Visual Analytics for Digital Radiotherapy: Towards a Comprehensible Pipeline

Renata Raidou, Marcel Breeuwer, Anna Vilanova
Visual Analytics for Digital Radiotherapy: Towards a Comprehensible Pipeline
Computer Graphics Forum (Proceedings of Eurographics), 36(), April 2017. [image2]

Information

Abstract

Prostate cancer is one of the most frequently occurring types of cancer in males. It is often treated with radiation therapy,which aims at irradiating tumors with a high dose, while sparing the surrounding healthy tissues. In the course of the years,radiotherapy technology has undergone great advancements. However, tumors are not only different from each other, theyare also highly heterogeneous within, consisting of regions with distinct tissue characteristics, which should be treated withdifferent radiation doses. Tailoring radiotherapy planning to the specific needs and intra-tumor tissue characteristics of eachpatient is expected to lead to more effective treatment strategies. Currently, clinical research is moving towards this direction,but an understanding of the specific tumor characteristics of each patient, and the integration of all available knowledge into apersonalizable radiotherapy planning pipeline are still required. The present work describes solutions from the field of VisualAnalytics, which aim at incorporating the information from the distinct steps of the personalizable radiotherapy planningpipeline, along with eventual sources of uncertainty, into comprehensible visualizations. All proposed solutions are meantto increase the – up to now, limited – understanding and exploratory capabilities of clinical researchers. These approachescontribute towards the interactive exploration, visual analysis and understanding of the involved data and processes at differentsteps of the radiotherapy planning pipeline, creating a fertile ground for future research in radiotherapy planning.

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BibTeX

@article{rraidou_EG17,
  title =      "Visual Analytics for Digital Radiotherapy: Towards a
               Comprehensible Pipeline",
  author =     "Renata Raidou and Marcel Breeuwer and Anna Vilanova",
  year =       "2017",
  abstract =   "Prostate cancer is one of the most frequently occurring
               types of cancer in males. It is often treated with radiation
               therapy,which aims at irradiating tumors with a high dose,
               while sparing the surrounding healthy tissues. In the course
               of the years,radiotherapy technology has undergone great
               advancements. However, tumors are not only different from
               each other, theyare also highly heterogeneous within,
               consisting of regions with distinct tissue characteristics,
               which should be treated withdifferent radiation doses.
               Tailoring radiotherapy planning to the specific needs and
               intra-tumor tissue characteristics of eachpatient is
               expected to lead to more effective treatment strategies.
               Currently, clinical research is moving towards this
               direction,but an understanding of the specific tumor
               characteristics of each patient, and the integration of all
               available knowledge into apersonalizable radiotherapy
               planning pipeline are still required. The present work
               describes solutions from the field of VisualAnalytics, which
               aim at incorporating the information from the distinct steps
               of the personalizable radiotherapy planningpipeline, along
               with eventual sources of uncertainty, into comprehensible
               visualizations. All proposed solutions are meantto increase
               the – up to now, limited – understanding and exploratory
               capabilities of clinical researchers. These
               approachescontribute towards the interactive exploration,
               visual analysis and understanding of the involved data and
               processes at differentsteps of the radiotherapy planning
               pipeline, creating a fertile ground for future research in
               radiotherapy planning.",
  month =      apr,
  journal =    "Computer Graphics Forum (Proceedings of Eurographics)",
  volume =     "36",
  booktitle =  "Computer Graphics Forum (Proceedings of Eurographics)",
  pages =      "--",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2017/rraidou_EG17/",
}