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We assessed the value of computed tomography (CT) and automated Alberta Stroke Program Early CT Score (ASPECTS) with net water uptake (NWU) to predict stroke onset time. Two-hundred forty stroke patients with anterior circulation large-vessel occlusion were included. CT-ASPECTS-NWU values were calculated by comparing the mean Hounsfield units of affected ASPECTS regions with unaffected contralateral regions. The correlation between ASPECTS-NWU and stroke onset to CT time was assessed. ASPECTS-NWU predictive values were calculated to identify a stroke onset to CT time of within 4.5/6 h. A correlation existed between stroke onset to CT time and ASPECTS-NWU (r = 0.65, p

To compare the DWI-Alberta Stroke Program Early Computed Tomography Score calculated by a deep learning–based automatic software tool (eDWI-ASPECTS) with the neuroradiologists’ evaluation for the acute stroke, with emphasis on its performance on 10 individual ASPECTS regions, and to determine the reasons for inconsistencies between eDWI-ASPECTS and neuroradiologists’ evaluation. This retrospective study included patients with middle cerebral artery stroke who underwent MRI from 2010 to 2019. All scans were evaluated by eDWI-ASPECTS and two independent neuroradiologists (with 15 and 5 years of experience in stroke study). Inter-rater agreement and agreement between manual vs. automated methods for total and each region were evaluated by calculating Kendall’s tau-b, intraclass correlation coefficient (ICC), and kappa coefficient. In total, 309 patients met our study criteria. For total ASPECTS, eDWI-ASPECTS and manual raters had a strong positive correlation (Kendall’s tau-b = 0.827 for junior raters vs. eDWI-ASPECTS; Kendall’s tau-b = 0.870 for inter-raters; Kendall’s tau-b = 0.848 for senior raters vs. eDWI-ASPECTS) and excellent agreement (ICC = 0.923 for junior raters and automated scores; ICC = 0.954 for inter-raters; ICC = 0.939 for senior raters and automated scores). Agreement was different for individual ASPECTS regions. All regions except for M5 region (κ = 0.216 for junior raters and automated scores), internal capsule (κ = 0.525 for junior raters and automated scores), and caudate (κ = 0.586 for senior raters and automated scores) showed good to excellent concordance. The eDWI-ASPECTS performed equally well as senior neuroradiologists’ evaluation, although interference by uncertain scoring rules and midline shift resulted in poor to moderate consistency in the M5, internal capsule, and caudate nucleus regions. • The eDWI-ASPECTS based on deep learning perform equally well as senior neuroradiologists’ evaluations. • Among the individual ASPECTS regions, the M5, internal capsule, and caudate regions mainly affected the overall consistency. • Uncertain scoring rules and midline shift are the main reasons for regional inconsistency.

Introduction: Carotid computed tomography angiography (CTA) is routinely used for evaluating the atherosclerotic process. Radiomics allows the extraction of imaging markers of lesion heterogeneity and spatial complexity. These quantitative features can be used as the input for machine learning (ML). Therefore, in this study, we aimed to evaluate the diagnostic performance of radiomics-based ML assessment of carotid CTA data to identify symptomatic patients with carotid artery atherosclerosis. Methods: In this retrospective study, participants with carotid artery atherosclerosis who underwent carotid CTA and brain magnetic resonance imaging from May 2010 to December 2017 were studied. The participants were grouped into symptomatic and asymptomatic groups according to their recent symptoms (determination of ipsilateral ischemic stroke). Eight conventional plaque features and 2,107 radiomics parameters were extracted from carotid CTA images. A radiomics-based ML model was fitted on the training set, and the radiomics-based ML model and conventional assessment were compared using the area under the curve (AUC) to identify symptomatic participants. Results: After excluding participants with other stroke sources, 120 patients with 148 carotid arteries were analyzed. Of these 148 carotid arteries, 34 (22.97%) were classified into the symptomatic group. Plaque ulceration (odds ratio [OR] = 0.257; 95% confidence interval [CI], 0.094–0.698) and plaque enhancement (OR = 0.305; 95% CI, 0.094–0.988) were associated with the symptomatic status. Twenty radiomics parameters were chosen to be inputs in the radiomics-based ML model. In the identification of symptomatic participants, the discriminatory value of the radiomics-based ML model was significantly higher than that of the conventional assessment (AUC = 0.858 vs. AUC = 0.706, p = 0.021). Conclusion: Radiomics-based ML analysis improves the discriminatory power of carotid CTA in the identification of recent ischemic symptoms in patients with carotid artery atherosclerosis.

CT densitometry-based methods to directly quantify net water uptake in ischemic brain tissue have been increasingly applied recently. There is potential for net water uptake to be used as an imaging biomarker for the pathophysiology of infarcted lesions. This review is aimed at summarizing the potential and current status of the application of net water uptake as a biomarker in the management of ischemic stroke and future directions in this context. Specifically, we provide a brief overview of the principle and different methods of net water uptake measurement, followed by a discussion of the role of net water uptake in predicting malignant brain edema and hemorrhagic transformation, evaluating lesion age, and predicting the efficacy of reperfusion therapy and long-term clinical prognosis. Artificial intelligence will help address the lack of automation and standardization in the measurement of net water absorption. Further validation of net water uptake in a prospective multicenter setting is necessary. KEY POINTS: • NWU can be used as a quantitative imaging biomarker for developing malignant brain edema in anterior and posterior circulation strokes. • The difference in NWU in edema arrest or reversibility suggests that rapid and successful revascularization can influence the progression of ischemic edema. • NWU can be used to predict the age of a lesion, with predictive power comparable to that of DWI/FLAIR mismatch.

Introduction: Imaging-based early warning indicators and feasible stratification of acute ischemic stroke (AIS) patients with hemorrhagic transformation (HT), especially high-risk patients with parenchymal hematoma (PH), are crucial in determining subsequent treatment strategies. This study combined automated ASPECTS software with noncontrast CT (NCCT) and CTA source image (CTASI) attenuation changes using Hounsfield unit (HU) values to predict HT and PH in patients with AIS. Materials and Methods: We retrospectively enrolled 172 consecutive patients with anterior circulation large-vessel occlusion between 2016 and 2020. Univariate and multivariate logistic regression and receiver operating characteristic (ROC) analyses were used to investigate the relationship between NCCT and CTASI-ASPECTS-HU, as well as other clinical and radiological parameters of HT and PH. Univariate and multivariate logistic regression analyses were performed to explore risk factors for HT or PH, and an ROC curve was used to evaluate their diagnostic values. Results: A multivariate analysis showed that CTASI-ASPECTS-HU and NIHSS score were independent predictors of HT (CTASI-ASPECTS-HU: odds ratio (OR), 2.22; 95% CI, 1.01–4.92; NIHSS: OR, 1.07; 95% CI, 1.02–1.13) and PH (CTASI-ASPECTS-HU: OR, 6.51; 95% CI, 2.29–18.50; NIHSS: OR, 1.07; 95% CI, 1.01–1.13). According to ROC analysis, CTASI-ASPECTS-HU >0.09 identified HT (area under the curve, 0.70; sensitivity, 70.15%; specificity, 61.90%), and CTASI-ASPECTS-HU >0.10 identified PH (area under the curve, 0.79; sensitivity, 76.19%; specificity, 73.33%). The area under the curve for predicting HT or PH increased when CTASI-ASPECTS-HU was combined with NIHSS score (HT: area under the curve, 0.74; sensitivity, 73.13%; specificity, 70.48%; PH: area under the curve, 0.81; sensitivity, 85.71%; specificity, 72.38%). Conclusion: CTASI-ASPECTS-HU is a reliable radiological predictor of HT and PH in patients with AIS. Its predictive efficacy is moderately improved when combined with NIHSS score.

We assessed the value of computed tomography (CT) and automated Alberta Stroke Program Early CT Score (ASPECTS) with net water uptake (NWU) to predict stroke onset time.Two-hundred forty stroke patients with anterior circulation large-vessel occlusion were included. CT-ASPECTS-NWU values were calculated by comparing the mean Hounsfield units of affected ASPECTS regions with unaffected contralateral regions. The correlation between ASPECTS-NWU and stroke onset to CT time was assessed. ASPECTS-NWU predictive values were calculated to identify a stroke onset to CT time of within 4.5/6 h.A correlation existed between stroke onset to CT time and ASPECTS-NWU (r = 0.65, p 0.001), which was affected by collateral status and infarct location. The area under the receiver operating characteristic (ROC) curve (AUC) for distinguishing a stroke onset to CT time of within 4.5 h was 0.837 (95% confidence interval [CI] 0.784-0.881; optimal cutoff 7%; sensitivity 87.10%; specificity 62.36%). The multi-index AUC was 0.884 (95% CI 0.837-0.922). The AUC for distinguishing a stroke onset to CT time of within 6 h was 0.836 (95% CI 0.783-0.880; optimal cutoff 9%; sensitivity 72.73%; specificity 81.16%). The multi-index AUC was 0.881 (95% CI 0.834-0.920).ASPECTS-NWU may be used to determine stroke onset time in patients with unwitnessed or wake-up stroke.

Net water uptake (NWU) has been shown to have a linear relationship with brain edema. Based on an automated-Alberta Stroke Program Early Computed Tomography Score (ASPECTS) technique, we automatically derived NWU from baseline multimodal computed tomography (CT), namely ASPECTS-NWU. We aimed to determine if ASPECTS-NWU can predict the development of malignant cerebral edema (MCE).One hundred and forty-six patients with large-vessel occlusion were retrospectively enrolled. Quantitative NWU based on automated-ASPECTS was measured both on nonenhanced CT (NECT) and CT angiography (CTA), namely NECT-ASPECT-NWU and CTA-ASPECTS-NWU. The correlation between ASPECTS-NWU and cerebral edema (CED) grades was calculated using Spearman rank correlation. Univariate logistic regression was used to assess the effect of radiological and clinical features on MCE, and a multivariable model with significant factors from the univariate regression analysis was built. Receiver operating characteristic (ROC) was obtained and area under curve (AUC) was compared.CTA-ASPECTS-NWU had a moderate positive correlation with CED grades (r = 0.62; 95% confidence interval [CI], 0.51-0.71; p 0.001). The CTA-ASPECTS-NWU performed better than the NECT-ASPECTS-NWU with AUC: 0.88 vs. 0.71 (p 0.001). Multivariable logistic regression model integrating CTA-ASPECTS-NWU, collateral score, and age showed the CTA-ASPECTS-NWU was an independent predictor of MCE with an AUC of 0.94 (95% CI: 0.90-0.98; p 0.001).This study demonstrates that ASPECTS-NWU is a quantitative predictor of MCE after large-vessel occlusion of the middle cerebral artery territory. The multivariable logistic regression model may enhance the identification of patients with MCE needing anti-edematous treatment.• The automated-ASPECTS technique can automatically detect the affected regions with early ischemic changes and NWU could be manually calculated. • The CTA-ASPECTS-NWU performs better than the NECT-ASPECTS-NWU on predicting the development of MCE. • The multivariable logistic regression model may enhance the identification of patients with MCE needing anti-edematous treatment.

This study aimed to use the automated Alberta Stroke Program Early CT Score (ASPECTS) software to assess the value of different CT modalities (non-contrast CT, CT angiography [CTA]-arterial, CTA-venous, and arterial- and venous-phase mismatch-ASPECTS) in predicting the final infarct extent and clinical outcome in large-vessel occlusion stroke.This retrospective study included patients with large-vessel occlusion stroke who underwent reperfusion therapy during 2015 to 2019. Correlations between different CT-ASPECTS modalities and follow-up CT-ASPECTS and outcome were determined using Spearman rank correlation coefficient. Receiver operating characteristic curve analysis was used to assess the ability of different CT-ASPECTS modalities to identify patients with good outcomes.One hundred and thirty-five patients were included. We found almost-perfect correlation between CTA-venous-ASPECTS and follow-up CT-ASPECTS (r = 0.92; 95% CI: 0.89-0.95), better than that in other CT modalities. The 90-day modified Rankin scale (mRS) score substantially correlated with CTA-venous-ASPECTS (r = -0.64; 95% CI: -0.73 to -0.52). The ROC curve analysis showed CTA-venous-ASPECTS had the highest area under the curve (AUC: 0.82; 95% CI: 0.75-0.89; P 0.001), followed by mismatch-ASPECTS (AUC: 0.75; 95% CI: 0.65-0.85; P 0.001). When emphasizing the sensitivity for identifying patients with good outcomes, the best cut-off point of mismatch-ASPECTS was -3 with the highest sensitivity (91.30%).CTA-venous-ASPECTS is a reliable tool to predict the infarct extent and outcome. Furthermore, mismatch-ASPECTS may represent images in different angiographic phases and was sensitive for prognosis prediction.

To compare the DWI-Alberta Stroke Program Early Computed Tomography Score calculated by a deep learning-based automatic software tool (eDWI-ASPECTS) with the neuroradiologists' evaluation for the acute stroke, with emphasis on its performance on 10 individual ASPECTS regions, and to determine the reasons for inconsistencies between eDWI-ASPECTS and neuroradiologists' evaluation.This retrospective study included patients with middle cerebral artery stroke who underwent MRI from 2010 to 2019. All scans were evaluated by eDWI-ASPECTS and two independent neuroradiologists (with 15 and 5 years of experience in stroke study). Inter-rater agreement and agreement between manual vs. automated methods for total and each region were evaluated by calculating Kendall's tau-b, intraclass correlation coefficient (ICC), and kappa coefficient.In total, 309 patients met our study criteria. For total ASPECTS, eDWI-ASPECTS and manual raters had a strong positive correlation (Kendall's tau-b = 0.827 for junior raters vs. eDWI-ASPECTS; Kendall's tau-b = 0.870 for inter-raters; Kendall's tau-b = 0.848 for senior raters vs. eDWI-ASPECTS) and excellent agreement (ICC = 0.923 for junior raters and automated scores; ICC = 0.954 for inter-raters; ICC = 0.939 for senior raters and automated scores). Agreement was different for individual ASPECTS regions. All regions except for M5 region (κ = 0.216 for junior raters and automated scores), internal capsule (κ = 0.525 for junior raters and automated scores), and caudate (κ = 0.586 for senior raters and automated scores) showed good to excellent concordance.The eDWI-ASPECTS performed equally well as senior neuroradiologists' evaluation, although interference by uncertain scoring rules and midline shift resulted in poor to moderate consistency in the M5, internal capsule, and caudate nucleus regions.• The eDWI-ASPECTS based on deep learning perform equally well as senior neuroradiologists' evaluations. • Among the individual ASPECTS regions, the M5, internal capsule, and caudate regions mainly affected the overall consistency. • Uncertain scoring rules and midline shift are the main reasons for regional inconsistency.

Background: In acute ischemic stroke, diffusion-weighted imaging (DWI) volume is an independent predictive factor of poor outcome and an exclusion criterion for thrombolytic treatment. A simplified diameters method (ABC/2, orthogonal diameter [OD], and the maximum diameter [MD]) was proposed to replace the conventional measuring method and overcome the tedious and time-consuming defects, but its accuracy remains to be determined. Objective: The objective of this study is to clarify the reliability and reproducibility of the diameter-based estimations in the infarct volume in DWI (Vol-DWI) measured by automated software. Methods: Data of 316 patients with acute ischemic stroke who underwent MRI within 72 h at Jinling Hospital were retrospectively reviewed. Subgroup analysis by the location (cortex, white matter and deep gray nuclei, and combined) and volume (70 mL) of cerebral infarction was evaluated. Relationship and consistency between the diameters methods and Vol-DWI were determined using Spearman rank correlation, Wilcoxon signed-rank test, and Bland-Altman plots. The OD and MD thresholds indicating infarct size >15, 70, and 100 mL were determined by generating receiver-operating characteristic (ROC) curves. Interobserver reliability was established using intraclass correlation coefficient and Bland-Altman plot. Results: There was a strong positive correlation between the diameters and the Vol-DWI (ABC/2: r = 0.992, OD: r = 0.984, MD: r = 0.970, p < 0.001). Infarct volumes measured using the ABC/2 formula were significantly lower than those measured with Vol-DWI (Wilcoxon signed-rank test, z = 6.476, p < 0.001). Bland-Altman plot showed that the agreement of the volume 15, 70, and 100 mL, the cutoff value for the MD was identified at 5, 6.9, and 8.4 cm, and the OD was identified at 12.47, 26.4, and 36.4 cm2, respectively, with a sensitivity and specificity >90%. Conclusions: The MD method was the best for achieving a rapid and excellent interobserver reliability for estimating infarct volume. Both OD and MD methods can quickly screen patients suitable for recanalization treatment and predict poor prognosis through threshold evaluation.