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Ren Yuan



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    MA 14 - Diagnostic Radiology, Staging and Screening for Lung Cancer I (ID 672)

    • Event: WCLC 2017
    • Type: Mini Oral
    • Track: Radiology/Staging/Screening
    • Presentations: 1
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      MA 14.11 - Malignancy Risk Prediction of Pulmonary Nodule in Lung Cancer Screening – Diameter Or Volumetric Measurement  (ID 9113)

      16:55 - 17:00  |  Presenting Author(s): Ren Yuan

      • Abstract
      • Presentation
      • Slides

      Background:
      Nodule size is an important parameter to determine malignancy risk. Semi-automated size measurements have the potential to replace manual measurements due to their higher accuracy and reproducibility, and less inter/intra-user variation. However, controversy exists regarding the relative accuracy of 2D diameter versus 3D volumetric measurement to predict malignancy risk. The objective of this study is to compare nodule malignancy prediction models based on 2D mean diameter versus volumetric measurement, both generated by a CAD Software.

      Method:
      We analyzed baseline LDCT reconstructed using high spatial frequency algorithm from 1746 participants (47% women, 53% men, age: 62.5 ± 5.8 yrs) in the Pan-Canadian Early Detection of Lung Cancer Study (PanCan), who had ≥1 non-calcified nodules ≥3mm in diameter. CAD software (CIRRUS Lung Screening, Radboud University Medical Center, Nijmegen, the Netherlands) performed an automatic nodule segmentation, which could be optimised manually, measurement of mean diameter and volume was generated. Malignant or benign nodule status was confirmed by pathology or prolonged follow-up (median follow-up 5.5 years). Logistic regression models predicting cancer were prepared with one including mean diameter and the other including volume. The discrimination, the ability to classify cancer versus benign nodules correctly, was evaluated by the area under the receiver operator characteristic cure (AUC). The calibration - do predicted probabilities match observed probabilities, was assessed using Spiegelhalter’s z-test and graphically by plotting the observed and predicted mean probabilities of cancer by deciles of model risk.

      Result:
      There were in total 5878 nodules, including 119 cancers in 115 individuals. Both models gave similar predictive performances. AUC was 0.947 (95% CI 0.922-0.964) in the mean diameter model and 0.946 (95% CI 0.921-0.966) in the volumetric model (p=0.83). The calibrations were similar between the two models (figure). Figure 1



      Conclusion:
      The predictive performances of nodule malignancy prediction models using mean 2D nodule diameter and 3D volumetric data were indistinguishable.

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