Uncertainty estimation in female pelvic synthetic computed tomography generated from iterative reconstructed cone-beam computed tomography

Abstract

Background and Purpose

Iterative reconstruction (IR) can be used to improve cone-beam computed tomography (CBCT) image quality and from such iterative reconstructed (iCBCT) images, synthetic CT (sCT) images can be generated to enable accurate dose calculations. The aim of this study was to evaluate the uncertainty in generating sCT from iCBCT using vendor-supplied software for online adaptive radiotherapy.

Materials and Methods

Projection data from 20 female pelvic CBCTs were used to reconstruct iCBCT images. The process was repeated with 128 different IR parameter combinations. From these iCBCTs, sCTs were generated. Voxel value variation in the 128 iCBCT and 128 sCT images per patient was quantified by the standard deviation (STD). Additional sub-analysis was performed per parameter category.

Results

Generated sCTs had significantly higher maximum STD-values, median of 438 HU, compared to input iCBCT, median of 198 HU, indicating limited robustness to parameter changes. The highest STD-values of sCTs were within bone and soft-tissue compared to air. Variations in sCT numbers were parameter dependent. Scatter correction produced the highest variance in sCTs (median: 358 HU) despite no visible changes in iCBCTs, whereas total variation regularization resulted in the lowest variance in sCTs (median: 233 HU) despite increased iCBCT blurriness.

Conclusions

Variations in iCBCT reconstruction parameters affected the CT number representation in the sCT. The sCT variance depended on the parameter category, with subtle iCBCT changes leading to significant density alterations in sCT. Therefore, it is recommended to evaluate both iCBCT and sCT generation, especially when updating software or settings.