Lung cancer screening by nodule volume in Lung-RADS v1.1: negative baseline CT yields potential for increased screening interval

Mario Silva, Gianluca Milanese, Stefano Sestini, Federica Sabia, Colin Jacobs, Bram van Ginneken, Mathias Prokop, Cornelia M Schaefer-Prokop, Alfonso Marchianò, Nicola Sverzellati, Ugo Pastorino, Mario Silva, Gianluca Milanese, Stefano Sestini, Federica Sabia, Colin Jacobs, Bram van Ginneken, Mathias Prokop, Cornelia M Schaefer-Prokop, Alfonso Marchianò, Nicola Sverzellati, Ugo Pastorino

Abstract

Objectives: The 2019 Lung CT Screening Reporting & Data System version 1.1 (Lung-RADS v1.1) introduced volumetric categories for nodule management. The aims of this study were to report the distribution of Lung-RADS v1.1 volumetric categories and to analyse lung cancer (LC) outcomes within 3 years for exploring personalized algorithm for lung cancer screening (LCS).

Methods: Subjects from the Multicentric Italian Lung Detection (MILD) trial were retrospectively selected by National Lung Screening Trial (NLST) criteria. Baseline characteristics included selected pre-test metrics and nodule characterization according to the volume-based categories of Lung-RADS v1.1. Nodule volume was obtained by segmentation with dedicated semi-automatic software. Primary outcome was diagnosis of LC, tested by univariate and multivariable models. Secondary outcome was stage of LC. Increased interval algorithms were simulated for testing rate of delayed diagnosis (RDD) and reduction of low-dose computed tomography (LDCT) burden.

Results: In 1248 NLST-eligible subjects, LC frequency was 1.2% at 1 year, 1.8% at 2 years and 2.6% at 3 years. Nodule volume in Lung-RADS v1.1 was a strong predictor of LC: positive LDCT showed an odds ratio (OR) of 75.60 at 1 year (p < 0.0001), and indeterminate LDCT showed an OR of 9.16 at 2 years (p = 0.0068) and an OR of 6.35 at 3 years (p = 0.0042). In the first 2 years after negative LDCT, 100% of resected LC was stage I. The simulations of low-frequency screening showed a RDD of 13.6-21.9% and a potential reduction of LDCT burden of 25.5-41%.

Conclusions: Nodule volume by semi-automatic software allowed stratification of LC risk across Lung-RADS v1.1 categories. Personalized screening algorithm by increased interval seems feasible in 80% of NLST eligible.

Key points: • Using semi-automatic segmentation of nodule volume, Lung-RADS v1.1 selected 10.8% of subjects with positive CT and 96.87 relative risk of lung cancer at 1 year, compared to negative CT. • Negative low-dose CT by Lung-RADS v1.1 was found in 80.6% of NLST eligible and yielded 40 times lower relative risk of lung cancer at 2 years, compared to positive low-dose CT; annual screening could be preference sensitive in this group. • Semi-automatic segmentation of nodule volume and increased screening interval by volumetric Lung-RADS v1.1 could retrospectively suggest a 25.5-41% reduction of LDCT burden, at the cost of 13.6-21.9% rate of delayed diagnosis.

Keywords: Diagnostic screening programs; Lung neoplasms; Lung volume measurements; Solitary pulmonary nodule; Volume computed tomography.

Conflict of interest statement

The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Figures

Fig. 1
Fig. 1
The flow diagram details the selection of high-risk subjects, classification by nodule volume in ACR Lung-RADS v1.1 at baseline low-dose computed tomography and relevant cumulative distribution of lung cancer
Fig. 2
Fig. 2
Relative distribution of LDCT result and LC diagnosis at 1 year, 2 years and 3 years
Fig. 3
Fig. 3
Time-resolved relative risk (RR) for lung cancer, according to the baseline LDCT result
Fig. 4
Fig. 4
Kaplan-Meier curve for diagnosis of LC through 3 years, according to the baseline LDCT result. The bottom section shows the HR by each pre-defined time point analysis of LC probability

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