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  P2.01 - Advanced NSCLC (Not CME Accredited Session) (ID 950)

  • Event: WCLC 2018
  • Type: Poster Viewing in the Exhibit Hall
  • Track:
  • Presentations: 1
  • Moderators:
  • Coordinates: 9/25/2018, 16:45 - 18:00, Exhibit Hall

  • 26875

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    P2.01-73 - Automated Image Analysis Tool for Tumor Volume Growth Rate to Guide Precision Cancer Therapy: EGFR-Mutant NSCLC as a Paradigm (ID 11971)

    16:45 - 18:00  |  Author(s): Hisashi Tachizaki
    • Abstract

    Background
    

    Imaging remains a crucial component in the evaluation of the therapeutic benefit of precision cancer therapy, because it objectively characterizes tumor burden changes during therapy and provides guides for treatment decisions. The purpose of the present study is to develop an automated analytic module for calculation of tumor growth rate from serial CT scans and evaluate the module functionality and reproducibility in a pilot cohort of advanced NSCLC patients with EGFR mutations treated with EGFR tyrosine kinase inhibitors.

    a9ded1e5ce5d75814730bb4caaf49419 Method
    

    The module utilized a commercially available image-processing workstation equipped with a validated tumor volume measurement tool. A novel analytic software module was programmed with the capability to record and display serial tumor volume changes and to calculate tumor volume growth rate over time and added to the workstation. The functionality and reproducibility of the module was evaluated using a pilot cohort of 24 EGFR-mutant patients treated with EGFR inhibitors by two independent thoracic radiologists.

    4c3880bb027f159e801041b1021e88e8 Result
    

    The module analyzed chest CT scans from 24 patients (5 males, 19 females; median age: 61) with a median of 8 scans per patient, totaling 227 scans and provided a graphical display with an automated calculation of tumor growth rate after the nadir volume for each patient. High inter and intraobserver agreements were noted for tumor growth rates, with concordance correlation coefficients of 0.9323 and 0.9668, respectively. Interpretation of slow versus fast tumor growth using previously identified threshold of ≤0.15/month had a perfect interobserver agreement (κ=1.00), and an excellent intraobserver agreement (κ=0.895).

    8eea62084ca7e541d918e823422bd82e Conclusion
    

    The present study describes the development of an image analytic module for assessing tumor growth rate and the data demonstrates the functionality and reproducibility of the module in a pilot cohort of EGFR-mutant NSCLC patients treated with EGFR-TKI. The image analytic module is an initial step for clinical translation of the tumor growth rate approach to guide cancer treatment in precision oncology.

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