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《医疗健康领域的数字孪生变革》翻译与简评

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来源:数字孪生体实验室原创

翻译和简评:陈志强

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本文是土耳其安卡拉的HAVELSAN公司研发人员托尔加•埃罗尔(Tolga Erol)和阿里夫•弗坎(Arif Furkan Mendi)等共同编写的一篇关于医疗健康领域数字孪生变革应用的技术文章。HAVELSAN是一家土耳其软件和系统公司,在国防和IT领域拥有业务。HAVELSAN业务涉及:C4ISR、海军作战系统、电子政务应用、管理信息系统、模拟和培训系统、后勤支持、国土安全系统和能源管理系统等领域。

HAVELSAN主要负责提供地面支持部分,包括船员培训、任务规划和软件维护功能。

在此根据原稿正文内容进行了翻译与整理。鉴于翻译水平有限,本文将原文一并给出,以方便读者理解阅读。

读后感和简评

数字孪生技术与区块链、边缘计算等一起,跻身Gartner的 2019年十大战略技术趋势之列。数字孪生技术的不断成熟应用将深深地影响到每个人的未来生活,甚至可能改变每个人的生存模式。本文系统介绍了数字孪生技术在涉及医疗健康行业的数字患者、制药行业、医院和可穿戴技术四个主要领域应用成果及案例,指出了目前医疗健康领域数字孪生应用暂局限于人体某器官研究的相关问题,并就医疗健康领域数字孪生的未来应用研究提出了相应的见解和方向,如军队士兵数字孪生体的研究应用,整个人体数字孪生体的综合应用研究等,是一篇较完整介绍数字孪生体技术在医疗健康领域变革应用的文章,可为相关医疗卫生部门或科研机构提供一定的参考指导。


0 Abstract  摘要

Digital Twin technology entered our lives in the fields of production and engineering at the beginning with Industry 4.0, and it has also shown itself with studies that can be evaluated as revolutionary in the field of health. The Digital Twin is a digital replica that allows modeling the state of a physical asset or system. In the healthcare field, serious steps have been taken in creating Digital Twins of patients as well as Digital Twins of medical devices. The Digital Twin of the patient is created as a result of transferring the patient's physical characteristics and changes in the body to the digital environment. This technology offers innovative and definitive solutions for correct diagnosis and following the treatment processes suitable for the patient, which is one of the most important principles of medicine. At the same time, the use of technology is seen in studies in the personalized medicine and pharmaceutical industry. In this study, considering the impressive potential of the Digital Twin technology in the field of health, qualified studies that will guide future studies are emphasized. 

从工业4.0开始,数字孪生技术就进入了生产和工程领域的生活,并且通过在医疗健康领域具有革命性意义的研究也表明了数字孪生技术的影响力。数字孪生体是一个数字副本,可以对实体资产或系统的状态进行数字建模。在医疗健康领域,在创建患者的数字孪生体以及医疗设备的数字孪生体方面已采取了严格的步骤。通过将患者的身体特征和身体变化数据转移到数字环境中,创建了患者的数字孪生体。这项技术为正确诊断和遵循适合患者的治疗过程提供了创新的确定性解决方案,这是医学上最重要的应用之一。同时,在个性化医学和制药行业的研究中也看到了该技术的使用。在这项研究中,考虑到数字孪生技术在医疗健康领域的巨大潜力,强调了可以指导未来研究的有效研究方向。

Keywords-Digital Tiwin, Digital Transformation, Healthcare, Industry 4.0 

关键字-数字孪生、数字化转型、医疗健康领域、工业4.0


Introduction 介绍

With the COVID-19 pandemic process, the importance of human health and health services has increased. In addition to this, it has come to the fore to ensure that working lives are sustainable from a distance and digitally. Governments and organizations have carried out various studies on digitalization and plans/arrangements continue. The health sector has been the most needed and demanding sector among the pandemic process. At the same time, in various fields, there have been situations such as digitalizing systems so that business processes can be managed remotely, and product/system development processes are accelerated. Meeting these demands is possible with Digital Twin technology. Studies are carried out for both the health sector and the digitalization field. In the "Hype Cycle for Healthcare Providers,2020" report of Gartner, one of the leading research organizations in the world, it is stated that the subject of "Digital Twins in Healthcare" is on the rise and the interest in technology is gradually increasing [1]. Digital Twin technology, which is expected to increase in both the number and diversity of healthcare activities, offers promising revolutionary solutions.

随着近期新冠病毒大流行过程的发展,人类健康和保健服务的重要性日益提高。除此之外,确保远距离和数字化的工作生活已成为人们关注的焦点。各国政府和组织已对数字化转型进行了各种研究,并且计划/安排仍在继续。在新冠病毒大流行过程中,医疗卫生部门一直是最需要数字化应用和要求最高的部门。同时,在各个领域中,都存在诸如将系统数字化应用这样的情况,以便可以远程管理相关业务流程,并加速产品/系统开发流程。使用数字孪生技术可以满足以上这些需求,并在医疗卫生部门和数字化领域都进行了应用研究。全球领先的研究组织之一Gartner的“ 2020年医疗健康行业发展周期预测”报告指出,“医疗健康领域的数字孪生体应用”的主题正在增加,并且对该数字孪生技术的兴趣也正逐渐增加[1]。预计数字孪生技术将增加医疗保健应用活动的数量和种类,并提供有希望的革命性解决方案。 

The Digital Twin is a digital copy obtained by modeling the state of a physical system, collecting data through sensors placed on these systems, and reflecting this data into digital media. Digital Twins build a bridge between the physical and digital world by enabling us to understand the past and present processes and make predictions for the future. Known for its various studies in the field of engineering, this technology has many applications in various branches in the field of health. Similar to the engineering approach, it can also be applied to the healthcare field. Predictive maintenance services involved in engineering, early failure predictions; In the field of health, it refers to concepts such as predicting and early diagnosis of diseases that may occur by examining organs or symptoms in the body. In the case of atherosclerosis in the health field, performing a vascular bypass operation to restore blood flow, replacing the eye lens of cataract patients with a new lens, and organ transplantations can actually be defined as engineering activities in the health field [2].

数字孪生体是通过对物理系统的状态建模,通过放置在这些系统上的传感器收集数据并将此数据反映到数字环境中而获得的虚拟数字副本。数字孪生体使我们能够了解物理世界过去和现在的过程并为其未来发展做出预测,从而在物理世界和数字世界之间架起了一座桥梁。以其在工程领域的各种研究应用而闻名,该技术在医疗健康领域的各个分支中也有许多应用。与工程领域应用方法类似,数字孪生应用方法也可以应用于医疗保健领域。如工程领域中涉及的预测性维护服务、早期故障预测;在医疗健康领域它指的是诸如对可能通过检查人体器官或症状而发生的疾病进行预测和早期诊断的概念。在医疗健康领域发生冠状动脉粥样硬化的情况下,执行冠状动脉搭桥手术以恢复血流;用新的晶状体替换白内障患者的眼镜,器官移植等实际上可以被定义为医疗健康领域的工程活动[2]。

图片

Fig.1.An Example of Digital Human Body and Data [3] 

图1 个人数字孪生体与数据示例[3] 


Errors that may occur in medical devices, incorrect detection of medical findings, and misinterpretation of the findings can lead to misdiagnosis, wrong diagnoses to wrong treatments, and wrong treatments that may result in negativity. For this reason, it is very important to anticipate and prevent errors. As a result of misdiagnosis and treatment, the patient's vital functions may deteriorate, leading to irreversible consequences in his life, and even the patient may lose his life. For example, if the leg muscle infarction is not diagnosed at the right time, or if it is misdiagnosed and treated, it can cause muscle death in the leg and cause irreversible damage to the leg, resulting in amputation or permanent disability. Digital Twin technology will also help in early and accurate diagnosis of cancer diseases. Cancer treatments are very difficult and risky processes for patients, patient relatives, and doctors. In critical diseases, a group of different patients with the same disease may respond positively to a certain treatment method, but not another group. With this situation, Hippocrates '"There is no disease, there is a patient."[4] when we consider the aphorism, the importance of personalized medicine is understood. When we examine personalized medicine, we can talk about personalization of treatment, especially personalized medicines based on data. Digital twins used for this purpose are built on computer-based, or in silico, models that are fed individual and population data [5]. There are Digital Twin studies, such as the creating of Digital Twin of the whole human body and personalized medicine, whose foundation is laid but expected to be completed in the future. The studies will bring about revolutionary developments in the health sector and will lead to an increase in the progress in the field of health and the success rates in the treatment methods applied. In this study, we will examine the Digital Twin studies that have been and are planned to be carried out in the field of health, shedding light on the future, from the perspectives of digital patients, the pharmaceutical industry, hospital, and wearable technologies. Then we will make future suggestions and predictions for Digital Twin technology in healthcare. 


医疗检测设备中可能发生的错误,如对医疗行业结果的错误检测以及对结果的误判可能导致医生的错误诊断,从而导致医生因错误诊断而实施错误治疗以及可能导致隐藏的医源性损害治疗。因此,医疗健康领域的检测预判并防止错误非常重要。由于误诊而治疗,患者的生命机能可能因此恶化,导致其生命不可挽回的后果,甚至患者还可能丧生。例如,如果未在正确的时间诊断患者腿部肌肉梗塞,或者如果误诊而治疗,可能会导致患者腿部肌肉坏死并导致其腿部不可逆转的损伤,从而导致患者截肢或永久性残疾。数字孪生技术还将有助于医生在患者早期准确地诊断癌症。对于患者、患者亲属和医生而言,癌症诊断和治疗是非常困难且危险的过程。在严重疾病中,一组患有相同疾病的不同患者可能对某种治疗方法有积极反应,而另一组则无反应。在这种情况下,希波克拉底提出“没有疾病,只有病人。” [4]当我们考虑到这个格言时,就可以理解个性化药物的重要性。当我们检查个性化药物时,我们可以谈论治疗的个性化,尤其是基于数据的个性化药物。用于此目的的数字孪生体是建立在基于计算机或计算机模拟的模型上的,该模型可提供个人和人口数据[5]。有相应的数字孪生应用研究,例如创建整个人体的数字孪生体和个性化医学,其基础已经建立,但有望在将来完成。这些研究将带来医疗卫生部门的革命性发展,并将导致医疗卫生领域的进步以及所采用的治疗方法的成功率增加。在本研究中,我们将从数字化患者、制药行业、医院和可穿戴技术的角度,对已经在和计划在医疗健康领域进行的数字孪生技术应用研究进行研究,以阐明未来方向。然后,我们将对医疗健康领域的数字孪生技术提出未来的应用建议和预测。



2. Healthcare Applications 医疗健康应用

With the development of technology day by day, developments are occurring in the field of healthcare. According to Markets and Markets' loT in Health Market report, the global loT in healthcare market size is expected to grow from USD 72.5 billion in 2020 to USD 188.2 billion by 2025, at a Compound Annual Growth Rate(CAGR) of 21.0% during the forecast period [6]. 

随着技术的日新月异,医疗健康领域正在发生巨大变化。根据Markets and Markets的《医疗健就好市场报告》,全球医疗健康市场规模预计将从2020年的725亿美元增长到2025年的1882亿美元,在预测期内的复合年增长率(CAGR)为21.0%[6]。 

Digital Twin is used in the healthcare field for purposes such as improving, analyzing, and developing predictions for patients, hospitals, and the pharmaceutical industry. This technology gives very successful results for processes and machines. The development of the Digital Twin of the human body is similar to engineering products but consists of more advanced and complex processes. Sensors can efficiently provide data to the Digital Twin of the designed object but can be more expensive and time-consuming as data from individuals is often obtained through blood tests, imaging systems, and health scans. However, the developments that will be achieved as a result of the Digital Twin studies for the human body will accelerate the diagnosis and treatment processes and increase the accuracy rates. In this context, the concept of "Digital Patient" has come to the fore with the efforts to create the Digital Twin of the human body. The digital patient is patient-specific modeling to support medical decisions. This concept was introduced as part of an R&D project funded by the European Commission. Digital Patient Roadmap (Digital Patient Roadmap) report was prepared with the DISCIPULUS project, which is part of the Coordination and Support Action Plan financed by the European Commission. With the project carried out within the scope of the European Union 7th R&D Framework Program (2007-2013), it is aimed to determine the roadmap for realizing the digital patient paradigm. Partners in the DISCIPULUS project were: University College London. United Kingdom; empirica Communication and Technology Research. Germany; The University of Sheffield, United Kingdom; Istituto Ortopedico Rizzoli, Italy and Universitat Pompeu Fabra, Spain. Prominent recommendations according to the Digital Patient Roadmap report are as follows: 

数字孪生技术在医疗健康领域主要用于针对患者的医疗诊断技术和方法工具的改善、分析和开发;以及用于医院和制药行业的分析和预测。这项技术为医疗诊断过程能力提升和医疗检测设备能力带来了非常成功的应用结果。人体数字孪生的发展与工程产品相似,但包含更先进和复杂的应用过程。人体通过可穿戴设备等传感器可以有效地将人体数据提供给该对象的数字孪生体,但由于通常通过血液检测、成像系统和健康扫描来获取个人数据,因此可能更加昂贵且耗时。但是,数字孪生体的应用研究将加速人体的疾病诊断和治疗过程,并提高医疗诊断和治疗准确率。在这种情况下,“数字病人”的概念随着创造人体数字孪生体的努力而脱颖而出。数字患者是特定于患者的模型,以更好的支持医生的相关医疗决策。这一概念是由欧盟委员会资助的研发项目的一部分中提出的。“数字患者路线图”报告是由DISCIPULUS项目准备的,该项目是由欧盟委员会资助的“协调与支持行动计划”的一部分。该项目是在欧盟第七个R&D框架计划(2007-2013)范围内进行的,旨在确定实现数字患者应用案例的路线图。DISCIPULUS项目的合作伙伴是:英国伦敦大学学院 ; 欧盟《Empirica》期刊-通信和技术研究;德国; 英国谢菲尔德大学;意大利里佐利骨科学院和西班牙的庞培法布拉大学。根据“数字患者路线图”报告提出的建议如下:

Silico medicine, also known as computational medicine,includes modeling and simulation technologies that directly contribute to theprevention, diagnosis, treatment planning, execution, and management of thedisease. There is a difficult process to overcome in creating a digital patient.Integrated and interdisciplinary applied studies of biomedical, mathematics,bioengineering, and computer science branches are needed.

生物医药信息学,也称为计算医学,包括直接有助于疾病预防、诊断、治疗计划实施和管理的建模和模拟仿真技术。创建数字患者需要克服一个困难的过程,需要对生物医学、数学、生物工程和计算机科学分支进行综合和跨学科的应用研究。

More data is needed for the digital patient. To date,only a few virtual patient projects have been completed.

数字患者需要更多数据。迄今为止,仅完成了几个虚拟患者项目。

Virtual patient technology has been defined as a fullyautonomous process. However, there are two important points in theimplementation of this vision in practice. The first of these is the need forexperienced people in the field for the processes of creating the Digital Twindue to the complex nature of the human being. The second is that the collecteddata, which is important in terms of decision making, are complete and madesuitable for analysis [7].

虚拟患者技术已被定义为完全自主的过程。但是,在实践中实施此技术构想有两个要点。首先,由于人类的复杂性,该领域需要经验丰富的人员来创建数字孪生体;第二个是收集到的数据必须是完整的,且适合进行分析应用,这对于决策很重要[7]。

We will examine digital twin healthpractices in four main areas: digital patients, the pharmaceutical industry,hospitals, and wearable technologies.

我们将在以下四个主要的医疗健康领域研究数字孪生体的应用实践:数字患者、制药行业、医院和可穿戴技术。


A.   Digital Patient 数字患者

 An article was published by Chineseresearchers in 2018 to understand how the connections between memory and neuralnetworks are formed and to create a detailed three dimensional brain map of thehuman brain. They conducted various studies in the field of neuroscience andartificial intelligence to learn about the research problems in the article. Atthe same time, two projects named Brain Initiative and Human Brain Project wereinitiated in America to solve the structure and connections of the human brainand transfer it to the computer. The Blue Brain Project is one of the subprojects of the Human Brain Project [8]. The project also referred to as theBlue Brain Cell Atlas, is the most comprehensive and accessible resourcedescribing the number, types, and locations of cells in all areas of the mousebrain. He published the first three-dimensional atlas containing the entiremouse brain [9].

中国研究人员在2018年发表了一篇文章,以了解人体记忆与神经网络之间的联系是如何形成的,并创建了人脑的详细三维脑图。他们在神经科学和人工智能领域进行了各种研究,以了解本文中的研究问题。同时在美国启动了两个名为“大脑计划”和“人脑计划”的项目,以解决人脑的结构和连接并将其传输到计算机上的问题。“蓝脑计划”是人脑计划的子项目之一[8]。该项目也称为“蓝脑细胞图集”,是最全面、可访问的资源,它描述了小鼠脑各区域中细胞的数量、类型和位置。他发表了第一个包含整个小鼠大脑的三维图集[9]。

image.png


Fig.2.An ExampleBrain Image from the Blue Brain Project in Digital Environment [10]

图2.“蓝脑项目”数字环境中的示例脑图像[10]


Another work in the field of health isto create virtual twins of soldiers with the US Army and the University ofNevada. Digital twins of soldiers will be created using various imagingtechniques such as MRI. Thus, it has been reported that organs can be producedby the 3D printing method by using models in Digital Twins in case of anyinjury.


医疗卫生领域的另一项研究工作是与美国陆军和内华达大学一起使用各种成像技术(例如MRI)来创建陆军士兵的数字孪生虚拟体。因此,据报道在发生任何伤害的情况下,美国陆军可以通过使用士兵数字孪生体中的模型以3D打印方法来为受伤害的士兵修复受损身体。


Sim & Cure is the first company tomarket a patient-based simulation model that allows predicting the placement ofmedical devices (flow guiding, intravascular device, laser-cut stent) foraneurysm treatment. Sim & Size simulates each size and device type based onthe patient's unique anatomy to provide the necessary information beforeimplant sizing selection. In 25 countries, more than 250 hospitals and morethan 2000 operations were simulated and aimed to minimize the margin of error[11]. The first of the two main visions of the company is personalized medicineand the second is to develop a treatment plan by securing the treatment appliedto the patient [12]. In Sim & Cure's new method,3D rotational angiographyis used to create a 3D model of the aneurysm and surrounding blood vesselsafter the patient is prepared for surgery. Sim & Cure's software importsthe model of the artery and presents it to the surgeon who chooses the pointsdefining the ideal end position on the artery and the size of the implant placed.Using software developed by ANSYS, the physician can rotate and zoom the imageto fully understand the relationship between implant and aneurysm. Color codingcan be used to show the exact area where the implant touches theembolism(occlusion). A cross-sectional profile shows any gap between theimplant and the artery. Each simulation takes only 10 to 25 seconds dependingon the device selected. The surgeon can easily select and simulate additionaldevices and sizes for analysis to determine which will provide the bestresults. In less than five minutes, the surgeon can complete the simulationprocess, select the most suitable device, and initiate the operation [13].


Sim&Cure是第一家销售基于患者仿真模型分析并协助外科医生成功完成手术的公司,该仿真模型可以预测用于动脉瘤治疗的医疗设备(血流引导、血管内设备、激光切割支架)的放置。其开发的软件解决方案Sim&Size可根据患者的独特生理解剖结构模拟每种需植入体尺寸和相应的医疗设备类型,为外科医生在选择适合患者植入体的尺寸之前提供必要的参考信息。该软件解决方案在25个国家/地区,模拟了250多家医院的2000多场手术室,旨在最大程度地协助外科医生降低手术错误率[11]。该公司有两个主要愿景:第一个是个性化药物;第二个是通过确保对患者的治疗安全来协助医生制定治疗计划[12]。在Sim&Cure的应用方案中,患者准备手术后,可以使用3D旋转血管造影术来创建其动脉瘤和周围血管的3D模型。然后通过Sim&Cure的软件导入患者动脉3D模型,并将其提供给外科医生,由外科医生患者动脉3D模型上选择定义动脉上理想末端位置和所植入体尺寸的点。外科医生通过使用ANSYS开发的软件,可以旋转和缩放图像,以充分了解植入物与动脉瘤之间的关系;同时可以使用颜色编码来显示植入物接触患者栓塞(阻塞)的确切区域,横截面轮廓显示了植入物和动脉之间的任何间隙。每次仿真分析仅需10到25秒,具体取决于外科医生所选择的医疗设备。外科医生可以轻松地选择和模拟其他医疗设备和植入物尺寸以进行分析,以确定哪种医疗设备可以提供最佳手术治疗结果。在不到五分钟的时间内,外科医生即可完成手术前的仿真分析过程,选择最合适的手术设备,然后开始手术[13]。


Thanks to the Digital Twin technology,the times when physical parts in the machines need to be changed can bedetected early. Similarly, Philips created the "Heart Model", apersonalized Digital Twin of the heart, which is an important step towards theidea of the digital patient, starting with the question of whether it ispossible to discover and treat ailments in the human body before they occur.Based on the unique images of the heart, Heart Model adapts the generic modelto a personalized model. The Philips Heart Navigator tool, also developed byPhilips, combines the Computed Tomography (CT) images obtained before thesurgical procedure in a single image of a patient's heart anatomy with a layerof live X-ray information during surgery. The tool helps the surgeon select theright device by simplifying prior procedure planning. Provides real-time 3Dinsight to position the device during surgery. This device is a physical guidefor the surgeon on how to proceed [14].


由于采用了数字孪生技术,因此可以及早发现需要更换机器中物理零件的时间。同样,飞利浦创建了“心脏模型”,这是个性化的心脏数字孪生体,这是朝着数字患者的理念应用迈出的重要一步,首先要问的是,是否有可能在患者疾病发生之前就发现并治疗人的疾病。基于心脏的独特图像,心脏模型可将通用模型调整为个性化模型。飞利浦开发的心脏导航仪工具将在手术前获得的计算机断层扫描(CT)图像与患者心脏解剖结构的单个图像相结合,并在手术过程中提供了一层实时X射线信息。该工具可简化外科医生先前的手术计划,从而帮助外科医生选择合适的手术设备,并提供实时3D洞察力,以在手术过程中精准定位设备。该设备是外科医生如何进行手术的物理向导[14]。


图片

Fig.3.An Example Heart Image from Philips Heart Model [15]

图3.来自飞利浦“心脏模型”的心脏图像示例[15]


Siemens Healthineers producesintelligent algorithms that can generate digital organ models based on largeamounts of data. Cardiologists in a research project at Heidelberg Universityhave tested these algorithms for cardiac resynchronization therapy. This usedtherapy is a treatment option for patients with chronic congestive heartfailure. In the study, cardiologists simulated the heart's electrical signalswith the help of electrodes in a computer environment and created the DigitalTwin with an artificial intelligence infrastructure. Models created with MRimages and ECG measurements simulated the first and fully simulated heart. Thanksto the created Digital Twin, it saves time in terms of making a definitivediagnosis as well as performing various treatment trials [16].


西门子医疗部门Healthineers开发了可以基于大数据生成数字器官模型的智能算法。海德堡大学的一个研究项目的心脏科医生已经对这些用于心脏再同步治疗的算法进行了测试。对于慢性充血性心力衰竭患者,这种使用的疗法是一种治疗选择。在这项研究中,心脏病专家在计算机环境中借助电极模拟了心脏的电信号,并创建了具有人工智能基础设施的数字孪生体。同时用MR图像和ECG测量创建的模型模拟了第一个和完全模拟的心脏。多亏了创建的数字孪生体,它可以节省进行明确诊断以及进行各种治疗试验的时间[16]。


Siemens Healthineers Turkey, about newtechnologies in health care and imaging solutions to digitalize internationalparticipation 40th National Congress of Radiology TURKRAD was introduced in2019. Participating in the event with the slogan We are Shaping the Future inHealth', Siemens Healthineers attracts great attention with the demos of theDigital Twin technology and various products and continues to work to offer theDigital Twin technology used in different industries to the service of thehealth sector. Following heart modeling, its first work in this area, thecompany is moving towards developing the Digital Twins of other organs,including the brain. Digital Twins, which are routinely used by cardiologists,provide better results thanks to pre-operative visualization and 3D imaging.This technology, which provides great convenience to cardiologists andcardiovascular surgeons, especially in correcting congenital heart defects inbabies, was introduced with a demo at TURKRAD 2019. Siemens Turkey Healthineershas set up a display for attendees who want to see their simple Digital Twins.The application, which attracted attention, was presented as a visual demo ofthe digital future in the health sector, the route of sensitive and personalizedmedicine [17].


西门子土耳其医疗健康公司于2019年在土耳其第40届全国放射学大会上介绍了用于国际参与的数字化医疗健康和成像解决方案的新技术,会上同时展示了数字孪生体应用技术和各种产品的演示,并继续致力于为医疗健康行业提供用于不同行业的数字孪生体技术。在进行心脏建模(这是该领域的第一项工作)之后,该公司正朝着开发其他器官(包括大脑)的数字孪生体迈进。心脏病专家通常使用的数字孪生体得益于术前可视化和3D成像技术,可协助提供更好的手术和治疗结果。西门子土耳其医疗健康公司在2019年全国大会的演示中引入了这项技术,演示了该技术应用为心脏病专家和心血管外科医生提供了极大的便利,尤其是在治疗婴儿先天性心脏缺陷方面。西门子土耳其医疗健康公司人员已经为想要看他们数字孪生技术简单应用的与会者设置了一个应用程序。该应用程序引起了人们的关注,以可视化方式演示了医疗卫生部门未来数字化应用的途径,即敏感和个性化医学的途径[17]。

When the studies in the field ofdigital patients are examined, most of the studies are aimed at developing theDigital Twin of a whole human body and focused on the creation of Digital Twinsof some organs. It is not too far to carry out studies on integrated DigitalTwins, where the number of studies in this field is increasing and theinteractions between organs will be seen.

当梳理数字患者领域的各项研究时,发现大多数研究还旨在开发整个人体的数字孪生体,并着重于某些器官的数字孪生体的创建。在集成数字孪生体上进行综合研究应用还不是太远,该领域的研究课题数量正在不断增加,并且器官之间的相互作用也将得到关注。


B.   PharmaceuticalIndustry 制药行业

Companies and researchers focused onlongevity are looking at body processes at the cellular level to see how agingprogresses, and try to find the right medicines and treatments that can slowthem down [5]. Some studies are also carried out on optimizing medicineproduction processes and personalized medicine issues. In addition to thesesubjects, the Computational Science Laboratory of the University of Amsterdamconducts studies in the fields of urban complex systems, computational finance,computational biology, complex systems theory, and computational bio-medicine. TheEuropean CompBioMed project, in which a research group in the laboratoryparticipated, is concerned with the development of the virtual human, as eachhuman life and physiology are different, the treatment method and medicinesshould be personal, changes in the performance of the human body can be seenwith a virtual twin created by the genetic code in the DNA of the people.Information in this area was published in a short film. The film also includesinformation about the application of appropriate treatment to patients, as theeffects of medicines on their bodies are first seen through this virtual twin[18]. A virtual twin is told about how medications can affect the right areas,what diet, exercise, and habits are necessary to improve quality of life, and even how bonescan be strengthened [19].

专注于长寿的公司和研究人员正在细胞生长水平上研究人体过程,以了解衰老如何发展,并试图找到合适的药物和疗法来延缓衰老[5]。还对优化药品生产过程和个性化药品问题进行了一些研究。除这些学科外,阿姆斯特丹大学计算科学实验室还从事城市复杂系统、计算金融、计算生物学、复杂系统理论和计算生物医学等领域的研究。实验室研究小组参加的欧洲CompBioMed(计算生物医学卓越中心)项目关注虚拟人类的发展,因为每个人类的生命和生理机制都不相同,因此治疗方法和药物应因人而异,改变人类的机能可以看到一个虚拟的数字孪生体,该数字孪生体是由人类DNA中的遗传密码产生的。这方面的信息已发布在相应的影片中。这部影片还包括有关对患者进行适当治疗的信息,因为首先通过这个虚拟数字孪生环境看到了药物对他们身体的影响[18]。一个虚拟的人体数字孪生体被告知药物如何影响正确的区域,改善生活质量所必需的饮食、运动和习惯,甚至是如何加强骨骼[19]。

The SIMULIA Living Heart project, whichDassault Systemes and the US Food and Drug Administration signed in 2014,signed a 5-year agreement, is the first study to use Digital Twin technologyspecifically to see the interaction of an organ with medicines. Thanks to thisstudy, it is aimed to reduce the activities of testing medicine trials onanimals [20]. SIMULIA Living Heart is a Digital Twin model that has beenvalidated against a wide variety of clinical measurements and created bysimulating a human heart. Educators, researchers in the field ofcardiovascular, medical device developers, clinicians, and many institutionsworked together to create the model. With computer simulation, doctors had theopportunity to see what they cannot see due to the mobility of the heart tissueand to study the complex structure in the heart by experimenting with the sameorgan model. It leads to personalized treatment by entering patient-specificvital signs and promising research in future medical treatments [21].

达索系统与美国食品和药物管理局于2014年签署了为期5年的SIMULIA心血管模拟仿真项目协议,这是第一个专门使用数字孪生技术观察器官与药物相互作用的研究。关于这项研究,其目的是减少对动物进行医学试验的活动[20]。SIMULIA心血管模拟仿真是一种数字孪生体模型,已针对各种临床测量结果进行了验证,并通过模拟人体的心脏来创建。教育者、心血管领域的研究人员、医疗设备开发人员、临床医生和许多机构共同合作创建了该数字孪生体模型。通过计算机模拟,医生有机会看到由于心脏组织的活动性而看不到的东西,并通过试验相同的器官模型来研究心脏中的复杂结构。通过输入患者特定的生命体征和在未来的医学治疗中有前途的研究,它可以导致个性化治疗技术的发展[21]。

IBM, together with the supercomputerWatson, aims to simulate biochemical processes in the body by using artificialintelligence techniques to detect cancerous cells in health data obtained fromthe past. However, the interaction of the 37 trillion cells that make up thehuman body is a process that is difficult to understand and almost impossibleto follow. However, even if each cell has different characteristics, it carriesthe same genetic information. Damage to cells caused by various reasons cancause the cells to divide and multiply uncontrollably and tumor formation. TheAlacris computer model can interpret the developing situations by understandingwhy the cell divides and the variables that cause its death with 800 genes and45 biochemical methods. Thus, which medicines can stop dangerous cells frommultiplying uncontrollably can be tested on the Digital Twins of patients. In apatient group with cancer, the mucous membrane tumor in the frontal sinus couldnot be killed as a result of chemotherapy, immunotherapy, and radiationreceived during normal treatment processes. However,70% of the cells dividinguncontrollably, as a result of the administration of medicine developed onlyfor breast and kidney cancer, which was designed in the Digital Twin, the dataobtained from the biopsy of the tumor after a few months show that the rate ofdividing cells decreased to 15% [22].

IBM利用沃森超级计算机,结合使用人工智能技术来检测过去获得的健康数据中的癌细胞来模拟在人体内的生化过程。但是,构成人体的37万亿个细胞之间的相互作用是一个难以理解且几乎无法遵循的过程。即使每个细胞具有不同的特征,它也携带相同的遗传信息。由于各种原因引起的细胞损伤可导致细胞不受控制地分裂繁殖,并形成肿瘤。Alacris计算机模型可以通过了解细胞分裂的原因以及使用800个基因和45种生物化学方法导致其死亡的变量来解释发育情况。因此,可以在患者的数字孪生体上测试哪些药物可以阻止癌细胞不受控制地繁殖。在患有癌症的患者组中,在正常治疗过程中进行化学疗法、免疫疗法和放疗等无法杀死鼻窦癌等粘膜肿瘤,且有70%的细胞不受控制地分裂。由于使用了数字孪生设计的仅针对乳腺癌和肾癌开发的药物,几个月后从肿瘤活检中获得的数据表明,分裂细胞的比率降低至15%[22] 。

Semic Health's Digital Body Total hasdeveloped the Digital Twin of Artificial Intelligence-based human biologicalsystems or organs or molecular systems, based on aggregated data and medicalhistories, to help diagnose current medical conditions and predict possiblehealth problems. Realistic predictions can be made by testing scenarios such asadjusting medicines doses for the treatment of many diseases such as differenttypes of cancer, liver sclerosis, Acute Myocardial Infarction, Alzheimer'sDisease on Digital Body Total [3].

Semic Health的数字化人体部门根据汇总的数据和病历开发了基于人工智能的人类生物系统或器官或分子系统的数字孪生体,以帮助诊断当前的医疗状况并预测可能的健康问题。根据数字孪生体,可以通过测试各种场景来做出现实的预测,例如调整用于治疗多种疾病的药物剂量,例如在数字化人体上汇总不同类型的癌症、肝硬化、急性心肌梗塞和阿尔茨海默氏病的应用[3]。


图片

Fig.4. Semic Health's Digital Body Total FuturePredictions [3]

图4.Semic Health的数字化人体未来总预测 [3]


Takeda Pharmaceuticals, which has madevarious initiatives to offer transformative therapies to patients all over theworld, has switched to Digital Twin technology in production to shortenpharmaceutical processes that take years to bring to market. By creatingDigital Twins of all processes, it can make realistic input output predictionsabout biochemical reactions that are difficult to model with machine learningtechniques used in Digital Twins [23].

武田制药已采取各种举措向全世界的患者提供变革性疗法,现已在转投生产中使用数字孪生技术,以缩短需要数年才能推向市场的药物研制过程。通过创建药物研制过程的所有数字孪生体,它可以对药物生化反应做出现实的输入输出预测,而这些预测很难通过数字孪生体中使用的机器学习技术来建模[23]。

Atos and Siemens are working with thepharmaceutical industry to improve manufacturing with an innovative solutionbased on a digital copy of the pharmaceutical manufacturing process. With"Process Digital Twin" for medicine production, currently tested inthe pharmaceutical industry and supported by IoT, artificial intelligence, andadvanced analysis, it aims to provide enhanced efficiency and flexibility forlong processes in the production of pharmaceutical products. Digital Twins ofphysical processes were created in the study and it was aimed to overcome thedifficulties in medicine production and efficiency by using real time data[24].

Atos和西门子正在与制药行业合作,通过基于制药生产过程数字孪生体的创新解决方案来改善药物制造过程。借助用于药品生产的“过程数字孪生体”(目前已在制药行业进行测试,并得到物联网、人工智能和高级分析的支持),它旨在为药品生产中的长流程提供更高的效率和灵活性。该研究创建了药物制造过程的数字孪生体,其目的是通过使用制药过程的实时数据来克服药物生产和效率方面的困难[24]。

In order to benefit from the efficiencyof the Digital Twin technology in the pharmaceutical industry, intensivestudies have been carried out in areas that are expressed with parameters suchas the medicine production process, human DNA, organs, cell behavior, etc.Developments in these areas are expected to assist in optimizing thepersonalized medicine and medicine launch processes planned for thepharmaceutical industry.

为了从数字孪生技术在制药行业的研制效率中受益,已经在用诸如药物生产过程、人类DNA、器官、细胞行为等参数表示的领域进行了深入研究。这些领域的发展有望帮助优化针对制药行业的个性化药物和药物开发流程。

 

C.   Hospital 医院

A Digital Twin study was carried outwith Siemens Healthineers to improve hospital processes due to high patientdemand, increasing waiting times, etc. in the radiology department of MaterPrivate Hospitals in Ireland. Within the scope of the study, a Digital Twin ofthe radiology department fed with real data was created. With the Digital Twin,various predictions were obtained and various scenarios were tested on thistwin. According to some data and recommendations of Digital Twin for MPH;

由于患者数量大、候诊时间增加等原因,爱尔兰Mater私立医院与西门子医疗健康公司基于其放射科的实际运营情况进行了数字孪生应用研究,以改善医院放射科的就诊流程。在研究范围内,根据放射科提供实际运营数据创建了数字孪生体。使用放射科数字孪生体,可以在此数字孪生体上获得各种预测并测试各种场景。以下为根据有关MPH的数字孪生体的一些数据和建议;


  • If less time is spent 13 minutes for CTand 25 minutes for MRI (Magnetic Resonance Imaging), patients' waiting timesmay be shortened.

  • 如果在CT上能减少13分钟和MRI(核磁共振)上能减少25分钟时间的话,则可能会缩短患者的候诊等待时间。


  • If less time is spent 28 minutes for CTand 34 minutes for MRI, patients will be able to return faster.

  • 如果在CT上能减少28分钟和MRI(核磁共振)上能减少34分钟时间的话,则患者可能会更快的完成就诊过程。


  • If MRI runs 32% and BT 26% more, theincreased equipment usage will not be left.

  • 如果MRI(核磁共振)的运行率高出32%,而BT(生物技术)的运行率高出26%,那么增加设备使用率的问题将不复存在。


  • If 50 minutes more hours of work per dayfor MRI, personnel costs can be reduced and 9,500 Euros per year can be saved[25].

  • 如果每天的MRI(核磁共振)设备多工作50分钟,则可以减少相应的人员成本,如每年可以节省9,500欧元[25]。



Thus, in the light of the informationprovided by the Digital Twin, the changes to be made in the planning andorganization for the radiology department of the hospital were determined.

因此,根据“数字孪生体”提供的信息,确定了医院放射科诊疗计划和组织方面要进行的更改。


图片

Fig.5.Realistic 3D Animation of Hospital [26]

图5.医院基于实际场景的3D动画[26]


The use of Digital Twins is expectedfor many hospital systems and resource management such as this study. Inparticular, it can be used in matters such as solving lack of the resource inhealth care during the COVID-19 pandemic process.

像本研究一样,有望在许多医院系统和资源管理中使用数字孪生体。特别是,它可用于解决新冠病毒大流行过程中医疗保健资源短缺的问题。


D.   WearableTechnologies 可穿戴技术

The startup acceleration center General Electric Health InnovationVillage, which supports 26 local startups in the fields of health and medicinein Helen ski, operates in partnership with USA-based Startup Health, theworld's largest digital health hub. GE also offers an innovative approach bybringing health to the cloud. Engineers in Helsinki specifically observepatients and are working on wireless devices that will not exceed a bandwidthsoon and transmit other information such as heart rate, blood pressure,respiration, etc. to the cloud continuously. With this information to beanalyzed by software, Digital Twins of each of the people can be created andthe system is working to develop software that can alert doctors in unexpectedcrises [27].

GE医疗健康创业创新中心与总部位于美国的Startup Health合作为Helen ski的26个本地健康和医药领域的本地创业公司提供支持,后者是世界上最大的数字健康中心。GE还通过将运行状况带入云来提供创新的方法。赫尔辛基的工程师在专门观察患者实际数据,并正在研究不会很快超过带宽的无线设备,并将其他信息(例如心率、血压呼吸等)连续传输到云中。借助软件对这些信息进行分析后,可以创建每个人的数字孪生体,并且系统正在开发可在患者发生意外危机中提醒医生的软件[27]。

Sooma, one of the startups that creates solutions that change people'slives in the healthcare industry with wearable technology, develops devicesthat simulate the electrical signals of the brain to treat depression, otherneurological and psychiatric disorders. Patients use these devices for30minutes in single-use and 5 days a week for 2 weeks. The patient places anelectrode on each of his temples that sends an electronic signal to the brain. Thepositive electrode boosts immediate brain activity, which is very useful fordealing with depressive symptoms. Studies show that brain activity andmetabolism in depressive patients is reduced or impaired. With the simulationof these areas, it is possible to restore normal brain functions and reducesymptoms of depression. With the Sooma Software Suite, patients can also bemonitored at home. An application is installed on the phone of the patientwhere he can enter data about his daily mood and feelings. All these data areupdated and uploaded to a cloud that the doctor can access on the internet. Byexamining these data and simulations, the doctor can monitor the treatmentprocess and make changes in the treatment program. Although Sooma anticipates theuse of this technology in hospitals very soon, it aims to create an alternativeto depression drugs and to eliminate the side effects of drugs by reducing theuse of drugs [28].

Sooma公司是使用可穿戴技术创造可改变人们在医疗健康领域中生活的解决方案的初创公司之一,其开发的设备可模拟大脑的电流信号以治疗抑郁症、其他神经系统疾病和精神疾病。患者在每个太阳穴上放置一个电极,该电极将电子信号发送到大脑。正极可以促进患者立即的大脑活动,这对于治疗抑郁症状非常有用。研究表明患者持续2周,每周使用5天,一次性使用这些设备30分钟,通过模拟抑郁症患者的大脑活动和新陈代谢减少或受损,可以恢复患者正常的脑功能并减轻抑郁症状。使用Sooma软件套件,还可以在家中监视患者。例如在患者的电话上安装一个应用程序,他可以在其中输入有关他的日常情绪和感觉的数据。所有这些数据都将更新并上传到医生可以在因特网上访问的云中。通过检查这些数据和模拟分析,医生可以监视患者抑郁症治疗过程并随时根据需要更改治疗程序。尽管Sooma公司预计很快会在医院中使用该技术,但它的目的是创建抑郁症药物的替代品,并通过减少药物的使用来消除药物对抑郁症患者的副作用[28]。

Developing products that use muscleactivation technology and electromyography (EMG) for a new dimension inunderstanding the behavior of muscles, Myontec analyzes the activity in themuscles and their responses to exercises according to the general health of thebody and transfers them to a digital environment thanks to the technologyplaced between the threads, and makes more effective exercises in the light ofthese data. The company examines the user's activities through shorts they havedeveloped, calculates the threshold at which the muscles perform best,increases training efficiency, and provides information about the warming andcooling times by reducing the risk of muscle injury [29]. The technologyintegrated into the product called Myontec Mbody Pro measures the electricalactivity of the muscles during training and provides an understanding of howthey behave under what conditions. With the sensor technology in the product,it records and analyzes the EMG data in the muscles together with the heartrate, heart rhythm, and heart rate. Thanks to real-time data and post-exerciseanalysis, it allows users to make their working techniques healthy andefficient, and to detect and prevent problems such as imbalances and deviationsin your muscular system [30].

Myontec公司开发了使用肌肉激活技术和肌电图(EMG)的产品来了解人体肌肉行为的新维度,该产品会根据人体的整体健康状况分析其肌肉的活动及其对运动的反应,并利用数字线程及传输技术将其转移到数字孪生环境中,并根据这些肌肉行为实时数据进行了更有效的模拟和分析。该公司通过他们开发的智能运动短裤来检查用户的肌肉活动,并计算出肌肉表现最佳的阈值,帮助用户提高训练效率,并可以通过降低肌肉受伤的风险来为用户提供有关保暖和降温时间的信息[29]。该智能运动短裤利用Myontec Mbody Pro技术可测量用户肌肉在训练过程中的电流活动,并了解它们在不同条件下的不同表现行为。利用产品中的传感器技术,它可以记录和分析用户肌肉中的EMG数据以及心率、心律和心率。得益于对用户运动实时数据和运动后分析,该智能运动短裤使用户的健康运动更加高效,并能够及时检测和预防用户肌肉系统的不平衡和偏离等问题[30]。

Expanding and combining wearabletechnologies that enable patients to be tracked physically and mentally willincrease efforts to create and track innovative and wider Digital Twins. In thenear future, wearable Digital Twin technologies will be applied to examinechanges in the musculoskeletal system of patients with mobility impairments aswell as paralysis.

扩展和组合应用可追踪身体和心理状况的可穿戴技术,将加大各企业和研究机构创建和追踪更广泛的数字孪生创新应用的努力。在不久的将来,可穿戴的数字孪生技术将用于检查行动不便和瘫痪患者的肌肉骨骼系统的变化。



3. Future Insights 未来见解

With the work done in the field ofDigital Twin and the developments in loT, sensors, big data, and artificialintelligence technologies, which have a large share in the formation of theDigital Twin, the number and variety of innovative studies in this field willincrease. Before physical interventions such as medicine therapy, radiotherapy,or surgical operations are performed on the human body, various studies can becarried out to make sure that it is really necessary. Even if it is notpreferred in case of difficulties in diagnosing diseases, a method that can beapplied is to use exploratory surgery. With the creation of a holistic DigitalTwin of the human body, the disease can be diagnosed by examining the necessaryregions on the patient's Digital Twin, without using the exploratory surgerymethod, which can sometimes be painful for the patient and prolong thepatient's treatment process. If the treatment method considered suitable forthe disease is tested on the patient's Digital Twin and is expected to yieldsuccessful results with a high probability, the relevant treatment may beapplied to the patient.

随着数字孪生领域的工作以及物联网、传感器、大数据和人工智能技术的发展(在数字孪生技术体系的形成中占有很大份额),医疗健康领域中数字孪生创新应用研究项目的数量和种类将越来越多增加。在对人体进行物理干预(例如药物治疗、放射治疗或外科手术)之前,可以进行各种数字孪生体模拟研究以确保该治疗手段或药物确实有必要。通过创建人体整体数字孪生体,医生可以通过检查患者数字孪生体上的必要区域来诊断疾病,而无需使用探索性手术方法,因为这有时会使患者感到痛苦并延长患者的治疗过程。即使在诊断疾病有困难的情况下不是首选方法,也还可以采用探索性手术的方法来诊断。如果认为适合该疾病的治疗方法并在患者的数字孪生体上进行了测试,并且有望以高概率获得治疗成功的结果,医生则可以立即对患者进行相关治疗。

In the field of physiotherapy, theDigital Twin technology can be used to monitor the muscle development ofpatients, to monitor the changes in the cells in the spine and bone movementwith physical therapy in conditions such as scoliosis. Following the treatmentprocess with the personal data of the patient, predictions can be made for itsimprovement. With the creation of Digital Twins of these patients who receivephysiotherapy as a result of in-vehicle and out-of-vehicle traffic accidents orparalyzed patients to be able to stand, walk and return to their former lives,information about what kind of treatment could be followed. In addition, thanksto real-time data transfer, various Digital Twin studies can be performed onchanges in exercise and muscle activities, whether the strain or exercises showthe right effect. It can be understood whether the patients respond to thetreatment by following their condition and whether the treatment provides thedesired effect. In addition, by testing various treatment methods on thepatient's Digital Twin, which one is most suitable, time is saved and costlytreatments that will not respond positively to the patient are avoided.

在物理康复治疗领域,数字孪生技术可用于监测患者的肌肉发育,通过脊柱侧凸等物理疗法来监测患者脊柱中细胞的变化和骨骼运动。根据患者的个人数据进行治疗后,可以对其进行康复预测。这些数字孪生体的创建和应用,为这些因车内和车外交通事故而接受理疗的患者或瘫痪的患者能够站立、行走和返回其受伤前的状态时,提供了可以参考和遵循的相关治疗方法信息。此外,得益于实时数据传输,可以对患者运动和肌肉活动的变化来进行各种数字孪生体的模拟并判断患者是股肉劳损还是锻炼的状态。同时可以了解,患者是否通过遵循自己的病情对治疗做出反应,以及治疗是否提供所需的效果。此外,通过在患者的数字孪生体上测试最合适的各种治疗方法,可以节省治疗时间,并避免了对患者没有积极反应和效果的昂贵治疗。

With the introduction of technologiesin the field of personalized medicines, it is aimed to accelerate the medicinedevelopment processes and to decrease the use of test subject animals. Inaddition, studies are carried out to detect and reduce the side effects ofdrugs early. Some patients may experience allergic reactions to the activeingredients of certain drugs. For example, a patient who is allergic toSulfonamide, which is included in some antibiotic drugs, may cause rash-likereactions as well as life-threatening situations due to the use ofSulfonamide-containing drugs [31]. Serious health problems can occur as aresult of allergic reactions to many substances such as these. Many people donot know that they are allergic to such substances. For this reason, somechemical properties in the Digital Twins of patients can be examined beforeadministering certain medications that may cause an allergic reaction. Inallergies that cannot be detected by blood tests such as sulfonamide, it ispossible to use medication on the real patient in a controlled manner and byexamining real-time data feeding the patient's Digital Twin by doctors todetect and prevent complications that may occur early.

随着个性化药物领域数字孪生技术的引入,旨在加速药物开发过程并减少受试动物的使用。另外,正在进行研究以及早发现并减少药物对患者的副作用。一些患者可能会对某些药物的活性成分产生过敏反应。例如,对某些抗生素药物中含有磺胺类药物过敏的患者,由于使用了含磺酰胺类药物,可能引起皮疹样反应以及危及生命的情况[31]。对许多这类物质的过敏反应可能会导致严重的健康问题。许多人不知道他们对这类物质过敏。因此,在使用某些可能引起过敏反应的药物之前,可以检查患者的数字孪生中的某些化学反应性质。在无法通过血液检测(例如磺胺类药物)检测到的过敏症中,可以通过可控的方式对真实患者使用药物,医生通过检查患者的数字孪生体所提供的实时数据来发现并预防可能早期发生的并发症。

With the developments in 5G andinfrastructure technologies, Digital Twin studies can be carried out to checkthe health of military teams that go to special operations, to be aware of thesituation when they are injured, and how to intervene. Soldiers can transmitdata to their Digital Twins in a distance, wearing clothing that is equippedwith sensors but does not restrict mobility.

随着5G和基础设施技术的发展,可以通过开展数字孪生体的应用研究来检查参加特殊行动的军事团队人员的健康状况,以了解其受伤时的状况以及如何进行医疗健康干预。士兵可以穿着装备传感器但不限制移动性的服装,远距离传输数据到他们的数字孪生体。

Digital Twin technology can also beused in organ transplantation, to resolve uncertainties about whether tissueadaptation will be achieved after transplantation or to predict probability.

数字孪生技术也可以用于器官移植,以解决患者有关器官移植后是否将实现组织适应性的不确定性或预测可能性。

While the demand for hospitals hasintensified especially during the COVID-19 pandemic process, the problem ofcapacity and resources has come to the fore in many issues such as the numberof respirators, intensive care units, and healthcare personnel in hospitals.With the creation of Digital Twins of hospitals or departments, resourcemanagement and planning can be viewed from a broad perspective in terms of moreaccurate management of resources in hospitals, so that needs-orientedactivities can be better planned. As a result of machine learning and artificialintelligence techniques used in Digital Twins, various remedial predictions canbe made to optimize process and resource use. New approaches gained in light offoresight can be tested on the hospital/department's Digital Twin. Thesituations obtained as a result of the scenarios run on the Digital Twin willbe examined and the methods found right by the authorized experts can beapplied in the hospital/department. Thus, more efficient processes can becreated for resource management activities.

尽管对医院的需求特别是在新冠病毒大流行过程中一直在增加,但是医院患者就诊容量和资源问题已在许多问题中脱颖而出,例如医院的呼吸器、重症监护病房和医护人员的数量。通过创建医院或部门的数字孪生体,可以从更广泛的角度看待医院资源管理和计划,从而可以更准确地管理医院中的资源,更好地实施以需求为导向的计划活动。由于医院数字孪生体中使用了机器学习和人工智能技术,因此可以预测或优化医院流程来对各种资源使用做出补救。根据医院卓越运营获得的各种新方法,可以在医院/部门的数字孪生体上进行测试,并且由授权专家检查各种新方法在数字孪生体上运行的状况,从而找到适合医院/部门卓越运营的正确方法。因此,可以通过数字孪生体的研究应用为医院资源管理活动创建更有效的运营过程。



4. Conclusion 结论

Digital Twin studies in the field ofhealth have mainly focused on the creation of twins of the organs in the humanbody, understanding the cell behavior in the body, and applying appropriatemedicines and treatments. Furthermore, in parallel with the development ofsensor, IoT, and machine learning technologies and the development of imagingsystems, Digital Twin technology will also accelerate. With this rise intechnology, great strides will be taken towards creating the Digital Twin ofthe entire human body that has long been desired. In addition, there will bewidespread use of the Digital Twin to solve the problems in the management ofhospital systems and medical resources, which have become more prominent withthe COVID-19 pandemic. Similarly, it is expected that Digital Twin solutionswill be used to accelerate the vaccine and medicine development processes thatoccur with COVID-19. In this study, we discussed the important Digital Twinstudies conducted in different branches of health, which could lead to newstudies, and talked about our predictions about what kind of developments thesetechnologies may develop in the future. In the future, in addition to thehealth field mentioned in this study, detailed studies can be carried out onDigital Twin technology from different perspectives such as aerospace,military, education, security systems. Besides, studies can be conducted formore specific application areas that have not been done yet in the field ofhealth.

医疗健康领域的数字孪生应用研究主要集中在人体器官孪生体的创建,了解人体细胞行为以及应用适当的药物和治疗方法上。此外,与传感器、物联网和机器学习技术的发展以及成像系统的发展同时,数字孪生技术的应用也将加速发展。随着技术的进步,将朝着创造长久以来渴望的整个人体的“数字孪生体”迈出巨大的步伐。此外,数字孪生体将广泛用于解决医院系统和医疗资源管理中的问题,这些问题在当今新冠病毒大流行过程中变得更加突出。同样,预计将使用数字孪生技术解决方案来加速抑制新冠病毒发生的疫苗和药物开发过程。在这项研究中,我们讨论了在不同医疗健康领域进行的重要数字孪生体研究,这些研究可能会导致新的研究方向,并讨论了我们对这些技术未来可能发展的预测。将来,除了本研究中提到的医疗健康领域之外,还可以从航空航天、军事、教育、安全系统等不同角度对数字孪生技术进行详细的研究。此外,可以针对医疗健康领域尚未完成的更具体的数字孪生应用领域进行研究。




 作 者 介 绍  陈志强 安世亚太战略合作部咨询顾问

二十年企业管理咨询和信息化规划,三年增材制造生态圈业务拓展。在企业质量管理、供应链管理、企业管理体系规划等方面积累了丰富经验。


理论科普数字孪生医疗器具其他软件
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首次发布时间:2021-03-13
最近编辑:3年前
数字孪生体实验室
围绕数字孪生技术的创新研发,推...
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