A Community-Driven Validation Service for Standard Medical Imaging Objects

Digital medical imaging laboratories contain many distinct types of equipment provided by different manufacturers. Interoperability is a critical issue and the DICOM protocol is a de facto standard in those environments. However, manufacturers' implementation of the standard may have non-conformities at several levels, which will hinder systems' integration. Moreover, medical staff may be responsible for data inconsistencies when entering data. Those situations severely affect the quality of healthcare services since they can disrupt system operations. The existence of software able to confirm data quality and compliance with the DICOM standard is important for programmers, IT staff and healthcare technicians. Although there are a few solutions that try to accomplish this goal, they are unable to deal with certain situations that require user input. Furthermore, these cases usually require the setup of a working environment, which makes the sharing of validation information more difficult. This article proposes and describes the development of a Web DICOM validation service for the community. This solution requires no configuration by the user, promotes validation results share-ability in the community and preserves patient data privacy since files are de-identified on the client side.Comment: Computer Standards & Interfaces, 201

Data infrastructures and digital labour : the case of teleradiology

In this thesis, I investigate the effects of digitalisation in teleradiology, the practice of outsourcing radiology diagnosis, through an analysis of the role of infrastructures that enable the transfer, storage, and processing of digital medical data. Consisting of standards, code, protocols and hardware, these infrastructures contribute to the making of complex supply chains that intervene into existing labour processes and produce interdependent relations among radiologists, patients, data engineers, and auxiliary workers. My analysis focuses on three key infrastructures that facilitate teleradiology: Picture Archiving and Communication Systems (PACS), the Digital Imaging and Communication in Medicine (DICOM) standard, and the Health Level 7 (HL7) standard. PACS is a system of four interconnected components: imaging hardware, a secure network, viewing stations for reading images, and data storage facilities. All of these components use DICOM, which specifies data formats and network protocols for the transfer of data within PACS. HL7 is a standard that defines data structures for the purposes of transfer between medical information systems. My research draws on fieldwork in teleradiology companies in Sydney, Australia, and Bangalore, India, which specialise in international outsourcing of medical imaging diagnostics and provide services for hospitals in Europe, USA, and Singapore, among others. I argue that PACS, DICOM, and HL7 establish a technopolitical context that erodes boundaries between social institutions of labour management and material infrastructures of data control. This intertwining of bureaucratic and infrastructural modes of regulation gives rise to a variety of strategies deployed by companies for maximising productivity, as well as counter-strategies of workers in leveraging mobility and qualifications to their advantage

An Internet of Things (IoT) Ecosystem for Detection and Removal of Radon Gas

The region that served as the basis for this work is characterized by the abundance of different types of granite. In some places, the predominance of certain uraniferous minerals, the existence of faults and mines may even be responsible for the existence of very high levels of natural radioactivity, especially with regard to radon. The main motivation for studying the effects of population exposure to radon is based on the fact that this gas, radioactive, odorless, colorless and tasteless, has been recognized since 1988 by the World Health Organization as the 2nd leading cause of death from lung cancer for the general population, after tobacco. Approximately 80 % of the background radiation to which populations are exposed daily comes from natural sources, which can include radioactive materials of natural origin, NORM, present in the earth’s crust, in food, in some drinks and, including certain building materials. In December 2018, a new legislation was approved in Portugal, DL no 108/2018, transposed from European Directive 59/2013 / Euratom, which establishes uniform basic safety standards for the protection of the health of people subject to exposure professional, public and medical professionals against the dangers arising from ionizing radiation. The radon isotope, 222Rn, which results from radio disintegration, 226Ra, and one of the uranium decay products, 238U, is the main radionuclide of radiological interest in terms human health. This radioactive gas is spontaneously released from some rocks and, being slightly denser than air, it tends to accumulate in ground areas of closed spaces and is responsible for the majority of the radiation dose received by the population. Some traditional solutions have been applied in order to solve the problem, however, after the detection of the radon they do not use the data collected in order to combat and prevent the gas from accumulating in the interior spaces. In Portugal it is a problem that has not been given due attention. Taking into account the possible harmful effects of radon on the population, the main motivation of this work was the development of an IoT (Internet of Things) system with the objective of detecting, mitigating and predicting the levels of radon gas inside homes. Based on this assumption, it will be possible to create a healthier environment that will reduce health risks in closed environments. To achieve this goal, an IoT system was developed, consisting of a radon sensor and an automated switch, which allows the fans installed and / or switched off to be installed in the residence, as well as predicting and making decisions in the face of a potentially dangerous situation based on the records provided by the sensors. This system also includes a web application that allows the user to consult the statistical data related to the average radon concentration. On the other hand, through the web application, it is possible to not only activate the fans manually, but also to edit the limit at which the fans are activated. This system was tested in a real context and, therefore, it is possible to compare two radon gas mitigation methods and identify which would be the most effective. Once the method to be used was determined and after stabilizing the data obtained by the sensor, the results obtained by the system were analyzed, which allowed us to conclude that the system reduced considerably the levels of radon in the house. On average, there was a 93% reduction in the concentration of radon gas. This result demonstrates that the implementation of the system was successful and allows us to conclude that it can be applied on a larger scale.A região que serviu de base para a realização deste trabalho é caracterizada pela abundância de diversos tipos de granitos. Em alguns locais, a predominância de determinados minerais uraníferos, a existência de falhas e minas podem, inclusivamente, ser responsáveis pela existência de níveis de radioatividade natural bastante elevados, especialmente no que se refere ao radão. A principal motivação para se estudar os efeitos da exposição das populações ao radão baseia-se no facto de este gás, radioativo, inodoro, incolor e insípido, ser desde 1988, reconhecido pela Organização Mundial de Saúde como a 2a causa de morte por cancro pulmonar para a população geral, depois do tabaco. Cerca de 80% da radiação de fundo a que as populações estão, diariamente, expostas tem origem em fontes naturais nas quais se podem incluir os materiais radioativos de origem natural, NORM, presentes na crosta terrestre, na comida, em algumas bebidas e, inclusivamente, em certos materiais de construção. Em dezembro de 2018, foi aprovada, em Portugal, uma nova legislação, o DL no 108/2018, transposta da Diretiva Europeia 59/2013/Euratom, que estabelece normas de segurança de base uniformes para a proteção da saúde de pessoas sujeitas a exposição profissional, da população e médica contra os perigos resultantes das radiações ionizantes. O isótopo radão, 222Rn, que resulta da desintegração do radio, 226Ra, e um dos produtos de decaimento do urânio, 238U, é o principal radionuclídeo com interesse radiológico em termos de saúde humana. Este gás radioativo liberta-se, espontaneamente de algumas rochas e, sendo ligeiramente mais denso do que o ar, tem tendência a acumular-se em zonas térreas de espaços fechados e é responsável pela maioria da dose de radiação recebida pela população. Algumas soluções tradicionais têm sido aplicadas de modo a resolver o problema, no entanto, depois da deteção do radão estas não usam os dados recolhidos de forma a combater e a prevenir que o gás se acumule nos espaços interiores. Em Portugal é um problema que não tem a devida atenção. Tendo em conta os possíveis efeitos nocivos do radão na população, a principal motivação deste trabalho consistiu no desenvolvimento de um sistema IoT (Internet das Coisas) com o objetivo de detetar, mitigar e prever os níveis do gás radão no interior das habitações. Partindo deste pressuposto, será possível criar um ambiente mais saudável que permitirá reduzir os riscos para a saúde em ambientes fechados. Para se concretizar este objetivo foi desenvolvido um sistema IoT que consiste em um sensor de radão e um interruptor automatizado, que permite ligar e/ou desligar os ventiladores instalados na residência, bem como prever e tomar decisões perante uma situação potencialmente perigosa com base nos registos fornecidos pelos sensores. Este sistema integra também uma aplicação web que permite ao utilizador consultar os dados estatísticos relativos à concentração média de radão. Por outro lado, através da aplicação web, é possível não só ativar os ventiladores manualmente, como também editar o limite em que os ventiladores são accionados. Este sistema foi testado num contexto real e, por isso, possível comparar dois métodos de mitigação do gás radão e identificar qual seria o mais eficaz. Uma vez determinado o método a ser utilizado e após a estabilização dos dados obtidos pelo sensor, analisaram-se os resultados obtidos pelo sistema que permitiram concluir que o sistema reduziu consideravelmente os níveis de radão na habitação. Foi verificada, em média, uma redução de cerca de 93% na concentração de gás radão. Este resultado demonstra que a implementação do sistema foi um sucesso e permite concluir que poderá ser aplicado numa escala maior

Röntgenhoitajan työnkuva teleradiologiassa

Teleradiologia on yksi eniten käytetyimmistä ja pisimpään kliinisessä käytössä olleista telelääketieteen osaalueista. Artikkelissa tarkastellaan miten röntgenhoitajan rooli teleradiologiassa näyttäytyy tutkimuksissa. Aiheesta tehtiin systemaattinen kirjallisuuskatsaus, jossa aineistoa haettiin suomen‐ ja englanninkielisistä terveysalan sähköisistä tieteellisistä tietokannoista sekä ammattikorkeakoulujen opinnäytetietokannasta. Lisäksi selattiin Journal of Digital Imaging –lehden vuosikerrat. Haku rajattiin tieteellisiin julkaisuihin. Sille ei asetettu aikarajausta, koska tutkittava ilmiö on suhteellisen uusi. Hakujen sisäänottokriteereinä käytettiin sitä, että valituissa tutkimuksissa röntgenhoitaja kuvattiin aktiivisessa roolissa toimijana tai hyödynsaajana. Haettiin tutkimuksia, joissa kuvattiin röntgenhoitajan roolia diagnostisessa tai terapeuttisessa teleradiologiassa. Hakutulokset analysoitiin käyttäen induktiivista sisällönanalyysiä, jonka avulla analysoitiin tutkimusten tulososiot.Keskeisimmiksi röntgenhoitajan tehtäväalueiksi teleradiologiassa näyttäytyivät tutkimusten perusteella potilastietojärjestelmän tietojen käsittely ja niiden yhdistäminen kuvantamis‐ tai hoitotietoihin ja röntgenkuviin eli työskentely RIS–PACS –rajapinnalla (RIS, Radiological Information System; PACS, Picture archiving and communication system), kuvantaminen ja/tai sädehoidon toteutus, kuvien käsittely ja tallentaminen PACSiin sekä turvallisuudesta, laadunvarmistuksesta ja säteilyaltistuksen optimoinnista huolehtiminen. Muita tärkeitä röntgenhoitajan tehtäviä teleradiologiassa ovat kouluttaminen ja itsensä sekä työnsä kehittäminen, moniammatillinen yhteistyö, asiakaslähtöinen potilasohjaus ja hoitotoiminta sekä tietosuojasta ja –turvasta huolehtiminen. Lisäksi talouden suunnittelu ja hallinta kuuluvat erityisesti PACS‐asiantuntijan työhön. Nämä tehtäväalueet tulisi huomioida suunniteltaessa röntgenhoitajien koulutusta niin ammattiin valmistavassa nuoriso‐ ja aikuiskoulutuksessa, täydennys ja jatkokoulutuksessa sekä työpaikkakoulutuksessa. Tehtäväalueiden vaatima osaaminen tulisi lisäksi tunnistaa suunniteltaessa kuvantamisyksiköiden henkilöstön tehtäväkuvia sekä työn vaativuuden arvioinnissa ja palkitsemisjärjestelmissä

Pre and post computerized radiography film reject analysis in a private hospital in Kenya

The production of good quality radiographs is a complex process, given the high level of image quality required (Sniureviciute & Adliene, 2005: 260). Exposure of patients to x-rays, a factor in the production of quality radiographs also entails a risk of radiation injury. In 2006, computerized radiography (CR) was introduced at The Nairobi Hospital to try and reduce the film reject rate, decrease repeats, reduce financial costs of consumables like x-ray films and processing chemicals. However, to date, no formal film reject analysis has been conducted at The Nairobi Hospital. Four years after the incorporation of CR, there is apparently, still a significant number of film rejects, implying operational costs may still be high. The cause of film rejects and overall reject cost is not known. This has led to the research question: “Has the film reject rate in the A & E x-ray unit at The Nairobi Hospital reduced following incorporation of CR?” A quantitative, retrospective, descriptive study involving a reject film analysis of rejected radiographs in the Accident and Emergency (A&E) x-ray unit in the Nairobi Hospital, Kenya was conducted. The researcher collected data for a period of 6 months between 2/12/07 and 28/05/08 using a purpose-designed data collection form. All rejected x-ray films during the study period were included. Capture and analysis of the collected data was completed by the researcher using SPSS 10 and EPINFO computer packages. Permission to conduct the study was obtained from The Nairobi Hospital Education Committee and due consideration to patient and radiographer confidentiality was maintained throughout the study. A total of 851(2.5 percent) x-ray films were collected during the study period. Four hundred and fourteen (2.6 percent) radiographs and 437 (2.5 percent) radiographs were rejected prior to and after the incorporation of CR respectively. Chest radiographs were the most frequently rejected accounting for 277(66.9 percent) and 123 (28.1 percent) prior to and after the incorporation of CR respectively. The most frequently rejected film size was 35x35cm prior to the incorporation of CR (61.6 percent) and 26x35cm film size after the incorporation of CR (91.3 percent). The most frequent cause of film rejects was radiographer causes both prior to and after the incorporation of CR accounting for 496 (58.3 percent). The film reject rate did not significantly reduce after the incorporation of CR, suggesting that there are other factors which contribute to reject rate, other than CR. The study also shows that higher film consumption does not necessarily lead to high reject rates. The percentage value on annual rejects did not change after the incorporation of CR and a demonstrated increase in the annual cost of purchasing x-ray films was attributed to an increase in annual consumption after the incorporation of CR, and also to the higher cost of digital x-ray films. Despite some identified limitations to this study, some recommendations, which included conduction of regular reject analyses and regular continuing professional development with respect to radiographic technique amongst others, were suggested

Emergency Department Quality Dashboard; a Systematic Review of Performance Indicators, Functionalities, and Challenges

Introduction: Effective information management in the emergency department (ED) can improve the control and management of ED processes. Dashboards, known as data management tools, efficiently provide information and contribute greatly to control and management of ED. This study aimed to identify performance indicators and quality dashboard functionalities, and analyze the challenges associated with dashboard implementation in the ED. Methods: This systematic review began with a search in four databases (Web of Science, PubMed, Embase, and Scopus) from 2000 to May 30, 2020, when the final search for papers was conducted. The data were collected using a data extraction form and the contents of the extracted papers were analyzed through ED performance indicators, dashboard functionalities, and implementation challenges. Results: Performance indicators reported in the reviewed papers were classified as the quality of care, patient flow, timeliness, costs, and resources. The main dashboard functionalities noted in the papers included reporting, customization, alert creation, resource management, and real-time information display. The dashboard implementation challenges included data sources, data quality, integration with other systems, adaptability of dashboard functionalities to user needs, and selection of appropriate performance indicators. Conclusions: Quality dashboards facilitate processes, communication, and situation awareness in the ED; hence, they can improve care provision in this department. To enhance the effectiveness and efficiency of ED dashboards, officials should set performance indicators and consider the conformity of dashboard functionalities with user needs. They should also integrate dashboards with other relevant systems at the departmental and hospital levels

Current Challenges in the Application of Algorithms in Multi-institutional Clinical Settings

The Coronavirus disease pandemic has highlighted the importance of artificial intelligence in multi-institutional clinical settings. Particularly in situations where the healthcare system is overloaded, and a lot of data is generated, artificial intelligence has great potential to provide automated solutions and to unlock the untapped potential of acquired data. This includes the areas of care, logistics, and diagnosis. For example, automated decision support applications could tremendously help physicians in their daily clinical routine. Especially in radiology and oncology, the exponential growth of imaging data, triggered by a rising number of patients, leads to a permanent overload of the healthcare system, making the use of artificial intelligence inevitable. However, the efficient and advantageous application of artificial intelligence in multi-institutional clinical settings faces several challenges, such as accountability and regulation hurdles, implementation challenges, and fairness considerations. This work focuses on the implementation challenges, which include the following questions: How to ensure well-curated and standardized data, how do algorithms from other domains perform on multi-institutional medical datasets, and how to train more robust and generalizable models? Also, questions of how to interpret results and whether there exist correlations between the performance of the models and the characteristics of the underlying data are part of the work. Therefore, besides presenting a technical solution for manual data annotation and tagging for medical images, a real-world federated learning implementation for image segmentation is introduced. Experiments on a multi-institutional prostate magnetic resonance imaging dataset showcase that models trained by federated learning can achieve similar performance to training on pooled data. Furthermore, Natural Language Processing algorithms with the tasks of semantic textual similarity, text classification, and text summarization are applied to multi-institutional, structured and free-text, oncology reports. The results show that performance gains are achieved by customizing state-of-the-art algorithms to the peculiarities of the medical datasets, such as the occurrence of medications, numbers, or dates. In addition, performance influences are observed depending on the characteristics of the data, such as lexical complexity. The generated results, human baselines, and retrospective human evaluations demonstrate that artificial intelligence algorithms have great potential for use in clinical settings. However, due to the difficulty of processing domain-specific data, there still exists a performance gap between the algorithms and the medical experts. In the future, it is therefore essential to improve the interoperability and standardization of data, as well as to continue working on algorithms to perform well on medical, possibly, domain-shifted data from multiple clinical centers

An Evaluation of a Networked Radiation Detection System

First responders assess a Nuclear/Radiological (NUCRAD) event in a timely and accurate manner by creating a site characterization that reflects the location of various levels of contamination based on their instruments’ readings. The survey team experiences difficulty in accurately recording this critical data due to the challenge of operating multiple devices and communicating the devices’ readings to other survey members. First responders produce a representation of the contamination or activity on a map that contain rings outlining the levels of activity and/or single locations of a single activity. Recently, several agencies began creating software programs that record a first responder’s instrument readings, time, and the global positioning system (GPS) location plotting the information in real-time. The Environmental Protection Agency (EPA) Region 5 developed the Rapid Assessment Tool (RAT). This research evaluates the effectiveness of RAT by comparing the timeliness and accuracy of the site characterization created by multiple survey teams (one team not using RAT and another team using RAT). All of the Bioenvironmental Engineer (BEE) Survey Teams using RAT decreased their survey times for all scenarios. The Weapons of Mass Destruction – Civil Support Team (WMD-CST) survey teams using RAT decreased their survey times during the lane, bounce and bypass, star, and cloverleaf scenarios. However, survey times increased for the zigzag and radial scenarios

Development of a Web-based Instructional Module for Interpretation of Craniofacial Cone Beam CT Pathology

The introduction of Cone Beam Computed Tomography (CBCT) in dental practice constitutes a paradigm shift in the way clinicians look at and interpret diagnostic information. With the rapid pace of CBCT development, and with new manufacturers and models appearing in the market each year, it is clear that this technology is assuming an increasingly important role in dental diagnosis. Because of this it will be important to provide a solid foundation on which dental students, general practitioners and specialists alike can build diagnostic skills utilizing this imaging modality. CBCT provides volumetric scans of the patient head that can be visualized in a variety of ways both in 2D and 3D. The newly developed MARCILAN website offers a highly interactive, multimedia rich, web-based, didactic module for interpretation and correlation of 3D anatomical structures as seen on CBCT. However, the current offering does not include a module to aid clinicians in the diagnosis of pathological conditions. The purpose of this study is to develop a web-based instructional module to interpret pathology as presented on cone beam CT images

Hukkakuva-analyysi HUS-Röntgenissä

Opinnäytetyön tarkoituksena oli selvittää HUS-Röntgenin röntgentoimipisteiden käytäntöjä natiivikuvantamisessa tehtävään hukkakuva-analyysiin. HUS-Röntgenillä ei ollut yhtenäistä ohjeistusta hukkakuva-analyysin suorittamiseksi, ja haluttiin kartoittaa yksiköiden hyviksi havaitsemia toimintatapoja sekä tavoitella koko organisaation laajuista käytäntöä. Opinnäytetyön teoriataustaa kerättiin röntgenkuvantamisen laadunvarmistuksesta ja tarkemmin hukkakuva-analyysista, niin kansainvälisistä kuin kotimaisista lähteistä. Tietoja hukkakuva-analyysin toteutustavoista pyydettiin HUS-Röntgenin toimipisteiltä kyselyn avulla. Kyselyn vastauksista eriteltiin hukkakuva-analyysin tekotapoihin sekä sen tuloksien hyödynnettävyyteen liittyviä asioita. Toimipisteiltä saatuja vastauksia verrattiin kansainvälisiin julkaisuihin aineistoa ja teoriaa yhdistävän abduktiivisen päättelytavan avulla. 20 eri toimipisteestä saadusta vastauksesta kävi ilmi hukkakuva-analyysin erilaiset menetelmät HUS-Röntgenissä. Yksiköistä saatiin tiedot viimeisimmästä sen suorittamasta hukkakuva-analyysista sekä siitä, miten hukkakuva-analyysin tuloksia on hyödynnetty yksikössä. Suurimmassa osassa yksiköitä tuloksia käytiin läpi henkilökunnan kanssa ja jos systemaattisia virheitä havaittiin, asiaan puututtiin. HUS-Röntgenin laajan röntgenlaitekannan ja niihin liittyvien ohjelmistojen yhteensovittaminen asettaa haasteita yhtenäisen ohjeistuksen luomiselle hukkakuva-analyysin tekoon. Jotta röntgenyksiköiden hukkakuva-analyysin tuloksia voidaan verrata, olisi käytäntöjen kuitenkin hyvä olla samankaltaiset koko organisaatiossa. Kuvien hylkäyssyiden tulisi olla yhtenäiset. Hukkakuvien sekä hukkakuva-analyysin tulosten läpikäyminen henkilökunnan kanssa olisi suotavaa. Käytäntöjä voidaan myös yhtenäistää esimerkiksi analyysin hyödynnettävyyden osalta.The objective of this study was to find out methods and customs for carrying out reject analysis in computed radiography in the organization of HUS-Röntgen, the leading medical imaging provider in Finland, which produces medical imaging services for the Hospital District of Helsinki and Uusimaa. Furthermore the study aimed to create a guideline for reject analysis for the entire organization. Information about quality assurance and reject analysis in computed radiography was collected from studies and journals in the field of radiography. Data from the departments of HUS-Röntgen were gathered by sending a small questionnaire on the latest reject analysis performed in the unit. The responses received from the units were analyzed and compared with the data from previous studies. In total 18 responses were received from the departments of HUS-Röntgen. The data included information on the latest reject analysis and the benefits of the results of the reject analysis. Most of the departments went through the results with personnel and if systematic errors occurred they were processed. The different devices and software of computed radiography in the organization makes it challenging to make a general guideline or instructions for carrying out reject analysis. It would be important to create common instructions among HUS-Röntgen, to enable the comparison of the results of reject analysis between different units. Finally, it would be recommended to study some of the rejected images and to analyze the results of the reject analysis with the staff in purpose of training. Practices can be integrated for instance in the utilization of the results of the reject analysis