Abstract

In the field of extra-cranial radiotherapy, several inaccuracies can make the application of frameless stereotactic localization techniques error-prone. When optical tracking systems based on surface fiducials are used, inter- and intra-fractional uncertainties in marker three-dimensional (3D) detection may lead to inexact tumor position estimation, resulting in erroneous patient setup. This is due to the fact that external fiducials misdetection results in deformation effects that are poorly handled in a rigid-body approach. In this work, the performance of two frameless stereotactic localization algorithms for 3D tumor position reconstruction in extra-cranial radiotherapy has been specifically tested. Two strategies, unweighted versus weighted, for stereotactic tumor localization were examined by exploiting data coming from 46 patients treated for extra-cranial lesions. Measured isocenter displacements and rotations were combined to define isocentric procedures, featuring 6 degrees of freedom, for correcting patient alignment (isocentric positioning correction). The sensitivity of the algorithms to uncertainties in the 3D localization of fiducials was investigated by means of 184 numerical simulations. The performance of the implemented isocentric positioning correction was compared to conventional point-based registration. The isocentric positioning correction algorithm was tested on a clinical dataset of inter-fractional and intra-fractional setup errors, which was collected by means of an optical tracker on the same group of patients. The weighted strategy exhibited a lower sensitivity to fiducial localization errors in simulated misalignments than those of the unweighted strategy. Isocenter 3D displacements provided by the weighted strategy were consistently smaller than those featured by the unweighted strategy. The peak decrease in median and quartile values of isocenter 3D displacements were 1.4 and 2.7 mm, respectively. Concerning clinical data, the weighted strategy isocentric positioning correction provided the reduction of fiducial registration errors, featuring up to 61.7% decrease in median values (versus 46.8% for the unweighted strategy) of initial displacements. The weighted strategy proved high performance in minimizing the effects of fiducial localization errors, showing a great potential in improving patient setup. The clinical data analysis revealed that the application of a robust reconstruction algorithm may provide high-quality results in patient setup verification, by properly managing external fiducials localization errors.

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