Author of

• 10946

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  P1.19 - Poster Session 1 - Imaging (ID 179)

  • Event: WCLC 2013
  • Type: Poster Session
  • Track: Imaging, Staging & Screening
  • Presentations: 1
  • Moderators:
  • Coordinates: 10/28/2013, 09:30 - 16:30, Exhibit Hall, Ground Level

  • 10952

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    P1.19-006 - Predictors of nodule malignancy in the Danish Lung Cancer Screening Trial (DLCST) (ID 2172)

    09:30 - 09:30  |  Author(s): Z. Saghir
    • Abstract

    Background
    Pulmonary nodules are detected more frequently than ever in both clinical and screening settings. Timely and correct suspicion of malignancy is of great importance in the subsequent management of the nodules. We present data on pulmonary nodule growth and participants baseline characteristics to determine predictors of malignancy.

    Methods
    In DLCST, 4,104 current and former smokers, with a history of at least 20 pack years and age between 50-70 years, were randomized to either five annual multi-slice low-dose CT screenings or no screening. All participants had an annual visit to the screening clinic where lung function tests and questionnaires concerning health, lifestyle, smoking habits etc. were performed. The scans were read by two chest radiologists who recorded the location and size of any nodules. Nodules of diameters between 5-15 mm were considered indeterminate, and rescanned after three months. Participants with nodules larger than 15 mm were referred to diagnostic workup, as were those with growing nodules. Lung cancer was diagnosed by pathological evaluation. Using volumetric software solid and nonsolid/partsolid nodules were segmented and followed. Only visually correct segmented nodules that were present more than one year were included. Doubling times of mass, volume and diameter from the first to the last record of the nodule were calculated. We performed logistic regression analysis with malignancy as the outcome and baseline characteristics, nodule type and growth measurements as explanatory variables.

    Results
    975 nodules in 618 participants were included. 31 nodules (3%) were diagnosed as lung cancers. 10(33%) of the malignant nodules were nonsolid/partsolid. Fig. 1 shows histograms of growth measurements. Fig. 2 show the logistic regression analysis. In both cases FEV1 and Mass Doubling Times predicted malignancy significantly.Figure 1Figure 2

    Conclusion
    Growth rates measured by volumetric software and FEV1 are powerful predictors for malignancy when a pulmonary nodule is present in a low dose chest CT scan.