Publication

VAPOR: Visual Analytics for the Exploration of Pelvic Organ Variability in Radiotherapy

Furmanová, K., Grossmann, N., Muren, L. P., Casares-Magaz, O., Moiseenko, V., Einck, J. P., Gröller, M. E. & Raidou, R. G., Oct-2020, In : Computers & graphics-Uk. 91, p. 25-38 14 p.

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  • VAPOR: Visual Analytics for the Exploration of Pelvic Organ Variability in Radiotherapy

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DOI

  • Katarina Furmanová
  • Nicolas Grossmann
  • Ludvig P Muren
  • Oscar Casares-Magaz
  • Vitali Moiseenko
  • John P Einck
  • M Eduard Gröller
  • Renata G Raidou

In radiation therapy (RT) for prostate cancer, changes in patient anatomy during treatment might lead to inadequate tumor coverage and higher irradiation of healthy tissues in the nearby pelvic organs. Exploring and analyzing anatomical variability throughout the course of RT can support the design of more robust treatment strategies, while identifying patients that are prone to radiation-induced toxicity. We present VAPOR, a novel application for the exploration of pelvic organ variability in a cohort of patients, across the entire treatment process. Our application addresses: (i) the global exploration and analysis of anatomical variability in an abstracted tabular view, (ii) the local exploration and analysis thereof in anatomical 2D/3D views, where comparative and ensemble visualizations are integrated, and (iii) the correlation of anatomical variability with radiation doses and potential toxicity. The workflow is based on available retrospective cohort data, which include segmentations of the bladder, the prostate, and the rectum through the entire treatment period. VAPOR is applied to four usage scenarios, which were conducted with two medical physicists. Our application provides clinical researchers with promising support in demonstrating the significance of treatment adaptation to anatomical changes.

Original languageEnglish
Pages (from-to)25-38
Number of pages14
JournalComputers & graphics-Uk
Volume91
Publication statusPublished - Oct-2020
Externally publishedYes

ID: 132713403