Nicolas Grossmann, Oscar Casares-Magaz, Ludvig P. Muren,
Vitali Moiseenko, John P. Einck, Meister Eduard Gröller, and Renata Raidou
(Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM), pp.69-78, 2019; doi)
In radiation therapy, anatomical changes in the patient might lead to deviations between the planned and delivered dose- including inadequate tumor coverage, and overradiation of healthy tissues. Exploring and analyzing anatomical changes throughout the entire treatment period can help clinical researchers to design appropriate treatment strategies, while identifying patients that are more prone to radiation-induced toxicity. We present the Pelvis Runner, a novel application for exploring the variability of segmented pelvic organs in multiple patients, across the entire radiation therapy treatment process. Our application addresses (i) the global exploration and analysis of pelvic organ shape variability in an abstracted tabular view and (ii) the local exploration and analysis thereof in anatomical 2D/3D views, where comparative and ensemble visualizations are integrated. The workflow is based on available retrospective cohort data, which incorporate segmentations of the bladder, the prostate, and the rectum through the entire radiation therapy process. The Pelvis Runner is applied to four usage scenarios, which were conducted with two clinical researchers, i.e., medical physicists. Our application provides clinical researchers with promising support in demonstrating the significance of treatment plan adaptation to anatomical changes.
BibTeX
@inproceedings {Grossmann:PelvisRunner:2019,
booktitle = {Eurographics Workshop on Visual Computing for Biology and Medicine},
title = {{Pelvis Runner: Visualizing Pelvic Organ Variability in a Cohort of Radiotherapy Patients}},
author = {Grossmann, Nicolas and Casares-Magaz, Oscar and Muren, Ludvig Paul and Moiseenko, Vitali and Einck, John P. and Gröller, Eduard and Raidou, Renata Georgia},
year = {2019},
pages = {69--78},
publisher = {The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {10.2312/vcbm.20191233}
}