Fifty-sixth annual meeting of the American association of physicists in medicine
TU-C-BRE-11: 3D EPID-Based in Vivo Dosimetry: A Major Step Forward Towards Optimal Quality and Safety in Radiation Oncology Practice
To develop a 3D in vivo dosimetry method that is able to substitute pre-treatment verification in an efficient way, and to terminate treatment delivery if the online measured 3D dose distribution deviates too much from the predicted dose distribution.
A back-projection algorithm has been further developed and implemented to enable automatic 3D in vivo dose verification of IMRT/VMAT treatments using a-Si EPIDs. New software tools were clinically introduced to allow automated image acquisition, to periodically inspect the record-and-verify database, and to automatically run the EPID dosimetry software. The comparison of the EPID-reconstructed and planned dose distribution is done offline to raise automatically alerts and to schedule actions when deviations are detected. Furthermore, a software package for online dose reconstruction was also developed. The RMS of the difference between the cumulative planned and reconstructed 3D dose distributions was used for triggering a halt of a linac.
The implementation of fully automated 3D EPID-based in vivo dosimetry was able to replace pre-treatment verification for more than 90% of the patient treatments. The process has been fully automated and integrated in our clinical workflow where over 3,500 IMRT/VMAT treatments are verified each year. By optimizing the dose reconstruction algorithm and the I/O performance, the delivered 3D dose distribution is verified in less than 200 ms per portal image, which includes the comparison between the reconstructed and planned dose distribution. In this way it was possible to generate a trigger that can stop the irradiation at less than 20 cGy after introducing large delivery errors.
The automatic offline solution facilitated the large scale clinical implementation of 3D EPID-based in vivo dose verification of IMRT/VMAT treatments; the online approach has been successfully tested for various severe delivery errors.