ABSTRACT
Objective: To investigate a dual-energy X-ray fluoroscopy imaging method to acquire a high-and low-energy X-ray image sequence within a breathing cycle, so as to obtain soft tissue image through an improved dual-energy image subtraction algorithm to improve tumor visibility for marker-less lung tumor tracking in image-guided radiotherapy. Methods: A dual-energy X-ray fluoroscopy imaging system with a C-arm rotating mechanical structure and a high-low energy fast switching mechanism was designed. A sequence of high-and low-energy X-ray image pairs of 9 or 10 breathing phase within a breathing cycle were acquired from 4 different projection directions. For a high-and low-energy image pair in the same phase, a soft tissue image was obtained by removing the skeleton through an optimized weighted logarithmic subtraction algorithm. The best soft tissue image was automatically determined by using CNR as the image quality evaluation parameter in the subtraction algorithm. Twenty patients with lung tumor were collected, and their data were analyzed to evaluate the improvement of tumor visibility in soft tissue subtraction images. Results: In the projection directions of 0°, 45°, 90° and 135°, 198, 196, 198 and 198 high and low energy image pairs were collected, respectively. The visibility images of tumor were 198, 38, 69 and 49 pairs, respectively. On soft tissue images after removing skeleton from high and low energy image pairs by automatic subtraction algorithm, the visibility images of tumors were 198, 108, 149 and 159, respectively. Conclusion: The above mentioned dual-energy X-ray fluoroscopy method can be used to acquire real-time high-and low-energy X-ray image sequences of respiratory cycle, therefore obtain soft tissue subtraction images and significantly improve the visibility of lung tumors.