Development and performance assessment of an advanced Lucas-Kanade algorithm for dose mapping of cervical cancer...

The aim of this study was to verify the possibility of summing the dose distributions of combined radiotherapeutic treatment of cervical cancer using the extended Lucas-Kanade algorithm for deformable image registration.

First, a deformable registration of planning computed tomography images for the external radiotherapy and brachytherapy treatment of 10 patients with different parameter settings of the Lucas-Kanade algorithm was performed. By evaluating the registered data using landmarks distance, root mean square error of Hounsfield units and 2D gamma analysis, the optimal parameter values were found. Next, with another group of 10 patients, the accuracy of the dose mapping of the optimized Lucas-Kanade algorithm was assessed and compared with Horn-Schunck and modified Demons algorithms using dose differences at landmarks.

The best results of the Lucas-Kanade deformable registration were achieved for two pyramid levels in combination with a window size of 3 voxels. With this registration setting, the average landmarks distance was 2.35 mm, the RMSE was the smallest and the average gamma score reached a value of 86.7%. The mean dose difference at the landmarks after mapping the external radiotherapy and brachytherapy dose distributions was 1.33 Gy. A statistically significant difference was observed on comparing the Lucas-Kanade method with the Horn-Schunck and Demons algorithms, where after the deformable registration, the average difference in dose was 1.60 Gy (P-value: 0.0055) and 1.69 Gy (P-value: 0.0012), respectively.

Lucas-Kanade deformable registration can lead to a more accurate model of dose accumulation and provide a more realistic idea of the dose distribution.