An on-line replanning method for head and neck adaptive radiotherapy. Med Phys 2009 Oct;36(10):4776-90
Date
11/26/2009Pubmed ID
19928108DOI
10.1118/1.3215532Scopus ID
2-s2.0-70349653543 (requires institutional sign-in at Scopus site) 58 CitationsAbstract
Daily setup for head and neck (HN) radiotherapy (RT) can vary randomly due to neck rotation and anatomy change. These differences cannot be totally corrected by the current practice of image guided RT with translational repositioning. The authors present a novel rapid correction scheme that can be used on-line to correct both interfractional setup variation and anatomy change for HN RT. The scheme consists of two major steps: (1) Segment aperture morphing (SAM) and (2) segment weight optimization (SWO). SAM is accomplished by applying the spatial relationship between the apertures and the contours of the planning target and organs at risk (OARs) to the new target and OAR contours. The new target contours are transferred from planning target contours to the CT of the day by means of deformable registration (MIMVISTA). The dose distribution for each new aperture was generated using a planning system with a fast dose engine and hardware and was input into a newly developed SWO package using fast sequential quadratic programming. The entire scheme was tested based on the daily CT images acquired for representative HN IMRT cases treated with a linac and CT-on-Rails combo. It was found that the target coverage and/or OAR sparing was degraded based on the CT of the day with the current standard repositioning from rigid registration. This degradation can be corrected by the SAM/SWO scheme. The target coverage and OAR sparing for the SAM/SWO plans were found to be equivalent to the original plan. The SAM/SWO process took 5-8 min for the head and neck cases studied. The proposed aperture morphing with weight optimization is an effective on-line approach for correcting interfractional patient setup and anatomic changes for head and neck cancer radiotherapy.
Author List
Ahunbay EE, Peng C, Godley A, Schultz C, Li XAAuthors
Ergun Ahunbay PhD Professor in the Radiation Oncology department at Medical College of WisconsinChristopher J. Schultz MD Professor in the Radiation Oncology department at Medical College of Wisconsin
MESH terms used to index this publication - Major topics in bold
Head and Neck NeoplasmsHumans
Online Systems
Radiographic Image Interpretation, Computer-Assisted
Radiometry
Radiotherapy Dosage
Radiotherapy Planning, Computer-Assisted
Radiotherapy, Computer-Assisted
Radiotherapy, Conformal
Tomography, X-Ray Computed