Jonas Petersen

Jonas Petersen

Bachelor's Thesis

Increasing the Comprehensibility of Rheumatoid Arthritis in Virtual Reality

Advisors:

Markus Wirth (M.Sc.), Prof. Dr. Björn Eskofier

Duration:

01/2021 – 05/2021

Abstract:

Rheumatoid Arthritis is a chronic inflammatory autoimmune disease that leads to joint destruction, functional disability and early death. Circumstances such as genetic background as well as personal and environmental factors can increase the probability to develop the disease. The prevalence of the global population of Rheumatoid Arthritis is about 1% [1, 2, 3]. To treat Rheumatoid Arthritis medications are used, which can be divided into three classes: nonsteroidal antiinflammatory drugs (NSAIDs), corticosteroids, and DMARDs [4].
Beyond optimizing medication, it is further essential that patients comprehend and acknowledge their disease for successful treatment. One possibility to achieve this, is to communicate the stage and progression of the disease using visual images like a CT scan of the affected areas. Further, the T-score, a definition for osteoporosis [5], is used to express the bone density. This indicator is highly intransparent for patients and therefore only has limited impact in supporting the education of patients. To reduce the obstacles to understand and accept the disease and its progression, results of examinations must be made more comprehensible to be meaningful for patients.
Virtual Reality (VR) technology has great potential to reduce the barriers of educating patients by providing high immersion and three-dimensional representations to the user utilizing stereoscopic vision. For visualizing disease patterns this can be beneficial, since it enables to create a more tangible understanding of affected joints. Further, it gives patients the possibility to monitor and follow processes in their entirety, making treatment safer and more efficient. Previous research already explored the representation of medical data in VR. The main areas of application are surgery and diagnosis [6]. The primary goal in this context is to facilitate a simple and vivid illustration of patient data, to increase the efficiency of medical education and treatment processes. One example is the training for surgeons to achieve higher accuracy and better predictability [7]. Other research work addresses the field of preprocessing CT data for the use in VR to enable realistic representations of medical data [8, 9]. In terms of patient education only few work explored the applicability of VR. One example is the use of 360 degree VR video footage to explain technical operation aspects to patients [10]. In order to not only refer to general information, like technical aspects of an operation, but create valuable individualized content for patients, it is inevitable to present personalized data (e.g. CT or MRT) in VR [11].
Therefore, the aim of this thesis is to explore the possibilities of VR for patient education using personalized data. CT scans of patients suffering from Rheumatoid Arthritis are integrated and illustrated in VR to make the stage and process of the disease more graspable for them. For the implementation Unity, and displaying a HTC Vive system is used. The main step is the integration of patient data into Unity, whereby the CT scans must be converted to OBJ-files for the purpose of embedding them in Unity.
In a user study, including at least ten participants, the applicability of the implemented VR system is investigated. In detail, the user experience and usability of the system is researched. Further, the efficiency of different interaction methods is investigated by measuring the performance of patients. For performance analysis the task completion time as well as the understanding of disease relevant aspects will be examined using several tasks.

References:

[1] Malviya, Gaurav, et al.: Biological therapies for rheumatoid arthritis: progress to date. BioDrugs 27.4, 329-345, 2013.
[2] McInnes, Iain B., and Georg Schett: The pathogenesis of rheumatoid arthritis. New England Journal of Medicine 365.23, 2205-2219, 2011.
[3] Heidari B: Rheumatoid Arthritis: Early diagnosis and treatment outcomes. Caspian J Intern Med 2(1), 161-170, 2011.
[4] O’Dell, James R.: Therapeutic strategies for rheumatoid arthritis. New England Journal of Medicine 350.25, 2591-2602, 2004.
[5] Blake, Glen M., and Ignac Fogelman: The role of DXA bone density scans in the diagnosis and treatment of osteoporosis. Postgraduate medical journal 83.982, 509-517, 2007.
[6] Torner Ribe, Jordi, et al.: Virtual reality application applied to biomedical models reconstructed from CT scanning. Computer Science Research Notes [CSRN], 2016.
[7] Dammann, Florian, et a.l: Computer-aided surgical planning for implantation of hearing aids based on CT data in a VR environment. Radiographics 21.1, 183-190, 2001.
[8] Tylova, Na’a, et al.: 3D Reconstruction of CT Scans For Visualization in Virtual Reality., 2019.
[9] Kohout, Jan, et al.: Preprocessing CT Images for Virtual Reality Based on MATLAB. Proceedings of the Computational Methods in Systems and Software. Springer, Cham, 2019.
[10] Johnson, Kalaina, et al.: Learning in 360 degrees: A pilot study on the use of virtual reality for radiation therapy patient education. Journal of Medical Imaging and Radiation Sciences, 2020.
[11] Wolfartsberger, Josef: Analyzing the potential of Virtual Reality for engineering design review. Automation in Construction 104, 27-37, 2019.