Purpose: To develop a three‐dimensional (3‐D) volumetric registration algorithm to estimate the intra‐fractional lung tumor motion between respiratory phases for improving the accuracy of radiotherapy treatment. Methods: The 3‐D thoracic CT volumes (512×512×160 voxels, with dimensions 0.97×0.97×2.5 mm3) in different respiratory phases were acquired on a General Electric Optima T580 scanner in cine mode. As a preprocess, a bicubic interpolation was used to interpolate the original 3‐D volumes along the cephalo‐caudal axis to volumes of size 512×512×400 voxels, with dimensions 0.97×0.97×1 mm3. In each respiratory phase, a sub‐volume covering the tumor was roughly specified manually. A 3‐D phase correlation of two sub‐volumes was computed by using the 3‐D inverse Fourier transformation of the normalized cross power spectrum of two sub‐volumes. The 3‐D displacements along three axes were estimated by finding the location of the highest peak in the 3‐D phase correlation. Results: Experiments were conducted on an artificial 4‐D CT data set and three clinical 4‐D CT data sets. Experimental results shown that the proposed algorithm was capable of estimating the tumor motion between respiratory phases with a high‐accuracy (mean square error <1 mm). Conclusions: This work extended the conventional image registration techniques from 2‐D to 3‐D for tumor motion estimation. This work indicates a potential for significant accuracy improvement in radiotherapy treatment planning. The high‐accurate 3‐D tumor motion information provides a reliable basis for expanding a clinical target volume (CTV) to a planning target volume (PTV) to incorporate the intra‐fractional tumor motion.
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging