Correlation between pretreatment and follow-up infarct volume using CT perfusion imaging: the Bayesian versus singular value decomposition method.

There are various analysis methods for CT perfusion (CTP). Although the advantages of Bayesian estimation algorithms have been newly suggested, comparisons with other analysis methods on clinical data are still limited. In this study, we compared the Bayesian estimation method with the singular value decomposition (SVD) method in the evaluation of patients with acute cerebral infarction and examined its usefulness. CTP data from 13 patients with acute stroke were analyzed using the SVD and Bayesian estimation methods implemented in Vitrea. Evaluation of visual clarity of the ischemic area and quantitative values of the healthy side-affected side ratio using the mean values of the left and right region of interest (ROI) on the images were compared using the SVD and Bayesian estimation methods. In visual evaluation, there were significant differences in CBV in four cases, and in CBF, MTT, and TTP in many cases. The healthy side-affected side ratio of the SVD and Bayesian estimation methods were as follows: CBF 1.19, 1.84; CBV 1.09, 1.02; MTT 1.12, 1.79; and TTP 1.48, 1.19. For CBF and MTT, the Bayesian estimation method had a larger ratio of the healthy side to the affected side, and for TTP, the SVD method had a larger ratio of the test side to the affected side. We suggest that the Bayesian estimation method is more useful than the SVD method for assessing CBF and MTT in CTP analysis of patients with acute stroke.

(1) Background: Follow-up infarct volume (FIV) may have implications for prognostication in acute ischemic stroke patients. Factors predicting the discrepancy between FIV and 90-day outcomes are poorly understood. We aimed to develop a comprehensive predictive model of FIV and explore factors associated with the discrepancy. (2) Methods: Patients with acute anterior circulation large vessel occlusion were included. Baseline clinical and CT features were extracted and analyzed, including the CTP-based hypoperfusion index (HI) and the NCCT-based e-ASPECT, measured by automated software. FIV was assessed on follow-up NCCT at 3−7 days. Multiple linear regression was used to construct the predictive model. Subgroup analysis was performed to explore factors associated with poor outcomes (90-mRS scores 3−6) in small FIV (<70 mL). (3) Results: There were 170 patients included. Baseline e-ASPECT, infarct core volume, hypoperfusion volume, HI, baseline international normalized ratio, and successful recanalization were associated with FIV and included in constructing the predictive model. Baseline NIHSS, baseline hypertension, stroke history, and current tobacco use were associated with poor outcomes in small FIV. (4) Conclusions: A comprehensive predictive model (including HI) of FIV was constructed. We also emphasized the importance of hypertension and smoking status at baseline for the functional outcomes in patients with a small FIV.

To evaluate the collateral flow of patients with acute ischemic stroke by dynamic CT angiography (CTA) and to analyze the relationship between collateral flow and outcome after intravenous thrombolysis. We retrospectively analyzed CT perfusion (CTP) imaging of 22 acute ischemic stroke patients with middle cerebral artery (MCA) or internal carotid artery (ICA) occlusion undergoing intravenous thrombolysis, and reconstructed the images for dynamic CTA in the Second Affiliated Hospital, Zhejiang University School of Medicine from June 2009 to October 2013. The total extent and flow speed of collateral flow based on dynamic CTA images of these patients were evaluated. The scores of National Institute of Health stroke scale (NIHSS) in different collateral flows were compared with repeated measuring. The nonparametric Spearman's rank correlation was used to assess the relationship between collateral flow and modified Rankin scale (mRS) at 3 months after thrombolytic therapy. Compared with the poor collateral flow group, patients with good collateral flow had lower NIHSS at 1 month after thrombolysis (4.7±5.0 vs 25.1±15.1, P=0.001) and higher reperfusion percentage (69%±32% vs 23%±54%, P=0.044). The total condition score of collateral flow was positively correlated with mRS at 3 months after treatment (r=0.450, P=0.001). Acute ischemic stroke patients with good collateral flow after intravenous thrombolysis have a better outcome. The dynamic CTA can be used to evaluate the collateral flow and to predict clinical outcomes in patients with acute ischemic stroke after thrombolysis therapy.

Background- Significant numbers of acute ischemic stroke (AIS) patients recover with timely-administered intravenous tissue plasminogen activator (IV-TPA). However, rates and extent of recovery remain variable. Considering scarce and costly resources, early identification of reliable predictors for functional outcomes is important for planning rehabilitation strategies. We hypothesized that venous drainage would be impaired on the side of cerebral hypoperfusion due to acute occlusion of internal carotid or middle cerebral artery. The 2 internal cerebral veins (ICV) drain the deep parts of hemispheres and run backward to form great cerebral vein. Since ICVs are consistently seen on CT angiography (CTA), parallel and run very close to each other, even minor asymmetry in their filling can be easily diagnosed. ICV asymmetry in pre-TPA CTA can change in patients achieving arterial recanalization, rendering it less useful for predicting the long-term outcomes. Thus, we aimed at evaluating whether the presence of ICV asymmetry on follow-up CTA can predict the final outcome. Methods- Data from consecutive AIS patients treated with IV-TPA, in a standardized protocol, from Jan2007 to March2010 were included in a prospective registry at our tertiary center. In this study, we excluded posterior circulation strokes. Significant proportion AIS patients undergo CTA on day 2 after IV-TPA to assess the status of arterial patency. ICV asymmetry was assessed by 2 independent stroke neurologists/ neuroradiologists, blinded to patient data or outcomes. Functional outcomes were assessed by modified Rankin Scale (mRS) at 3-months, dichotomized as good outcome (mRS 0-1) and poor outcome (mRS 2-6). Data were analyzed for the early predictors of function outcome. Results- Of the total of 2238 patients admitted during the study period, 226 (10.1%) with anterior circulation AIS treated with intravenous thrombolysis were included. Median age was 65yrs (range 19-92), 63% males and median National Institute of Health Stroke Scale (NIHSS) 16points (range 4-32). Hypertension was the commonest vascular risk factor in 144 (76%) while 63 (33%) patients suffered from atrial fibrillation (AF). Overall, 108 (47.8%) patients achieved poor functional outcome at 3-months. ICV asymmetry could be assessed only in 103 (45.5%) patients on their follow up CTA films. Admission NIHSS score (OR1.08;95%CI 1.001-1.157,p=0.048) and ICV asymmetry on follow-up CT scan (OR 23.9;95%CI 5.15-63.99,p &lt;0.0001) were associated with poor outcome at 3-months. Conclusion- Presence of the asymmetry of internal cerebral veins on the follow up CT angiography in acute ischemic stroke patients treated with IV-TPA can be used as an early predictor of poor functional outcome.

IntroductionMechanical thrombectomy (MT) has been shown to improve functional outcome in patients with anterior circulation stroke. However, previous works suggest only limited explanatory effect of infarct volume reduction on outcome...

A new method for evaluating the decay ratios in a boiling water reactor (BWR) using the singular value decomposition (SVD) method had been proposed. In this method, a signal component closely related to the BWR stability can be extracted from independent components of the neutron noise signal decomposed by the SVD method. However, real-time stability monitoring by the SVD method requires an efficient procedure for screening such compoments. For efficient screening, an artificial neural network (ANN) with three layers was adopted. The trained ANN was actually applied to decomposed components of local power range monitor (LPRM) signals that were measured in stability experiments conducted in the Ringhals-1 BWR. In each LPRM signal, multiple candidates were screened from the decomposed components. However, decay ratios could be estimated by introducing appropriate criterions for selecting the most suitable component among the candidates. The estimated decay ratios are almost identical to those evaluated by visual screening in a previous study. The selected components commonly have the largest singular value, the largest decay ratio and the least squared fitting error among the candidates. By virtue of excellent screening performance of the trained ANN, the real-time stability monitoring by the SVD method can be applied in practice.

To determine the most suitable postprocessing technique for magnetic resonance (MR) perfusion imaging in patients with vascular stenosis, by comparing the cerebral blood flow (CBF) maps of single photon emission tomography (SPECT) and perfusion MR imaging (MRI). In 15 consecutive patients (14 men and one woman, mean age 73.9 +/- 6.0 years) with stenosis of common carotid artery (CCA) or internal carotid artery (ICA) of more than 75%, both brain perfusion MRI and brain perfusion SPECT were performed. From perfusion MR images, CBF maps were calculated with the first moment, singular value decomposition (SVD), and block circulant SVD (b-SVD) methods, and CBF maps from each algorithm were compared with those from SPECT. The b-SVD method had the best correlation with SPECT (R = 0.814), followed by the first moment method (R = 0.776) and the SVD method (R = 0.723). The b-SVD method has the least mean difference with SPECT (0.118), the first moment method also had less difference (0.121), and the SVD had greatest mean difference (0.164). Our results suggest that in patients with vascular impairment the b-SVD method will be the technique of choice rather than SVD or first moment method.

Singular value decomposition (SVD) method is a very important matrix decomposition method in linear algebra. It is widely used in signal processing, statistics, data compression and other fields. The paper introduces a SVD method to reduce dimension of original dataset and makes use of the attribute of LSA technique to combine SVD method with LSA technique, and then presents new methods for dual private protection data mining. Finally we conduct experiments to test and verify the proposed approach and get good results.

BackgroundSilent Information Regulator 2 (SIRT2) protein inhibition has been shown to play a neuroprotective role in acute ischemic stroke (AIS) in mice. However, its role in AIS patients has not been fully understood. In this study, we aimed to analyze SIRT2 protein expression in serum exosomes of AIS and non-AIS patients, and evaluate its potential role in diagnosis and prognosis of AIS.MethodsSerum exosomes from 75 non-AIS subjects and 75 AIS patients were isolated. The SIRT2 protein levels in exosomes were analyzed using enzyme linked immunosorbent assay (ELISA). The National Institutes of Health Stroke Scale (NIHSS) was used to evaluate the severity of the disease. The modified Rankin Scale (mRS) was employed to assess the functional outcomes of the patients at 3-months following stroke onset.ResultsThe SIRT2 protein concentration of serum exosomes were higher in AIS patients than non-AIS patients (p < 0.001). Furthermore, the receiver operative characteristic curve (ROC) demonstrated that higher serum exosome SIRT2 could differentiate AIS patients from non-AIS patients with a sensitivity of 81.3% and a specificity of 75.3%. The area under the curve was 0.838 (95% CI: 0.775, 0.902). Additionally, higher SIRT2 concentration of serum exosomes were associated with NIHSS ≥ 4 (p < 0.001) and mRS ≥ 3 (p = 0.025) in AIS patients. The ROC analysis showed SIRT2 could discriminate stroke with NIHSS ≥ 4 from mild stroke (NIHSS < 4) with a sensitivity of 75.0% and a specificity of 69.6%. The area under the curve was 0.771 (95% CI: 0.661,0.881). Similarly, the test showed SIRT2 could differentiate between AIS patients with mRS ≥ 3 from those with mRS < 3 with a sensitivity of 78.3% and a specificity of 51.9%. The area under the curve was 0.663 (95% CI: 0.531,0.796). The logistic regression analysis revealed that SIRT2 concentration in serum exosomes can independently predict the diagnosis of AIS (odd ratio = 1.394, 95%CI 1.231–1.577, p < 0.001) and higher NIHSS scores (≥ 4) (odd ratio = 1.258, 95%CI 1.084–1.460, p = 0.002). However, it could not independently predict the prognosis of AIS (odd ratio = 1.065, 95%CI 0.983–1.154, p = 0.125).ConclusionThe elevation of SIRT2 in serum exosomes may be a valuable biomarker of AIS, which may be a potential diagnostic tool to facilitate decision making for AIS patients.

Deterioration of insulation materials caused by partial discharge is one of the important reasons for the failure of power equipment. The noise caused by the interference of the external electromagnetic environment seriously affects the accuracy of partial discharge detection. Aiming at the problem of partial discharge noise suppression, this paper proposed a partial discharge signal noise suppression method based on adaptive window singular value decomposition. This method first randomly generated a series of windows with different positions and lengths on the noisy partial discharge signal; Then singular value decomposition method was employed to denoise the signals in each window; Finally, the denoising index was chosen as the fitness function, through the particle swarm algorithm to obtain the optimal solution of the window position and length. The noise signals obtained by simulation and experiment were verified, and the method was compared with adaptive singular value decomposition, wavelet denoising, and other methods. The results showed that this method could achieve a better denoising effect.

The traditional singular value decomposition (SVD) method is unable to diagnose the weak fault feature of bearings effectively, which means, it is difficult to retain the effective singular components (SCs). Therefore, a new singular value decomposition method, SVD based on the FIC (fault information content), is proposed, which takes the amplitude characteristics of fault feature frequency as the selection index FIC of singular components. Firstly, the Hankel matrix of the original signal is constructed, and SVD is applied in the matrix. Secondly, the proposed index FIC is used to evaluate the information of the decomposed SCs. Finally, the SCs with fault information are selected and added to obtain the denoised signal. The results of bearing fault simulation signals and experimental signals show that compared with the traditional differential singular value decomposition (DS-SVD), the proposed method can select the singular components with larger amount of fault information and is able to diagnose the fault under the heavy noise interference. The new method can be used for signal denoising and weak fault feature extraction.

An improved ridge estimation (IRE) method for troposphere water vapor tomography

When seismic waves encounter abrupt points of stratum or lithology in the process of propagation, such as fault edges, pinch-out points, or the protrusion of unconformity surfaces, the Snell law will break down and many diffractions will be generated. However, the diffraction information is typically masked by strong reflections; thus, separating diffractions is one key issue for diffraction imaging. The traditional singular value decomposition (SVD) method with the ability for wavefield decomposition and reconstruction is useful in removing strong reflections of large singular values. However, the continuously changing characteristics of the singular value of steep-slope reflections make it difficult to choose a suitable parameter for separating diffractions. To solve the problem of singular value selection in diffractions reconstruction by the SVD method, we have developed a Cook-distance SVD method by mathematically least-squares measuring the contribution of every singular value. The Cook-distance SVD can amplify the difference between continuously changing singular values and easily find the singular values representing diffractions. Synthetic examples and field data applications demonstrate that our Cook-distance SVD method can avoid parameter testing and has good performance in diffraction separation and can highlight reservoir-involved small-scale geologic edges and scatterers.

Radiological findings play an essential role in therapeutic decision making and prognostication in acute ischemic stroke (AIS). The Boston Acute Stroke Imaging Scale (BASIS) and Middle Cerebral Artery-BASIS (M1-BASIS) methodologies are rapid purely radiological instruments and easily applicable for patients with AIS. We validated these methods in patients with AIS treated with intravenous tissue-type plasminogen activator. For BASIS, patients were labeled as having major stroke if there was occlusion of distal internal carotid artery, proximal (both M1 and M2 segments) of middle cerebral artery or the basilar artery, or an Alberta Stroke Program Early CT Score≤7. M1-BASIS differs from BASIS by classifying AIS patients with M2 occlusion as a minor stroke. We evaluated these classification systems for predicting functional outcomes (modified Rankin Scale score 0-1) at 3 months. Two hundred sixty-five consecutive AIS patients treated with intravenous tissue-type plasminogen activator were included. On multivariate analysis, younger age (odds ratio, 1.039, 95% confidence interval, 1.009-1.070; P=0.011), lower National Institutes of Health Stroke Scale score (odds ratio, 1.140; 95% confidence interval, 1.073-1.210; P<0.001), and minor stroke by M1-BASIS (odds ratio, 2.376; 95% confidence interval, 1.047-5.393; P=0.039) were independent predictors of good functional outcome. When compared with National Institutes of Health Stroke Scale, the receiver operating characteristic curves for both BASIS (area under the curve, 0.721) and M1-BASIS (area under the curve, 0.795) correlated well with clinical severity scores. M1-BASIS has an additive effect with the National Institutes of Health Stroke Scale score to predict good outcomes. The purely radiological M1-BASIS correlates well with the clinical severity of stroke and can be a reliable prognostication tool in thrombolyzed AIS patients. This system might find an important place in the current era of telestroke.

The aim of this study was to investigate the technical success and in-hospital outcomes of endovascular thrombectomy (ET) in acute ischemic stroke (AIS) patients performed by interventional cardiologists. ET for AIS provides fast, effective and safe recanalization. Insufficient number of catheter laboratories for stroke interventions and experienced interventional neurologists are limiting the widespread application of such a promising treatment method. 123 patients with AIS and eligible for ET were evaluated retrospectively. 65 patients were female (52.8%) and the mean age of the patients was 71.5 ± 11.9 years. Most of the patients had a middle cerebral artery (MCA) occlusion (112 patients, 91%). Successful recanalization (thrombolysis in cerebral infarction grading 2b or higher) was achieved in 109 patients (88.6%). Access site complication was observed only in 3 patients (2.4%). Intracranial bleeding was observed in 17 patients (13.8%) and only 8 of them were symptomatic (6.5%). In-hospital death occurred in 19 patients (15.4%). The initial National Institutes of Health Stroke Scale (NIHSS) was 16.8±3.3 (median 18) which improved significantly to 10.4±7.2 (median 11) at 24 hours (p<0.001). Dramatic neurologic improvement was observed in 60 of 123 patients (48.8%). The modified rankin score of the patients was significantly lower at discharge compared to admission (4.2±0.7 vs. 2.9±2, p<0.001). ET in AIS can be performed safely with high success rates by trained interventional cardiologists within the stroke team. Until the number of stroke centers is sufficient, endovascular treatment of AIS can be supported by experienced interventional cardiologists.