Purpose: To investigate the dosimetric advantages of an image guided replanning strategy utilizing on‐board CBCTs for VMAT plans. An intensity corrected grey‐scale based CBCT to planning CT deformable image registration algorithm, combined with an intra‐fractional morphing aperture optimization algorithm (ICDIR‐MAO), is dosimtrically evaluated for head and neck cancer patients. Methods: : Head and neck VMAT plans were retrospectively adapted using the ICDIR‐MAO algorithm. Patient CBCT and CT images are deformably registered with an intensity corrected demons based deformable image registration algorithm. The deformation vector field is applied to the PTV on the structure set to obtain a deformed PTV. Digitally reconstructed radiographs of the original PTV and deformed PTV are created for each treatment angle. MLC positions are generated to contour both PTVs and a ratio of original vs. deformed MLC positions that outline the PTV beam's eye view contour is applied to each angle of the planned MLC sequence. The deformed image is then sliced up and reformatted back into dicom files, with the associated metadata. The deformation vector field is added to the structure set at every point and a new dicom structure set is created. The new mlc sequences are reformatted back into dicom plans. All three dicom files are imported back into eclipse, and dose is re‐calculated on the deformed plan, deformed image set, and associated deformed structures. Results: The mean and maximum dose ratios for the OARS were lowered for all cases. The mean dose for the PTV70Gy, PTV60Gy, and PTV54Gy was the same or better for the deformed plans. The dosimetric improvement was proportional to the contour volume overlap between the deformed CT and the original CT. Conclusion: : ICDIR‐MAO for adaptive VMAT replanning improves the dosimetric quality for head and neck patients. This research is supported by CPRIT Individual Investigator Award RP110329.
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging