T Pan*, A Thomas, D Luo, UT MD Anderson Cancer Center, Houston, TX

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  T Pan

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PO-GePV-M-94 (Sunday, 7/10/2022)   [Eastern Time (GMT-4)]

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Purpose: We developed an automated data-driven gated (DDG) CT based on the lung CT numbers and body outlines of the cine CT images for radiotherapy treatment planning (RTP).

Methods: The lung region was calculated by thresholding the lungs and removing the air space and imaging table. The cine CT images with the largest and smallest average HU in the lung region become the end-expiratory (EE) and end-inspiratory (EI) images, respectively. For the image slices without any lung region, the largest and smallest body outline contours are selected for the EE and EI phases, respectively. Finally, a consistency check is conducted to ensure the selection of EE or EI phase images across the slice locations acquired at the same time are together. The new DDG CT was compared to two commercial CT gating methods of D4D and 4D CT in 38 patient data sets with respect to selection of EI and EE respiratory phases and image artifacts.

Results: In the EE phase, the images selected by DDG CT and 4D CT were identical 62.5±21.6% of the time, while DDG CT and D4D CT were 6.5±9.7%, and 4D CT and D4D CT were 8.6±12.2%. These differences were significant (p<0.0001). In the EI phase, the images selected by DDG CT and 4D CT were identical 68.2±18.9%, DDG CT and D4D CT 63.9±18.8%, and 4D CT and D4D CT 61.2±19.8%. These differences were not significant. DDG CT was better than D4D or 4D CT in appropriate selection of the EE and EI phases. D4D CT was found to reverse the EE and EI phases or not select the correct images in some cases.

Conclusion: A new automatic DDG CT was developed for RTP without any hardware gating. The new DDG CT provides the benefits of 4D CT without the need for external hardware gating.

Funding Support, Disclosures, and Conflict of Interest: Tinsu Pan is a consultant of Bracco Medical Systems.

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