Attenuation Coefficient Estimation of Normal Placentas

Attenuation coefficient estimation has the potential to be a useful tool for placental tissue characterization. A current challenge is the presence of inhomogeneities in biological tissue that result in a large variance in the attenuation coefficient estimate (ACE), restricting its clinical utility. In this work, we propose a new Attenuation Estimation Region Of Interest (AEROI) selection method for computing the ACE based on the (i) envelope signal-to-noise ratio deviation and (ii) coefficient of variation of the transmit pulse bandwidth. The method was first validated on a tissue-mimicking phantom, for which an 18%–21% reduction in the standard deviation of ACE and a 14%–24% reduction in the ACE error, expressed as a percentage of reported ACE, were obtained. A study on 59 post-delivery clinically normal placentas was then performed. The proposed AEROI selection method reduced the intra-subject standard deviation of ACE from 0.72 to 0.39 dB/cm/MHz. The measured ACE of 59 placentas was 0.77 ± 0.37 dB/cm/MHz, which establishes a baseline for future studies on placental tissue characterization.     

基于Oncomine数据库分析SNRPB基因在乳腺癌中的表达及临床意义

目的:研究小核糖体核蛋白B（small nuclear ribonucleoprotein polypeptides B and B1，SNRPB)在乳腺癌中的表达及临床意义。方法:运用Oncomine数据库搜索乳腺癌与SNRPB基因相关的数据，通过Kaplan-Meier Plotter数据库分析SNRPB基因与乳腺癌患者预后的关系。结果:Oncomine数据库中SNRPB基因癌组织／正常组织表达量分析结果共有414个，在癌组织中显著高表达109个，低表达3个。其中13个分析结果显示SNRPB在乳腺癌组织(包括6个侵袭性乳腺癌分析结果)中显著高表达，低表达的分析结果为1个。运用Kaplan-Meier Plotter数据库分析结果显示，高表达SNRPB的乳腺癌患者其总体生存率（OS）、无复发生存率（PFS）、无远处转移生存率（DMFS）显著低于低表达SNRPB的乳腺癌患者(P＜0.05)。结论:SNRPB基因在乳腺癌中高表达，可以作为有效的生物标志物预测乳腺癌患者转移的发生及判断预后，可为乳腺癌的靶向治疗提供依据。     

Finite Neuron Method and Convergence Analysis

We study a family of $H^m$-conforming piecewise polynomials based on the artificial neural network, referred to as the finite neuron method (FNM), for numerical solution of $2m$-th-order partial differential equations in$\mathbb{R}^d$ for any $m,d≥1$ and then provide convergence analysis for this method. Given a general domain Ω$⊂\mathbb{R}^d$ and a partition$\mathcal{T}_h$ of Ω, it is still an open problem in general how to construct a conforming finite element subspace of $H^m$(Ω) that has adequate approximation properties. By using techniques from artificial neural networks, we construct a family of $H^m$-conforming functions consisting of piecewise polynomials of degree $k$ for any $k≥m$ and we further obtain the error estimate when they are applied to solve the elliptic boundary value problem of any order in any dimension. For example, the error estimates that $‖u−u_N‖_{H^m(\rm{Ω})}=\mathcal{O}(N^{−\frac{1}{2}−\frac{1}{d}})$ is obtained for the error between the exact solution $u$ and the finite neuron approximation $u_N$. A discussion is also provided on the difference and relationship between the finite neuron method and finite element methods (FEM). For example, for the finite neuron method, the underlying finite element grids are not given a priori and the discrete solution can be obtained by only solving a non-linear and non-convex optimization problem. Despite the many desirable theoretical properties of the finite neuron method analyzed in the paper, its practical value requires further investigation as the aforementioned underlying non-linear and non-convex optimization problem can be expensive and challenging to solve. For completeness and the convenience of the reader, some basic known results and their proofs are introduced.     

Effect of multidisciplinary team care on the risk of recurrence in breast cancer patients: A national matched cohort study

BackgroundCancer has been the leading cause of death in the past decade in Taiwan, with breast cancer being the most common type of cancer in females. Very few studies looked at the risk of recurrence in patients who received multidisciplinary team (MDT) care. We analyzed the influence of MDT on the risk of recurrence and death in breast cancer patients.MethodIn this retrospective study, we included newly diagnosed patients from 2004 to 2010. The study included 9,266 breast cancer patients who were enrolled in MDT care and 9,266 patients who were not. The study used log-rank test to analyze patients’ characteristics, hospital characteristics, cancer staging, and treatment methods to compare the recurrence rates in MDT care and non-MDT care participants. We used Cox proportional hazards model to examine the effect of MDT and associated factors on the risk of recurrence and mortality of breast cancer patients.ResultsRelative risk of recurrence was lower for patients who received MDT care than for patients who did not (HR, 0.84; 95%CI: 0.70–0.99) after matching. The mortality risk for breast cancer patients with relapse was 8.48 times (95%CI: 7.53–9.54) than that for patients without relapse.ConclusionsThe relative risk of recurrence and death was significantly lower for breast cancer patients who received MDT care than for those who did not. We suggest that MDT care be implanted in the National Health Policy settings of breast cancer patients.     

A note on the empirical Bayes heterogeneity variance estimator in meta-analysis

This paper focuses on the empirical Bayes (EB) or Mandel-Paule estimator of the heterogeneity variance in meta-analysis, which was discussed by Morris and proposed in earlier publications by Mandel and Paule in an inter-laboratory context. The relationship of the EB estimator to other heterogeneity variance estimators typically used in meta-analysis is explored, and approximate variance estimators for the EB estimate of the heterogeneity variance are proposed based on the M-estimation method. Statistical inference for the overall treatment effect using the EB estimator and the proposed standard errors is discussed using two example data sets from meta-analysis applications.     

Super-Closeness Between the Ritz Projection and the Finite Element Solution for Some Elliptic Problems

We prove the super-closeness between the finite element solution and the Ritz projection for some second order and fourth order elliptic equations in both the $H^1$and the $L^2$norms. For the fourth order problem, a Ciarlet-Raviart type mixed formulation is used in the analysis. The main tool in the proof is a negative norm estimate of the Ritz projection, which requires $H^{q+1}$ regularity for second order elliptic equations. Therefore, the analysis is done on a domain Ω with smooth boundary, and hence we only consider the pure Neumann boundary problems which can be discretized naturally on such domains, if ignoring the effect of numerical integrals. For the fourth order problem, our results amend the gap between the theoretical estimates and the numerical examples in a previous work [22].     

Long-Term Seizure Outcome following Resective Surgery for Epilepsy: To Be or Not to Be Completely Cured?

Surgical intervention is expected to improve the quality of life in patients with intractable epilepsy by providing adequate seizure control. Although many previous studies showed various rates of seizure freedom, definite conclusions have not yet been made regarding outcomes. In order to clarify the long-term postoperative outcome for a period up to 10 years, a retrospective review of our patients was performed longitudinally by using the survival analysis method. The postoperative state of epilepsy in 76 patients who underwent resection surgery was assessed based on Engel’s criteria. In addition, Kaplan-Meier survival analysis was used to calculate the probability of seizure freedom. In this patient group, abnormal lesion were detected by MRI in 70 out of 76 cases, and the ictal onset zone was finally identified within temporal lobe in 51 cases. The most favorable outcome, defined as Engel Class Ia, was observed in 26 (37%), 24 (40%), and 18 (41%) cases at 2, 5, and 10 years after surgery, respectively. The Kaplan-Meier survival curve in the overall group estimated the probability of seizure freedom as 75% (95% confidence interval [CI] 70–80%), 67% (62–72%), and 51% (45–57%) at 2, 5, and 10 years follow up, respectively. Half of all seizure recurrences occurred within the first 2 postoperative years. In this study, we showed that long-term favorable outcome of seizure control following resection surgery can be achieved in more than half of the patients.