P1.17-01 Robustness of an Image-Based Data Mining Approach in Lung Cancer Patients

Abstract

Image-based data mining (IBDM) enables exploring the correlation of dose distributions and outcomes in large cohorts of patients without the requirement of additional contouring. IBDM has recently identified the dose to the base of the heart as an important predictor for overall survival (OS) in lung cancer patients receiving radiotherapy [McWilliam et al EJC 2017]. IBDM relies on non-rigid registration to set inter-patient dosimetric data into a common reference anatomy or reference patient. Here, we investigated the uncertainties associated with the choice of reference patient, and their influence on the correlation between incidental dose to the base of the heart and OS. In previous work, 1101 NSCLC patients (55Gy / 20 fractions) were randomly selected, and their planning CT images non-rigidly registered to a reference patient CT scan using NiftyReg (http://cmictig.cs.ucl.ac.uk/wiki/) as part of IBDM process. In this work, 5 additional patients with small cell lung cancer (i.e. without a large tumour burden) were used as “reference patients” and the IBDM analysis in the whole cohort was repeated for each reference patient. Permutation testing with 100 iterations was applied to assess statistical significance. Figure 1 shows the regions of highly significant correlation between dose and OS for each reference patient. In spite of large variations in anatomy between the reference patients, each analysis identified similar anatomical regions as significantly associated with OS (t>5). Moreover, permutation testing was consistent with the original findings. IBDM is a robust approach and, in this analysis, does not appear to be sensitive to the choice of reference patient for the investigated dose-effect correlation. Prospective studies are necessary to confirm the correlation between dose to the base of the heart and OS in NSCLC patients. Methodological studies are needed to determine the level of effect strength and region size that this general technique can identify.