Uncertainty guidance in proton therapy planning visualization

Information

• Publication Type: Journal Paper with Conference Talk
• Workgroup(s)/Project(s): not specified
• Date: February 2023
• Journal: Computers and Graphics
• Volume: 111
• Open Access: yes
• ISSN: 1873-7684
• Event: VCBM 2023
• DOI: 10.1016/j.cag.2023.02.002
• Publisher: PERGAMON-ELSEVIER SCIENCE LTD
• Pages: 166 – 179
• Keywords: Visual analytics, Applied computing, Decision support systems

Abstract

We investigate uncertainty guidance mechanisms to support proton therapy (PT) planning visualization. Uncertainties in the PT workflow pose significant challenges for navigating treatment plan data and selecting the most optimal plan among alternatives. Although guidance techniques have not yet been applied to PT planning scenarios, they have successfully supported sense- and decision-making processes in other contexts. We hypothesize that augmenting PT uncertainty visualization with guidance may influence the intended users' perceived confidence and provide new insights. To this end, we follow an iterative co-design process with domain experts to develop a visualization dashboard enhanced with distinct level-of-detail uncertainty guidance mechanisms. Our approach classifies uncertainty guidance into two dimensions: degree of intrusiveness and detail-orientation. Our dashboard supports the comparison of multiple treatment plans (i.e., nominal plans with their translational variations) while accounting for multiple uncertainty factors. We subsequently evaluate the designed and developed strategies by assessing perceived confidence and effectiveness during a sense- and decision-making process. Our findings indicate that uncertainty guidance in PT planning visualization does not necessarily impact the perceived confidence of the users in the process. Nonetheless, it provides new insights and raises uncertainty awareness during treatment plan selection. This observation was particularly evident for users with longer experience in PT planning.

Additional Files and Images

Weblinks

• Entry in reposiTUm (TU Wien Publication Database)
• DOI: 10.1016/j.cag.2023.02.002

BibTeX

@article{musleh-2023-ugi,
  title =      "Uncertainty guidance in proton therapy planning
               visualization",
  author =     "Maath Musleh and Ludvig Paul Muren and Laura Toussaint and
               Anne Vestergaard and Eduard Gr\"{o}ller and Renata Raidou",
  year =       "2023",
  abstract =   "We investigate uncertainty guidance mechanisms to support
               proton therapy (PT) planning visualization. Uncertainties in
               the PT workflow pose significant challenges for navigating
               treatment plan data and selecting the most optimal plan
               among alternatives.  Although guidance techniques have not
               yet been applied to PT planning scenarios, they have
               successfully supported sense- and decision-making processes
               in other contexts. We hypothesize that augmenting PT
               uncertainty visualization with guidance may influence the
               intended users' perceived confidence and provide new
               insights. To this end, we follow an iterative co-design
               process with domain experts to develop a visualization
               dashboard enhanced with distinct level-of-detail uncertainty
               guidance mechanisms. Our approach classifies uncertainty
               guidance into two dimensions: degree of intrusiveness and
               detail-orientation. Our dashboard supports the comparison of
               multiple treatment plans (i.e., nominal plans with their
               translational variations) while accounting for multiple
               uncertainty factors. We subsequently evaluate the designed
               and developed strategies by assessing perceived confidence
               and effectiveness during a sense- and decision-making
               process. Our findings indicate that uncertainty guidance in
               PT planning visualization does not necessarily impact the
               perceived confidence of the users in the process.
               Nonetheless, it provides new insights and raises uncertainty
               awareness during treatment plan selection. This observation
               was particularly evident for users with longer experience in
               PT planning.",
  month =      feb,
  journal =    "Computers and Graphics",
  volume =     "111",
  issn =       "1873-7684",
  doi =        "10.1016/j.cag.2023.02.002",
  publisher =  "PERGAMON-ELSEVIER SCIENCE LTD",
  pages =      "166--179",
  keywords =   "Visual analytics, Applied computing, Decision support
               systems",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2023/musleh-2023-ugi/",
}