Collateral Score Research Articles

CT perfusion based rCBF

Collateral status (CS) is an important biomarker of functional outcomes in patients with acute ischemic stroke secondary to large vessel occlusion (AIS-LVO). Pretreatment CT perfusion (CTP) parameters serve as reliable surrogates of collateral status (CS). In this study, we aim to assess the relationship between the relative cerebral blood flow less than 38% (rCBF <38%), with the reference standard American Society of Interventional and Therapeutic Neuroradiology (ASITN) collateral score (CS) on DSA. In this prospectively collected, retrospectively reviewed analysis, inclusion criteria were as follows: (a) CT angiography (CTA) confirmed anterior circulation large vessel occlusion from 9/1/2017 to 10/01/2023; (b) diagnostic CT perfusion; and (c) underwent mechanical thrombectomy with documented ASITN CS. The ratios of the CTP-derived CBF values were calculated by dividing the values of the ischemic lesion by the corresponding values of the contralateral normal region (which were defined as rCBF). Spearman's rank correlation and logistic regression analysis were performed to determine the relationship of rCBF <38% lesion volume with DSA ASITN CS. p ≤ .05 was considered significant. In total, 223 patients [mean age: 67.77 ± 15.76 years, 56.1% (n = 125) female] met our inclusion criteria. Significant negative correlation was noted between rCBF <38% volume and DSA CS (ρ = -0.37, p < .001). On multivariate logistic regression analysis, rCBF <38% volume was found to be independently associated with worse ASITN CS (unadjusted OR: 3.03, 95% CI: 1.60-5.69, p < .001, and adjusted OR: 2.73, 95% CI: 1.34-5.50, p < .01). Greater volume of tissue with rCBF <38% is independently associated with better DSA CS. rCBF <38% is a useful adjunct tool in collateralization-based prognostication. Future studies are needed to expand our understanding of the role of rCBF <38% within the decision-making in patients with AIS-LVO.

The Relative Cerebral Blood Volume (rCBV) < 42% Is Independently Associated with Collateral Status in Anterior Circulation Large Vessel Occlusion.

Background: The pretreatment CT perfusion (CTP) marker the relative cerebral blood volume (rCBV) < 42% lesion volume has recently been shown to predict 90-day functional outcomes; however, studies assessing correlations of the rCBV < 42% lesion volume with other outcomes remain sparse. Here, we aim to assess the relationship between the rCBV < 42% lesion volume and the reference standard digital subtraction angiography (DSA)-derived American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology (ASITN) collateral score, hereby referred as the DSA CS. Methods: In this retrospective evaluation of our prospectively collected database, we included acute stroke patients triaged by multimodal CT imaging, including CT angiography and perfusion imaging, with confirmed anterior circulation large vessel occlusion between 1 September 2017 and 1 October 2023. Group differences were assessed using the Student's t test, Mann-Whitney U test and Chi-Square test. Spearman's rank correlation and logistic regression analyses were used to assess associations between rCBV < 42% and DSA CS. Results: In total, 222 patients (median age: 69 years, 56.3% female) met our inclusion criteria. In the multivariable logistic regression analysis, taking into account age, sex, race, hypertension, hyperlipidemia, diabetes, atrial fibrillation, prior stroke or transient ischemic attack, the admission National Institute of Health stroke scale, the premorbid modified Rankin score, the Alberta stroke program early CT score (ASPECTS), and segment occlusion, the rCBV < 42% lesion volume (adjusted OR: 0.98, p < 0.05) was independently associated with the DSA CS. Conclusion: The rCBV < 42% lesion volume is independently associated with the DSA CS.

Predictors of Outcome after Direct Aspiration of Basilar Artery Occlusion.

Background: Basilar artery occlusion (BAO) is a serious disease with a poor prognosis if left untreated. Endovascular therapy (EVT) is the most effective treatment that is able to reduce mortality and disability. Treatment results are influenced by a wide range of factors that have not been clearly identified. In the present study, direct aspiration was chosen as a first-line treatment. The safety and effectiveness of direct aspiration in BAO were determined, and factors affecting patient outcomes were identified. Methodology: Data for patients with BAO treated between November 2013 and December 2021 were evaluated using a database. The association between clinical and procedural parameters and functional outcome was assessed. Results: A total of 89 patients with BAO were identified. Full recanalization was achieved in 69.7% of cases and partial recanalization in 19.1%. Intracranial hemorrhage was detected in 11 (12.4%) patients, of which, eight (9.0%) patients experienced symptomatic intracranial hemorrhage. Patients with good outcomes presented with milder strokes (mean NIHSS score of 12.58 vs. 24.00, p < 0.001), had higher collateral scores (6.79 vs. 5.88, p = 0.016), more often achieved complete recanalization (87.9% vs. 58.9%, p = 0.009), and more often experienced early neurological improvement (66.7% vs. 26.8%, p < 0.001). On the contrary, patients with worse outcomes had higher serum glucose levels (p = 0.05), occlusion of the middle portion of the basilar artery (MAB) (30.3% vs. 53.6%, p = 0.033), longer thrombus lengths (10.51 vs. 16.48 mm, p = 0.046), and intracranial hemorrhage (p = 0.035). Conclusions: The present study results suggest that direct aspiration is a safe and effective treatment for patients with BAO. We identified several factors affecting the patients' outcome.

Comparison of collateral status in anterior circulation acute ischemic stroke on single-phase and multiphase CT angiography in prediction of clinical and radiological outcome

Objectives Various collateral scoring systems are used to assess the collateral status on single or multiphase CT angiography (CTA) to forecast outcomes in anterior circulation acute ischemic stroke patients. Our study aimed to compare the predictive ability of these collateral scoring systems in determining clinical and radiological outcomes in patients with anterior circulation acute ischemic stroke. Material and Methods In this observational prospective study, data was obtained from December 2020 to June 2022 in consecutive acute ischemic stroke patients referred to our department for neuroimaging. The collateral scores were assessed using Tan and Menon scoring systems described for single and multiphase CTA, respectively. The correlations between various collateral scores, the National Institute of Health Stroke Scale (NIHSS), Modified Rankin Scale (mRS), and final infarct volume were studied. Receiver operating characteristics (ROC) curves and multivariate logistic regression analysis were performed to assess the predictive ability of scoring systems for clinical and radiological outcomes Results A total of 32 patients met the inclusion criteria. Both single- and multiphase collateral scores showed statistically significant negative correlations with clinical and radiological outcomes. Spearman correlation coefficient and p-value for the radiological outcome being -Tan score (r- -0.73, p- &lt; 0.001), single-phase Menon score (r- -0.81, p- &lt; 0.001), and multiphase Menon score (r- -0.79, p- &lt; 0.001). ROC curve analysis revealed that the multiphase Menon score performed slightly better than the single-phase Menon score (area under the curve [AUC], 0.815 vs 0.810) in predicting a favorable 90-day modified Rankin scale score. Conclusion Our study concluded that collateral status on both multiphase CTA (mCT) and conventional (Single phase arterial CTA) showed statistically significant results in the prediction of clinical and radiological outcomes.

Utilizing imaging parameters for functional outcome prediction in acute ischemic stroke: A machine learning study.

We aimed to predict the functional outcome of acute ischemic stroke patients with anterior circulation large vessel occlusions (LVOs), irrespective of how they were treated or the severity of the stroke at admission, by only using imaging parameters in machine learning models. Consecutive adult patients with anterior circulation LVOs who were scanned with CT angiography (CTA) and CT perfusion were queried in this single-center, retrospective study. The favorable outcome was defined as a modified Rankin score (mRS) of 0-2 at 90 days. Predictor variables included only imaging parameters. CatBoost, XGBoost, and Random Forest were employed. Algorithms were evaluated using the area under the receiver operating characteristic curve (AUROC), the area under the precision-recall curve (AUPRC), accuracy, Brier score, recall, and precision. SHapley Additive exPlanations were implemented. A total of 180 patients (102 female) were included, with a median age of 69.5. Ninety-two patients had an mRS between 0 and 2. The best algorithm in terms of AUROC was XGBoost (0.91). Furthermore, the XGBoost model exhibited a precision of 0.72, a recall of 0.81, an AUPRC of 0.83, an accuracy of 0.78, and a Brier score of 0.17. Multiphase CTA collateral score was the most significant feature in predicting the outcome. Using only imaging parameters, our model had an AUROC of 0.91 which was superior to most previous studies, indicating that imaging parameters may be as accurate as conventional predictors. The multiphase CTA collateral score was the most predictive variable, highlighting the importance of collaterals.

Evaluation of the relationship between computed tomography angiography collateral scores and clinical outcome.

The relationship between collateral circulation and prognosis after endovascular treatment in anterior circulation strokes has been reported in many studies. In this study, we aimed to compare the predictive power of clinical outcome by comparing five different collateral scores that are frequently used. Among the patients who underwent endovascular treatment in our clinic between November 2019 and December 2021, patients with premorbid mRS < 3, intracranial ICA and/or MCA M1 occlusion, and a pre-procedural multiphase CTA examination were included in the study. Demographic, technical, and duration information about the procedure, major events after the procedure, and clinical outcomes at 3 months were recorded. The mCTA, Tan, Maas, Miteff, and rLMC collateral scores of the patients were evaluated. Clinical outcome at 3 months were good in 37 of the 68 patients included in the study (mRS ≤ 2). Only the mCTA and rLMC collateral scores were statistically significantly higher in those with a good clinical outcome. Significant correlation with 3-month mRS was detected only in mCTA and rLMC scores. Although rLMC and mCTA collateral scores showed a statistically significant association with prognosis, they were not sufficient to be an independent predictor of prognosis. mCTA and rLMC were found to have the highest predictive power of clinical outcome and the highest correlation with the 3-month clinical outcome. Our study suggests that it would be beneficial to develop a new scoring system over multiphase CTA, which combines regional and temporal evaluation, which are the strengths of both collateral scoring.

Clinical and imaging markers for the prognosis of acute ischemic stroke.

Significant differences in the outcomes observed in patients with acute ischemic stroke (AIS) have led to research investigations for identifying the predictors. In this retrospective study, we aimed to investigate the relationship of different clinical and imaging factors with the prognosis of AIS. All clinical and imaging metrics were compared between the good and poor prognosis groups according to the modified Rankin Scale (mRS) score at 90 days after discharge. Clinical factors included gender, age, NIHSS scores at admission, and other medical history risk factors. Imaging markers included the lesion's size and location, diffusion, and perfusion metrics of infarction core and peripheral regions, and the state of collateral circulation. Spearman's correlations were analyzed for age and imaging markers between the different groups. The Chi-square test and Cramer's V coefficient analysis were performed for gender, collateral circulation status, NIHSS score, and other stroke risk factors. A total of 89 patients with AIS were divided into the good (mRS score ≤ 2) and poor prognosis groups (mRS score ≥ 3). There were differences in NIHSS score at the admission; relative MK (rMK), relative MD (rMD), relative CBF (rCBF) of the infarction core; relative mean transit time (rMTT), relative time to peak (rTTP), and relative CBF (rCBF) of peripheral regions; and collateral circulation status between the two groups (p < 0.05). Among them, the rMK of infarction lesions had the strongest correlation with the mRS score at 90 days after discharge (r = 0.545, p < 0.001). Perfusion and diffusion metrics could reflect the microstructure and blood flow characteristics of the lesion, which were the key factors for the salvage ability and prognosis of the infarction tissue. The characteristics of the infarction core and peripheral regions have different effects on the outcomes. Diffusion of infarction core has strong relations with the prognosis, whereas the time metrics (MTT, TTP) were more important for peripheral regions. MK had a more significant association with prognosis than MD. These factors were the primary markers influencing the prognosis of cerebral infarction patients.

Radiomics-Based Prediction of Collateral Status from CT Angiography of Patients Following a Large Vessel Occlusion Stroke.

A major driver of individual variation in long-term outcomes following a large vessel occlusion (LVO) stroke is the degree of collateral arterial circulation. We aimed to develop and evaluate machine-learning models that quantify LVO collateral status using admission computed tomography angiography (CTA) radiomics. We extracted 1116 radiomic features from the anterior circulation territories from admission CTAs of 600 patients experiencing an acute LVO stroke. We trained and validated multiple machine-learning models for the prediction of collateral status based on consensus from two neuroradiologists as ground truth. Models were first trained to predict (1) good vs. intermediate or poor, or (2) good vs. intermediate or poor collateral status. Then, model predictions were combined to determine a three-tier collateral score (good, intermediate, or poor). We used the receiver operating characteristics area under the curve (AUC) to evaluate prediction accuracy. We included 499 patients in training and 101 in an independent test cohort. The best-performing models achieved an averaged cross-validation AUC of 0.80 ± 0.05 for poor vs. intermediate/good collateral and 0.69 ± 0.05 for good vs. intermediate/poor, and AUC = 0.77 (0.67-0.87) and AUC = 0.78 (0.70-0.90) in the independent test cohort, respectively. The collateral scores predicted by the radiomics model were correlated with (rho = 0.45, p = 0.002) and were independent predictors of 3-month clinical outcome (p = 0.018) in the independent test cohort. Automated tools for the assessment of collateral status from admission CTA-such as the radiomics models described here-can generate clinically relevant and reproducible collateral scores to facilitate a timely treatment triage in patients experiencing an acute LVO stroke.

Abstract WP190: Comparison of Collateral Score to ASPECTS to Exclude "Very Large" Infarct Core Volumes in Anterior Circulation Large Vessel Occlusion Strokes at 0-24 Hours

Purpose: ASPECTS&lt;3 was an explicit exclusion criterion in the SELECT2 trial to exclude "very large" infarcts (&gt;100mL) for reperfusion using endovascular thrombectomy (EVT). While specific, ASPECTS&lt;3 may be too insensitive of a threshold on noncontrast CT at 0-24 hours (especially 0-6 hours). We aim to determine if CTA based Collateral Score (CS) can be a more sensitive surrogate marker for infarct core volume (ICV)&gt;100mL while maintaining similar specificity to ASPECTS. Methods: Retrospective analysis included consecutive stroke patients arriving within 24 hours of onset, with intracranial ICA and/or M1 occlusion on CTA, and had concurrent CT perfusion. RAPID AI software estimated ICV using the rCBF&lt;30% threshold. CS was scored on CTA using the method of Tan et al on a 4-point scale for % collaterals compared to contralateral side: 0 none, 1 &gt;0 but &lt;50%, 2 &gt;=50 but &lt;100%, and 3 100%. ROC curve analysis was used to find the optimal CS cutpoint with high specificity for ICV&gt;100mL. Sensitivity and specificity of that CS threshold vs ASPECTS&lt;3 were compared using the N-1 chi square test. Results: 164 patients were included with median (IQR) age of 74 (66-84), NIHSS of 20 (12-25), and time of onset-to-CT of 4 hours (2-7.5). The LVOs were 17 ICA (10.4%), 108 M1 (65.9%), and 39 both (23.8%), with median ICV of 12mL (0-45). 16 patients had ICV&gt;100mL (9.8%) with median of 136mL (105-172). Using ASPECTS&lt;3 identified only 1 of these (ICV of 118mL at 18.5 hours), sensitivity of 6.3% (95% CI: 0.16-30.2%), with no false positives, specificity of 100% (95% CI: 97.6-100%). ROC analysis for CS showed AUC=0.818 (p&lt;0.001), with maximal specificity at CS=0 (no visible collaterals). Using CS=0 identified 6 of these infarcts, sensitivity of 37.5% [95% CI: 15.2-64.6%], with 2 false positives, specificity of 98.7% [95% CI: 95.2-99.8%]. The 2 false positives were ICV of 97mL at 2 hours and 96mL at 3 hours. The improved sensitivity of CS=0 over ASPECTS&lt;3 was significant (p=0.036) while the difference in specificity was not (p=0.144). Conclusion: In our cohort of LVOs, CS=0 was a more sensitive surrogate marker for ICV&gt;100mL compared to ASPECTS&lt;3 while maintaining near 100% specificity. If confirmed in future prospective studies, CS=0 has the potential to further streamline patient selection for EVT.

Abstract 40: Relationship of Collateral Status With Clinical Outcomes in Endovascular Thrombectomy for Large Core Stroke: A SELECT2 Subanalysis

Background: Previous studies demonstrating association of collateral status with clinical outcomes after endovascular thrombectomy (EVT) excluded patients with large core infarcts. We analyzed the association of collateral status with clinical outcomes and EVT treatment effect in SELECT2. Methods: In SELECT2, a central core lab adjudicated CT-angiographic collateral status using collateral scores (CS) by Tan et al. Patients were stratified based on CS into poor (CS 0-1) vs good (CS 2-3) collaterals. The primary outcome was the distribution of modified Rankin Scale score at 90-day follow-up. Models were adjusted for core volume, ASPECTS in addition to age, stroke severity and time to randomization. Results: Of 352 patients, 180 received EVT. Median collateral status was 2(IQR 1-2). Patients presenting &lt;6h after last known well (LKW) (n=100) had poorer collaterals than those presenting at 6-24 hours (n=252), median 1 (1-2) vs 2 (1-2), p&lt;0.001. Collateral status inversely correlated with CTP core volume (Rho=-0.32, p&lt;0.0001), but not with CT ASPECTS (Rho=0.07, p=0.16). Overall, point estimates favored EVT in patients with poor (CS 0-1) [aGenOR: 1.32, 95% CI: 0.98-1.79, p=0.068] and good (CS 2-3) collaterals [aGenOR: 1.97, 95% CI: 1.43-2.72, p&lt;0.001] without significant heterogeneity [p-interaction=0.094]. However, in the earlier 0-6h time window, there was evidence of treatment effect hetermogeneity with a larger treatment effect when good collaterals were present [aGenOR: 4.10, 95% CI: 1.81-9.29] and an absent treatment effect when only poor collaterals were observed [aGenOR: 1.26, 95% CI: 0.79-1.99], p-interaction=0.023. In the late time window, (6-12h), the EVT treatment effect did not differ significantly between poor collaterals (aGenOR: 1.35, 95% CI: 0.91-2.01) and good collaterals (aGenOR: 1.78, 95% CI: 1.24-2.56, p-interaction=0.50). Conclusion: Collateral status was worse in large core patients presenting in early (&lt;6 hours) window; and correlated with ischemic core volume but not ASPECTS. Collaterals status modified EVT treatment effect in the early but not the late time window, in which both good and poor collaterals still benefited from EVT. Clinicaltrials.gov registration: NCT03876457

Abstract 129: An Automated Perfusion Collateral Score as a Tool to Predict Inter-Hospital Infarct Growth and Functional Outcome

Background: The accuracy of infarct growth prediction based on collateral scores, assessed on CT perfusion (CTP) and CT angiography, has been modest. We aimed to investigate the accuracy of infarct growth prediction using a novel collateral score based on two CTP parameters. Methods: Patients were included from CRISP2, a multi-center prospective cohort study of stroke patients with an anterior circulation large vessel occlusion who are transferred from a primary stroke center (PSC) to a comprehensive stroke center (CSC). CTP was performed at the PSC, and MRI was performed immediately after arrival at the CSC. The inter-hospital infarct growth rate was calculated as the difference between the co-registered infarct volumes on MRI and CTP divided by the time interval between the scans, with fast inter-hospital growth ≥ 5ml/h. The hypoperfusion intensity ratio (HIR) was defined as the ratio of the volumes of Tmax &gt;6s and Tmax &gt;10s, and the CBV index as the ratio of mean CBV values within the Tmax &gt;6s volume and the mean CBV in normal brain regions. An automated collateral score, based on the HIR and CBV index, was calculated from the CTP images at the PSC ( Fig 1A ). Results: Of 183 patients who were included, 111 (61%) were classified as having good collaterals and 72 (39%) as poor. Patients with poor collaterals experienced more rapid early infarct growth (median 2.19 ml/h IQR [0.32, 5.46] vs 7.92 [4.23, 16.23]; p-value &lt;0.001) and had worse 90-day functional outcomes (p=0.01). The combined collateral score, based on both HIR and CBVindex, showed a trend towards better prediction of fast infarct growth compared to HIR alone (HIR ≥ 0.40 = poor collaterals) and CBV alone (CBVindex &lt; 0.85 = poor collaterals) ( Fig 1B ). Conclusion: A perfusion collateral score, based on HIR and CBV index, is strongly associated with inter-hospital infarct growth rate and functional outcome. This automated tool can aid in patient selection for (neuroprotective) treatment strategies and transfer decisions.

Abstract 23: Results of CRISP2: CTP and CTA Assessment of Collaterals Predicts Inter-Hospital Infarct Growth

Background: Acute ischemic stroke patients with a large vessel occlusion (LVO) who present in a primary stroke center (PSC) without endovascular treatment capability, are often transferred to a comprehensive stroke center (CSC) for thrombectomy. CRISP2 was a prospective NIH funded multi-center study that aimed to determine characteristics associated with infarct growth during inter-hospital transfer. Methods: Data from patients with an anterior circulation LVO transferred to two CSCs were collected. A CT perfusion (CTP) was obtained at the PSC followed by an MRI at the CSC, before consideration of thrombectomy. The inter-hospital infarct growth rate was defined as the difference between the co-registered infarct volumes on MRI and CTP, divided by the time between the two scans. Multivariable logistic regression was used to determine characteristics associated with fast inter-hospital progression, defined as a growth rate ≥ 5ml/h. The hypoperfusion intensity ratio (HIR) was calculated automatically from the CTP, while the Tan collateral score was visually rated on baseline CT angiography. Results: A total of 183 patients, of whom 45% were fast progressors, were included. Baseline characteristics are presented in Table 1 . An HIR ≥0.40 identified fast infarct growth with a sensitivity of 0.76 (95%CI 0.65-0.84) and a specificity of 0.55 (95%CI 0.44-0.65), whereas for Tan 0-1 sensitivity was 0.37 (95%CI 0.27-0.48) and specificity 0.93 (95%CI 0.86-0.97). In multivariable models, baseline core volume and poor collaterals defined as either an HIR ≥ 0.40 (aOR = 2.18 (95%CI 1.10-4.42); p = 0.03) or a Tan score of 0-1 (aOR = 4.74 (95%CI 1.90-13.07); p=0.001), remained independently associated with fast infarct growth. Conclusion: An HIR ≥ 0.40 is a predictor of fast inter-hospital infarct growth with high sensitivity and a Tan score of 0-1 predicts fast growth with high specificity. These are promising imaging markers for patient selection in future neuroprotective trials.

Abstract TP207: Endovascular Treatment in the Late Time Window: Strict Perfusion Imaging Screening Criteria in Case Selection

Background and purpose: Clinical-imaging mismatch or perfusion imaging mismatch criteria per DAWN (Clinical Mismatch in the Triage of Wake Up and Late Presenting Strokes Undergoing Neurointervention With Trevo) or DEFUSE-3 (Endovascular Therapy Following Imaging Evaluation for Ischemic Stroke), respectively were recommended for case selection for endovascular treatment (EVT) of acute ischemic stroke (AIS) in the late time window outside 6 hours of stroke onset. We aimed to compare the clinical functional outcomes in EVT patients with and without strict perfusion imaging screening criteria in the late time window. Methods: AIS patients with anterior circulation large vessel occlusion (LVO) presenting within 6 to 24h hours after symptom onset were selected from a retrospectively collected thrombectomy cohort database (RESTORE). According to the imaging criteria of DAWN and DEFUSE-3, we compared proportions of patients with a favorable functional outcome (defined as a modified Rankin Scale [mRS] score of 0-2) at 90 days between the DAWN or DEFUSE-3 patients (D/D) and the non-DAWN or DEFUSE-3 (non-D/D) patients. Results: Among 265 adult patients with anterior circulation LVO who received EVT within 6 to 24 hours after symptom onset, 142 patients met either DAWN or DEFUSE-3 imaging criteria. D/D group independently predicted favorable functional outcome at 90 days (50.7% vs. 35.0%, aOR 0.514; 95% CI 0.273-0.966, p=0.039) adjusted for age, sex, previous stroke, hypertension, atrial fibrillation, coronary heart disease, pre-EVT collateral score, successful recanalization, onset to CT time. Conclusions: In AIS patients with anterior circulation LVO in the late time window, our real world data support the guideline that DAWN or DEFUSE-3 imaging criteria are strongly recommended for EVT case selection.

Automated evaluation of collateral circulation for outcome prediction in acute ischemic stroke

IntroductionThe assessment of collateral circulation in acute ischemic stroke management is essential. Modern tools, such as Brainomix's e-CTA, powered by artificial intelligence, provide detailed insights into collateral assessment. This retrospective study aims to identify factors contributing to favorable collateral status and compare outcomes between patients with good collaterals (grade 3) and fair collaterals (grade 0–2). MethodThis retrospective study included 97 patients admitted to the Stroke Unit at the Hospital de Clínicas of the Federal University of Paraná, Brazil, from September 2021 to January 2023. Comparative analyses involved demographic factors, cardiovascular risk factors, and the combined outcome of mortality and moderate to severe disability at discharge, 30-day, and 90-day follow-ups. ResultsAmong the 97 cases, 58.8 % showed 'good collaterals' with a grade 3 status. Variables affecting collateral status included age (p = 0.042), neutrophil-lymphocyte ratio (p = 0.005), and initial NIHSS scores (p<0.001). The presence of good collaterals according to e-CTA reduced the odds of death and moderate-severe disability at discharge (p = 0.003; OR 0.27) and at 30 days (p = 0.015; OR 0.33), although this effect diminished at the 90-day mark after multivariate analysis. DiscussionAutomated collateral assessment through e-CTA is a valuable tool in acute ischemic stroke evaluation. Good e-CTA collateral score serve as a promising imaging biomarker, guiding informed clinical decisions during Stroke Unit hospitalizations. This study highlights the relationship between collaterals and stroke outcomes and underscores the potential for AI-driven tools to enhance stroke care management.

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

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. 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. 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. 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.

Risk Factors for Massive Cerebral Infarction in Pediatric Patients With Moyamoya Disease

BackgroundTo explore the risk factors for preoperative massive cerebral infarction (MCI) in pediatric patients with moyamoya disease (MMD). MethodsPediatric patients with MMD treated between 2017 and 2022 were enrolled. Logistic regression analysis was performed to identify risk factors for MCI among the patients, and a nomogram was constructed to identify potential predictors of MCI. Receiver operating characteristic (ROC) curves and areas under the curves were calculated to determine the effects of different risk factors. ResultsThis study included 308 pediatric patients with MMD, including 36 with MCI. The MCI group exhibited an earlier age of onset than the non-MCI group. Significant intergroup differences were observed in familial MMD history, postcirculation involvement, duration from diagnosis to initiation of treatment, Suzuki stage, magnetic resonance angiography (MRA) score, collateral circulation score, and RNF213 p.R4810K variations. Family history, higher MRA score, lower collateral circulation score, and RNF213 p.R4810K variations were substantial risk factors for MCI in pediatric patients with MMD. The nomogram demonstrated excellent discrimination and calibration capabilities. The integrated ROC model, which included all the abovementioned four variables, showed superior diagnostic precision with a sensitivity of 67.86%, specificity of 87.01%, and accuracy of 85.11%. ConclusionsThis study showed that family history, elevated MRA score, reduced collateral circulation score, and RNF213 p.R4810K variations are risk factors for MCI in pediatric patients with MMD. The synthesized model including these variables demonstrated superior predictive efficacy; thus, it can facilitate early identification of at-risk patients and timely initiation of appropriate interventions.

Multilevel Multimodal Framework for Automatic Collateral Scoring in Brain Stroke

Multilevel Multimodal Framework for Automatic Collateral Scoring in Brain Stroke

New insight in massive cerebral infarction predictions after anterior circulation occlusion

To predict massive cerebral infarction (MCI) occurrence after anterior circulation occlusion (ACO) by cASPECTS-CTA-CS (combined ASPECTS and CTA-CS). Of 185 cerebral infarction patients with the ACO, their collateral circulation scores from CT angiography (CTA) images in two groups (MCI and non-MCI) were evaluated using Alberta Stroke Program Early CT Score (ASPECTS) and CT angiography collateral score (CTA-CS) approaches. The cASPECTS-CTA-CS was validated internally using the bootstrap sampling method with 1000 bootstrap repetitions and compared to CTA-CS. Receiver-operating characteristic curve (ROC), clinical impact curve (CIC), and decision curve analysis (DCA) strategies were used to assess the clinical practicality and predictability of both approaches (cASPECTS-CTA-CS and CTA-CS). Using net reclassification improvement (NRI) and integrated discrimination improvement (IDI) analyses, discrimination levels of the cASPECTS-CTA-CS were compared with CTA-CS. Classification and regression tree (CART) analyses was conducted to identify the best predictive values and identify subgroup of MCI. The discrimination ability of collateral circulation evaluation score using the cASPECTS-CTA-CS [AUC: 0.918, 95% confidence interval (CI): 0.869–0.967, P < 0.01; NRI: 0.200, 95% CI: −0.104 to 0.505, P = 0.197; and IDI: 0.107, 95% CI: 0.035–0.178, P = 0.004] was better than CTA-CS alone (AUC: 0.885, 95% CI: 0.833–0.937, P < 0.01). DCA indicated the net benefits of the cASPECTS-CTA-CS approach was higher than CTA-CS alone when the threshold probability range over 20%. CIC analyses showed that the number of high risks and true positives were in agreement when the threshold probability > 80%. Less than 23 of cASPECTS-CTA-CS by CART was important factor in determining MCI occurrence, and ASPECTS < 7 was followed factor. The cASPECTS-CTA-CS approach cumulatively predicted MCI after ACO.

Clot burden score and collateral score on high resolution magnetic resonance

Clot burden score and collateral score on high resolution magnetic resonance

Effect of collateral status on the outcomes of endovascular treatment of acute basilar artery occlusion due to large-artery atherosclerosis.

Authors of this study aimed to evaluate the effects of collateral status on the prognostic value of endovascular treatment (EVT) in patients with basilar artery occlusion (BAO) due to large-artery atherosclerosis (LAA). The study included 312 patients from the BASILAR (Endovascular Treatment for Acute Basilar Artery Occlusion Study) registry who had undergone EVT for acute BAO due to LAA and whose composite collateral scores were available. The effects of collateral status on EVT were assessed based on the composite collateral score (0-2 vs 3-5). The primary outcome was a favorable outcome (modified Rankin Scale score of 0-3) at 90 days. The composite collateral score was 0-2 in 130 patients and 3-5 in 182. A good collateral status (composite collateral score 3-5) was associated with a favorable outcome (66/182 [36.3%] vs 31/130 [23.8%], adjusted odds ratio [aOR] 2.21, 95% CI 1.18-4.14, p = 0.014). A lower baseline National Institutes of Health Stroke Scale (NIHSS) score was an independent predictor of a favorable outcome in the poor collateral status group (aOR 0.91, 95% CI 0.87-0.96, p = 0.001). In the good collateral status group, there was a significant correlation between favorable outcomes and a younger age (aOR 0.96, 95% CI 0.92-0.99, p = 0.016), lower baseline NIHSS score (aOR 0.89, 95% CI 0.85-0.93, p < 0.001), lower proportion of diabetes mellitus (aOR 0.31, 95% CI 0.13-0.75, p = 0.009), and shorter procedure time (aOR 0.99, 95% CI 0.98-1.00, p = 0.003). A good collateral status was a strong prognostic factor after EVT in patients with BAO underlying LAA. A shorter procedure time was associated with favorable outcomes in patients with a good collateral status.