Trends in the incidence of pulmonary nodules in chest computed tomography: 10-year results from two Dutch hospitals

Abstract

Objective: To study trends in the incidence of reported pulmonary nodules and stage I lung cancer in chest CT.

Methods: We analyzed the trends in the incidence of detected pulmonary nodules and stage I lung cancer in chest CT scans in the period between 2008 and 2019. Imaging metadata and radiology reports from all chest CT studies were collected from two large Dutch hospitals. A natural language processing algorithm was developed to identify studies with any reported pulmonary nodule.

Results: Between 2008 and 2019, a total of 74,803 patients underwent 166,688 chest CT examinations at both hospitals combined. During this period, the annual number of chest CT scans increased from 9955 scans in 6845 patients in 2008 to 20,476 scans in 13,286 patients in 2019. The proportion of patients in whom nodules (old or new) were reported increased from 38% (2595/6845) in 2008 to 50% (6654/13,286) in 2019. The proportion of patients in whom significant new nodules (≥ 5 mm) were reported increased from 9% (608/6954) in 2010 to 17% (1660/9883) in 2017. The number of patients with new nodules and corresponding stage I lung cancer diagnosis tripled and their proportion doubled, from 0.4% (26/6954) in 2010 to 0.8% (78/9883) in 2017.

Conclusion: The identification of incidental pulmonary nodules in chest CT has steadily increased over the past decade and has been accompanied by more stage I lung cancer diagnoses.

Clinical relevance statement: These findings stress the importance of identifying and efficiently managing incidental pulmonary nodules in routine clinical practice.

Key points: • The number of patients who underwent chest CT examinations substantially increased over the past decade, as did the number of patients in whom pulmonary nodules were identified. • The increased use of chest CT and more frequently identified pulmonary nodules were associated with more stage I lung cancer diagnoses.

Keywords: Incidence; Multiple pulmonary nodules; Natural language processing; Tomography, X-ray computed.

Fig. 1

Flow diagram of the data collection and analysis. (1) Netherlands Cancer Registry (NCR). (2) Electronic Health Records (EHR), which stores both radiology reports and patient information (i.e., age, gender). (3) Picture Archiving and Communication System (PACS), which stores all the metadata of the CT scans (i.e., slice thickness, scanner model). (4) Based on a Natural Language Processing (NLP) analysis. (5) Supplementary analysis of other lung cancer stages can be found in Appendix E8 (supplement). (6) The nodule and corresponding lung cancer were manually linked; more details can be found in Appendix E2 (supplement)

Fig. 2

Overview of the natural language processing (NLP) algorithm for the detection of reported pulmonary nodules. The numbers on the right side of a box refer to the lookup tables in Appendix E1 (supplement)

Fig. 3

Annual number of unique patients with a (positive) chest CT scan in hospitals A and B in the period 2008–2019

Fig. 4

The proportion of patients with a new positive chest CT scan in hospitals A and B in the period 2010–2019, grouped by age and sex. The denominator is the number of patients with a chest CT per age group. Only the first new positive finding of a patient is counted

Fig. 5

The number of patients with a new positive CT scan (all nodules and nodules  ≥ 5 mm) compared with those with a subsequent stage I lung cancer diagnosis within 2 years in hospitals A and B in the period 2010–2017