Open AccessVisualization of 4D multimodal imaging data and its applications in radiotherapy planning
Author(s) -
Schlachter Matthias,
Fechter Tobias,
Adebahr Sonja,
SchimekJasch Tanja,
Nestle Ursula,
Bühler Katja
Publication year - 2017
Publication title -
journal of applied clinical medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.83
H-Index - 48
ISSN - 1526-9914
DOI - 10.1002/acm2.12209
Subject(s) - computer science , visualization , correctness , radiation treatment planning , rendering (computer graphics) , medical physics , ground truth , consistency (knowledge bases) , data mining , artificial intelligence , radiation therapy , radiology , medicine , programming language
Purpose To explore the benefit of using 4D multimodal visualization and interaction techniques for defined radiotherapy planning tasks over a treatment planning system used in clinical routine (C‐ TPS ) without dedicated 4D visualization. Methods We developed a 4D visualization system (4D‐ VS ) with dedicated rendering and fusion of 4D multimodal imaging data based on a list of requirements developed in collaboration with radiation oncologists. We conducted a user evaluation in which the benefits of our approach were evaluated in comparison to C‐ TPS for three specific tasks: assessment of internal target volume ( ITV ) delineation, classification of tumor location in peripheral or central, and assessment of dose distribution. For all three tasks, we presented test cases for which we measured correctness, certainty, consistency followed by an additional survey regarding specific visualization features. Results Lower quality of the test ITV s (ground truth quality was available) was more likely to be detected using 4D‐ VS . ITV ratings were more consistent in 4D‐ VS and the classification of tumor location had a higher accuracy. Overall evaluation of the survey indicates 4D‐ VS provides better spatial comprehensibility and simplifies the tasks which were performed during testing. Conclusions The use of 4D‐ VS has improved the assessment of ITV delineations and classification of tumor location. The visualization features of 4D‐ VS have been identified as helpful for the assessment of dose distribution during user testing.