The impact of cine EPID image acquisition frame rate on markerless soft-tissue tracking

Abstract

Purpose: Although reduction of the cine electronic portal imaging device (EPID) acquisition frame rate through multiple frame averaging may reduce hardware memory burden and decrease image noise, it can hinder the continuity of soft-tissue motion leading to poor autotracking results. The impact of motion blurring and image noise on the tracking performance was investigated.

Methods: Phantom and patient images were acquired at a frame rate of 12.87 Hz with an amorphous silicon portal imager (AS1000, Varian Medical Systems, Palo Alto, CA). The maximum frame rate of 12.87 Hz is imposed by the EPID. Low frame rate images were obtained by continuous frame averaging. A previously validated tracking algorithm was employed for autotracking. The difference between the programmed and autotracked positions of a Las Vegas phantom moving in the superior-inferior direction defined the tracking error (δ). Motion blurring was assessed by measuring the area change of the circle with the greatest depth. Additionally, lung tumors on 1747 frames acquired at 11 field angles from four radiotherapy patients are manually and automatically tracked with varying frame averaging. δ was defined by the position difference of the two tracking methods. Image noise was defined as the standard deviation of the background intensity. Motion blurring and image noise are correlated with δ using Pearson correlation coefficient (R).

Results: For both phantom and patient studies, the autotracking errors increased at frame rates lower than 4.29 Hz. Above 4.29 Hz, changes in errors were negligible withδ < 1.60 mm. Motion blurring and image noise were observed to increase and decrease with frame averaging, respectively. Motion blurring and tracking errors were significantly correlated for the phantom (R = 0.94) and patient studies (R = 0.72). Moderate to poor correlation was found between image noise and tracking error with R -0.58 and -0.19 for both studies, respectively.

Conclusions: Cine EPID image acquisition at the frame rate of at least 4.29 Hz is recommended. Motion blurring in the images with frame rates below 4.29 Hz can significantly reduce the accuracy of autotracking.

Figure 1

(a) Setup of the Las Vegas phantom on the dynamic motion phantom. EPID images of the Las Vegas phantom acquired at frame rates 12.87 Hz (b), 6.43 Hz (average every two frames) (c), 3.216 Hz (average every four frames) (d), 1.61 Hz (average every eight frames) (e). The circle with the greatest depth is shown within the upper box. Lower box defines the background region.

Figure 2

(a) Error of autotracking as a function of frame rate. (b) Areas of circles as a function of frame rare. (c) Image noise of the Las Vegas Phantom as a function of frame rate.

Figure 3

(a) Tracking errors (δ) as a function of frame rates, (b) relative contrast (η/η_12.87Hz), (c) relative image noise (σ/σ_{12.87 Hz}). The top vertical line of a boxplot represents 95th–99th percentiles of the data. The bottom vertical line is the 5th–25th percentiles. Interquartile range (IQR) of the data is indicated by the width of the boxplot. Asterisks indicate the maximum and minimum differences. Median and mean differences are indicated by bar and square inside the box plots. Diamond shape dots indicate individual imaging sequence.

Figure 4

(a)–(c) An EPID image of sequence #6 displayed with windows/levels. Inner box indicates the observer defined ROI. Outer box approximates the background of ROI (∂ROI).