In this work we develop techniques that can derive the tumor position from external respiratory surrogates (abdominal surface motion) through periodically updated internal/external correlation. A simple linear function is used to express the correlation between the tumor and surrogate motion. The function parameters are established during a patient setup session with the tumor and surrogate positions simultaneously measured at a 30 Hz rate. During treatment, the surrogate position, constantly acquired at 30 Hz, is used to derive the tumor position. Occasionally, a pair of radiographic images is acquired to enable the updating of the linear correlation function. Four update methods, two aggressive and two conservative, are investigated: (A1) shift line through the update point; (A2) re-fit line through the update point; (C1) re-fit line with extra weight to the update point; (C2) minimize the distances to the update point and previous line fit point. In the present study of eight lung cancer patients, tumor and external surrogate motion demonstrate a high degree of linear correlation which changes dynamically over time. It was found that occasionally updating the correlation function leads to more accurate predictions than using external surrogates alone. In the case of high imaging rates during treatment (greater than 2 Hz) the aggressive update methods (A1 and A2) are more accurate than the conservative ones (C1 and C2). The opposite is observed in the case of low imaging rates.
ASJC Scopus subject areas
- Radiological and Ultrasound Technology
- Radiology Nuclear Medicine and imaging