Purpose Megavoltage computed tomographic (MVCT) imaging has been widely used for the 3-dimensional (3-D) setup of patients treated with helical tomotherapy (HT). One drawback of MVCT is its very long imaging time, the result of slow couch speeds of approximately 1 mm/s, which can be difficult for the patient to tolerate. We sought to develop an MVCT imaging method allowing faster couch speeds and to assess its accuracy for image guidance for HT. Methods and Materials Three cadavers were scanned 4 times with couch speeds of 1, 2, 3, and 4 mm/s. The resulting MVCT images were reconstructed using an iterative reconstruction (IR) algorithm with a penalty term of total variation and with a conventional filtered back projection (FBP) algorithm. The MVCT images were registered with kilovoltage CT images, and the registration errors from the 2 reconstruction algorithms were compared. This fast MVCT imaging was tested in 3 cases of total marrow irradiation as a clinical trial. Results The 3-D registration errors of the MVCT images reconstructed with the IR algorithm were smaller than the errors of images reconstructed with the FBP algorithm at fast couch speeds (2, 3, 4 mm/s). The scan time and imaging dose at a speed of 4 mm/s were reduced to 30% of those from a conventional coarse mode scan. For the patient imaging, faster MVCT (3 mm/s couch speed) scanning reduced the imaging time and still generated images useful for anatomic registration. Conclusions Fast MVCT with the IR algorithm is clinically feasible for large 3-D target localization, which may reduce the overall time for the treatment procedure. This technique may also be useful for calculating daily dose distributions or organ motion analyses in HT treatment over a wide area. Automated integration of this imaging is at least needed to further assess its clinical benefits.
|Original language||English (US)|
|Number of pages||8|
|Journal||International Journal of Radiation Oncology Biology Physics|
|State||Published - Nov 1 2016|
Bibliographical notePublisher Copyright:
© 2016 Elsevier Inc.