Posttreatment Infarct Volumes when Compared with 24-Hour and 90-Day Clinical Outcomes: Insights from the REVASCAT Randomized Controlled Trial

Al-Ajlan, Fahad S.; Sultan, Abdulaziz S Al; Minhas, Priyanka; Assis, Zarina; Miquel, María Ángeles de; Millán, Mònica; Román, Luís San; Tomassello, Alejandro; Demchuk, Andrew M.; Jovin, Tudor G; Cuadras, Patricia; Dávalos, Antoni; Goyal, Mayank; Menon, Bijoy K

doi:10.3174/ajnr.a5463

Cited by 24 publications

(31 citation statements)

References 24 publications

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“…Our results indicate that total ischemic volume is a major determinant for acute symptom severity in LVO patients measured by the NIHSS. Notably, there is also an established linear relationship between NIHSS after 24 h and post-treatment infarction volume hinting toward similar mechanisms moderating morphology and symptom severity in the hyperacute and post-therapeutic acute stroke phase ( 26 ). We also observed significant association of the clot burden score with NIHSS on admission similar to other studies ( 8 , 9 ).…”

Section: Discussionmentioning

confidence: 99%

Decomposing Acute Symptom Severity in Large Vessel Occlusion Stroke: Association With Multiparametric CT Imaging and Clinical Parameters

et al. 2021

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Background and Purpose: Acute ischemic stroke of the anterior circulation due to large vessel occlusion (LVO) is a multifactorial process, which causes neurologic symptoms of different degree. Our aim was to examine the impact of neuromorphologic and vascular correlates as well as clinical factors on acute symptom severity in LVO stroke.Methods: We selected LVO stroke patients with known onset time from a consecutive cohort which underwent multiparametric CT including non-contrast CT, CT angiography and CT perfusion (CTP) before thrombectomy. Software-based quantification was used to calculate CTP total ischemic and ischemic core volume. Symptom severity was assessed using the National Institutes of Health Stroke Scale (NIHSS) upon admission. Multivariable regression analysis was performed to determine independent associations of admission NIHSS with imaging and clinical parameters. Receiver operating characteristics (ROC) analyses were used to examine performance of imaging parameters to classify symptom severity.Results: We included 142 patients. Linear and ordinal regression analyses for NIHSS and NIHSS severity groups identified significant associations for total ischemic volume [β = 0.31, p = 0.01; Odds ratio (OR) = 1.11, 95%-confidence-interval (CI): 1.02–1.19], clot burden score (β = −0.28, p = 0.01; OR = 0.76, 95%-CI: 0.64–0.90) and age (β = 0.17, p = 0.04). No association was found for ischemic core volume, stroke side, collaterals and time from onset. Stroke topography according to the Alberta Stroke Program CT Score template did not display significant influence after correction for multiple comparisons. AUC for classification of the NIHSS threshold ≥6 by total ischemic volume was 0.81 (p < 0.001).Conclusions: We determined total ischemic volume, clot burden and age as relevant drivers for baseline NIHSS in acute LVO stroke. This suggests that not only mere volume but also degree of occlusion influences symptom severity. Use of imaging parameters as surrogate for baseline NIHSS reached limited performance underlining the need for combined clinical and imaging assessment in acute stroke management.

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Section: Discussionmentioning

confidence: 99%

Decomposing Acute Symptom Severity in Large Vessel Occlusion Stroke: Association With Multiparametric CT Imaging and Clinical Parameters

et al. 2021

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“…Considering this fact, the DSC of 72.5% is suggesting a satisfactory level of agreement between two segmentations [30]. In addition, the infarct and hemorrhage volume is more important compared to the computational metrics, such as DSC, MAD, and MAXD, if clinical outcome is considered [2], [3]. The additional analyses using Pearson correlation and Bland-Altman analyses in this study demonstrated a strong correlation and minimal error range between the algorithm segmented and manually contoured volume, demonstrating the clinical benefits of this study.…”

Section: Discussionmentioning

confidence: 99%

“…Recent randomized clinical trials revolutionized stroke care by confirming clinical benefit of modern endovascular therapy (EVT) in acute ischemic stroke (AIS) patients due to proximal anterior circulation occlusion [1]. A recent study showed that the beneficial effect of EVT on clinical outcomes could be explained by a reduction in post-treatment cerebral infarct volume (CIV) [2], [3], measured on follow-up non-contrast CT (NCCT) scans. Post-treatment CIV of AIS patients in NCCT typically includes ischemic infarct only.…”

Section: Introductionmentioning

confidence: 99%

Segmenting Hemorrhagic and Ischemic Infarct Simultaneously From Follow-Up Non-Contrast CT Images in Patients With Acute Ischemic Stroke

2019

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Cerebral infarct volume (CIV) measured from follow-up non contrast CT (NCCT) scans of acute ischemic stroke (AIS) patients is an important radiologic outcome measure of the effectiveness of ischemic stroke treatment. Post-treatment CIV in NCCT of AIS patients typically includes ischemic infarct only. In around 10% of AIS patients, however, hemorrhagic transformation or frank hemorrhage occurs along with ischemic infarction. Manual segmentation used to segment CIV into these two components in clinical practice is tedious and user dependent. Although automated segmentation methods exist, they can only segment either hemorrhage or ischemic infarct alone. In order to measure post-treatment CIV more efficiently, a novel joint segmentation approach is proposed to segment ischemic and hemorrhage infarct simultaneously. The proposed method makes use of advances in deep learning and convex optimization techniques. Specifically, convolutional neural network learned semantic information, local image context, and high-level user initialized prior are integrated into a multi-region time-implicit contour evolution scheme, which can be globally optimized by convex relaxation. The proposed segmentation approach is quantitatively evaluated using 30 patient images using Dice similarity coefficient and the mean and maximum absolute surface distance, compared to the gold standard of manual segmentation. The results show that the proposed semi-automatic segmentation is accurate and robust, outperforming some state-of-the-art semiand automatic segmentation approaches. INDEX TERMS Intracerebral hemorrhage, ischemic infarct, multi-region image segmentation, convex optimization, deep learning, non contrast CT.

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“…Studies have shown that patients with low mRS scores at 90 days may have smaller infarctions after endovascular therapy but have higher NIHSS scores at 24/48 h. This may be related to whether the infarction is located in the eloquent brain or not. 31 Ganesh et al found that patients with large posttreatment infarct volume (PIV) rarely developed serious adverse events. 32 This result is consistent with our findings.…”

Section: Discussionmentioning

confidence: 99%

Developing a Nomogram to Predict the Probability of Subsequent Vascular Events at 6-Month in Chinese Patients with Minor Ischemic Stroke

Du¹,

Cui

et al. 2021

TCRM

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Purpose To develop a nomogram to predict the risk of subsequent vascular events (SVE) at 6-month in Chinese patients with minor ischemic stroke (MIS). Patients and Methods We performed a retrospective analysis of 260 MIS patients, which were randomly divided into a derivation set (193 cases) and a verification set (67 cases) at a ratio of 3:1. Multi-factor logistic regression was used to construct a predictive model of SVE from the derivation set and verify it in the verification set. Results Finally, there were 51 cases (19.6%) of SVE in 260 MIS cases. Age, fasting blood glucose, metabolic syndrome, number of lesions found on MRI, and the infarct size were used to construct the prediction model and nomogram. The AUC in the derivation set was 0.901, with a sensitivity of 0.795, a specificity of 0.877, a positive likelihood ratio of 6.443, and a negative likelihood ratio of 0.234. The AUC in the verification set was 0.897, which was not significantly different from the derivation set (P = 0.937). The predictive model based on clinical parameters has good diagnostic efficiency and robustness. Conclusion The nomogram can provide personalized predictions for the 6-month SVE risk in Chinese MIS patients.

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Posttreatment Infarct Volumes when Compared with 24-Hour and 90-Day Clinical Outcomes: Insights from the REVASCAT Randomized Controlled Trial

Cited by 24 publications

References 24 publications

Decomposing Acute Symptom Severity in Large Vessel Occlusion Stroke: Association With Multiparametric CT Imaging and Clinical Parameters

Decomposing Acute Symptom Severity in Large Vessel Occlusion Stroke: Association With Multiparametric CT Imaging and Clinical Parameters

Segmenting Hemorrhagic and Ischemic Infarct Simultaneously From Follow-Up Non-Contrast CT Images in Patients With Acute Ischemic Stroke

Developing a Nomogram to Predict the Probability of Subsequent Vascular Events at 6-Month in Chinese Patients with Minor Ischemic Stroke

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