Investigation of relayed nuclear Overhauser enhancement effect at -1.6 ppm in an ischemic stroke model.

Background: When an ischemic stroke happens, it triggers a complex signalling cascade that may eventually lead to neuronal cell death if no reperfusion. Recently, the relayed nuclear Overhauser enhancement effect at -1.6 ppm [NOE(-1.6 ppm)] has been postulated may allow for a more in-depth analysis of the ischemic injury. This study assessed the potential utility of NOE(-1.6 ppm) in an ischemic stroke model. Methods: Diffusion-weighted imaging, perfusion-weighted imaging, and chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) data were acquired from five rats that underwent scans at 9.4 T after middle cerebral artery occlusion. Results: The apparent diffusion coefficient (ADC), cerebral blood flow (CBF), and apparent exchange-dependent relaxations (AREX) at 3.5 ppm and NOE(-1.6 ppm) were quantified. AREX(3.5 ppm) and NOE(-1.6 ppm) were found to be hypointense and exhibited different signal patterns within the ischemic tissue. The NOE(-1.6 ppm) deficit areas were equal to or larger than the ADC deficit areas, but smaller than the AREX(3.5 ppm) deficit areas. This suggested that NOE(-1.6 ppm) might further delineate the acidotic tissue estimated using AREX(3.5 ppm). Since NOE(-1.6 ppm) is closely related to membrane phospholipids, NOE(-1.6 ppm) potentially highlighted at-risk tissue affected by lipid peroxidation and membrane damage. Altogether, the ADC/NOE(-1.6 ppm)/AREX(3.5 ppm)/CBF mismatches revealed four zones of increasing sizes within the ischemic tissue, potentially reflecting different pathophysiological information. Conclusions: Using CEST coupled with ADC and CBF, the ischemic tissue may thus potentially be separated into four zones to better understand the pathophysiology after stroke and improve ischemic tissue fate definition. Further verification of the potential utility of NOE(-1.6 ppm) may therefore lead to a more precise diagnosis.

Impact of e-ASPECTS software on the performance of physicians compared to a consensus ground truth: a multi-reader, multi-case study.

Background: The Alberta Stroke Program Early CT Score (ASPECTS) is used to quantify the extent of injury to the brain following acute ischemic stroke (AIS) and to inform treatment decisions. The e-ASPECTS software uses artificial intelligence methods to automatically process non-contrast CT (NCCT) brain scans from patients with AIS affecting the middle cerebral artery (MCA) territory and generate an ASPECTS. This study aimed to evaluate the impact of e-ASPECTS (Brainomix, Oxford, UK) on the performance of US physicians compared to a consensus ground truth. Methods: The study used a multi-reader, multi-case design. A total of 10 US board-certified physicians (neurologists and neuroradiologists) scored 54 NCCT brain scans of patients with AIS affecting the MCA territory. Each reader scored each scan on two occasions: once with and once without reference to the e-ASPECTS software, in random order. Agreement with a reference standard (expert consensus read with reference to follow-up imaging) was evaluated with and without software support. Results: A comparison of the area under the curve (AUC) for each reader showed a significant improvement from 0.81 to 0.83 (p = 0.028) with the support of the e-ASPECTS tool. The agreement of reader ASPECTS scoring with the reference standard was improved with e-ASPECTS compared to unassisted reading of scans: Cohen's kappa improved from 0.60 to 0.65, and the case-based weighted Kappa improved from 0.70 to 0.81. Conclusion: Decision support with the e-ASPECTS software significantly improves the accuracy of ASPECTS scoring, even by expert US neurologists and neuroradiologists.

Posterior circulation ischaemic stroke diagnosis and management.

This narrative review provides an overview of the posterior circulation and the clinical features of common posterior circulation stroke (PCS) syndromes in the posterior arterial territories and how to distinguish them from mimics. We outline the hyperacute management of patients with suspected PCS with emphasis on how to identify those who are likely to benefit from intervention based on imaging findings. Finally, we review advances in treatment options, including developments in endovascular thrombectomy (EVT) and intravenous thrombolysis (IVT), and the principles of medical management and indications for neurosurgery. Observational and randomised clinical trial data have been equivocal regarding EVT in PCS, but more recent studies strongly support its efficacy. There have been concomitant advances in imaging of posterior stroke to guide optimal patient selection for thrombectomy. Recent evidence suggests that clinicians should have a heightened suspicion of posterior circulation events with the resultant implementation of timely, evidence-based management.

Reduced Left Atrial Rotational Flow Is Independently Associated With Embolic Brain Infarcts.

BACKGROUND: Up to 25% of embolic strokes occur in individuals without atrial fibrillation (AF) or other identifiable mechanisms. OBJECTIVES: This study aims to assess whether left atrial (LA) blood flow characteristics are associated with embolic brain infarcts, independently of AF. METHODS: The authors recruited 134 patients: 44 with a history of ischemic stroke and 90 with no history of stroke but CHA2DS2VASc score ≥1. Cardiac magnetic resonance (CMR) evaluated cardiac function and LA 4-dimensional flow parameters, including velocity and vorticity (a measure of rotational flow), and brain magnetic resonance imaging (MRI) was performed to detect large noncortical or cortical infarcts (LNCCIs) (likely embolic), or nonembolic lacunar infarcts. RESULTS: Patients (41% female; age 70 ± 9 years) had moderate stroke risk (median CHA2DS2VASc = 3, Q1-Q3: 2-4). Sixty-eight (51%) had diagnosed AF, of whom 58 (43%) were in AF during CMR. Thirty-nine (29%) had ≥1 LNCCI, 20 (15%) had ≥1 lacunar infarct without LNCCI, and 75 (56%) had no infarct. Lower LA vorticity was significantly associated with prevalent LNCCIs after adjustment for AF during CMR, history of AF, CHA2DS2VASc score, LA emptying fraction, LA indexed maximum volume, left ventricular ejection fraction, and indexed left ventricular mass (OR: 2.06 [95% CI: 1.08-3.92 per SD]; P = 0.027). By contrast, LA flow peak velocity was not significantly associated with LNCCIs (P = 0.21). No LA parameter was associated with lacunar infarcts (all P > 0.05). CONCLUSIONS: Reduced LA flow vorticity is significantly and independently associated with embolic brain infarcts. Imaging LA flow characteristics may aid identification of individuals who would benefit from anticoagulation for embolic stroke prevention, regardless of heart rhythm.

Automated CT angiography collateral scoring in anterior large vessel occlusion stroke: A multireader study.

BACKGROUND: Computed tomography (CT) angiography collateral score (CTA-CS) is an important clinical outcome predictor following mechanical thrombectomy for ischemic stroke with large vessel occlusion (LVO). The present multireader study aimed to evaluate the performance of e-CTA software for automated assistance in CTA-CS scoring. MATERIALS AND METHODS: Brain CTA images of 56 patients with anterior LVO were retrospectively processed. Twelve readers of various clinical training, including junior neuroradiologists, senior neuroradiologists, and neurologists graded collateral flow using visual CTA-CS scale in two sessions separated by a washout period. Reference standard was the consensus of three expert readers. Duration of reading time, inter-rater reliability, and statistical comparison of readers' performance metrics were analyzed between the e-CTA assisted and unassisted sessions. RESULTS: e-CTA assistance resulted in significant increase in mean accuracy (58.6% to 67.5%, p = 0.003), mean F1 score (0.574 to 0.676, p = 0.002), mean precision (58.8% to 68%, p = 0.007), and mean recall (58.7% to 69.9%, p = 0.002), especially with slight filling deficit (CTA-CS 2 and 3). Mean reading time was reduced across all readers (103.4 to 59.7 s, p = 0.001), and inter-rater agreement in CTA-CS assessment was increased (Krippendorff's alpha 0.366 to 0.676). Optimized occlusion laterality detection was also noted with mean accuracy (92.9% to 96.8%, p = 0.009). CONCLUSION: Automated assistance for CTA-CS using e-CTA software provided helpful decision support for readers in terms of improving scoring accuracy and reading efficiency for physicians with a range of experience and training backgrounds and leading to significant improvements in inter-rater agreement.

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

Introduction: In 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. Methods: Except 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. Results: In 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 < 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. Conclusion: In 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.

Efficacy of Cerebrolysin Treatment as an Add-On Therapy to Mechanical Thrombectomy in Patients With Acute Ischemic Stroke Due to Large Vessel Occlusion: Study Protocol for a Prospective, Open Label, Single-Center Study With 12 Months of Follow-Up.

This study is designed to determine the efficacy of Cerebrolysin treatment as an add-on therapy to mechanical thrombectomy (MT) in reducing global disability in subjects with acute ischemic stroke (AIS). We have planned a single center, prospective, open-label, single-arm study with a 12-month follow-up of 50 patients with moderate to severe AIS, with a small established infarct core and with good collateral circulation who achieve significant reperfusion following MT and who receive additional Cerebrolysin within 8 h of stroke onset compared to 50 historical controls treated with MT alone, matched for age, clinical severity, occlusion location, baseline perfusion lesion volume, onset to reperfusion time, and use of iv thrombolytic therapy. The primary outcome measure will be the overall proportion of subjects receiving Cerebrolysin compared to the control group experiencing a favorable functional outcome (by modified Rankin Scale 0-2) at 90 days, following stroke onset. The secondary objectives are to determine the efficacy of Cerebrolysin as compared to the control group in reducing the risk of symptomatic secondary hemorrhagic transformation, improving neurological outcomes (NIHSS 0-2 at day 7, day 30, and 90), reducing mortality rates (over the 90-day and 12 months study period), and improving: activities of daily living (by Barthel Index), health-related quality of life (EQ-5D-5L) assessed at day 30, 90, and at 12 months. The other measures of efficacy in the Cerebrolysin group will include: assessment of final stroke volume and penumbral salvage (measured by CT/CTP at 30 days) and its change compared to baseline volume, changes over time in language function (by the 15-item Boston Naming Test), hemispatial neglect (by line bisection test), global cognitive function (by The Montreal Cognitive Assessment), and depression (by Hamilton Depression Rating Scale) between day 30 and day 90 assessments). The patients will receive 30 ml of Cerebrolysin within 8 h of AIS stroke onset and continue treatment once daily until day 21 (first cycle) and they will receive a second cycle of treatment (30 ml/d for 21 days given in the Outpatient Department or Neurorehabilitation Clinic) from day 69 to 90.

Interpretable Machine Learning Modeling for Ischemic Stroke Outcome Prediction.

Background and Purpose: Mechanical thrombectomy greatly improves stroke outcomes. Nonetheless, some patients fall short of full recovery despite good reperfusion. The purpose of this study was to develop machine learning (ML) models for the pre-interventional prediction of functional outcome at 3 months of thrombectomy in acute ischemic stroke (AIS), using clinical and auto-extractable radiological information consistently available upon first emergency evaluation. Materials and Methods: A two-center retrospective cohort of 293 patients with AIS who underwent thrombectomy was analyzed. ML models were developed to predict dichotomized modified Rankin score at 90 days (mRS-90) using clinical and imaging features, both separately and combined. Conventional and experimental imaging biomarkers were quantified using automated image-processing software from non-contract computed tomography (CT) and computed tomography angiography (CTA). Shapley Additive Explanation (SHAP) was applied for model interpretability and predictor importance analysis of the optimal model. Results: Merging clinical and imaging features returned the best results for mRS-90 prediction. The best performing classifier was Extreme Gradient Boosting (XGB) with an area under the receiver operating characteristic curve (AUC) = 84% using selected features. The most important classifying features were age, baseline National Institutes of Health Stroke Scale (NIHSS), occlusion side, degree of brain atrophy [primarily represented by cortical cerebrospinal fluid (CSF) volume and lateral ventricle volume], early ischemic core [primarily represented by e-Alberta Stroke Program Early CT Score (ASPECTS)], and collateral circulation deficit volume on CTA. Conclusion: Machine learning that is applied to quantifiable image features from CT and CTA alongside basic clinical characteristics constitutes a promising automated method in the pre-interventional prediction of stroke prognosis. Interpretable models allow for exploring which initial features contribute the most to post-thrombectomy outcome prediction overall and for each individual patient outcome.

Quantitative chemical exchange saturation transfer imaging of nuclear overhauser effects in acute ischemic stroke.

PURPOSE: In chemical exchange saturation transfer imaging, saturation effects between - 2 to - 5 ppm (nuclear Overhauser effects, NOEs) have been shown to exhibit contrast in preclinical stroke models. Our previous work on NOEs in human stroke used an analysis model that combined NOEs and semisolid MT; however their combination might feasibly have reduced sensitivity to changes in NOEs. The aim of this study was to explore the information a 4-pool Bloch-McConnell model provides about the NOE contribution in ischemic stroke, contrasting that with an intentionally approximate 3-pool model. METHODS: MRI data from 12 patients presenting with ischemic stroke were retrospectively analyzed, as well as from six animals induced with an ischemic lesion. Two Bloch-McConnell models (4 pools, and a 3-pool approximation) were compared for their ability to distinguish pathological tissue in acute stroke. The association of NOEs with pH was also explored, using pH phantoms that mimic the intracellular environment of naïve mouse brain. RESULTS: The 4-pool measure of NOEs exhibited a different association with tissue outcome compared to 3-pool approximation in the ischemic core and in tissue that underwent delayed infarction. In the ischemic core, the 4-pool measure was elevated in patient white matter ( 1.20±0.20 ) and in animals ( 1.27±0.20 ). In the naïve brain pH phantoms, significant positive correlation between the NOE and pH was observed. CONCLUSION: Associations of NOEs with tissue pathology were found using the 4-pool metric that were not observed using the 3-pool approximation. The 4-pool model more adequately captured in vivo changes in NOEs and revealed trends depending on tissue pathology in stroke.

Improved Stroke Care in a Primary Stroke Centre Using AI-Decision Support.

BACKGROUND: Patient selection for reperfusion therapies requires significant expertise in neuroimaging. Increasingly, machine learning-based analysis is used for faster and standardized patient selection. However, there is little information on how such software influences real-world patient management. AIMS: We evaluated changes in thrombolysis and thrombectomy delivery following implementation of automated analysis at a high volume primary stroke centre. METHODS: We retrospectively collected data on consecutive stroke patients admitted to a large university stroke centre from two identical 7-month periods in 2017 and 2018 between which the e-Stroke Suite (Brainomix, Oxford, UK) was implemented to analyse non-contrast CT and CT angiography results. Delivery of stroke care was otherwise unchanged. Patients were transferred to a hub for thrombectomy. We collected the number of patients receiving intravenous thrombolysis and/or thrombectomy, the time to treatment; and outcome at 90 days for thrombectomy. RESULTS: 399 patients from 2017 and 398 from 2018 were included in the study. From 2017 to 2018, thrombolysis rates increased from 11.5% to 18.1% with a similar trend for thrombectomy (2.8-4.8%). There was a trend towards shorter door-to-needle times (44-42 min) and CT-to-groin puncture times (174-145 min). There was a non-significant trend towards improved outcomes with thrombectomy. Qualitatively, physician feedback suggested that e-Stroke Suite increased decision-making confidence and improved patient flow. CONCLUSIONS: Use of artificial intelligence decision support in a hyperacute stroke pathway facilitates decision-making and can improve rate and time of reperfusion therapies in a hub-and-spoke system of care.

Frailty and cerebrovascular disease: Concepts and clinical implications for stroke medicine.

Frailty is a distinctive health state in which the ability of older people to cope with acute stressors is compromised by an increased vulnerability brought by age-associated declines in physiological reserve and function across multiple organ systems. Although closely associated with age, multimorbidity, and disability, frailty is a discrete syndrome that is associated with poorer outcomes across a range of medical conditions. However, its role in cerebrovascular disease and stroke has received limited attention. The estimated rise in the prevalence of frailty associated with changing demographics over the coming decades makes it an important issue for stroke practitioners, cerebrovascular research, clinical service provision, and stroke survivors alike. This review will consider the concept and models of frailty, how frailty is common in cerebrovascular disease, the impact of frailty on stroke risk factors, acute treatments, and rehabilitation, and considerations for future applications in both cerebrovascular clinical and research settings.

Automated quantification of atrophy and acute ischemic volume for outcome prediction in endovascular thrombectomy.

Background: Short- and long-term outcomes from endovascular thrombectomy (EVT) for large vessel occlusion stroke remain variable. Numerous relevant predictors have been identified, including severity of neurological deficits, age, and imaging features. The latter is typically defined as acute changes (most commonly Alberta Stroke Programme Early CT Score, ASPECTS, at presentation), but there is little information on the impact of imaging assessment of premorbid brain health as a determinant of outcome. Aims: To examine the impact of automated measures of stroke severity and underlying brain frailty on short- and long-term outcomes in acute stroke treated with EVT. Methods: In 215 patients with anterior circulation stroke, who subsequently underwent EVT, automated analysis of presenting non-contrast CT scans was used to determine acute ischemic volume (AIV) and e-ASPECTS as markers of stroke severity, and cerebral atrophy as a marker of brain frailty. Univariate and multivariate logistic regression were used to identify significant predictors of NIHSS improvement, modified Rankin scale (mRS) at 90 and 30 days, mortality at 90 days and symptomatic intracranial hemorrhage (sICH) following successful EVT. Results: For long-term outcome, atrophy and presenting NIHSS were significant predictors of mRS 0-2 and death at 90 days, whereas age did not reach significance in multivariate analysis. Conversely, for short-term NIHSS improvement, AIV and age were significant predictors, unlike presenting NIHSS. The interaction between age and NIHSS was similar to the interaction of AIV and atrophy for mRS 0-2 at 90 days. Conclusion: Combinations of automated software-based imaging analysis and clinical data can be useful for predicting short-term neurological outcome and may improve long-term prognostication in EVT. These results provide a basis for future development of predictive tools built into decision-aiding software in stroke.

Clinical translation of amide proton transfer (APT) MRI for ischemic stroke: a systematic review (2003-2020).

Amide proton transfer (APT) magnetic resonance imaging (MRI) is a pH-sensitive imaging technique that can potentially complement existing clinical imaging protocol for the assessment of ischemic stroke. This review aims to summarize the developments in the clinical research of APT imaging of ischemic stroke after 17 years of progress since its first preclinical study in 2003. Three electronic databases: PubMed, Scopus, and Cochrane Library were systematically searched for articles reporting clinical studies on APT imaging of ischemic stroke. Only articles in English published between 2003 to 2020 that involved patients presenting ischemic stroke-like symptoms that underwent APT MRI were included. Of 1,093 articles screened, 14 articles met the inclusion criteria with a total of 282 patients that had been scanned using APT imaging. Generally, the clinical studies agreed APT effect to be hypointense in ischemic tissue compared to healthy tissue, allowing for the detection of ischemic stroke. Other uses of APT imaging have also been investigated in the studies, including penumbra identification, predicting long term clinical outcome, and serving as a biomarker for supportive treatment monitoring. The published results demonstrated the potential of APT imaging in these applications, but further investigations and larger trials are needed for conclusive evidence. Future studies are recommended to report the result of asymmetry analysis at 3.5 ppm along with the findings of the study to reduce this contribution to the heterogeneity of experimental methods observed and to facilitate effective comparison of results between studies and centers. In addition, it is important to focus on the development of fast 3D imaging for full volumetric ischemic tissue assessment for clinical translation.

Noncontrast Computed Tomography e-Stroke Infarct Volume Is Similar to RAPID Computed Tomography Perfusion in Estimating Postreperfusion Infarct Volumes.

BACKGROUND AND PURPOSE: The e-Stroke Suite software (Brainomix, Oxford, United Kingdom) is a tool designed for the automated quantification of The Alberta Stroke Program Early CT Score and ischemic core volumes on noncontrast computed tomography (NCCT). We sought to compare the prediction of postreperfusion infarct volumes and the clinical outcomes across NCCT e-Stroke software versus RAPID (IschemaView, Menlo Park, CA) computed tomography perfusion measurements. METHODS: All consecutive patients with anterior circulation large vessel occlusion stroke presenting at a tertiary care center between September 2010 and November 2018 who had available baseline infarct volumes on both NCCT e-Stroke Suite software and RAPID CTP as well as final infarct volume (FIV) measurements and achieved complete reperfusion (modified Thrombolysis in Cerebral Infarction scale 2c-3) post-thrombectomy were included. The associations between estimated baseline ischemic core volumes and FIV as well as 90-day functional outcomes were assessed. RESULTS: Four hundred seventy-nine patients met inclusion criteria. Median age was 64 years (55-75), median e-Stroke and computed tomography perfusion ischemic core volumes were 38.4 (21.8-58) and 5 (0-17.7) mL, respectively, whereas median FIV was 22.2 (9.1-56.2) mL. The correlation between e-Stroke and CTP ischemic core volumes was moderate (R=0.44; P<0.001). Similarly, moderate correlations were observed between e-Stroke software ischemic core and FIV (R=0.52; P<0.001) and CTP core and FIV (R=0.43; P<0.001). Subgroup analysis showed that e-Stroke software and CTP performance was similar in the early and late (>6 hours) treatment windows. Multivariate analysis showed that both e-Stroke software NCCT baseline ischemic core volume (adjusted odds ratio, 0.98 [95% CI, 0.97-0.99]) and RAPID CTP ischemic core volume (adjusted odds ratio, 0.98 [95% CI, 0.97-0.99]) were independently and comparably associated with good outcome (modified Rankin Scale score of 0-2) at 90 days. CONCLUSIONS: NCCT e-Stroke Suite software performed similarly to RAPID CTP in assessing postreperfusion FIV and functional outcomes for both early- and late-presenting patients. NCCT e-Stroke volumes seems to represent a viable alternative in centers where access to advanced imaging is limited. Moreover, the future development of fusion maps of NCCT and CTP ischemic core estimates may improve upon the current performance of these tools as applied in isolation.

A Comparison of T2 Relaxation-Based MRI Stroke Timing Methods in Hyperacute Ischemic Stroke Patients: A Pilot Study.

BACKGROUND: T2 relaxation-based magnetic resonance imaging (MRI) signals may provide onset time for acute ischemic strokes with an unknown onset. The ability of visual and quantitative MRI-based methods in a cohort of hyperacute ischemic stroke patients was studied. METHODS: A total of 35 patients underwent 3T (3 Tesla) MRI (<9-hour symptom onset). Diffusion-weighted (DWI), apparent diffusion coefficient (ADC), T1-weighted (T1w), T2-weighted (T2w), and T2 relaxation time (T2) images were acquired. T2-weighted fluid attenuation inversion recovery (FLAIR) images were acquired for 17 of these patients. Image intensity ratios of the average intensities in ischemic and non-ischemic reference regions were calculated for ADC, DWI, T2w, T2 relaxation, and FLAIR images, and optimal image intensity ratio cut-offs were determined. DWI and FLAIR images were assessed visually for DWI/FLAIR mismatch. RESULTS: The T2 relaxation time image intensity ratio was the only parameter with significant correlation with stroke duration (r = 0.49, P = .003), an area under the receiver operating characteristic curve (AUC = 0.77, P < .0001), and an optimal cut-off (T2 ratio = 1.072) that accurately identified patients within the 4.5-hour thrombolysis treatment window with sensitivity of 0.74 and specificity of 0.74. In the patients with the additional FLAIR, areas under the precision-recall-gain curve (AUPRG) and F1 scores showed that the T2 relaxation time ratio (AUPRG = 0.60, F1 = 0.73) performed considerably better than the FLAIR ratio (AUPRG = 0.39, F1 = 0.57) and the visual DWI/FLAIR mismatch (F1 = 0.25). CONCLUSIONS: Quantitative T2 relaxation time is the preferred MRI parameter in the assessment of patients with unknown onset for treatment stratification.

Innovative use of artificial intelligence and digital communication in acute stroke pathway in response to COVID-19.

Acute stroke care demands real-time, specialist-led treatment decisions, including thrombolysis and referral for mechanical thrombectomy. Pathways designed to deliver time-critical interventions for stroke patients are under intense pressure due to the impact of COVID-19 pandemic. In response to this unprecedented burden on acute care services, stroke clinicians are having to reconfigure existing clinical pathways both within and between hospitals. Incorporating artificial intelligence and digital communication support into clinical pathways offers an opportunity to mitigate the disruption to acute stroke care. In this case study we describe how Royal Berkshire Hospital, working collaboratively with Brainomix, a UK-based artificial intelligence software company, adopted technological innovation and integrated it into the hyperacute stroke pathway. A case is presented to demonstrate how this innovation can support patient care and deliver successful patient outcomes. We believe this model can be adopted in other hospitals and networks to deliver safe and efficient hyperacute stroke care.

Determining T2 relaxation time and stroke onset relationship in ischaemic stroke within apparent diffusion coefficient-defined lesions. A user-independent method for quantifying the impact of stroke in the human brain.

BACKGROUND AND OBJECTIVE: In hyperacute ischaemic stroke, T2 of cerebral water increases with time. Quantifying this change may be informative of the extent of tissue damage and onset time. Our objective was to develop a user-unbiased method to measure the effect of cerebral ischaemia on T2 to study stroke onset time-dependency in human acute stroke lesions. METHODS: Six rats were subjected to permanent middle cerebral occlusion to induce focal ischaemia, and a consecutive cohort of acute stroke patients (n = 38) were recruited within 9 hours from symptom onset. T1-weighted structural, T2 relaxometry, and diffusion MRI for apparent diffusion coefficient (ADC) were acquired. Ischaemic lesions were defined as regions of lowered ADC. The median T2 difference (ΔT2) between lesion and contralateral non-ischaemic control region was determined by the newly-developed spherical reference method, and data compared to that obtained by the mirror reference method. Linear regressions and receiver operating characteristics (ROC) were compared between the two methods. RESULTS: ΔT2 increases linearly in rat brain ischaemia by 1.9 ± 0.8 ms/h during the first 6 hours, as determined by the spherical reference method. In patients, ΔT2 linearly increases by 1.6 ± 1.4 and 1.9 ± 0.9 ms/h in the lesion, as determined by the mirror reference and spherical reference method, respectively. ROC analyses produced areas under the curve of 0.83 and 0.71 for the spherical and mirror reference methods, respectively. CONCLUSIONS: Data from the spherical reference method showed that the median T2 increase in the ischaemic lesion is correlated with stroke onset time in a rat as well as in a human patient cohort, opening the possibility of using the approach as a timing tool in clinics.