Cerebrovascular Reactivity in Patients With Small Vessel Disease: A Cross-Sectional Study.

BACKGROUND: Cerebrovascular reactivity (CVR) is inversely related to white matter hyperintensity severity, a marker of cerebral small vessel disease (SVD). Less is known about the relationship between CVR and other SVD imaging features or cognition. We aimed to investigate these cross-sectional relationships. METHODS: Between 2018 and 2021 in Edinburgh, we recruited patients presenting with lacunar or cortical ischemic stroke, whom we characterized for SVD features. We measured CVR in subcortical gray matter, normal-appearing white matter, and white matter hyperintensity using 3T magnetic resonance imaging. We assessed cognition using Montreal Cognitive Assessment. Statistical analyses included linear regression models with CVR as outcome, adjusted for age, sex, and vascular risk factors. We reported regression coefficients with 95% CIs. RESULTS: Of 208 patients, 182 had processable CVR data sets (median age, 68.2 years; 68% men). Although the strength of association depended on tissue type, lower CVR in normal-appearing tissues and white matter hyperintensity was associated with larger white matter hyperintensity volume (BNAWM=-0.0073 [95% CI, -0.0133 to -0.0014] %/mm Hg per 10-fold increase in percentage intracranial volume), more lacunes (BNAWM=-0.00129 [95% CI, -0.00215 to -0.00043] %/mm Hg per lacune), more microbleeds (BNAWM=-0.00083 [95% CI, -0.00130 to -0.00036] %/mm Hg per microbleed), higher deep atrophy score (BNAWM=-0.00218 [95% CI, -0.00417 to -0.00020] %/mm Hg per score point increase), higher perivascular space score (BNAWM=-0.0034 [95% CI, -0.0066 to -0.0002] %/mm Hg per score point increase in basal ganglia), and higher SVD score (BNAWM=-0.0048 [95% CI, -0.0075 to -0.0021] %/mm Hg per score point increase). Lower CVR in normal-appearing tissues was related to lower Montreal Cognitive Assessment without reaching convention statistical significance (BNAWM=0.00065 [95% CI, -0.00007 to 0.00137] %/mm Hg per score point increase). CONCLUSIONS: Lower CVR in patients with SVD was related to more severe SVD burden and worse cognition in this cross-sectional analysis. Longitudinal analysis will help determine whether lower CVR predicts worsening SVD severity or vice versa. REGISTRATION: URL: https://www.isrctn.com; Unique identifier: ISRCTN12113543.

A four-dimensional computational model of dynamic contrast-enhanced magnetic resonance imaging measurement of subtle blood-brain barrier leakage.

Dynamic contrast-enhanced MRI (DCE-MRI) is increasingly used to quantify and map the spatial distribution of blood-brain barrier (BBB) leakage in neurodegenerative disease, including cerebral small vessel disease and dementia. However, the subtle nature of leakage and resulting small signal changes make quantification challenging. While simplified one-dimensional simulations have probed the impact of noise, scanner drift, and model assumptions, the impact of spatio-temporal effects such as gross motion, k-space sampling and motion artefacts on parametric leakage maps has been overlooked. Moreover, evidence on which to base the design of imaging protocols is lacking due to practical difficulties and the lack of a reference method. To address these problems, we present an open-source computational model of the DCE-MRI acquisition process for generating four dimensional Digital Reference Objects (DROs), using a high-resolution brain atlas and incorporating realistic patient motion, extra-cerebral signals, noise and k-space sampling. Simulations using the DROs demonstrated a dominant influence of spatio-temporal effects on both the visual appearance of parameter maps and on measured tissue leakage rates. The computational model permits greater understanding of the sensitivity and limitations of subtle BBB leakage measurement and provides a non-invasive means of testing and optimising imaging protocols for future studies.

Sources of systematic error in DCE-MRI estimation of low-level blood-brain barrier leakage.

PURPOSE: Dynamic contrast-enhanced (DCE) -MRI with Patlak model analysis is increasingly used to quantify low-level blood-brain barrier (BBB) leakage in studies of pathophysiology. We aimed to investigate systematic errors due to physiological, experimental, and modeling factors influencing quantification of the permeability-surface area product PS and blood plasma volume vp , and to propose modifications to reduce the errors so that subtle differences in BBB permeability can be accurately measured. METHODS: Simulations were performed to predict the effects of potential sources of systematic error on conventional PS and vp quantification: restricted BBB water exchange, reduced cerebral blood flow, arterial input function (AIF) delay and B1+ error. The impact of targeted modifications to the acquisition and processing were evaluated, including: assumption of fast versus no BBB water exchange, bolus versus slow injection of contrast agent, exclusion of early data from model fitting and B1+ correction. The optimal protocol was applied in a cohort of recent mild ischaemic stroke patients. RESULTS: Simulation results demonstrated substantial systematic errors due to the factors investigated (absolute PS error ≤ 4.48 × 10-4 min-1 ). However, these were reduced (≤0.56 × 10-4 min-1 ) by applying modifications to the acquisition and processing pipeline. Processing modifications also had substantial effects on in-vivo normal-appearing white matter PS estimation (absolute change ≤ 0.45 × 10-4 min-1 ). CONCLUSION: Measuring subtle BBB leakage with DCE-MRI presents unique challenges and is affected by several confounds that should be considered when acquiring or interpreting such data. The evaluated modifications should improve accuracy in studies of neurodegenerative diseases involving subtle BBB breakdown.

Observer Agreement on Computed Tomography Perfusion Imaging in Acute Ischemic Stroke.

Background and Purpose- Computed tomography (CT) perfusion (CTP) provides potentially valuable information to guide treatment decisions in acute stroke. Assessment of interobserver reliability of CTP has, however, been limited to small, mostly single center studies. We performed a large, internet-based study to assess observer reliability of CTP interpretation in acute stroke. Methods- We selected 24 cases from the IST-3 (Third International Stroke Trial), ATTEST (Alteplase Versus Tenecteplase for Thrombolysis After Ischaemic Stroke), and POSH (Post Stroke Hyperglycaemia) studies to illustrate various perfusion abnormalities. For each case, observers were presented with noncontrast CT, maps of cerebral blood volume, cerebral blood flow, mean transit time, delay time, and thresholded penumbra maps (dichotomized into penumbra and core), together with a short clinical vignette. Observers used a structured questionnaire to record presence of perfusion deficit, its extent compared with ischemic changes on noncontrast CT, and an Alberta Stroke Program Early CT Score for noncontrast CT and CTP. All images were viewed, and responses were collected online. We assessed observer agreement with Krippendorff-α. Intraobserver agreement was assessed by inviting observers who reviewed all scans for a repeat review of 6 scans. Results- Fifty seven observers contributed to the study, with 27 observers reviewing all 24 scans and 17 observers contributing repeat readings. Interobserver agreement was good to excellent for all CTP. Agreement was higher for perfusion maps compared with noncontrast CT and was higher for mean transit time, delay time, and penumbra map (Krippendorff-α =0.77, 0.79, and 0.81, respectively) compared with cerebral blood volume and cerebral blood flow (Krippendorff-α =0.69 and 0.62, respectively). Intraobserver agreement was fair to substantial in the majority of readers (Krippendorff-α ranged from 0.29 to 0.80). Conclusions- There are high levels of interobserver and intraobserver agreement for the interpretation of CTP in acute stroke, particularly of mean transit time, delay time, and penumbra maps.

Visual Rating Scales of White Matter Hyperintensities and Atrophy: Comparison of Computed Tomography and Magnetic Resonance Imaging.

GOAL: Magnetic resonance imaging (MRI) is the preferred modality for research on structural age-related brain changes. However, computed tomography (CT) is widely available and has practical and cost advantages over MRI for large-scale brain imaging research studies in acutely unwell patients. However, the relationships between MRI and CT measures of white matter hyperintensities (WMH) and atrophy are unclear. We examined the relationships between visual ratings of WMH, atrophy, and old infarcts in patients who had both CT and MRI scans. MATERIALS AND METHODS: Patients who had both CT and MRI scans in the International Stroke Trial-3 were studied. In both modalities, 2 raters independently completed standardized visual rating scales for WMH, and for central and superficial atrophy using a 5-point scale. In addition, 1 rater recorded old infarcts according to size and location. FINDINGS: Seventy patients with a mean age of 69 years were studied. There were moderate to substantial intrarater CT-MRI agreements for periventricular components of WMH scales (weighted Κappa = .55-.75). Agreements for basal ganglia ratings were lower (weighted Κappa = .18-.44), partly because of the misclassification of prominent perivascular spaces. Atrophy scales showed moderate to substantial CT-MRI agreements (weighted Κappa = .44-.70). MRI was more sensitive in the detection of smaller infarcts and cavitated lesions. CONCLUSIONS: Standardized visual rating scales of white matter lesions and atrophy mostly show substantial agreement between CT and MRI. Clinical CT scans have a strong potential for wider exploitation in research studies, particularly in acutely unwell populations.

Arterial Obstruction on Computed Tomographic or Magnetic Resonance Angiography and Response to Intravenous Thrombolytics in Ischemic Stroke.

BACKGROUND AND PURPOSE: Computed tomographic angiography and magnetic resonance angiography are used increasingly to assess arterial patency in patients with ischemic stroke. We determined which baseline angiography features predict response to intravenous thrombolytics in ischemic stroke using randomized controlled trial data. METHODS: We analyzed angiograms from the IST-3 (Third International Stroke Trial), an international, multicenter, prospective, randomized controlled trial of intravenous alteplase. Readers, masked to clinical, treatment, and outcome data, assessed prerandomization computed tomographic angiography and magnetic resonance angiography for presence, extent, location, and completeness of obstruction and collaterals. We compared angiography findings to 6-month functional outcome (Oxford Handicap Scale) and tested for interactions with alteplase, using ordinal regression in adjusted analyses. We also meta-analyzed all available angiography data from other randomized controlled trials of intravenous thrombolytics. RESULTS: In IST-3, 300 patients had prerandomization angiography (computed tomographic angiography=271 and magnetic resonance angiography=29). On multivariable analysis, more extensive angiographic obstruction and poor collaterals independently predicted poor outcome (P<0.01). We identified no significant interaction between angiography findings and alteplase effect on Oxford Handicap Scale (P≥0.075) in IST-3. In meta-analysis (5 trials of alteplase or desmoteplase, including IST-3, n=591), there was a significantly increased benefit of thrombolytics on outcome (odds ratio>1 indicates benefit) in patients with (odds ratio, 2.07; 95% confidence interval, 1.18-3.64; P=0.011) versus without (odds ratio, 0.88; 95% confidence interval, 0.58-1.35; P=0.566) arterial obstruction (P for interaction 0.017). CONCLUSIONS: Intravenous thrombolytics provide benefit to stroke patients with computed tomographic angiography or magnetic resonance angiography evidence of arterial obstruction, but the sample was underpowered to demonstrate significant treatment benefit or harm among patients with apparently patent arteries. CLINICAL TRIAL REGISTRATION: URL: http://www.isrctn.com. Unique identifier: ISRCTN25765518.

Metric to quantify white matter damage on brain magnetic resonance images.

PURPOSE: Quantitative assessment of white matter hyperintensities (WMH) on structural Magnetic Resonance Imaging (MRI) is challenging. It is important to harmonise results from different software tools considering not only the volume but also the signal intensity. Here we propose and evaluate a metric of white matter (WM) damage that addresses this need. METHODS: We obtained WMH and normal-appearing white matter (NAWM) volumes from brain structural MRI from community dwelling older individuals and stroke patients enrolled in three different studies, using two automatic methods followed by manual editing by two to four observers blind to each other. We calculated the average intensity values on brain structural fluid-attenuation inversion recovery (FLAIR) MRI for the NAWM and WMH. The white matter damage metric is calculated as the proportion of WMH in brain tissue weighted by the relative image contrast of the WMH-to-NAWM. The new metric was evaluated using tissue microstructure parameters and visual ratings of small vessel disease burden and WMH: Fazekas score for WMH burden and Prins scale for WMH change. RESULTS: The correlation between the WM damage metric and the visual rating scores (Spearman ρ > =0.74, p < 0.0001) was slightly stronger than between the latter and WMH volumes (Spearman ρ > =0.72, p < 0.0001). The repeatability of the WM damage metric was better than WM volume (average median difference between measurements 3.26% (IQR 2.76%) and 5.88% (IQR 5.32%) respectively). The follow-up WM damage was highly related to total Prins score even when adjusted for baseline WM damage (ANCOVA, p < 0.0001), which was not always the case for WMH volume, as total Prins was highly associated with the change in the intense WMH volume (p = 0.0079, increase of 4.42 ml per unit change in total Prins, 95%CI [1.17 7.67]), but not with the change in less-intense, subtle WMH, which determined the volumetric change. CONCLUSION: The new metric is practical and simple to calculate. It is robust to variations in image processing methods and scanning protocols, and sensitive to subtle and severe white matter damage.

Cerebral White Matter Hypoperfusion Increases with Small-Vessel Disease Burden. Data From the Third International Stroke Trial.

BACKGROUND: Leukoaraiosis is associated with impaired cerebral perfusion, but the effect of individual and combined small-vessel disease (SVD) features on white matter perfusion is unclear. METHODS: We studied patients recruited with perfusion imaging in the Third International Stroke Trial. We rated individual SVD features (leukoaraiosis, lacunes) and brain atrophy on baseline plain computed tomography or magnetic resonance imaging. Separately, we assessed white matter at the level of the lateral ventricles in the cerebral hemisphere contralateral to the stroke for visible areas of hypoperfusion (present or absent) on 4 time-based perfusion imaging parameters. We examined associations between SVD features (individually and summed) and presence of hypoperfusion using logistic regression adjusted for age, sex, baseline National Institutes of Health Stroke Scale, hypertension, and diabetes. RESULTS: A total of 115 patients with median (interquartile range) age of 81 (72-86) years, 78 (52%) of which were male, had complete perfusion data. Hypoperfusion was most frequent on mean transit time (MTT; 63 patients, 55%) and least frequent on time to maximum flow (19 patients, 17%). The SVD score showed stronger independent associations with hypoperfusion (e.g., MTT, odds ratio [OR] = 2.80; 95% confidence interval [CI] = 1.56-5.03) than individual SVD markers (e.g., white matter hypoattenuation score, MTT, OR = 1.49, 95% CI = 1.09-2.04). Baseline blood pressure did not differ by presence or absence of hypoperfusion or across strata of SVD score. Presence of white matter hypoperfusion increased with SVD summed score. CONCLUSIONS: The SVD summed score was associated with hypoperfusion more consistently than individual SVD features, providing validity to the SVD score concept. Increasing SVD burden indicates worse perfusion in the white matter.

Progression of White Matter Disease and Cortical Thinning Are Not Related in Older Community-Dwelling Subjects.

BACKGROUND AND PURPOSE: We assessed cross-sectional and longitudinal relationships between whole brain white matter hyperintensity (WMH) volume and regional cortical thickness. METHODS: We measured WMH volume and regional cortical thickness on magnetic resonance imaging at ≈73 and ≈76 years in 351 community-dwelling subjects from the Lothian Birth Cohort 1936. We used multiple linear regression to calculate cross-sectional and longitudinal associations between regional cortical thickness and WMH volume controlling for age, sex, Mini Mental State Examination, education, intelligence quotient at age 11, and vascular risk factors. RESULTS: We found cross-sectional associations between WMH volume and cortical thickness within and surrounding the Sylvian fissure at 73 and 76 years (rho=-0.276, Q=0.004). However, we found no significant longitudinal associations between (1) baseline WMH volume and change in cortical thickness; (2) baseline cortical thickness and change in WMH volume; or (3) change in WMH volume and change in cortical thickness. CONCLUSIONS: Our results show that WMH volume and cortical thinning both worsen with age and are associated cross-sectionally within and surrounding the Sylvian fissure. However, changes in WMH volume and cortical thinning from 73 to 76 years are not associated longitudinally in these relatively healthy older subjects. The underlying cause(s) of WMH growth and cortical thinning have yet to be fully determined.

Tracer kinetic modelling for DCE-MRI quantification of subtle blood-brain barrier permeability.

There is evidence that subtle breakdown of the blood-brain barrier (BBB) is a pathophysiological component of several diseases, including cerebral small vessel disease and some dementias. Dynamic contrast-enhanced MRI (DCE-MRI) combined with tracer kinetic modelling is widely used for assessing permeability and perfusion in brain tumours and body tissues where contrast agents readily accumulate in the extracellular space. However, in diseases where leakage is subtle, the optimal approach for measuring BBB integrity is likely to differ since the magnitude and rate of enhancement caused by leakage are extremely low; several methods have been reported in the literature, yielding a wide range of parameters even in healthy subjects. We hypothesised that the Patlak model is a suitable approach for measuring low-level BBB permeability with low temporal resolution and high spatial resolution and brain coverage, and that normal levels of scanner instability would influence permeability measurements. DCE-MRI was performed in a cohort of mild stroke patients (n=201) with a range of cerebral small vessel disease severity. We fitted these data to a set of nested tracer kinetic models, ranking their performance according to the Akaike information criterion. To assess the influence of scanner drift, we scanned 15 healthy volunteers that underwent a "sham" DCE-MRI procedure without administration of contrast agent. Numerical simulations were performed to investigate model validity and the effect of scanner drift. The Patlak model was found to be most appropriate for fitting low-permeability data, and the simulations showed vp and K(Trans) estimates to be reasonably robust to the model assumptions. However, signal drift (measured at approximately 0.1% per minute and comparable to literature reports in other settings) led to systematic errors in calculated tracer kinetic parameters, particularly at low permeabilities. Our findings justify the growing use of the Patlak model in low-permeability states, which has the potential to provide valuable information regarding BBB integrity in a range of diseases. However, absolute values of the resulting tracer kinetic parameters should be interpreted with extreme caution, and the size and influence of signal drift should be measured where possible.