Megavoltage image-based dynamic multileaf collimator tracking of a NiTi stent in porcine lungs on a linear...

To investigate the accuracy and potential limitations of MV image-based dynamic multileaf collimator (DMLC) tracking in a porcine model on a linear accelerator.

A thermo-expandable NiTi stent designed for kilovoltage (kV) X-ray visualization of lung lesions was inserted into the bronchia of three anaesthetized Göttingen minipigs. A four-dimensional computed tomography scan was used for planning a five-field conformal treatment with circular multileaf collimator (MLC) apertures. A 22.5 Gy single fraction treatment was delivered to the pigs. The peak-to-peak stent motion was 3 to 8 mm, with breathing periods of 1.2 to 4 s. Before treatment, X-ray images were used for image-guided setup based on the stent. During treatment delivery, continuous megavoltage (MV) portal images were acquired at 7.5 Hz. The stent was segmented in the images and used for continuous adaptation of the MLC aperture. Offline, the tracking error in beam's eye view of the treatment beam was calculated for each MV image as the difference between the MLC aperture center and the segmented stent position. The standard deviations of the systematic error Σ and the random error σ were determined and compared with the would-be errors for a nontracking treatment with pretreatment image-guided setup.

Reliable stent segmentation was obtained for 11 of 15 fields. Segmentation failures occurred when image contrast was dominated by overlapping anatomical structures (ribs, diaphragm) rather than by the stent, which was designed for kV rather than MV X-ray visibility. For the 11 fields with reliable segmentation, Σ was 0.5 mm/0.4 mm in the two imager directions, whereas σ was 0.5 mm/1.1 mm. Without tracking, Σ and σ would have been 1.7 mm/1.4 mm and 0.8 mm/1.4 mm, respectively.

For the first time, in vivo DMLC tracking has been demonstrated on a linear accelerator showing the potential for improved targeting accuracy. The study mimicked the envisioned patient workflow of future patient treatments. Clinical implementation of MV image-based tracking would require markers designed for MV visibility.