局部晚期直肠癌新辅助治疗同期加量调强与三维适形放疗随机对照研究

目的 评估局部晚期直肠癌新辅助治疗同期加量调强放疗对比三维适形放疗疗效及安全性。方法 前瞻性研究自2010年5月至2015年5月,临床分期为T₃/T₄或淋巴结阳性且肿瘤下缘距肛门10 cm以内初治直肠腺癌患者共130例。采用随机数字表法分为调强放疗组和三维适形放疗组,调强放疗组66例,三维适形放疗组64例。调强放疗方案为盆腔放疗剂量45 Gy,1.8 Gy/次,共5周,同步原发病灶及转移淋巴结外放1 cm加量放疗剂量至55 Gy。三维适形放疗为盆腔放疗45 Gy,1.8 Gy/次,共5周,两组于放疗第1~14天及第22~35天接受卡培他滨1 650 mg·m^-2·d^-1口服化疗。手术于放化疗结束后6~8周进行。结果 两组患者性别、年龄、肿瘤位置、病理分化程度以及临床分期基线指标差异均无统计学意义(P>0.05)。2例患者出现放疗终止情况,分别为调强放疗组1例3级腹泻与三维适形放疗组1例3级乏力。两组血液及非血液不良反应差异均无统计学意义,无4级及以上不良反应出现。手术类型及术后并发症两组差异均无统计学意义。术后4级病理降期(病理完全缓解)率调强放疗组为22.7%,三维适形放疗组为15.6%,两组比较差异无统计学意义(P>0.05),3级与4级病理降期率两组比例分别为42.4%和25.0%,两组比较差异有统计学意义(χ²=4.406, P=0.036)。结论 局部晚期直肠癌新辅助同期加量调强放疗为可行治疗方案,与三维适形放疗相比可进一步提高病理降期。临床试验注册 中国临床试验注册中心,ChiCTR-INR-16008004。     

教育环境测量在护理教育中的应用

[目的]调查护理教育环境中存在的问题。[方法]采用世界性医学教育测量工具(DREEM)对我校护理专业406名本科生(涉外班学生192名,普通班学生214名)进行护理教育环境进行调查。[结果]护理专业本科生对总体教育环境及学习、教师、氛围的感受和学术自我感受4个子领域相对比较满意,但在社交方面的自我感受则不容乐观,而且涉外班学生对教育环境感知的得分均低于普通班(P<0.01)。[结论]通过关注学生的感受、丰富校园文化生活、改进学习方法以及扩大中外护理信息交流等途径,营造良好的护理教育环境。     

Meta-Analysis of Functional Roles of DICCCOLs

DICCCOL (Dense Individualized and Common Connectivity-based Cortical Landmarks) is a recently published system composed of 358 cortical landmarks that possess consistent correspondences across individuals and populations. Meanwhile, each DICCCOL landmark is localized in an individual brain’s unique morphological profile, and therefore the DICCCOL system offers a universal and individualized brain reference and localization framework. However, in current 358 diffusion tensor imaging (DTI)-derived DICCCOLs, only 95 of them have been functionally annotated via task-based or resting-state fMRI datasets and the functional roles of other DICCCOLs are unknown yet. This work aims to take the advantage of existing literature fMRI studies (1110 publications) reported and aggregated in the BrainMap database to examine the possible functional roles of 358 DICCCOLs via meta-analysis. Our experimental results demonstrate that a majority of 358 DICCCOLs can be functionally annotated by the BrainMap database, and many DICCCOLs have rich and diverse functional roles in multiple behavior domains. This study provides novel insights into the functional regularity and diversity of 358 DICCCOLs, and offers a starting point for future elucidation of fine-grained functional roles of cortical landmarks.     

A hybrid approach to automatic clustering of white matter fibers

Recently, the tract-based white matter (WM) fiber analysis has been recognized as an effective framework to study the diffusion tensor imaging (DTI) data of human brain. This framework can provide biologically meaningful results and facilitate the tract-based comparison across subjects. However, due to the lack of quantitative definition of WM bundle boundaries, the complexity of brain architecture and the variability of WM shapes, clustering WM fibers into anatomically meaningful bundles is nontrivial. In this paper, we propose a hybrid top-down and bottom-up approach for automatic clustering and labeling of WM fibers, which utilizes both brain parcellation results and similarities between WM fibers. Our experimental results show reasonably good performance of this approach in clustering WM fibers into anatomically meaningful bundles.     

Feasibility and toxicity of hypofractionated image guided radiation therapy for large volume limited metastatic disease

PurposeHypofractionated image guided radiation therapy (HIGRT) is increasingly used for limited metastases. Reported studies have mostly treated small volume tumors. Here, we report the toxicity and oncologic outcomes following treatment of large volume metastases.Methods and MaterialsHIGRT patients treated from October 2005 to March 2010 were reviewed. Gross tumor volumes (GTV) and planning target volumes (PTV) were obtained from planning software. A metastasis was considered large volume if the treated PTV exceeded 50 cc. Patients were treated with either 10-fraction (4-5 Gy per fraction) or 3-5 fraction (8-14 Gy per fraction) regimens. Toxicity was obtained from both prospectively collected databases and retrospectively from patient charts.ResultsSixty-four patients with 93 treated lesions > 50 cc were identified. The median GTV and PTV volumes were 41 and 119 cc, respectively. The median number of treated large volume lesions was 1, and a maximum of 3 large volume lesions were treated in a single patient. Primary malignancies included non–small cell lung cancer, renal cell, colorectal, breast, bladder, pituitary, small cell lung cancer, sarcoma, head-and-neck cancer, and hepatocellular cancer. Treated sites included lung (n = 33), regional lymph nodes (n = 20), bone (n = 17), adrenal (n = 9), and liver (n = 6). The most frequently used treatment regimen was 50 Gy in 5 Gy fractions. The median follow-up was 27 months for surviving patients. Treated lesion control was 78%. Low rates of acute and late grade 3 or higher toxicity were reported, with 3 and 5 patients experiencing each, respectively.ConclusionsHIGRT to large volume oligometastatic disease is tolerable and feasible with promising tumor control. Local radiation therapy should be considered in patients with large volume, limited metastatic disease.     

An Automated Method for Cell Detection in Zebrafish

Quantification of cells is a critical step towards the assessment of cell fate in neurological disease or developmental models. Here, we present a novel cell detection method for the automatic quantification of zebrafish neuronal cells, including primary motor neurons, Rohon–Beard neurons, and retinal cells. Our method consists of four steps. First, a diffused gradient vector field is produced. Subsequently, the orientations and magnitude information of diffused gradients are accumulated, and a response image is computed. In the third step, we perform non-maximum suppression on the response image and identify the detection candidates. In the fourth and final step the detected objects are grouped into clusters based on their color information. Using five different datasets depicting zebrafish cells, we show that our method consistently displays high sensitivity and specificity of over 95%. Our results demonstrate the general applicability of this method to different data samples, including nuclear staining, immunohistochemistry, and cell death detection.     

Individual Functional ROI Optimization Via Maximization of Group-Wise Consistency of Structural and Functional Profiles

Studying connectivities among functional brain regions and the functional dynamics on brain networks has drawn increasing interest. A fundamental issue that affects functional connectivity and dynamics studies is how to determine the best possible functional brain regions or ROIs (regions of interest) for a group of individuals, since the connectivity measurements are heavily dependent on ROI locations. Essentially, identification of accurate, reliable and consistent corresponding ROIs is challenging due to the unclear boundaries between brain regions, variability across individuals, and nonlinearity of the ROIs. In response to these challenges, this paper presents a novel methodology to computationally optimize ROIs locations derived from task-based fMRI data for individuals so that the optimized ROIs are more consistent, reproducible and predictable across brains. Our computational strategy is to formulate the individual ROI location optimization as a group variance minimization problem, in which group-wise consistencies in functional/structural connectivity patterns and anatomic profiles are defined as optimization constraints. Our experimental results from multimodal fMRI and DTI data show that the optimized ROIs have significantly improved consistency in structural and functional profiles across individuals. These improved functional ROIs with better consistency could contribute to further study of functional interaction and dynamics in the human brain.     

Increased cortico-subcortical functional connectivity in schizophrenia

It has been widely reported that structural and functional connectivities are disturbed in cortical networks in schizophrenia (SZ). However, much less is known about the structural and functional connectivities between cortical and subcortical regions in SZ. Here, diffusion tensor imaging (DTI) data was used to identify consistent cortico-subcortical structural connection patterns across SZ patients and controls, and thus 13 common cortical Regions of Interest (ROIs) were determined. DTI and resting state fMRI (R-fMRI) datasets were used to assess the structural and functional connectivities between the 13 cortical ROIs and 12 subcortical regions in 8 SZ patients and 10 normal controls. It was found that there are significantly increased functional connectivities for 7 cortico-subcortical connections between the 13 cortical ROIs and 12 subcortical regions. Among most of these connections, the functional connectivity strength was doubled in SZ in comparison to controls. The cortical ROIs with functional hyper-connectivities to subcortical regions are localized in frontal and parietal lobes. However, no significant difference in the structural connectivity between these cortical and subcortical regions was found between SZ and controls. Additional analysis results showed 4 significantly increased and 2 significantly decreased cortico-cortical connections. Our study results suggest the functional hyper-connectivity between cortical and subcortical regions, adding further evidence to literature findings that SZ is a disorder of connectivity between components of large-scale brain networks. The result of either increased or decreased functional connectivities among cortical ROIs exhibits the complex pattern of disturbance of brain networks in SZ.