Automated Cerebral Infarct Volume Measurement in Follow-up Noncontrast CT Scans of Patients with Acute Ischemic Stroke

Introduction: Final infarct volume (FIV) is a commonly used imaging endpoint in stroke trials. The aim of this study was to investigate the potential of an automated masking pipeline (Brain Intensity AbNormality Classification Algorithm - BIANCA) on detecting ischemic stroke lesions of follow-up imaging on patients with acute ischemic stroke. Methods: Patients were retrospectively selected from a prospectively acquired mechanical thrombectomy (MT) database from January to July 2019, and were included if they had a follow-up magnetic resonance imaging DWI within 72h from procedure available. Masks were generated on B1000 imaging by clinical research stroke personnel and then compared with volumes delineated by a fully automated supervised method for lesion detection, based on a k-nearest neighbor (k-NN) algorithm. Results: Seventy patients were included. Human FIV measurements mean was comparable with BIANCA [67.7±73.2 vs 71.8±67 (p<0.05)]. Dice similarity index showed to be 0.710 whilst the ICC was 0.960 (p<0.05). Conclusion: The automated masking pipeline measurement showed to behighlysimilar to a standardized protocol of FIV estimation at a busy neuroendovascular center and could be used in trials with large numbers of patients.

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Semi‐automated infarct segmentation from follow‐up noncontrast CT scans in patients with acute ischemic stroke

Medical Physics ◽

10.1002/mp.13703 ◽

2019 ◽

Vol 46 (9) ◽

pp. 4037-4045 ◽

Cited By ~ 4

Author(s):

Hulin Kuang ◽

Bijoy K. Menon ◽

Wu Qiu

Keyword(s):

Ischemic Stroke ◽

Acute Ischemic Stroke ◽

Ct Scans ◽

Noncontrast Ct

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Abstract P538: A Detailed Analysis of Intracranial Hemorrhage After Endovascular Treatment in Acute Ischemic Stroke Due to Large Vessel Occlusion in the Escape-NA1 Trial

Stroke ◽

10.1161/str.52.suppl_1.p538 ◽

2021 ◽

Vol 52 (Suppl_1) ◽

Author(s):

Johanna Ospel ◽

Michael D Hill ◽

Nima Kashani ◽

Arnuv Mayank ◽

Nishita Singh ◽

...

Keyword(s):

Ischemic Stroke ◽

Acute Ischemic Stroke ◽

Intracranial Hemorrhage ◽

Intraventricular Hemorrhage ◽

Infarct Volume ◽

Prognostic Impact ◽

Vessel Occlusion ◽

Good Outcome

Purpose: We investigated the prevalence and prognostic impact on outcome of any intracranial hemorrhage, hemorrhage morphology, type and volume in acute ischemic stroke patients undergoing mechanical thrombectomy. Methods: Prevalence of intracranial hemorrhage, hemorrhage type, morphology and volume was determined on 24h follow-up imaging (non contrast head CT or gradient-echo/susceptibility-weighted MRI). Proportions of good outcome (mRS 0-2 at 90 days) were reported for patients with vs. without any intracranial hemorrhage. Multivariable logistic regression with adjustment for key minimization variables and total infarct volume was performed to obtain adjusted effect size estimates for hemorrhage type and volume on good outcome. Results: Hemorrhage on follow up-imaging was seen in 372/1097 (33.9%) patients, among them 126 (33.9%) with hemorrhagic infarction (HI) type 1, 108 (29.0%) with HI-2, 72 /19.4%) with parenchymal hematoma (PH) type 1, 37 (10.0) with PH2, 8 (2.2%) with remote PH and 21 (5.7%) with extra-parenchymal/intraventricular hemorrhage. Good outcomes were less often achieved by patients with hemorrhage on follow-up imaging (164/369 [44.4%] vs. 500/720 [69.4%]). Any type of intracranial hemorrhage was strongly associated with decreased chances of good outcome ( adj OR 0.62 [CI 95 0.44 - 0.87]). The effect of hemorrhage was driven by both PH hemorrhage sub-type [PH-1 ( adj OR 0.39 [CI 95 0.21 - 0.72]), PH-2 ( adj OR 0.15 [CI 95 0.05 - 0.50])] and extra-parenchymal/intraventricular hemorrhage ( adj OR 0.60 (0.20-1.78) Petechial hemorrhages (HI-1 and HI-2) were not associated with poorer outcomes. Hemorrhage volume ( adj OR 0.97 [CI 95 0.05 - 0.99] per ml increase) was significantly associated with decreased chances of good outcome. Conclusion: Presence of any hemorrhage on follow-up imaging was seen in one third of patients and strongly associated with decreased chances of good outcome.

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Abstract 3681: Early Anticoagulation Is Not Associated With Hemorrhagic Transformation Of Ischemic Stroke In Patients With Atrial Fibrillation

Stroke ◽

10.1161/str.43.suppl_1.a3681 ◽

2012 ◽

Vol 43 (suppl_1) ◽

Author(s):

H. B Brouwers ◽

Svetlana Lorenzano ◽

Lyndsey H Starks ◽

David M Greer ◽

Steven K Feske ◽

...

Keyword(s):

Atrial Fibrillation ◽

Ischemic Stroke ◽

Acute Ischemic Stroke ◽

Clinical Data ◽

Infarct Volume ◽

Hemorrhagic Transformation ◽

P Value ◽

Long Term Outcome ◽

Nihss Score

Purpose: Hemorrhagic transformation (HT) is a common and potentially devastating complication of ischemic stroke, however its prevalence, predictors, and outcome remain unclear. Early anticoagulation is thought to be a risk factor for HT which raises the clinical question when to (re)start anticoagulation in ischemic stroke patients who have a compelling indication, such as atrial fibrillation. We conducted a prospective cohort study to address this question and to identify association of hemorrhagic transformation with outcome measures in patients with atrial fibrillation in the setting of acute ischemic stroke. Materials and Methods: We performed a prospective study which enrolled consecutive patients admitted with acute ischemic stroke presenting to a single center over a three-year period. As part of the observational study, baseline clinical data and stroke characteristics as well as 3 month functional outcome were collected. For this sub-study, we restricted the analysis to subjects diagnosed with atrial fibrillation. CT and MRI scans were reviewed by experienced readers, blinded to clinical data, to assess for hemorrhagic transformation (using ECASS 2 criteria), microbleeds and infarct volumes in both admission and follow-up scans. Clinical and outcome data were analyzed for association with hemorrhagic transformation. Results: Of 94 patients, 63 had a history of atrial fibrillation (67.0%) and 31 had newly discovered atrial fibrillation (33.0%). We identified HT in 3 of 94 baseline scans (3.2%) and 22 of 48 follow-up scans (45.8%) obtained a median of 3 days post-stroke. In-hospital initiation of either anti-platelet (n = 36; OR 0.34 [95% CI 0.10-1.16], p-value = 0.09) or anticoagulation with unfractionated intravenous heparin or low molecular weight heparin (n = 72; OR 0.25 [95% CI 0.06-1.15], p-value = 0.08) was not associated with HT. Initial NIH Stroke Scale (NIHSS) score (median 13.0 [IQR 15.0] vs. 7.0 [IQR 10.0], p-value = 0.029) and baseline infarct volume (median 17 [IQR 42.03] vs. 5 [IQR 10.95], p-value = 0.011) were significantly higher in patients with HT compared to those without. Hemorrhagic transformation was associated with a significantly higher 48-hour median NIHSS score (20 [IQR 3.0] vs. 2 [IQR 3.25], p-value = 0.007) and larger final infarct volume (81.40 [IQR 82.75] vs. 9.95 [IQR 19.73], p-value < 0.001). Finally, we found a trend towards poorer 3-month modified Rankin Scale scores in subjects with HT (OR 11.25 [95% CI 0.97-130.22], p-value = 0.05). Conclusion: In patients with atrial fibrillation, initial NIHSS score and baseline infarct volume are associated with hemorrhagic transformation in acute ischemic stroke. Early initiation of antithrombotic therapy was not associated with hemorrhagic transformation. Patients with hemorrhagic transformation were found to have a poorer short and long term outcome and larger final infarct volumes.

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Automated Infarct Segmentation from Follow-up Non-Contrast CT Scans in Patients with Acute Ischemic Stroke Using Dense Multi-Path Contextual Generative Adversarial Network

Lecture Notes in Computer Science - Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 ◽

10.1007/978-3-030-32248-9_95 ◽

2019 ◽

pp. 856-863

Author(s):

Hulin Kuang ◽

Bijoy K. Menon ◽

Wu Qiu

Keyword(s):

Ischemic Stroke ◽

Acute Ischemic Stroke ◽

Ct Scans ◽

Generative Adversarial Network ◽

Adversarial Network ◽

Contrast Ct

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KADAR FIBRIN MONOMER DAN UKURAN INFARK DI STROK ISKEMIK AKUT

INDONESIAN JOURNAL OF CLINICAL PATHOLOGY AND MEDICAL LABORATORY ◽

10.24293/ijcpml.v20i3.470 ◽

2016 ◽

Vol 20 (3) ◽

pp. 171

Author(s):

Ani Kartini ◽

Mansyur Arif ◽

Hardjoeno Hardjoeno

Keyword(s):

Ischemic Stroke ◽

Infarct Size ◽

Acute Ischemic Stroke ◽

Thrombus Formation ◽

Infarct Volume ◽

Cross Sectional Study ◽

Cerebral Infarct ◽

Cross Sectional ◽

Fibrin Monomer ◽

Significant Difference

Coagulation activation and thrombosis frequently exist in ischemic stroke, thrombus formation can be detected early by the presence of fibrin monomer. The purpose of this study was to know the correlation of fibrin monomer level with cerebral infarct size in acute ischemic stroke patients. This was a cross sectional study with a total of 39 samples. The fibrin monomer level was determined by immunoturbidimetry method using STA-Compact and the measurement of the infarct size was done by CT scan of the head using Broderick formula. The results of this study showed that the median level of fibrin monomer in acute ischemic stroke with nonlacunar infarct type and lacunar infarct type were 14.46 μg/mL and 4.29 μg/mL, respectively. Mann-Whitney test showed there was a significant difference of fibrin monomer levels between nonlacunar infarct type and the lacunar type, p=0.000. The cut-off point analysis result of the fibrin monomer level was 5.96 μg/mL with a sensitivity of 88.9% and specificity of 76.4%, respectively. Spearman correlation test showed that fibrin monomer level was positively correlated with cerebral infarct volume in acute ischemic stroke (r=0.56, p=0.000). Based on this study, it can be concluded that fibrin monomer level can be used as a marker to predict the type of cerebral infarct and volume of acute ischemic stroke as well.

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Abstract T P10: Hounsfield Unit Value and Clot Length in the Acutely Occlude Vessel and Time Required to Achieve Thrombectomy, Complications and Outcome

Stroke ◽

10.1161/str.45.suppl_1.tp10 ◽

2014 ◽

Vol 45 (suppl_1) ◽

Author(s):

Alejandro Spiotta ◽

Jan Vargas ◽

Harris Hawk ◽

Raymond Turner ◽

Imran Chaudry ◽

...

Keyword(s):

Ischemic Stroke ◽

Acute Ischemic Stroke ◽

Functional Outcome ◽

Hounsfield Unit ◽

Hounsfield Units ◽

Unit Value ◽

Procedural Complications ◽

Noncontrast Ct ◽

Time Required

Introduction: Intra-arterial therapy for acute ischemic stroke (AIS) now has an established role. We investigated if Hounsfield Units (HU) quantification on noncontrast CT is associated with ease and efficacy of mechanical thrombectomy and outcomes. Methods: We retrospectively studied a prospectively maintained database of cases of acute ischemic stroke that underwent intra-arterial therapy between May 2008 and August 2012. Functional outcome was assessed by ninety-day follow up modified Rankin Scale (mRS). Patients were dichotomized base on time to recanalization. Hounsfield units were calculated on head CT. Thrombus location and length were determined on CT angiography. Simple linear regression was used to analyze the association between clot length, average HU, and other clinical variables. Results: 141 patients were included. There was no difference in clot length or average HU among patients with good recanalization achieved within an hour compared to those in which procedures extended beyond an hour. There was no relationship between clot length or density and recanalization. The thrombus length and density were not significantly different between patients with procedural complications and those without. The presence of post procedure intracranial hemorrhage was not associated with thrombus length or density. Ninety day mRS was not associated with thrombus length or density. Conclusions: We have not found any significant associations between either thrombus length or density and likelihood of recanalization, time to achieve recanalization, intraprocedural complications, postprocedural hemorrhage or functional outcome at ninety days. These results do not support a predictive value for thrombus quantification in the evaluation of AIS.

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Computed Tomography Perfusion–Based Machine Learning Model Better Predicts Follow-Up Infarction in Patients With Acute Ischemic Stroke

Stroke ◽

10.1161/strokeaha.120.030092 ◽

2021 ◽

Vol 52 (1) ◽

pp. 223-231

Author(s):

Hulin Kuang ◽

Wu Qiu ◽

Anna M. Boers ◽

Scott Brown ◽

Keith Muir ◽

...

Keyword(s):

Computed Tomography ◽

Blood Flow ◽

Cerebral Blood Flow ◽

Ischemic Stroke ◽

Acute Ischemic Stroke ◽

Infarct Volume ◽

Interquartile Range ◽

Time Dependent ◽

Computed Tomography Perfusion

Background and Purpose: Prediction of infarct extent among patients with acute ischemic stroke using computed tomography perfusion is defined by predefined discrete computed tomography perfusion thresholds. Our objective is to develop a threshold-free computed tomography perfusion–based machine learning (ML) model to predict follow-up infarct in patients with acute ischemic stroke. Methods: Sixty-eight patients from the PRoveIT study (Measuring Collaterals With Multi-Phase CT Angiography in Patients With Ischemic Stroke) were used to derive a ML model using random forest to predict follow-up infarction voxel by voxel, and 137 patients from the HERMES study (Highly Effective Reperfusion Evaluated in Multiple Endovascular Stroke Trials) were used to test the derived ML model. Average map, T max , cerebral blood flow, cerebral blood volume, and time variables including stroke onset-to-imaging and imaging-to-reperfusion time, were used as features to train the ML model. Spatial and volumetric agreement between the ML model predicted follow-up infarct and actual follow-up infarct were assessed. Relative cerebral blood flow <0.3 threshold using RAPID software and time-dependent T max thresholds were compared with the ML model. Results: In the test cohort (137 patients), median follow-up infarct volume predicted by the ML model was 30.9 mL (interquartile range, 16.4–54.3 mL), compared with a median 29.6 mL (interquartile range, 11.1–70.9 mL) of actual follow-up infarct volume. The Pearson correlation coefficient between 2 measurements was 0.80 (95% CI, 0.74–0.86, P <0.001) while the volumetric difference was −3.2 mL (interquartile range, −16.7 to 6.1 mL). Volumetric difference with the ML model was smaller versus the relative cerebral blood flow <0.3 threshold and the time-dependent T max threshold ( P <0.001). Conclusions: A ML using computed tomography perfusion data and time estimates follow-up infarction in patients with acute ischemic stroke better than current methods.

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Spatial Resolution and the Magnitude of Infarct Volume Measurement Error in DWI in Acute Ischemic Stroke

American Journal of Neuroradiology ◽

10.3174/ajnr.a6520 ◽

2020 ◽

Vol 41 (5) ◽

pp. 792-797

Author(s):

J.M. Ospel ◽

A. Jaffray ◽

V. Schulze-Zachau ◽

S. Kozerke ◽

C. Federau

Keyword(s):

Ischemic Stroke ◽

Measurement Error ◽

Acute Ischemic Stroke ◽

Spatial Resolution ◽

Infarct Volume ◽

Volume Measurement

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Automatic segmentation of cerebral infarcts in follow-up computed tomography images with convolutional neural networks

Journal of NeuroInterventional Surgery ◽

10.1136/neurintsurg-2019-015471 ◽

2019 ◽

Vol 12 (9) ◽

pp. 848-852 ◽

Cited By ~ 1

Author(s):

Renan Sales Barros ◽

Manon L Tolhuisen ◽

Anna MM Boers ◽

Ivo Jansen ◽

Elena Ponomareva ◽

...

Keyword(s):

Neural Networks ◽

Ischemic Stroke ◽

Acute Ischemic Stroke ◽

Convolutional Neural Networks ◽

Infarct Volume ◽

Automatic Segmentation ◽

Ct Images ◽

Reference Standard ◽

Computed Tomography Images

Background and purposeInfarct volume is a valuable outcome measure in treatment trials of acute ischemic stroke and is strongly associated with functional outcome. Its manual volumetric assessment is, however, too demanding to be implemented in clinical practice.ObjectiveTo assess the value of convolutional neural networks (CNNs) in the automatic segmentation of infarct volume in follow-up CT images in a large population of patients with acute ischemic stroke.Materials and methodsWe included CT images of 1026 patients from a large pooling of patients with acute ischemic stroke. A reference standard for the infarct segmentation was generated by manual delineation. We introduce three CNN models for the segmentation of subtle, intermediate, and severe hypodense lesions. The fully automated infarct segmentation was defined as the combination of the results of these three CNNs. The results of the three-CNNs approach were compared with the results from a single CNN approach and with the reference standard segmentations.ResultsThe median infarct volume was 48 mL (IQR 15–125 mL). Comparison between the volumes of the three-CNNs approach and manually delineated infarct volumes showed excellent agreement, with an intraclass correlation coefficient (ICC) of 0.88. Even better agreement was found for severe and intermediate hypodense infarcts, with ICCs of 0.98 and 0.93, respectively. Although the number of patients used for training in the single CNN approach was much larger, the accuracy of the three-CNNs approach strongly outperformed the single CNN approach, which had an ICC of 0.34.ConclusionConvolutional neural networks are valuable and accurate in the quantitative assessment of infarct volumes, for both subtle and severe hypodense infarcts in follow-up CT images. Our proposed three-CNNs approach strongly outperforms a more straightforward single CNN approach.

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