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Taimei Tachibana

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    P1.05 - Interventional Diagnostics/Pulmonology (Not CME Accredited Session) (ID 937)

    • Event: WCLC 2018
    • Type: Poster Viewing in the Exhibit Hall
    • Track:
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/24/2018, 16:45 - 18:00, Exhibit Hall
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      P1.05-18 - Predictive Performance of Semi-Quantitative Metabolic Metrics on FDG-PET/CT for the Identification of EGFR Mutations (ID 13190)

      16:45 - 18:00  |  Presenting Author(s): Taimei Tachibana

      • Abstract
      • Slides


      FDG-PET/CT is highly useful in evaluating biological malingancy of lung cancer cases. The maximum standardized uptake values (SUVmax) of the primary lesion is widely reported to be associated with prognosis in lung cancer while other metabolic metrics, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) have also been explored as a measure of metabolic tumor burden in recent years. Several recent reports have shown that measurement of these metabolic metrics on PET/CT could be beneficial for the identification of driver gene mutational status such as EGFR and KRAS. The purpose of this study is to investigate the role of quantitative metabolic metrics (SUVmax, MTV, TLG) in identifying adenocarcinoma harboring EGFR mutations.

      a9ded1e5ce5d75814730bb4caaf49419 Method

      We enrolled 247 patients with clinical stage I adenocarcinoma with pre- or postoperative EGFR genotyping. All the patients underwent surgical resection after preoperative FDG-PET/CT scanning during the period from January 2012 to January 2018. SUVmax, MTV, and TLG of each lung tumor were determined with Synapse Vincent System (Fujifilm Medical, Tokyo, Japan) as the volume viewer software. MTV is defined as the volume of the area of ​​SUV 2.5 or higher while TLG was calculated as meanSUV x MTV. Correlation between age, gender, smoking history, clinical stage, SUVmax, MTV, TLG, and EGFR gene mutation status was analyzed.

      4c3880bb027f159e801041b1021e88e8 Result

      A total of 114patients (46%) were identified as having EGFR mutations. Univariate analysis showed that sex (p = 0.001), smoking status (p = 0.019), SUVmax (p = 0.001), MTV (p = 0.007), and TLG (p = 0.014) were significantly associated with EGFR mutations. Multivariate analysis demonstrated that sex (p = 0.004) and SUVmax (P = 0.004) were independent predictors of EGFR mutations. The receiver operating characteristic curve yielded area under the curve values of 0.622, 0.604, and 0.609 for SUVmax, MTV, and TLG, respectively (SUVmax of 2.95, MTV of 0.10mm3, and TLG of 0.26, respectively). The frequency of EGFR mutations of patients with SUVmax < 2.95, MTV < 0.10mm3, TLG < 0.26, female, and never-smokers were 64.2%, 64.2%, 64.2%, 63.5%, and 61.2%, respectively.

      8eea62084ca7e541d918e823422bd82e Conclusion

      In clinical stage I lung adenocarcinoma, SUVmax, MTV, and TLG measured by FDG-PET/CT were associated with EGFR mutation status.


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