Predicting survival and local control after radiochemotherapy in locally advanced head and neck cancer by means of computed tomography based radiomics

Research output: Contribution to journalArticlepeer-review

Abstract

PURPOSE: To appraise the ability of a radiomics signature to predict clinical outcome after definitive radiochemotherapy (RCT) of stage III-IV head and neck cancer.

METHODS: A cohort of 110 patients was included in a retrospective analysis. Radiomics texture features were extracted from the gross tumor volumes contoured on planning computed tomography (CT) images. The cohort of patients was randomly divided into a training (70 patients) and a validation (40 patients) cohorts. Textural features were correlated to survival and control data to build predictive models. All the significant predictors of the univariate analysis were included in a multivariate model. The quality of the models was appraised by means of the concordance index (CI).

RESULTS: A signature with 3 features was identified as predictive of overall survival (OS) with CI = 0.88 and 0.90 for the training and validation cohorts, respectively. A signature with 2 features was identified for progression-free survival (PFS; CI = 0.72 and 0.80); 2 features also characterized the signature for local control (LC; CI = 0.72 and 0.82). In all cases, the stratification in high- and low-risk groups for the training and validation cohorts led to significant differences in the actuarial curves. In the validation cohort the mean OS times (in months) were 78.9 ± 2.1 vs 67.4 ± 6.0 in the low- and high-risk groups, respectively, the PFS was 73.1 ± 3.7 and 50.7 ± 7.2, while the LC was 78.7 ± 2.1 and 63.9 ± 6.5.

CONCLUSION: CT-based radiomic signatures that correlate with survival and control after RCT were identified and allow low- and high-risk groups of patients to be identified.

Original languageEnglish
Pages (from-to)805-818
Number of pages14
JournalStrahlentherapie und Onkologie
Volume195
Issue number9
DOIs
Publication statusPublished - Sep 2019

Keywords

  • Aged
  • Chemoradiotherapy/methods
  • Dose Fractionation, Radiation
  • Female
  • Humans
  • Male
  • Middle Aged
  • Neoplasm Staging
  • Otorhinolaryngologic Neoplasms/pathology
  • Radiotherapy Dosage
  • Tomography, X-Ray Computed/methods

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