Investigating rectal toxicity associated dosimetric features with deformable accumulated rectal surface dose maps for cervical cancer radiotherapy

Abstract

Background: Better knowledge of the dose-toxicity relationship is essential for safe dose escalation to improve local control in cervical cancer radiotherapy. The conventional dose-toxicity model is based on the dose volume histogram, which is the parameter lacking spatial dose information. To overcome this limit, we explore a comprehensive rectal dose-toxicity model based on both dose volume histogram and dose map features for accurate radiation toxicity prediction.

Methods: Forty-two cervical cancer patients treated with combined external beam radiotherapy (EBRT) and brachytherapy (BT) were retrospectively studied, including 12 with Grade ≥ 2 rectum toxicity and 30 patients with Grade 0-1 toxicity (non-toxicity patients). The cumulative equivalent 2-Gy rectal surface dose was deformably summed using the deformation vector fields obtained through a recent developed local topology preserved non-rigid point matching algorithm. The cumulative three-dimensional (3D) dose was flattened and mapped to a two-dimensional (2D) plane to obtain the rectum surface dose map (RSDM). The dose volume parameters (DVPs) were calculated from the 3D rectum surface, while the texture features and the dose geometric parameters (DGPs) were extracted from the 2D RSDM. Representative features further computed from DVPs, textures and DGPs by principle component analysis (PCA) and statistical analysis were respectively fed into a support vector machine equipped with a sequential feature selection procedure. The predictive powers of the representative features were compared with the GEC-ESTRO dosimetric parameters D_0.1/1/2cm³.

Results: Satisfactory predictive accuracy of sensitivity 74.75 and 84.75%, specificity 72.67 and 79.87%, and area under the receiver operating characteristic curve (AUC) 0.82 and 0.91 were respectively achieved by the PCA features and statistical significant features, which were superior to the D_0.1/1/2cm³ (AUC 0.71). The relative area in dose levels of 64Gy, 67Gy, 68Gy, 87Gy, 88Gy and 89Gy, perimeters in dose levels of 89Gy, as well as two texture features were ranked as the important factors that were closely correlated with rectal toxicity.

Conclusions: Our extensive experimental results have demonstrated the feasibility of the proposed scheme. A future large patient cohort study is still needed for model validation.

Keywords: Cervical cancer; Deformable registration; Dose accumulation; Machine learning; Rectum toxicity prediction.

Fig. 1

Example of DGPs extracted from the RSDM at a certain dose level

Fig. 2

a Three example rectum TOP-DIRs with small, large and complex deformation. b Boxplots of DC, PE, VVD and HD over the patient groups before and after TOP-DIR. The boxes run from the 25th to 75th percentile; the two ends of the whiskers represent the 10 and 90% percentiles, the horizontal line and the square in the box represent the median and mean values, respectively. The diamonds represent outliers. Significant differences are marked with “*”

Fig. 3

a ROC analysis for different significant features and their combinations via SVM-SFS. b ROC curves comparisons via Z-test (p-values were adjusted by the Bonferroni correction)

Fig. 4

Feature ranking via SVM-SFS (repeated 100 times) on feature combinations of “DVPs + Texture + DGPs” from F_sta