Stochastic triangulation for prostate positioning during radiotherapy using short CBCT arcs

• Published in: Radiotherapy and oncology 2013-02, Vol.106 (2), p.241-249
• Main Authors: Hoegele, Wolfgang, Loeschel, Rainer, Dobler, Barbara, Koelbl, Oliver, Beard, Clair, Zygmanski, Piotr
• Format: Article
• Language: English
• Subjects: Cone-Beam Computed Tomography - methods; Hematology, Oncology and Palliative Medicine; Humans; Image Processing, Computer-Assisted; Male; Maximum A Posteriori estimation; Patient Positioning; Prostatic Neoplasms - radiotherapy; Radiotherapy, Image-Guided - methods; Setup error; Short arc; Stochastic Processes; Stochastic triangulation
• ISSN: 0167-8140; 1879-0887
• DOI: 10.1016/j.radonc.2013.01.005

Abstract Background and purpose Fast and reliable tumor localization is an important part of today’s radiotherapy utilizing new delivery techniques. This proof-of-principle study demonstrates the use of a method called herein ‘stochastic triangulation’ for this purpose. Stochastic triangulation uses very short imaging arcs and a few projections. Materials and methods A stochastic Maximum A Posteriori (MAP) estimator is proposed based on an uncertainty-driven model of the acquisition geometry and inter-/intra-fractional deformable anatomy. The application of this method was designed to use the available linac-mounted cone-beam computed tomography (CBCT) and/or electronic portal imaging devices (EPID) for the patient setup based on short imaging arcs. For the proof-of-principle clinical demonstration, the MAP estimator was applied to 5 CBCT scans of a prostate cancer patient with 2 implanted gold markers. Estimation was performed for several (18) very short imaging arcs of 5° with 10 projections resulting in 90 estimations. Results Short-arc stochastic triangulation led to residual radial errors compared to manual inspection with a mean value of 1.4 mm and a standard deviation of 0.9 mm (median 1.2 mm, maximum 3.8 mm) averaged over imaging directions all around the patient. Furthermore, abrupt intra-fractional motion of up to 10 mm resulted in radial errors with a mean value of 1.8 mm and a standard deviation of 1.1 mm (median 1.5 mm, maximum 5.6 mm). Slow periodic intra-fractional motions in the range of 12 mm resulted in radial errors with a mean value of 1.8 mm and a standard deviation of 1.1 mm (median 1.6 mm, maximum 4.7 mm). Conclusion Based on this study, the proposed stochastic method is fast, robust and can be used for inter- as well as intra-fractional target localization using current CBCT units.