Semiautomated motion correction of XXXX in lung CT-perfusion studies.

@entity1 @entity2 @entity5
RATIONALE AND OBJECTIVES: To compare the relative performance of one-dimensional (1D) manual, rigid-translational, and nonrigid registration techniques to correct misalignment of @entity2 anatomy acquired from computed tomography perfusion (CTp) datasets. MATERIALS AND METHODS: Twenty-five datasets in @entity1 with @entity2 who had undergone a CTp protocol were evaluated. Each dataset consisted of one reference CT image from an initial cine slab and six subsequent breathhold helical volumes (16-row multi-detector CT), acquired during intravenous contrast administration. Each helical volume was registered to the reference image using two semiautomated intensity-based registration methods (rigid-translational and nonrigid), and 1D manual registration (the only registration method available in the relevant application software). The performance of each technique to align @entity5 regions was assessed quantitatively (percent overlap and distance of center of mass), and by a visual validation study (using a 5-point scale). The registration methods were statistically compared using linear mixed and ordinal probit regression models. RESULTS: Quantitatively, @entity5 alignment with the nonrigid method compared to rigid-translation was borderline significant, which in turn was significantly better than the 1D manual method: average (   SD) percent overlap, 91.8    2.3%, 87.7    5.5%, and 77.6    5.9%, respectively; and average (   SD) DCOM, 0.41    0.16 mm, 1.08    1.13 mm, and 2.99    2.93 mm, respectively (all P < .0001). Visual validation confirmed these findings. CONCLUSION: Semiautomated registration methods achieved superior @entity2 compared to the 1D manual method. This will hopefully translate into more reliable CTp analyses.
