The role of automated computed topography perfusion in prediction of hemorrhagic transformation after acute ischemic stroke

Predictive value of CT imaging features on the risk of hemorrhagic transformation after mechanical thrombectomy for acute ischemic stroke with large vessel obstruction

OBJECTIVE

To investigate the predictive value of computer tomography (CT) imaging features for the risk of hemorrhagic transformation (HT) after mechanical thrombectomy for acute ischemic stroke with large vessel obstruction (AIS-LVO).

METHODS

A total of 135 patients with AIS-LVO diagnosed and treated in our hospital from August 2021 to May 2023 were selected as the research subjects. Their clinical data were retrospectively analyzed. Mechanical thrombectomy was performed in all patients. The patients were divided into the HT group (n = 27) and the non-HT group (n = 108) according to whether HT occurred within 24 h after thrombectomy. CT examination was performed after mechanical thrombectomy in the two groups, and the changes in CT imaging indexes in the two groups were observed. Logistic regression was used to analyze the influencing factors and a prediction model was constructed based on the influencing factors. The receiver operating characteristic (ROC) curve was established to analyze the predictive value. Additionally, ROC curve was used to analyze the diagnostic value of serum CT imaging features.

RESULTS

Compared with the non-HT group, the proportion of atrial fibrillation history in the HT group was significantly increased, and the National Institute of Health Stroke Scale (NIHSS) score and galectin-3 (Gal-3) level were significantly increased before thrombectomy (P < 0.01). Compared with the non-HT group, the proportion of exudation of contrast medium and Hyperdense Middle Cerebral Artery Sign (HMCAS) in the HT group was significantly increased, time to peak (TTP) was significantly prolonged, and cerebral blood flow (CBF) was significantly decreased (P < 0.001). The history of atrial fibrillation, NIHSS score before thrombectomy, Gal-3, contrast agent exudation, HMCAS, TTP and CBF were the influencing factors of postoperative HT after mechanical thrombectomy in AIS-LVO (P < 0.05). Based on the results of multivariate logistic regression analysis, a prediction model was established as follows: Logit (P) = -3.520 + 1.529 × history of atrial fibrillation + 0.968 × NIHSS score before thrombectomy + 0.806 × Gal-3 + 1.134 × contrast agent exudation + 2.146 × HMCAS + 0.684 × TTP-0.725 × CBF. The area under the curve (AUC) of the logistic prediction model for predicting HT after AIS-LVOLVO mechanical thrombectomy was 0.873 (95% CI 0.817-0.929) with a sensitivity of 78.75% and a specificity of 83.33%, indicating that the prediction model had good prediction efficiency. The AUC of TTP and CBF alone in predicting HT after mechanical thrombectomy in AIS-LVO patients was 0.728 and 0.736, respectively. The AUC of combined detection was 0.783, and the combined detection had a high diagnostic value for HT after mechanical thrombectomy in AIS-LVO patients.

CONCLUSION

The combined detection of TTP and CBF of CT imaging features had certain diagnostic value for HT in AIS-LVO patients after mechanical thrombectomy. The logistic prediction model based on these influencing factors had a high diagnostic value for HT after mechanical thrombectomy.

Association between CT Perfusion Parameters and Hemorrhagic Transformation after Endovascular Treatment in Acute Ischemic Stroke: Results from the ESCAPE-NA1 Trial

BACKGROUND AND PURPOSE

Hemorrhagic transformation can occur as a complication of endovascular treatment for acute ischemic stroke. This study aimed to determine whether ischemia depth as measured by admission CTP metrics can predict the development of hemorrhagic transformation at 24 hours.

MATERIALS AND METHODS

Patients with baseline CTP and 24-hour follow-up imaging from the ESCAPE-NA1 trial were included. RAPID software was used to generate CTP volume maps for relative CBF, CBV, and time-to-maximum at different thresholds. Hemorrhage on 24-hour imaging was classified according to the Heidelberg system, and volumes were calculated. Univariable and multivariable regression analyses assessed the association between CTP lesion volumes and hemorrhage/hemorrhage subtypes.

RESULTS

Among 408 patients with baseline CTP, 142 (35%) had hemorrhagic transformation at 24-hour follow-up, with 89 (63%) classified as hemorrhagic infarction (HI1/HI2), and 53 (37%), as parenchymal hematoma (PH1/PH2). Patients with HI or PH had larger volumes of low relative CBF and CBV at each threshold compared with those without hemorrhage. After we adjustied for baseline and treatment variables, only increased relative CBF <30% lesion volume was associated with any hemorrhage (adjusted OR, 1.14; 95% CI, 1.02-1.27 per 10 mL), as well as parenchymal hematoma (adjusted OR, 1.23; 95% CI, 1.06-1.43 per 10 mL). No significant associations were observed for hemorrhagic infarction.

CONCLUSIONS

Larger "core" volumes of relative CBF <30% were associated with an increased risk of PH following endovascular treatment. This particular metric, in conjunction with other clinical and imaging variables, may, therefore, help estimate the risk of post-endovascular treatment hemorrhagic complications.

Low blood flow ratio is associated with hemorrhagic transformation secondary to mechanical thrombectomy in patients with acute ischemic stroke

BACKGROUND AND PURPOSE

A significant decrease of cerebral blood flow (CBF) is a risk factor for hemorrhagic transformation (HT) in acute ischemic stroke (AIS). This study aimed to ascertain whether the ratio of different CBF thresholds derived from computed tomography perfusion (CTP) is an independent risk factor for HT after mechanical thrombectomy (MT).

METHODS

A retrospective single center cohort study was conducted on patients with AIS undergoing MT at the First Affiliated Hospital of Wenzhou Medical University from August 2018 to December 2023. The perfusion parameters before thrombectomy were obtained according to CTP automatic processing software. The low blood flow ratio (LFR) was defined as the ratio of brain volume with relative CBF <20 % over volume with relative CBF <30 %. HT was evaluated on the follow-up CT images. Binary logistic regression was used to analyze the correlation between parameters that differ between the two groups with regards to HT occurrence. The predictive efficacy was assessed utilizing the receiver operating characteristic curve.

RESULTS

In total, 243 patients met the inclusion criteria. During the follow-up, 46.5 % of the patients (113/243) developed HT. Compared with the Non-HT group, the HT group had a higher LFR (0.47 (0.34-0.65) vs. 0.32 (0.07-0.56); P < 0.001). According to the binary logistic regression analysis, the LFR (aOR: 6.737; 95 % CI: 1.994-22.758; P = 0.002), Hypertension history (aOR: 2.231; 95 % CI: 1.201-4.142; P = 0.011), plasma FIB levels before MT (aOR: 0.641; 95 % CI: 0.456-0.902; P = 0.011), and the mismatch ratio (aOR: 0.990; 95 % CI: 0.980-0.999; P = 0.030) were independently associated with HT secondary to MT. The area under the curve of the regression model for predicting HT was 0.741.

CONCLUSION

LFR, a ratio quantified via CTP, demonstrates potential as an independent risk factor of HT secondary to MT.

Proposal of multimodal computed tomography-based scoring system in prediction of hemorrhagic transformation in acute ischemic stroke

INTRODUCTION

The routinely used computed tomography (CT)-based workup in the setting of acute ischemic stroke (AIS) includes non-contrast brain CT, CT angiography (CTA), and CT perfusion. Several CT, CTA, CTP-based radiological biomarkers of hemorrhagic transformation (HT) were reported.

AIM OF THE STUDY

To assess the predictive value of the combined multimodal CT parameters for HT after AIS and proposal of predictive scoring scale.

METHODS

The source images of the NCCT, CTA and CTP of 282 AIS patients involving the anterior circulation (HT = 91, non-HT = 191) were retrospectively reviewed and the following biomarkers were recorded and analyzed: Early subtle ischemic signs, hyperdense middle cerebral artery sign (HMCAS) and Alberta Stroke Program Early CT Score (ASPECTS) < 7 in NCCT, large-vessel occlusion (LVO), clot burden score (CBS) < 6, large-vessel occlusion, poor collateral score (CS) and Tmax > 6 s ≥ 56.5 ml. A scoring system to predict HT based on these biomarkers was developed. Each biomarker counts for a single point with the total score ranging from 0 to 7.

RESULTS

All the aforementioned multimodal CT biomarkers and the selected cut offs were significantly associated with higher HT risk. The calculated scores were statistically significant different between the HT and the non-HT groups with AUC 0.761 (95% CI 0.703-0.819, P < 0.0000001). Rates of HT were approximately five times higher in patients with score ≥ 3.

CONCLUSION

Multimodal CT-based scoring system may provide highly reliable predictive model of hemorrhagic transformation in acute ischemic stroke.

Predictive Value of CT Perfusion in Hemorrhagic Transformation after Acute Ischemic Stroke: A Systematic Review and Meta-Analysis

Background: Existing studies indicate that some computed tomography perfusion (CTP) parameters may predict hemorrhagic transformation (HT) after acute ischemic stroke (AIS), but there is an inconsistency in the conclusions alongside a lack of comprehensive comparison. Objective: To comprehensively evaluate the predictive value of CTP parameters in HT after AIS. Data sources: A systematical literature review of existing studies was conducted up to 1st October 2022 in six mainstream databases that included original data on the CTP parameters of HT and non-HT groups or on the diagnostic performance of relative cerebral blood flow (rCBF), relative permeability-surface area product (rPS), or relative cerebral blood volume (rCBV) in patients with AIS that completed CTP within 24 h of onset. Data Synthesis: Eighteen observational studies were included. HT and non-HT groups had statistically significant differences in CBF, CBV, PS, rCBF, rCBV, and rPS (p < 0.05 for all). The hierarchical summary receiver operating characteristic (HSROC) revealed that rCBF (area under the curve (AUC) = 0.9), rPS (AUC = 0.89), and rCBV (AUC = 0.85) had moderate diagnostic performances in predicting HT. The pooled sensitivity and specificity of rCBF were 0.85 (95% CI, 0.75−0.91) and 0.83 (95% CI, 0.63−0.94), respectively. Conclusions: rCBF, rPS, and rCBV had moderate diagnostic performances in predicting HT, and rCBF had the best pooled sensitivity and specificity.