Poster Poster Program Therapy Physics

Deformable Surface Registration for Automated Patient Positioning In Head and Neck Radiation Therapy

Abstract
Purpose

Conventional iterative closest point (ICP) algorithms capable of 3D surface registration perform best with non-deformable surfaces. Such methods are not efficient in head and neck (HN) RT, where one part of the surface is rigid (head) while another part is deformable (neck). This work seeks to develop a novel ICP algorithm capable of decomposing a surface into rigid and non-region regions, scoring these surfaces with different metrics that take into account biokinematic motion constraints of the HN, and outputting efficient patient motion corrections.

Methods

A novel ICP algorithm was developed to enable surface registration across semi-deformable surfaces, in which points on a surface are permitted to move relative to one another. This approach differs from conventional ICP algorithms, which assume rigid, non-deformable surfaces and cannot account for naturally occurring anatomical deformations. The algorithm was applied to automation of patient positioning in head and neck radiation therapy, where registration must account for skin stretching and soft-tissue deformation in regions such as the neck. This surface registration algorithm is used in concert with a biokinematic model of the HN, discussed in a separate work. Accuracy was quantified using the root mean square (RMS) distance between registered surfaces. Patient position can be automatically corrected using a robotic head positioning system utilizing six linear actuators capable of rotating and translating the head along six degrees of freedom.

Results

The algorithm demonstrated accurate registration of patient positioning while accounting for clinically relevant surface deformations. Using a digital phantom with representative head and neck surfaces, the algorithm successfully matched surfaces across a range of initial misalignments. Registration converged to an RMS distance of <1mm.

Conclusion

This work demonstrates the feasibility of a semi-deformable ICP algorithm for registration of semi-deformable anatomical surfaces, such as 3D HN patient surface data, with potential application to automated patient positioning.

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