Time-Dependent Computed Tomographic Perfusion Thresholds for Patients With Acute Ischemic Stroke

Current State of Evidence for Neuroimaging Paradigms in Management of Acute Ischemic Stroke

Stroke is the chief differential diagnosis in patient presenting to the emergency room with abrupt onset focal neurological deficits. Neuroimaging, including non-contrast computed tomography (CT), magnetic resonance imaging (MRI), vascular and perfusion imaging, is a cornerstone in the diagnosis and treatment decision-making. This review examines the current state of evidence behind the different imaging paradigms for acute ischemic stroke diagnosis and treatment, including current recommendations from the guidelines. Non-contrast CT brain, or in some centers MRI, can help differentiate ischemic stroke and intracerebral hemorrhage (ICH), a pivotal juncture in stroke diagnosis and treatment algorithm, especially for early window thrombolytics. Advanced imaging such as MRI or perfusion imaging can also assist making a diagnosis of ischemic stroke versus mimics such as migraine, Todd's paresis, or functional disorders. Identification of medium-large vessel occlusions with CT or MR angiography triggers consideration of endovascular thrombectomy (EVT), with additional perfusion imaging help identify salvageable brain tissue in patients who are likely to benefit from reperfusion therapies, particularly in the ≥6 h window. We also review recent advances in neuroimaging and ongoing trials in key therapeutic areas and their imaging selection criteria to inform the readers on potential future transitions into use of neuroimaging for stroke diagnosis and treatment decision making. ANN NEUROL 2024;95:1017-1034.

Hypoperfusion index ratio and pretreatment with intravenous thrombolysis are independent predictors of good functional outcome in acute ischemic stroke patients with large vessel occlusion treated with acute reperfusion therapies

INTRODUCTION

We aimed to investigate the performance of several neuroimaging markers provided by perfusion imaging of Acute Ischemic Stroke (AIS) patients with large vessel occlusion (LVO) in order to predict clinical outcomes following reperfusion treatments.

METHODS

We prospectively evaluated consecutive AIS patients with LVO who were treated with reperfusion therapies, during a six-year period. In order to compare patients with good (mRS scores 0-2) and poor (mRS scores 3-6) functional outcomes, data regarding clinical characteristics, the Alberta Stroke Programme Early Computed Tomography Score (ASPECTS) based on unenhanced computed tomography (CT), CT angiography collateral status and perfusion parameters including ischemic core, hypoperfusion volume, mismatch volume between core and penumbra, Tmax > 10 s volume, CBV index and the Hypoperfusion Index Ratio (HIR) were assessed.

RESULTS

A total of 84 acute stroke patients with LVO who met all the inclusion criteria were enrolled. In multivariable logistic regression models increasing age (odds ratio [OR]: 0.93; 95%CI: 0.88-0.96, p = 0.001), lower admission National Institute of Health Stroke Scale (NIHSS)-score (OR: 0.88; 95%CI: 0.80-0.95, p = 0.004), pretreatment with intravenous thrombolysis (OR: 3.83; 95%CI: 1.29-12.49, p = 0.019) and HIR (OR:0.36; 95%CI: 0.10-0.95, p = 0.042) were independent predictors of good functional outcome at 3 months. The initial univariable associations between HIR and higher likelihood for symptomatic intracranial hemorrhage (sICH) and parenchymal hematoma type 2 (PH2) were attenuated in multivariable analyses failing to reach statistical significance.

DISCUSSION

Our pilot observational study of unselected AIS patients with LVO treated with reperfusion therapies demonstrated that pre-treatment low HIR in perfusion imaging and IVT were associated with better functional outcomes.

Reducing False-Positives in CT Perfusion Infarct Core Segmentation Using Contralateral Local Normalization

BACKGROUND AND PURPOSE

The established global threshold of rCBF <30% for infarct core segmentation can lead to false-positives, as it does not account for the differences in blood flow between GM and WM and patient-individual factors, such as microangiopathy. To mitigate this problem, we suggest normalizing each voxel not only with a global reference value (ie, the median value of normally perfused tissue) but also with its local contralateral counterpart.

MATERIALS AND METHODS

We retrospectively enrolled 2830 CTP scans with suspected ischemic stroke, of which 335 showed obvious signs of microangiopathy. In addition to the conventional, global normalization, a local normalization was performed by dividing the rCBF maps with their mirrored and smoothed counterpart, which sets each voxel value in relation to the contralateral counterpart, intrinsically accounting for GM and WM differences and symmetric patient individual microangiopathy. Maps were visually assessed and core volumes were calculated for both methods.

RESULTS

Cases with obvious microangiopathy showed a strong reduction in false-positives by using local normalization (mean 14.7 mL versus mean 3.7 mL in cases with and without microangiopathy). On average, core volumes were slightly smaller, indicating an improved segmentation that was more robust against naturally low blood flow values in the deep WM.

CONCLUSIONS

The proposed method of local normalization can reduce overestimation of the infarct core, especially in the deep WM and in cases with obvious microangiopathy. False-positives in CTP infarct core segmentation might lead to less-than-optimal therapy decisions when not correctly interpreted. The proposed method might help mitigate this problem.

Value of Immediate Flat Panel Perfusion Imaging after Endovascular Therapy (AFTERMATH): A Proof of Concept Study

BACKGROUND AND PURPOSE

Potential utility of flat panel CT perfusion imaging (FPCT-PI) performed immediately after mechanical thrombectomy (MT) is unknown. We aimed to assess whether FPCT-PI obtained directly post-MT could provide additional potentially relevant information on tissue reperfusion status.

MATERIALS AND METHODS

This was a single-center analysis of all patients with consecutive acute stroke admitted between June 2019 and March 2021 who underwent MT and postinterventional FPCT-PI (n = 26). A core lab blinded to technical details and clinical data performed TICI grading on postinterventional DSA images and qualitatively assessed reperfusion on time-sensitive FPCT-PI maps. According to agreement between DSA and FPCT-PI, all patients were classified into 4 groups: hypoperfusion findings perfectly matched by location (group 1), hypoperfusion findings mismatched by location (group 2), complete reperfusion on DSA with hypoperfusion on FPCT-PI (group 3), and hypoperfusion on DSA with complete reperfusion on FPCT-PI (group 4).

RESULTS

Detection of hypoperfusion (present/absent) concurred in 21/26 patients. Of these, reperfusion findings showed perfect agreement on location and size in 16 patients (group 1), while in 5 patients there was a mismatch by location (group 2). Of the remaining 5 patients with disagreement regarding the presence or absence of hypoperfusion, 3 were classified into group 3 and 2 into group 4. FPCT-PI findings could have avoided TICI overestimation in all false-positive operator-rated TICI 3 cases (10/26).

CONCLUSIONS

FPCT-PI may provide additional clinically relevant information in a considerable proportion of patients undergoing MT. Hence, FPCT-PI may complement the evaluation of reperfusion efficacy and potentially inform decision-making in the angiography suite.

CT perfusion stroke lesion threshold calibration between deconvolution algorithms

CTP is an important diagnostic tool in managing patients with acute ischemic stroke, but challenges persist in the agreement of stroke lesion volumes and ischemic core-penumbra mismatch profiles determined with different CTP post-processing software. We investigated a systematic method of calibrating CTP stroke lesion thresholds between deconvolution algorithms using a digital perfusion phantom to improve inter-software agreement of mismatch profiles. Deconvolution-estimated cerebral blood flow (CBF) and Tmax was compared to the phantom ground truth via linear regression for one model-independent and two model-based deconvolution algorithms. Using the clinical standard of model-independent CBF < 30% and Tmax > 6 s as reference thresholds for ischemic core and penumbra, respectively, we determined that model-based CBF < 15% and Tmax > 6 s were the corresponding calibrated thresholds after accounting for quantitative differences revealed at linear regression. Calibrated thresholds were then validated in 63 patients with large vessel stroke by evaluating agreement (concordance and Cohen's kappa, κ) between the two model-based and model-independent deconvolution methods in determining mismatch profiles used for clinical decision-making. Both model-based deconvolution methods achieved 95% concordance with model-independent assessment and Cohen's kappa was excellent (κ = 0.87; 95% confidence interval [CI] 0.72-1.00 and κ = 0.86; 95% CI 0.70-1.00). Our systematic method of calibrating CTP stroke lesion thresholds may help harmonize mismatch profiles determined by different software.

Automated advanced imaging in acute ischemic stroke. Certainties and uncertainties

The purpose of this is study was to review pearls and pitfalls of advanced imaging, such as computed tomography perfusion and diffusion-weighed imaging and perfusion-weighted imaging in the selection of acute ischemic stroke (AIS) patients suitable for endovascular treatment (EVT) in the late time window (6-24 h from symptom onset). Advanced imaging can quantify infarct core and ischemic penumbra using specific threshold values and provides optimal selection parameters, collectively called target mismatch. More precisely, target mismatch criteria consist of core volume and/or penumbra volume and mismatch ratio (the ratio between total hypoperfusion and core volumes) with precise cut-off values. The parameters of target mismatch are automatically calculated with dedicated software packages that allow a quick and standardized interpretation of advanced imaging. However, this approach has several limitations leading to a misclassification of core and penumbra volumes. In fact, automatic software platforms are affected by technical artifacts and are not interchangeable due to a remarkable vendor-dependent variability, resulting in different estimate of target mismatch parameters. In addition, advanced imaging is not completely accurate in detecting infarct core, that can be under- or overestimated. Finally, the selection of candidates for EVT remains currently suboptimal due to the high rates of futile reperfusion and overselection caused by the use of very stringent inclusion criteria. For these reasons, some investigators recently proposed to replace advanced with conventional imaging in the selection for EVT, after the demonstration that non-contrast CT ASPECTS and computed tomography angiography collateral evaluation are not inferior to advanced images in predicting outcome in AIS patients treated with EVT. However, other authors confirmed that CTP and PWI/DWI postprocessed images are superior to conventional imaging in establishing the eligibility of patients for EVT. Therefore, the routine application of automatic assessment of advanced imaging remains a matter of debate. Recent findings suggest that the combination of conventional and advanced imaging might improving our selection criteria.

Ischemic stroke patients with low DWI ASPECTS scores require puncture to recanalization within 30 min for large vessel occlusion

BACKGROUND

The clinical benefits of faster recanalization in acute large vessel occlusion are well recognized, but the optimal procedure time remains uncertain. The aim of this study was to identify patient characteristics that necessitate puncture-to-recanalization (P-R) time within 30 min to achieve favorable outcome.

METHODS

We evaluated the patients from a prospective, multicenter, observational registry of acute ischemic stroke patients. The study included patients who underwent endovascular therapy for ICA or MCA M1 occlusion and achieved successful recanalization. Patients were categorized into subgroups based on pre-treatment characteristics and the frequency of favorable outcomes was compared between P-R time < 30 min and ≥ 30 min. Interaction terms were incorporated into the models to assess the correlation between each patient characteristic and P-R time.

RESULTS

A total of 1053 patients were included in the study. Univariate analysis within each subgroup revealed a significant association between P-R < 30 min and favorable outcomes in patients with DWI ASPECTS ≤6, age > 85 and NIHSS ≥16. In the multivariable analysis, NIHSS, age, time from symptom recognition to puncture, and DWI ASPECTS were significant independent predictors of favorable outcomes. Notably, only DWI ASPECTS exhibited interaction terms with P-R < 30 min. The multivariable analysis indicated that P-R < 30 min was an independent predictor for favorable outcome in DWI ASPECTS ≤6 group, whereas not in DWI ≥7.

CONCLUSIONS

P-R time < 30 min is predictive of favorable outcomes; however, the effect depends on DWI ASPECTS. Target P-R time < 30 min is appropriate for patients with DWI ASPECTS ≤6.

Assessing the diagnostic accuracy of CT perfusion: a systematic review

Background and purpose

Computed tomography perfusion (CTP) has successfully extended the time window for reperfusion therapies in ischemic stroke. However, the published perfusion parameters and thresholds vary between studies. Using Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Diagnostic Test Accuracy Studies (PRISMA-DTA) guidelines, we conducted a systematic review to investigate the accuracy of parameters and thresholds for identifying core and penumbra in adult stroke patients.

Methods

We searched Medline, Embase, the Cochrane Library, and reference lists of manuscripts up to April 2022 using the following terms "computed tomography perfusion," "stroke," "infarct," and "penumbra." Studies were included if they reported perfusion thresholds and undertook co-registration of CTP to reference standards. The quality of studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool and Standards for Reporting of Diagnostic Accuracy (STARD) guidelines.

Results

A total of 24 studies were included. A meta-analysis could not be performed due to insufficient data and significant heterogeneity in the study design. When reported, the mean age was 70.2 years (SD+/-3.69), and the median NIHSS on admission was 15 (IQR 13-17). The perfusion parameter identified for the core was relative cerebral blood flow (rCBF), with a median threshold of <30% (IQR 30, 40%). However, later studies reported lower thresholds in the early time window with rapid reperfusion (median 25%, IQR 20, 30%). A total of 15 studies defined a single threshold for all brain regions irrespective of collaterals and the gray and white matter.

Conclusion

A single threshold and parameter may not always accurately differentiate penumbra from core and oligemia. Further refinement of parameters is needed in the current era of reperfusion therapy.

Minimal Imaging Requirements

The minimal requirements for imaging studies prior to endovascular treatment (EVT) of acute ischemic stroke are those that can provide the information necessary to determine the indication for treatment (treatment triage) and procedural strategies without being time-consuming. An important notion is to determine whether the patient can benefit from EVT. We should recognize that the perfect diagnostic imaging technique does not yet exist, and each has advantages and disadvantages. Generally, stroke imaging protocols to triage for EVT include the following three options: 1) non-contrast CT and CTA, 2) CT perfusion and CTA, and 3) MRI and MRA. It is not known if perfusion imaging or MRI is mandatory for patients with stroke presenting within 6 hours of onset, although non-contrast CT alone has less power to obtain the necessary information. Dual-energy CT can distinguish between post-EVT hemorrhage and contrast agent leakage immediately after EVT.

Association of Intravenous Thrombolysis with Delayed Reperfusion After Incomplete Mechanical Thrombectomy

PURPOSE

Treatment of distal vessel occlusions causing incomplete reperfusion after mechanical thrombectomy (MT) is debated. We hypothesized that pretreatment with intravenous thrombolysis (IVT) may facilitate delayed reperfusion (DR) of residual vessel occlusions causing incomplete reperfusion after MT.

METHODS

Retrospective analysis of patients with incomplete reperfusion after MT, defined as extended thrombolysis in cerebral infarction (eTICI) 2a-2c, and available perfusion follow-up imaging at 24 ± 12 h after MT. DR was defined as absence of any perfusion deficit on time-sensitive perfusion maps, indicating the absence of any residual occlusion. The association of IVT with the occurrence of DR was evaluated using a logistic regression analysis adjusted for confounders. Sensitivity analyses based on IVT timing (time between IVT start and the occurrence incomplete reperfusion following MT) were performed.

RESULTS

In 368 included patients (median age 73.7 years, 51.1% female), DR occurred in 225 (61.1%). Atrial fibrillation, higher eTICI grade, better collateral status and longer intervention-to-follow-up time were all associated with DR. IVT did not show an association with the occurrence of DR (aOR 0.80, 95% CI 0.44-1.46, even in time-sensitive strata, aOR 2.28 [95% CI 0.65-9.23] and aOR 1.53 [95% CI 0.52-4.73] for IVT to incomplete reperfusion following MT timing <80 and <100 min, respectively).

CONCLUSION

A DR occurred in 60% of patients with incomplete MT at ~24 h and did not seem to occur more often in patients receiving pretreatment IVT. Further research on potential associations of IVT and DR after MT is required.

CT perfusion extended window ischemic core estimation: Bayesian algorithm versus oscillation index singular value decomposition

BACKGROUND AND PURPOSE

Ischemic core estimation by CT perfusion (CTp) is a diagnostic challenge, mainly because of the intrinsic noise associated with perfusion data. However, an accurate and reliable quantification of the ischemic core is critical in the selection of patients for reperfusion therapies. Our study aimed at assessing the diagnostic accuracy of two different CTp postprocessing algorithms, that is, the Bayesian Method and the oscillation index singular value decomposition (oSVD).

METHODS

All the consecutive stroke patients studied in the extended time window (>4.5 hours from stroke onset) by CTp and diffusion-weighted imaging (DWI), between October 2019 and December 2021, were enrolled. The agreement between both algorithms and DWI was assessed by the Bland-Altman plot, Wilcoxon signed-rank test, Spearman's rank correlation coefficient, and the intraclass correlation coefficient (ICC).

RESULTS

Twenty-four patients were enrolled (average age: 72 ± 15 years). The average National Institutes of Health Stroke Scale was 14.42 ± 6.75, the median Alberta Stroke Program Early CT score was 8.50 (interquartile range [IQR] = 7.75-9), and median time from stroke onset to neuroimaging was 7.5 hours (IQR = 6.5-8). There was an excellent correlation between DWI and oSVD (ρ = .87, p-value < .001) and DWI and Bayesian algorithm (ρ = .94, p-value < .001). There was a stronger ICC between DWI and Bayesian algorithm (.97, 95% confidence interval [CI]: .92-.99, p-value < .001) than between DWI and oSVD (.59, 95% CI: .26-.8, p-value < .001).

DISCUSSION

The agreement between Bayesian algorithm and DWI was greater than between oSVD and DWI in the extended window. The more accurate estimation of the ischemic core offered by the Bayesian algorithm may well play a critical role in the accurate selection of patients for reperfusion therapies.

Correlation between pretreatment and follow-up infarct volume using CT perfusion imaging: the Bayesian versus singular value decomposition method

PURPOSE

Pretreatment ischemic core volume is conceptually equal to follow-up infarct volume (FIV) in patients with successful recanalization. However, there is sometimes an absolute volume difference (AD) between pretreatment core volume and FIV. The aim was to compare the AD values between the Bayesian and the singular value decomposition (SVD) methods with time from onset-to-imaging in acute ischemic stroke (AIS) patients undergoing mechanical thrombectomy.

METHODS

Consecutive AIS patients were included if they had the following: (1) anterior large vessel occlusion (internal carotid or middle cerebral artery); (2) within 24 h of onset; (3) pretreatment CT perfusion (CTP); (4) successful recanalization (mTICI ≥ 2b); and (5) 24-h diffusion-weighted imaging (DWI). FIV was measured on 24-h DWI. The AD value between FIV and the pretreatment core volume was calculated for Bayesian and SVD methods. Spearman's rank correlation coefficient (rho) was calculated as appropriate.

RESULTS

In the 47 patients enrolled (25 men; median age 78 years; median baseline National Institutes of Health Stroke Scale, 22), the median time from onset-to-imaging and onset-to-recanalization was 136 and 220 min, respectively. Shorter onset-to-imaging time was correlated with a larger AD value, and more trend was seen in the SVD method (rho =  - 0.28, p = 0.05) compared with the Bayesian method (rho =  - 0.08). A larger pretreatment core volume was correlated with a larger AD value, and this tendency was slightly stronger for the SVD (rho = 0.63, p < 0.01) than for the Bayesian (rho = 0.32, p = 0.03) method.

CONCLUSIONS

The Bayesian method might be more correlated with FIV than the SVD method in patients with a large ischemic lesion immediately after stroke onset, but not perfect.

Predicting the tissue outcome of acute ischemic stroke from acute 4D computed tomography perfusion imaging using temporal features and deep learning

Predicting follow-up lesions from baseline CT perfusion (CTP) datasets in acute ischemic stroke patients is important for clinical decision making. Deep convolutional networks (DCNs) are assumed to be the current state-of-the-art for this task. However, many DCN classifiers have not been validated against the methods currently used in research (random decision forests, RDF) and clinical routine (Tmax thresholding). Specialized DCNs have even been designed to extract complex temporal features directly from spatiotemporal CTP data instead of using standard perfusion parameter maps. However, the benefits of applying deep learning to source or deconvolved CTP data compared to perfusion parameter maps have not been formally investigated so far. In this work, a modular UNet-based DCN is proposed that separates temporal feature extraction from tissue outcome prediction, allowing for both model validation using perfusion parameter maps as well as end-to-end learning from spatiotemporal CTP data. 145 retrospective datasets comprising baseline CTP imaging, perfusion parameter maps, and follow-up non-contrast CT with manual lesion segmentations were assembled from acute ischemic stroke patients treated with intravenous thrombolysis alone (IV; n = 43) or intra-arterial mechanical thrombectomy (IA; n = 102) with or without combined IV. Using the perfusion parameter maps as input, the proposed DCN (mean Dice: 0.287) outperformed the RDF (0.262) and simple Tmax-thresholding (0.249). The performance of the proposed DCN was approximately equal using features optimized from the deconvolved residual curves (0.286) compared to perfusion parameter maps (0.287), while using features optimized from the source concentration-time curves (0.296) provided the best tissue outcome predictions.

Low-dose CT Perfusion with Sparse-view Filtered Back Projection in Acute Ischemic Stroke

RATIONALE AND OBJECTIVES

Radiation dose associated with computed tomography (CT) perfusion (CTP) may discourage its use despite its added diagnostic benefit in quantifying ischemic lesion volume. Sparse-view CT reduces scan dose by acquiring fewer X-ray projections per gantry rotation but is contaminated by streaking artifacts using filtered back projection (FBP). We investigated the achievable dose reduction by sparse-view CTP with FBP without affecting CTP lesion volume estimations.

MATERIALS AND METHODS

Thirty-eight consecutive patients with acute ischemic stroke and CTP were included in this simulation study. CTP projection data was simulated by forward projecting original reconstructions with 984 views and adding Gaussian noise. Full-view (984 views) and sparse-view (492, 328, 246, and 164 views) CTP studies were simulated by FBP of simulated projection data. Cerebral blood flow (CBF) and time-to-maximum of the impulse residue function (Tmax) maps were generated by deconvolution for each simulated CTP study. Ischemic volumes were measured by CBF<30% relative to the contralateral hemisphere and Tmax > 6 s. Volume accuracy was evaluated with respect to the full-view CTP study by the Friedman test with post hoc multiplicity-adjusted pairwise tests and Bland-Altman analysis.

RESULTS

Friedman and multiplicity-adjusted pairwise tests indicated that 164-view CBF < 30%, 246- and 164-view Tmax > 6 s volumes were significantly different to full-view volumes (p < 0.001). Mean difference ± standard deviation (sparse minus full-view lesion volume) ranged from -1.0 ± 2.8 ml to -4.1 ± 11.7 ml for CBF < 30% and -2.9 ± 3.8 ml to -12.5 ± 19.9 ml for Tmax > 6 s from 492 to 164 views, respectively.

CONCLUSION

By ischemic volume accuracy, our study indicates that sparse-view CTP may allow dose reduction by up to a factor of 3.

Optimizing the Definition of Ischemic Core in CT Perfusion: Influence of Infarct Growth and Tissue-Specific Thresholds

BACKGROUND AND PURPOSE

CTP allows estimating ischemic core in patients with acute stroke. However, these estimations have limited accuracy compared with MR imaging. We studied the effect of applying WM- and GM-specific thresholds and analyzed the infarct growth from baseline imaging to reperfusion.

MATERIALS AND METHODS

This was a single-center cohort of consecutive patients (n = 113) with witnessed strokes due to proximal carotid territory occlusions with baseline CT perfusion, complete reperfusion, and follow-up DWI. We segmented GM and WM, coregistered CTP with DWI, and compared the accuracy of the different predictions for each voxel on DWI through receiver operating characteristic analysis. We assessed the yield of different relative CBF thresholds to predict the final infarct volume and an estimated infarct growth-corrected volume (subtracting the infarct growth from baseline imaging to complete reperfusion) for a single relative CBF threshold and GM- and WM-specific thresholds.

RESULTS

The fixed threshold underestimated lesions in GM and overestimated them in WM. Double GM- and WM-specific thresholds of relative CBF were superior to fixed thresholds in predicting infarcted voxels. The closest estimations of the infarct on DWI were based on a relative CBF of 25% for a single threshold, 35% for GM, and 20% for WM, and they decreased when correcting for infarct growth: 20% for a single threshold, 25% for GM, and 15% for WM. The combination of 25% for GM and 15% for WM yielded the best prediction.

CONCLUSIONS

GM- and WM-specific thresholds result in different estimations of ischemic core in CTP and increase the global accuracy. More restrictive thresholds better estimate the actual extent of the infarcted tissue.

Clinical and therapeutic variables may influence the association between infarct core predicted by CT perfusion and clinical outcome in acute stroke

OBJECTIVES

After an acute ischemic stroke, patients with a large CT perfusion (CTP) predicted infarct core (pIC) have poor clinical outcome. However, previous research suggests that this relationship may be relevant for subgroups of patients determined by pretreatment and treatment-related variables while negligible for others. We aimed to identify these variables.

METHODS

We included a cohort of 828 patients with acute proximal carotid arterial occlusions imaged with a whole-brain CTP within 8 h from stroke onset. pIC was computed on CTP Maps (cerebral blood flow < 30%), and poor clinical outcome was defined as a 90-day modified Rankin Scale score > 2. Potential mediators of the association between pIC and clinical outcome were evaluated through first-order and advanced interaction analyses in the derivation cohort (n = 654) for obtaining a prediction model. The derived model was further validated in an independent cohort (n = 174).

RESULTS

The volume of pIC was significantly associated with poor clinical outcome (OR = 2.19, 95% CI = 1.73 - 2.78, p < 0.001). The strength of this association depended on baseline National Institute of Health Stroke Scale, glucose levels, the use of thrombectomy, and the interaction of age with thrombectomy. The model combining these variables showed good discrimination for predicting clinical outcome in both the derivation cohort and validation cohorts (area under the receiver operating characteristic curve 0.780 (95% CI = 0.746-0.815) and 0.782 (95% CI = 0.715-0.850), respectively).

CONCLUSIONS

In patients imaged within 8 h from stroke onset, the association between pIC and clinical outcome is significantly modified by baseline and therapeutic variables. These variables deserve consideration when evaluating the prognostic relevance of pIC.

KEY POINTS

•The volume of CT perfusion (CTP) predicted infarct core (pIC) is associated with poor clinical outcome in acute ischemic stroke imaged within 8 h of onset. •The relationship between pIC and clinical outcome may be modified by baseline clinical severity, glucose levels, thrombectomy use, and the interaction of age with thrombectomy. •CTP pIC should be evaluated in an individual basis for predicting clinical outcome in patients imaged within 8 h from stroke onset.

Tmax Volumes Predict Final Infarct Size and Functional Outcome in Ischemic Stroke Patients Receiving Endovascular Treatment

OBJECTIVE

The objective of this paper was to explore the utility of time to maximum concentration (T_max )-based target mismatch on computed tomography perfusion (CTP) in predicting radiological and clinical outcomes in patients with acute ischemic stroke (AIS) with anterior circulation large vessel occlusion (LVO) selected for endovascular treatment (EVT).

METHODS

Patients with AIS underwent CTP within 24 hours from onset followed by EVT. Critically hypoperfused tissue and ischemic core volumes were automatically calculated using T_max thresholds >9.5 seconds and >16 seconds, respectively. The difference between T_max  > 9.5 seconds and T_max  > 16 seconds volumes and the ratio between T_max  > 9.5 seconds and T_max  > 16 seconds volumes were considered ischemic penumbra and T_max mismatch ratio, respectively. Final infarct volume (FIV) was measured on follow-up non-contrast computed tomography (CT) at 24 hours. Favorable clinical outcome was defined as 90-day modified Rankin Scale 0 to 2. Predictors of FIV and outcome were assessed with multivariable logistic regression. Optimal T_max volumes for identification of good outcome was defined using receiver operating curves.

RESULTS

A total of 393 patients were included, of whom 298 (75.8%) achieved successful recanalization and 258 (65.5%) achieved good outcome. In multivariable analyses, all T_max parameters were independent predictors of FIV and outcome. T_max  > 16 seconds volume had the strongest association with FIV (beta coefficient = 0.596 p <0.001) and good outcome (odds ratio [OR] = 0.96 per 1 ml increase, 95% confidence interval [CI] = 0.95-0.97, p < 0.001). T_max  > 16 seconds volume had the highest discriminative ability for good outcome (area under the curve [AUC] = 0.88, 95% CI = 0.842-0.909). A T_max  > 16 seconds volume of ≤67 ml best identified subjects with favorable outcome (sensitivity = 0.91 and specificity = 0.73).

INTERPRETATION

T_max target mismatch predicts radiological and clinical outcomes in patients with AIS with LVO receiving EVT within 24 hours from onset. ANN NEUROL 2022;91:878-888.

Accuracy of CT Perfusion-Based Core Estimation of Follow-up Infarction: Effects of Time Since Last Known Well

BACKGROUND AND OBJECTIVES

To assess the accuracy of baseline CT perfusion (CTP) ischemic core estimates.

METHODS

From SELECT (Optimizing Patient Selection for Endovascular Treatment in Acute Ischemic Stroke), a prospective multicenter cohort study of imaging selection, patients undergoing endovascular thrombectomy who achieved complete reperfusion (modified Thrombolysis In Cerebral Ischemia score 3) and had follow-up diffusion-weighted imaging (DWI) available were evaluated. Follow-up DWI lesions were coregistered to baseline CTP. The difference between baseline CTP core (relative cerebral blood flow [rCBF] <30%) volume and follow-up infarct volume was classified as overestimation (core ≥10 mL larger than infarct), adequate, or underestimation (core ≥25 mL smaller than infarct) and spatial overlap was evaluated.

RESULTS

Of 101 included patients, median time from last known well (LKW) to imaging acquisition was 138 (82-244) minutes. The median baseline ischemic core estimate was 9 (0-31.9) mL and median follow-up infarct volume was 18.4 (5.3-68.7) mL. All 6/101 (6%) patients with overestimation of the subsequent infarct volume were imaged within 90 minutes of LKW and achieved rapid reperfusion (within 120 minutes of CTP). Using rCBF <20% threshold to estimate ischemic core in patients presenting within 90 minutes eliminated overestimation. Volumetric correlation between the ischemic core estimate and follow-up imaging improved as LKW time to imaging acquisition increased: Spearman ρ <90 minutes 0.33 (p = 0.049), 90-270 minutes 0.63 (p < 0.0001), >270 minutes 0.86 (p < 0.0001). Assessment of the spatial overlap between baseline CTP ischemic core lesion and follow-up infarct demonstrated that a median of 3.2 (0.0-9.0) mL of estimated core fell outside the subsequent infarct. These regions were predominantly in white matter.

DISCUSSION

Significant overestimation of irreversibly injured ischemic core volume was rare, was only observed in patients who presented within 90 minutes of LKW and achieved reperfusion within 120 minutes of CTP acquisition, and occurred primarily in white matter. Use of a more conservative (rCBF <20%) threshold for estimating ischemic core in patients presenting within 90 minutes eliminated all significant overestimation cases.

TRIAL REGISTRATION INFORMATION

ClinicalTrials.gov: NCT03876457.

Multiphase CTA-derived tissue maps aid in detection of medium vessel occlusions

PURPOSE

Medium vessel occlusions (MeVOs) can be challenging to detect on imaging. Multiphase computed tomography angiography (mCTA) has been shown to improve large vessel occlusion (LVO) detection and endovascular treatment (EVT) selection. The aims of this study were to determine if mCTA-derived tissue maps can (1) accurately detect MeVOs and (2) predict infarction on 24-h follow-up imaging with comparable accuracy to CT perfusion (CTP).

METHODS

Two readers assessed mCTA tissue maps of 116 ischemic stroke patients (58 MeVOs, 58 non-MeVOs) and determined by consensus: (1) MeVO (yes/no) and (2) occlusion site, blinded to clinical or imaging data. Sensitivity, specificity, and area under the curve (AUC) for MeVO detection were estimated in comparison to reference standards of (1) expert readings of baseline mCTA and (2) CTP maps. Volumetric and spatial agreement between mCTA- and CTP-predicted infarcts was assessed using concordance/intraclass correlation and Dice coefficients. Interrater agreement for MeVO detection on mCTA tissue maps was estimated with Cohen's kappa.

RESULTS

MeVO detection from mCTA-derived tissue maps had a sensitivity of 91% (95% CI: 80-97), specificity of 82% (95% CI: 70-90), and AUC of 0.87 (95% CI: 0.80-0.93) compared to expert reads of baseline mCTA. Interrater reliability was good (0.72, 95% CI: 0.60-0.85). Compared to CTP maps, sensitivity was 87% (95% CI: 75-95), specificity was 78% (95%CI: 65-88), and AUC was 0.83 (95% CI: 0.76-0.90). The mean difference between mCTA- and CTP-predicted final infarct volume was 4.8 mL (limits of agreement: - 58.5 to 68.1) with a Dice coefficient of 33.5%.

CONCLUSION

mCTA tissue maps can be used to reliably detect MeVO stroke and predict tissue fate.

Predictive value of Tmax perfusion maps on final core in acute ischemic stroke: an observational single-center study

PURPOSE

To assess utility of computed tomography perfusion (CTP) protocols for selection of patients with acute ischemic stroke (AIS) for reperfusive treatments and compare the diagnostic accuracy (ACC) in predicting follow-up infarction, using time-to-maximum (Tmax) maps.

METHODS

We retrospectively reviewed consecutive AIS patients evaluated for reperfusive treatments at comprehensive stroke center, employing a multimodal computed tomography. To assess prognostic accuracy of CTP summary maps in predicting final infarct area (FIA) in AIS patients, we assumed the best correlation between non-viable tissue (NVT) and FIA in early and fully recanalized patients and/or in patients with favorable clinical response (FCR). On the other hand, the tissue at risk (TAR) should better correlate with FIA in untreated patients and in treatment failure.

RESULTS

We enrolled 158 patients, for which CTP maps with Tmax thresholds of 9.5 s and 16 s, presented sensitivity of 82.5%, specificity of 74.6%, and ACC of 75.9%. In patients selected for perfusion deficit in anterior circulation territory, CTP-Tmax > 16 s has proven relatively reliable to identify NVT in FCR patients, with a tendency to overestimate NVT. Similarly, CTP-Tmax > 9.5 s was reliable for TAR, but it was overestimated comparing to FIA, in patients with unfavorable outcomes.

CONCLUSIONS

In our experience, Tmax thresholds have proven sufficiently reliable to identify global hypoperfusion, with tendency to overestimate both NVT and TAR, not yielding satisfactory differentiation between true penumbra and benign oligoemia. In particular, the overestimation of NVT could have serious consequences in not selecting potential candidates for a reperfusion treatment.

Clinical Imaging of the Penumbra in Ischemic Stroke: From the Concept to the Era of Mechanical Thrombectomy

The ischemic penumbra is defined as the severely hypoperfused, functionally impaired, at-risk but not yet infarcted tissue that will be progressively recruited into the infarct core. Early reperfusion aims to save the ischemic penumbra by preventing infarct core expansion and is the mainstay of acute ischemic stroke therapy. Intravenous thrombolysis and mechanical thrombectomy for selected patients with large vessel occlusion has been shown to improve functional outcome. Given the varying speed of infarct core progression among individuals, a therapeutic window tailored to each patient has recently been proposed. Recent studies have demonstrated that reperfusion therapies are beneficial in patients with a persistent ischemic penumbra, beyond conventional time windows. As a result, mapping the penumbra has become crucial in emergency settings for guiding personalized therapy. The penumbra was first characterized as an area with a reduced cerebral blood flow, increased oxygen extraction fraction and preserved cerebral metabolic rate of oxygen using positron emission tomography (PET) with radiolabeled O₂. Because this imaging method is not feasible in an acute clinical setting, the magnetic resonance imaging (MRI) mismatch between perfusion-weighted imaging and diffusion-weighted imaging, as well as computed tomography perfusion have been proposed as surrogate markers to identify the penumbra in acute ischemic stroke patients. Transversal studies comparing PET and MRI or using longitudinal assessment of a limited sample of patients have been used to define perfusion thresholds. However, in the era of mechanical thrombectomy, these thresholds are debatable. Using various MRI methods, the original penumbra definition has recently gained a significant interest. The aim of this review is to provide an overview of the evolution of the ischemic penumbra imaging methods, including their respective strengths and limitations, as well as to map the current intellectual structure of the field using bibliometric analysis and explore future directions.

Acute stroke imaging selection for mechanical thrombectomy in the extended time window: is it time to go back to basics? A review of current evidence

Treatment with endovascular therapy in the extended time window for acute ischaemic stroke with large vessel occlusion involves stringent selection criteria based on the two landmark studies DAWN and DEFUSE3. Current protocols typically include the requirement of advanced perfusion imaging which may exclude a substantial proportion of patients from receiving a potentially effective therapy. Efforts to offer endovascular reperfusion therapies to all appropriate candidates may be facilitated by the use of simplified imaging selection paradigms with widely available basic imaging techniques, such as non-contrast CT and CT angiography. Currently available evidence from our literature review suggests that patients meeting simplified imaging selection criteria may benefit as much as those patients selected using advanced imaging techniques (CT perfusion or MRI) from endovascular therapy in the extended time window. A comprehensive understanding of the role of imaging in patient selection is critical to optimising access to endovascular therapy in the extended time window and improving outcomes in acute stroke. This article provides an overview on current developments and future directions in this emerging area.

Imaging as a Selection Tool for Thrombectomy in Acute Ischemic Stroke: Pathophysiologic Considerations

Large vessel occlusion (LVO) stroke represents a stroke subset associated with the highest morbidity and mortality. Multiple prospective randomized trials have shown that thrombectomy, alone or in conjunction with IV thrombolysis, is highly effective in reestablishing cerebral perfusion and improving clinical outcomes. In unselected patients and especially in patients with poor collaterals, the benefit of reperfusion therapy is exquisitely time sensitive; the earlier thrombectomy is started, the lower the likelihood of disability or death. Understanding both the pathophysiologic underpinnings and the modifying factors of this strong time-to-treatment effect demonstrated in numerous randomized clinical trials is important for implementation of intrahospital workflow measures to maximize time efficiency of thrombectomy. Reducing delays in reperfusion therapy initiation has become a priority in acute stroke care, and therefore a thorough understanding of the main systems-based factors responsible for these delays is critical. Because the time spent evaluating the patient in the emergency department, which typically includes neuroimaging studies performed in scanners remote from the angiography suite, represents the main source of delays in thrombectomy initiation, the direct to angiography (DTA) model has emerged as a means to substantially reduce treatment times and is being instituted at an increasing number of thrombectomy centers across the world. The aim of this report is to introduce DTA as an emerging stroke care paradigm for patients with suspicion of LVO stroke, review results from studies evaluating its feasibility and impact on outcomes, describe current barriers to its more widespread adoption, and propose potential solutions to overcoming these barriers.

Tissue outcome prediction in hyperacute ischemic stroke: Comparison of machine learning models

Machine Learning (ML) has been proposed for tissue fate prediction after acute ischemic stroke (AIS), with the aim to help treatment decision and patient management. We compared three different ML models to the clinical method based on diffusion-perfusion thresholding for the voxel-based prediction of final infarct, using a large MRI dataset obtained in a cohort of AIS patients prior to recanalization treatment. Baseline MRI (MRI₀), including diffusion-weighted sequence (DWI) and Tmax maps from perfusion-weighted sequence, and 24-hr follow-up MRI (MRI_24h) were retrospectively collected in consecutive 394 patients AIS patients (median age = 70 years; final infarct volume = 28mL). Manually segmented DWI_24h lesion was considered the final infarct. Gradient Boosting, Random Forests and U-Net were trained using DWI, apparent diffusion coefficient (ADC) and Tmax maps on MRI₀ as inputs to predict final infarct. Tissue outcome predictions were compared to final infarct using Dice score. Gradient Boosting had significantly better predictive performance (median [IQR] Dice Score as for median age, maybe you can replace the comma with an equal sign for consistency 0.53 [0.29-0.68]) than U-Net (0.48 [0.18-0.68]), Random Forests (0.51 [0.27-0.66]), and clinical thresholding method (0.45 [0.25-0.62]) (P < 0.001). In this benchmark of ML models for tissue outcome prediction in AIS, Gradient Boosting outperformed other ML models and clinical thresholding method and is thus promising for future decision-making.

Impact of Multiphase Computed Tomography Angiography for Endovascular Treatment Decision-Making on Outcomes in Patients with Acute Ischemic Stroke

BACKGROUND AND PURPOSE

Various imaging paradigms are used for endovascular treatment (EVT) decision-making and outcome estimation in acute ischemic stroke (AIS). We aim to compare how these imaging paradigms perform for EVT patient selection and outcome estimation.

METHODS

Prospective multi-center cohort study of patients with AIS symptoms with multi-phase computed tomography angiography (mCTA) and computed tomography perfusion (CTP) baseline imaging. mCTA-based EVT-eligibility was defined as presence of large vessel occlusion (LVO) and moderate-to-good collaterals on mCTA. CTP-based eligibility was defined as presence of LVO, ischemic core (defined on relative cerebral blood flow, absolute cerebral blood flow, and cerebral blood volume maps) <70 mL, mismatch-ratio >1.8, absolute mismatch >15 mL. EVT-eligibility and adjusted rates of good outcome (modified Rankin Scale 0-2) based on these imaging paradigms were compared.

RESULTS

Of 289/464 patients with LVO, 263 (91%) were EVT-eligible by mCTA-criteria versus 63 (22%), 19 (7%) and 103 (36%) by rCBF, aCBF, and CBV-CTP-criteria. CTP and mCTA-criteria were discordant in 40% to 53%. Estimated outcomes were best in patients who met both mCTA and CTP eligibility-criteria and were treated with EVT (62% to 87% good outcome). Patients eligible for EVT by mCTA-criteria and not by CTP-criteria receiving EVT achieved good outcome rates of 53% to 57%. Few patients met CTP-criteria and not mCTA-criteria for EVT.

CONCLUSIONS

Simpler imaging selection criteria that rely on little else than detection of the occluded blood vessel may be more sensitive and less specific, thus resulting in more patients being offered EVT and arguably benefiting from it.

Acute Stroke Imaging Research Roadmap IV: Imaging Selection and Outcomes in Acute Stroke Clinical Trials and Practice

BACKGROUND AND PURPOSE

The Stroke Treatment Academic Industry Roundtable (STAIR) sponsored an imaging session and workshop during the Stroke Treatment Academic Industry Roundtable XI via webinar on October 1 to 2, 2020, to develop consensus recommendations, particularly regarding optimal imaging at primary stroke centers.

METHODS

This forum brought together stroke neurologists, neuroradiologists, neuroimaging research scientists, members of the National Institute of Neurological Disorders and Stroke, industry representatives, and members of the US Food and Drug Administration to discuss imaging priorities in the light of developments in reperfusion therapies, particularly in an extended time window, and reinvigorated interest in brain cytoprotection trials.

RESULTS

The imaging session summarized and compared the imaging components of recent acute stroke trials and debated the optimal imaging strategy at primary stroke centers. The imaging workshop developed consensus recommendations for optimizing the acquisition, analysis, and interpretation of computed tomography and magnetic resonance acute stroke imaging, and also recommendations on imaging strategies for primary stroke centers.

CONCLUSIONS

Recent positive acute stroke clinical trials have extended the treatment window for reperfusion therapies using imaging selection. Achieving rapid and high-quality stroke imaging is therefore critical at both primary and comprehensive stroke centers. Recommendations for enhancing stroke imaging research are provided.

Perfusion Imaging and Clinical Outcome in Acute Ischemic Stroke with Large Core

OBJECTIVE

Mechanical thrombectomy (MT) is not recommended for acute stroke with large vessel occlusion (LVO) and a large volume of irreversibly injured tissue ("core"). Perfusion imaging may identify a subset of patients with large core who benefit from MT.

METHODS

We compared two cohorts of LVO-related patients with large core (>50 ml on diffusion-weighted-imaging or CT-perfusion using RAPID), available perfusion imaging, and treated within 6 hours from onset by either MT + Best Medical Management (BMM) in one prospective study, or BMM alone in the pre-MT era from a prospective registry. Primary outcome was 90-day modified Rankin Scale ≤2. We searched for an interaction between treatment group and amount of penumbra as estimated by the mismatch ratio (MMRatio = critical hypoperfusion/core volume).

RESULTS

Overall, 107 patients were included (56 MT + BMM and 51 BMM): Mean age was 68 ± 15 years, median core volume 99 ml (IQR: 72-131) and MMRatio 1.4 (IQR: 1.0-1.9). Baseline clinical and radiological variables were similar between the two groups, except for a higher intravenous thrombolysis rate in the BMM group. The MMRatio strongly modified the clinical outcome following MT (p_interaction  < 0.001 for continuous MMRatio); MT was associated with a higher rate of good outcome in patients with, but not in those without, MMRatio>1.2 (adjusted OR [95% CI] = 6.8 [1.7-27.0] vs 0.7 [0.1-6.2], respectively). Similar findings were present for MMRatio ≥1.8 in the subgroup with core ≥70 ml. Parenchymal hemorrhage on follow-up imaging was more frequent in the MT + BMM group regardless of the MMRatio.

INTERPRETATION

Perfusion imaging may help select which patients with large core should be considered for MT. Randomized studies are warranted. ANN NEUROL 2021.

Penumbra Consumption Rates Based on Time-to-Maximum Delay and Reperfusion Status: A Post Hoc Analysis of the DEFUSE 3 Trial

BACKGROUND AND PURPOSE

In patients with acute large vessel occlusion, the natural history of penumbral tissue based on perfusion time-to-maximum (T_max) delay is not well established in relation to late-window endovascular thrombectomy. In this study, we sought to evaluate penumbra consumption rates for T_max delays in patients with large vessel occlusion evaluated between 6 and 16 hours from last known normal.

METHODS

This is a post hoc analysis of the DEFUSE 3 trial (The Endovascular Therapy Following Imaging Evaluation for Ischemic Stroke), which included patients with an acute ischemic stroke due to anterior circulation occlusion within 6 to 16 hours of last known normal. The primary outcome is percentage penumbra consumption, defined as (24-hour magnetic resonance imaging infarct volume-baseline core infarct volume)/(T_max 6 or 10 s volume-baseline core volume). We stratified the cohort into 4 categories based on treatment modality and Thrombolysis in Cerebral Infarction (TICI score; untreated, TICI 0-2a, TICI 2b, and TICI3) and calculated penumbral consumption rates in each category.

RESULTS

We included 141 patients, among whom 68 were untreated. In the untreated versus TICI 3 patients, a median (interquartile range) of 53.7% (21.2%-87.7%) versus 5.3% (1.1%-14.6%) of penumbral tissue was consumed based on T_max >6 s (P<0.001). In the same comparison for T_max>10 s, we saw a difference of 165.4% (interquartile range, 56.1%-479.8%) versus 25.7% (interquartile range, 3.2%-72.1%; P<0.001). Significant differences were not demonstrated between untreated and TICI 0-2a patients for penumbral consumption based on T_max >6 s (P=0.52) or T_max >10 s (P=0.92).

CONCLUSIONS

Among extended window endovascular thrombectomy patients, T_max >10-s mismatch volume may comprise large volumes of salvageable tissue, whereas nearly half the T_max >6-s mismatch volume may remain viable in untreated patients at 24 hours.

The core/penumbra model: implications for acute stroke treatment and patient selection in 2021

Despite major advances in prevention, ischaemic stroke remains one of the leading causes of death and disability worldwide. After centuries of nihilism and decades of failed neuroprotection trials, the discovery, initially in non-human primates and subsequently in man, that ischaemic brain tissue termed the ischaemic penumbra can be salvaged from infarction up to and perhaps beyond 24 h after stroke onset has underpinned the development of highly efficient reperfusion therapies, namely intravenous thrombolysis and endovascular thrombectomy, which have revolutionized the management of the acute stroke patient. Animal experiments have documented that how long the penumbra can survive depends not only on time elapsed since arterial occlusion ('time is brain'), but also on how severely perfusion is reduced. Novel imaging techniques allowing the penumbra and the already irreversibly damaged core in the individual subject to be mapped have documented that the time course of core growth at the expense of the penumbra widely differs from patient to patient, and hence that individual physiology should be considered in addition to time since stroke onset for decision-making. This concept has been implemented to optimize patient selection in pivotal trials of reperfusion therapies beyond 3 h after stroke onset and is now routinely applied in clinical practice, using computed tomography or magnetic resonance imaging. The notion that, in order to be both efficient and harmless, treatment should be tailored to each patient's physiological characteristics represents a radical move towards precision medicine.

Controversies in Imaging of Patients with Acute Ischemic Stroke: AJR Expert Panel Narrative Review

The development of reperfusion therapies has profoundly impacted stroke care, initially with the advent of IV thrombolytic (IVT) treatment and, more recently, with the development and refinement of endovascular treatment (EVT). Progress in neuroimaging has supported the paradigm shift of stroke care, and advanced neuroimaging now has a fundamental role in triaging patients for both IVT and EVT. As the standard of care for acute ischemic stroke (AIS) evolves, controversies remain in certain clinical scenarios. This article explores the use of multimodality imaging for treatment selection of AIS in the context of recent guidelines, highlighting controversial topics and providing guidance for clinical practice. Results of major randomized trials supporting EVT are reviewed. Advantages and disadvantages of CT, CTA, MRI, and MRA in stroke diagnosis are summarized, with attention to level 1 evidence supporting the role of vascular imaging and perfusion imaging. Patient selection is compared between approaches based on time thresholds and physiologic approaches based on infarct core measurement using imaging. Moreover, various imaging approaches to core measurement are described. As ongoing studies push treatment boundaries, advanced imaging is expected to help identify a widening range of patients who may benefit from therapy.

Tissue at Risk and Ischemic Core Estimation Using Deep Learning in Acute Stroke

BACKGROUND AND PURPOSE

In acute stroke patients with large vessel occlusions, it would be helpful to be able to predict the difference in the size and location of the final infarct based on the outcome of reperfusion therapy. Our aim was to demonstrate the value of deep learning-based tissue at risk and ischemic core estimation. We trained deep learning models using a baseline MR image in 3 multicenter trials.

MATERIALS AND METHODS

Patients with acute ischemic stroke from 3 multicenter trials were identified and grouped into minimal (≤20%), partial (20%-80%), and major (≥80%) reperfusion status based on 4- to 24-hour follow-up MR imaging if available or into unknown status if not. Attention-gated convolutional neural networks were trained with admission imaging as input and the final infarct as ground truth. We explored 3 approaches: 1) separate: train 2 independent models with patients with minimal and major reperfusion; 2) pretraining: develop a single model using patients with partial and unknown reperfusion, then fine-tune it to create 2 separate models for minimal and major reperfusion; and 3) thresholding: use the current clinical method relying on apparent diffusion coefficient and time-to-maximum of the residue function maps. Models were evaluated using area under the curve, the Dice score coefficient, and lesion volume difference.

RESULTS

Two hundred thirty-seven patients were included (minimal, major, partial, and unknown reperfusion: n = 52, 80, 57, and 48, respectively). The pretraining approach achieved the highest median Dice score coefficient (tissue at risk = 0.60, interquartile range, 0.43-0.70; core = 0.57, interquartile range, 0.30-0.69). This was higher than the separate approach (tissue at risk = 0.55; interquartile range, 0.41-0.69; P = .01; core = 0.49; interquartile range, 0.35-0.66; P = .04) or thresholding (tissue at risk = 0.56; interquartile range, 0.42-0.65; P = .008; core = 0.46; interquartile range, 0.16-0.54; P < .001).

CONCLUSIONS

Deep learning models with fine-tuning lead to better performance for predicting tissue at risk and ischemic core, outperforming conventional thresholding methods.

Automated Prediction of Ischemic Brain Tissue Fate from Multiphase Computed Tomographic Angiography in Patients with Acute Ischemic Stroke Using Machine Learning

Background and Purpose

Multiphase computed tomographic angiography (mCTA) provides time variant images of pial vasculature supplying brain in patients with acute ischemic stroke (AIS). To develop a machine learning (ML) technique to predict tissue perfusion and infarction from mCTA source images.

Methods

284 patients with AIS were included from the Precise and Rapid assessment of collaterals using multi-phase CTA in the triage of patients with acute ischemic stroke for Intra-artery Therapy (Prove-IT) study. All patients had non-contrast computed tomography, mCTA, and computed tomographic perfusion (CTP) at baseline and follow-up magnetic resonance imaging/non-contrast-enhanced computed tomography. Of the 284 patient images, 140 patient images were randomly selected to train and validate three ML models to predict a pre-defined Tmax thresholded perfusion abnormality, core and penumbra on CTP. The remaining 144 patient images were used to test the ML models. The predicted perfusion, core and penumbra lesions from ML models were compared to CTP perfusion lesion and to follow-up infarct using Bland-Altman plots, concordance correlation coefficient (CCC), intra-class correlation coefficient (ICC), and Dice similarity coefficient.

Results

Mean difference between the mCTA predicted perfusion volume and CTP perfusion volume was 4.6 mL (limit of agreement [LoA], –53 to 62.1 mL; P=0.56; CCC 0.63 [95% confidence interval [CI], 0.53 to 0.71; P<0.01], ICC 0.68 [95% CI, 0.58 to 0.78; P<0.001]). Mean difference between the mCTA predicted infarct and follow-up infarct in the 100 patients with acute reperfusion (modified thrombolysis in cerebral infarction [mTICI] 2b/2c/3) was 21.7 mL, while it was 3.4 mL in the 44 patients not achieving reperfusion (mTICI 0/1). Amongst reperfused subjects, CCC was 0.4 (95% CI, 0.15 to 0.55; P<0.01) and ICC was 0.42 (95% CI, 0.18 to 0.50; P<0.01); in non-reperfused subjects CCC was 0.52 (95% CI, 0.20 to 0.60; P<0.001) and ICC was 0.60 (95% CI, 0.37 to 0.76; P<0.001). No difference was observed between the mCTA and CTP predicted infarct volume in the test cohort (P=0.67).

Conclusions

A ML based mCTA model is able to predict brain tissue perfusion abnormality and follow-up infarction, comparable to CTP.

Management of Acute Ischemic Stroke

Objectives:

Concise “synthetic” review of the state of the art of management of acute ischemic stroke.

Data Sources:

Available literature on PubMed.

Study Selection:

We selected landmark studies, recent clinical trials, observational studies, and professional guidelines on the management of stroke including the last 10 years.

Data Extraction:

Eligible studies were identified and results leading to guideline recommendations were summarized.

Data Synthesis:

Stroke mortality has been declining over the past 6 decades, and as a result, stroke has fallen from the second to the fifth leading cause of death in the United States. This trend may follow recent advances in the management of stroke, which highlight the importance of early recognition and early revascularization. Recent studies have shown that early recognition, emergency interventional treatment of acute ischemic stroke, and treatment in dedicated stroke centers can significantly reduce stroke-related morbidity and mortality. However, stroke remains the second leading cause of death worldwide and the number one cause for acquired long-term disability, resulting in a global annual economic burden.

Conclusions:

Appropriate treatment of ischemic stroke is essential in the reduction of mortality and morbidity. Management of stroke involves a multidisciplinary approach that starts and extends beyond hospital admission.

Ischemic Core Overestimation on Computed Tomography Perfusion

[Figure: see text].

Integrating regional perfusion CT information to improve prediction of infarction after stroke

Physiological evidence suggests that neighboring brain regions have similar perfusion characteristics (vascular supply, collateral blood flow). It is largely unknown whether integrating perfusion CT (pCT) information from the area surrounding a given voxel (i.e. the receptive field (RF)) improves the prediction of infarction of this voxel. Based on general linear regression models (GLMs) and using acute pCT-derived maps, we compared the added value of cuboid RF to predict the final infarct. To this aim, we included 144 stroke patients with acute pCT and follow-up MRI, used to delineate the final infarct. Overall, the performance of GLMs to predict the final infarct improved when using RF for all pCT maps (cerebral blood flow, cerebral blood volume, mean transit time and time-to-maximum of the tissue residual function (Tmax)). The highest performance was obtained with Tmax (glm(Tmax); AUC = 0.89 ± 0.03 with RF vs. 0.78 ± 0.02 without RF; p < 0.001) and with a model combining all perfusion parameters (glm(multi); AUC 0.89 ± 0.02 with RF vs. 0.79 ± 0.02 without RF; p < 0.001). These results suggest that prediction of infarction improves by integrating perfusion information from adjacent tissue. This approach may be applied in future studies to better identify ischemic core and penumbra thresholds and improve patient selection for acute stroke treatment.

Advances in imaging acute ischemic stroke: evaluation before thrombectomy

Recent advances in neuroimaging have demonstrated significant assessment benefits and appropriate triage of patients based on specific clinical and radiological features in the acute stroke setting. Endovascular thrombectomy is arguably the most important aspect of acute stroke management with an extended time window. Imaging-based physiological information may potentially shift the treatment paradigm from a rigid time-based model to a more flexible and individualized, tissue-based approach, increasing the proportion of patients amenable to treatment. Various imaging modalities are routinely used in the diagnosis and management of acute ischemic stroke, including multimodal computed tomography (CT) and magnetic resonance imaging (MRI). Therefore, these imaging methods should provide information beyond the presence or absence of intracranial hemorrhage as well as the presence and extent of the ischemic core, collateral circulation and penumbra in patients with neurological symptoms. Target mismatch may optimize selection of patients with late or unknown symptom onset who would potentially be eligible for revascularization therapy. The purpose of this study was to provide a comprehensive review of the current evidence about efficacy and theoretical basis of present imaging modalities, and explores future directions for imaging in the management of acute ischemic stroke.

Comparison of a Bayesian estimation algorithm and singular value decomposition algorithms for 80-detector row CT perfusion in patients with acute ischemic stroke

PURPOSE

A variety of postprocessing algorithms for CT perfusion are available, with substantial differences in terms of quantitative maps. Although potential advantages of a Bayesian estimation algorithm are suggested, direct comparison with other algorithms in clinical settings remains scarce. We aimed to compare performance of a Bayesian estimation algorithm and singular value decomposition (SVD) algorithms for the assessment of acute ischemic stroke using an 80-detector row CT perfusion.

METHODS

CT perfusion data of 36 patients with acute ischemic stroke were analyzed using the Vitrea implemented a standard SVD algorithm, a reformulated SVD algorithm and a Bayesian estimation algorithm. Correlations and statistical differences between affected and contralateral sides of quantitative parameters (cerebral blood volume [CBV], cerebral blood flow [CBF], mean transit time [MTT], time to peak [TTP] and delay) were analyzed. Agreement of the CT perfusion-estimated and the follow-up diffusion-weighted imaging-derived infarct volume were evaluated by nonparametric Passing-Bablok regression analysis.

RESULTS

CBF and MTT of the Bayesian estimation algorithm were substantially different and showed a better correlation with the standard SVD algorithm (ρ = 0.78 and 0.80, p < 0.001) than with the reformulated SVD algorithm (ρ = 0.59 and 0.39, p < 0.001). There is no significant difference in MTT only when using the reformulated SVD algorithm (p = 0.217). Regarding the regression lines, the slope and intercept were nearly ideal with the Bayesian estimation algorithm (y = 2.42 x-6.51; ρ = 0.60, p < 0.001) in comparison with the SVD algorithms.

CONCLUSIONS

The Bayesian estimation algorithm can lead to a better performance compared with the SVD algorithms in the assessment of acute ischemic stroke because of better delineation of abnormal perfusion areas and accurate estimation of infarct volume.

Role of Favorable Perfusion Imaging in Predicting the Outcome of Patients with Acute Ischemic Stroke due to Large Vessel Occlusion Undergoing Effective Thrombectomy: A Single-Center Study

Introduction

We sought to verify the predicting role of a favorable profile on computed tomography perfusion (CTP) in the outcome of patients with acute ischemic stroke (AIS) due to large vessel occlusion (LVO) undergoing effective mechanical thrombectomy (MT).

Methods

We retrospectively enrolled 25 patients with AIS due to LVO and with a CTP study showing the presence of ischemic penumbra who underwent effective MT, regardless of the time of onset. The controls were 25 AIS patients with overlapping demographics and clinical and computed tomography angiography features at admission who had undergone successful MT within 6 h from onset and without a previous CTP study. The outcome measure was the modified Rankin Scale (mRS) score at 90 days.

Results

Sixty-four percent of the study patients had an mRS score of 0–1 at 90 days versus 12% of the control patients (p < 0.001). Patients of the study group had a more favorable distribution of disability scores (median mRS [IQR] score of 0 [0–2] vs. 2 [2–3]). Multivariate analysis showed that the selection of patients based on a favorable CTP study was strongly associated (p < 0.001) with a better neurological outcome.

Conclusions

In our small-sized and retrospective study, the presence of ischemic penumbra was associated with a better clinical outcome in patients with AIS due to LVO after MT. In the future, a larger and controlled study with similar criteria of enrollment is needed to further validate the role of CTP in patient selection for MT, regardless of the time from the onset of symptoms.

Rapid Treatment of Acute Ischemic Stroke Using a Computed Tomography-Based Reperfusion Protocol: The Reality of a Local Community Hospital with Limited Resources

Objective

In patients with acute ischemic stroke (AIS), prognosis strongly depends on the onset-to-recanalization time. The Ishinomaki protocol for rapid recanalization has been used since October 2017. This protocol determines the indication for reperfusion therapy based on computed tomography (CT)/three-dimensional CT angiography (3DCTA) findings and intends to reduce the onset-to-recanalization time. We aimed to compare the outcomes before and after protocol introduction.

Methods

Our hospital is the only thrombectomy-capable center in Ishinomaki, Tome, and Kesennuma medical area. Before protocol introduction (April 2014-June 2016), both CT and magnetic resonance imaging were performed to determine the indications for intravenous (IV) recombinant tissue-plasminogen activator (rt-PA) or mechanical thrombectomy within 6 hours of disease onset. However, after protocol introduction (from October 2017), plain CT and 3DCTA were used. We collected data on patients who underwent mechanical thrombectomy and/or IV rt-PA before (n = 13) and after (n = 34) the protocol introduction. The required time from onset to door (OTD), door to needle (DTN), needle to puncture (NTP), puncture to recanalization (PTR), and door to recanalization (DTR) were compared before and after protocol introduction. Furthermore, thrombolysis in cerebral infarction (TICI) grades and modified Rankin scale (mRS) scores at discharge were compared.

Results

The outcomes before and after protocol introduction were as follows: OTD: 105 ± 73.8 (mean ± standard deviation) vs. 120 ± 68.1 min (p = 0.376, Mann-Whitney U test); DTN: 62.9 ± 15.9 vs. 41 ± 17 min (p <0.01); NTP: 112 ± 69.8 vs. 39.9 ± 33.7 min (p <0.01); PTR: 87.9 ± 45.4 vs. 52.5 ± 27.9 min (p <0.01); and DTR, 230 ± 69.9 vs. 110 ± 40.3 min (p <0.0001). Before and after protocol introduction, the proportion of patients with TICI grade 2b-3, mRS score of 0-2 at discharge, and mRS score of 5-6 were 54% vs. 50% (p = 0.815, Fisher's exact test), 23% vs. 21% (p = 0.854), and 15% vs. 50% (p = 0.046), respectively.

Conclusion

The Ishinomaki protocol reduced the mean DTR time by 120 min. The reduction in treatment time was due to the change in CT-based recanalization and collaboration with emergency physicians and paramedics. There was no increase in good outcomes, but there was a significant increase in poor outcomes at discharge. Patients who could not be salvaged were indicated for reperfusion therapy as CT and 3DCTA cannot detect the ischemic core.

Neuroimaging in Acute Stroke

PURPOSE OF REVIEW

This article describes how imaging can be used by physicians in diagnosing, determining prognosis, and making appropriate treatment decisions in a timely manner in patients with acute stroke.

RECENT FINDINGS

Advances in acute stroke treatment, including the use of endovascular thrombectomy in patients with large vessel occlusion and, more recently, of IV thrombolysis in an extended time window, have resulted in a paradigm shift in how imaging is used in patients with acute stroke. This paradigm shift, combined with the understanding that "time is brain," means that imaging must be fast, reliable, and available around the clock for physicians to make appropriate clinical decisions. CT has therefore become the primary imaging modality of choice. Recognition of a large vessel occlusion using CT angiography has become essential in identifying patients for endovascular thrombectomy, and techniques such as imaging collaterals on CT angiography or measuring blood flow to predict tissue fate using CT perfusion have become useful tools in selecting patients for acute stroke therapy. Understanding the use of these imaging modalities and techniques in dealing with an emergency such as acute stroke has therefore become more important than ever for physicians treating patients with acute stroke.

SUMMARY

Imaging the brain and the blood vessels supplying it using modern tools and techniques is a key step in understanding the pathophysiology of acute stroke and making appropriate and timely clinical decisions.

Computed Tomography Perfusion-Based Machine Learning Model Better Predicts Follow-Up Infarction in Patients With Acute Ischemic Stroke

BACKGROUND AND PURPOSE

Prediction of infarct extent among patients with acute ischemic stroke using computed tomography perfusion is defined by predefined discrete computed tomography perfusion thresholds. Our objective is to develop a threshold-free computed tomography perfusion-based machine learning (ML) model to predict follow-up infarct in patients with acute ischemic stroke.

METHODS

Sixty-eight patients from the PRoveIT study (Measuring Collaterals With Multi-Phase CT Angiography in Patients With Ischemic Stroke) were used to derive a ML model using random forest to predict follow-up infarction voxel by voxel, and 137 patients from the HERMES study (Highly Effective Reperfusion Evaluated in Multiple Endovascular Stroke Trials) were used to test the derived ML model. Average map, T_max, cerebral blood flow, cerebral blood volume, and time variables including stroke onset-to-imaging and imaging-to-reperfusion time, were used as features to train the ML model. Spatial and volumetric agreement between the ML model predicted follow-up infarct and actual follow-up infarct were assessed. Relative cerebral blood flow <0.3 threshold using RAPID software and time-dependent T_max thresholds were compared with the ML model.

RESULTS

In the test cohort (137 patients), median follow-up infarct volume predicted by the ML model was 30.9 mL (interquartile range, 16.4-54.3 mL), compared with a median 29.6 mL (interquartile range, 11.1-70.9 mL) of actual follow-up infarct volume. The Pearson correlation coefficient between 2 measurements was 0.80 (95% CI, 0.74-0.86, P<0.001) while the volumetric difference was -3.2 mL (interquartile range, -16.7 to 6.1 mL). Volumetric difference with the ML model was smaller versus the relative cerebral blood flow <0.3 threshold and the time-dependent T_max threshold (P<0.001).

CONCLUSIONS

A ML using computed tomography perfusion data and time estimates follow-up infarction in patients with acute ischemic stroke better than current methods.

The ischemic penumbra: From concept to reality

The discovery that brain tissue could potentially be salvaged from ischaemia due to stroke, has led to major advances in the development of therapies for ischemic stroke. In this review, we detail the advances in the understanding of this area termed the ischaemic penumbra, from its discovery to the evolution of imaging techniques, and finally some of the treatments developed. Evolving from animal studies from the 70s and 80s and translated to clinical practice, the field of ischemic reperfusion therapy has largely been guided by an array of imaging techniques developed to positively identify the ischemic penumbra, including positron emission tomography, computed tomography and magnetic resonance imaging. More recently, numerous penumbral identification imaging studies have allowed for a better understanding of the progression of the ischaemic core at the expense of the penumbra, and identification of patients than can benefit from reperfusion therapies in the acute phase. Importantly, 40 years of critical imaging research on the ischaemic penumbra have allowed for considerable extension of the treatment time window and better patient selection for reperfusion therapy. The translation of the penumbra concept into routine clinical practice has shown that "tissue is at least as important as time."

Defining reperfusion post endovascular therapy in ischemic stroke using MR-dynamic contrast enhanced perfusion

OBJECTIVES

Cerebral blood flow (CBF) measurements after endovascular therapy (EVT) for acute ischemic stroke are important to distinguish early secondary injury related to persisting ischemia from that related to reperfusion when considering clinical response and infarct growth.

METHODS

We compare reperfusion quantified by the modified Thrombolysis in Cerebral Infarction Score (mTICI) with perfusion measured by MRI dynamic contrast-enhanced perfusion within 5 h of EVT anterior circulation stroke. MR perfusion (rCBF, rCBV, rTmax, rT0) and mTICI scores were included in a predictive model for change in NIHSS at 24 h and diffusion-weighted imaging (DWI) lesion growth (acute to 24 h MRI) using a machine learning RRELIEFF feature selection coupled with a support vector regression.

RESULTS

For all perfusion parameters, mean values within the acute infarct for the TICI-2b group (considered clinically good reperfusion) were not significantly different from those in the mTICI <2b (clinically poor reperfusion). However, there was a statistically significant difference in perfusion values within the acute infarct region of interest between the mTICI-3 group versus both mTICI-2b and <2b (p = 0.02). The features that made up the best predictive model for change in NIHSS and absolute DWI lesion volume change was rT0 within acute infarct ROI and admission CTA collaterals respectively. No other variables, including mTICI scores, were selected for these best models. The correlation coefficients (Root mean squared error) for the cross-validation were 0.47 (13.7) and 0.51 (5.7) for change in NIHSS and absolute DWI lesion volume change.

CONCLUSION

MR perfusion following EVT provides accurate physiological approach to understanding the relationship of CBF, clinical outcome, and DWI growth.

ADVANCES IN KNOWLEDGE

MR perfusion CBF acquired is a robust, objective reperfusion measurement providing following recanalization of the target occlusion which is critical to distinguish potential therapeutic harm from the failed technical success of EVT as well as improve the responsiveness of clinical trial outcomes to disease modification.

Localized prediction of tissue outcome in acute ischemic stroke patients using diffusion- and perfusion-weighted MRI datasets

BACKGROUND

An accurate prediction of tissue outcome in acute ischemic stroke patients is of high interest for treatment decision making. To date, various machine learning models have been proposed that combine multi-parametric imaging data for this purpose. However, most of these machine learning models were trained using voxel information extracted from the whole brain, without taking differences in susceptibility to ischemia into account that exist between brain regions. The aim of this study was to develop and evaluate a local tissue outcome prediction approach, which makes predictions using locally trained machine learning models and thus accounts for regional differences.

MATERIAL AND METHODS

Multi-parametric MRI data from 99 acute ischemic stroke patients were used for the development and evaluation of the local tissue outcome prediction approach. Diffusion (ADC) and perfusion parameter maps (CBF, CBV, MTT, Tmax) and corresponding follow-up lesion masks for each patient were registered to the MNI brain atlas. Logistic regression (LR) and random forest (RF) models were trained employing a local approach, which makes predictions using models individually trained for each specific voxel position using the corresponding local data. A global approach, which uses a single model trained using all voxels of the brain, was used for comparison. Tissue outcome predictions resulting from the global and local RF and LR models, as well as a combined (hybrid) approach were quantitatively evaluated and compared using the area under the receiver operating characteristic curve (ROC AUC), the Dice coefficient, and the sensitivity and specificity metrics.

RESULTS

Statistical analysis revealed the highest ROC AUC and Dice values for the hybrid approach. With 0.872 (ROC AUC; LR) and 0.353 (Dice; RF), these values were significantly higher (p < 0.01) than the values of the two other approaches. In addition, the local approach achieved the highest sensitivity of 0.448 (LR). Overall, the hybrid approach was only outperformed in sensitivity (LR) by the local approach and in specificity by both other approaches. However, in these cases the effect sizes were comparatively small.

CONCLUSION

The results of this study suggest that using locally trained machine learning models can lead to better lesion outcome prediction results compared to a single global machine learning model trained using all voxel information independent of the location in the brain.

Real-World Comparison of Human and Software Image Assessment in Acute Ischemic Stroke Patients' Qualification for Reperfusion Treatment

Our aim was to compare human and computer accuracy in reading medical images of acute stroke patients. We analyzed data of patients who underwent assessment of Alberta Stroke Program Early CT Score (ASPECTS) and CT Perfusion (CTP) via Rapid Processing of Perfusion and Diffusion (RAPID) software RAPID ASPECTS, and RAPID CTP), compared to radiologist reports and manual measurements. We compared volumes calculated by RAPID CTP software with those selected by scanner-equipped software (GE). For reference, follow-up images were manually assessed in accordance with the Alberta Stroke Program Early CT Score (ASPECTS) territories retrospectively. Although exact ASPECTS score agreement between the automatic and manual methods, and between each method and follow-up, was poor, crossing of the threshold for reperfusion therapy was characterized by an 80% match. CT perfusion analyses yielded only slight agreement (kappa = 0.193) in the qualification of patients for therapy. Either automatic or manual scoring methods of non-contrast images imply similar clinical decisions in real-world circumstances. However, volume measurements performed by fully automatic and manually assisted systems are not comparable. Thresholds devised and validated for computer algorithms are not compatible with measurements performed manually using other software and should not be applied to setups other than those with which they were developed.

Perfusion Parameter Thresholds That Discriminate Ischemic Core Vary with Time from Onset in Acute Ischemic Stroke

BACKGROUND AND PURPOSE

When mapping the ischemic core and penumbra in patients with acute ischemic stroke using perfusion imaging, the core is currently delineated by applying the same threshold value for relative CBF at all time points from onset to imaging. We investigated whether the degree of perfusion abnormality and optimal perfusion parameter thresholds for defining ischemic core vary with time from onset to imaging.

MATERIALS AND METHODS

In a prospectively maintained registry, consecutive patients were analyzed who had ICA or M1 occlusion, baseline perfusion and diffusion MR imaging, treatment with IV tPA and/or endovascular thrombectomy, and a witnessed, well-documented time of onset. Ten superficial and deep MCA ROIs were analyzed in ADC and perfusion-weighted images.

RESULTS

Among the 66 patients meeting entry criteria, onset-to-imaging time was 162 minutes (range, 94-326 minutes). Of the 660 ROIs analyzed, 164 (24.8%) showed severely or moderately reduced ADC (ADC ≤ 620, ischemic core), and 496 (75.2%), mildly reduced or normal ADC (ADC  > 620). In ischemic core ADC regions, longer onset-to-imaging times were associated with more highly abnormal perfusion parameters-relative CBF: Spearman correlation, r = -0.22, P = .005; relative CBV: r = -0.41, P < .001; MTT: - r = -0.29, P < .001; and time-to-maximum: r = 0.35, P < .001. As onset-to-imaging times increased, the best cutoff values for relative CBF and relative CBV to discriminate core from noncore tissue became progressively lower and overall accuracy of the core tissue definition increased.

CONCLUSIONS

Perfusion abnormalities in ischemic core regions become progressively more abnormal with longer intervals from onset to imaging. Perfusion parameter value thresholds that best delineate ischemic core are more severely abnormal and have higher accuracy with longer onset-to-imaging times.

Dynamic CTA-Derived Perfusion Maps Predict Final Infarct Volume: The Simple Perfusion Reconstruction Algorithm

BACKGROUND AND PURPOSE

Infarct core volume measurement using CTP (CT perfusion) is a mainstay paradigm for stroke treatment decision-making. Yet, there are several downfalls with cine CTP technology that can be overcome by adopting the simple perfusion reconstruction algorithm (SPIRAL) derived from multiphase CTA. We compare SPIRAL with CTP parameters for the prediction of 24-hour infarction.

MATERIALS AND METHODS

Seventy-two patients had admission NCCT, multiphase CTA, CTP, and 24-hour DWI. All patients had successful/quality reperfusion. Patient-level and cohort-level receiver operator characteristic curves were generated to determine accuracy. A 10-fold cross-validation was performed on the cohort-level data. Infarct core volume was compared for SPIRAL, CTP-time-to-maximum, and final DWI by Bland-Altman analysis.

RESULTS

When we compared the accuracy in patients with early and late reperfusion for cortical GM and WM, there was no significant difference at the patient level (0.83 versus 0.84, respectively), cohort level (0.82 versus 0.81, respectively), or the cross-validation (0.77 versus 0.74, respectively). In the patient-level receiver operating characteristic analysis, the SPIRAL map had a slightly higher, though nonsignificant (P < .05), average receiver operating characteristic area under the curve (cortical GM/WM, r = 0.82; basal ganglia  = 0.79, respectively) than both the CTP-time-to-maximum (cortical GM/WM = 0.82; basal ganglia = 0.78, respectively) and CTP-CBF (cortical GM/WM = 0.74; basal ganglia = 0.78, respectively) parameter maps. The same relationship was observed at the cohort level. The Bland-Altman plot limits of agreement for SPIRAL and time-to-maximum infarct volume were similar compared with 24-hour DWI.

CONCLUSIONS

We have shown that perfusion maps generated from a temporally sampled helical CTA are an accurate surrogate for infarct core.