Investigating the pathophysiology of acute ischaemic stroke using magnetic resonance imaging

The original description of the ischaemic penumbra asserted that both cerebral blood flow and metabolism would be required to monitor therapeutic intervention in acute ischaemic stroke. However, imaging in stroke trials has predominantly used biomarkers of infarction or perfusion-weighted signal to identify the pathophysiological processes that occur. This approach has neither identified novel treatment targets, nor been shown to consistently select patients who might benefit from intervention. The aim of this thesis was to use magnetic resonance imaging (MRI) biomarkers to identify and describe the pathophysiology of acute ischaemic stroke in patients. Patients admitted to the John Radcliffe Hospital in Oxford were recruited into a clinical imaging study. Serial imaging data were acquired, predominantly in the first hours after symptom onset, to capture the early dynamics of brain pathophysiology. Tissue status was meticulously defined over time to ensure robust interpretation of the novel imaging biomarkers: multiple post labeling delay arterial spin labeling to measure cerebral blood flow (CBF), and amide proton transfer to generate an intracellular pH-weighted signal. At a group level, the regions with the most severe injury had the lowest mean CBF and the greatest acidosis at presentation. There was a gradient of mean CBF and pH-weighted signal from the most ischaemic tissue to healthy tissue, but at the level of the individual there was considerable overlap in both parameters. The dynamics of perfusion were not sufficient to explain tissue outcome. Both acidosis and alkalosis were observed up to 24 hours in tissue that infarcted, and the nature of the pH change correlated with the timing of infarction. These data show that single imaging biomarkers cannot explain the pathophysiology of stroke and tissue fate. There is heterogeneity of pathophysiology both within and between patients, and the dynamics of these processes vary. Insight from pH-weighted imaging highlights the limitations of using perfusion imaging alone to assess tissue status, and supports the use of complementary metabolic imaging in the investigation of ischaemic stroke

Prospects for investigating brain oxygenation in acute stroke: Experience with a non‐contrast quantitative BOLD based approach

Metabolic markers of baseline brain oxygenation and tissue perfusion have an important role to play in the early identification of ischaemic tissue in acute stroke. Although well established MRI techniques exist for mapping brain perfusion, quantitative imaging of brain oxygenation is poorly served. Streamlined-qBOLD (sqBOLD) is a recently developed technique for mapping oxygenation that is well suited to the challenge of investigating acute stroke. In this study a noninvasive serial imaging protocol was implemented, incorporating sqBOLD and arterial spin labelling to map blood oxygenation and perfusion, respectively. The utility of these parameters was investigated using imaging based definitions of tissue outcome (ischaemic core, infarct growth and contralateral tissue). Voxel wise analysis revealed significant differences between all tissue outcomes using pairwise comparisons for the transverse reversible relaxation rate (R 2 '), deoxygenated blood volume (DBV) and deoxyghaemoglobin concentration ([dHb]; p < 0.01 in all cases). At the patient level (n = 9), a significant difference was observed for [dHb] between ischaemic core and contralateral tissue. Furthermore, serial analysis at the patient level (n = 6) revealed significant changes in R 2 ' between the presentation and 1 week scans for both ischaemic core (p < 0.01) and infarct growth (p < 0.05). In conclusion, this study presents evidence supporting the potential of sqBOLD for imaging oxygenation in stroke

Optimizing image registration and infarct definition in stroke research

Objective: Accurate representation of final infarct volume is essential for assessing the efficacy of stroke interventions in imaging-based studies. This study defines the impact of image registration methods used at different timepoints following stroke, and the implications for infarct definition in stroke research. Methods: Patients presenting with acute ischemic stroke were imaged serially using magnetic resonance imaging. Infarct volume was defined manually using four metrics: 24-h b1000 imaging; 1-week and 1-month T2-weighted FLAIR; and automatically using predefined thresholds of ADC at 24 h. Infarct overlap statistics and volumes were compared across timepoints following both rigid body and nonlinear image registration to the presenting MRI. The effect of nonlinear registration on a hypothetical trial sample size was calculated. Results: Thirty-seven patients were included. Nonlinear registration improved infarct overlap statistics and consistency of total infarct volumes across timepoints, and reduced infarct volumes by 4.0 mL (13.1%) and 7.1 mL (18.2%) at 24 h and 1 week, respectively, compared to rigid body registration. Infarct volume at 24 h, defined using a predetermined ADC threshold, was less sensitive to infarction than b1000 imaging. 1-week T2-weighted FLAIR imaging was the most accurate representation of final infarct volume. Nonlinear registration reduced hypothetical trial sample size, independent of infarct volume, by an average of 13%. Interpretation: Nonlinear image registration may offer the opportunity of improving the accuracy of infarct definition in serial imaging studies compared to rigid body registration, helping to overcome the challenges of anatomical distortions at subacute timepoints, and reducing sample size for imaging-based clinical trials

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Stratifying Ischaemic Stroke Patients Across 3 Treatment Windows Using T2 Relaxation Times, Ordinal Regression and Cumulative Probabilities

Unknown onset time is a common contraindication for anti-thrombolytic treatment of ischaemic stroke. T2 relaxation-based signal changes within the lesion can identify patients within or beyond the 4.5-hour intravenous thrombolysis treatment-window. However, now that intra-arterial thrombolysis is recommended between 4.5 and 6 hours from symptom onset and mechanical thrombectomy is considered safe between 6 and 24 hours, there are three treatment-windows to consider. Here we show a cumulative ordinal regression model, incorporating the T2 relaxation time, predicts the probabilities of a patient being within one of the three treatment-windows and is more accurate than signal intensity changes from T2 weighted images

Artificial intelligence-based decision support software to improve the efficacy of acute stroke pathway in the NHS: an observational study

IntroductionIn a drip-and-ship model for endovascular thrombectomy (EVT), early identification of large vessel occlusion (LVO) and timely referral to a comprehensive center (CSC) are crucial when patients are admitted to an acute stroke center (ASC). Several artificial intelligence (AI) decision-aid tools are increasingly being used to facilitate the rapid identification of LVO. This retrospective cohort study aimed to evaluate the impact of deploying e-Stroke AI decision support software in the hyperacute stroke pathway on process metrics and patient outcomes at an ASC in the United Kingdom.MethodsExcept for the deployment of e-Stroke on 01 March 2020, there were no significant changes made to the stroke pathway at the ASC. The data were obtained from a prospective stroke registry between 01 January 2019 and 31 March 2021. The outcomes were compared between the 14 months before and 12 months after the deployment of AI (pre-e-Stroke cohort vs. post-e-Stroke cohort) on 01 March 2020. Time window analyses were performed using Welch’s t-test. Cochran–Mantel–Haenszel test was used to compare changes in disability at 3 months assessed by modified Rankin Score (mRS) ordinal shift analysis, and Fisher’s exact test was used for dichotomised mRS analysis.ResultsIn the pre-e-Stroke cohort, 19 of 22 patients referred received EVT. In the post-e-Stroke cohort, 21 of the 25 patients referred were treated. The mean door-in-door-out (DIDO) and door-to-referral times in pre-e-Stroke vs. post-e-Stroke cohorts were 141 vs. 79 min (difference 62 min, 95% CI 96.9–26.8 min, p &lt; 0.001) and 71 vs. 44 min (difference 27 min, 95% CI 47.4–5.4 min, p = 0.01), respectively. The adjusted odds ratio (age and NIHSS) for mRS ordinal shift analysis at 3 months was 3.14 (95% CI 0.99–10.51, p = 0.06) and the dichotomized mRS 0–2 at 3 months was 16% vs. 48% (p = 0.04) in the pre- vs. post-e-Stroke cohorts, respectively.ConclusionIn this single-center study in the United Kingdom, the DIDO time significantly decreased since the introduction of e-Stroke decision support software into an ASC hyperacute stroke pathway. The reduction in door-in to referral time indicates faster image interpretation and referral for EVT. There was an indication of an increased proportion of patients regaining independent function after EVT. However, this should be interpreted with caution given the small sample size. Larger, prospective studies and further systematic real-world evaluation are needed to demonstrate the widespread generalisability of these findings

Amide proton transfer imaging in stroke

Amide proton transfer (APT) imaging, a variant of chemical exchange saturation transfer MRI, has shown promise in detecting ischemic tissue acidosis following impaired aerobic metabolism in animal models and in human stroke patients due to the sensitivity of the amide proton exchange rate to changes in pH within the physiological range. Recent studies have demonstrated the possibility of using APT-MRI to detect acidosis of the ischemic penumbra, enabling the assessment of stroke severity and risk of progression, monitoring of treatment progress, and prognostication of clinical outcome. This paper reviews current APT imaging methods actively used in ischemic stroke research and explores the clinical aspects of ischemic stroke and future applications for these methods

Artificial intelligence assisted detection of large vessel occlusion on CT angiography in acute stroke patients: a multi-reader multi-case study

Objectives: We assessed the impact of artificial intelligence (AI) software (e-CTA, Brainomix) on clinical decision-making in patients with suspected acute ischemic stroke. Methods: A retrospective, multi-reader-multi-case crossover design compared readers’ performance with vs without software support. Twenty cases were included, 10 with large vessel occlusion (LVO) and 10 without LVO. Twenty-one NHS clinicians, representing intended software users ranging in experience, conducted 2 sessions (washout period > 2 weeks). In session 1, software support was provided for 10 randomly selected cases. In session 2, support allocation was reversed. Outcome measures included LVO detection, collateral scoring, diagnosis, treatment decision, time taken and confidence. Results: Sensitivity, specificity, and accuracy of LVO detection improved with imaging software for LVO detection, with increased confidence and reduced time taken. There was no significant difference in collateral scoring or diagnoses. Conclusion: e-CTA can improve performance of NHS clinicians when interpreting acute stroke imaging. Advances in knowledge: This paper provides new evidence that AI decision support software has the capacity to improve the performance of representative users in the NHS when interpreting imaging to identify patients for acute stroke treatments

Automatically quantified follow-up imaging biomarkers predict clinical outcomes after acute ischemic stroke

Background: Follow-up infarct volume (FIV) is a proposed surrogate endpoint for proof-of-concept clinical studies in acute ischemic stroke (AIS). This study aimed to provide clinical validation of an automated FIV algorithm, demonstrating the association of imaging biomarkers with clinical outcomes to support the use of these imaging endpoints in clinical trials. Methods: Data were gathered for adult AIS patients undergoing mechanical thrombectomy with follow-up imaging 12–96 h from initial assessment. Non-contrast computed tomography was used to quantify infarct volume. Image processing used the AI-powered software Brainomix 360 Stroke (Brainomix Ltd., Oxford, United Kingdom) and Brainomix core lab research software. Measures included total FIV and components–ischemic injury corrected FIV (cFIV), hemorrhagic transformation (HT), anatomical distortion (AD; a marker of edema) and infarct growth (IG). The primary clinical endpoint was modified Rankin Scale (mRS) at 90 days; secondary clinical endpoint was NIH Stroke Scale (NIHSS) score at 24 h. Results: Of 986 patients, 843 (85.5%; median age 72 years, 56.7% male) had complete data and were included in the study analysis. Median baseline NIHSS score was 17 (IQR: 12–21). Median imaging follow-up time was 24 h (IQR 20–28). Median 24 h NIHSS score was 11 (5–17); 34% of patients had mRS 0–2 at 90 days. Median FIV was 30.2 mL (12.5–120.8 mL). FIV was significantly associated with 90-day mRS (concordance = 0.819, p < 0.001) and NIHSS at 24 h (concordance = 0.722, p < 0.001). cFIV, HT, AD, and IG were also significantly associated with good clinical outcomes in both 90-day mRS (concordance = 0.702, p < 0.001; 0.660, p < 0.001; 0.591, p = 0.002; and 0.663, p < 0.001, respectively) and NIHSS at 24 h (0.774, p < 0.001; 0.652, p = 0.004 L; 0.694, p < 0.001; and 0.716, p < 0.001, respectively). In multivariate analysis, FIV remained strongly associated with 90-day mRS. FIV showed a bimodal distribution consistent with success/failure of recanalization during thrombectomy. Conclusion: Of the algorithm outputs assessed, FIV was most strongly associated with clinical outcomes. Ischemic injury, HT, edema and IG were also independently significantly associated with clinical outcome. This study validates the prognostic significance of automated FIV and its composites as mechanistic endpoints to improve early-stage trials of therapeutics in AIS

CT perfusion for lesion-symptom mapping in large vessel occlusion ischemic stroke

Background: Identifying eloquent regions associated with poor outcomes based on CT perfusion (CTP) may help inform personalized decisions on selection for endovascular therapy (EVT) in patients with large vessel occlusion (LVO) ischemic stroke. This study aimed to characterize the relationship between CTP-defined hypoperfusion and National Institutes of Health Stroke Scale (NIHSS) subitem deficits. Methods: Patients with anterior circulation LVO, baseline CTP, itemized NIHSS at presentation and 24 hours were included. CTP was analyzed using e-CTP (Brainomix, UK). Time to maximal contrast (Tmax) prolongation was defined as >6 s, and penumbra as the difference between Tmax and ischemic core (relative cerebral blood flow<30%). Voxel-lesion-symptom mapping was performed using sparse canonical correlation analysis. For each NIHSS subitem, and total NIHSS, the associations were plotted between Tmax voxels with baseline NIHSS, and penumbra voxels with delta NIHSS (24 hours minus baseline). Results: This study included 171 patients. Total NIHSS was predicted by hypoperfusion in left frontal cortex and subcortical white matter tracts. Voxels associated with neurological recovery were symmetrical and subcortical. Limb deficits were associated with respective motor cortex regions and descending motor tracts, with negative correlation within the contralateral hemispheres. A similar but smaller cluster of voxels within the penumbra was associated with NIHSS improvement. Language impairment correlated with left frontal cortex and superior temporal gyrus voxels. With the exception of dysarthria, significant associations were observed and more diffusely distributed in all other NIHSS subitems. Conclusions: These results demonstrate the feasibility of hypoperfusion-to-symptom mapping in LVO. Symptom-based mapping from presenting imaging could refine treatment decisions targeting specific neurological deficits