TY - JOUR
T1 - Integrating the OHIF Viewer into XNAT
T2 - Achievements, Challenges and Prospects for Quantitative Imaging Studies
AU - Doran, Simon J.
AU - Al Sa’D, Mohammad
AU - Petts, James A.
AU - Darcy, James
AU - Alpert, Kate
AU - Cho, Woonchan
AU - Sanchez, Lorena Escudero
AU - Alle, Sachidanand
AU - El Harouni, Ahmed
AU - Genereaux, Brad
AU - Ziegler, Erik
AU - Harris, Gordon J.
AU - Aboagye, Eric O.
AU - Sala, Evis
AU - Koh, Dow Mu
AU - Marcus, Dan
N1 - Funding Information:
Funding: This study represents independent research supported by the National Institute for Health Research (NIHR) Biomedical Research Centre, the Clinical Research Facility in Imaging and the Cancer Research Network at The Royal Marsden NHS Foundation Trust (RMH) and the Institute of Cancer Research, London (ICR), as well as the National Institute of Health Research (NIHR) Cambridge Biomedical Research Centre (BRC-1215-20014). Staff effort for this project was supported by CRUK funding C4278/A27066 for the National Cancer Imaging Translational Accelerator (NCITA) and for the Cancer Research UK (CRUK) Cambridge Centre [C9685/A25177], as well as National Cancer Institute (NCI) grants 1U24CA204854 and 1U24CA199460. This project was made possible in part by grant 2020-225168 from the Chan Zuckerberg Initiative DAF, an advised fund of Silicon Valley Community Foundation, and has also benefited from historical support of the Cancer Imaging Centre at the RMH and the ICR from Cancer Research UK (CRUK) and the Engineering and Physical Sciences Research Council, in association with Medical Research Council and Department of Health C1060/A10334, C1060/A16464. E Ziegler is supported by Radical Imaging LLC and via NCI grant R01CA235589 as a subcontract to Novometrics LLC.
Funding Information:
This study represents independent research supported by the National Institute for Health Research (NIHR) Biomedical Research Centre, the Clinical Research Facility in Imaging and the Cancer Research Network at The Royal Marsden NHS Foundation Trust (RMH) and the Institute of Cancer Research, London (ICR), as well as the National Institute of Health Research (NIHR) Cambridge Biomedical Research Centre (BRC-1215-20014). Staff effort for this project was supported by CRUK funding C4278/A27066 for the National Cancer Imaging Translational Accelerator (NCITA) and for the Cancer Research UK (CRUK) Cambridge Centre [C9685/A25177], as well as National Cancer Institute (NCI) grants 1U24CA204854 and 1U24CA199460. This project was made possible in part by grant 2020-225168 from the Chan Zuckerberg Initiative DAF, an advised fund of Silicon Valley Community Foundation, and has also benefited from historical support of the Cancer Imaging Centre at the RMH and the ICR from Cancer Research UK (CRUK) and the Engineering and Physical Sciences Research Council, in association with Medical Research Council and Department of Health C1060/A10334, C1060/A16464. E Ziegler is supported by Radical Imaging LLC and via NCI grant R01CA235589 as a subcontract to Novometrics LLC.Although, in the years since the inception of the project, numerous commercial and academic ventures have incorporated the OHIF Viewer, few such examples were available at the outset. The authors are thus grateful for initial hints and preliminary expertise gained by Amin EL-Rowmeim, Department of Radiology at Memorial Sloan Kettering Cancer Centre. The data for Figure 4 were made available by kind permission of Ben Glocker (Imperial College London) Alexandra Taylor and David Bernstein (Royal Marsden Hospital).
Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2022/2
Y1 - 2022/2
N2 - Purpose: XNAT is an informatics software platform to support imaging research, particularly in the context of large, multicentre studies of the type that are essential to validate quantitative imaging biomarkers. XNAT provides import, archiving, processing and secure distribution facilities for image and related study data. Until recently, however, modern data visualisation and annotation tools were lacking on the XNAT platform. We describe the background to, and implementation of, an integration of the Open Health Imaging Foundation (OHIF) Viewer into the XNAT environment. We explain the challenges overcome and discuss future prospects for quantitative imaging studies. Materials and methods: The OHIF Viewer adopts an approach based on the DICOM web protocol. To allow operation in an XNAT environment, a data-routing methodology was developed to overcome the mismatch between the DICOM and XNAT information models and a custom viewer panel created to allow navigation within the viewer between different XNAT projects, subjects and imaging sessions. Modifications to the development environment were made to allow developers to test new code more easily against a live XNAT instance. Major new developments focused on the creation and storage of regions-of-interest (ROIs) and included: ROI creation and editing tools for both contour-and mask-based regions; a “smart CT” paintbrush tool; the integration of NVIDIA’s Artificial Intelligence Assisted Annotation (AIAA); the ability to view surface meshes, fractional segmentation maps and image overlays; and a rapid image reader tool aimed at radiologists. We have incorporated the OHIF microscopy extension and, in parallel, introduced support for microscopy session types within XNAT for the first time. Results: Integration of the OHIF Viewer within XNAT has been highly successful and numerous additional and enhanced tools have been created in a programme started in 2017 that is still ongoing. The software has been downloaded more than 3700 times during the course of the development work reported here, demonstrating the impact of the work. Conclusions: The OHIF open-source, zero-footprint web viewer has been incorporated into the XNAT platform and is now used at many institutions worldwide. Further innovations are envisaged in the near future.
AB - Purpose: XNAT is an informatics software platform to support imaging research, particularly in the context of large, multicentre studies of the type that are essential to validate quantitative imaging biomarkers. XNAT provides import, archiving, processing and secure distribution facilities for image and related study data. Until recently, however, modern data visualisation and annotation tools were lacking on the XNAT platform. We describe the background to, and implementation of, an integration of the Open Health Imaging Foundation (OHIF) Viewer into the XNAT environment. We explain the challenges overcome and discuss future prospects for quantitative imaging studies. Materials and methods: The OHIF Viewer adopts an approach based on the DICOM web protocol. To allow operation in an XNAT environment, a data-routing methodology was developed to overcome the mismatch between the DICOM and XNAT information models and a custom viewer panel created to allow navigation within the viewer between different XNAT projects, subjects and imaging sessions. Modifications to the development environment were made to allow developers to test new code more easily against a live XNAT instance. Major new developments focused on the creation and storage of regions-of-interest (ROIs) and included: ROI creation and editing tools for both contour-and mask-based regions; a “smart CT” paintbrush tool; the integration of NVIDIA’s Artificial Intelligence Assisted Annotation (AIAA); the ability to view surface meshes, fractional segmentation maps and image overlays; and a rapid image reader tool aimed at radiologists. We have incorporated the OHIF microscopy extension and, in parallel, introduced support for microscopy session types within XNAT for the first time. Results: Integration of the OHIF Viewer within XNAT has been highly successful and numerous additional and enhanced tools have been created in a programme started in 2017 that is still ongoing. The software has been downloaded more than 3700 times during the course of the development work reported here, demonstrating the impact of the work. Conclusions: The OHIF open-source, zero-footprint web viewer has been incorporated into the XNAT platform and is now used at many institutions worldwide. Further innovations are envisaged in the near future.
KW - Image visualisation
KW - OHIF
KW - Rapid reader
KW - Regions-of-interest
KW - Web viewer
KW - XNAT
UR - http://www.scopus.com/inward/record.url?scp=85124833906&partnerID=8YFLogxK
U2 - 10.3390/tomography8010040
DO - 10.3390/tomography8010040
M3 - Article
C2 - 35202205
AN - SCOPUS:85124833906
SN - 2379-1381
VL - 8
SP - 497
EP - 512
JO - Tomography (Ann Arbor, Mich.)
JF - Tomography (Ann Arbor, Mich.)
IS - 1
ER -