Delta-radiomics features during radiotherapy improve the prediction of late xerostomia

Lisanne V. van Dijk*, Johannes A. Langendijk, Tian-Tian Zhai, Thea A. Vedelaar, Walter Noordzij, Roel J. H. M. Steenbakkers, Nanna M. Sijtsema

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

51 Citations (Scopus)
192 Downloads (Pure)

Abstract

The response of the major salivary glands, the parotid glands, to radiation dose is patient-specific. This study was designed to investigate whether parotid gland changes seen in weekly CT during treatment, quantified by delta-radiomics features (Delta features), could improve the prediction of moderate-to-severe xerostomia at 12 months after radiotherapy (Xer(12m)). Parotid gland Delta features were extracted from in total 68 planning and 340 weekly CTs, representing geometric, intensity and texture characteristics. Bootstrapped forward variable selection was performed to identify the best predictors of Xer(12m). The predictive contribution of the resulting Delta features to a pre-treatment reference model, based on contralateral parotid gland mean dose and baseline xerostomia scores (Xer(baseline)) only, was evaluated. Xer(12m) was reported by 26 (38%) of the 68 patients included. The most predictive.feature was the contralateral parotid gland surface change, which was significantly associated with Xer(12m) for all weeks (p <0.04), but performed best for week 3 (Delta PG-surface(w3); p <0.001). Moreover, Delta PG-surface(w3) showed a significant predictive contribution in addition to the pre-treatment reference model (likelihood-ratio test; p = 0.003), resulting in a significantly better model performance (AUC(train) = 0.92; AUC(test) = 0.93) compared to that of the pre-treatment model (AUC(train) = 0.82; AUC(test) = 0.82). These results suggest that mid-treatment parotid gland changes substantially improve the prediction of late radiation-induced xerostomia.

Original languageEnglish
Article number12483
Number of pages8
JournalScientific Reports
Volume9
Issue number1
DOIs
Publication statusPublished - 28-Aug-2019

Keywords

  • INTENSITY-MODULATED RADIOTHERAPY
  • CT-BASED DELINEATION
  • NECK-CANCER
  • SUBMANDIBULAR-GLANDS
  • TEXTURAL FEATURES
  • PAROTID-GLAND
  • HEAD
  • MODEL
  • ORGANS
  • RISK

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