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E. Narukami



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    P1.02 - Biology/Pathology (ID 614)

    • Event: WCLC 2017
    • Type: Poster Session with Presenters Present
    • Track: Biology/Pathology
    • Presentations: 1
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      P1.02-034 - Non-Invasive Qualitative Diagnosis of Lung Cancer Enabled by Spectrum Analysis of Ultrasound (ID 9376)

      09:30 - 09:30  |  Author(s): E. Narukami

      • Abstract

      Background:
      Ultrasound has been widely utilized in clinical to visualize the internal structure of the objective non-invasively. However ultrasound image can’t distinguish malignant lesion from the normal tissue. Spectrum analysis of ultrasound is a newly developed technology which may reflect on the histological feature. We examine if the spectrum analysis is able to distinguish malignant tissue from normal tissue.

      Method:
      Spectrum was measured using a prototype ultrasound processor EUME5 given by Olympus Japan. three parameters of spectrum such as Midband-fit(M), Intercept(I), and Slope(S) were measured for the objective tissue. In animal study, human lung cancer Xenograft were created in nude mice for each lung cancer cell line (A549, H460, HCC827, and H3122). In clinical setting, surgically excised lungs including lung cancers were examined spectrum analysis for both lung cancers (n=19, 106 slices) and normal lungs (n=17, 65 slices).

      Result:
      Four different Xenografts exhibited significant differences of spectrum data. In the clinical study, the mean value of M, I and S of both lung cancers and normal lungs were M: -43.22 ±4.09 vs -39.31±3.87(p<0.01,) I: -55.28±3.19 vs -54.13±2.4 (N.S), S: -1.43±0.35 vs -1.73±0.30 (p<0.01)

      Conclusion:
      Each lung cancer Xenograft of different histology showed different spectrum value. Spectrum analysis is likely to reflect the histological feature. In clinical, M and S showed statistically different values between lung cancer and normal lung. Based on spectrum value, a malignant tumor can be distinguished from the normal lung in the ultrasound image.