2D-3D registration for brain radiation therapy using a 3D CBCT and a single limited field-of-view 2D kV radiograph

We report results of an intensity-based 2D-3D rigid registration framework for patient positioning and monitoring during brain radiotherapy. We evaluated two intensity-based similarity measures, the Pearson Correlation Coefficient (ICC) and Maximum Likelihood with Gaussian noise (MLC) derived from the statistics of transmission images. A useful image frequency band was identified from the bone-to-no-bone ratio. Validation was performed on gold-standard data consisting of 3D kV CBCT scans and 2D kV radiographs of an anthropomorphic head phantom acquired at 23 different poses with parameter variations along six degrees of freedom. At each pose, a single limited field of view kV radiograph was registered to the reference CBCT. The ground truth was determined from markers affixed to the phantom and visible in the CBCT images. The mean (and standard deviation) of the absolute errors in recovering each of the six transformation parameters along the x, y and Z axes for ICC were ([phi] sub(x): 0.08(0.04)[degrees], [phi] sub(y): 0.10(0.09)[degrees], [phi] sub(z): 0.03(0.03)[degrees], t sub(x): 0.13(0.11) mm, t sub(y): 0.08(0.06) mm and t sub(z): 0.44(0.23) mm. For MLG, the corresponding results were ([phi] sub(x): 0.10(0.04)[degrees], [phi] sub(y): 0.10(0.09)[degrees], [phi] sub(z): 0.05(0.07)[degrees], t sub(x): 0.11(0.13) mm, t sub(y): 0.05(0.05) mm and t sub(z): 0.44(0.31) mm. lt is feasible to accurately estimate all six transformation parameters from a 3D CBCT of the head and a single 2D kV radiograph within an intensity-based registration framework that incorporates the physics of transmission images.