Automatic Segmentation of Acute Ischemic Stroke From DWI Using 3-D Fully Convolutional DenseNets

2018 ◽  
Vol 37 (9) ◽  
pp. 2149-2160 ◽  
Author(s):  
Rongzhao Zhang ◽  
Lei Zhao ◽  
Wutao Lou ◽  
Jill M. Abrigo ◽  
Vincent C. T. Mok ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Automatic Segmentation

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

2019 ◽  
Vol 12 (9) ◽  
pp. 848-852 ◽  
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.

Effect of MRI Images Based on Semi-Automatic Volume Segmentation in Patients with Acute Ischemic Stroke

2021 ◽  
Vol 11 (1) ◽  
pp. 223-229
Author(s):  
Peng Ji ◽  
Limin Jiang ◽  
Xiangdong Guo ◽  
Yajing Sun ◽  
Xueping Qu ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Automatic Segmentation ◽  
Diagnostic Value ◽  
Processing Method ◽  
Segmentation Method ◽  
Adc Value ◽  
Conventional Mri ◽  
Infarct Area ◽  
Signal Characteristics

Objective: To study the MRI and CT characteristics of different periods of acute ischemic stroke and evaluate its diagnostic value by using semi-automatic mention segmentation method. Methods: CT, conventional MRI and DWI were performed in 64 patients with acute ischemic stroke. The average ADC value and average relative ADC (rADC) value of infarct lesions were measured and statistically analyzed. Results: There were no significant differences in CT, conventional MRI, and DWI signal characteristics between 1 and 7 days after the onset of acute ischemic stroke. The average ADC value and the average rADC value decreased, but the average rADC in the infarct area increased with time. The rADC value was statistically significant with the onset of 1d, 2d, 3d, and 4d (P < 0.05), but not statistically significant with the onset of 5d and 6d (P > 0.05). Conclusion: In the image processing method of semi-automatic segmentation method, the characteristics of CT, conventional MRI, and DWI signals combined with the evolution of rADC values over time can help to judge the pathophysiological changes of acute ischemic stroke, which is ischemic. Stroke staging and treatment guidance are provided.

Predictive value of the ankle brachial index in patients with acute ischemic stroke

VASA ◽  
2014 ◽  
Vol 43 (1) ◽  
pp. 55-61 ◽  
Author(s):  
Konstantinos Tziomalos ◽  
Vasilios Giampatzis ◽  
Stella Bouziana ◽  
Athinodoros Pavlidis ◽  
Marianna Spanou ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Hospital Mortality ◽  
Acute Ischemic Stroke ◽  
Ankle Brachial Index ◽  
Arterial Disease ◽  
National Institutes Of Health ◽  
Limited Data ◽  
Severe Stroke ◽  
Hospital Outcome ◽  
Peripheral Arterial

Background: Peripheral arterial disease (PAD) is frequently present in patients with acute ischemic stroke. However, there are limited data regarding the association between ankle brachial index (ABI) ≤ 0.90 (which is diagnostic of PAD) or > 1.40 (suggesting calcified arteries) and the severity of stroke and in-hospital outcome in this population. We aimed to evaluate these associations in patients with acute ischemic stroke. Patients and methods: We prospectively studied 342 consecutive patients admitted for acute ischemic stroke (37.4 % males, mean age 78.8 ± 6.4 years). The severity of stroke was assessed with the National Institutes of Health Stroke Scale (NIHSS)and the modified Rankin scale (mRS) at admission. The outcome was assessed with the mRS and dependency (mRS 2 - 5) at discharge and in-hospital mortality. Results: An ABI ≤ 0.90 was present in 24.6 % of the patients whereas 68.1 % had ABI 0.91 - 1.40 and 7.3 % had ABI > 1.40. At admission, the NIHSS score did not differ between the 3 groups (10.4 ± 10.6, 8.3 ± 9.3 and 9.3 ± 9.4, respectively). The mRS score was also comparable in the 3 groups (3.6 ± 1.7, 3.1 ± 1.8 and 3.5 ± 2.3, respectively). At discharge, the mRS score did not differ between the 3 groups (2.9 ± 2.2, 2.3 ± 2.1 and 2.7 ± 2.5, respectively) and dependency rates were also comparable (59.5, 47.6 and 53.3 %, respectively). In-hospital mortality was almost two-times higher in patients with ABI ≤ 0.90 than in patients with ABI 0.91 - 1.40 or > 1.40 but this difference was not significant (10.9, 6.6 and 6.3 %, respectively). Conclusions: An ABI ≤ 0.90 or > 1.40 does not appear to be associated with more severe stroke or worse in-hospital outcome in patients with acute ischemic stroke.

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