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.

scholarly journals Added value of diffusion-weighted MRI in assessment of pleural lesions

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
Youssriah Yahia Sabri ◽  
Ikram Hamed Mahmoud ◽  
Lamis Tarek El-Gendy ◽  
Mohamed Raafat Abd El-Mageed ◽  
Sally Fouad Tadros
Keyword(s):  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Diagnostic Value ◽  
Added Value ◽  
Adc Value ◽  
Pleural Diseases ◽  
Conventional Mri ◽  
Malignant Lesions

Abstract Background There are many causes of pleural disease including variable benign and malignant etiologies. DWI is a non-enhanced functional MRI technique that allows qualitative and quantitative characterization of tissues based on their water molecules diffusivity. The aim of this study was to evaluate the diagnostic value of DWI-MRI in detection and characterization of pleural diseases and its capability in differentiating benign from malignant pleural lesions. Results Conventional MRI was able to discriminate benign from malignant lesions by using morphological features (contour and thickness) with sensitivity 89.29%, specificity 76%, positive predictive value 89%, negative predictive value 76.92%, and accuracy 85.37%. ADC value as a quantitative parameter of DWI found that ADC values of malignant pleural diseases were significantly lower than that of benign lesions (P < 0.001). Hence, we discovered that using ADC mean value of 1.68 × 10-3 mm2/s as a cutoff value can differentiate malignant from benign pleural diseases with sensitivity 89.3%, specificity 100%, positive predictive value 100%, negative predictive value 81.2%, and accuracy 92.68% (P < 0.001). Conclusion Although DWI-MRI is unable to differentiate between malignant and benign pleural effusion, its combined morphological and functional information provide valid non-invasive method to accurately characterize pleural soft tissue diseases differentiating benign from malignant lesions with higher specificity and accuracy than conventional MRI.

scholarly journals Multiphasic Computed Tomography Angiography Findings for Identifying Pseudo-Occlusion of the Internal Carotid Artery

Stroke ◽  
2020 ◽  
Vol 51 (8) ◽  
pp. 2558-2562
Author(s):  
Jai Ho Choi ◽  
Jinhee Jang ◽  
Jaseong Koo ◽  
Kook-Jin Ahn ◽  
Yong Sam Shin ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Ischemic Stroke ◽  
Carotid Artery ◽  
Internal Carotid Artery ◽  
Acute Ischemic Stroke ◽  
Computed Tomography Angiography ◽  
Internal Carotid ◽  
Diagnostic Value ◽  
Fisher Exact Test ◽  
Anterior Circulation

Background and Purpose: Differentiation between pseudo-occlusion and true occlusion of internal carotid artery (ICA) is important in treatment planning for acute ischemic stroke patients. We compared the findings of multiphasic computed tomography angiography between cervical ICA pseudo-occlusion and true occlusion at the cervical ICA in patients with anterior circulation acute ischemic stroke to determine their diagnostic value. Methods: Thirty patients with nonvisualization of the proximal ICA were included. Diagnosis of pseudo- or true occlusion of the ICA was made based on digital subtraction angiography. Diagnostic performances of multiphasic computed tomography angiography findings—(1) a flame-shaped stump and (2) delayed contrast filling at the cervical ICA— were evaluated and compared. The Fisher exact test, χ 2 test, or Wilcoxon rank-sum test and McNemar test were used in the data analysis. Results: Twelve patients had true proximal ICA occlusion and 18 had pseudo-occlusion. Delayed contrast filling at the cervical ICA on multiphasic computed tomography angiography was found in all patients with pseudo-occlusion of the ICA, while 1 case of true occlusion showed delayed contrast filling ( P <0.001). The presence of a flame-shaped stump was not significantly different between the pseudo- and true occlusion groups. The sensitivity of delayed contrast filling (0.94 [95% CI, 0.73–1]) was significantly higher than that of flame-shaped stump (0.75 [95% CI, 0.36–0.83]). Conclusions: We demonstrated that the delayed filling sign on multiphasic computed tomography angiography could be a useful and readily available finding for differentiating proximal ICA pseudo-occlusion from true occlusion.

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.

scholarly journals Deep Learning-Based Acute Ischemic Stroke Lesion Segmentation Method on Multimodal MR Images Using a Few Fully Labeled Subjects

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Bin Zhao ◽  
Zhiyang Liu ◽  
Guohua Liu ◽  
Chen Cao ◽  
Song Jin ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Segmentation Method ◽  
Lesion Segmentation ◽  
Resonance Imaging ◽  
Mr Images ◽  
Dice Coefficient ◽  
Automatic Methods ◽  
Stroke Lesion ◽  
Magnetic Resonance Imaging Mri

Acute ischemic stroke (AIS) has been a common threat to human health and may lead to severe outcomes without proper and prompt treatment. To precisely diagnose AIS, it is of paramount importance to quantitatively evaluate the AIS lesions. By adopting a convolutional neural network (CNN), many automatic methods for ischemic stroke lesion segmentation on magnetic resonance imaging (MRI) have been proposed. However, most CNN-based methods should be trained on a large amount of fully labeled subjects, and the label annotation is a labor-intensive and time-consuming task. Therefore, in this paper, we propose to use a mixture of many weakly labeled and a few fully labeled subjects to relieve the thirst of fully labeled subjects. In particular, a multifeature map fusion network (MFMF-Network) with two branches is proposed, where hundreds of weakly labeled subjects are used to train the classification branch, and several fully labeled subjects are adopted to tune the segmentation branch. By training on 398 weakly labeled and 5 fully labeled subjects, the proposed method is able to achieve a mean dice coefficient of 0.699 ± 0.128 on a test set with 179 subjects. The lesion-wise and subject-wise metrics are also evaluated, where a lesion-wise F1 score of 0.886 and a subject-wise detection rate of 1 are achieved.

scholarly journals Prediction of Hemorrhagic Transformation and Functional Prognosis in Patients With Acute Ischemic Stroke Using One-stop CT Examination: A Study on the Plateau Region of China

2021 ◽  
Author(s):  
Meng Li ◽  
Huiying Hu ◽  
Weixia Li ◽  
Chengpin Bai ◽  
Xin Bai ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Diagnostic Value ◽  
Hemorrhagic Transformation ◽  
Imaging Data ◽  
Plateau Region ◽  
Ct Examination ◽  
Great Vessels ◽  
One Stop

Abstract There are few studies on the early hemorrhagic transformation of ischemic stroke in plateau area. This study aimed to analyze the value of one-stop CT in predicting HT and functional outcomes in patients with acute ischemic stroke (AIS) caused by occlusion of great vessels before treatment in the high plateau region. Data were obtained from patients who underwent non-enhanced CT (NCCT), CTP and CTA examination within 24 hours from October 2019 to December 2020. Follow-up CT/MRI was performed within one month to determine if HT occurred later. The clinical data, laboratory results and imaging data of patients with and without HT were compared. Of the 74 patients included, 32(43.3%) had HT during follow-up, and HT was more likely to occur in poor collateral circulation (p = 0.029). The values of MTT, Tmax, PS, rCBV, rMTT, rPS in HT group were higher than those in non-HT group (p < 0.05). The results showed that PS > 1.315 ml/100 g/min (AUC, 0.753, p = 0.001) and rCBV > 1.470(AUC, 0.764; p=0.001) had better diagnostic value for HT. One-stop CT examination was performed before treatment in patients with AIS. Quantitative perfusion parameters and multi-phase CTA were used to evaluate the prognosis of HT after recanalization of proximal great vessels.

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 Early diagnostic value of serum procalcitonin levels for catheter-related blood stream infection in first-ever acute ischemic stroke patients

BMC Neurology ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Yicheng Xu ◽  
Ruiwei Chen ◽  
Wei Qin ◽  
Peifu Wang ◽  
Peiyao Li ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Blood Stream Infection ◽  
Characteristic Curve ◽  
Diagnostic Value ◽  
Blood Stream ◽  
Stroke Patients ◽  
Neurological Intensive Care Unit ◽  
Predictive Values ◽  
Neurological Intensive Care

Abstract Objective The traditional approaches for diagnosing catheter-related bloodstream infection(CRBSI) is time consuming, which could not meet the clinical requirement. Our aim was to investigate the value of serum procalcitonin(PCT) in predicting CRBSI in first-ever acute ischemic stroke patients with central venous catheters (CVCs). Methods This was a retrospective study. First-ever acute ischemic stroke patients hospitalized in neurological intensive care unit(NICU) of Aerospace Center Hospital and NICU of Beijing Chaoyang Hospital during January 2010 and December 2017 with clinically suspected CRBSI were enrolled. Peripheral blood white blood cell (WBC) count, neutrophils percentage(NE%), the levels of serum PCT, dwell time of catheterization and outcome of the patients were collected. According to the diagnosis of CRBSI or not, they were divided into CRBSI group and no CRBSI group. We used receiver operating characteristic curve (ROC) to evaluate the value of serum PCT levels in predicting CRBSI in patients with clinically suspected CRBSI. Results Forty-five patients with suspected CRBSI were included in this study, and 13 patients were diagnosed with CRBSI. Comparing to those in no CRBSI group, the maximum body temperature (Tmax) (p = 0.036) and the PCT levels (P = 0.013) in CRBSI group were both significantly higher. The area under ROC of the serum PCT levels and the Tmax to predict the CRBSI were 0.803 (0.95CI,0.660–0.946) and 0.680 (0.95CI,0.529–0.832) respectively. The PCT cut-off value was 0.780 ng/ml, with the sensitivity 69.23%, specificity 87.50%, positive predictive values 69.23% and negative predictive values 87.50%. Conclusion It could be helpful to adopt PCT as a rapid diagnostic biomarker for first-ever acute stroke patients with suspected CRBSI.

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