Using deep learning generated CBCT contours for online dose assessment of prostate SABR treatments.

Conor Sinclair Smith^1,2, Isabelle Gagne², Karl Otto³, Carter Kolbeck³, Joshua Giambattista^3,4, Abraham Alexander⁵, Sonja Murchison⁵, Andrew Pritchard⁵, Erika Chin⁶

¹Department of Physics and Astronomy, University of Victoria, Victoria, British Columbia, Canada.

²Department of Medical Physics, BC Cancer Victoria, Victoria, British Columbia, Canada.

³Radformation Inc, New York, New York, USA.

⁴Allan Blair Cancer Centre, Saskatchewan Cancer Agency, Regina, Saskatchewan, Canada.

⁵Department of Radiation Oncology, BC Cancer Victoria, Victoria, British Columbia, Canada.

⁶Department of Computer Science, Mathematics, Physics, and Statistics, University of British Columbia-Okanagan, Kelowna, British Columbia, Canada.

PubMed PMC DOI PDF

Abstract

Prostate Stereotactic Ablative Body Radiotherapy (SABR) is an ultra-hypofractionated treatment where small setup errors can lead to higher doses to organs at risk (OARs). Although bowel and bladder preparation protocols reduce inter-fraction variability, inconsistent patient adherence still results in OAR variability. At many centers without online adaptive machines, radiation therapists use decis…

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