Dosiomics-based detection of dose distribution variations in helical tomotherapy for prostate cancer patients: influence of treatment plan parameters.

Abstract

The stability of dosiomics features (DFs) and dose-volume histogram (DVH) parameters for detecting disparities in helical tomotherapy planned dose distributions was assessed. Treatment plans of 18 prostate patients were recalculated using the followings: field width (WF) (2.5 vs. 5), pitch factor (PF) (0.433 vs. 0.444), and modulation factor (MF) (2.5 vs. 3). From each of the eight plans per patient, ninety-three original and 744 wavelet-based DFs were extracted, using 3D-Slicer software, across six regions including: target volume (PTV), pelvic lymph nodes (PTV-LN), PTV + PTV-LN (PTV-All), one cm rind around PTV-All (PTV-Ring), rectum, and bladder. For the resulting DFs and DVH parameters, the coefficient of variation (CV) was calculated, and using hierarchical clustering, the features were classified into low/high variability. The significance of parameters on instability was analyzed by a three-way analysis of variance. All DF's were stable in PTV, PTV-LN, and PTV-Ring (average CV ( $\overline{\mathrm{CV}})$  ≤ 0.36). Only one feature in the bladder ( $\overline{\mathrm{CV}}$  = 0.9), rectum ( $\overline{\mathrm{CV}}$  = 0.4), and PTV-All ( $\overline{\mathrm{CV}}$  = 0.37) were considered unstable due to change in MF in the bladder and WF in the PTV-All. The value of $\overline{\mathrm{CV}}$ for the wavelet features was much higher than that for the original features. Out of 225 unstable wavelet features, 84 features had $\overline{\mathrm{CV}}$  ≥ 1. The CVs for all the DVHs remained very small ( $\overline{\mathrm{CV}}$ < 0.06). This study highlights that the sensitivity of DFs to changes in tomotherapy planning parameters is influenced by the region and the DFs, particularly wavelet features, surpassing the effectiveness of DVHs.