A segmentation and point-matching enhanced efficient deformable image registration method for dose accumulation...

Area of Science:

• Medical Imaging
• Radiotherapy Physics
• Computational Anatomy

Background:

• Deformable image registration (DIR) of fractional high-dose-rate (HDR) CT images is complicated by brachytherapy applicators.
• Applicator-induced deformation vector fields (DVF) can cause significant errors in dose mapping.
• Accurate dose accumulation across treatment fractions is crucial for effective radiotherapy.

Purpose of the Study:

• To develop a novel segmentation and point-matching enhanced efficient DIR (SPEED) scheme.
• To address challenges in DIR caused by applicator artifacts in HDR CT images.
• To improve dose accumulation accuracy in brachytherapy HDR treatments.

Main Methods:

• A semi-automatic seed point generation and random walks algorithm to segment and remove the applicator region (AR), creating AR cavities.
• A feature-based thin-plate-spline robust point matching algorithm for AR cavity surface point registration.
• B-spline approximation for initial DVF estimation, followed by Demons-based DIR for final DVF calculation and dose mapping.

Main Results:

• The SPEED scheme effectively segments and removes applicator regions, leaving cavities in HDR CT images.
• Accurate point matching and DVF estimation were achieved using the proposed methods.
• Quantitative assessment on nine clinical HDR cases demonstrated the accuracy of SPEED in registering images and accumulating doses.

Conclusions:

• The SPEED scheme successfully suppresses applicator artifacts in DIR for HDR CT images.
• It enables accurate registration of interfractional HDR CT images.
• SPEED facilitates precise dose accumulation by accurately deforming and mapping doses between fractions.