Value of Quantitative Collateral Scoring on CT Angiography in Patients with Acute Ischemic Stroke

Rapid identification and prognosis evaluation by dual-phase computed tomography angiography for stroke patients with a large ischemic region in the anterior circulation treated with endovascular thrombectomy

Purpose

To investigate the value of dual-phase head-and-neck computed tomography angiography (CTA) in assessing advantages and risks associated with mechanical thrombectomy for stroke with a large ischemic region in the anterior circulation within 6 h of onset.

Methods

We retrospectively analyzed the data of patients with acute occlusion of the internal carotid artery or middle cerebral artery-M1 segment. Baseline dual-phase CTA was performed for collateral grading using the 4-point visual collateral score (0, 0% filling; 1, >0% and ≤50% filling; 2, >50 and <100% filling; 3, 100% filling). The rates of modified Rankin score (MRS) ≤ 3 at 90 days, any intracranial hemorrhage (ICH) within 48 h, malignant cerebral edema within 24 h, and all-cause 90-day mortality were analyzed.

Results

Among the 69 study patients, 15, 26, 17, and 11 patients had collateral grades of 0, 1, 2, and 3, respectively. At 90 days, the MRS was ≤3 in 0, 8.33, 29.41, and 36.36% of patients with grades 0, 1, 2, and 3, respectively. ICH incidence was 73.33, 57.69, 29.41, and 18.18% for grades 0, 1, 2, and 3, respectively, while the incidence of malignant brain edema was 100, 76.92, 35.29, and 0%, respectively. All-cause 90-day mortality was 53.33% for grade 0 and 30.77% for grade 1; no deaths occurred at grades 2 and 3.

Conclusion

Collateral grading based on dual-phase CTA enables simple and rapid preoperative evaluation prior to mechanical thrombectomy for acute anterior-circulation stroke with a large ischemic focus, particularly for patients presenting within the 6-h time window.

Siamese model for collateral score prediction from computed tomography angiography images in acute ischemic stroke

Introduction

Imaging biomarkers, such as the collateral score as determined from Computed Tomography Angiography (CTA) images, play a role in treatment decision making for acute stroke patients. In this manuscript, we present an end-to-end learning approach for automatic determination of a collateral score from a CTA image. Our aim was to investigate whether such end-to-end learning approaches can be used for this classification task, and whether the resulting classification can be used in existing outcome prediction models.

Methods

The method consists of a preprocessing step, where the CTA image is aligned to an atlas and divided in the two hemispheres: the affected side and the healthy side. Subsequently, a VoxResNet based convolutional neural network is used to extract features at various resolutions from the input images. This is done by using a Siamese model, such that the classification is driven by the comparison between the affected and healthy using a unique set of features for both hemispheres. After masking the resulting features for both sides with the vascular region and global average pooling (per hemisphere) and concatenation of the resulting features, a fully connected layer is used to determine the categorized collateral score.

Experiments

Several experiments have been performed to optimize the model hyperparameters and training procedure, and to validate the final model performance. The hyperparameter optimization and subsequent model training was done using CTA images from the MR CLEAN Registry, a Dutch multi-center multi-vendor registry of acute stroke patients that underwent endovascular treatment. A separate set of images, from the MR CLEAN Trial, served as an external validation set, where collateral scoring was assessed and compared with both human observers and a recent more traditional model. In addition, the automated collateral scores have been used in an existing functional outcome prediction model that uses both imaging and non-imaging clinical parameters.

Conclusion

The results show that end-to-end learning of collateral scoring in CTA images is feasible, and does perform similar to more traditional methods, and the performance also is within the inter-observer variation. Furthermore, the results demonstrate that the end-to-end classification results also can be used in an existing functional outcome prediction model.

MRI-based parameter inference for cerebral perfusion modelling in health and ischaemic stroke

Cerebral perfusion modelling is a promising tool to predict the impact of acute ischaemic stroke treatments on the spatial distribution of cerebral blood flow (CBF) in the human brain. To estimate treatment efficacy based on CBF, perfusion simulations need to become suitable for group-level investigations and thus account for physiological variability between individuals. However, computational perfusion modelling to date has been restricted to a few patient-specific cases. This study set out to establish automated parameter inference for perfusion modelling based on neuroimaging data and thus enable CBF simulations of groups. Magnetic resonance imaging (MRI) data from 75 healthy senior adults were utilised. Brain geometries were computed from healthy reference subjects' T1-weighted MRI. Haemodynamic model parameters were determined from spatial CBF maps measured by arterial spin labelling (ASL) perfusion MRI. Thereafter, perfusion simulations were conducted in 75 healthy cases followed by 150 acute ischaemic stroke cases representing an occlusion and CBF cessation in the left and right middle cerebral arteries. The anatomical fitness of the brain geometries was evaluated by comparing the simulated grey (GM) and white matter (WM) volumes to measurements in healthy reference subjects. Strong positive correlations were found in both tissue types (GM: Pearson's r 0.74, P<0.001; WM: Pearson's r 0.84, P<0.001). Haemodynamic parameter tuning was verified by comparing the total volumetric blood flow rate to the brain in healthy reference subjects and simulations (Pearson's r 0.89, P<0.001). In acute ischaemic stroke cases, the simulated infarct volume using a perfusion-based estimate was 197±25 ml. Computational predictions were in agreement with anatomical and haemodynamic values from the literature concerning T1-weighted, T2-weighted, and phase-contrast MRI measurements in healthy scenarios and acute ischaemic stroke cases. The acute stroke simulations did not capture small infarcts (left tail of the distribution), which could be explained by neglected compensatory mechanisms, e.g. collaterals. The proposed parameter inference method provides a foundation for group-level CBF simulations and for in silico clinical stroke trials which could assist in medical device and drug development.

Pivotal role of multiphase computed tomography angiography for collateral assessment in patients with acute ischemic stroke

The cerebral collateral circulation is the main compensatory mechanism that maintains the ischemic penumbra viable, the tissue at risk for infarction that can be saved if blood flow is restored by reperfusion therapies. In clinical practice, the extent of collateral vessels recruited after vessel occlusion can be easily assessed with computed tomography angiography (CTA) using two different techniques: single-phase CTA (sCTA) and multi-phase CTA (mCTA). Both these methodologies have demonstrated a high prognostic predictive value for prognosis due to the strong association between the presence of good collaterals and favorable radiological and clinical outcomes in patients with acute ischemic stroke (AIS). However, mCTA seems to be superior to sCTA in the evaluation of collaterals and a promising tool for identifying AIS patients who can benefit from reperfusion therapies. In particular, it has recently been proposed the use of mCTA eligibility criteria has been recently proposed for the selection of AIS patients suitable for endovascular treatment instead of the current accepted criteria based on CT perfusion. In this review, we analyzed the characteristics, advantages and disadvantages of sCTA and mCTA to better understand their fields of application and the potential of mCTA in becoming the method of choice to assess collateral extent in AIS patients.

Automated LVO detection and collateral scoring on CTA using a 3D self-configuring object detection network: a multi-center study

The use of deep learning (DL) techniques for automated diagnosis of large vessel occlusion (LVO) and collateral scoring on computed tomography angiography (CTA) is gaining attention. In this study, a state-of-the-art self-configuring object detection network called nnDetection was used to detect LVO and assess collateralization on CTA scans using a multi-task 3D object detection approach. The model was trained on single-phase CTA scans of 2425 patients at five centers, and its performance was evaluated on an external test set of 345 patients from another center. Ground-truth labels for the presence of LVO and collateral scores were provided by three radiologists. The nnDetection model achieved a diagnostic accuracy of 98.26% (95% CI 96.25-99.36%) in identifying LVO, correctly classifying 339 out of 345 CTA scans in the external test set. The DL-based collateral scores had a kappa of 0.80, indicating good agreement with the consensus of the radiologists. These results demonstrate that the self-configuring 3D nnDetection model can accurately detect LVO on single-phase CTA scans and provide semi-quantitative collateral scores, offering a comprehensive approach for automated stroke diagnostics in patients with LVO.

Collateral Status and Outcomes after Thrombectomy

Endovascular treatment (EVT) using novel mechanical thrombectomy devices has been the gold standard for patients with acute ischemic stroke caused by large vessel occlusion. Selection criteria of randomized control trials commonly include baseline infarct volume with or without penumbra evaluation. Although the collateral status has been studied and is known to modify imaging results and clinical course, it has not been commonly used for trials. Many post hoc studies, however, revealed that collateral status can help predict infarct growth, recanalization success, decreased hemorrhagic transformation after EVT, and extension of the therapeutic time window for revascularization. Here, we systematically review the recent literature and summarized the outcomes of EVT according to the collateral status of patients with acute ischemic stroke caused by large vessel occlusion. The studies reviewed indicate that pretreatment collateral circulation is associated with both clinical and imaging outcomes after EVT in patients with acute ischemic stroke due to large vessel occlusion although most patients were already selected by other imaging or clinical criteria. However, treatment decisions using information on patients' collateral status have not progressed in clinical practice. Further randomized trials are needed to evaluate the risks and benefits of EVT in consideration of collateral status.

Automated Collateral Scoring on CT Angiography of Patients with Acute Ischemic Stroke Using Hybrid CNN and Transformer Network

Collateral scoring plays an important role in diagnosis and treatment decisions of acute ischemic stroke (AIS). Most existing automated methods rely on vessel prominence and amount after vessel segmentation. The purpose of this study was to design a vessel-segmentation free method for automating collateral scoring on CT angiography (CTA). We first processed the original CTA via maximum intensity projection (MIP) and middle cerebral artery (MCA) region segmentation. The obtained MIP images were fed into our proposed hybrid CNN and Transformer model (MPViT) to automatically determine the collateral scores. We collected 154 CTA scans of patients with AIS for evaluation using five-folder cross validation. Results show that the proposed MPViT achieved an intraclass correlation coefficient of 0.767 (95% CI: 0.68-0.83) and a Kappa of 0.6184 (95% CI: 0.4954-0.7414) for three-point collateral score classification. For dichotomized classification (good vs. non-good and poor vs. non-poor), it also achieved great performance.

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.

Quantitative collateral score for the prediction of clinical outcomes in stroke patients: Better than visual grading

Objectives

To identify preoperative prognostic factors for acute ischemic stroke (AIS) patients receiving mechanical thrombectomy (MT) and compare the performance of quantitative collateral score (qCS) and visual collateral score (vCS) in outcome prediction.

Methods

Fifty-five patients with AIS receiving MT were retrospectively enrolled. qCS was defined as the percentage of the volume of collaterals of both hemispheres. Based on the dichotomous outcome assessed using a 90-day modified Rankin Scale (mRS), we compared qCS, vCS, age, sex, National Institute of Health stroke scale score, etiological subtype, platelet count, international normalized ratio, glucose levels, and low-density lipoprotein cholesterol (LDL-C) levels between favorable and unfavorable outcome groups. Logistic regression analysis was performed to determine the effect on the clinical outcome. The discriminatory power of qCS, vCS, and their combination with cofounders for determining favorable outcomes was tested with the area under the receiver-operating characteristic curve (AUC).

Results

vCS, qCS, LDL-C, and age could all predict clinical outcomes. qCS is superior over vCS in predicting favorable outcomes with a relatively higher AUC value (qCS vs. vCS: 0.81 vs. 0.74) and a higher sensitivity rate (qCS vs. vCS: 72.7% vs. 40.9%). The prediction power of qCS + LDL-C + age was best with an AUC value of 0.91, but the accuracy was just increased slightly compared to that of qCS alone.

Conclusion

Collateral scores, LDL-C and age were independent prognostic predictors for patients with AIS receiving MT; qCS was a better predictor than vCS. Furthermore, qCS + LDL-C + age offers a strong prognostic prediction power and qCS alone was another good choice for predicting clinical outcome.

Collateral Capacity Assessment : Robustness and Interobserver Agreement of Two Grading Scales and Agreement with Quantitative Scoring

BACKGROUND AND PURPOSE

Intracranial collateral capacity is conducive to imply parenchymal perfusion of affected territory after acute vessel occlusion. The Tan collateral score is commonly used to assess the intracranial collateral capacity; however, this score is coarsely grained and interobserver agreement is low, which reduces prognostic value and clinical utility. We introduce and evaluate an alternative extended Tan score based on the conventional Tan scale and assess the agreement with a quantitative score.

METHODS

We included 100 consecutive patients with a proven acute single large vessel occlusion of the proximal anterior circulation. Collaterals were graded with the conventional and extended Tan score and an automated quantitative score. The extended Tan score is a finer 6‑scale manual score based on the conventional 4‑point Tan scale. The quantitative score is calculated by an automatic software package (StrokeViewer). Interobserver agreement of the manual scores was assessed with the weighted kappa. The Spearman correlation coefficient was calculated to determine the agreement between the manual and automated collateral scores.

RESULTS

The interobserver agreement was higher for the extended score than for the conventional score with a weighted kappa of 0.70 and 0.65, respectively. For the extended and conventional score, the Spearman correlation coefficient for the agreement with the automated score was 0.78 and 0.76, respectively.

CONCLUSION

Because of the good interobserver agreement and good agreement with quantitative assessment, the extended collateral score is a strong candidate to improve prognostic value of collateral assessment and implementation in clinical practice.

Automated scoring of collaterals, blood pressure, and clinical outcome after endovascular treatment in patients with acute ischemic stroke and large-vessel occlusion

Introduction

We aimed to determine whether the degree of collateral circulation is associated with blood pressure at admission in acute ischemic stroke patients treated with endovascular treatment and to determine its prognostic value.

Methods

We evaluated patients with anterior large vessel occlusion treated with endovascular treatment in a single-center prospective registry. We collected clinical and radiological data. Automated and validated software (Brainomix Ltd., Oxford, UK) was used to generate the collateral score (CS) from the baseline single-phase CT angiography: 0, filling of ≤10% of the occluded MCA territory; 1, 11–50%; 2, 51–90%; 3, >90%. When dichotomized, we considered that CS was good (CS = 2–3), or poor (CS = 0–1). We performed bivariate and multivariable ordinal logistic regression analysis to predict CS categories in our population. The secondary outcome was to determine the influence of automated CS on functional outcome at 3 months. We defined favorable functional outcomes as mRS 0–2 at 3 months.

Results

We included 101 patients with a mean age of 72.1 ± 13.1 years and 57 (56.4%) of them were women. We classified patients into 4 groups according to the CS: 7 patients (6.9%) as CS = 0, 15 (14.9%) as CS = 1, 43 (42.6%) as CS = 2 and 36 (35.6%) as CS = 3. Admission systolic blood pressure [aOR per 10 mmHg increase 0.79 (95% CI 0.68–0.92)] and higher baseline NIHSS [aOR 0.90 (95% CI, 0.84–0.96)] were associated with a worse CS. The OR of improving 1 point on the 3-month mRS was 1.63 (95% CI, 1.10–2.44) favoring a better CS (p = 0.016).

Conclusion

In acute ischemic stroke patients with anterior large vessel occlusion treated with endovascular treatment, admission systolic blood pressure was inversely associated with the automated scoring of CS on baseline CT angiography. Moreover, a good CS was associated with a favorable outcome.

Cerebral Collateral Circulation in the Era of Reperfusion Therapies for Acute Ischemic Stroke

Clinical outcomes of patients with acute ischemic stroke depend in part on the extent of their collateral circulation. A good collateral circulation has also been associated with greater benefit of intravenous thrombolysis and endovascular treatment. Treatment decisions for these reperfusion therapies are increasingly guided by a combination of clinical and imaging parameters, particularly in later time windows. Computed tomography and magnetic resonance imaging enable a rapid assessment of both the collateral extent and cerebral perfusion. Yet, the role of the collateral circulation in clinical decision-making is currently limited and may be underappreciated due to the use of rather coarse and rater-dependent grading methods. In this review, we discuss determinants of the collateral circulation in patients with acute ischemic stroke, report on commonly used and emerging neuroimaging techniques for assessing the collateral circulation, and discuss the therapeutic and prognostic implications of the collateral circulation in relation to reperfusion therapies for acute ischemic stroke.

Inter-rater reliability for assessing intracranial collaterals in patients with acute ischemic stroke: comparing 29 raters and an artificial intelligence-based software

Purpose

Outcome of endovascular treatment in acute ischemic stroke patients is depending on the collateral circulation maintaining blood flow to the ischemic territory. We evaluated the inter-rater reliability and accuracy of raters and an automated algorithm for assessing the collateral score (CS, range: 0–3) in acute ischemic stroke patients.

Methods

Baseline CTA scans with an intracranial anterior occlusion from the MR CLEAN study (n=500) were used. For each core lab CS, ten CTA scans with sufficient quality were randomly selected. After a training session in collateral scoring, all selected CTA scans were individually evaluated for a visual CS by three groups: 7 radiologists, 13 junior and 9 senior radiology residents. Two additional radiologists scored CS to be used as reference, with a third providing a CS to produce a 2 out of 3 consensus CS in case of disagreement. An automated algorithm was also used to compute CS. Inter-rater agreement was reported with intraclass correlation coefficient (ICC). Accuracy of visual and automated CS were calculated.

Results

39 CTA scans were assessed (1 corrupt CTA-scan excluded). All groups showed a moderate ICC (0.689-0.780) in comparison to the reference standard. Overall human accuracy was 65± 7% and increased to 88± 5% for dichotomized CS (0–1, 2–3). Automated CS accuracy was 62%, and 90% for dichotomized CS. No significant difference in accuracy was found between groups with different levels of expertise.

Conclusion

After training, inter-rater reliability in collateral scoring was not influenced by experience. Automated CS performs similar to residents and radiologists in determining a collateral score.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00234-022-02984-z.

Diagnostic performance of an algorithm for automated collateral scoring on computed tomography angiography

OBJECTIVES

Outcome of endovascular treatment in acute ischemic stroke patients depends on collateral circulation to provide blood supply to the ischemic territory. We evaluated the performance of a commercially available algorithm for assessing the collateral score (CS) in acute ischemic stroke patients.

METHODS

Retrospectively, baseline CTA scans (≤ 3-mm slice thickness) with an intracranial carotid artery (ICA), middle cerebral artery segment M1 or M2 occlusion, from the MR CLEAN Registry (n = 1627) were evaluated. All CTA scans were evaluated for visual CS (0-3) by eight expert radiologists (reference standard). A Web-based AI algorithm quantified the collateral circulation (0-100%) for correctly detected occlusion sides. Agreement between visual CS and categorized automated CS (0: 0%, 1: > 0- ≤ 50%, 2: > 50- < 100%, 3: 100%) was assessed. Area under the curve (AUC) values for classifying patients in having good (CS: 2-3) versus poor (CS: 0-1) collaterals and for predicting functional independence (90-day modified Rankin Scale 0-2) were computed. Influence of CTA acquisition timing after contrast material administration was reported.

RESULTS

In the analyzed scans (n = 1024), 59% agreement was found between visual CS and automated CS. An AUC of 0.87 (95% CI: 0.85-0.90) was found for discriminating good versus poor CS. Timing of CTA acquisition did not influence discriminatory performance. AUC for predicting functional independence was 0.66 (95% CI 0.62-0.69) for automated CS, similar to visual CS 0.64 (95% CI 0.61-0.68).

CONCLUSIONS

The automated CS performs similar to radiologists in determining a good versus poor collateral score and predicting functional independence in acute ischemic stroke patients with a large vessel occlusion.

KEY POINTS

• Software for automated quantification of intracerebral collateral circulation on computed tomography angiography performs similar to expert radiologists in determining a good versus poor collateral score. • Software for automated quantification of intracerebral collateral circulation on computed tomography angiography performs similar to expert radiologists in predicting functional independence in acute ischemic stroke patients with a large vessel occlusion. • The timing of computed tomography angiography acquisition after contrast material administration did not influence the performance of automated quantification of the collateral status.

Bio-clinical evaluation of collateral score in acute middle cerebral artery occlusion

BACKGROUND

Acute ischemic stroke (AIS) is characterized as a neurological deficit owing to an acute focal damage to the brain by cerebral infarction. A collateral score is the most significant factor evaluating the prognosis of AIS, its relationship with demographic data, serum biochemical parameters, and clinical disability in this field.

METHODS

We conducted a single-center retrospective study with 100 patients with AIS within the first 6 h of ischemic stroke. Data for consecutive AIS patients were collected from February 2019 to May 2020. The collateral score was assessed by using developed scoring systems defined by Maas et al. The correlations between collateral score and demographic data, biochemical parameters, NIHSS scores (National Institutes of Health Stroke Scale), mRS (modified Rankin scale) scores were recorded.

RESULTS

The research was performed in 100 patients (median age, 71.55 ± 11.46 years), and there was a statistically significant difference between elevated erythrocyte distribution width (RDW) and Maas collateral score (insular cortex) (p = 0.024) and lymphocyte/ monocyte ratio (LMO) and Maas collateral (leptomeningeal) score (p = 0.025).

Preliminary Application of a Quantitative Collateral Assessment Method in Acute Ischemic Stroke Patients With Endovascular Treatments: A Single-Center Study

Objectives: To develop an efficient and quantitative assessment of collateral circulation on time maximum intensity projection CT angiography (tMIP CTA) in patients with acute ischemic stroke (AIS). Methods: Eighty-one AIS patients who underwent one-stop CTA-CT perfusion (CTP) from February 2016 to October 2020 were retrospectively reviewed. Single-phase CTA (sCTA) and tMIP CTA were developed from CTP data. Ischemic core (IC) volume, ischemic penumbra volume, and mismatch ratio were calculated. The Tan scale was used for the qualitative evaluation of collateral based on sCTA and tMIP CTA. Quantitative collateral circulation (CCq) parameters were calculated semi-automatically with software by the ratio of the vascular volume (V) on both hemispheres, including tMIP CTA V_CCq and sCTA V_CCq. Spearman correlation analysis was used to analyze the correlation of collateral-related parameters with final infarct volume (FIV). ROC and multivariable regression analysis were calculated to compare the significance of the above parameters in clinical outcome evaluation. The analysis time of the observers was also compared. Results: tMIP CTA V_CCq (r = 0.61, p < 0.01), IC volume (r = 0.66, p < 0.01), Tan score on tMIP CTA (r = 0.52, p < 0.01) and mismatch ratio (r = 0.60, p < 0.01) showed moderate negative correlations with FIV. tMIP CTA V_CCq showed the best prognostic value for clinical outcome (AUC = 0.93, p < 0.001), and was an independent predictive factor of clinical outcome (OR = 0.14, p = 0.009). There was no difference in analysis time of tMIP CTA V_CCq among observers (p = 0.079). Conclusion: The quantitative evaluation of collateral circulation on tMIP CTA is associated with clinical outcomes in AIS patients with endovascular treatments.

Venous outflow profiles are associated with early edema progression in ischemic stroke

BACKGROUND

In patients with acute ischemic stroke due to large vessel occlusion (AIS-LVO), development of extensive early ischemic brain edema is associated with poor functional outcomes, despite timely treatment. Robust cortical venous outflow (VO) profiles correlate with favorable tissue perfusion. We hypothesized that favorable VO profiles (VO+) correlate with a reduced early edema progression rate (EPR) and good functional outcomes.

METHODS

Multicenter, retrospective analysis to investigate AIS-LVO patients treated by mechanical thrombectomy between May 2013 and December 2020. Baseline computed tomography angiography (CTA) was used to determine VO using the cortical vein opacification score (COVES); VO+ was defined as COVES ⩾ 3 and unfavorable as COVES ⩽ 2. EPR was determined as the ratio of net water uptake (NWU) on baseline non-contrast CT and time from symptom onset to admission imaging. Multivariable regression analysis was performed to assess primary (EPR) and secondary outcome (good functional outcomes defined as 0-2 points on the modified Rankin scale).

RESULTS

A total of 728 patients were included. Primary outcome analysis showed VO+ (β: -0.03, SE: 0.009, p = 0.002), lower presentation National Institutes of Health Stroke Scale (NIHSS; β: 0.002, SE: 0.001, p = 0.002), and decreased time from onset to admission imaging (β: -0.00002, SE: 0.00004, p < 0.001) were independently associated with reduced EPR. VO+ also predicted good functional outcomes (odds ratio (OR): 5.07, 95% CI: 2.839-9.039, p < 0.001), while controlling for presentation NIHSS, time from onset to imaging, general vessel reperfusion, baseline Alberta Stroke Program Early CT Score, infarct core volume, EPR, and favorable arterial collaterals.

CONCLUSIONS

Favorable VO profiles were associated with slower infarct edema progression and good long-term functional outcomes as well as better neurological status and ischemic brain alterations at admission.

Automated Detection of Ischemic Stroke and Subsequent Patient Triage in Routinely Acquired Head CT

Purpose

Advanced machine-learning (ML) techniques can potentially detect the entire spectrum of pathology through deviations from a learned norm.

We investigated the utility of a weakly supervised ML tool to detect characteristic findings related to ischemic stroke in head CT and provide subsequent patient triage.

Methods

Patients having undergone non-enhanced head CT at a tertiary care hospital in April 2020 with either no anomalies, subacute or chronic ischemia, lacunar infarcts of the deep white matter or hyperdense vessel signs were retrospectively analyzed. Anomaly detection was performed using a weakly supervised ML classifier. Findings were displayed on a voxel-level (heatmap) and pooled to an anomaly score. Thresholds for this score classified patients into i) normal, ii) inconclusive, iii) pathological. Expert-validated radiological reports were considered as ground truth. Test assessment was performed with ROC analysis; inconclusive results were pooled to pathological predictions for accuracy measurements.

Results

During the investigation period 208 patients were referred for head CT of which 111 could be included. Definite ratings into normal/pathological were feasible in 77 (69.4%) patients. Based on anomaly scores, the AUC to differentiate normal from pathological scans was 0.98 (95% CI 0.97–1.00). The sensitivity, specificity, positive and negative predictive values were 100%, 40.6%, 80.6% and 100%, respectively.

Conclusion

Our study demonstrates the potential of a weakly supervised anomaly-detection tool to detect stroke findings in head CT. Definite classification into normal/pathological was made with high accuracy in > 2/3 of patients. Anomaly heatmaps further provide guidance towards pathologies, also in cases with inconclusive ratings.

Distinct intra-arterial clot localization affects tissue-level collaterals and venous outflow profiles

BACKGROUND AND PURPOSE

Arterial clot localization affects collateral flow to ischemic brain in patients with acute ischemic stroke due to large vessel occlusion (AIS-LVO). We determined the association between vessel occlusion locations, tissue-level collaterals (TLC), and venous outflow (VO) profiles and their impact on good functional outcomes.

METHODS

We conducted a multicenter retrospective cohort study of consecutive AIS-LVO patients who underwent thrombectomy triage. Baseline computed tomographic angiography (CTA) was used to localize vessel occlusion, which was dichotomized into proximal vessel occlusion (PVO; internal carotid artery and proximal first segment of the middle cerebral artery [M1]) and distal vessel occlusion (DVO; distal M1 and M2), and to assess collateral scores. TLC were assessed on computed tomographic perfusion data using the hypoperfusion intensity ratio. VO was determined on baseline CTA by the cortical vein opacification score. Primary outcomes were favorable VO and TLC; secondary outcome was the modified Rankin Scale after 90 days.

RESULTS

A total of 649 patients met inclusion criteria. Of these, 376 patients (58%) had a PVO and 273 patients (42%) had a DVO. Multivariate ordinal logistic regression showed that DVO predicted favorable TLC (odds ratio [OR] = 1.77, 95% confidence interval [CI] = 1.24-2.52, p = 0.002) and favorable VO (OR = 7.2, 95% CI = 5.2-11.9, p < 0.001). DVO (OR = 3.4, 95% CI = 2.1-5.6, p < 0.001), favorable VO (OR = 6.4, 95% CI = 3.8-10.6, p < 0.001), and favorable TLC (OR = 3.2, 95% CI = 2-5.3, p < 0.001), but not CTA collaterals (OR = 1.07, 95% CI = 0.60-1.91, p = 0.813), were predictors of good functional outcome.

CONCLUSIONS

DVO in AIS-LVO patients correlates with favorable TLC and VO profiles, which are associated with good functional outcome.

Emerging role of artificial intelligence in stroke imaging

Introduction: The recognition and therapy of patients with stroke is becoming progressively intricate as additional treatment choices become accessible and new associations between disease characteristics and treatment response are incessantly uncovered. Therefore, clinicians must regularly learn new skill, stay up to date with the literature and integrate advances into daily practice. The application of artificial intelligence (AI) to assist clinical decision making could diminish inter-rater variation in routine clinical practice and accelerate the mining of vital data that could expand recognition of patients with stroke, forecast of treatment responses and patient outcomes.Areas covered: In this review, the authors provide an up-to-date review of AI in stroke, analyzing the latest papers on this subject. These have been divided in two main groups: stroke diagnosis and outcome prediction.Expert opinion: The highest value of AI is its capability to merge, select and condense a large amount of clinical and imaging features of a single patient and to associate these with fitted models that have gone through robust assessment and optimization with large cohorts of data to support clinical decision making.

On the Sensitivity Analysis of Porous Finite Element Models for Cerebral Perfusion Estimation

Computational physiological models are promising tools to enhance the design of clinical trials and to assist in decision making. Organ-scale haemodynamic models are gaining popularity to evaluate perfusion in a virtual environment both in healthy and diseased patients. Recently, the principles of verification, validation, and uncertainty quantification of such physiological models have been laid down to ensure safe applications of engineering software in the medical device industry. The present study sets out to establish guidelines for the usage of a three-dimensional steady state porous cerebral perfusion model of the human brain following principles detailed in the verification and validation (V&V 40) standard of the American Society of Mechanical Engineers. The model relies on the finite element method and has been developed specifically to estimate how brain perfusion is altered in ischaemic stroke patients before, during, and after treatments. Simulations are compared with exact analytical solutions and a thorough sensitivity analysis is presented covering every numerical and physiological model parameter. The results suggest that such porous models can approximate blood pressure and perfusion distributions reliably even on a coarse grid with first order elements. On the other hand, higher order elements are essential to mitigate errors in volumetric blood flow rate estimation through cortical surface regions. Matching the volumetric flow rate corresponding to major cerebral arteries is identified as a validation milestone. It is found that inlet velocity boundary conditions are hard to obtain and that constant pressure inlet boundary conditions are feasible alternatives. A one-dimensional model is presented which can serve as a computationally inexpensive replacement of the three-dimensional brain model to ease parameter optimisation, sensitivity analyses and uncertainty quantification. The findings of the present study can be generalised to organ-scale porous perfusion models. The results increase the applicability of computational tools regarding treatment development for stroke and other cerebrovascular conditions.

Favorable Venous Outflow Profiles Correlate With Favorable Tissue-Level Collaterals and Clinical Outcome

BACKGROUND AND PURPOSE

Patients with acute ischemic stroke due to large vessel occlusion and favorable tissue-level collaterals (TLCs) likely have robust cortical venous outflow (VO). We hypothesized that favorable VO predicts robust TLC and good clinical outcomes.

METHODS

Multicenter retrospective cohort study of consecutive acute ischemic stroke due to large vessel occlusion patients who underwent thrombectomy triage. Included patients had interpretable prethrombectomy computed tomography, computed tomography angiography, and cerebral perfusion imaging. TLCs were measured on cerebral perfusion studies using the hypoperfusion intensity ratio (volume ratio of brain tissue with [Tmax >10 s/Tmax >6 s]). VO was determined by opacification of the vein of Labbé, sphenoparietal sinus, and superficial middle cerebral vein on computed tomography angiography as 0, not visible; 1, moderate opacification; and 2, full. Clinical and demographic data were determined from the electronic medical record. Using multivariable regression analyses, we determined the association between VO and (1) favorable TLC status (defined as hypoperfusion intensity ratio ≤0.4) and (2) good functional outcome (modified Rankin Scale score, 0-2).

RESULTS

Six hundred forty-nine patients met inclusion criteria. Patients with favorable VO were younger (median age, 72 [interquartile range (IQR), 62-80] versus 77 [IQR, 66-84] years), had a lower baseline National Institutes of Health Stroke Scale (median, 12 [IQR, 7-17] versus 19 [IQR, 13-20]), and had a higher Alberta Stroke Program Early Computed Tomography Score (median, 9 [IQR, 7-10] versus 7 [IQR, 6-9]). Favorable VO strongly predicted favorable TLC (odds ratio, 4.5 [95% CI, 3.1-6.5]; P<0.001) in an adjusted regression analysis. Favorable VO also predicted good clinical outcome (odds ratio, 10 [95% CI, 6.2-16.0]; P<0.001), while controlling for favorable TLC, age, glucose, baseline National Institutes of Health Stroke Scale, and good vessel reperfusion status.

CONCLUSIONS

In this selective retrospective cohort study of acute ischemic stroke due to large vessel occlusion patients undergoing thrombectomy triage, favorable VO profiles correlated with favorable TLC and were associated with good functional outcomes after treatment. Future prospective studies should independently validate our findings.

Anemia Predicts Poor Clinical Outcome in Mechanical Thrombectomy Patients with Fair or Good Collateral Circulation

Background and Purpose

Anemia predicts poor clinical outcome of ischemic stroke in the general stroke population. We studied whether this applies to those treated with mechanical thrombectomy for proximal anterior circulation occlusion in the setting of differing collateral circulation.

Methods

We collected the data of 347 consecutive anterior circulation stroke patients who underwent mechanical thrombectomy after multimodal CT imaging in a single tertiary stroke care center. Patients with occlusion of the internal carotid artery and/or the first segment of the middle cerebral artery were included. We recorded baseline clinical, laboratory, procedural, and imaging variables, and the technical, imaging, and clinical outcomes. Differences between anemic and nonanemic patients were studied with appropriate statistical tests and binary logistic regression analysis.

Results

Ninety-four out of the 285 patients eligible for analysis had anemia, and 243 had fair or good collateral circulation (collateral score, CS, >0). Fifty-four percent of the patients experienced good 3-month clinical outcome (modified Rankin Scale ≤2). In pooled analyses of the CS 1–4 and 2–4 ranges, nonanemic patients had good clinical outcome significantly more often (p < 0.001 for both). This effect was not seen in patients with poor collateral circulation (CS = 0). Nonanemic patients had significantly better odds of good clinical outcome (OR = 2.6, 95% CI 1.377–5.030, p = 0.004) in a binary regression model. A 0.1 g/dL increase in hemoglobin improved the odds of good clinical outcome by 2% (OR = 1.02, 95% CI 1.002–1.044, p = 0.03).

Conclusions

Low hemoglobin on admission predicts poor clinical outcome in mechanical thrombectomy patients with fair or good collateral circulation.

Artificial intelligence in stroke imaging: Current and future perspectives

Artificial intelligence (AI) is a fast-growing research area in computer science that aims to mimic cognitive processes through a number of techniques. Supervised machine learning, a subfield of AI, includes methods that can identify patterns in high-dimensional data using labeled 'ground truth' data and apply these learnt patterns to analyze, interpret, or make predictions on new datasets. Supervised machine learning has become a significant area of interest within the medical community. Radiology and neuroradiology in particular are especially well suited for application of machine learning due to the vast amount of data that is generated. One devastating disease for which neuroimaging plays a significant role in the clinical management is stroke. Within this context, AI techniques can play pivotal roles for image-based diagnosis and management of stroke. This overview focuses on the recent advances of artificial intelligence methods - particularly supervised machine learning and deep learning - with respect to workflow, image acquisition and reconstruction, and image interpretation in patients with acute stroke, while also discussing potential pitfalls and future applications.

Cerebral collaterals in acute ischaemia: Implications for acute ischaemic stroke patients receiving reperfusion therapy

The cerebral collaterals play an important role in penumbral tissue sustenance after an acute ischaemic stroke. Recent studies have demonstrated the potential role of collaterals in the selection of acute ischaemic stroke patients eligible for reperfusion therapy. However, the understanding of the significance and evidence around the role of collateral status in predicting outcomes in acute ischaemic stroke patients treated with reperfusion therapy is still unclear. Moreover, the use of pre-treatment collaterals in patient selection and prognosis is relatively underappreciated in clinical settings. A focused review of the literature was performed on the various methods of collateral evaluation and the role of collateral status in acute ischaemic stroke patients receiving reperfusion therapy. We discuss the methods of evaluating pre-treatment collaterals in clinical settings. The patient selection based on collateral status as well as the prognostic and therapeutic value of collaterals in acute ischaemic stroke, in settings of intravenous thrombolysis or endovascular therapy alone, and bridge therapy, are summarized. Recommendations for future research and possible pharmacological intervention strategies aimed at collateral enhancement are also discussed. Collaterals may play an important role in identifying acute ischaemic stroke patients who are likely to benefit from endovascular treatment in an extended time window. Future neuroscientific efforts to better improve our understanding of the role of collaterals in acute ischaemia as well as clinical studies to delineate its role in patient selection and acute stroke prognosis are warranted.

In-Silico Trials for Treatment of Acute Ischemic Stroke

Despite improved treatment, a large portion of patients with acute ischemic stroke due to a large vessel occlusion have poor functional outcome. Further research exploring novel treatments and better patient selection has therefore been initiated. The feasibility of new treatments and optimized patient selection are commonly tested in extensive and expensive randomized clinical trials. in-silico trials, computer-based simulation of randomized clinical trials, have been proposed to aid clinical trials. In this white paper, we present our vision and approach to set up in-silico trials focusing on treatment and selection of patients with an acute ischemic stroke. The INSIST project (IN-Silico trials for treatment of acute Ischemic STroke, www.insist-h2020.eu) is a collaboration of multiple experts in computational science, cardiovascular biology, biophysics, biomedical engineering, epidemiology, radiology, and neurology. INSIST will generate virtual populations of acute ischemic stroke patients based on anonymized data from the recent stroke trials and registry, and build on the existing and emerging in-silico models for acute ischemic stroke, its treatment (thrombolysis and thrombectomy) and the resulting perfusion changes. These models will be used to design a platform for in-silico trials that will be validated with existing data and be used to provide a proof of concept of the potential efficacy of this emerging technology. The platform will be used for preliminary evaluation of the potential suitability and safety of medication, new thrombectomy device configurations and methods to select patient subpopulations for better treatment outcome. This could allow generating, exploring and refining relavant hypotheses on potential causal pathways (which may follow from the evidence obtained from clinical trials) and improving clinical trial design. Importantly, the findings of the in-silico trials will require validation under the controlled settings of randomized clinical trials.

Automatic collateral circulation scoring in ischemic stroke using 4D CT angiography with low-rank and sparse matrix decomposition

PURPOSE

Sufficient collateral blood supply is crucial for favorable outcomes with endovascular treatment. The current practice of collateral scoring relies on visual inspection and thus can suffer from inter and intra-rater inconsistency. We present a robust and automatic method to score cerebral collateral blood supply to aid ischemic stroke treatment decision making. The developed method is based on 4D dynamic CT angiography (CTA) and the ASPECTS scoring protocol.

METHODS

The proposed method, ACCESS (Automatic Collateral Circulation Evaluation in iSchemic Stroke), estimates a target patient's unfilled cerebrovasculature in contrast-enhanced CTA using the lack of contrast agent due to clotting. To do so, the fast robust matrix completion algorithm with in-face extended Frank-Wolfe optimization is applied on a cohort of healthy subjects and a target patient, to model the patient's unfilled vessels and the estimated full vasculature as sparse and low-rank components, respectively. The collateral score is computed as the ratio of the unfilled vessels to the full vasculature, mimicking existing clinical protocols.

RESULTS

ACCESS was tested with 46 stroke patients and obtained an overall accuracy of 84.78%. The optimal threshold selection was evaluated using a receiver operating characteristics curve with the leave-one-out approach, and a mean area under the curve of 85.39% was obtained.

CONCLUSION

ACCESS automates collateral scoring to mitigate the shortcomings of the standard clinical practice. It is a robust approach, which resembles how radiologists score clinical scans, and can be used to help radiologists in clinical decisions of stroke treatment.

Clinical and Imaging Determinants of Collateral Status in Patients With Acute Ischemic Stroke in MR CLEAN Trial and Registry

Background and Purpose- Collateral circulation status at baseline is associated with functional outcome after ischemic stroke and effect of endovascular treatment. We aimed to identify clinical and imaging determinants that are associated with collateral grade on baseline computed tomography angiography in patients with acute ischemic stroke due to an anterior circulation large vessel occlusion. Methods- Patients included in the MR CLEAN trial (Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands; n=500) and MR CLEAN Registry (n=1488) were studied. Collateral status on baseline computed tomography angiography was scored from 0 (absent) to 3 (good). Multivariable ordinal logistic regression analyses were used to test the association of selected determinants with collateral status. Results- In total, 1988 patients were analyzed. Distribution of the collateral status was as follows: absent (7%, n=123), poor (32%, n=596), moderate (39%, n=735), and good (23%, n=422). Associations for a poor collateral status in a multivariable model existed for age (adjusted common odds ratio, 0.92 per 10 years [95% CI, 0.886-0.98]), male (adjusted common odds ratio, 0.64 [95% CI, 0.53-0.76]), blood glucose level (adjusted common odds ratio, 0.97 [95% CI, 0.95-1.00]), and occlusion of the intracranial segment of the internal carotid artery with occlusion of the terminus (adjusted common odds ratio 0.50 [95% CI, 0.41-0.61]). In contrast to previous studies, we did not find an association between cardiovascular risk factors and collateral status. Conclusions- Older age, male sex, high glucose levels, and intracranial internal carotid artery with occlusion of the terminus occlusions are associated with poor computed tomography angiography collateral grades in patients with acute ischemic stroke eligible for endovascular treatment.

Scoring of Middle Cerebral Artery Collaterals Predicts RAPID CT-Perfusion Analysis and Short-Term Outcomes in Acute Ischemic Stroke Patients Undergoing Thrombectomy

OBJECTIVE

The rapid processing of perfusion and diffusion (RAPID) system for automating perfusion and diffusion data from head computed tomography has improved acute ischemic stroke treatment by quickly and accurately identifying those patients who may benefit from thrombectomy. Collateral scoring (CS) of cerebral arteries using computed tomography angiography (CTA) has proven useful in predicting postintervention infarct volumes and functional outcomes in ischemic stroke patients. Here we evaluate the relationship between CS and RAPID software in an effort to augment triage and provide improved predictability of functional outcomes in ischemic stroke patients.

METHODS

A retrospective review of 77 mechanical thrombectomy patients from January 2017 to October 2018 with large vessel occlusions of the anterior circulation who underwent RAPID and CTA imaging was performed. Baseline characteristics, RAPID data, CS, modified Rankin Scale score, and procedural data were collected. magnetic resonance imaging was used to calculate the postintervention stroke volume.

RESULTS

CS inversely correlates with the volume of RAPID cerebral blood flow <30% (β= -18.131, 95% confidence interval [CI] -24.384 to -11.879, P < 0.001), RAPID Tmax >6s (β= -22.205, 95% CI -39.125 to -5.285, P = 0.011), postintervention stroke volume (β= -30.637, 95% CI -41.554 to -19.720, P < 0.001), and discharge National Institutes of Health Stroke Scale score (β= -1.922, 95% CI -3.575 to -0.269, P = 0.023).

CONCLUSIONS

CS on CTA may be a useful way to identify patients who would benefit from mechanical thrombectomy and predict functional outcomes postintervention. CS may allow the stroke team to optimize the care of patients who may not be able to obtain RAPID analysis.

Collateral Circulation and Outcome in Atherosclerotic Versus Cardioembolic Cerebral Large Vessel Occlusion

Supplemental Digital Content is available in the text.

Due to chronic hypoperfusion, cervical atherosclerosis may promote cerebral collateral circulation. We hypothesized that patients with ischemic stroke due to cervical carotid atherosclerosis have a more extensive collateral circulation and better outcomes than patients with cardioembolism. We tested this hypothesis in a population of patients who underwent endovascular treatment for large vessel occlusion.

Computer-aided imaging analysis in acute ischemic stroke - background and clinical applications

Tools for medical image analysis have been developed to reduce the time needed to detect abnormalities and to provide more accurate results. Particularly, tools based on artificial intelligence and machine learning techniques have led to significant improvements in medical imaging interpretation in the last decade. Automatic evaluation of acute ischemic stroke in medical imaging is one of the fields that witnessed a major development. Commercially available products so far aim to identify (and quantify) the ischemic core, the ischemic penumbra, the site of arterial occlusion and the collateral flow but they are not (yet) intended as standalone diagnostic tools. Their use can be complementary; they are intended to support physicians' interpretation of medical images and hence standardise selection of patients for acute treatment. This review provides an introduction into the field of computer-aided diagnosis and focuses on the automatic analysis of non-contrast-enhanced computed tomography, computed tomography angiography and perfusion imaging. Future studies are necessary that allow the evaluation and comparison of different imaging strategies and post-processing algorithms during the diagnosis process in patients with suspected acute ischemic stroke; which may further facilitate the standardisation of treatment and stroke management.