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Gutiérrez Alliende J, Kazerooni EA, Crosbie PAJ, Xie X, Sharma A, Reis J. The present and future of lung cancer screening: latest evidence. Future Oncol 2025:1-9. [PMID: 40340737 DOI: 10.1080/14796694.2025.2501516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2024] [Accepted: 04/30/2025] [Indexed: 05/10/2025] Open
Abstract
Lung cancer is the leading cause of cancer-related mortality worldwide. Early lung cancer detection improves lung cancer-related mortality and survival. This report summarizes presentations and panel discussions from a webinar, "The Present and Future of Lung Cancer Screening: Latest Evidence and AI Perspectives." The webinar provided the perspectives of experts from the United States, United Kingdom, and China on evidence-based recommendations and management in lung cancer screening (LCS), barriers, and the role of artificial intelligence (AI). With several countries now incorporating the utilization of AI in their screening programs, AI offers potential solutions to some of the challenges associated with LCS.
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Affiliation(s)
| | - Ella A Kazerooni
- Departments of Radiology & Internal Medicine, University of Michigan Medical School, Michigan, MI, USA
| | - Philip A J Crosbie
- Division of Immunology, Immunity to Infection & Respiratory Medicine, University of Manchester, Manchester, UK
| | - Xueqian Xie
- Radiology Department, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ankur Sharma
- Medical Affairs for Digital Radiology, Bayer AG, Berlin, Germany
| | - Joana Reis
- Medical Affairs for Digital Radiology, Bayer AG, Berlin, Germany
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2
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Bonney A, Pascoe DM, McCusker MW, Steinfort D, Marshall H, McWilliams A, Brims FJ, Stone E, Fogarty P, Silver JD, Milner B, Silverstone E, Hsu E, Nguyen D, Rofe C, White C, Hu X, Mayo J, Myers R, Fong KM, Manser R, Lam S. Incidental findings during lung low-dose computed tomography cancer screening in Australia and Canada, 2016-21: a prospective observational study. Med J Aust 2025; 222:403-411. [PMID: 40320382 PMCID: PMC12050252 DOI: 10.5694/mja2.52649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2024] [Accepted: 10/21/2024] [Indexed: 05/08/2025]
Abstract
OBJECTIVES To investigate the type and frequency of incidental findings in people at high risk of lung cancer who undergo baseline low-dose computed tomography (LDCT) lung cancer screening in Australia and Canada. STUDY DESIGN Prospective observational study; sub-study of the single-arm International Lung Screen Trial (ILST) lung cancer screening study. SETTING, PARTICIPANTS Australian and Canadian people enrolled in the ILST, 25 August 2016 - 21 November 2020; inclusion criteria: aged 50-80 years, active smoking history, and high risk of lung cancer (estimated six-year lung cancer risk of 1.51% or more, based on the PLCOm2012 risk prediction model; or a smoking history of 30 pack-years or more). Initial LDCT screening was undertaken at one of five participating hospitals in Australia and one in Canada. MAIN OUTCOME MEASURES Prevalence of incidental findings during baseline LDCT lung cancer screening (using a research checklist), by country, classified by experienced radiologists as requiring or not requiring clinical follow-up; reporting of incidental findings in clinical reports for treating physicians (two Australian sites only). RESULTS A total of 4403 participants completed baseline LDCT screening at the six participating hospitals. The mean age (64-65 years) and the proportions of participants who currently smoked (47-55%) were similar at all six sites; the proportion of female participants was larger in Sydney (52%) and Vancouver (51%) than the other sites (39-44%). At least one incidental finding was made during baseline LDCT screening of 3225 people (72.8%); findings in 454 people (10.3%) required clinical follow-up. The most frequent incidental findings were coronary artery calcification (3022 of 4380 participants with recorded results, 69.0%) and emphysema (2378 of 4401, 54.0%). Marked differences between the Australian and Canadian sites in the prevalence of incidental findings were noted, and also between the two Australian sites in their communication of incidental findings in clinical screening reports. CONCLUSION Incidental findings during lung cancer screening were frequent, and clinical reporting of these findings was inconsistent. When LDCT lung cancer screening is introduced in Australia, a standardised reporting template should be used to provide clear guidance about the clinical significance of such findings. TRIAL REGISTRATION ClinicalTrials.gov, NCT02871856 (prospective, 18 August 2016).
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Affiliation(s)
- Asha Bonney
- Royal Melbourne HospitalMelbourneVIC
- The University of MelbourneMelbourneVIC
| | - Diane M Pascoe
- Royal Melbourne HospitalMelbourneVIC
- The University of MelbourneMelbourneVIC
| | - Mark W McCusker
- Royal Melbourne HospitalMelbourneVIC
- The University of MelbourneMelbourneVIC
| | - Daniel Steinfort
- Royal Melbourne HospitalMelbourneVIC
- The University of MelbourneMelbourneVIC
| | - Henry Marshall
- The Prince Charles HospitalBrisbaneQLD
- Thoracic Research Centre, the University of QueenslandBrisbaneQLD
| | - Annette McWilliams
- Fiona Stanley HospitalPerthWA
- The University of Western AustraliaPerthWA.
| | - Fraser J Brims
- Sir Charles Gairdner HospitalPerthWA
- Curtin Medical School, Curtin UniversityPerthWA
| | - Emily Stone
- St Vincent's HospitalSydneyNSW
- St Vincent's Clinical School, University of New South WalesSydneyNSW
| | | | - Jeremy D Silver
- Statistical Consulting Centre, the University of MelbourneMelbourneVIC
| | | | | | | | | | | | | | | | - John Mayo
- Vancouver General HospitalVancouverCanada
| | - Renelle Myers
- The University of British ColumbiaVancouverCanada
- BC CancerVancouverCanada
| | - Kwun M Fong
- UQ Thoracic Research Centre, the Prince Charles HospitalBrisbaneQLD
| | - Renee Manser
- Royal Melbourne HospitalMelbourneVIC
- The University of MelbourneMelbourneVIC
| | - Stephen Lam
- The University of British ColumbiaVancouverCanada
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3
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Lancaster HL, Jiang B, Davies MPA, Gratama JWC, Silva M, Yi J, Heuvelmans MA, de Bock GH, Devaraj A, Field JK, Oudkerk M. Histological proven AI performance in the UKLS CT lung cancer screening study: Potential for workload reduction. Eur J Cancer 2025; 220:115324. [PMID: 40022836 DOI: 10.1016/j.ejca.2025.115324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2025] [Revised: 02/14/2025] [Accepted: 02/19/2025] [Indexed: 03/04/2025]
Abstract
PURPOSE Artificial intelligence (AI) could reduce lung cancer screening computer tomography (CT)-reading workload if used as a first-reader, ruling-out negative CT-scans at baseline. Evidence is lacking to support AI performance when compared to gold-standard lung cancer outcomes. This study validated the performance of a commercially available AI software in the UK lung cancer screening (UKLS) trial dataset, with comparison to human reads and histological lung cancer outcomes, and estimated CT-reading workload reduction. METHODS 1252 UKLS-baseline-CT-scans were evaluated independently by AI and human readers. AI performance was evaluated on two-levels. Firstly, AI classification and individual reads were compared to a EU reference standard (based on NELSON2.0-European Position Statement) determined by a European expert panel blinded from individual results. A positive misclassification was defined as a nodule positive read ≥ 100mm3 and no/<100mm3 nodules in the expert read; A negative misclassification was defined as a nodule negative read, whereas an indeterminate or positive finding in the expert read. Secondly, AI nodule classification was compared to gold-standard histological lung cancer outcomes. CT-reading workload reduction was calculated from AI negative CT-scans when AI was used as first-reader. RESULTS Expert panel reference standard reported 815 (65 %) negative and 437 (35 %) indeterminate/positive CT-scans in the dataset of 1252 UKLS-participants. Compared to the reference standard, AI resulted in less misclassification than human reads, NPV 92·0 %(90·2 %-95·3 %). On comparison to gold-standard, AI detected all 31 baseline-round lung cancers, but classified one as negative due to the 100mm3 threshold, NPV 99·8 %(99·0 %-99·9 %). Estimated maximum CT-reading workload reduction was 79 %. CONCLUSION Implementing AI as first-reader to rule-out negative CT-scans, shows considerable potential to reduce CT-reading workload and does not lead to missed lung cancers.
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Affiliation(s)
- Harriet L Lancaster
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands; Institute for Diagnostic Accuracy, Groningen, the Netherlands
| | - Beibei Jiang
- Institute for Diagnostic Accuracy, Groningen, the Netherlands
| | - Michael P A Davies
- Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, United Kingdom
| | - Jan Willem C Gratama
- Department of Radiology and Nuclear Medicine, Gelre Hospitals, Apeldoorn, the Netherlands
| | - Mario Silva
- Scienze Radiologische, Department of Medicine and Surgery (DiMeC), University of Parma, Parma, Italy; Department of Radiology, University of Massachusetts Memorial Health, University of Massachusetts, Chan Medical School, Worcester, MA, United States
| | | | - Marjolein A Heuvelmans
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands; Institute for Diagnostic Accuracy, Groningen, the Netherlands; Department of Respiratory Medicine, University of Amsterdam, Amsterdam University Medical Centers, Amsterdam, the Netherlands
| | - Geertruida H de Bock
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Anand Devaraj
- Royal Brompton Hospital London, Sydney St, Chelsea, London, United Kingdom; National Heart and Lung Institute, Imperial College, London, United Kingdom
| | - John K Field
- Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, United Kingdom.
| | - Matthijs Oudkerk
- Institute for Diagnostic Accuracy, Groningen, the Netherlands; Faculty of Medical Sciences, University of Groningen, Groningen, the Netherlands.
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Ledda RE, Milanese G, Revel MP, Snoeckx A. Pros and cons of reporting incidental findings in lung cancer screening. Eur Radiol 2025:10.1007/s00330-025-11580-7. [PMID: 40234338 DOI: 10.1007/s00330-025-11580-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2024] [Revised: 03/08/2025] [Accepted: 03/13/2025] [Indexed: 04/17/2025]
Abstract
Incidental findings (IFs) are common in lung cancer screening (LCS). While the detection of some of these findings can lead to early diagnosis and treatment of clinically significant conditions, it also carries the risks of overdiagnosis and overtreatment, causing anxiety for patients and increased economic costs for health systems. Effective management of IFs requires a balanced approach guided by clear guidelines, standardized reporting, and participants-centered communication. As the field of LCS evolves, continued research and innovation will be essential in refining the strategies for managing IFs, ensuring that the benefits of screening are maximized while minimizing potential harm. Evidence-based guidelines on reporting and management of IFs, however, are still lacking. This narrative review explores the pros and cons of reporting IFs in LCS, focusing on key controversies. KEY POINTS: Reporting and managing incidental findings in lung cancer screening is largely debated. The detection of incidental findings can lead to early diagnosis of clinically significant conditions but carries the risks of overdiagnosis and overtreatment. A balance must be found to have a positive impact on the population while not placing a burden on healthcare systems.
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Affiliation(s)
- Roberta Eufrasia Ledda
- Department of Medicine and Surgery (DiMeC), University of Parma, Parma, Italy
- Thoracic Surgery Unit, Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy
| | - Gianluca Milanese
- Department of Medicine and Surgery (DiMeC), University of Parma, Parma, Italy.
| | - Marie-Pierre Revel
- Department of Radiology, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, Paris, France
- Université Paris Cité, Faculté de Médecine, Paris, France
| | - Annemiek Snoeckx
- Antwerp University Hospital, Edegem, Belgium
- Faculty of Medicine and Health Sciences, University of Antwerp, Wilrijk, Belgium
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Henderson LM, Kim RY, Tanner NT, Tsai EB, Begnaud A, Dako F, Gieske M, Kallianos K, Richman I, Sakoda LC, Schwartz RG, Yeboah J, Fong KM, Lam S, Lee P, Pasquinelli M, Smith RA, Triplette M, Tanoue LT, Rivera MP. Lung Cancer Screening and Incidental Findings: A Research Agenda: An Official American Thoracic Society Research Statement. Am J Respir Crit Care Med 2025; 211:436-451. [PMID: 39928329 PMCID: PMC11936151 DOI: 10.1164/rccm.202501-0011st] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2025] [Indexed: 02/11/2025] Open
Abstract
Background: Lung cancer screening with low-dose computed tomography (LDCT) may uncover incidental findings (IFs) unrelated to lung cancer. There may be potential benefits from identifying clinically significant IFs that warrant intervention and potential harms related to identifying IFs that are not clinically significant but may result in additional evaluation, clinician effort, patient anxiety, complications, and excess cost. Objectives: To identify knowledge and research gaps and develop and prioritize research questions to address the approach to and management of IFs. Methods: We convened a multidisciplinary panel to review the available literature on IFs detected in lung cancer screening LDCT examinations, focusing on variability and standardizing reporting, management of IFs, and evaluation of the benefits and harms of IFs, particularly cardiovascular-related IFs. We used a three-round modified Delphi process to prioritize research questions. Results: This statement identifies knowledge gaps in 1) reporting of IFs, 2) management of IFs, and 3) identifying and reporting coronary artery calcification found on lung cancer screening LDCT. Finally, we present the panel's initial 36 research questions and the final 20 prioritized questions. Conclusions: This statement provides a prioritized research agenda to further efforts focused on evaluating, managing, and increasing awareness of IFs in lung cancer screening.
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Sabia F, Valsecchi C, Ledda RE, Bogani G, Orlandi R, Rolli L, Ferrari M, Balbi M, Marchianò A, Pastorino U. Automated Measurement of Coronary Artery Calcifications and Routine Perioperative Blood Tests Predict Survival in Resected Stage I Lung Cancer. JTO Clin Res Rep 2025; 6:100788. [PMID: 39990140 PMCID: PMC11847048 DOI: 10.1016/j.jtocrr.2025.100788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2024] [Revised: 12/13/2024] [Accepted: 12/22/2024] [Indexed: 02/25/2025] Open
Abstract
Introduction Coronary artery calcification (CAC) is a well-known cardiovascular risk factor. In the past year, the CAC score has been investigated in lung cancer (LC) screening, suggesting promising results in terms of mortality risk assessment. Nevertheless, its role in patients with LC is still to be investigated. This study aimed to evaluate the performance of a fully automated CAC scoring alone and combined with a prognostic index on the basis of perioperative routine blood tests in predicting 5-year survival of patients with stage I LC. Methods This study included 536 consecutive patients with stage I LC who underwent preoperative chest computed tomography followed by surgical resection. The CAC score was measured by commercially available, fully automated artificial intelligence software. The primary outcome was the 5-year overall survival rate. Results A total of 110 patients (20.5%) had a CAC score greater than or equal to 400, 149 (27.8%) between 100 and 399, and 277 (51.7%) had less than 100. Male smokers had the highest CAC values: 32% compared with only 17% of nonsmokers. Females had lower CAC values compared with males both in smokers and nonsmokers: CAC greater than or equal to 400 only for 10% of smoking females and 0% in nonsmoking females. The 5-year survival was 80.3% overall, 84.7% in CAC less than 100, 77.5% in CAC 100 to 399, and 73.5% in CAC greater than or equal to 400 (p = 0.0047). Conclusions We observed that the CAC score predicted the 5-year overall survival in patients with resected stage I LC, both alone and combined with the modified routine blood test score. These results open new prospects for the prevention of noncancer mortality in patients with early-stage LC.
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Affiliation(s)
- Federica Sabia
- Division of Thoracic Surgery, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Nazionale dei Tumori, Milan, Italy
| | - Camilla Valsecchi
- Division of Thoracic Surgery, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Nazionale dei Tumori, Milan, Italy
| | - Roberta Eufrasia Ledda
- Division of Thoracic Surgery, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Nazionale dei Tumori, Milan, Italy
- Section of Radiology, Department of Medicine and Surgery (DiMeC), University Hospital of Parma, Parma, Italy
| | - Giorgio Bogani
- Department of Gynecologic Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy
| | - Riccardo Orlandi
- Department of Thoracic Surgery, University of Milan, Milan, Italy
| | - Luigi Rolli
- Division of Thoracic Surgery, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Nazionale dei Tumori, Milan, Italy
| | - Michele Ferrari
- Division of Thoracic Surgery, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Nazionale dei Tumori, Milan, Italy
| | - Maurizio Balbi
- Radiology Unit, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Italy
| | - Alfonso Marchianò
- Department of Radiology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Ugo Pastorino
- Division of Thoracic Surgery, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Nazionale dei Tumori, Milan, Italy
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7
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Bonney A, Chua M, McCusker MW, Pascoe D, Joshi SB, Steinfort D, Marshall H, Silver JD, Xie C, Yang S, Watson J, Fogarty P, Stone E, Brims F, McWilliams A, Hu X, Rofe C, Milner B, Lam S, Fong KM, Manser R. Coronary artery calcification detected on low-dose computed tomography in high-risk participants of an Australian lung cancer screening program: A prospective observational study. Respirology 2025; 30:62-69. [PMID: 39318183 DOI: 10.1111/resp.14832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Accepted: 09/11/2024] [Indexed: 09/26/2024]
Abstract
BACKGROUND AND OBJECTIVES Coronary artery calcification (CAC) is a frequent additional finding on lung cancer screening (LCS) low-dose computed tomography (LDCT). Cardiovascular disease (CVD) is a major cause of death in LCS participants. We aimed to describe prevalence of incidental CAC detected on LDCT in LCS participants without prior history of coronary artery disease (CAD), evaluate their CVD risk and describe subsequent investigation and management. METHODS Prospective observational nested cohort study including all participants enrolled at a single Australian site of the International Lung Screen Trial. Baseline LDCTs were reviewed for CAC, and subsequent information collected regarding cardiovascular health. 5-year CVD risk was calculated using the AusCVD risk calculator. RESULTS 55% (226/408) of participants had CAC on LDCT and no prior history of CAD, including 23% with moderate-severe CAC. Mean age of participants with CAC was 65 years, 68% were male. 53% were currently smoking. Majority were high risk (51%) or intermediate risk (32%) of a cardiovascular event in 5 years. 21% of participants were re-stratified to a higher CVD risk group when CAC detected on LCS was incorporated. Only 10% of participants with CAC received lifestyle advice (only 3% currently smoking received smoking cessation advice). 80% of participants at high-risk did not meet guideline recommendations, with 47% of this group remaining without cholesterol lowering therapy. CONCLUSION LCS with LDCT offers the potential to identify and communicate CVD risk in this population. This may improve health outcomes for high-risk LCS participants and further personalize management once screening results are known.
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Affiliation(s)
- Asha Bonney
- Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia
- Department of Respiratory and Sleep Medicine, Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | - Michelle Chua
- Department of Radiology, Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | - Mark W McCusker
- Department of Radiology, Royal Melbourne Hospital, Melbourne, Victoria, Australia
- Department of Radiology, University of Melbourne, Melbourne, Victoria, Australia
| | - Diane Pascoe
- Department of Radiology, Royal Melbourne Hospital, Melbourne, Victoria, Australia
- Department of Radiology, University of Melbourne, Melbourne, Victoria, Australia
| | - Subodh B Joshi
- Department of Cardiology, Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | - Daniel Steinfort
- Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia
- Department of Respiratory and Sleep Medicine, Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | - Henry Marshall
- Thoracic Research Centre, University of Queensland, Chermside, Queensland, Australia
- Department of Thoracic Medicine, The Prince Charles Hospital, Chermside, Queensland, Australia
| | - Jeremy D Silver
- Statistical Consulting Centre, School of Mathematics and Statistics, University of Melbourne, Melbourne, Victoria, Australia
| | - Cheng Xie
- Department of Respiratory and Sleep Medicine, Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | - Sally Yang
- Department of Respiratory and Sleep Medicine, Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | - Jack Watson
- Department of Respiratory and Sleep Medicine, Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | - Paul Fogarty
- Respiratory Department, Epworth Eastern Hospital, Box Hill, Victoria, Australia
| | - Emily Stone
- Department of Thoracic Medicine and Lung Transplantation, St Vincent's Hospital, Darlinghurst, New South Wales, Australia
- University of New South Wales, School of Clinical Medicine, St Vincent's Clinical School; School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Fraser Brims
- Department of Respiratory Medicine, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- Curtin Medical School, Curtin University, Bentley, Western Australia, Australia
- National Centre for Asbestos Related Diseases, Institute for Respiratory Health, Nedlands, Western Australia, Australia
| | - Annette McWilliams
- Department of Respiratory Medicine, Fiona Stanley Hospital, Murdoch, Western Australia, Australia
- Department of Medicine, University of Western Australia, Nedlands, Western Australia, Australia
| | - XinXin Hu
- Department of Thoracic Medicine and Lung Transplantation, St Vincent's Hospital, Darlinghurst, New South Wales, Australia
| | - Christopher Rofe
- Department of Thoracic Medicine and Lung Transplantation, St Vincent's Hospital, Darlinghurst, New South Wales, Australia
| | - Brad Milner
- Department of Thoracic Medicine and Lung Transplantation, St Vincent's Hospital, Darlinghurst, New South Wales, Australia
| | - Stephen Lam
- Department of Medicine, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Kwun M Fong
- Thoracic Research Centre, University of Queensland, Chermside, Queensland, Australia
- Department of Thoracic Medicine, The Prince Charles Hospital, Chermside, Queensland, Australia
| | - Renee Manser
- Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia
- Department of Respiratory and Sleep Medicine, Royal Melbourne Hospital, Melbourne, Victoria, Australia
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8
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Leong TL. Bringing down two Goliaths with one stone: Reducing lung cancer and cardiovascular mortality with low-dose CT screening. Respirology 2025; 30:18-20. [PMID: 39632103 DOI: 10.1111/resp.14860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2024] [Accepted: 11/19/2024] [Indexed: 12/07/2024]
Abstract
See related article
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Affiliation(s)
- Tracy L Leong
- Department of Respiratory Medicine, Austin Health, Heidelberg, Victoria, Australia
- Olivia Newton-John Cancer Research Institute, Heidelberg, Victoria, Australia
- University of Melbourne, Melbourne, Victoria, Australia
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Fathi JT, Barry AM, Greenberg GM, Henschke CI, Kazerooni EA, Kim JJ, Mazzone PJ, Mulshine JL, Pyenson BS, Shockney LD, Smith RA, Wiener RS, White CS, Thomson CC. The American Cancer Society National Lung Cancer Roundtable strategic plan: Implementation of high-quality lung cancer screening. Cancer 2024; 130:3961-3972. [PMID: 39302235 DOI: 10.1002/cncr.34621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/22/2024]
Abstract
More than a decade has passed since researchers in the Early Lung Cancer Action Project and the National Lung Screening Trial demonstrated the ability to save lives of high-risk individuals from lung cancer through regular screening by low dose computed tomography scan. The emergence of the most recent findings in the Dutch-Belgian lung-cancer screening trial (Nederlands-Leuvens Longkanker Screenings Onderzoek [NELSON]) further strengthens and expands on this evidence. These studies demonstrate the benefit of integrating lung cancer screening into clinical practice, yet lung cancer continues to lead cancer mortality rates in the United States. Fewer than 20% of screen eligible individuals are enrolled in lung cancer screening, leaving millions of qualified individuals without the standard of care and benefit they deserve. This article, part of the American Cancer Society National Lung Cancer Roundtable (ACS NLCRT) strategic plan, examines the impediments to successful adoption, dissemination, and implementation of lung cancer screening. Proposed solutions identified by the ACS NLCRT Implementation Strategies Task Group and work currently underway to address these challenges to improve uptake of lung cancer screening are discussed. PLAIN LANGUAGE SUMMARY: The evidence supporting the benefit of lung cancer screening in adults who previously or currently smoke has led to widespread endorsement and coverage by health plans. Lung cancer screening programs should be designed to promote high uptake rates of screening among eligible adults, and to deliver high-quality screening and follow-up care.
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Affiliation(s)
- Joelle T Fathi
- Department of Biobehavioral Nursing and Health Informatics, School of Nursing, University of Washington, Seattle, Washington, USA
- GO2 for Lung Cancer, Washington, District of Columbia, USA
| | - Angela M Barry
- GO2 for Lung Cancer, Washington, District of Columbia, USA
| | - Grant M Greenberg
- Department of Family Medicine, Lehigh Valley Health Network, Allentown, Pennsylvania, USA
| | - Claudia I Henschke
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Phoenix Veterans Health Care System, Phoenix, Arizona, USA
| | - Ella A Kazerooni
- Department of Radiology, Michigan Medicine/University of Michigan, Ann Arbor, Michigan, USA
- Department of Internal Medicine, Michigan Medicine/University of Michigan, Ann Arbor, Michigan, USA
| | - Jane J Kim
- Department of Veterans Affairs, National Center for Health Promotion and Disease Prevention, Durham, North Carolina, USA
| | - Peter J Mazzone
- Respiratory Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - James L Mulshine
- Department of Internal Medicine, Rush University Medical College, Chicago, Illinois, USA
| | | | - Lillie D Shockney
- Surgical Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Robert A Smith
- Center for Early Cancer Detection Science, American Cancer Society, Atlanta, Georgia, USA
| | - Renda Soylemez Wiener
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, The Pulmonary Center, Boston University School of Medicine, Boston, Massachusetts, USA
| | - Charles S White
- Department of Radiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Carey C Thomson
- Department of Medicine, Division of Pulmonary and Critical Care, Mount Auburn Hospital/Beth Israel Lahey Health, Cambridge, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
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10
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Waite S, Davenport MS, Graber ML, Banja JD, Sheppard B, Bruno MA. Opportunity and Opportunism in Artificial Intelligence-Powered Data Extraction: A Value-Centered Approach. AJR Am J Roentgenol 2024; 223:e2431686. [PMID: 39291941 DOI: 10.2214/ajr.24.31686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/19/2024]
Abstract
Radiologists' traditional role in the diagnostic process is to respond to specific clinical questions and reduce uncertainty enough to permit treatment decisions to be made. This charge is rapidly evolving due to forces such as artificial intelligence (AI), big data (opportunistic imaging, imaging prognostication), and advanced diagnostic technologies. A new modernistic paradigm is emerging whereby radiologists, in conjunction with computer algorithms, will be tasked with extracting as much information from imaging data as possible, often without a specific clinical question being posed and independent of any stated clinical need. In addition, AI algorithms are increasingly able to predict long-term outcomes using data from seemingly normal examinations, enabling AI-assisted prognostication. As these algorithms become a standard component of radiology practice, the sheer amount of information they demand will increase the need for streamlined workflows, communication, and data management techniques. In addition, the provision of such information raises reimbursement, liability, and access issues. Guidelines will be needed to ensure that all patients have access to the benefits of this new technology and guarantee that mined data do not inadvertently create harm. In this Review, we discuss the challenges and opportunities relevant to radiologists in this changing landscape, with an emphasis on ensuring that radiologists provide high-value care.
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Affiliation(s)
- Stephen Waite
- Departments of Radiology and Internal Medicine, SUNY Downstate Medical Center, 450 Clarkson Ave, Brooklyn, NY 11203
| | - Matthew S Davenport
- Departments of Radiology and Urology, Ronald Weiser Center for Prostate Cancer, Michigan Medicine, Ann Arbor, MI
| | - Mark L Graber
- Department of Internal Medicine, Stony Brook University, Stony Brook, NY
| | - John D Banja
- Department of Rehabilitation Medicine and Center for Ethics, Emory University, Atlanta, GA
| | | | - Michael A Bruno
- Departments of Radiology and Medicine, Penn State Milton S. Hershey Medical Center, Hershey, PA
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11
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Labaki WW, Agusti A, Bhatt SP, Bodduluri S, Criner GJ, Fabbri LM, Halpin DMG, Lynch DA, Mannino DM, Miravitlles M, Papi A, Sin DD, Washko GR, Kazerooni EA, Han MK. Leveraging Computed Tomography Imaging to Detect Chronic Obstructive Pulmonary Disease and Concomitant Chronic Diseases. Am J Respir Crit Care Med 2024; 210:281-287. [PMID: 38843079 PMCID: PMC11348973 DOI: 10.1164/rccm.202402-0407pp] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Accepted: 06/04/2024] [Indexed: 08/02/2024] Open
Affiliation(s)
| | - Alvar Agusti
- Cathedra Salut Respiratoria, University of Barcelona, Barcelona, Spain
- Pulmonary Service, Respiratory Institute, Clinic Barcelona, Barcelona, Spain
- Fundació Clinic, Institut d’Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, Barcelona, Spain
| | - Surya P. Bhatt
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - Sandeep Bodduluri
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - Gerard J. Criner
- Department of Thoracic Medicine and Surgery, Lewis Katz School of Medicine at Temple University, Philadelphia, Pennsylvania
| | | | - David M. G. Halpin
- Respiratory Medicine, University of Exeter Medical School, Exeter, United Kingdom
| | - David A. Lynch
- Department of Radiology, National Jewish Health, Denver, Colorado
| | - David M. Mannino
- Department of Medicine, University of Kentucky, Lexington, Kentucky
| | - Marc Miravitlles
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, Barcelona, Spain
- Neumología, Hospital Universitari Vall d’Hebron/Vall d’Hebron Institut de Recerca, Barcelona, Spain
| | - Alberto Papi
- Section of Respiratory Medicine, University of Ferrara, Ferrara, Italy
| | - Don D. Sin
- Centre for Heart Lung Innovation, St. Paul’s Hospital and University of British Columbia, Vancouver, British Columbia, Canada
- Division of Respiratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - George R. Washko
- Division of Pulmonary and Critical Care Medicine and
- Applied Chest Imaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Ella A. Kazerooni
- Division of Pulmonary and Critical Care Medicine and
- Department of Radiology, University of Michigan, Ann Arbor, Michigan
| | - MeiLan K. Han
- Division of Pulmonary and Critical Care Medicine and
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12
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Lin Y, Khurelsukh K, Li IG, Wu CT, Wu YM, Lin G, Toh CH, Wan YL. Incidental Findings in Lung Cancer Screening. Cancers (Basel) 2024; 16:2600. [PMID: 39061238 PMCID: PMC11274500 DOI: 10.3390/cancers16142600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2024] [Revised: 07/18/2024] [Accepted: 07/19/2024] [Indexed: 07/28/2024] Open
Abstract
While low-dose computed tomography (LDCT) for lung cancer screening (LCS) has been recognized for its effectiveness in reducing lung cancer mortality, it often simultaneously leads to the detection of incidental findings (IFs) unrelated to the primary screening indication. These IFs present diagnostic and management challenges, potentially causing unnecessary anxiety and further invasive diagnostic procedures for patients. This review article provides an overview of IFs encountered in LDCT, emphasizing their clinical significance and recommended management strategies. We categorize IFs based on their anatomical locations (intrathoracic-intrapulmonary, intrathoracic-extrapulmonary, and extrathoracic) and discuss the most common findings. We highlight the importance of utilizing guidelines and standardized reporting systems by the American College of Radiology (ACR) to guide appropriate follow-ups. For each category, we present specific IF examples, their radiologic features, and the suggested management approach. This review aims to provide radiologists and clinicians with a comprehensive understanding of IFs in LCS for accurate assessment and management, ultimately enhancing patient care. Finally, we outline a few key aspects for future research and development in managing IFs.
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Affiliation(s)
- Yenpo Lin
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan City 333, Taiwan; (Y.L.); (C.-T.W.); (Y.-M.W.); (G.L.); (C.-H.T.)
| | - Khulan Khurelsukh
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan City 333, Taiwan;
| | - I-Gung Li
- Department of Medical Imaging and Intervention, New Taipei Municipal Tucheng Hospital, New Taipei City 236, Taiwan;
| | - Chen-Te Wu
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan City 333, Taiwan; (Y.L.); (C.-T.W.); (Y.-M.W.); (G.L.); (C.-H.T.)
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan City 333, Taiwan;
| | - Yi-Ming Wu
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan City 333, Taiwan; (Y.L.); (C.-T.W.); (Y.-M.W.); (G.L.); (C.-H.T.)
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan City 333, Taiwan;
| | - Gigin Lin
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan City 333, Taiwan; (Y.L.); (C.-T.W.); (Y.-M.W.); (G.L.); (C.-H.T.)
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan City 333, Taiwan;
| | - Cheng-Hong Toh
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan City 333, Taiwan; (Y.L.); (C.-T.W.); (Y.-M.W.); (G.L.); (C.-H.T.)
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan City 333, Taiwan;
| | - Yung-Liang Wan
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan City 333, Taiwan; (Y.L.); (C.-T.W.); (Y.-M.W.); (G.L.); (C.-H.T.)
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan City 333, Taiwan;
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13
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Jhala K, Byrne SC, Hammer MM. Interpreting Lung Cancer Screening CTs: Practical Approach to Lung Cancer Screening and Application of Lung-RADS. Clin Chest Med 2024; 45:279-293. [PMID: 38816088 DOI: 10.1016/j.ccm.2023.08.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2024]
Abstract
Lung cancer screening via low-dose computed tomography (CT) reduces mortality from lung cancer, and eligibility criteria have recently been expanded to include patients aged 50 to 80 with at least 20 pack-years of smoking history. Lung cancer screening CTs should be interepreted with use of Lung Imaging Reporting and Data System (Lung-RADS), a reporting guideline system that accounts for nodule size, density, and growth. The revised version of Lung-RADS includes several important changes, such as expansion of the definition of juxtapleural nodules, discussion of atypical pulmonary cysts, and stepped management for suspicious nodules. By using Lung-RADS, radiologists and clinicians can adopt a uniform approach to nodules detected during CT lung cancer screening and reduce false positives.
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Affiliation(s)
- Khushboo Jhala
- Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02215, USA
| | - Suzanne C Byrne
- Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02215, USA
| | - Mark M Hammer
- Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02215, USA.
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14
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Park C, Lee BC, Jeong WG, Park WJ, Jin GY, Kim YH. Coronary Artery Calcification on Low-Dose Lung Cancer Screening CT in South Korea: Visual and Artificial Intelligence-Based Assessment and Association With Cardiovascular Events. AJR Am J Roentgenol 2024; 222:e2430852. [PMID: 38447024 DOI: 10.2214/ajr.24.30852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
BACKGROUND. Coronary artery calcification (CAC) on lung cancer screening low-dose chest CT (LDCT) is a cardiovascular risk marker. South Korea was the first Asian country to initiate a national LDCT lung cancer screening program, although CAC-related outcomes are poorly explored. OBJECTIVE. The purpose of this article is to evaluate CAC prevalence and severity using visual analysis and artificial intelligence (AI) methods and to characterize CAC's association with major adverse cardiovascular events (MACEs) in patients undergoing LDCT in Korea's national lung cancer screening program. METHODS. This retrospective study included 1002 patients (mean age, 62.4 ± 5.4 [SD] years; 994 men, eight women) who underwent LDCT at two Korean medical centers between April 2017 and May 2023 as part of Korea's national lung cancer screening program. Two radiologists independently assessed CAC presence and severity using visual analysis, consulting a third radiologist to resolve differences. Two AI software applications were also used to assess CAC presence and severity. MACE occurrences were identified by EMR review. RESULTS. Interreader agreement for CAC presence and severity, expressed as kappa, was 0.793 and 0.671, respectively. CAC prevalence was 53.4% by consensus visual assessment, 60.1% by AI software I, and 56.6% by AI software II. CAC severity was mild, moderate, and severe by consensus visual analysis in 28.0%, 10.3%, and 15.1%; by AI software I in 39.9%, 14.0%, and 6.2%; and by AI software II in 34.9%, 14.3%, and 7.3%. MACEs occurred in 36 of 625 (5.6%) patients with follow-up after LDCT (median, 1108 days). MACE incidence in patients with no, mild, moderate, and severe CAC for consensus visual analysis was 1.1%, 5.0%, 2.9%, and 8.6%, respectively (p < .001); for AI software I, it was 1.3%, 3.0%, 7.9%, and 11.3% (p < .001); and for AI software II, it was 1.2%, 3.4%, 7.7%, and 9.6% (p < .001). CONCLUSION. For Korea's national lung cancer screening program, MACE occurrence increased significantly with increasing CAC severity, whether assessed by visual analysis or AI software. The study is limited by the large sex imbalance for Korea's national lung cancer screening program. CLINICAL IMPACT. The findings provide reference data for health care practitioners engaged in developing and overseeing national lung cancer screening programs, highlighting the importance of routine CAC evaluation.
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Affiliation(s)
- Chan Park
- Department of Radiology, Chonnam National University Hospital and Chonnam National University Medical School, Gwangju, Republic of Korea
| | - Byung Chan Lee
- Department of Radiology, Chonnam National University Hwasun Hospital and Chonnam National University Medical School, 322 Seoyang-ro, Hwasun-eup, Hwasun-gun, Jeollanam-do, Republic of Korea 58128
| | - Won Gi Jeong
- Department of Radiology, Chonnam National University Hwasun Hospital and Chonnam National University Medical School, 322 Seoyang-ro, Hwasun-eup, Hwasun-gun, Jeollanam-do, Republic of Korea 58128
| | - Won-Ju Park
- Department of Occupational and Environmental Medicine, Chonnam National University Medical School, Chonnam National University Hwasun Hospital, Hwasun-eup, Hwasun-gun, Jeollanam-do, Republic of Korea
| | - Gong Yong Jin
- Department of Radiology, Research Institute of Clinical Medicine, Jeonbuk National University-Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju, Republic of Korea
| | - Yun-Hyeon Kim
- Department of Radiology, Chonnam National University Hospital and Chonnam National University Medical School, Gwangju, Republic of Korea
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15
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Christensen J, Prosper AE, Wu CC, Chung J, Lee E, Elicker B, Hunsaker AR, Petranovic M, Sandler KL, Stiles B, Mazzone P, Yankelevitz D, Aberle D, Chiles C, Kazerooni E. ACR Lung-RADS v2022: Assessment Categories and Management Recommendations. J Am Coll Radiol 2024; 21:473-488. [PMID: 37820837 DOI: 10.1016/j.jacr.2023.09.009] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 08/08/2023] [Accepted: 09/21/2023] [Indexed: 10/13/2023]
Abstract
The ACR created the Lung CT Screening Reporting and Data System (Lung-RADS) in 2014 to standardize the reporting and management of screen-detected pulmonary nodules. Lung-RADS was updated to version 1.1 in 2019 and revised size thresholds for nonsolid nodules, added classification criteria for perifissural nodules, and allowed for short-interval follow-up of rapidly enlarging nodules that may be infectious in etiology. Lung-RADS v2022, released in November 2022, provides several updates including guidance on the classification and management of atypical pulmonary cysts, juxtapleural nodules, airway-centered nodules, and potentially infectious findings. This new release also provides clarification for determining nodule growth and introduces stepped management for nodules that are stable or decreasing in size. This article summarizes the current evidence and expert consensus supporting Lung-RADS v2022.
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Affiliation(s)
- Jared Christensen
- Vice Chair and Professor of Radiology, Department of Radiology, Duke University, Durham, North Carolina; Chair, ACR Lung-RADS Committee.
| | - Ashley Elizabeth Prosper
- Assistant Professor and Section Chief of Cardiothoracic Imaging, Department of Radiological Sciences, University of California, Los Angeles, California
| | - Carol C Wu
- Professor of Diagnostic Imaging, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jonathan Chung
- Professor of Radiology Vice Chair of Quality Section Chief of Cardiopulmonary Imaging, University of Chicago, Chicago, Illinois
| | - Elizabeth Lee
- Clinical Associate Professor, Radiology, Michigan Medicine, Ann Arbor, Michigan
| | - Brett Elicker
- Chief of the Cardiac & Pulmonary Imaging Section, University of California, San Francisco, California
| | - Andetta R Hunsaker
- Brigham and Women's Hospital, Boston, Massachusetts; Associate Professor Harvard Medical School Chief Division of Thoracic Imaging
| | - Milena Petranovic
- Instructor, Radiology, Harvard Medical School Divisional Quality Director, Thoracic Imaging and Intervention, Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Kim L Sandler
- Associate Professor, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Brendon Stiles
- Professor and Chair, Thoracic Surgery and Surgical Oncology, Montefiore Health System, Albert Einstein College of Medicine, Bronx, New York
| | | | | | - Denise Aberle
- Professor of Radiology, Department of Radiological Sciences; David Geffen School of Medicine at UCLA, Los Angeles, California
| | - Caroline Chiles
- Professor of Radiology Director, Lung Screening Program, Atrium Health Wake Forest, Winston-Salem, North Carolina
| | - Ella Kazerooni
- Professor of Radiology & Internal Medicine and Associate Chief Clinical Officer for Diagnostics, Michigan Medicine/University of Michigan Medical School, Ann Arbor, Michigan; Clinical Information Management, University of Michigan Medical Group
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16
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Christensen J, Prosper AE, Wu CC, Chung J, Lee E, Elicker B, Hunsaker AR, Petranovic M, Sandler KL, Stiles B, Mazzone P, Yankelevitz D, Aberle D, Chiles C, Kazerooni E. ACR Lung-RADS v2022: Assessment Categories and Management Recommendations. Chest 2024; 165:738-753. [PMID: 38300206 DOI: 10.1016/j.chest.2023.10.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2024] Open
Abstract
The American College of Radiology created the Lung CT Screening Reporting and Data System (Lung-RADS) in 2014 to standardize the reporting and management of screen-detected pulmonary nodules. Lung-RADS was updated to version 1.1 in 2019 and revised size thresholds for nonsolid nodules, added classification criteria for perifissural nodules, and allowed for short-interval follow-up of rapidly enlarging nodules that may be infectious in etiology. Lung-RADS v2022, released in November 2022, provides several updates including guidance on the classification and management of atypical pulmonary cysts, juxtapleural nodules, airway-centered nodules, and potentially infectious findings. This new release also provides clarification for determining nodule growth and introduces stepped management for nodules that are stable or decreasing in size. This article summarizes the current evidence and expert consensus supporting Lung-RADS v2022.
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Affiliation(s)
- Jared Christensen
- Vice Chair and Professor of Radiology, Department of Radiology, Duke University, Durham, North Carolina; Chair, ACR Lung-RADS Committee.
| | - Ashley Elizabeth Prosper
- Assistant Professor and Section Chief of Cardiothoracic Imaging, Department of Radiological Sciences, University of California, Los Angeles, California
| | - Carol C Wu
- Professor of Diagnostic Imaging, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jonathan Chung
- Professor of Radiology Vice Chair of Quality Section Chief of Cardiopulmonary Imaging, University of Chicago, Chicago, Illinois
| | - Elizabeth Lee
- Clinical Associate Professor, Radiology, Michigan Medicine, Ann Arbor, Michigan
| | - Brett Elicker
- Chief of the Cardiac & Pulmonary Imaging Section, University of California, San Francisco, California
| | - Andetta R Hunsaker
- Brigham and Women's Hospital, Boston, Massachusetts; Associate Professor Harvard Medical School Chief Division of Thoracic Imaging
| | - Milena Petranovic
- Instructor, Radiology, Harvard Medical School Divisional Quality Director, Thoracic Imaging and Intervention, Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Kim L Sandler
- Associate Professor, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Brendon Stiles
- Professor and Chair, Thoracic Surgery and Surgical Oncology, Montefiore Health System, Albert Einstein College of Medicine, Bronx, New York
| | | | | | - Denise Aberle
- Professor of Radiology, Department of Radiological Sciences; David Geffen School of Medicine at UCLA, Los Angeles, California
| | - Caroline Chiles
- Professor of Radiology Director, Lung Screening Program, Atrium Health Wake Forest, Winston-Salem, North Carolina
| | - Ella Kazerooni
- Professor of Radiology & Internal Medicine and Associate Chief Clinical Officer for Diagnostics, Michigan Medicine/University of Michigan Medical School, Ann Arbor, Michigan; Clinical Information Management, University of Michigan Medical Group
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17
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Wolf AMD, Oeffinger KC, Shih TYC, Walter LC, Church TR, Fontham ETH, Elkin EB, Etzioni RD, Guerra CE, Perkins RB, Kondo KK, Kratzer TB, Manassaram-Baptiste D, Dahut WL, Smith RA. Screening for lung cancer: 2023 guideline update from the American Cancer Society. CA Cancer J Clin 2024; 74:50-81. [PMID: 37909877 DOI: 10.3322/caac.21811] [Citation(s) in RCA: 93] [Impact Index Per Article: 93.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Accepted: 09/14/2023] [Indexed: 11/03/2023] Open
Abstract
Lung cancer is the leading cause of mortality and person-years of life lost from cancer among US men and women. Early detection has been shown to be associated with reduced lung cancer mortality. Our objective was to update the American Cancer Society (ACS) 2013 lung cancer screening (LCS) guideline for adults at high risk for lung cancer. The guideline is intended to provide guidance for screening to health care providers and their patients who are at high risk for lung cancer due to a history of smoking. The ACS Guideline Development Group (GDG) utilized a systematic review of the LCS literature commissioned for the US Preventive Services Task Force 2021 LCS recommendation update; a second systematic review of lung cancer risk associated with years since quitting smoking (YSQ); literature published since 2021; two Cancer Intervention and Surveillance Modeling Network-validated lung cancer models to assess the benefits and harms of screening; an epidemiologic and modeling analysis examining the effect of YSQ and aging on lung cancer risk; and an updated analysis of benefit-to-radiation-risk ratios from LCS and follow-up examinations. The GDG also examined disease burden data from the National Cancer Institute's Surveillance, Epidemiology, and End Results program. Formulation of recommendations was based on the quality of the evidence and judgment (incorporating values and preferences) about the balance of benefits and harms. The GDG judged that the overall evidence was moderate and sufficient to support a strong recommendation for screening individuals who meet the eligibility criteria. LCS in men and women aged 50-80 years is associated with a reduction in lung cancer deaths across a range of study designs, and inferential evidence supports LCS for men and women older than 80 years who are in good health. The ACS recommends annual LCS with low-dose computed tomography for asymptomatic individuals aged 50-80 years who currently smoke or formerly smoked and have a ≥20 pack-year smoking history (strong recommendation, moderate quality of evidence). Before the decision is made to initiate LCS, individuals should engage in a shared decision-making discussion with a qualified health professional. For individuals who formerly smoked, the number of YSQ is not an eligibility criterion to begin or to stop screening. Individuals who currently smoke should receive counseling to quit and be connected to cessation resources. Individuals with comorbid conditions that substantially limit life expectancy should not be screened. These recommendations should be considered by health care providers and adults at high risk for lung cancer in discussions about LCS. If fully implemented, these recommendations have a high likelihood of significantly reducing death and suffering from lung cancer in the United States.
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Affiliation(s)
- Andrew M D Wolf
- University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Kevin C Oeffinger
- Department of Medicine, Duke University School of Medicine and Duke Cancer Institute Center for Onco-Primary Care, Durham, North Carolina, USA
| | - Tina Ya-Chen Shih
- David Geffen School of Medicine and Jonsson Comprehensive Cancer Center, University of California Los Angeles, Los Angeles, California, USA
| | - Louise C Walter
- Department of Medicine, University of California San Francisco and San Francisco Veterans Affairs Medical Center, San Francisco, California, USA
| | - Timothy R Church
- Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota, USA
| | - Elizabeth T H Fontham
- Health Sciences Center, School of Public Health, Louisiana State University, New Orleans, Louisiana, USA
| | - Elena B Elkin
- Department of Health Policy and Management, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Ruth D Etzioni
- Fred Hutchinson Cancer Research Center, University of Washington, Seattle, Washington, USA
| | - Carmen E Guerra
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Rebecca B Perkins
- Obstetrics and Gynecology, Boston University Chobanian and Avedisian School of Medicine, Boston, Massachusetts, USA
| | - Karli K Kondo
- Early Cancer Detection Science, American Cancer Society, Atlanta, Georgia, USA
| | - Tyler B Kratzer
- Cancer Surveillance and Health Equity Science, American Cancer Society, Atlanta, Georgia, USA
| | | | | | - Robert A Smith
- Early Cancer Detection Science, American Cancer Society, Atlanta, Georgia, USA
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18
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Lam S, Bai C, Baldwin DR, Chen Y, Connolly C, de Koning H, Heuvelmans MA, Hu P, Kazerooni EA, Lancaster HL, Langs G, McWilliams A, Osarogiagbon RU, Oudkerk M, Peters M, Robbins HA, Sahar L, Smith RA, Triphuridet N, Field J. Current and Future Perspectives on Computed Tomography Screening for Lung Cancer: A Roadmap From 2023 to 2027 From the International Association for the Study of Lung Cancer. J Thorac Oncol 2024; 19:36-51. [PMID: 37487906 PMCID: PMC11253723 DOI: 10.1016/j.jtho.2023.07.019] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 06/13/2023] [Accepted: 07/18/2023] [Indexed: 07/26/2023]
Abstract
Low-dose computed tomography (LDCT) screening for lung cancer substantially reduces mortality from lung cancer, as revealed in randomized controlled trials and meta-analyses. This review is based on the ninth CT screening symposium of the International Association for the Study of Lung Cancer, which focuses on the major themes pertinent to the successful global implementation of LDCT screening and develops a strategy to further the implementation of lung cancer screening globally. These recommendations provide a 5-year roadmap to advance the implementation of LDCT screening globally, including the following: (1) establish universal screening program quality indicators; (2) establish evidence-based criteria to identify individuals who have never smoked but are at high-risk of developing lung cancer; (3) develop recommendations for incidentally detected lung nodule tracking and management protocols to complement programmatic lung cancer screening; (4) Integrate artificial intelligence and biomarkers to increase the prediction of malignancy in suspicious CT screen-detected lesions; and (5) standardize high-quality performance artificial intelligence protocols that lead to substantial reductions in costs, resource utilization and radiologist reporting time; (6) personalize CT screening intervals on the basis of an individual's lung cancer risk; (7) develop evidence to support clinical management and cost-effectiveness of other identified abnormalities on a lung cancer screening CT; (8) develop publicly accessible, easy-to-use geospatial tools to plan and monitor equitable access to screening services; and (9) establish a global shared education resource for lung cancer screening CT to ensure high-quality reading and reporting.
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Affiliation(s)
- Stephen Lam
- Department of Integrative Oncology, British Columbia Cancer Research Institute, Vancouver, British Columbia, Canada; Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.
| | - Chunxue Bai
- Shanghai Respiratory Research Institute and Chinese Alliance Against Cancer, Shanghai, People's Republic of China
| | - David R Baldwin
- Nottingham University Hospitals National Health Services (NHS) Trust, Nottingham, United Kingdom
| | - Yan Chen
- Digital Screening, Faculty of Medicine & Health Sciences, University of Nottingham Medical School, Nottingham, United Kingdom
| | - Casey Connolly
- International Association for the Study of Lung Cancer, Denver, Colorado
| | - Harry de Koning
- Department of Public Health, Erasmus MC University Medical Centre Rotterdam, The Netherlands
| | - Marjolein A Heuvelmans
- University of Groningen, Groningen, The Netherlands; Department of Epidemiology, University Medical Center Groningen, Groningen, The Netherlands; The Institute for Diagnostic Accuracy, Groningen, The Netherlands
| | - Ping Hu
- Division of Cancer Prevention, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Ella A Kazerooni
- Division of Cardiothoracic Radiology, Department of Radiology, University of Michigan Medical School, Ann Arbor, Michigan; Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan
| | - Harriet L Lancaster
- University of Groningen, Groningen, The Netherlands; Department of Epidemiology, University Medical Center Groningen, Groningen, The Netherlands; The Institute for Diagnostic Accuracy, Groningen, The Netherlands
| | - Georg Langs
- Computational Imaging Research Laboratory, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Annette McWilliams
- Department of Respiratory Medicine, Fiona Stanley Hospital, Murdoch, Western Australia, Australia; Australia University of Western Australia, Nedlands, Western Australia
| | | | - Matthijs Oudkerk
- Center for Medical Imaging and The Institute for Diagnostic Accuracy, Faculty of Medical Sciences, University of Groningen, Groningen, The Netherlands
| | - Matthew Peters
- Woolcock Institute of Respiratory Medicine, Macquarie University, Sydney, New South Wales, Australia
| | - Hilary A Robbins
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
| | - Liora Sahar
- Data Science, American Cancer Society, Atlanta, Georgia
| | - Robert A Smith
- Early Cancer Detection Science, American Cancer Society, Atlanta, Georgia
| | | | - John Field
- Department of Molecular and Clinical Cancer Medicine, The University of Liverpool, Liverpool, United Kingdom
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19
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Melzer AC, Atoma B, Fabbrini AE, Campbell M, Clothier BA, Fu SS. Variation in Reporting of Incidental Findings on Initial Lung Cancer Screening and Associations With Clinician Assessment. J Am Coll Radiol 2024; 21:118-127. [PMID: 37516160 PMCID: PMC11155613 DOI: 10.1016/j.jacr.2023.03.023] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 03/22/2023] [Accepted: 03/27/2023] [Indexed: 07/31/2023]
Abstract
PURPOSE The aim of this study was to quantify the distribution, frequency, and clinical significance of incidental findings (IFs) on initial lung cancer screening (LCS) and the association of report characteristics with subsequent assessment. METHODS Health records of patients undergoing initial LCS from 2015 to 2018 in the Minneapolis VA Health Care System were retrospectively reviewed for demographics, Lung CT Screening Reporting & Data System coding, IFs, and subsequent clinical assessment. IFs were considered potentially significant if they were likely to require any follow-up. High-risk significant IFs (SIFs) were potentially malignant. The primary outcome was the SIF being addressed. Outcomes were analyzed using a mixed-effects model. RESULTS Patients (n = 901) were primarily male (94.1%) smokers (62.1%) with a mean age of 65.2 years. IFs were extremely common (93.9%), with an average of 2.6 IFs per scan (n = 2,296). Seven hundred eighty-six IFs (34.2%) were deemed likely SIFs, of which 58 (7.4%) were high risk. Two hundred twenty-two (28.2%) were addressed by clinicians, of which 104 (13.2%) underwent testing. Reporting of SIFs varied among radiologists, with at least one SIF in the impression in 24% to 78% of low-dose CT studies with the S modifier, used to indicate the presence of a SIF, applied to 0% to 51% of reports. In the mutually adjusted model, radiologist recommendation (adjusted odds ratio [OR], 4.67; 95% confidence interval [CI], 2.23-9.76), high-risk finding (adjusted OR, 4.35; 95% CI, 1.81-10.45), and reporting in the impression (adjusted OR, 2.58; 95% CI, 1.28-5.18) were associated with increased odds of the SIF's being addressed. CONCLUSIONS Radiologists vary in their reporting of IFs on LCS. Further standardization of reporting of SIFs may improve this process, with the simultaneous goals of generating appropriate testing when needed and minimizing low-value care.
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Affiliation(s)
- Anne C Melzer
- Medical Director of Lung Cancer Screening, Center for Care Delivery and Outcomes Research, Minneapolis VA Health Care System, Minneapolis, Minnesota; Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Minnesota Medical School, Minneapolis, Minnesota; Department of Medicine, University of Minnesota Medical School, Minneapolis, Minnesota.
| | - Bethlehem Atoma
- Department of Medicine, University of Minnesota Medical School, Minneapolis, Minnesota
| | - Angela E Fabbrini
- Program Manager, National Center for Lung Cancer Screening, Minneapolis VA Health Care System, Minneapolis, Minnesota
| | - Megan Campbell
- Center for Care Delivery and Outcomes Research, Minneapolis VA Health Care System, Minneapolis, Minnesota
| | - Barbara A Clothier
- Center for Care Delivery and Outcomes Research, Minneapolis VA Health Care System, Minneapolis, Minnesota
| | - Steven S Fu
- Department of Medicine, University of Minnesota Medical School, Minneapolis, Minnesota; Director, Center for Care Delivery and Outcomes Research, Minneapolis VA Health Care System, Minneapolis, Minnesota
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20
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Martin MD, Kanne JP, Broderick LS, Kazerooni EA, Meyer CA. RadioGraphics Update: Lung-RADS 2022. Radiographics 2023; 43:e230037. [PMID: 37856315 DOI: 10.1148/rg.230037] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2023]
Abstract
Editor's Note.-RadioGraphics Update articles supplement or update information found in full-length articles previously published in RadioGraphics. These updates, written by at least one author of the previous article, provide a brief synopsis that emphasizes important new information such as technological advances, revised imaging protocols, new clinical guidelines involving imaging, or updated classification schemes.
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Affiliation(s)
- Maria D Martin
- From the Department of Radiology, University of Wisconsin School of Medicine, 600 Highland Ave, Madison, WI 53792-3252 (M.D.M., J.P.K., L.S.B., C.A.M.); and Department of Radiology, University of Michigan Health System, Ann Arbor, Mich (E.A.K.)
| | - Jeffrey P Kanne
- From the Department of Radiology, University of Wisconsin School of Medicine, 600 Highland Ave, Madison, WI 53792-3252 (M.D.M., J.P.K., L.S.B., C.A.M.); and Department of Radiology, University of Michigan Health System, Ann Arbor, Mich (E.A.K.)
| | - Lynn S Broderick
- From the Department of Radiology, University of Wisconsin School of Medicine, 600 Highland Ave, Madison, WI 53792-3252 (M.D.M., J.P.K., L.S.B., C.A.M.); and Department of Radiology, University of Michigan Health System, Ann Arbor, Mich (E.A.K.)
| | - Ella A Kazerooni
- From the Department of Radiology, University of Wisconsin School of Medicine, 600 Highland Ave, Madison, WI 53792-3252 (M.D.M., J.P.K., L.S.B., C.A.M.); and Department of Radiology, University of Michigan Health System, Ann Arbor, Mich (E.A.K.)
| | - Cristopher A Meyer
- From the Department of Radiology, University of Wisconsin School of Medicine, 600 Highland Ave, Madison, WI 53792-3252 (M.D.M., J.P.K., L.S.B., C.A.M.); and Department of Radiology, University of Michigan Health System, Ann Arbor, Mich (E.A.K.)
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21
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Catarata MJ, Van Geffen WH, Banka R, Ferraz B, Sidhu C, Carew A, Viola L, Gijtenbeek R, Hardavella G. ERS International Congress 2022: highlights from the Thoracic Oncology Assembly. ERJ Open Res 2023; 9:00579-2022. [PMID: 37583965 PMCID: PMC10423989 DOI: 10.1183/23120541.00579-2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 05/31/2023] [Indexed: 08/17/2023] Open
Abstract
Thoracic malignancies are associated with a substantial public health burden. Lung cancer is the leading cause of cancer-related mortality worldwide, with significant impact on patients' quality of life. Following 2 years of virtual European Respiratory Society (ERS) Congresses due to the COVID-19 pandemic, the 2022 hybrid ERS Congress in Barcelona, Spain allowed peers from all over the world to meet again and present their work. Thoracic oncology experts presented best practices and latest developments in lung cancer screening, lung cancer diagnosis and management. Early lung cancer diagnosis, subsequent pros and cons of aggressive management, identification and management of systemic treatments' side-effects, and the application of artificial intelligence and biomarkers across all aspects of the thoracic oncology pathway were among the areas that triggered specific interest and will be summarised here.
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Affiliation(s)
- Maria Joana Catarata
- Pulmonology Department, Hospital de Braga, Braga, Portugal
- Tumour & Microenvironment Interactions Group, I3S-Institute for Health Research & Innovation, University of Porto, Porto, Portugal
| | - Wouter H. Van Geffen
- Department of Respiratory Medicine, Medical Center Leeuwarden, Leeuwarden, The Netherlands
| | - Radhika Banka
- P.D. Hinduja National Hospital and Medical Research Centre, Mumbai, India
| | - Beatriz Ferraz
- Pulmonology Department, Centro Hospitalar e Universitário do Porto, Porto, Portugal
- ICBAS School of Medicine and Biomedical Sciences, University of Porto, Porto, Portugal
| | | | - Alan Carew
- Queensland Lung Transplant Service, Department of Thoracic Medicine, Prince Charles Hospital, Brisbane, Australia
- Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - Lucia Viola
- Thoracic Oncology Service, Fundación Neumológica Colombiana, Bogotá, Colombia
- Thoracic Clinic, Luis Carlos Sarmiento Angulo Cancer Treatment and Research Center (Fundación CTIC), Bogotá, Colombia
| | - Rolof Gijtenbeek
- Department of Respiratory Medicine, Medical Center Leeuwarden, Leeuwarden, The Netherlands
| | - Georgia Hardavella
- 9th Department of Respiratory Medicine, “Sotiria” Athens Chest Diseases Hospital, Athens, Greece
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22
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Gareen IF, Gutman R, Sicks J, Tailor TD, Hoffman RM, Trivedi AN, Flores E, Underwood E, Cochancela J, Chiles C. Significant Incidental Findings in the National Lung Screening Trial. JAMA Intern Med 2023; 183:677-684. [PMID: 37155190 PMCID: PMC10167600 DOI: 10.1001/jamainternmed.2023.1116] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 02/24/2023] [Indexed: 05/10/2023]
Abstract
Importance Low-dose computed tomography (LDCT) lung screening has been shown to reduce lung cancer mortality. Significant incidental findings (SIFs) have been widely reported in patients undergoing LDCT lung screening. However, the exact nature of these SIF findings has not been described. Objective To describe SIFs reported in the LDCT arm of the National Lung Screening Trial and classify SIFs as reportable or not reportable to the referring clinician (RC) using the American College of Radiology's white papers on incidental findings. Design, Setting, and Participants This was a retrospective case series study of 26 455 participants in the National Lung Screening Trial who underwent at least 1 screening examination with LDCT. The trial was conducted from 2002 to 2009, and data were collected at 33 US academic medical centers. Main Outcomes and Measures Significant incident findings were defined as a final diagnosis of a negative screen result with significant abnormalities that were not suspicious for lung cancer or a positive screen result with emphysema, significant cardiovascular abnormality, or significant abnormality above or below the diaphragm. Results Of 26 455 participants, 10 833 (41.0%) were women, the mean (SD) age was 61.4 (5.0) years, and there were 1179 (4.5%) Black, 470 (1.8%) Hispanic/Latino, and 24 123 (91.2%) White individuals. Participants were scheduled to undergo 3 screenings during the course of the trial; the present study included 75 126 LDCT screening examinations performed for 26 455 participants. A SIF was reported for 8954 (33.8%) of 26 455 participants who were screened with LDCT. Of screening tests with a SIF detected, 12 228 (89.1%) had a SIF considered reportable to the RC, with a higher proportion of reportable SIFs among those with a positive screen result for lung cancer (7632 [94.1%]) compared with those with a negative screen result (4596 [81.8%]). The most common SIFs reported included emphysema (8677 [43.0%] of 20 156 SIFs reported), coronary artery calcium (2432 [12.1%]), and masses or suspicious lesions (1493 [7.4%]). Masses included kidney (647 [3.2%]), liver (420 [2.1%]), adrenal (265 [1.3%]), and breast (161 [0.8%]) abnormalities. Classification was based on free-text comments; 2205 of 13 299 comments (16.6%) could not be classified. The hierarchical reporting of final diagnosis in NLST may have been associated with an overestimate of severe emphysema in participants with a positive screen result for lung cancer. Conclusions and Relevance This case series study found that SIFs were commonly reported in the LDCT arm of the National Lung Screening Trial, and most of these SIFs were considered reportable to the RC and likely to require follow-up. Future screening trials should standardize SIF reporting.
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Affiliation(s)
- Ilana F. Gareen
- Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island
- Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island
| | - Roee Gutman
- Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island
- Department of Biostatistics, Brown University of Public Health, Providence, Rhode Island
| | - JoRean Sicks
- Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island
| | - Tina D. Tailor
- Division of Cardiothoracic Radiology, Department of Radiology, Duke Health, Durham, North Carolina
| | - Richard M. Hoffman
- Holden Comprehensive Cancer Center, Department of Medicine, University of Iowa Carver College of Medicine, University of Iowa, Iowa City
| | - Amal N. Trivedi
- Department of Health Services, Policy and Practice, Brown University School of Public Health, Providence, Rhode Island
- Center of Innovation for Long-term Services and Supports, Providence Veterans Affairs Medical Center, Providence, Rhode Island
| | - Efren Flores
- Department of Radiology, Massachusetts General Hospital, Boston
| | - Ellen Underwood
- Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island
| | - Jerson Cochancela
- Department of Biostatistics, Brown University of Public Health, Providence, Rhode Island
| | - Caroline Chiles
- Department of Radiology, Atrium Health Wake Forest Baptist, Winston-Salem, North Carolina
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