WE-AB-BRA-06: Patient Specific Quantitative Assessment of Deformable Image Registration Quality Applied to Head and Neck Adaptive Therapy




While is it feasible to utilize quantitative techniques such as target registration error for commissioning Deformable Image Registration (DIR), clinical assessment of DIR quality is typically visual and qualitative. We propose a quantitative approach to registration quality assessment, based on measures of deformation quality, numerical robustness, and surrogate measures of alignment accuracy.


Original planning CTs were registered to re-planning CTs for 27 Head and Neck patients using a selection of registration parameters intended to produce a range of DIR results. Registrations were graded by an expert on a scale of 0–5 (from “very poor” to “perfect “) for four broad regions (Skull, Nose- Oral Cavity-Jaw, Neck, Thorax) by visually assessing alignment accuracy and deformation field quality. Grades were assigned for each region and for the overall case. For each registration, ten quantitative measures of registration quality were calculated for each voxel, without user input. These measures consisted of measures of deformation quality, numerical robustness and surrogates for alignment accuracy. Acceptable ranges for each measure were set for each feature based on physical tissue properties and from other examples of good registrations. An average voxel pass-rate was calculated for each region and for the registration overall.


Good correlation (r2 = 0.86) was found between the overall clinical grading and the quantitative registration assessment. Additionally, good correlations were found with the measures of deformation quality (r2 = 0.86–0.91) and robustness (r2 = 0.88). There were no examples of gross anatomical registration failures; consequently, the clinical grades were dominated by the assessment of the deformation field.


Quantitative characterization of clinical registration may assist in clinical assessment of patient-specific registration. While anatomical alignment must still be assessed visually, this approach was able to highlight areas of concerns within the registration, and provide a quantitative assessment without user mark-up.

M Gooding, LC Pickup and T Kadir are employees of Mirada Medical Ltd