@article {1229, title = {Data model harmonization for the All Of Us Research Program: Transforming i2b2 data into the OMOP common data model.}, journal = {PLoS One}, volume = {14}, year = {2019}, month = {2019}, pages = {e0212463}, abstract = {

BACKGROUND: The All Of Us Research Program (AOU) is building a nationwide cohort of one million patients{\textquoteright} EHR and genomic data. Data interoperability is paramount to the program{\textquoteright}s success. AOU is standardizing its EHR data around the Observational Medical Outcomes Partnership (OMOP) data model. OMOP is one of several standard data models presently used in national-scale initiatives. Each model is unique enough to make interoperability difficult. The i2b2 data warehousing and analytics platform is used at over 200 sites worldwide, which uses a flexible ontology-driven approach for data storage. We previously demonstrated this ontology system can drive data reconfiguration, to transform data into new formats without site-specific programming. We previously implemented this on our 12-site Accessible Research Commons for Health (ARCH) network to transform i2b2 into the Patient Centered Outcomes Research Network model.

METHODS AND RESULTS: Here, we leverage our investment in i2b2 high-performance transformations to support the AOU OMOP data pipeline. Because the ARCH ontology has gained widespread national interest (through the Accrual to Clinical Trials network, other PCORnet networks, and the Nebraska Lexicon), we leveraged sites{\textquoteright} existing investments into this standard ontology. We developed an i2b2-to-OMOP transformation, driven by the ARCH-OMOP ontology and the OMOP concept mapping dictionary. We demonstrated and validated our approach in the AOU New England HPO (NEHPO). First, we transformed into OMOP a fake patient dataset in i2b2 and verified through AOU tools that the data was structurally compliant with OMOP. We then transformed a subset of data in the Partners Healthcare data warehouse into OMOP. We developed a checklist of assessments to ensure the transformed data had self-integrity (e.g., the distributions have an expected shape and required fields are populated), using OMOP{\textquoteright}s visual Achilles data quality tool. This i2b2-to-OMOP transformation is being used to send NEHPO production data to AOU. It is open-source and ready for use by other research projects.

}, issn = {1932-6203}, doi = {10.1371/journal.pone.0212463}, author = {Klann, Jeffrey G and Joss, Matthew A H and Embree, Kevin and Murphy, Shawn N} } @article {1223, title = {Health4Afrika - Implementing HL7 FHIR Based Interoperability.}, journal = {Stud Health Technol Inform}, volume = {264}, year = {2019}, month = {2019 Aug 21}, pages = {20-24}, abstract = {

Supported by the European Commission under Horizon 2020, mHealth4Afrika is co-designing and validating a modular, multilingual, state-of-the-art health information system addressing primary healthcare requirements in resource constrained environments. mHealth4Afrika has co-designed a comprehensive range of functionality and medical programs in partnership with Ministries of Health, district health officers, clinic managers and primary healthcare workers from urban, rural and deep rural health facilities in Ethiopia, Kenya, Malawi and South Africa. This paper provides insights into how mHealth4Afrika is leveraging HL7 FHIR to support standards-based data exchange and interoperability between Electronic Medical Records and DHIS2. This work is currently being validated in the field.

}, issn = {1879-8365}, doi = {10.3233/SHTI190175}, author = {Baskaya, Mert and Yuksel, Mustafa and Erturkmen, Gokce Banu Laleci and Cunningham, Miriam and Cunningham, Paul} } @article {1302, title = {Open source capillary electrophoresis.}, journal = {Electrophoresis}, volume = {40}, year = {2019}, month = {2019 01}, pages = {65-78}, abstract = {

Open source paradigm is becoming widely accepted in scientific communities and open source hardware is finding its steady place in chemistry research. In this review article, we provide the reader with the most up-to-date information on open source hardware and software resources enabling the construction and utilization of an "open source capillary electrophoresis instrument". While CE is still underused as a separation technique, it offers unique flexibility, low-cost, and high efficiency and is particularly suitable for open source instrumental development. We overview the major parts of CE instruments, such as high voltage power supplies, detectors, data acquisition systems, and CE software resources with emphasis on availability of the open source information on the web and in the scientific literature. This review is the first of its kind, revealing accessible blueprints of most parts from which a fully functional open source CE system can be built. By collecting the extensive information on open source capillary electrophoresis in this review article, the authors aim at facilitating the dissemination of knowledge on CE within and outside the scientific community, fosters innovation and inspire other researchers to improve the shared CE blueprints.

}, keywords = {Electronics, Electrophoresis, Capillary, Equipment Design, Software}, issn = {1522-2683}, doi = {10.1002/elps.201800304}, author = {Kub{\'a}{\v n}, Petr and Foret, Franti{\v s}ek and Erny, Guillaume} } @article {1217, title = {STEM: An Open Source Tool for Disease Modeling.}, journal = {Health Secur}, volume = {17}, year = {2019}, month = {2019 Jul/Aug}, pages = {291-306}, abstract = {

The Spatiotemporal Epidemiologic Modeler (STEM) is an open source software project supported by the Eclipse Foundation and used by a global community of researchers and public health officials working to track and, when possible, control outbreaks of infectious disease in human and animal populations. STEM is not a model or a tool designed for a specific disease; it is a flexible, modular framework supporting exchange and integration of community models, reusable plug-in components, and denominator data, available to researchers worldwide at www.eclipse.org/stem. A review of multiple projects illustrates its capabilities. STEM has been used to study variations in transmission of seasonal influenza in Israel by strains; evaluate social distancing measures taken to curb the H1N1 epidemic in Mexico City; study measles outbreaks in part of London and inform local policy on immunization; and gain insights into H7N9 avian influenza transmission in China. A multistrain dengue fever model explored the roles of the mosquito vector, cross-strain immunity, and antibody response in the frequency of dengue outbreaks. STEM has also been used to study the impact of variations in climate on malaria incidence. During the Ebola epidemic, a weekly conference call supported the global modeling community; subsequent work modeled the impact of behavioral change and tested disease reintroduction via animal reservoirs. Work in Germany tracked salmonella in pork from farm to fork; and a recent doctoral dissertation used the air travel feature to compare the potential threats posed by weaponizing infectious diseases. Current projects include work in Great Britain to evaluate control strategies for parasitic disease in sheep, and in Germany and Hungary, to validate the model and inform policy decisions for African swine fever. STEM Version 4.0.0, released in early 2019, includes tools used in these projects and updates technical aspects of the framework to ease its use and re-use.

}, issn = {2326-5108}, doi = {10.1089/hs.2019.0018}, author = {Douglas, Judith V and Bianco, Simone and Edlund, Stefan and Engelhardt, Tekla and Filter, Matthias and G{\"u}nther, Taras and Hu, Kun Maggie and Nixon, Emily J and Sevilla, Nereyda L and Swaid, Ahmad and Kaufman, James H} } @article {1272, title = {Data for decision making: using a dashboard to strengthen routine immunisation in Nigeria.}, journal = {BMJ Glob Health}, volume = {3}, year = {2018}, month = {2018}, pages = {e000807}, abstract = {

Availability of reliable data has for a long time been a challenge for health programmes in Nigeria. Routine immunisation (RI) data have always been characterised by conflicting coverage figures for the same vaccine across different routine data reporting platforms. Following the adoption of District Health Information System version 2 (DHIS2) as a national electronic data management platform, the DHIS2 RI Dashboard Project was initiated to address the absence of some RI-specific indicators on DHIS2. The project was also intended to improve visibility and monitoring of RI indicators as well as strengthen the broader national health management information system by promoting the use of routine data for decision making at all governance levels. This paper documents the process, challenges and lessons learnt in implementing the project in Nigeria. A multistakeholder technical working group developed an implementation framework with clear preimplementation; implementation and postimplementation activities. Beginning with a pilot in Kano state in 2014, the project has been scaled up countrywide. Nearly 34 000 health workers at all administrative levels were trained on RI data tools and DHIS2 use. The project contributed to the improvement in completeness of reports on DHIS2 from 53 \% in first quarter 2014 to 81 \% in second quarter 2017. The project faced challenges relating to primary healthcare governance structures at the subnational level, infrastructure and human resource capacity. Our experience highlights the need for early and sustained advocacy to stakeholders in a decentralised health system to promote ownership and sustainability of a centrally coordinated systems strengthening initiative.

}, issn = {2059-7908}, doi = {10.1136/bmjgh-2018-000807}, author = {Etamesor, Sulaiman and Ottih, Chibuzo and Salihu, Ismail Ndalami and Okpani, Arnold Ikedichi} } @article {1294, title = {How the introduction of a human resources information system helped the Democratic Republic of Congo to mobilise domestic resources for an improved health workforce.}, journal = {Health Policy Plan}, volume = {32}, year = {2017}, month = {2017 Nov 01}, pages = {iii25-iii31}, abstract = {

The Democratic Republic of Congo has flagged health workforce management and compensation as issues requiring attention, including the problem of ghost workers (individuals on payroll who do not exist and/or show up at work). Recognising the need for reliable health workforce information, the government has worked to implement iHRIS, an open source human resources information system that facilitates health workforce management. In Kasa{\"\i} Central and Kasa{\"\i} Provinces, health workers brought relevant documentation to data collection points, where trained teams interviewed them and entered contact information, identification, photo, current job, and employment and education history into iHRIS on laptops. After uploading the data, the Ministry of Public Health used the database of over 11 500 verified health worker records to analyse health worker characteristics, density, compensation, and payroll. Both provinces had less than one physician per 10 000 population and a higher urban versus rural health worker density. Most iHRIS-registered health workers (57\% in Kasa{\"\i} Central and 73\% in Kasa{\"\i}) reported receiving no regular government pay of any kind (salaries or risk allowances). Payroll analysis showed that 27\% of the health workers listed as salary recipients in the electronic payroll system were ghost workers, as were 42\% of risk allowance recipients. As a result, the Ministries of Public Health, Public Service, and Finance reallocated funds away from ghost workers to cover salaries (n = 781) and risk allowances (n = 2613) for thousands of health workers who were previously under- or uncompensated due to lack of funds. The reallocation prioritised previously under- or uncompensated mid-level health workers, with 49\% of those receiving salaries and 68\% of those receiving risk allowances representing cadres such as nurses, laboratory technicians, and midwifery cadres. Assembling accurate health worker records can help governments understand health workforce characteristics and use data to direct scarce domestic resources to where they are most needed.

}, keywords = {Democratic Republic of the Congo, Health Personnel, Health Workforce, Humans, Management Information Systems, Personnel Management, Remuneration}, issn = {1460-2237}, doi = {10.1093/heapol/czx113}, author = {Likofata Esanga, Jean-Robert and Viadro, Claire and McManus, Leah and Wesson, Jennifer and Matoko, Nicaise and Ngumbu, Epiphane and Gilroy, Kate E and Trudeau, Daren} } @article {1285, title = {Long-Term Outcomes of Aflibercept Treatment for Neovascular Age-Related Macular Degeneration in a Clinical Setting.}, journal = {Am J Ophthalmol}, volume = {174}, year = {2017}, month = {2017 Feb}, pages = {160-168}, abstract = {

PURPOSE: To report 2-year treatment outcomes with intravitreal aflibercept for neovascular age-related macular degeneration (nAMD) in routine clinical practice.

DESIGN: Retrospective, nonrandomized, interventional case series.

METHODS: Retrospective analysis of electronic medical record (EMR) notes (OpenEyes) and paper case notes and review of spectral-domain optical coherence tomography (SDOCT) imaging of patients with consecutively treated eyes with previously untreated nAMD. Patients were commenced on aflibercept injections in 1 or both eyes from October 1, 2013 to December 31, 2013. Data including age, sex, visual acuity (VA) measured on Early Treatment Diabetic Retinopathy Study charts, injection episodes, and complications were recorded. Additionally, SDOCT data, including presence or absence of macular fluid and automated central subfield macular thickness (CSMT) at year 1 and 2, were recorded.

RESULTS: Of the 109 eyes of 102 patients treated, data from 94 eyes of 88 patients were available at 2-year follow-up (86\% of patients). In the analysis of 2-year outcomes, there were 58 women (65.9\%); the mean ({\textpm} standard deviation) age was 77.5 {\textpm} 8 years. Over the 2 years, these eyes received a median of 12 (mean, 11.4 {\textpm} 4) injections at a median of 100 (mean, 99.3 {\textpm} 5.3) weeks of follow-up. The mean VA changed from 55.9 {\textpm} 15 letters at baseline to 61.3 {\textpm} 16.9 letters (VA gain 5.4 letters) at 1 year and to 61 {\textpm} 17.1 letters (VA gain 5.1 {\textpm} 14.9 letters) at 2 years. The reduction in CSMT was 79~μm with absence of macular fluid in 72.7\% of the 88 eyes with SDOCT data available at 2-year follow-up.

CONCLUSIONS: The VA and SDOCT results compare favorably with outcomes seen in randomized controlled trials. The results suggest that good long-term outcomes can be achieved using aflibercept for nAMD in clinical settings.

}, keywords = {Aged, Dose-Response Relationship, Drug, Female, Fluorescein Angiography, Follow-Up Studies, Fundus Oculi, Humans, Intravitreal Injections, Macula Lutea, Macular Degeneration, Male, Receptors, Vascular Endothelial Growth Factor, Recombinant Fusion Proteins, Retinal Neovascularization, Retrospective Studies, Time Factors, Tomography, Optical Coherence, Treatment Outcome, Visual Acuity}, issn = {1879-1891}, doi = {10.1016/j.ajo.2016.09.038}, author = {Eleftheriadou, Maria and Vazquez-Alfageme, Clara and Citu, Cristina Maria and Crosby-Nwaobi, Roxanne and Sivaprasad, Sobha and Hykin, Philip and Hamilton, Robin D and Patel, Praveen J} } @article {1123, title = {3D for the people: multi-camera motion capture in the field with consumer-grade cameras and open source software.}, journal = {Biol Open}, year = {2016}, month = {2016 Jul 21}, abstract = {

Ecological, behavioral, and biomechanical studies often need to quantify animal movement and behavior in three dimensions. In laboratory studies, a major tool to accomplish these measurements is the use of multiple, calibrated high-speed cameras. Until very recently, the complexity, weight, and cost of such cameras have made their deployment in field situations risky; furthermore, such cameras are not affordable to many researchers. Here we show how inexpensive, consumer-grade cameras can accomplish these measurements both within the laboratory and in the field. Combined with our methods and open source software, the availability of inexpensive, portable and rugged cameras will open up new areas of biological study by providing precise 3D tracking and quantification of animal and human movement to researchers in a wide variety of field and laboratory contexts.

}, issn = {2046-6390}, doi = {10.1242/bio.018713}, author = {Jackson, Brandon E and Evangelista, Dennis J and Ray, Dylan D and Hedrick, Tyson L} } @article {1135, title = {Improving documentation of clinical care within a clinical information network: an essential initial step in efforts to understand and improve care in Kenyan hospitals.}, journal = {BMJ Glob Health}, volume = {1}, year = {2016}, month = {2016 May 24}, pages = {e000028}, abstract = {

In many low income countries health information systems are poorly equipped to provide detailed information on hospital care and outcomes. Information is thus rarely used to support practice improvement. We describe efforts to tackle this challenge and to foster learning concerning collection and use of information. This could improve hospital services in Kenya. We are developing a Clinical Information Network, a collaboration spanning 14 hospitals, policy makers and researchers with the goal of improving information available on the quality of inpatient paediatric care across common childhood illnesses in Kenya. Standardised data from hospitals{\textquoteright} paediatric wards are collected using non-commercial and open source tools. We have implemented procedures for promoting data quality which are performed prior to a process of semi-automated analysis and routine report generation for hospitals in the network. In the first phase of the Clinical Information Network, we collected data on over 65 000 admission episodes. Despite clinicians{\textquoteright} initial unfamiliarity with routine performance reporting, we found that, as an initial focus, both engaging with each hospital and providing them information helped improve the quality of data and therefore reports. The process has involved mutual learning and building of trust in the data and should provide the basis for collaborative efforts to improve care, to understand patient outcome, and to evaluate interventions through shared learning. We have found that hospitals are willing to support the development of a clinically focused but geographically dispersed Clinical Information Network in a low-income setting. Such networks show considerable promise as platforms for collaborative efforts to improve care, to provide better information for decision making, and to enable locally relevant research.

}, issn = {2059-7908}, doi = {10.1136/bmjgh-2016-000028}, author = {Tuti, Timothy and Bitok, Michael and Malla, Lucas and Paton, Chris and Muinga, Naomi and Gathara, David and Gachau, Susan and Mbevi, George and Nyachiro, Wycliffe and Ogero, Morris and Julius, Thomas and Irimu, Grace and English, Mike} } @article {1131, title = {Increasing the impact of medical image computing using community-based open-access hackathons: The NA-MIC and 3D Slicer experience.}, journal = {Med Image Anal}, year = {2016}, month = {2016 Jul 7}, abstract = {

The National Alliance for Medical Image Computing (NA-MIC) was launched in 2004 with the goal of investigating and developing an open source software infrastructure for the extraction of information and knowledge from medical images using computational methods. Several leading research and engineering groups participated in this effort that was funded by the US National Institutes of Health through a variety of infrastructure grants. This effort transformed 3D Slicer from an internal, Boston-based, academic research software application into a professionally maintained, robust, open source platform with an international leadership and developer and user communities. Critical improvements to the widely used underlying open source libraries and tools-VTK, ITK, CMake, CDash, DCMTK-were an additional consequence of this effort. This project has contributed to close to a thousand peer-reviewed publications and a growing portfolio of US and international funded efforts expanding the use of these tools in new medical computing applications every year. In this editorial, we discuss what we believe are gaps in the way medical image computing is pursued today; how a well-executed research platform can enable discovery, innovation and reproducible science ("Open Science"); and how our quest to build such a software platform has evolved into a productive and rewarding social engineering exercise in building an open-access community with a shared vision.

}, issn = {1361-8423}, doi = {10.1016/j.media.2016.06.035}, author = {Kapur, Tina and Pieper, Steve and Fedorov, Andriy and Fillion-Robin, J-C and Halle, Michael and O{\textquoteright}Donnell, Lauren and Lasso, Andras and Ungi, Tamas and Pinter, Csaba and Finet, Julien and Pujol, Sonia and Jagadeesan, Jayender and Tokuda, Junichi and Norton, Isaiah and Estepar, Raul San Jose and Gering, David and Aerts, Hugo J W L and Jakab, Marianna and Hata, Nobuhiko and Ibanez, Luiz and Blezek, Daniel and Miller, Jim and Aylward, Stephen and Grimson, W Eric L and Fichtinger, Gabor and Wells, William M and Lorensen, William E and Schroeder, Will and Kikinis, Ron} } @article {1121, title = {Open Source Drug Discovery with the Malaria Box Compound Collection for Neglected Diseases and Beyond.}, journal = {PLoS Pathog}, volume = {12}, year = {2016}, month = {2016 Jul}, pages = {e1005763}, abstract = {

A major cause of the paucity of new starting points for drug discovery is the lack of interaction between academia and industry. Much of the global resource in biology is present in universities, whereas the focus of medicinal chemistry is still largely within industry. Open source drug discovery, with sharing of information, is clearly a first step towards overcoming this gap. But the interface could especially be bridged through a scale-up of open sharing of physical compounds, which would accelerate the finding of new starting points for drug discovery. The Medicines for Malaria Venture Malaria Box is a collection of over 400 compounds representing families of structures identified in phenotypic screens of pharmaceutical and academic libraries against the Plasmodium falciparum malaria parasite. The set has now been distributed to almost 200 research groups globally in the last two years, with the only stipulation that information from the screens is deposited in the public domain. This paper reports for the first time on 236 screens that have been carried out against the Malaria Box and compares these results with 55 assays that were previously published, in a format that allows a meta-analysis of the combined dataset. The combined biochemical and cellular assays presented here suggest mechanisms of action for 135 (34\%) of the compounds active in killing multiple life-cycle stages of the malaria parasite, including asexual blood, liver, gametocyte, gametes and insect ookinete stages. In addition, many compounds demonstrated activity against other pathogens, showing hits in assays with 16 protozoa, 7 helminths, 9 bacterial and mycobacterial species, the dengue fever mosquito vector, and the NCI60 human cancer cell line panel of 60 human tumor cell lines. Toxicological, pharmacokinetic and metabolic properties were collected on all the compounds, assisting in the selection of the most promising candidates for murine proof-of-concept experiments and medicinal chemistry programs. The data for all of these assays are presented and analyzed to show how outstanding leads for many indications can be selected. These results reveal the immense potential for translating the dispersed expertise in biological assays involving human pathogens into drug discovery starting points, by providing open access to new families of molecules, and emphasize how a small additional investment made to help acquire and distribute compounds, and sharing the data, can catalyze drug discovery for dozens of different indications. Another lesson is that when multiple screens from different groups are run on the same library, results can be integrated quickly to select the most valuable starting points for subsequent medicinal chemistry efforts.

}, issn = {1553-7374}, doi = {10.1371/journal.ppat.1005763}, author = {Van Voorhis, Wesley C and Adams, John H and Adelfio, Roberto and Ahyong, Vida and Akabas, Myles H and Alano, Pietro and Alday, Aintzane and Alem{\'a}n Resto, Yesmalie and Alsibaee, Aishah and Alzualde, Ainhoa and Andrews, Katherine T and Avery, Simon V and Avery, Vicky M and Ayong, Lawrence and Baker, Mark and Baker, Stephen and Ben Mamoun, Choukri and Bhatia, Sangeeta and Bickle, Quentin and Bounaadja, Lotfi and Bowling, Tana and Bosch, J{\"u}rgen and Boucher, Lauren E and Boyom, Fabrice F and Brea, Jose and Brennan, Marian and Burton, Audrey and Caffrey, Conor R and Camarda, Grazia and Carrasquilla, Manuela and Carter, Dee and Belen Cassera, Maria and Chih-Chien Cheng, Ken and Chindaudomsate, Worathad and Chubb, Anthony and Colon, Beatrice L and Col{\'o}n-L{\'o}pez, Daisy D and Corbett, Yolanda and Crowther, Gregory J and Cowan, Noemi and D{\textquoteright}Alessandro, Sarah and Le Dang, Na and Delves, Michael and DeRisi, Joseph L and Du, Alan Y and Duffy, Sandra and Abd El-Salam El-Sayed, Shimaa and Ferdig, Michael T and Fern{\'a}ndez Robledo, Jos{\'e} A and Fidock, David A and Florent, Isabelle and Fokou, Patrick V T and Galstian, Ani and Gamo, Francisco Javier and Gokool, Suzanne and Gold, Ben and Golub, Todd and Goldgof, Gregory M and Guha, Rajarshi and Guiguemde, W Armand and Gural, Nil and Guy, R Kiplin and Hansen, Michael A E and Hanson, Kirsten K and Hemphill, Andrew and Hooft van Huijsduijnen, Rob and Horii, Takaaki and Horrocks, Paul and Hughes, Tyler B and Huston, Christopher and Igarashi, Ikuo and Ingram-Sieber, Katrin and Itoe, Maurice A and Jadhav, Ajit and Naranuntarat Jensen, Amornrat and Jensen, Laran T and Jiang, Rays H Y and Kaiser, Annette and Keiser, Jennifer and Ketas, Thomas and Kicka, Sebastien and Kim, Sunyoung and Kirk, Kiaran and Kumar, Vidya P and Kyle, Dennis E and Lafuente, Maria Jose and Landfear, Scott and Lee, Nathan and Lee, Sukjun and Lehane, Adele M and Li, Fengwu and Little, David and Liu, Liqiong and Llin{\'a}s, Manuel and Loza, Maria I and Lubar, Aristea and Lucantoni, Leonardo and Lucet, Isabelle and Maes, Louis and Mancama, Dalu and Mansour, Nuha R and March, Sandra and McGowan, Sheena and Medina Vera, Iset and Meister, Stephan and Mercer, Luke and Mestres, Jordi and Mfopa, Alvine N and Misra, Raj N and Moon, Seunghyun and Moore, John P and Morais Rodrigues da Costa, Francielly and M{\"u}ller, Joachim and Muriana, Arantza and Nakazawa Hewitt, Stephen and Nare, Bakela and Nathan, Carl and Narraidoo, Nathalie and Nawaratna, Sujeevi and Ojo, Kayode K and Ortiz, Diana and Panic, Gordana and Papadatos, George and Parapini, Silvia and Patra, Kailash and Pham, Ngoc and Prats, Sarah and Plouffe, David M and Poulsen, Sally-Ann and Pradhan, Anupam and Quevedo, Celia and Quinn, Ronald J and Rice, Christopher A and Abdo Rizk, Mohamed and Ruecker, Andrea and St Onge, Robert and Salgado Ferreira, Rafaela and Samra, Jasmeet and Robinett, Natalie G and Schlecht, Ulrich and Schmitt, Marjorie and Silva Villela, Filipe and Silvestrini, Francesco and Sinden, Robert and Smith, Dennis A and Soldati, Thierry and Spitzm{\"u}ller, Andreas and Stamm, Serge Maximilian and Sullivan, David J and Sullivan, William and Suresh, Sundari and Suzuki, Brian M and Suzuki, Yo and Swamidass, S Joshua and Taramelli, Donatella and Tchokouaha, Lauve R Y and Theron, Anjo and Thomas, David and Tonissen, Kathryn F and Townson, Simon and Tripathi, Abhai K and Trofimov, Valentin and Udenze, Kenneth O and Ullah, Imran and Vallieres, Cindy and Vigil, Edgar and Vinetz, Joseph M and Voong Vinh, Phat and Vu, Hoan and Watanabe, Nao-Aki and Weatherby, Kate and White, Pamela M and Wilks, Andrew F and Winzeler, Elizabeth A and Wojcik, Edward and Wree, Melanie and Wu, Wesley and Yokoyama, Naoaki and Zollo, Paul H A and Abla, Nada and Blasco, Benjamin and Burrows, Jeremy and Laleu, Beno{\^\i}t and Leroy, Didier and Spangenberg, Thomas and Wells, Timothy and Willis, Paul A} } @article {1110, title = {Open-source hardware for medical devices.}, journal = {BMJ Innov}, volume = {2}, year = {2016}, month = {2016 Apr}, pages = {78-83}, abstract = {

Open-source hardware is hardware whose design is made publicly available so anyone can study, modify, distribute, make and sell the design or the hardware based on that design. Some open-source hardware projects can potentially be used as active medical devices. The open-source approach offers a unique combination of advantages, including reducing costs and faster innovation. This article compares 10 of open-source healthcare projects in terms of how easy it is to obtain the required components and build the device.

}, issn = {2055-642X}, doi = {10.1136/bmjinnov-2015-000080}, author = {Niezen, Gerrit and Eslambolchilar, Parisa and Thimbleby, Harold} } @article {1158, title = {{SCIFIO}: an extensible framework to support scientific image formats}, journal = {BMC bioinformatics}, volume = {17}, year = {2016}, pages = {521}, abstract = {BACKGROUND: No gold standard exists in the world of scientific image acquisition; a proliferation of instruments each with its own proprietary data format has made out-of-the-box sharing of that data nearly impossible. In the field of light microscopy, the Bio-Formats library was designed to translate such proprietary data formats to a common, open-source schema, enabling sharing and reproduction of scientific results. While Bio-Formats has proved successful for microscopy images, the greater scientific community was lacking a domain-independent framework for format translation. RESULTS: SCIFIO (SCientific Image Format Input and Output) is presented as a freely available, open-source library unifying the mechanisms of reading and writing image data. The core of SCIFIO is its modular definition of formats, the design of which clearly outlines the components of image I/O to encourage extensibility, facilitated by the dynamic discovery of the SciJava plugin framework. SCIFIO is structured to support coexistence of multiple domain-specific open exchange formats, such as Bio-Formats{\textquoteright} OME-TIFF, within a unified environment. CONCLUSIONS: SCIFIO is a freely available software library developed to standardize the process of reading and writing scientific image formats.}, keywords = {Bio-Formats, Image analysis, ImageJ, open-source, SCIFIO}, issn = {1471-2105}, doi = {10.1186/s12859-016-1383-0}, author = {Hiner, Mark C. and Rueden, Curtis T. and Eliceiri, Kevin W.} } @article {970, title = {The ImageJ ecosystem: An open platform for biomedical image analysis.}, journal = {Mol Reprod Dev}, year = {2015}, month = {2015 Jul 7}, abstract = {

Technology in microscopy advances rapidly, enabling increasingly affordable, faster, and more precise quantitative biomedical imaging, which necessitates correspondingly more-advanced image processing and analysis techniques. A wide range of software is available-from commercial to academic, special-purpose to Swiss army knife, small to large-but a key characteristic of software that is suitable for scientific inquiry is its accessibility. Open-source software is ideal for scientific endeavors because it can be freely inspected, modified, and redistributed; in particular, the open-software platform ImageJ has had a huge impact on the life sciences, and continues to do so. From its inception, ImageJ has grown significantly due largely to being freely available and its vibrant and helpful user community. Scientists as diverse as interested hobbyists, technical assistants, students, scientific staff, and advanced biology researchers use ImageJ on a daily basis, and exchange knowledge via its dedicated mailing list. Uses of ImageJ range from data visualization and teaching to advanced image processing and statistical analysis. The software{\textquoteright}s extensibility continues to attract biologists at all career stages as well as computer scientists who wish to effectively implement specific image-processing algorithms. In this review, we use the ImageJ project as a case study of how open-source software fosters its suites of software tools, making multitudes of image-analysis technology easily accessible to the scientific community. We specifically explore what makes ImageJ so popular, how it impacts the life sciences, how it inspires other projects, and how it is self-influenced by coevolving projects within the ImageJ ecosystem. Mol. Reprod. Dev. 2015. {\textcopyright} 2015 Wiley Periodicals, Inc.

}, issn = {1098-2795}, doi = {10.1002/mrd.22489}, author = {Schindelin, Johannes and Rueden, Curtis T and Hiner, Mark C and Eliceiri, Kevin W} } @article {997, title = {Innovating to enhance clinical data management using non-commercial and open source solutions across a multi-center network supporting inpatient pediatric care and research in Kenya.}, journal = {J Am Med Inform Assoc}, year = {2015}, month = {2015 Jun 10}, abstract = {

OBJECTIVE: To share approaches and innovations adopted to deliver a relatively inexpensive clinical data management (CDM) framework within a low-income setting that aims to deliver quality pediatric data useful for supporting research, strengthening the information culture and informing improvement efforts in local clinical practice.

MATERIALS AND METHODS: The authors implemented a CDM framework to support a Clinical Information Network (CIN) using Research Electronic Data Capture (REDCap), a noncommercial software solution designed for rapid development and deployment of electronic data capture tools. It was used for collection of standardized data from case records of multiple hospitals{\textquoteright} pediatric wards. R, an open-source statistical language, was used for data quality enhancement, analysis, and report generation for the hospitals.

RESULTS: In the first year of CIN, the authors have developed innovative solutions to support the implementation of a secure, rapid pediatric data collection system spanning 14 hospital sites with stringent data quality checks. Data have been collated on over 37 000 admission episodes, with considerable improvement in clinical documentation of admissions observed. Using meta-programming techniques in R, coupled with branching logic, randomization, data lookup, and Application Programming Interface (API) features offered by REDCap, CDM tasks were configured and automated to ensure quality data was delivered for clinical improvement and research use.

CONCLUSION: A low-cost clinically focused but geographically dispersed quality CDM (Clinical Data Management) in a long-term, multi-site, and real world context can be achieved and sustained and challenges can be overcome through thoughtful design and implementation of open-source tools for handling data and supporting research.

}, issn = {1527-974X}, doi = {10.1093/jamia/ocv028}, author = {Tuti, Timothy and Bitok, Michael and Paton, Chris and Makone, Boniface and Malla, Lucas and Muinga, Naomi and Gathara, David and English, Mike} } @article {993, title = {Open Source Software For Patient Data Management In Critical Care.}, journal = {Stud Health Technol Inform}, volume = {216}, year = {2015}, month = {2015}, pages = {920}, abstract = {

We have previously developed a Patient Data Management System for Intensive Care based on Open Source Software. The aim of this work was to adapt this software to use in Emergency Departments in low resource environments. The new software includes facilities for utilization of the South African Triage Scale and prediction of mortality based on independent predictive factors derived from data from the Tabarre Emergency Trauma Center in Port au Prince, Haiti.

}, issn = {0926-9630}, author = {Massaut, Jacques and Charretk, Nicolas and Gayraud, Olivia and Van Den Bergh, Rafael and Charles, Adelin and Edema, Nathalie} } @article {980, title = {Virtualization of Open-Source Secure Web Services to Support Data Exchange in a Pediatric Critical Care Research Network.}, journal = {J Am Med Inform Assoc}, year = {2015}, month = {2015 Mar 21}, abstract = {

OBJECTIVES: To examine the feasibility of deploying a virtual web service for sharing data within a research network, and to evaluate the impact on data consistency and quality.

MATERIAL AND METHODS: Virtual machines (VMs) encapsulated an open-source, semantically and syntactically interoperable secure web service infrastructure along with a shadow database. The VMs were deployed to 8 Collaborative Pediatric Critical Care Research Network Clinical Centers.

RESULTS: Virtual web services could be deployed in hours. The interoperability of the web services reduced format misalignment from 56\% to 1\% and demonstrated that 99\% of the data consistently transferred using the data dictionary and 1\% needed human curation.

CONCLUSIONS: Use of virtualized open-source secure web service technology could enable direct electronic abstraction of data from hospital databases for research purposes.

}, issn = {1527-974X}, doi = {10.1093/jamia/ocv009}, author = {Frey, Lewis J and Sward, Katherine A and Newth, Christopher Jl and Khemani, Robinder G and Cryer, Martin E and Thelen, Julie L and Enriquez, Rene and Shaoyu, Su and Pollack, Murray M and Harrison, Rick E and Meert, Kathleen L and Berg, Robert A and Wessel, David L and Shanley, Thomas P and Dalton, Heidi and Carcillo, Joseph and Jenkins, Tammara L and Dean, J Michael} } @article {945, title = {ExpertEyes: Open-source, high-definition eyetracking.}, journal = {Behav Res Methods}, year = {2014}, month = {2014 Jun 17}, abstract = {

ExpertEyes is a low-cost, open-source package of hardware and software that is designed to provide portable high-definition eyetracking. The project involves several technological innovations, including portability, high-definition video recording, and multiplatform software support. It was designed for challenging recording environments, and all processing is done offline to allow for optimization of parameter estimation. The pupil and corneal reflection are estimated using a novel forward eye model that simultaneously fits both the pupil and the corneal reflection with full ellipses, addressing a common situation in which the corneal reflection sits at the edge of the pupil and therefore breaks the contour of the ellipse. The accuracy and precision of the system are comparable to or better than what is available in commercial eyetracking systems, with a typical accuracy of less than 0.4{\textdegree} and best accuracy below 0.3{\textdegree}, and with a typical precision (SD method) around 0.3{\textdegree} and best precision below 0.2{\textdegree}. Part of the success of the system comes from a high-resolution eye image. The high image quality results from uncasing common digital camcorders and recording directly to SD cards, which avoids the limitations of the analog NTSC format. The software is freely downloadable, and complete hardware plans are available, along with sources for custom parts.

}, issn = {1554-3528}, doi = {10.3758/s13428-014-0465-z}, author = {Parada, Francisco J and Wyatte, Dean and Yu, Chen and Akavipat, Ruj and Emerick, Brandi and Busey, Thomas} } @article {1051, title = {High dimensional biological data retrieval optimization with NoSQL technology.}, journal = {BMC Genomics}, volume = {15 Suppl 8}, year = {2014}, month = {2014}, pages = {S3}, abstract = {

BACKGROUND: High-throughput transcriptomic data generated by microarray experiments is the most abundant and frequently stored kind of data currently used in translational medicine studies. Although microarray data is supported in data warehouses such as tranSMART, when querying relational databases for hundreds of different patient gene expression records queries are slow due to poor performance. Non-relational data models, such as the key-value model implemented in NoSQL databases, hold promise to be more performant solutions. Our motivation is to improve the performance of the tranSMART data warehouse with a view to supporting Next Generation Sequencing data.

RESULTS: In this paper we introduce a new data model better suited for high-dimensional data storage and querying, optimized for database scalability and performance. We have designed a key-value pair data model to support faster queries over large-scale microarray data and implemented the model using HBase, an implementation of Google{\textquoteright}s BigTable storage system. An experimental performance comparison was carried out against the traditional relational data model implemented in both MySQL Cluster and MongoDB, using a large publicly available transcriptomic data set taken from NCBI GEO concerning Multiple Myeloma. Our new key-value data model implemented on HBase exhibits an average 5.24-fold increase in high-dimensional biological data query performance compared to the relational model implemented on MySQL Cluster, and an average 6.47-fold increase on query performance on MongoDB.

CONCLUSIONS: The performance evaluation found that the new key-value data model, in particular its implementation in HBase, outperforms the relational model currently implemented in tranSMART. We propose that NoSQL technology holds great promise for large-scale data management, in particular for high-dimensional biological data such as that demonstrated in the performance evaluation described in this paper. We aim to use this new data model as a basis for migrating tranSMART{\textquoteright}s implementation to a more scalable solution for Big Data.

}, keywords = {Database Management Systems, Databases, Genetic, High-Throughput Nucleotide Sequencing, Humans, Information Storage and Retrieval, Medical Informatics, Multiple Myeloma, Oligonucleotide Array Sequence Analysis, Transcriptome}, issn = {1471-2164}, doi = {10.1186/1471-2164-15-S8-S3}, author = {Wang, Shicai and Pandis, Ioannis and Wu, Chao and He, Sijin and Johnson, David and Emam, Ibrahim and Guitton, Florian and Guo, Yike} } @article {1003, title = {Innovative approaches to clinical data management in resource limited settings using open-source technologies.}, journal = {PLoS Negl Trop Dis}, volume = {8}, year = {2014}, month = {2014 Sep}, pages = {e3134}, issn = {1935-2735}, doi = {10.1371/journal.pntd.0003134}, author = {Omollo, Raymond and Ochieng, Michael and Mutinda, Brian and Omollo, Truphosa and Owiti, Rhoda and Okeyo, Seth and Wasunna, Monique and Edwards, Tansy} } @article {1033, title = {Making cytological diagnoses on digital images using the iPath network.}, journal = {Acta Cytol}, volume = {58}, year = {2014}, month = {2014}, pages = {453-60}, abstract = {

BACKGROUND: The iPath telemedicine platform Basel is mainly used for histological and cytological consultations, but also serves as a valuable learning tool.

AIM: To study the level of accuracy in making diagnoses based on still images achieved by experienced cytopathologists, to identify limiting factors, and to provide a cytological image series as a learning set.

METHOD: Images from 167 consecutive cytological specimens of different origin were uploaded on the iPath platform and evaluated by four cytopathologists. Only wet-fixed and well-stained specimens were used. The consultants made specific diagnoses and categorized each as benign, suspicious or malignant.

RESULTS: For all consultants, specificity and sensitivity regarding categorized diagnoses were 83-92 and 85-93\%, respectively; the overall accuracy was 88-90\%. The interobserver agreement was substantial (κ = 0.791). The lowest rate of concordance was achieved in urine and bladder washings and in the identification of benign lesions.

CONCLUSION: Using a digital image set for diagnostic purposes implies that even under optimal conditions the accuracy rate will not exceed to 80-90\%, mainly because of lacking supportive immunocytochemical or molecular tests. This limitation does not disqualify digital images for teleconsulting or as a learning aid. The series of images used for the study are open to the public at http://pathorama.wordpress.com/extragenital-cytology-2013/.

}, keywords = {Adolescent, Adult, Aged, Aged, 80 and over, Child, Child, Preschool, Computers, Handheld, Cytodiagnosis, Diagnosis, Differential, Female, Humans, Hyperplasia, Infant, Male, Metaplasia, Middle Aged, Neoplasms, Observer Variation, Reproducibility of Results, Sensitivity and Specificity, Telemedicine}, issn = {0001-5547}, doi = {10.1159/000369241}, author = {Dalquen, Peter and Savic Prince, Spasenija and Spieler, Peter and Kunze, Dietmar and Neumann, Heinrich and Eppenberger-Castori, Serenella and Adams, Heiner and Glatz, Katharina and Bubendorf, Lukas} } @article {931, title = {Managing multicentre clinical trials with open source.}, journal = {Inform Health Soc Care}, volume = {39}, year = {2014}, month = {2014 Mar}, pages = {67-80}, abstract = {

Background: Multicentre clinical trials are challenged by high administrative burden, data management pitfalls and costs. This leads to a reduced enthusiasm and commitment of the physicians involved and thus to a reluctance in conducting multicentre clinical trials. Objective: The purpose of this study was to develop a web-based open source platform to support a multi-centre clinical trial. Methods: We developed on Drupal, an open source software distributed under the terms of the General Public License, a web-based, multi-centre clinical trial management system with the design science research approach. Results: This system was evaluated by user-testing and well supported several completed and on-going clinical trials and is available for free download. Conclusion: Open source clinical trial management systems are capable in supporting multi-centre clinical trials by enhancing efficiency, quality of data management and collaboration.

}, issn = {1753-8165}, doi = {10.3109/17538157.2013.812647}, author = {Raptis, Dimitri Aristotle and Mettler, Tobias and Fischer, Michael Alexander and Patak, Michael and Lesurtel, Mickael and Eshmuminov, Dilmurodjon and de Rougemont, Olivier and Graf, Rolf and Clavien, Pierre-Alain and Breitenstein, Stefan} } @article {865, title = {GBM volumetry using the 3D Slicer medical image computing platform.}, journal = {Sci Rep}, volume = {3}, year = {2013}, month = {2013}, pages = {1364}, abstract = {

Volumetric change in glioblastoma multiforme (GBM) over time is a critical factor in treatment decisions. Typically, the tumor volume is computed on a slice-by-slice basis using MRI scans obtained at regular intervals. (3D)Slicer - a free platform for biomedical research - provides an alternative to this manual slice-by-slice segmentation process, which is significantly faster and requires less user interaction. In this study, 4 physicians segmented GBMs in 10 patients, once using the competitive region-growing based GrowCut segmentation module of Slicer, and once purely by drawing boundaries completely manually on a slice-by-slice basis. Furthermore, we provide a variability analysis for three physicians for 12 GBMs. The time required for GrowCut segmentation was on an average 61\% of the time required for a pure manual segmentation. A comparison of Slicer-based segmentation with manual slice-by-slice segmentation resulted in a Dice Similarity Coefficient of 88.43 {\textpm} 5.23\% and a Hausdorff Distance of 2.32 {\textpm} 5.23 mm.

}, issn = {2045-2322}, doi = {10.1038/srep01364}, author = {Egger, Jan and Kapur, Tina and Fedorov, Andriy and Pieper, Steve and Miller, James V and Veeraraghavan, Harini and Freisleben, Bernd and Golby, Alexandra J and Nimsky, Christopher and Kikinis, Ron} } @article {793, title = {Integrating clinical practice and public health surveillance using electronic medical record systems.}, journal = {Am J Prev Med}, volume = {42}, year = {2012}, month = {2012 Jun}, pages = {S154-62}, abstract = {Electronic medical record (EMR) systems have rich potential to improve integration between primary care and the public health system at the point of care. EMRs make it possible for clinicians to contribute timely, clinically detailed surveillance data to public health practitioners without changing their existing workflows or incurring extra work. New surveillance systems can extract raw data from providers{\textquoteright} EMRs, analyze them for conditions of public health interest, and automatically communicate results to health departments. The current paper describes a model EMR-based public health surveillance platform called Electronic Medical Record Support for Public Health (ESP). The ESP platform provides live, automated surveillance for notifiable diseases, influenza-like illness, and diabetes prevalence, care, and complications. Results are automatically transmitted to state health departments.}, issn = {1873-2607}, doi = {10.1016/j.amepre.2012.04.005}, author = {Klompas, Michael and McVetta, Jason and Lazarus, Ross and Eggleston, Emma and Haney, Gillian and Kruskal, Benjamin A and Yih, W Katherine and Daly, Patricia and Oppedisano, Paul and Beagan, Brianne and Lee, Michael and Kirby, Chaim and Heisey-Grove, Dawn and DeMaria, Alfred and Platt, Richard} } @article {868, title = {The caBIG{\textregistered} Life Science Business Architecture Model.}, journal = {Bioinformatics}, volume = {27}, year = {2011}, month = {2011 May 15}, pages = {1429-35}, abstract = {

MOTIVATION: Business Architecture Models (BAMs) describe what a business does, who performs the activities, where and when activities are performed, how activities are accomplished and which data are present. The purpose of a BAM is to provide a common resource for understanding business functions and requirements and to guide software development. The cancer Biomedical Informatics Grid (caBIG{\textregistered}) Life Science BAM (LS BAM) provides a shared understanding of the vocabulary, goals and processes that are common in the business of LS research.

RESULTS: LS BAM 1.1 includes 90 goals and 61 people and groups within Use Case and Activity Unified Modeling Language (UML) Diagrams. Here we report on the model{\textquoteright}s current release, LS BAM 1.1, its utility and usage, and plans for future use and continuing development for future releases. Availability and Implementation: The LS BAM is freely available as UML, PDF and HTML (https://wiki.nci.nih.gov/x/OFNyAQ).

}, keywords = {Biomedical Research, Computational Biology, Computer Systems, National Cancer Institute (U.S.), Neoplasms, Software, United States, Vocabulary, Controlled}, issn = {1367-4811}, doi = {10.1093/bioinformatics/btr141}, author = {Boyd, Lauren Becnel and Hunicke-Smith, Scott P and Stafford, Grace A and Freund, Elaine T and Ehlman, Michele and Chandran, Uma and Dennis, Robert and Fernandez, Anna T and Goldstein, Stephen and Steffen, David and Tycko, Benjamin and Klemm, Juli D} } @inbook {springerlink:10.1007/978-1-4419-8204-9_9, title = {Medical Image Registration}, booktitle = {Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies}, year = {2011}, note = {10.1007/978-1-4419-8204-9_9}, pages = {227-245}, publisher = {Springer New York}, organization = {Springer New York}, abstract = {In this chapter, we cover the necessary background information required to understand medical image registration, the basic tools required to implement registration algorithms, and demonstrate a complete application for various types of registration between different modalities using freely available and maintained software.}, isbn = {978-1-4419-8204-9}, url = {http://dx.doi.org/10.1007/978-1-4419-8204-9_9}, author = {Aladl, Usaf E. and Peters, Terry}, editor = {El-Baz, Ayman S. and Acharya U, Rajendra and Laine, Andrew F. and Suri, Jasjit S.} } @conference {lien:79670M, title = {Open source tools for standardized privacy protection of medical images}, booktitle = {Medical Imaging 2011: Advanced PACS-based Imaging Informatics and Therapeutic Applications}, volume = {7967}, number = {1}, year = {2011}, pages = {79670M}, publisher = {SPIE}, organization = {SPIE}, abstract = {In addition to the primary care context, medical images are often useful for research projects and community healthcare networks, so-called "secondary use". Patient privacy becomes an issue in such scenarios since the disclosure of personal health information (PHI) has to be prevented in a sharing environment. In general, most PHIs should be completely removed from the images according to the respective privacy regulations, but some basic and alleviated data is usually required for accurate image interpretation. Our objective is to utilize and enhance these specifications in order to provide reliable software implementations for de- and re-identification of medical images suitable for online and offline delivery. DICOM (Digital Imaging and Communications in Medicine) images are de-identified by replacing PHI-specific information with values still being reasonable for imaging diagnosis and patient indexing. In this paper, this approach is evaluated based on a prototype implementation built on top of the open source framework DCMTK (DICOM Toolkit) utilizing standardized de- and re-identification mechanisms. A set of tools has been developed for DICOM de-identification that meets privacy requirements of an offline and online sharing environment and fully relies on standard-based methods.}, doi = {10.1117/12.877989}, url = {http://link.aip.org/link/?PSI/7967/79670M/1}, author = {Chung-Yueh Lien and Onken, Michael and Marco Eichelberg and Tsair Kao and Andreas Hein}, editor = {William W. Boonn and Brent J. Liu} } @article {610, title = {Adaptive radiotherapy based on contrast enhanced cone beam CT imaging.}, journal = {Acta oncologica (Stockholm, Sweden)}, volume = {49}, year = {2010}, month = {2010 Oct}, pages = {972-7}, abstract = {Cone beam CT (CBCT) imaging has become an integral part of radiation therapy, with images typically used for offline or online patient setup corrections based on bony anatomy co-registration. Ideally, the co-registration should be based on tumor localization. However, soft tissue contrast in CBCT images may be limited. In the present work, contrast enhanced CBCT (CECBCT) images were used for tumor visualization and treatment adaptation. Material and methods. A spontaneous canine maxillary tumor was subjected to repeated cone beam CT imaging during fractionated radiotherapy (10 fractions in total). At five of the treatment fractions, CECBCT images, employing an iodinated contrast agent, were acquired, as well as pre-contrast CBCT images. The tumor was clearly visible in post-contrast minus pre-contrast subtraction images, and these contrast images were used to delineate gross tumor volumes. IMRT dose plans were subsequently generated. Four different strategies were explored: 1) fully adapted planning based on each CECBCT image series, 2) planning based on images acquired at the first treatment fraction and patient repositioning following bony anatomy co-registration, 3) as for 2), but with patient repositioning based on co-registering contrast images, and 4) a strategy with no patient repositioning or treatment adaptation. The equivalent uniform dose (EUD) and tumor control probability (TCP) calculations to estimate treatment outcome for each strategy. Results. Similar translation vectors were found when bony anatomy and contrast enhancement co-registration were compared. Strategy 1 gave EUDs closest to the prescription dose and the highest TCP. Strategies 2 and 3 gave EUDs and TCPs close to that of strategy 1, with strategy 3 being slightly better than strategy 2. Even greater benefits from strategies 1 and 3 are expected with increasing tumor movement or deformation during treatment. The non-adaptive strategy 4 was clearly inferior to all three adaptive strategies. Conclusion. CECBCT may prove useful for adaptive radiotherapy.}, keywords = {Animals, Carcinoma, Cone-Beam Computed Tomography, Contrast Media, Dog Diseases, Dogs, Female, Maxillary Neoplasms, Patient Positioning, Radiographic Image Enhancement, Radiotherapy Planning, Computer-Assisted}, issn = {1651-226X}, author = {S{\o}vik, Aste and R{\o}dal, Jan and Skogmo, Hege K and Lerv{\r a}g, Christoffer and Eilertsen, Karsten and Malinen, Eirik} } @article {20482787, title = {Screensaver: an open source lab information management system (LIMS) for high throughput screening facilities.}, journal = {BMC bioinformatics}, volume = {11}, year = {2010}, month = {2010}, pages = {260}, abstract = {BACKGROUND: Shared-usage high throughput screening (HTS) facilities are becoming more common in academe as large-scale small molecule and genome-scale RNAi screening strategies are adopted for basic research purposes. These shared facilities require a unique informatics infrastructure that must not only provide access to and analysis of screening data, but must also manage the administrative and technical challenges associated with conducting numerous, interleaved screening efforts run by multiple independent research groups. RESULTS: We have developed Screensaver, a free, open source, web-based lab information management system (LIMS), to address the informatics needs of our small molecule and RNAi screening facility. Screensaver supports the storage and comparison of screening data sets, as well as the management of information about screens, screeners, libraries, and laboratory work requests. To our knowledge, Screensaver is one of the first applications to support the storage and analysis of data from both genome-scale RNAi screening projects and small molecule screening projects. CONCLUSIONS: The informatics and administrative needs of an HTS facility may be best managed by a single, integrated, web-accessible application such as Screensaver. Screensaver has proven useful in meeting the requirements of the ICCB-Longwood/NSRB Screening Facility at Harvard Medical School, and has provided similar benefits to other HTS facilities.}, author = {Tolopko, Andrew N and Sullivan, John P and Erickson, Sean D and Wrobel, David and Chiang, Su L and Rudnicki, Katrina and Rudnicki, Stewart and Nale, Jennifer and Selfors, Laura M and Greenhouse, Dara and Muhlich, Jeremy L and Shamu, Caroline E} } @article {19745435, title = {Reversible anonymization of DICOM images using automatically generated policies.}, journal = {Studies in health technology and informatics}, volume = {150}, year = {2009}, month = {2009}, pages = {861-5}, abstract = {Many real-world applications in the area of medical imaging like case study databases require separation of identifying (IDATA) and non-identifying (MDATA) data, specifically those offering Internet-based data access. These kinds of projects also must provide a role-based access system, controlling, how patient data must be organized and how it can be accessed. On DICOM image level, different image types support different kind of information, intermixing IDATA and MDATA in a single object. To separate them, it is possible to reversibly anonymize DICOM objects by substituting IDATA by a unique anonymous token. In case that later an authenticated user needs full access to an image, this token can be used for re-linking formerly separated IDATA and MDATA, thus resulting in a dynamically generated, exact copy of the original image. The approach described in this paper is based on the automatic generation of anonymization policies from the DICOM standard text, providing specific support for all kinds of DICOM images. The policies are executed by a newly developed framework based on the DICOM toolkit DCMTK and offer a reliable approach to reversible anonymization. The implementation is evaluated in a German BMBF-supported expert network in the area of skeletal dysplasias, SKELNET, but may generally be applicable to related projects, enormously improving quality and integrity of diagnostics in a field focused on images. It performs effectively and efficiently on real-world test images from the project and other kind of DICOM images.}, author = {Onken, Michael and Riesmeier, J{\"o}rg and Engel, Marcel and Yabanci, Adem and Zabel, Bernhard and Despr{\'e}s, Stefan} } @article {18096909, title = {caGrid 1.0: an enterprise Grid infrastructure for biomedical research.}, journal = {Journal of the American Medical Informatics Association : JAMIA}, volume = {15}, year = {2008}, month = {2008 Mar-Apr}, pages = {138-49}, abstract = {OBJECTIVE: To develop software infrastructure that will provide support for discovery, characterization, integrated access, and management of diverse and disparate collections of information sources, analysis methods, and applications in biomedical research. DESIGN: An enterprise Grid software infrastructure, called caGrid version 1.0 (caGrid 1.0), has been developed as the core Grid architecture of the NCI-sponsored cancer Biomedical Informatics Grid (caBIG) program. It is designed to support a wide range of use cases in basic, translational, and clinical research, including 1) discovery, 2) integrated and large-scale data analysis, and 3) coordinated study. MEASUREMENTS: The caGrid is built as a Grid software infrastructure and leverages Grid computing technologies and the Web Services Resource Framework standards. It provides a set of core services, toolkits for the development and deployment of new community provided services, and application programming interfaces for building client applications. RESULTS: The caGrid 1.0 was released to the caBIG community in December 2006. It is built on open source components and caGrid source code is publicly and freely available under a liberal open source license. The core software, associated tools, and documentation can be downloaded from the following URL: https://cabig.nci.nih.gov/workspaces/Architecture/caGrid. CONCLUSIONS: While caGrid 1.0 is designed to address use cases in cancer research, the requirements associated with discovery, analysis and integration of large scale data, and coordinated studies are common in other biomedical fields. In this respect, caGrid 1.0 is the realization of a framework that can benefit the entire biomedical community.}, author = {Oster, Scott and Langella, Stephen and Hastings, Shannon and Ervin, David and Madduri, Ravi and Phillips, Joshua and Kurc, Tahsin and Siebenlist, Frank and Covitz, Peter and Shanbhag, Krishnakant and Foster, Ian and Saltz, Joel} } @article {803, title = {Designing Tracking Software for Image-Guided Surgery Applications: IGSTK Experience.}, journal = {Int J Comput Assist Radiol Surg}, volume = {3}, year = {2008}, month = {2008 Nov 1}, pages = {395-403}, abstract = {OBJECTIVE: Many image-guided surgery applications require tracking devices as part of their core functionality. The Image-Guided Surgery Toolkit (IGSTK) was designed and developed to interface tracking devices with software applications incorporating medical images. METHODS: IGSTK was designed as an open source C++ library that provides the basic components needed for fast prototyping and development of image-guided surgery applications. This library follows a component-based architecture with several components designed for specific sets of image-guided surgery functions. At the core of the toolkit is the tracker component that handles communication between a control computer and navigation device to gather pose measurements of surgical instruments present in the surgical scene. The representations of the tracked instruments are superimposed on anatomical images to provide visual feedback to the clinician during surgical procedures. RESULTS: The initial version of the IGSTK toolkit has been released in the public domain and several trackers are supported. The toolkit and related information are available at www.igstk.org. CONCLUSION: With the increased popularity of minimally invasive procedures in health care, several tracking devices have been developed for medical applications. Designing and implementing high-quality and safe software to handle these different types of trackers in a common framework is a challenging task. It requires establishing key software design principles that emphasize abstraction, extensibility, reusability, fault-tolerance, and portability. IGSTK is an open source library that satisfies these needs for the image-guided surgery community.}, issn = {1861-6429}, doi = {10.1007/s11548-008-0243-4}, author = {Enquobahrie, Andinet and Gobbi, David and Turek, Matt and Cheng, Patrick and Yaniv, Ziv and Lindseth, Frank and Cleary, Kevin} } @article {18755989, title = {Whose personal control? Creating private, personally controlled health records for pediatric and adolescent patients.}, journal = {Journal of the American Medical Informatics Association : JAMIA}, volume = {15}, year = {2008}, month = {2008 Nov-Dec}, pages = {737-43}, abstract = {Personally controlled health records (PCHRs) enable patients to store, manage, and share their own health data, and promise unprecedented consumer access to medical information. To deploy a PCHR in the pediatric population requires crafting of access and security policies, tailored to a record that is not only under patient control, but one that may also be accessed by parents, guardians, and third-party entities. Such hybrid control of health information requires careful consideration of both the PCHR vendor{\textquoteright}s access policies, as well as institutional policies regulating data feeds to the PCHR, to ensure that the privacy and confidentiality of each user is preserved. Such policies must ensure compliance with legal mandates to prevent unintended disclosures and must preserve the complex interactions of the patient-provider relationship. Informed by our own operational involvement in the implementation of the Indivo PCHR, we provide a framework for understanding and addressing the challenges posed by child, adolescent, and family access to PCHRs.}, author = {Bourgeois, Fabienne C and Taylor, Patrick L and Emans, S Jean and Nigrin, Daniel J and Mandl, Kenneth D} } @article {17917780, title = {Benefits of using the DCM4CHE DICOM archive.}, journal = {Journal of digital imaging : the official journal of the Society for Computer Applications in Radiology}, volume = {20 Suppl 1}, year = {2007}, month = {2007 Nov}, pages = {125-9}, url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2039778}, author = {Warnock, Max J and Toland, Christopher and Evans, Damien and Wallace, Bill and Nagy, Paul} } @article {802, title = {The image-guided surgery toolkit IGSTK: an open source C++ software toolkit.}, journal = {J Digit Imaging}, volume = {20 Suppl 1}, year = {2007}, month = {2007 Nov}, pages = {21-33}, abstract = {This paper presents an overview of the image-guided surgery toolkit (IGSTK). IGSTK is an open source C++ software library that provides the basic components needed to develop image-guided surgery applications. It is intended for fast prototyping and development of image-guided surgery applications. The toolkit was developed through a collaboration between academic and industry partners. Because IGSTK was designed for safety-critical applications, the development team has adopted lightweight software processes that emphasizes safety and robustness while, at the same time, supporting geographically separated developers. A software process that is philosophically similar to agile software methods was adopted emphasizing iterative, incremental, and test-driven development principles. The guiding principle in the architecture design of IGSTK is patient safety. The IGSTK team implemented a component-based architecture and used state machine software design methodologies to improve the reliability and safety of the components. Every IGSTK component has a well-defined set of features that are governed by state machines. The state machine ensures that the component is always in a valid state and that all state transitions are valid and meaningful. Realizing that the continued success and viability of an open source toolkit depends on a strong user community, the IGSTK team is following several key strategies to build an active user community. These include maintaining a users and developers{\textquoteright} mailing list, providing documentation (application programming interface reference document and book), presenting demonstration applications, and delivering tutorial sessions at relevant scientific conferences.}, keywords = {Computer Systems, Data Display, Database Management Systems, Humans, Information Dissemination, Information Storage and Retrieval, Safety, Software, Software Design, Software Validation, Surgery, Computer-Assisted, Systems Integration, User-Computer Interface}, issn = {0897-1889}, doi = {10.1007/s10278-007-9054-3}, author = {Enquobahrie, Andinet and Cheng, Patrick and Gary, Kevin and Ibanez, Luis and Gobbi, David and Lindseth, Frank and Yaniv, Ziv and Aylward, Stephen and Jomier, Julien and Cleary, Kevin} } @article {17846835, title = {Open source software projects of the caBIG In Vivo Imaging Workspace Software special interest group.}, journal = {Journal of digital imaging : the official journal of the Society for Computer Applications in Radiology}, volume = {20 Suppl 1}, year = {2007}, month = {2007 Nov}, pages = {94-100}, abstract = {The Cancer Bioinformatics Grid (caBIG) program was created by the National Cancer Institute to facilitate sharing of IT infrastructure, data, and applications among the National Cancer Institute-sponsored cancer research centers. The program was launched in February 2004 and now links more than 50 cancer centers. In April 2005, the In Vivo Imaging Workspace was added to promote the use of imaging in cancer clinical trials. At the inaugural meeting, four special interest groups (SIGs) were established. The Software SIG was charged with identifying projects that focus on open-source software for image visualization and analysis. To date, two projects have been defined by the Software SIG. The eXtensible Imaging Platform project has produced a rapid application development environment that researchers may use to create targeted workflows customized for specific research projects. The Algorithm Validation Tools project will provide a set of tools and data structures that will be used to capture measurement information and associated needed to allow a gold standard to be defined for the given database against which change analysis algorithms can be tested. Through these and future efforts, the caBIG In Vivo Imaging Workspace Software SIG endeavors to advance imaging informatics and provide new open-source software tools to advance cancer research.}, author = {Prior, Fred W and Erickson, Bradley J and Tarbox, Lawrence} } @article {17249408, title = {OpenSourcePACS: an extensible infrastructure for medical image management.}, journal = {IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society}, volume = {11}, year = {2007}, month = {2007 Jan}, pages = {94-109}, abstract = {The development of comprehensive picture archive and communication systems (PACS) has mainly been limited to proprietary developments by vendors, though a number of freely available software projects have addressed specific image management tasks. The openSourcePACS project aims to provide an open source, common foundation upon which not only can a basic PACS be readily implemented, but to also support the evolution of new PACS functionality through the development of novel imaging applications and services. openSourcePACS consists of four main software modules: 1) image order entry, which enables the ordering and tracking of structured image requisitions; 2) an agent-based image server framework that coordinates distributed image services including routing, image processing, and querying beyond the present digital image and communications in medicine (DICOM) capabilities; 3) an image viewer, supporting standard display and image manipulation tools, DICOM presentation states, and structured reporting; and 4) reporting and result dissemination, supplying web-based widgets for creating integrated reports. All components are implemented using Java to encourage cross-platform deployment. To demonstrate the usage of openSourcePACS, a preliminary application supporting primary care/specialist communication was developed and is described herein. Ultimately, the goal of openSourcePACS is to promote the wide-scale development and usage of PACS and imaging applications within academic and research communities.}, url = {http://escholarship.org/uc/item/186368fv}, author = {Bui, Alex A T and Morioka, Craig and Dionisio, John David N and Johnson, David B and Sinha, Usha and Ardekani, Siamak and Taira, Ricky K and Aberle, Denise R and El-Saden, Suzie and Kangarloo, Hooshang} } @article {762, title = {A flexible registration framework for multimodal image data.}, journal = {Conf Proc IEEE Eng Med Biol Soc}, volume = {3}, year = {2004}, month = {2004}, pages = {1755-8}, abstract = {This paper describes a registration framework based on the insight segmentation and registration toolkit (ITK) which can be used for matching multimodal image data. Different target groups with individual needs and precognition are addressed. The framework offers tools for supporting different matching tasks in a clinical environment. A setup editor defines specific rigid or non rigid matching approaches and the appropriate parameters. Different metrics including a correlation metric, a difference metric and mutual information based metrics are available. Furthermore, a test series editor can be used to evaluate the selected setup. The evaluation results, which are expressed in statistical figures, trends and performance measures, can be visualized and used for an optimal adapted setup configuration. Tests for matching precision, quality and parameter adjustments are offered. For export and import of image data, the most frequently used file formats of clinical environments like DICOM and ANALYZE are supported. We demonstrate some registration examples which frequently occur in the neurosurgical routine of a University Hospital.}, issn = {1557-170X}, doi = {10.1109/IEMBS.2004.1403526}, author = {Dickhaus, H and Floca, R and Eisenmann, U and Metzner, R and Wirtz, C R} } @article {15361001, title = {The RODS Open Source Project: removing a barrier to syndromic surveillance.}, journal = {Studies in health technology and informatics}, volume = {107}, year = {2004}, month = {2004}, pages = {1192-6}, abstract = {The goal of the Real-time Outbreak and Disease Surveillance (RODS) Open Source Project is to accelerate deployment of computer-based syndromic surveillance. To this end, the project has released the RODS software under the GNU General Public License and created an organizational structure to catalyze its development. This paper describes the design of the software, requested extensions, and the structure of the development effort.}, author = {Espino, Jeremy U and Wagner, Michael M and Tsui, Fu-Chang and Su, Hoah-Der and Olszewski, Robert T and Lie, Zhen and Chapman, Wendy and Zeng, Xiaoming and Ma, Lili and Lu, Zhong Wei and Dara, Jagan} } @article {12807803, title = {Technical description of RODS: a real-time public health surveillance system.}, journal = {Journal of the American Medical Informatics Association : JAMIA}, volume = {10}, year = {2003}, month = {2003 Sep-Oct}, pages = {399-408}, abstract = {This report describes the design and implementation of the Real-time Outbreak and Disease Surveillance (RODS) system, a computer-based public health surveillance system for early detection of disease outbreaks. Hospitals send RODS data from clinical encounters over virtual private networks and leased lines using the Health Level 7 (HL7) message protocol. The data are sent in real time. RODS automatically classifies the registration chief complaint from the visit into one of seven syndrome categories using Bayesian classifiers. It stores the data in a relational database, aggregates the data for analysis using data warehousing techniques, applies univariate and multivariate statistical detection algorithms to the data, and alerts users of when the algorithms identify anomalous patterns in the syndrome counts. RODS also has a Web-based user interface that supports temporal and spatial analyses. RODS processes sales of over-the-counter health care products in a similar manner but receives such data in batch mode on a daily basis. RODS was used during the 2002 Winter Olympics and currently operates in two states-Pennsylvania and Utah. It has been and continues to be a resource for implementing, evaluating, and applying new methods of public health surveillance.}, author = {Tsui, Fu-Chiang and Espino, Jeremy U and Dato, Virginia M and Gesteland, Per H and Hutman, Judith and Wagner, Michael M} }