title: Complexity and accuracy of image registration methods in SPECT-guided radiation therapy.
abstract: The use of functional imaging in radiotherapy treatment (RT) planning requires accurate co-registration of functional imaging scans to CT scans. We evaluated six methods of image registration for use in SPECT-guided radiotherapy treatment planning. Methods varied in complexity from 3D affine transform based on control points to diffeomorphic demons and level set non-rigid registration. Ten lung cancer patients underwent perfusion SPECT-scans prior to their radiotherapy. CT images from a hybrid SPECT/CT scanner were registered to a planning CT, and then the same transformation was applied to the SPECT images. According to registration evaluation measures computed based on the intensity difference between the registered CT images or based on target registration error, non-rigid registrations provided a higher degree of accuracy than rigid methods. However, due to the irregularities in some of the obtained deformation fields, warping the SPECT using these fields may result in unacceptable changes to the SPECT intensity distribution that would preclude use in RT planning. Moreover, the differences between intensity histograms in the original and registered SPECT image sets were the largest for diffeomorphic demons and level set methods. In conclusion, the use of intensity-based validation measures alone is not sufficient for SPECT/CT registration for RTTP. It was also found that the proper evaluation of image registration requires the use of several accuracy metrics.
authors.affiliation: Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC, V6T 1Z1, Canada. lyin@bccancer.bc.ca
authors.forename: L S
authors.initials: LS
authors.lastname: Yin
authors.forename: L
authors.initials: L
authors.lastname: Tang
authors.forename: G
authors.initials: G
authors.lastname: Hamarneh
authors.forename: B
authors.initials: B
authors.lastname: Gill
authors.forename: A
authors.initials: A
authors.lastname: Celler
authors.forename: S
authors.initials: S
authors.lastname: Shcherbinin
authors.forename: T F
authors.initials: TF
authors.lastname: Fua
authors.forename: A
authors.initials: A
authors.lastname: Thompson
authors.forename: M
authors.initials: M
authors.lastname: Liu
authors.forename: C
authors.initials: C
authors.lastname: Duzenli
authors.forename: F
authors.initials: F
authors.lastname: Sheehan
authors.forename: V
authors.initials: V
authors.lastname: Moiseenko
mesh_terms: D000328:Adult; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008175:Lung Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy; D008297:Male; D008875:Middle Aged; D055420:Perfusion Imaging / Q000379:methods; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D011881:Radiotherapy, Computer-Assisted / Q000379:methods*; D015899:Tomography, Emission-Computed, Single-Photon / Q000379:methods*