Incidental Pulmonary Nodules - What Do We Know in 2022

Respiration. 2022;101(11):1024-1034. doi: 10.1159/000526818. Epub 2022 Oct 13.

Abstract

Lung cancer (LC) is the leading cause of cancer-related mortality worldwide, and early LC diagnosis can significantly improve outcomes and survival rates in affected patients. Implementation of LC screening programs using low-dose computed tomography CT in high-risk subjects aims to detect LC as early as possible, but so far, adoption of screening programs into routine clinical care has been very slow. In recent years, the use of CT has significantly increased the rate of incidentally detected pulmonary nodules. Although most of those incidental pulmonary nodules (IPNs) are benign, some of them represent early-stage LC. Given the large number of IPNs detected in the range of several millions each year, this represents an additional, maybe even larger, opportunity to drive stage shift in LC diagnosis, next to LC screening programs. Comprehensive evaluation and targeted work-up of IPNs are mandatory to identify the malignant nodules from the crowd, and several guidelines provide radiologists and physicians' guidance on IPN assessment and management. However, IPNs still seem to be inadequately processed due to various reasons including insufficient reporting in the radiological report, missing communication between stakeholders, absence of patient tracking systems, and uncertainty regarding responsibilities for the IPN management. In recent years, several approaches such as lung nodule programs, patient tracking software, artificial intelligence, and communication software were introduced into clinical practice to address those shortcomings. This review evaluates the current situation of IPN management and highlights recent developments in process improvement to achieve first steps toward stage shift in LC diagnosis.

Keywords: Early-stage diagnosis; Incidental pulmonary nodules; Low-dose computed tomography; Lung cancer screening; Lung nodule management; Stage shift.

Publication types

  • Review

MeSH terms

  • Artificial Intelligence
  • Early Detection of Cancer
  • Humans
  • Incidental Findings
  • Lung Neoplasms* / diagnostic imaging
  • Multiple Pulmonary Nodules* / diagnostic imaging
  • Solitary Pulmonary Nodule* / diagnostic imaging
  • Tomography, X-Ray Computed

Grants and funding

AstraZeneca is supporting this article in the context of the Lung Ambition Alliance (LAA) initiative, where AZ and IASLC are partnering with the goal to support projects that have the potential to improve lung cancer 5-year-survival rates, independent of drug development. The medical writing assistance for this review was therefore funded by AstraZeneca, Hamburg, Germany.