Support-based extended field-of-view CT reconstruction for radiation treatment planning

Abstract

In radiation treatment planning (RTP), CT reconstruction that combats projection truncation artifacts induced by the patient being positioned partially outside the scan field-of-view (FOV) needs to maintain high geometric and Hounsfield Unit (HU) accuracy outside the scan FOV. A new image reconstruction method has been proposed for clinical helical CT simulation scans. This method generates support images using the Discrete Algebraic Reconstruction Technique to accurately estimate patient contours outside the scan FOV and then uses support images to guide the projection extension. The proposed method improved geometric accuracy in objects outside the scan FOV compared to a more conventional method and kept the geometric distortion within 5 mm under very severe truncation. It also demonstrated HU accuracy in objects outside the scan FOV within 2.5% for a variety of soft tissues and 15% for bone tissues on a typical electron density phantom. Images of three radiotherapy patient cases reconstructed with the proposed method exhibited clearly defined, naturally looking patient contours, including the recovery of skinfold outside the scan FOV. The proposed method shows the potential for providing clinically desirable extended FOV images for a variety of patient setups in RTP.