SU-E-J-97: Quality Assurance of Deformable Image Registration Algorithms: How Realistic Should Phantoms Be?

Journal Article · Mon Jun 15 04:00:00 EDT 2015 · Medical Physics

DOI:https://doi.org/10.1118/1.4924184· OSTI ID:22494114

Saenz, D; Stathakis, S; Kirby, N ^[1]; Kim, H; Chen, J ^[2]

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1. University of Texas Health Science Center at San Antonio, San Antonio, TX (United States)
2. University of California San Francisco, San Francisco, CA (United States)

Purpose: Deformable image registration (DIR) has widespread uses in radiotherapy for applications such as dose accumulation studies, multi-modality image fusion, and organ segmentation. The quality assurance (QA) of such algorithms, however, remains largely unimplemented. This work aims to determine how detailed a physical phantom needs to be to accurately perform QA of a DIR algorithm. Methods: Virtual prostate and head-and-neck phantoms, made from patient images, were used for this study. Both sets consist of an undeformed and deformed image pair. The images were processed to create additional image pairs with one through five homogeneous tissue levels using Otsu’s method. Realistic noise was then added to each image. The DIR algorithms from MIM and Velocity (Deformable Multipass) were applied to the original phantom images and the processed ones. The resulting deformations were then compared to the known warping. A higher number of tissue levels creates more contrast in an image and enables DIR algorithms to produce more accurate results. For this reason, error (distance between predicted and known deformation) is utilized as a metric to evaluate how many levels are required for a phantom to be a realistic patient proxy. Results: For the prostate image pairs, the mean error decreased from 1–2 tissue levels and remained constant for 3+ levels. The mean error reduction was 39% and 26% for Velocity and MIM respectively. For head and neck, mean error fell similarly through 2 levels and flattened with total reduction of 16% and 49% for Velocity and MIM. For Velocity, 3+ levels produced comparable accuracy as the actual patient images, whereas MIM showed further accuracy improvement. Conclusion: The number of tissue levels needed to produce an accurate patient proxy depends on the algorithm. For Velocity, three levels were enough, whereas five was still insufficient for MIM.

• OSTI ID: 22494114
• Journal Information: Medical Physics, Journal Name: Medical Physics Journal Issue: 6 Vol. 42; ISSN 0094-2405; ISSN MPHYA6
• Country of Publication: United States
• Language: English

Related Subjects

60 APPLIED LIFE SCIENCES
ACCURACY
ALGORITHMS
ANIMAL TISSUES
ERRORS
HEAD
IMAGES
NECK
PATIENTS
PHANTOMS
PROSTATE
QUALITY ASSURANCE
RADIATION DOSES
RADIOTHERAPY