disease Risk Factors on Cerebrovascular Dynamics in Gray Matter

AbstractBackgroundCerebrovascular functional parameters such as cerebral blood flow (CBF), cerebrovascular reactivity (CVR), and arterial transit time (ATT) may play an essential role in understanding the vascular contributions to dementia (VCID). We investigated the relationships between cerebrovascular functional parameters and AD risk factors, including APOE genotype, hypertension, and diabetes.MethodSixty‐five subjects (Table 1) enrolled in the Wake Forest Alzheimer’s Disease Research Center (ADRC) Clinical Core cohort underwent MRI, including pseudo‐continuous ASL (PCASL). CVR maps were obtained under a hypercapnic challenge using a computer‐controlled gas blender. A multi‐TI PCASL sequence was also employed to obtain resting CBF and ATT. Separate linear regression models were tested with response variables of quantitative CBF, CVR and ATT in whole brain gray matter (GM) and AD‐prone GM regions including hippocampus, parahippocampal, entorhinal, inferior parietal lobule, precuneus, and cuneus, adjusted for covariates: age, sex, and years of education. To investigate the effects of a risk factor on the interrelated vascular dynamic parameters, a cerebrovascular composite was created with the implementation of the weighting factors, obtained from covariates adjusted logistic regression, for each AD risk group and mild cognitive impairment (MCI). The factor score p‐values were calculated from two‐sample t‐tests with the cerebrovascular composite.ResultIn both whole brain GM and AD‐prone GM regions, subjects with the risk factors generally had lower resting CBF, but differential relationship with CVR. Subjects with hypertension had significantly higher CVR, while APOE e4 carriers showed significantly lower CVR (Figure 1 and 2). From the cerebrovascular composite analysis, CVR showed higher weights in hypertension and APOE e4 carrier groups in both whole brain GM and AD‐prone GM regions (Table 2) although there still were fractions of linear weights of CBF or ATT, which were not negligible.ConclusionHypertension and APOE e4 carrier showed group differences of CVR in both whole brain GM and AD‐prone GM regions and the directions were opposite, implying their pathophysiological mechanisms may differ. As resting CBF and ATT showed lower weights in the composite than CVR, CVR may be a more sensitive brain perfusion parameter relating VCID.

Modeling the dynamics of cerebrovascular reactivity to carbon dioxide in fMRI under task and resting-state conditions

Conventionally, cerebrovascular reactivity (CVR) is estimated as the amplitude of the hemodynamic response to vascular stimuli, most commonly carbon dioxide (CO2). While the CVR amplitude has established clinical utility, the temporal characteristics of CVR (dCVR) have been increasingly explored and may yield even more pathology-sensitive parameters. This work is motivated by the current need to evaluate the feasibility of dCVR modeling in various experimental conditions. In this work, we present a comparison of several recently published/utilized model-based deconvolution (response estimation) approaches for estimating the CO2 response function h(t), including maximum a posteriori likelihood (MAP), inverse logit (IL), canonical correlation analysis (CCA), and basis expansion (using Gamma and Laguerre basis sets). To aid the comparison, we devised a novel simulation framework that incorporates a wide range of SNRs, ranging from 10 to -7 dB, representative of both task and resting-state CO2 changes. In addition, we built ground-truth h(t) into our simulation framework, overcoming the conventional limitation that the true h(t) is unknown. Moreover, to best represent realistic noise found in fMRI scans, we extracted noise from in-vivo resting-state scans. Furthermore, we introduce a simple optimization of the CCA method (CCAopt) and compare its performance to these existing methods. Our findings suggest that model-based methods can accurately estimate dCVR even amidst high noise (i.e. resting-state), and in a manner that is largely independent of the underlying model assumptions for each method. We also provide a quantitative basis for making methodological choices, based on the desired dCVR parameters, the estimation accuracy and computation time. The BEL method provided the highest accuracy and robustness, followed by the CCAopt and IL methods. Of the three, the CCAopt method has the lowest computational requirements. These findings lay the foundation for wider adoption of dCVR estimation in CVR mapping.

Magnetic resonance imaging for cerebrovascular reactivity assessment

Purpose. To analyze the publications related to the technique of MRI mapping of cerebrovascular reactivity.Materials and methods. We have analyzed 75 publications (4 Russian, 71 foreign), published in the period from 1960 to 2021 years. More than half of these articles were published in the last ten years, with 26 studies – in the period from 2016 to 2021 years.Results. The article systematizes methods for assessing cerebrovascular reactivity and approaches to assessing cerebrovascular reactivity by MRI. The technique of non-enhanced MRI mapping of cerebrovascular reactivity with a hypercapnic challenge is described in detail; alternative vasoactive stimuli are also considered. Issues related to data processing and evaluation of research results were discussed.Conclusion. Impairment of cerebrovascular reactivity plays an important role in the pathogenesis of cerebrovascular diseases. Over the past decades, various radionuclide and ultrasound methods have been widely used to assess cerebrovascular reactivity. In recent years the interest of researchers in MRI as a method of mapping cerebrovascular reactivity has increased significantly. Noninvasiveness, safety, absence of radiation exposure, and good tolerability are the absolute advantages of MRI mapping over other methods of assessing cerebrovascular reactivity. However, the variety of methodological approaches to MRI mapping of cerebrovascular reactivity causes significant variability in the results of the study. Standardization of the procedure should be the first step toward the introduction of MRI mapping of cerebrovascular reactivity into clinical practice.

Vascular and neuronal effects of general anesthesia on the brain: An fMRI study.

A number of functional magnetic resonance imaging (fMRI) studies rely on application of anesthetic agents during scanning that can modulate and complicate interpretation of the measured hemodynamic blood oxygenation level-dependent (BOLD) response. The purpose of the present study was to investigate the effect of general anesthesia on two main components of BOLD signal including neuronal activity and vascular response. Breath-holding (BH) fMRI was conducted in wakefulness and under anesthesia states in 9 patients with drug-resistant epilepsy who needed to get scanned under anesthesia during laser interstitial thermal therapy. BOLD and BOLD cerebrovascular reactivity (BOLD-CVR) maps were compared using t-test between two states to assess the effect of anesthesia on neuronal activity and vascular factors (p<.05). Overall, our findings revealed an increase in BOLD-CVR and decrease in BOLD response under anesthesia in several brain regions. The results proposed that the modulatory mechanism of anesthetics on neuronal and vascular components of BOLD signal may work in different ways. This experiment for the first human study showed that anesthesia may play an important role in dissociation between neuronal and vascular responses contributed to hemodynamic BOLD signal using BH fMRI imaging that may assist the implication of general anesthesia and interpretation of outcomes in clinical setting.

Severity Evaluation of Regional Cerebrovascular Reactivity in Acute Stroke Patients Using SPECT.

Cerebrovascular Reactivity (CVR), as measured using perfusion Single Photon Emission Computed Tomography (SPECT), is an important indicator for the treatment and prognosis of cerebrovascular disease, but there are a few studies on acute stroke or small vascular disease using SPECT. This study evaluated the regional severity with quantitatively determined CVR in patients with acute stroke. Fifty-eight patients who took brain SPECT images were selected to localize quantitative CVR values. The severity of the disease (Grade 1 to 4) was determined through image-based clinical assessment in the absence and presence of a CVR map, and their results were compared. In 1st diagnosis without the map, the mean CVR values of Grades 2 and 3 were -6.07 % and -9.12 %, respectively (P=0.034), while they were -4.78 % and -12.34 % in 2nd diagnosis with the map, respectively (P<0.001), suggesting that the CVR difference with the map was much more pronounced than without the map. Furthermore, in the ROC analysis, the diagnostic sensitivity between Grades 2 and 3 in the 2nd diagnosis (AUC=0.899, P<0.001) was substantially greater than the 1st diagnosis (AUC=0.646, P=0.048). This study demonstrated that the quantitative CVR maps could reinforce the clinical evaluation of cerebral severity by showing that they can provide statistically significant results between severity and CVR. Furthermore, this study was the first to evaluate the effectiveness of quantitative CVR by examining the difference in the presence or absence of CVR in patients with acute stroke.