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

Combining Early Ischemic Change and Collateral Extent for Functional Outcomes After Endovascular Therapy: An Analysis From AcT Trial

BACKGROUND

Early ischemic change and collateral extent are colinear with ischemic core volume (ICV). We investigated the relationship between a combined score using the Alberta Stroke Program Early Computed Tomography Score and multiphase computed tomography angiography (mCTA) collateral extent, named mCTA-ACE score, on functional outcomes in endovascular therapy-treated patients.

METHODS

We performed a post hoc analysis of a subset of endovascular therapy-treated patients from the Alteplase Compared to Tenecteplase trial which was conducted between December 2019 and January 2022 at 22 centers across Canada. Ten-point mCTA collateral corresponding to M2 to M6 regions of the Alberta Stroke Program Early Computed Tomography Score grid was evaluated as 0 (poor), 1 (moderate), or 2 (normal) and additively combined with the 10-point Alberta Stroke Program Early Computed Tomography Score to produce a 20-point mCTA-ACE score. We investigated the association of mCTA-ACE score with modified Rankin Scale score ≤2 and return to prestroke level of function at 90 to 120 days using mixed-effects logistic regression. In the subset of patients who underwent baseline computed tomography perfusion imaging, we compared the mCTA-ACE score and ICV for outcome prediction.

RESULTS

Among 1577 intention-to-treat population in the trial, 368 (23%; 179 men; median age, 73 years) were included, with Alberta Stroke Program Early Computed Tomography Score, mCTA collateral, and combination of both (mCTA-ACE score: median [interquartile range], 8 [7-10], 9 [8-10], and 17 [16-19], respectively). The probability of modified Rankin Scale score ≤2 and return to prestroke level of function increased for each 1-point increase in mCTA-ACE score (odds ratio, 1.16 [95% CI, 1.06-1.28] and 1.22 [95% CI, 1.06-1.40], respectively). Among 173 patients in whom computed tomography perfusion data was assessable, the mCTA-ACE score was inversely correlated with ICV (ρ=-0.46; P<0.01). The mCTA-ACE score was comparable to ICV to predict a modified Rankin Scale score ≤2 and return to prestroke level of function (C statistics 0.71 versus 0.69 and 0.68 versus 0.64, respectively).

CONCLUSIONS

The mCTA-ACE score had a significant positive association with functional outcomes after endovascular therapy and had a similar predictive performance as ICV.

Computed tomography perfusion deficit volume predicts the functional outcome of endovascular therapy for basilar artery occlusion

OBJECTIVES

To investigate the relationship between baseline computed tomography perfusion deficit volumes and functional outcomes in patients with basilar artery occlusion (BAO) undergoing endovascular therapy.

METHODS

This was a single-center study in which the data of 64 patients with BAO who underwent endovascular therapy were retrospectively analyzed. All the patients underwent multi-model computed tomography on admission. The posterior-circulation Acute Stroke Prognosis Early Computed Tomography Score was applied to assess the ischemic changes. Perfusion deficit volumes were obtained using Syngo.via software. The primary outcome of the analysis was a good functional outcome (90-day modified Rankin Scale score ≤ 3). Logistic regression and receiver operating characteristic curves were used to explore predictors of functional outcome.

RESULTS

A total of 64 patients (median age, 68 years; 72 % male) were recruited, of whom 26 (41 %) patients achieved good functional outcomes, while 38 (59 %) had poor functional outcomes. Tmax > 10 s, Tmax > 6 s, and rCBF < 30 % volume were independent predictors of good functional outcomes (odds ratio range, 1.0-1.2; 95 % confidence interval [CI], 1.0-1.4]) and performed well in the receiver operating characteristic curve analyses, exhibiting positive prognostic value; the areas under the curve values were 0.85 (95 % CI, 0.75-0.94), 0.81 (95 % CI, 0.70-0.90), and 0.78 (95 % CI, 0.67-0.89).

CONCLUSION

Computed tomography perfusion deficit volume represents a valuable tool in predicting high risk of disability and mortality in patients with BAO after endovascular treatment.

Comparison of two automated CT perfusion software packages in patients with ischemic stroke presenting within 24 h of onset

Background

We compared the ischemic core and hypoperfused tissue volumes estimated by RAPID and JLK-CTP, a newly developed automated computed tomography perfusion (CTP) analysis package. We also assessed agreement between ischemic core volumes by two software packages against early follow-up infarct volumes on diffusion-weighted images (DWI).

Methods

This retrospective study analyzed 327 patients admitted to a single stroke center in Korea from January 2021 to May 2023, who underwent CTP scans within 24 h of onset. The concordance correlation coefficient (ρ) and Bland-Altman plots were utilized to compare the volumes of ischemic core and hypoperfused tissue volumes between the software packages. Agreement with early (within 3 h from CTP) follow-up infarct volumes on diffusion-weighted imaging (n = 217) was also evaluated.

Results

The mean age was 70.7 ± 13.0 and 137 (41.9%) were female. Ischemic core volumes by JLK-CTP and RAPID at the threshold of relative cerebral blood flow (rCBF) < 30% showed excellent agreement (ρ = 0.958 [95% CI, 0.949 to 0.966]). Excellent agreement was also observed for time to a maximum of the residue function (T max) > 6 s between JLK-CTP and RAPID (ρ = 0.835 [95% CI, 0.806 to 0.863]). Although early follow-up infarct volume showed substantial agreement in both packages (JLK-CTP, ρ = 0.751 and RAPID, ρ = 0.632), ischemic core volumes at the threshold of rCBF <30% tended to overestimate ischemic core volumes.

Conclusion

JLK-CTP and RAPID demonstrated remarkable concordance in estimating the volumes of the ischemic core and hypoperfused area based on CTP within 24 h from onset.

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

BACKGROUND AND PURPOSE

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Prolonged venous transit on perfusion imaging is associated with higher odds of mortality in successfully reperfused patients with large vessel occlusion stroke

BACKGROUND

Poor venous outflow (VO) profiles are associated with unfavorable outcomes in patients with acute ischemic stroke caused by large vessel occlusion (AIS-LVO), despite achieving successful reperfusion. The objective of this study is to assess the association between mortality and prolonged venous transit (PVT), a novel visual qualitative VO marker on CT perfusion (CTP) time to maximum (Tmax) maps.

METHODS

We performed a retrospective analysis of prospectively collected data from consecutive adult patients with AIS-LVO with successful reperfusion (modified Thrombolysis in Cerebral Infarction 2b/2c/3). PVT+ was defined as Tmax ≥10 s timing on CTP Tmax maps in at least one of the following: superior sagittal sinus (proximal venous drainage) and/or torcula (deep venous drainage). PVT- was defined as lacking this in both regions. The primary outcome was mortality at 90 days. In a 1:1 propensity score-matched cohort, regressions were performed to determine the effect of PVT on 90-day mortality.

RESULTS

In 127 patients of median (IQR) age 71 (64-81) years, mortality occurred in a significantly greater proportion of PVT+ patients than PVT- patients (32.5% vs 12.6%, P=0.01). This significant difference persisted after matching (P=0.03). PVT+ was associated with a significantly increased likelihood of 90-day mortality (OR 1.22 (95% CI 1.02 to 1.46), P=0.03) in the matched cohort.

CONCLUSIONS

PVT+ was significantly associated with 90-day mortality despite successful reperfusion therapy in patients with AIS-LVO. PVT is a simple VO profile marker with potential as an adjunctive metric during acute evaluation of AIS-LVO patients. Future studies will expand our understanding of using PVT in the evaluation of patients with AIS-LVO.

The collateral map: prediction of lesion growth and penumbra after acute anterior circulation ischemic stroke

OBJECTIVES

This study evaluated the collateral map's ability to predict lesion growth and penumbra after acute anterior circulation ischemic strokes.

METHODS

This was a retrospective analysis of selected data from a prospectively collected database. The lesion growth ratio was the ratio of the follow-up lesion volume to the baseline lesion volume on diffusion-weighted imaging (DWI). The time-to-maximum (Tmax)/DWI ratio was the ratio of the baseline Tmax  > 6 s volume to the baseline lesion volume. The collateral ratio was the ratio of the hypoperfused lesion volume of the phase_FU (phase with the hypoperfused lesions most approximate to the follow-up DWI lesion) to the hypoperfused lesion volume of the phase_baseline of the collateral map. Multiple logistic regression analyses were conducted to identify independent predictors of lesion growth. The concordance correlation coefficients of Tmax/DWI ratio and collateral ratio for lesion growth ratio were analyzed.

RESULTS

Fifty-two patients, including twenty-six males (mean age, 74 years), were included. Intermediate (OR, 1234.5; p < 0.001) and poor collateral perfusion grades (OR, 664.7; p = 0.006) were independently associated with lesion growth. Phase_FUs were immediately preceded phases of the phase_baselines in intermediate or poor collateral perfusion grades. The concordance correlation coefficients of the Tmax/DWI ratio and collateral ratio for the lesion growth ratio were 0.28 (95% CI, 0.17-0.38) and 0.88 (95% CI, 0.82-0.92), respectively.

CONCLUSION

Precise prediction of lesion growth and penumbra can be possible using collateral maps, allowing for personalized application of recanalization treatments. Further studies are needed to generalize the findings of this study.

CLINICAL RELEVANCE STATEMENT

Precise prediction of lesion growth and penumbra can be possible using collateral maps, allowing for personalized application of recanalization treatments.

KEY POINTS

• Cell viability in cerebral ischemia due to proximal arterial steno-occlusion mainly depends on the collateral circulation. • The collateral map shows salvageable brain extent, which can survive by recanalization treatments after acute anterior circulation ischemic stroke. • Precise estimation of salvageable brain makes it possible to make patient-specific treatment decision.

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

BACKGROUND AND PURPOSE

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

Preserved Corticospinal Tract Revealed by Acute Perfusion Imaging Relates to Better Outcome After Thrombectomy in Stroke

BACKGROUND

The indication for mechanical thrombectomy (MT) in stroke patients with large vessel occlusion has been constantly expanded over the past years. Despite remarkable treatment effects at the group level in clinical trials, many patients remain severely disabled even after successful recanalization. A better understanding of this outcome variability will help to improve clinical decision-making on MT in the acute stage. Here, we test whether current outcome models can be refined by integrating information on the preservation of the corticospinal tract as a functionally crucial white matter tract derived from acute perfusion imaging.

METHODS

We retrospectively analyzed 162 patients with stroke and large vessel occlusion of the anterior circulation who were admitted to the University Medical Center Lübeck between 2014 and 2020 and underwent MT. The ischemic core was defined as fully automatized based on the acute computed tomography perfusion with cerebral blood volume data using outlier detection and clustering algorithms. Normative whole-brain structural connectivity data were used to infer whether the corticospinal tract was affected by the ischemic core or preserved. Ordinal logistic regression models were used to correlate this information with the modified Rankin Scale after 90 days.

RESULTS

The preservation of the corticospinal tract was associated with a reduced risk of a worse functional outcome in large vessel occlusion-stroke patients undergoing MT, with an odds ratio of 0.28 (95% CI, 0.15-0.53). This association was still significant after adjusting for multiple confounding covariables, such as age, lesion load, initial symptom severity, sex, stroke side, and recanalization status.

CONCLUSIONS

A preinterventional computed tomography perfusion-based surrogate of corticospinal tract preservation or disconnectivity is strongly associated with functional outcomes after MT. If validated in independent samples this concept could serve as a novel tool to improve current outcome models to better understand intersubject variability after MT in large vessel occlusion stroke.

Automated advanced imaging in acute ischemic stroke. Certainties and uncertainties

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

Severely Hypoperfused Brain Tissue Correlates with Final Infarct Volume Despite Recanalization in DMVO Stroke

Objectives

We sought to assess whether there were any parameter(s) on baseline computed-tomography-perfusion (CTP) strongly correlating with final-infarct-volume, and infarct volume progression after endovascular recanalization of acute ischemic stroke (AIS) with primary distal, medium vessel occlusion (DMVO).

Materials and Methods

We performed a retrospective analysis of consecutive AIS patients who were successfully recanalized by thrombectomy for DMVO. By comparing baseline CTP and follow-up MRI, we evaluated the correlation between baseline infarct and hypoperfusion volumes, and final infarct volume and infarct volume progression. We also examined their effect on good clinical outcome at 3 months (defined as an mRS score of 0 to 2).

Results

Between January 2018 and January 2021, 38 patients met the inclusion criteria (76% [29/38] female, median age 75 [66-86] years). Median final infarct volume and infarct volume progression were 8.4 mL [IQR: 5.2-44.4] and 7.2 mL [IQR: 4.3-29.1] respectively. TMax > 10 sec volume was strongly correlated with both (r = 0.831 and r = 0.771 respectively, p < 0.0001), as well as with good clinical outcome (-0.5, p = 0.001). A higher baseline TMax > 10 sec volume increased the probability of a higher final-infarct-volume (r2 = 0.690, coefficient = 0.83 [0.64-1.00], p < 0.0001), whereas it decreased the probability of good clinical outcome at 3 months (odds ratio = -0.67 [-1.17 to -0.18], p = 0.008).

Conclusion

TMax > 10 sec volume on baseline CTP correlates strongly with final infarct volume as well as with clinical outcome after mechanical thrombectomy for an AIS with DMVO.

Magnetic Resonance Perfusion-Weighted Imaging in Predicting Hemorrhagic Transformation of Acute Ischemic Stroke: A Retrospective Study

Hemorrhagic transformation (HT) is one of the common complications in patients with acute ischemic stroke (AIS). This study aims to investigate the value of different thresholds of Tmax generated from perfusion-weighted MR imaging (PWI) and the apparent diffusion coefficient (ADC) value in the prediction of HT in AIS. A total of 156 AIS patients were enrolled in this study, with 55 patients in the HT group and 101 patients in non-HT group. The clinical baseline data and multi-parametric MRI findings were compared between HT and non-HT groups to identify indicators related to HT. The optimal parameters for predicting HT and the corresponding cutoff values were obtained using the receiver operating characteristic curve analysis of the volumes of ADC < 620 × 10-6 mm2/s and Tmax > 6 s, 8 s, and 10 s. The results showed that the volumes of ADC < 620 × 10-6 mm2/s and Tmax > 6 s, 8 s, and 10 s in the HT group were all significantly larger than that in the non-HT group and were all independent risk factors for HT. Early measurement of the volume of Tmax > 10 s had the highest value, with a cutoff lesion volume of 10.5 mL.

Assessing the diagnostic accuracy of CT perfusion: a systematic review

Background and purpose

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

Methods

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

Results

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

Conclusion

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

Development of machine learning models for predicting outcome in patients with distal medium vessel occlusions: a retrospective study

Background

While numerous prognostic factors have been reported for large vessel occlusion (LVO)-acute ischemic stroke (AIS) patients, the same cannot be said for distal medium vessel occlusions (DMVOs). We used machine learning (ML) algorithms to develop a model predicting the short-term outcome of AIS patients with DMVOs using demographic, clinical, and laboratory variables and baseline computed tomography (CT) perfusion (CTP) postprocessing quantitative parameters.

Methods

In this retrospective cohort study, consecutive patients with AIS admitted to two comprehensive stroke centers between January 1, 2017, and September 1, 2022, were screened. Demographic, clinical, and radiological data were extracted from electronic medical records. The clinical outcome was divided into two categories, with a cut-off defined by the median National Institutes of Health Stroke Scale (NIHSS) shift score. Data preprocessing involved addressing missing values through imputation, scaling with a robust scaler, normalization using min-max normalization, and encoding of categorical variables. The data were split into training and test sets (70:30), and recursive feature elimination (RFE) was employed for feature selection. For ML analyses, XGBoost, LightGBM, CatBoost, multi-layer perceptron, random forest, and logistic regression algorithms were utilized. Performance evaluation involved the receiver operating characteristic (ROC) curve, precision-recall curve (PRC), the area under these curves, accuracy, precision, recall, and Matthews correlation coefficient (MCC). The relative weights of predictor variables were examined using Shapley additive explanations (SHAP).

Results

Sixty-nine patients were included and divided into two groups: 35 patients with favorable outcomes and 34 patients with unfavorable outcomes. Utilizing ten selected features, the XGBoost algorithm achieved the best performance in predicting unfavorable outcomes, with an area under the ROC curve (AUROC) of 0.894 and an area under the PRC curve (AUPRC) of 0.756. The SHAP analysis ranked the following features in order of importance for the XGBoost model: mismatch volume, time-to-maximum of the tissue residue function (Tmax) >6 s, diffusion-weighted imaging (DWI) volume, neutrophil-to-platelet ratio (NPR), mean corpuscular volume (MCV), Tmax >10 s, hemoglobin, potassium, hypoperfusion index (HI), and Tmax >8 s.

Conclusions

Our ML models, trained on baseline quantitative laboratory and CT parameters, accurately predicted the short-term outcome in patients with DMVOs. These findings may aid clinicians in predicting prognosis and may be helpful for future research.

CT perfusion - an up-to-date element of the contemporary multimodal diagnostic approach to acute ischemic stroke

Acute ischemic stroke is of great clinical and societal importance due to its high incidence and mortality rates, as well as the fact that those who are affected suffer from permanent acquired disability. Modern trends explicitly state that the disease's diagnostic plan should use a multidisciplinary approach. The therapeutic steps that ultimately determine the clinical outcome are defined by an accurate diagnosis of acute ischemic stroke. Highly specialized facilities for the diagnosis and treatment of acute ischemic stroke (Stroke Units) are in operation in countries that make significant investments in healthcare. Imaging the brain parenchyma at risk, or the so-called ischemic penumbra, in acute ischemic stroke is one of the main tasks of the multimodal computed tomography approach. The most rapid method for imaging the ischemic penumbra is computed tomography perfusion (CTP). This modality provides information about the anatomy and the physiologic state of the brain parenchyma.

Parenchymal Blood Volume Changes Immediately After Endovascular Thrombectomy Predict Futile Recanalization in Patients with Emergent Large Vessel Occlusion

OBJECTIVE

More than one third of acute ischemic stroke (AIS) patients do not recover to functional independence even if endovascular thrombectomy (EVT) is performed rapidly and successfully. This suggests that angiographic recanalization does not necessarily lead to tissue reperfusion. Although recognition of reperfusion status after EVT is pivotal for optimal postoperative management, reperfusion imaging assessment immediately after recanalization has not been fully investigated. The present study aimed to evaluate whether reperfusion status based on parenchymal blood volume (PBV) assessment after angiographic recanalization influences infarct growth and functional outcome in patients who have undergone EVT following AIS.

METHODS

Seventy-nine patients who underwent successful EVT for AIS were retrospectively analyzed. PBV maps were acquired from flat-panel detector computed tomography (CT) perfusion images before and after angiographic recanalization. Reperfusion status was assessed from PBV values and their changes in regions of interest and collateral score.

RESULTS

Post-EVT PBV ratio and ΔPBV ratio, as PBV parameters indicating the degree of reperfusion, were significantly lower in the unfavorable prognosis group (P < 0.01 each). Poor reperfusion on PBV mapping was associated with significantly longer puncture-to-recanalization time, lower collateral score, and higher frequency of infarct growth. Logistic regression analysis identified low collateral score and low ΔPBV ratio as associated with poor prognosis after EVT (odds ratios, 2.48, 3.72; 95% confidence intervals, 1.06-5.81, 1.20-11.53; P = 0.04, 0.02, respectively).

CONCLUSIONS

Poor reperfusion in severely hypoperfused territories on PBV mapping immediately after recanalization may predict infarct growth and unfavorable prognosis in patients who undergo EVT following AIS.

Tmax volume can predict clinical type in patients with acute ischemic stroke

OBJECTIVE

Endovascular therapy (EVT) is performed for acute ischemic stroke (AIS) with large vessel occlusion (LVO), however, the treatment strategies and clinical outcomes differ between cardiac embolism (CE) and intracranial arteriosclerosis-derived LVO (ICAS-LVO). We analyzed whether the time-to-max (Tmax) volume derived from perfusion imaging predicted clinical classification in AIS patients before EVT.

METHODS

Consecutive AIS patients with anterior circulation LVO evaluated by automated imaging software were retrospectively identified. Patients were classified into a CE group and an ICAS-LVO group, and parameters were compared between groups.

RESULTS

Thirty-nine patients were included and Tmax volume and Tmax > 6 s volume/Tmax > 4 s volume were significantly greater in the CE group than in the ICAS-LVO group (Tmax > 4 s volume: 261 mL vs. 149 mL, p = .01, Tmax > 6 s volume: 143 mL vs. 59 mL, p = .001, Tmax > 6 s volume/Tmax > 4 s volume: 0.59 vs. 0.40, p < .001). Multiple logistic regression analysis indicated an association between clinical classification and high Tmax > 6 s volume/Tmax > 4 s volume (p = .04).

CONCLUSION

The Tmax volume derived from perfusion imaging predicts the clinical classification of AIS patients before EVT.

Non-contrast CT radiomics and machine learning for outcomes prediction of patients with acute ischemic stroke receiving conventional treatment

PURPOSE

Accurate prediction of outcomes for patients with acute ischemic stroke (AIS) is crucial for clinical decision-making. In this study, we developed prediction models based on non-contrast computed tomography (NCCT) radiomics and clinical features to predict the modified Rankin Scale (mRS) six months after hospital discharge.

METHOD

A two-center retrospective cohort of 240 AIS patients receiving conventional treatment was included. Radiomics features of the infarct area were extracted from baseline NCCT scans. We applied Kruskal-Wallis (KW) test and recursive feature elimination (RFE) to select features for developing clinical, radiomics, and fusion models (with clinical data and radiomics features), using support vector machine (SVM) algorithm. The prediction performance of the models was assessed by accuracy, sensitivity, specificity, F1 score, and receiver operating characteristic (ROC) curve. Shapley Additive exPlanations (SHAP) was applied to analyze the interpretability and predictor importance of the model.

RESULTS

A total of 1454 texture features were extracted from the NCCT images. In the test cohort, the ROC analysis showed that the radiomics model and the fusion model showed AUCs of 0.705 and 0.857, which outperformed the clinical model (0.643), with the fusion model exhibiting the best performance. Additionally, the accuracy and sensitivity of the fusion model were also the best among the models (84.8% and 93.8%, respectively).

CONCLUSIONS

The model based on NCCT radiomics and machine learning has high predictive efficiency for the prognosis of AIS patients receiving conventional treatment, which can be used to assist early personalized clinical therapy.

Comparing the predictive value of quantitative magnetic resonance imaging parametric response mapping and conventional perfusion magnetic resonance imaging for clinical outcomes in patients with chronic ischemic stroke

Predicting clinical outcomes after stroke, using magnetic resonance imaging (MRI) measures, remains a challenge. The purpose of this study was to investigate the prediction of long-term clinical outcomes after ischemic stroke using parametric response mapping (PRM) based on perfusion MRI data. Multiparametric perfusion MRI datasets from 30 patients with chronic ischemic stroke were acquired at four-time points ranging from V2 (6  weeks) to V5 (7  months) after stroke onset. All perfusion MR parameters were analyzed using the classic whole-lesion approach and voxel-based PRM at each time point. The imaging biomarkers from each acquired MRI metric that was predictive of both neurological and functional outcomes were prospectively investigated. For predicting clinical outcomes at V5, it was identified that PRM_Tmax-, PRM_rCBV-, and PRM_rCBV+ at V3 were superior to the mean values of the corresponding maps at V3. We identified correlations between the clinical prognosis after stroke and MRI parameters, emphasizing the superiority of the PRM over the whole-lesion approach for predicting long-term clinical outcomes. This indicates that complementary information for the predictive assessment of clinical outcomes can be obtained using PRM analysis. Moreover, new insights into the heterogeneity of stroke lesions revealed by PRM can help optimize the accurate stratification of patients with stroke and guide rehabilitation.