A proton therapy workflow based on CBCT provided clinical indicators similar to those using rCT for patients with lung cancer with considerable anatomic changes.

A comprehensive evaluation of the accuracy of CBCT and deformable registration based dose calculation 4 in lung proton therapy 5 The uncertainties in water equivalent thickness (WET) and accuracy of dose estimation using a virtual CT 30 (vCT), generated from deforming the planning CT (pCT) onto the daily cone-beam CT (CBCT), were 31 comprehensively evaluated in the context of lung malignancies and passive scattering proton therapy. The 32 validation methodology utilized multiple CBCT datasets to generate the vCTs of twenty lung cancer 33 patients. A correction step was applied to the vCTs to account for anatomical modifications that could not 34 be modeled by deformation alone. The CBCT datasets included a regular CBCT (rCBCT) and synthetic 35CBCTs created from the rCBCT and rescan CT (rCT), which minimized the variation in setup between the 36 vCT and the gold-standard image (i.e., rCT). The uncertainty in WET was defined as the voxelwise 37 2 difference in WET between vCT and rCT, and calculated in 3D (planning target volume, PTV) and 2D 1 (distal and proximal surfaces). The uncertainty in WET based dose warping was defined as the difference 2 between the warped dose and a forward dose recalculation on the rCT. The overall root mean square (RMS) 3 uncertainty in WET was 3.6±1.8, 2.2±1.4 and 3.3±1.8 mm for the distal surface, proximal surface and PTV, 4 respectively. For the warped dose, the RMS uncertainty of the voxelwise dose difference was 6±2% of the 5 maximum dose (%mD), using a 20% cut-off. The rCBCT resulted in higher uncertainties due to setup 6 variability with the rCT; the uncertainties reported with the two synthetic CBCTs were similar. The vCT 7 followed by a correction step was found to be an accurate alternative to rCT.

Radiation therapy (RT) of the lung requires deformation analysis. Deformable image registration (DIR) is the fundamental method to quantify deformations for various applications: motion compensation, contour propagation, dose accumulation, etc. DIR is therefore unavoidable in lung RT. DIR algorithms have been studied for decades and are now available both within commercial and academic packages. However, they are complex and have limitations that every user must be aware of before clinical implementation. In this paper, the main applications of DIR for lung RT with their associated uncertainties and their limitations are reviewed.