Beam's-Eye-View Imaging of Liver SBRT With a Novel Multi-Layer Imager

Abstract

Beams-eye view (BEV) imaging during radiation therapy can be used for real-time localization of the treatment target. However, clinical implementation is limited by the poor performance of current electronic portal imaging devices (EPIDs). A novel multilayer imager (MLI), consisting of four stacked conventional flat-panel imagers, was recently shown to have 5.7 times the detective quantum efficiency and nearly 2 times the contrast-to-noise ratio of a conventional EPID. In the current study, we compare the MLI against a single layer imager for the application of fiducial tracking during liver SBRT procedures. The hypothesis is that the MLI will provide more accurate and efficient fiducial tracking.The prototype MLI was installed in the standard MV imager housing on a clinical LINAC, replacing the conventional EPID. The MV imager arm was extended during volumetric modulated arc therapy (VMAT) SBRT treatments for passive data acquisition. Six patients with liver metastases receiving SBRT in 3-5 fractions (900-1200 cGy/fx) were studied. Data was acquired for two fractions of each treatment course, one fraction with the MLI using all 4 layers and one with the MLI using the top layer only. Automatic fiducial localization was performed using a modification of a previously published algorithm. Truth data was derived using external surrogate respiratory traces combined with manual tracking. Results for 4- and 1-layer modes were compared against truth data to determine tracking accuracy and efficiency. Tracking and noise improvements were assessed for any correlation.Between 2771 to 6505 image frames were acquired for each patient, with roughly half of each corresponding to acquisition in 1-layer mode and the other half 4-layer mode. Tracking accuracy with the 1-layer imager returned a root mean square error (RMSE) of 2.1 mm compared to 4-layer RMSE of 1.5 mm, a statistically significant (P < 0.001) improvement of 0.6 mm. Successful tracking efficiency with 4 layers improved to 82.8% versus 58.4% for the 1-layer mode, a relative improvement of 41.8% (P < 0.001). There was a strong correlation (r = 0.913) between the increase in successfully tracked frames and reduction in noise when using the 4-layer mode.Noise reduction and increased MV photon detection efficiency achieved by utilizing a multi-layer MV imager results in improved fiducial tracking for liver SBRT treatments. Future BEV clinical applications may be improved by pursuing similar noise reduction and photon detection enhancement strategies.