Original Article
Health Services Resarch and Policy
Managing Incidental Findings on Thoracic CT: Lung Findings. A White Paper of the ACR Incidental Findings Committee

https://doi.org/10.1016/j.jacr.2021.04.014Get rights and content

Abstract

The ACR Incidental Findings Committee presents recommendations for managing incidentally detected lung findings on thoracic CT. The Chest Subcommittee is composed of thoracic radiologists who endorsed and developed the provided guidance. These recommendations represent a combination of current published evidence and expert opinion and were finalized by informal iterative consensus. The recommendations address commonly encountered incidental findings in the lungs and are not intended to be a comprehensive review of all pulmonary incidental findings. The goal is to improve the quality of care by providing guidance on management of incidentally detected thoracic findings.

Section snippets

Overview of the ACR Incidental Findings Project

The core objectives of the Incidental Findings Project are to (1) develop consensus on patient characteristics and imaging features that are required to characterize an incidental finding; (2) provide guidance to manage such findings in ways that balance the risks and benefits to patients; (3) recommend reporting terms that reflect the level of confidence regarding a finding; and (4) focus future research by proposing a generalizable management framework across practice settings.

The Consensus Process: Management of Incidental Lung Findings

This article presents the recommendations from the Incidental Findings Committee (IFC) regarding incidental lung findings detected on thoracic CT. The publication is divided into two parts: (1) lung nodules and (2) other lung findings. The process of developing these recommendations included naming an overall Chest Subcommittee chair, who appointed Subcommittee members that are recognized experts in thoracic imaging. The scope of incidental thoracic findings was recognized to be large.

Elements of the Flowcharts: Color Coding

Algorithms for managing incidental findings are depicted in multiple flowcharts (Fig. 1, Fig. 2, Fig. 3, Fig. 4, Fig. 5, Fig. 6). Within each flowchart, yellow boxes indicate using or acquiring clinical data (eg, lesion size), green boxes describe recommendations for action (eg, follow-up imaging), and red boxes indicate that workup or followup may be terminated (eg, if the finding is presumed to be benign). To minimize complexity, each algorithm addresses most—but not all—imaging appearances

Inclusion and Exclusion Criteria

Patients for whom our recommendations are applicable include adults (≥35 years) who are asymptomatic and have undergone imaging for a reason unrelated to the incidental finding. The algorithm should not be applied if the patient has signs or symptoms related to the incidental finding. Radiologists should use discretion when considering patients with limited life expectancy and substantial comorbidities; further downstream care should not be pursued if patients are unable to tolerate therapy or

Imaging Protocol Optimization

In the discussion of the lung findings addressed in this article, comments apply to standard and low-dose examinations, whether performed with or without intravenous contrast. If relevant, those findings potentially affected by low-dose examinations are noted. All thoracic CT should be reconstructed into contiguous thin sections for viewing lung detail (eg, 1.0-1.5 mm) and thicker sections for overview of the lungs and soft tissues (eg, 2.0-3.0 mm).

Relevant Patient Populations

When considering management of incidental lung nodules, additional guidance concerning exclusion criteria is warranted, as detailed in the following four points. Importantly, the ACR’s IFC recommendations for incidental nodules closely follow those of Fleischner Society guidelines [3], providing clarification in specific domains.

Populations for which the IFC’s recommendations should not be used include the following:

  • 1.

    Recommendations do not apply for patients in a lung cancer screening program

Nature and Scope of the Problem

A pulmonary cyst is a region of low attenuation within the lung parenchyma with a wall that creates a well-defined interface with normal lung on thoracic CT [11]. Pulmonary cysts are common and likely related to aging. In one study, asymptomatic cysts were reported in 25% of patients older than 75 years and none in patients younger than 55 years [22]. Winter et al reported pulmonary cysts in 13% of patients older than 65 years but none in those 30 to 50 years old [23]. In the Framingham Heart

Take-Home Points

  • •

    We propose algorithms for managing incidental pulmonary findings, including lung nodules, pulmonary cysts, ground glass opacities, and interlobular septal thickening and reticular opacities.

  • •

    Pulmonary nodule(s) management centers on the risk of malignancy, which is primarily related to size, density, morphology, and patient risk factors.

  • •

    Pulmonary cysts are common and mostly benign but evaluation depends upon wall thickness and distribution within the lungs.

  • •

    Ground glass opacities are secondary to

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    Dr Munden reports other from Optellum, other from TheraBionics, outside the submitted work. Dr MacMahon reports personal fees from Riverain Technology, other from Hologic, grants from Bioclinica, grants from Philips Healthcare, outside the submitted work. Dr Ko reports grants from Siemens Healthineers, outside the submitted work. Dr Naidich reports personal fees from PM-Google Radiology Consulting—CLST, personal fees from IC-Radiologist Board Certified by Vituity, Inc, outside the submitted work. Dr Rossi reports speaker: Boehringer Ingelheim. Dr McAdams reports personal fees from Novartis, nonfinancial support from Pfizer, nonfinancial support from Gilead Sciences, nonfinancial support from Abbott Labs, nonfinancial support from Amgen, nonfinancial support from Johnson & Johnson, nonfinancial support from Bristol-Myers-Squibb, outside the submitted work. Dr Berland reports personal fees from Nuance, Inc; personal fees from iMedis AI, Inc; personal fees from DeepSight Technologies, Inc; and personal fees from American Medical Foundation, outside the submitted work. Dr Pandharipande reports grants from Medical Imaging and Technology Alliance, outside the submitted work. The other authors state that they have no conflict of interest related to the material discussed in this article. Dr Rossi is a partner. Dr McAdams is a partner. Dr Berland is retired from practice. Dr Munden, Dr Black, Dr Hartman, Dr MacMahon, Dr Ko, Dr Dyer, Dr Naidich, Dr Goodman, Dr Brown, Dr Kent, Dr Carter, Dr Chiles, Dr Leung, Dr Boiselle, Dr Kazerooni, and Dr Pandharipande are faculty.

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