Dose distribution comparison using image registration principles

Abstract

Radiotherapy relies on accurate dose distribution comparison methods, but current approaches have limitations. This study introduces a novel algorithm based on image registration principles to address these limitations. The algorithm uses a transformation matrix derived from image registration to align an evaluated dose distribution with a reference distribution. This transformation employs multiple steps: detecting keypoints, constructing descriptors, matching keypoints, and estimating an affine transformation matrix. The transformed distribution is then directly comparable to the reference through linear least squares regression. Validation on 174 dose distribution pairs demonstrated robust performance, with bias and precision within clinically acceptable limits. Linearity assessments confirmed consistent behavior across a wide range of dose intensities. Comparisons with gamma analysis showed substantial agreement (Cohen's Kappa: 0.77), while additional metrics highlighted its clinical suitability: precision (0.98), recall (0.95), accuracy (0.94), specificity (0.86), and F1-score (0.96). These results establish the algorithm as a promising complement to gamma analysis, with strong potential for clinical integration. • A novel algorithm for dose distribution comparison is proposed, addressing limitations of current methods. • The algorithm matches isodose contours via affine registration for direct comparison using regression line slopes. • The algorithm was validated using 174 dose distribution pairs, achieving acceptable bias, precision, and linearity • Strong agreement with gamma analysis suggests potential for clinical integration. • Future work will extend the algorithm to 3D dose distribution comparison.