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Anna Scaife

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    OA01 - Improving Outcomes in Locoregional NSCLC I (ID 892)

    • Event: WCLC 2018
    • Type: Oral Abstract Session
    • Track: Treatment of Locoregional Disease - NSCLC
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/24/2018, 10:30 - 12:00, Room 107
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      OA01.03 - Interaction Between Dose and Calcifications Is a Predictor for Overall Survival in Lung Cancer Patients Receiving Radiotherapy (ID 13920)

      10:50 - 11:00  |  Author(s): Anna Scaife

      • Abstract
      • Presentation
      • Slides


      Recently, incidental dose to the heart was found to be predictive for overall survival in lung cancer patients receiving radiotherapy [McWilliam et al EJC 2017, Johnson et al Radiother Oncol 2018]. These patients often present with multiple comorbidities that should be incorporated in survival analysis. However, such data is often missing. We investigated whether calcifications, identified on the radiotherapy planning CT, can be used as a surrogate for cardiac health. In particular, we investigated the interaction between calcifications, dose and survival.

      a9ded1e5ce5d75814730bb4caaf49419 Method

      Data from 814 unselected non-small cell lung cancer patients was used, all treated with 55Gy in 20 fractions. Methodology was developed to automatically segment calcifications within the heart, the aortic arch and their surroundings. The 3D planning CT scans, and the associated lung and spinal cord delineations were processed using well-established image processing algorithms, e.g., convex hull, thresholding, morphological operations, connected pixel analysis and flood filling to detect calcifications. Moreover, shape analysis was included to enhance regions that presented tubular or plate-like appearance. The detection algorithm was validated in a small subset of 10 patients, and this group was used to determine the success and error rate of the automatic segmentation. Finally, a Cox-proportional hazards multivariate analysis was performed for overall survival of all patients accounting for tumour size, total calcification volume, mean dose across all identified calcifications, and interaction between calcification volume and dose.

      4c3880bb027f159e801041b1021e88e8 Result

      The success rate of the algorithm for identifying calcifications was 81.8%, its error rate was 8.8%. The multivariate survival analysis identified tumour size (continuous, p<<0.0001) and the interaction of calcification volume and their mean dose (continuous, p=0.029) as significant. Calcification volume (p=0.57) or mean calcification radiation dose alone (p=0.269) were not found to be significant.

      8eea62084ca7e541d918e823422bd82e Conclusion

      Multivariate analysis shows a significant interaction between volume of the identified calcifications and their mean radiotherapy dose predicting survival. Further improvements to identify calcifications in the descending thoracic aorta and validation of our methodology are required. Further work linking our results with the established Agatston or Coronary Artery Calcium score is in progress.

      * EVO-FB share first authorship


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