Comparison of User-Directed and Automatic Mapping of the Planned Isocenter to Treatment Space for Prostate IGRT | Zendy

Z Xu | Zendy; Ronald C. Chen | Zendy; Andrew Z. Wang | Zendy; Andrea Kress | Zendy; Mark Foskey | Zendy; An Qin | Zendy; Timothy J. Cullip | Zendy; Gregg Tracton | Zendy; S Chang | Zendy; Joel E. Tepper | Zendy; Di Yan | Zendy; Edward L. Chaney | Zendy

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Comparison of User-Directed and Automatic Mapping of the Planned Isocenter to Treatment Space for Prostate IGRT

Author(s) -

Z Xu,

Ronald C. Chen,

Andrew Z. Wang,

Andrea Kress,

Mark Foskey,

An Qin,

Timothy J. Cullip,

Gregg Tracton,

S Chang,

Joel E. Tepper,

Di Yan,

Edward L. Chaney

Publication year - 2013

Publication title -

international journal of biomedical imaging

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.626

H-Index - 41

eISSN - 1687-4196

pISSN - 1687-4188

DOI - 10.1155/2013/892152

Subject(s) - image guided radiation therapy , isocenter , outlier , computer science , algorithm , prostate cancer , artificial intelligence , protocol (science) , nuclear medicine , radiation therapy , medicine , medical imaging , mathematics , radiology , cancer , alternative medicine , pathology

Image-guided radiotherapy (IGRT), adaptive radiotherapy (ART), and online reoptimization rely on accurate mapping of the radiation beam isocenter(s) from planning to treatment space. This mapping involves rigid and/or nonrigid registration of planning (pCT) and intratreatment (tCT) CT images. The purpose of this study was to retrospectively compare a fully automatic approach, including a non-rigid step, against a user-directed rigid method implemented in a clinical IGRT protocol for prostate cancer. Isocenters resulting from automatic and clinical mappings were compared to reference isocenters carefully determined in each tCT. Comparison was based on displacements from the reference isocenters and prostate dose-volume histograms (DVHs). Ten patients with a total of 243 tCTs were investigated. Fully automatic registration was found to be as accurate as the clinical protocol but more precise for all patients. The average of the unsigned x, y, and z offsets and the standard deviations ( σ ) of the signed offsets computed over all images were (avg. ± σ (mm)): 1.1 ± 1.4, 1.8 ± 2.3, 2.5 ± 3.5 for the clinical protocol and 0.6 ± 0.8, 1.1 ± 1.5 and 1.1 ± 1.4 for the automatic method. No failures or outliers from automatic mapping were observed, while 8 outliers occurred for the clinical protocol.

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