植入式人工肛门括约肌系统的实现及动物实验

背景：研制新型的符合人体生理需求的人工肛门括约肌系统具有十分重要的意义。目的：设计一种新型植入式人工肛门括约肌系统。方法：利用无线通讯模块和压力传感器重建排便控制机制,并由经皮能量传输模块供电,采用机电系统模拟人体自然器官的功能,最终实现人体肛门括约肌的控制效果。结果与结论：设计并实现了一种新型的植入式人工肛门括约肌系统,在重建排便机制和模型的基础上,一定程度上恢复肛门失禁患者的生物反馈控制能力,并带有经皮能量传输模块,为体内系统长期无缆式供电提供可能。该系统实现了植入式动物实验,完成了系统植入可行性和基本功能验证。     

基于3G网络移动监护信息传输定位系统的设计

背景:及时了解疾病状况,对及时诊治具有尤其重要的意义。目的:为解决院外监护和院前急救的数据传输问题,设计一种基于3G网络的移动监护信息传输定位系统。方法:通过定位传输模块把插件式监护仪实时采集的患者生理信息,连同患者的位置信息一起发送到3G移动通讯网,在具有实IP的PC机上编写服务器程序接收患者信息实现移动监护功能;通过无线传输协议的制定和软件设计,解决传输过程中丢包、错包问题。结果与结论:通过该装置实现了患者实时监护信息及位置信息的远程无线传输和显示。该系统运行稳定,费用低廉,具有较高的实际应用价值。     

基于医疗信息整合的超声科工作运行平台的构建与应用

目的实现超声影像信息系统(UIS)、医院信息系统(HIS)、PACS之间的信息传递与交互,构建客户端—中间服务层—服务端的3层架构的超声医学科工作运行平台。方法参照医疗信息整合(IHE)工作流模式设计工作流程,采用XML技术实现信息交互和共享,遵循DICOM 3.0标准完成影像信息的采集、传输、存储,遵循HL7标准完成模型之间的通讯。结果该平台可实现检查预约、排队叫号、结构化报告书写及发布等功能,并与Full PACS、EMR进行信息交互,缩短检查预约、排队等候和发送报告的时间,进一步优化和规范了超声科工作流程。结论该平台具有较高的推广应用价值。     

基于GPS和GPRS远程医疗监护报警系统的设计

背景：远程医疗监护系统可以传输医疗信息,实现动态生理监护。目的：设计一种基于GPS和GPRS的远程医疗监护报警系统。方法：系统由中心站和多个用户机组成。运用医疗信息监测技术、移动通信技术、嵌入式技术以及GPS技术,由定位传输模块把采集终端实时采集的患者生理信息,连同患者的位置信息一起发送到GSM移动通讯网,供医生进行及时诊断和处理,实现生理参数的远程实时监测与报警。结果与结论：该系统构建了家庭、社区、医院的三位一体远程医疗信息传输、医疗救治平台,第一时间将患者的医疗信息和位置信息传送到医疗中心,由专家协助诊断并提供救治指导和援助。该系统可用于院前急救、院外监护以及远程医疗与紧急救助,不仅适用于医院、装配在救护车里,也可以用于家庭,对慢性病患者进行有效的院外监测和跟踪。     

门诊雾化治疗室护士站信息系统的应用及体会

建立门诊雾化治疗室护士站信息系统,以数字化信息管理雾化治疗,系统设置执行治疗模块、撤销治疗模块、退费申请模块、患者历史治疗查询模块、治疗统计查询模块,操作后数据主动储存到数据库相应的模块。使用该系统2年来,没有发生护理人员由于个人因素而发生差错,治疗信息主动储存无需家长保管治疗单。门诊雾化治疗室护士站信息系统的应用提高了护理人员的工作效率;保障了患者治疗的安全;方便患者治疗单的管理;能够查询患者整个雾化治疗情况;能精确统计各项治疗量和个人工作量,对于药物管理和个人绩效提供详细的数据。     

医学领域实验室信息系统处理化验医嘱在护理工作中的应用

医学领域实验室信息系统（laboratory information system，LIS）是指利用计算机网络光电扫描阅读、设备识读并实现数据自动输入计算机的特殊编号一条形码，实现临床实验室的信息采集、存储、处理、传输、查询，并提供分析及诊断支持的计算机软件系统。LIS具有对实验室、检验科事务性管理功能，可通过局域网络接受申请、查询和传输患者的一般信息，录入和发送结果报告、打印统计表等。     

室内质控电子化管理系统的设计与应用

目的 通过实验室信息系统（LIS）建立室内质控月报表自动统计和电子审核功能，优化失控处理、信息记录等管理功能，实现室内质控全面电子管理。方法 通过联众智慧科技LIS完善实验室质控管理系统，包括优化室内质控失控处理模块，新建室内质控电子月报表功能，新建质控月报表电子审核系统。结果 优化了室内质控失控处理模块，可支持失控在线处理与保存；建立了室内质控月报表统计模块，可按要求统计指定月份或季度、指定设备、质控批号等13项指标及失控处理明细，该模块具有显著的随机误差、系统误差超标提示功能。建立了质控月报表三级电子审核系统，实现了由技术主管总结提交月报表、组长评阅审核、主任评阅审核的电子流转与存档功能。结论 建立与优化了基于LIS的室内质控电子管理系统，实现室内质控数据全面电子化管理。     

LIS系统与HIS系统数据交换及整合的应用

我院通过将检验科信息系统（LIS系统）与医院信息系统（HIS）进行整合，实现了患者信息、诊断信息、检验申请信息及检验结果的同步传输，实现了完整意义上的信息共享。下面对我院LIS系统和HIS系统的信息共享与交换整合的设计和实现进行简单的介绍。     

24小时自助取报告单系统的建立与应用

摘要：目的：组建自助取检验报告单系统,实现门、急诊24 h自助取单。 方法：用条形码扫描器、打印机等组建报告单打印输出装置,将实验室信息系统（LIS）的人工条形码取单模块改造为自助取单模块。 结果：患者将取单凭证上的条形码贴到扫描区域,扫描器自动识别条形码后,电脑屏幕立即显示报告单信息,同时进行语音播报;自助取单模块自动检索已完成检测的报告单信息,将未打印的报告信息提取后发送至打印机打印并从出单口输出给患者;使用该系统后,门、急诊患者满意度逐年上升;由原先每天必须有一人（高峰时两人）为患者打印报告单,至目前不需人值守。 结论：组装的取单系统实现了报告单发放的自助化与不间断化,比商品化取单装置更省钱、更方便。     

基于DICOM结构化报告模型和可扩展标记语言的放疗计划电子病历

背景：如何建立DICOM标准与医院信息系统间的互联和共享成为新的研究方向。目的：通过对DICOM结构化报告标准的研究,结合可扩展标记语言结构的特点,设计出适合放射治疗计划的电子病历。方法：根据DICOM结构化报告标准,设计放射治疗计划电子病历的专业模板,使用可扩展标记语言模式对DICOM数据格式进行重定义,以面向对象的方法生成符合结构化报告标准的可扩展标记语言文件,然后进行可扩展样式表语言的转换或者生成符合DICOM结构化报告标准的DICOM文件。结果与结论：针对放射治疗计划对象的特点,设计了放疗计划结构化报告模板,包含36个模板标识符。在VisualC＋＋2008平台编写的软件上可以生成3种格式的电子病历文件,可以很好的与医院信息系统互连,最终实现以电子化的方式管理放疗计划信息,减少人工误差,实现真正的无纸化。     

Knowledge-driven decision support for assessing dose distributions in radiation therapy of head and neck cancer

Purpose

Clinical data that are generated through routine radiation therapy procedures can be leveraged as a source of knowledge to provide evidence-based decision support for future patients. Treatment planning in radiation therapy often relies on trial-and-error iterations, experience, judgment calls and general guidelines. The authors present a knowledge-driven decision support system that assists clinicians by reducing some of the uncertainties associated with treatment planning and provides quantified empirical estimates to help minimize the radiation dose to healthy critical structures surrounding the tumor.

Methods

A database of retrospective DICOM RT data fuels a decision support engine, which assists clinicians in selecting dose constraints and assessing dose distributions. The first step is to quantify the spatial relationships between the tumor and surrounding critical structures through features that account for distance, volume, overlap, location, shape and orientation. These features are used to identify database cases that are anatomically similar to the new patient. The dose profiles of these database cases can help clinicians to estimate an acceptable dose distribution for the new case, based on empirical evidence. Since database diversity is essential for good system performance, an infrastructure for multi-institutional collaboration was also conceptualized in order to pave the way for data sharing of protected health information.

Results

A set of 127 retrospective test cases was collected from a single institution in order to conduct a leave-one-out evaluation of the decision support module. In 72 % of these retrospective test cases, patients with similar tumor anatomy were also found to exhibit similar radiation dose distributions. This demonstrates the system’s ability to successfully extract retrospective database cases that can estimate the new patient’s dose distribution.

Conclusion

The radiation therapy treatment planning decision support system presented here can assist clinicians in determining good dose constraints and assessing dose distributions by using knowledge gained from retrospective treatment plans.

     

Object recognition in medical images via anatomy-guided deep learning

PurposeDespite advances in deep learning, robust medical image segmentation in the presence of artifacts, pathology, and other imaging shortcomings has remained a challenge. In this paper, we demonstrate that by synergistically marrying the unmatched strengths of high-level human knowledge (i.e., natural intelligence (NI)) with the capabilities of deep learning (DL) networks (i.e., artificial intelligence (AI)) in garnering intricate details, these challenges can be significantly overcome. Focusing on the object recognition task, we formulate an anatomy-guided deep learning object recognition approach named AAR-DL which combines an advanced anatomy-modeling strategy, model-based non-deep-learning object recognition, and deep learning object detection networks to achieve expert human-like performance.MethodsThe AAR-DL approach consists of 4 key modules wherein prior knowledge (NI) is made use of judiciously at every stage. In the first module AAR-R, objects are recognized based on a previously created fuzzy anatomy model of the body region with all its organs following the automatic anatomy recognition (AAR) approach wherein high-level human anatomic knowledge is precisely codified. This module is purely model-based with no DL involvement. Although the AAR-R operation lacks accuracy, it is robust to artifacts and deviations (much like NI), and provides the much-needed anatomic guidance in the form of rough regions-of-interest (ROIs) for the following DL modules. The 2nd module DL-R makes use of the ROI information to limit the search region to just where each object is most likely to reside and performs DL-based detection of the 2D bounding boxes (BBs) in slices. The 2D BBs hug the shape of the 3D object much better than 3D BBs and their detection is feasible only due to anatomy guidance from AAR-R. In the 3rd module, the AAR model is deformed via the found 2D BBs providing refined model information which now embodies both NI and AI decisions. The refined AAR model more actively guides the 4th refined DL-R module to perform final object detection via DL. Anatomy knowledge is made use of in designing the DL networks wherein spatially sparse objects and non-sparse objects are handled differently to provide the required level of attention for each.ResultsUtilizing 150 thoracic and 225 head and neck (H&N) computed tomography (CT) data sets of cancer patients undergoing routine radiation therapy planning, the recognition performance of the AAR-DL approach is evaluated on 10 thoracic and 16 H&N organs in comparison to pure model-based approach (AAR-R) and pure DL approach without anatomy guidance. Recognition accuracy is assessed via location error/ centroid distance error, scale or size error, and wall distance error. The results demonstrate how the errors are gradually and systematically reduced from the 1st module to the 4th module as high-level knowledge is infused via NI at various stages into the processing pipeline. This improvement is especially dramatic for sparse and artifact-prone challenging objects, achieving a location error over all objects of 4.4 mm and 4.3 mm for the two body regions, respectively. The pure DL approach failed on several very challenging sparse objects while AAR-DL achieved accurate recognition, almost matching human performance, showing the importance of anatomy guidance for robust operation. Anatomy guidance also reduces the time required for training DL networks considerably.Conclusions(i) High-level anatomy guidance improves recognition performance of DL methods. (ii) This improvement is especially noteworthy for spatially sparse, low-contrast, inconspicuous, and artifact-prone objects. (iii) Once anatomy guidance is provided, 3D objects can be detected much more accurately via 2D BBs than 3D BBs and the 2D BBs represent object containment with much more specificity. (iv) Anatomy guidance brings stability and robustness to DL approaches for object localization. (v) The training time can be greatly reduced by making use of anatomy guidance.     

医院急诊管理软件的开发及临床应用

目的：研制医院急诊管理软件,并应用于急诊临床医疗工作。方法：采用微软可视化编程工具Mi—crosoftVisualFoxPro开发软件,自主开发适用于医院急诊管理的计算机辅助专家系统。医务人员通过该系统随时查阅急诊疾病的诊断和治疗,并可以进行流行病学分析,提出相应对策。结果：系统主要包括急诊流行病统计分析模块、急诊患者抢救质量控制模块、急诊患者抢救临床路径管理模块、急诊患者护理程序管理模块、急诊医学培训管理模块,并可对急诊统计数据进行处理和分析。结论：该软件可以满足急诊临床抢救需要,并可作为管理、科研、培训之用,具有较好的临床实用价值。     

Evaluating the Effectiveness of an Electronic Learning Tool for Volumetric Imaging Training—Perceptions of Radiation Therapy Professionals

PurposeDaily volumetric imaging through cone-beam computed tomography (CBCT) has greatly impacted the roles and responsibilities of radiation therapists (RTTs). A CBCT eLearning module was developed at our cancer centre to equip RTTs with critical thinking skills and clinical judgement required in a CBCT guidance environment. This study aims to evaluate the effectiveness of the electronic module and its impact on the learner's outcome from the perspectives of various radiation therapy professions and to assess the applicability of the eLearning module to RTTs, oncologists, and physicists.Methods and MaterialsThe module “Myths in Cone-Beam Computed Tomography Practice” was evaluated by participants from our in-house accelerated education program. A 21-item questionnaire was developed to assess the module effectiveness. Two cohorts of attendees from the in-house accelerated education program (19 oncologists, 14 physicists, 14 therapists) were asked to voluntarily complete the survey following review of the module. Data analyses were performed between groups to determine differences in their perceptions.ResultsTwenty-one participants (5 oncologists, 3 physicists, 13 therapists) responded to the survey yielding a response rate of 44.68%. Survey responses indicate learners found the format user friendly, clear, and easy to navigate. All participants agreed that the electronic format of this module is conducive to learning with 60% agreement that this module is more useful than live sessions; 94.74% agreed that the module increases confidence in practicing image-guided radiation therapy.ConclusionsThis module is a useful resource for all disciplines of radiation medicine. While the electronic format of this module may be useful worldwide in centres requiring training of their employees in volumetric image-guided radiation therapy, live interactive sessions should supplement this training.     

Management of oral disease prior to radiation therapy.

Radiation therapy for malignant tumors of the head and neck is associated with significant side effects involving the oral cavity. For example, radiation therapy leads to reduced vascularity and oxygen tension of the oral hard and soft tissues and also to salivary gland dysfunction. These changes increase the risk of dental decay and oral infections and lead to reduced healing capacity following oral surgery procedures. A severe complication of radiation therapy is osteoradionecrosis of the jaw bone. The purpose of this paper is to review preradiation oral examination and treatment. Patient management regarding oral disease prior to radiation therapy has to accomplish a number of goals: (1) to identify existing oral disease and potential risk of oral disease, (2) to remove infectious dental/oral foci before the start of radiation therapy, (3) to prepare the patient for the expected side effects with information about them, (4) to establish an adequate standard of oral hygiene to meet the increased challenge, (5) to provide a plan for maintaining oral hygiene and fluoride treatment, for oral rehabilitation, and for follow-up and (6) to inform the patient about the availability of any financial support for dental treatment, and finally (7) to establish the necessary multidiciplinary collaboration within the health care system so that oral symptoms and sequelae before, during and after the radiation therapy can be reduced or alleviated. The methods used to accomplish these goals may vary between cancer centers. Each center should have a multidisciplinary team to handle such problems. After the end of radiation therapy most of the dental treatments in our patients are done by private dentists, except for some oral surgery procedures, which are performed in hospital. In our experience, the major challenge in this process is related to (1) informing of the patient, (2) timing the coordination between all the health care workers involved, (3) establishing an adequate schedule for dental treatment and follow-up, and (4) securing patient compliance to prevent or reduce the oral side effects.     

肠造瘘病人生活质量与社会支持的相关性研究

[目的]探讨肠造瘘病人生活质量与社会支持之间的相关性。[方法]采用方便抽样的方法以2012年3月—2012年12月到门诊随访的80名肠造瘘病人作为调查对象,采用现有量表社会支持评定量表和癌症病人生命质量测定量表分别评定病人的社会支持和生活质量,并将取得的数据进行统计学分析。[结果]肠造瘘病人的生活质量普遍都偏低,与社会支持的三个维度之间都存在明显的正相关关系(P0.05),即社会支持高的肠造瘘病人生活质量普遍都较社会支持低的病人生活质量高。[结论]良好的社会支持能够提高肠造瘘病人的生活质量。