1
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Chassagnon G, Revel MP. The trade-off dilemma between radiation dose and image resolution. Diagn Interv Imaging 2024; 105:351-352. [PMID: 38945780 DOI: 10.1016/j.diii.2024.06.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2024] [Accepted: 06/12/2024] [Indexed: 07/02/2024]
Affiliation(s)
- Guillaume Chassagnon
- Department of Radiology, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, 75014 Paris, France; Université Paris Cité, Faculté de Médecine, 75006 Paris, France.
| | - Marie-Pierre Revel
- Department of Radiology, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, 75014 Paris, France; Université Paris Cité, Faculté de Médecine, 75006 Paris, France
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2
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Bae H, Lee JW, Jeong YJ, Hwang MH, Lee G. Increased Scan Speed and Pitch on Ultra-Low-Dose Chest CT: Effect on Nodule Volumetry and Image Quality. MEDICINA (KAUNAS, LITHUANIA) 2024; 60:1301. [PMID: 39202582 PMCID: PMC11356370 DOI: 10.3390/medicina60081301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/03/2024] [Revised: 08/08/2024] [Accepted: 08/09/2024] [Indexed: 09/03/2024]
Abstract
Background and Objectives: This study's objective was to investigate the influence of increased scan speed and pitch on image quality and nodule volumetry in patients who underwent ultra-low-dose chest computed tomography (CT). Material and Methods: One hundred and two patients who had lung nodules were included in this study. Standard-speed, standard-pitch (SSSP) ultra-low-dose CT and high-speed, high-pitch (HSHP) ultra-low-dose CT were obtained for all patients. Image noise was measured as the standard deviation of attenuation. One hundred and sixty-three nodules were identified and classified according to location, volume, and nodule type. Volume measurement of detected pulmonary nodules was compared according to nodule location, volume, and nodule type. Motion artifacts at the right middle lobe, the lingular segment, and both lower lobes near the lung bases were evaluated. Subjective image quality analysis was also performed. Results: The HSHP CT scan demonstrated decreased motion artifacts at the left upper lobe lingular segment and left lower lobe compared to the SSSP CT scan (p < 0.001). The image noise was higher and the radiation dose was lower in the HSHP scan (p < 0.001). According to the nodule type, the absolute relative volume difference was significantly higher in ground glass opacity nodules compared with those of part-solid and solid nodules (p < 0.001). Conclusion: Our study results suggest that HSHP ultra-low-dose chest CT scans provide decreased motion artifacts and lower radiation doses compared to SSSP ultra-low-dose chest CT. However, lung nodule volumetry should be performed with caution for ground glass opacity nodules.
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Affiliation(s)
- Heejoo Bae
- Department of Radiology and Medical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan 49241, Republic of Korea (J.W.L.); (M.-H.H.)
| | - Ji Won Lee
- Department of Radiology and Medical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan 49241, Republic of Korea (J.W.L.); (M.-H.H.)
| | - Yeon Joo Jeong
- Department of Radiology and Medical Research Institute, Yangsan Pusan National University Hospital, Pusan National University School of Medicine, Busan 50612, Republic of Korea;
| | - Min-Hee Hwang
- Department of Radiology and Medical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan 49241, Republic of Korea (J.W.L.); (M.-H.H.)
| | - Geewon Lee
- Department of Radiology and Medical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan 49241, Republic of Korea (J.W.L.); (M.-H.H.)
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3
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ten Berge H, Ramaker D, Piazza G, Pan X, Lamprecht B, Valipour A, Prosch H. Shall We Screen Lung Cancer with Volume Computed Tomography in Austria? A Cost-Effectiveness Modelling Study. Cancers (Basel) 2024; 16:2623. [PMID: 39123350 PMCID: PMC11310943 DOI: 10.3390/cancers16152623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2024] [Revised: 07/16/2024] [Accepted: 07/18/2024] [Indexed: 08/12/2024] Open
Abstract
This study assessed the cost-effectiveness of a lung cancer screening (LCS) program using low-dose computed tomography (LDCT) in Austria. An existing decision tree with an integrated Markov model was used to analyze the cost-effectiveness of LCS versus no screening from a healthcare payer perspective over a lifetime horizon. A simulation was conducted to model annual LCS for an asymptomatic high-risk population cohort aged 50-74 with a smoking history using the Dutch-Belgian Lung Cancer Screening Study (NEderlands-Leuvens Longkanker ScreeningsONderzoek, NELSON) screening outcomes. The principal measure utilized to assess cost-effectiveness was the incremental cost-effectiveness ratio (ICER). Sensitivity and scenario analyses were employed to determine uncertainties surrounding the key model inputs. At an uptake rate of 50%, 300,277 eligible individuals would participate in the LCS program, yielding 56,122 incremental quality-adjusted life years (QALYs) and 84,049 life years gained compared to no screening, with an ICER of EUR 24,627 per QALY gained or EUR 16,444 per life-year saved. Additionally, LCS led to the detection of 25,893 additional early-stage lung cancers and averted 11,906 premature lung cancer deaths. It was estimated that LCS would incur EUR 945 million additional screening costs and EUR 386 million additional treatment costs. These estimates were robust in sensitivity analyses. Implementation of annual LCS with LDCT for a high-risk population, using the NELSON screening outcomes, is cost-effective in Austria, at a threshold of EUR 50,000 per QALY.
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Affiliation(s)
- Hilde ten Berge
- Institute for Diagnostic Accuracy, 9713 GH Groningen, The Netherlands
| | - Dianne Ramaker
- Institute for Diagnostic Accuracy, 9713 GH Groningen, The Netherlands
| | - Greta Piazza
- Institute for Diagnostic Accuracy, 9713 GH Groningen, The Netherlands
| | - Xuanqi Pan
- Institute for Diagnostic Accuracy, 9713 GH Groningen, The Netherlands
- Unit of Global Health, Faculty of Medical Sciences, University of Groningen, 9713 GZ Groningen, The Netherlands
| | - Bernd Lamprecht
- Department of Pulmonary Medicine, Kepler University Hospital, 4020 Linz, Austria
- Medical Faculty, Johannes Kepler University, 4040 Linz, Austria
| | - Arschang Valipour
- Karl-Landsteiner-Institute for Lung Research and Pulmonary Oncology, Klinik Floridsdorf, 1210 Vienna, Austria
| | - Helmut Prosch
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna General Hospital, 1090 Vienna, Austria
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4
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Pereira LFF, dos Santos RS, Bonomi DO, Franceschini J, Santoro IL, Miotto A, de Sousa TLF, Chate RC, Hochhegger B, Gomes A, Schneider A, de Araújo CA, Escuissato DL, Prado GF, Costa-Silva L, Zamboni MM, Ghefter MC, Corrêa PCRP, Torres PPTES, Mussi RK, Muglia VF, de Godoy I, Bernardo WM. Lung cancer screening in Brazil: recommendations from the Brazilian Society of Thoracic Surgery, Brazilian Thoracic Association, and Brazilian College of Radiology and Diagnostic Imaging. J Bras Pneumol 2024; 50:e20230233. [PMID: 38536982 PMCID: PMC11095927 DOI: 10.36416/1806-3756/e20230233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 12/13/2023] [Indexed: 05/18/2024] Open
Abstract
Although lung cancer (LC) is one of the most common and lethal tumors, only 15% of patients are diagnosed at an early stage. Smoking is still responsible for more than 85% of cases. Lung cancer screening (LCS) with low-dose CT (LDCT) reduces LC-related mortality by 20%, and that reduction reaches 38% when LCS by LDCT is combined with smoking cessation. In the last decade, a number of countries have adopted population-based LCS as a public health recommendation. Albeit still incipient, discussion on this topic in Brazil is becoming increasingly broad and necessary. With the aim of increasing knowledge and stimulating debate on LCS, the Brazilian Society of Thoracic Surgery, the Brazilian Thoracic Association, and the Brazilian College of Radiology and Diagnostic Imaging convened a panel of experts to prepare recommendations for LCS in Brazil. The recommendations presented here were based on a narrative review of the literature, with an emphasis on large population-based studies, systematic reviews, and the recommendations of international guidelines, and were developed after extensive discussion by the panel of experts. The following topics were reviewed: reasons for screening; general considerations about smoking; epidemiology of LC; eligibility criteria; incidental findings; granulomatous lesions; probabilistic models; minimum requirements for LDCT; volumetric acquisition; risks of screening; minimum structure and role of the multidisciplinary team; practice according to the Lung CT Screening Reporting and Data System; costs versus benefits of screening; and future perspectives for LCS.
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Affiliation(s)
- Luiz Fernando Ferreira Pereira
- . Serviço de Pneumologia, Hospital das Clínicas, Faculdade de Medicina, Universidade Federal de Minas Gerais - UFMG - Belo Horizonte (MG) Brasil
| | - Ricardo Sales dos Santos
- . Serviço de Cirurgia Torácica, Hospital Israelita Albert Einstein, São Paulo (SP) Brasil
- . Programa ProPulmão, SENAI CIMATEC e SDS Healthline, Salvador (BA) Brasil
| | - Daniel Oliveira Bonomi
- . Departamento de Cirurgia Torácica, Faculdade de Medicina, Universidade Federal de Minas Gerais - UFMG - Belo Horizonte (MG) Brasil
| | - Juliana Franceschini
- . Programa ProPulmão, SENAI CIMATEC e SDS Healthline, Salvador (BA) Brasil
- . Fundação ProAR, Salvador (BA) Brasil
| | - Ilka Lopes Santoro
- . Disciplina de Pneumologia, Departamento de Medicina, Escola Paulista de Medicina, Universidade Federal de São Paulo - UNIFESP - São Paulo (SP) Brasil
| | - André Miotto
- . Disciplina de Cirurgia Torácica, Departamento de Cirurgia, Escola Paulista de Medicina, Universidade Federal de São Paulo - UNIFESP - São Paulo (SP) Brasil
| | - Thiago Lins Fagundes de Sousa
- . Serviço de Pneumologia, Hospital Universitário Alcides Carneiro, Universidade Federal de Campina Grande - UFCG - Campina Grande (PB) Brasil
| | - Rodrigo Caruso Chate
- . Serviço de Radiologia, Hospital Israelita Albert Einstein, São Paulo (SP) Brasil
| | - Bruno Hochhegger
- . Department of Radiology, University of Florida, Gainesville (FL) USA
| | - Artur Gomes
- . Serviço de Cirurgia Torácica, Santa Casa de Misericórdia de Maceió, Maceió (AL) Brasil
| | - Airton Schneider
- . Serviço de Cirurgia Torácica, Hospital São Lucas, Escola de Medicina, Pontifícia Universidade Católica do Rio Grande do Sul - PUCRS - Porto Alegre (RS) Brasil
| | - César Augusto de Araújo
- . Programa ProPulmão, SENAI CIMATEC e SDS Healthline, Salvador (BA) Brasil
- . Departamento de Radiologia, Faculdade de Medicina da Bahia - UFBA - Salvador (BA) Brasil
| | - Dante Luiz Escuissato
- . Departamento de Clínica Médica, Universidade Federal Do Paraná - UFPR - Curitiba (PR) Brasil
| | | | - Luciana Costa-Silva
- . Serviço de Diagnóstico por Imagem, Instituto Hermes Pardini, Belo Horizonte (MG) Brasil
| | - Mauro Musa Zamboni
- . Instituto Nacional de Câncer José Alencar Gomes da Silva, Rio de Janeiro (RJ) Brasil
- . Centro Universitário Arthur Sá Earp Neto/Faculdade de Medicina de Petrópolis -UNIFASE - Petrópolis (RJ) Brasil
| | - Mario Claudio Ghefter
- . Serviço de Cirurgia Torácica, Hospital Israelita Albert Einstein, São Paulo (SP) Brasil
- . Serviço de Cirurgia Torácica, Hospital do Servidor Público Estadual, São Paulo (SP) Brasil
| | | | | | - Ricardo Kalaf Mussi
- . Serviço de Cirurgia Torácica, Hospital das Clínicas, Universidade Estadual de Campinas - UNICAMP - Campinas (SP) Brasil
| | - Valdair Francisco Muglia
- . Departamento de Imagens Médicas, Oncologia e Hematologia, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo - USP - Ribeirão Preto (SP) Brasil
| | - Irma de Godoy
- . Disciplina de Pneumologia, Departamento de Clínica Médica, Faculdade de Medicina de Botucatu, Universidade Estadual Paulista, Botucatu (SP) Brasil
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5
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Warkentin MT, Al-Sawaihey H, Lam S, Liu G, Diergaarde B, Yuan JM, Wilson DO, Atkar-Khattra S, Grant B, Brhane Y, Khodayari-Moez E, Murison KR, Tammemagi MC, Campbell KR, Hung RJ. Radiomics analysis to predict pulmonary nodule malignancy using machine learning approaches. Thorax 2024; 79:307-315. [PMID: 38195644 PMCID: PMC10947877 DOI: 10.1136/thorax-2023-220226] [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: 03/07/2023] [Accepted: 12/04/2023] [Indexed: 01/11/2024]
Abstract
BACKGROUND Low-dose CT screening can reduce lung cancer-related mortality. However, most screen-detected pulmonary abnormalities do not develop into cancer and it often remains challenging to identify malignant nodules, particularly among indeterminate nodules. We aimed to develop and assess prediction models based on radiological features to discriminate between benign and malignant pulmonary lesions detected on a baseline screen. METHODS Using four international lung cancer screening studies, we extracted 2060 radiomic features for each of 16 797 nodules (513 malignant) among 6865 participants. After filtering out low-quality radiomic features, 642 radiomic and 9 epidemiological features remained for model development. We used cross-validation and grid search to assess three machine learning (ML) models (eXtreme Gradient Boosted Trees, random forest, least absolute shrinkage and selection operator (LASSO)) for their ability to accurately predict risk of malignancy for pulmonary nodules. We report model performance based on the area under the curve (AUC) and calibration metrics in the held-out test set. RESULTS The LASSO model yielded the best predictive performance in cross-validation and was fit in the full training set based on optimised hyperparameters. Our radiomics model had a test-set AUC of 0.93 (95% CI 0.90 to 0.96) and outperformed the established Pan-Canadian Early Detection of Lung Cancer model (AUC 0.87, 95% CI 0.85 to 0.89) for nodule assessment. Our model performed well among both solid (AUC 0.93, 95% CI 0.89 to 0.97) and subsolid nodules (AUC 0.91, 95% CI 0.85 to 0.95). CONCLUSIONS We developed highly accurate ML models based on radiomic and epidemiological features from four international lung cancer screening studies that may be suitable for assessing indeterminate screen-detected pulmonary nodules for risk of malignancy.
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Affiliation(s)
- Matthew T Warkentin
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Hamad Al-Sawaihey
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
| | - Stephen Lam
- Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Integrative Oncology, British Columbia Cancer Research Institute, Vancouver, British Columbia, Canada
| | - Geoffrey Liu
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Department of Medical Oncology and Hematology, Princess Margaret Hospital Cancer Centre, Toronto, Ontario, Canada
| | - Brenda Diergaarde
- Department of Human Genetics, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania, USA
- Cancer Epidemiology and Prevention Program, UPMC Hillman Cancer Center, Pittsburgh, Pennsylvania, USA
| | - Jian-Min Yuan
- Cancer Epidemiology and Prevention Program, UPMC Hillman Cancer Center, Pittsburgh, Pennsylvania, USA
- Department of Epidemiology, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania, USA
| | - David O Wilson
- Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Sukhinder Atkar-Khattra
- Department of Integrative Oncology, British Columbia Cancer Research Institute, Vancouver, British Columbia, Canada
| | - Benjamin Grant
- Department of Medical Oncology and Hematology, Princess Margaret Hospital Cancer Centre, Toronto, Ontario, Canada
| | - Yonathan Brhane
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
| | - Elham Khodayari-Moez
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
| | - Kiera R Murison
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
| | - Martin C Tammemagi
- Cancer Control and Evidence Integration, Cancer Care Ontario, Toronto, Ontario, Canada
| | - Kieran R Campbell
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Rayjean J Hung
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
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6
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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: 0] [Impact Index Per Article: 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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7
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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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8
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Iball GR, Beeching CE, Gabe R, Tam HZ, Darby M, Crosbie PAJ, Callister MEJ. An evaluation of CT radiation doses within the Yorkshire Lung Screening Trial. Br J Radiol 2024; 97:469-476. [PMID: 38308037 DOI: 10.1093/bjr/tqad045] [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: 06/09/2022] [Revised: 06/05/2023] [Accepted: 11/28/2023] [Indexed: 02/04/2024] Open
Abstract
OBJECTIVES To evaluate radiation doses for all low-dose CT scans performed during the first year of a lung screening trial. METHODS For all lung screening scans that were performed using a CT protocol that delivered image quality meeting the RSNA QIBA criteria, radiation dose metrics, participant height, weight, gender, and age were recorded. Values of volume CT dose index (CTDIvol) and dose length product (DLP) were evaluated as a function of weight in order to assess the performance of the scan protocol across the participant cohort. Calculated effective doses were used to establish the additional lifetime attributable cancer risks arising from trial scans. RESULTS Median values of CTDIvol, DLP, and effective dose (IQR) from the 3521 scans were 1.1 mGy (0.70), 42.4 mGycm (24.9), and 1.15 mSv (0.67), whilst for 60-80kg participants the values were 1.0 mGy (0.30), 35.8 mGycm (11.4), and 0.97 mSv (0.31). A statistically significant correlation between CTDIvol and weight was identified for males (r = 0.9123, P < .001) and females (r = 0.9052, P < .001), however, the effect of gender on CTDIvol was not statistically significant (P = .2328) despite notable differences existing at the extremes of the weight range. The additional lifetime attributable cancer risks from a single scan were in the range 0.001%-0.006%. CONCLUSIONS Low radiation doses can be achieved across a typical lung screening cohort using scan protocols that have been shown to deliver high levels of image quality. The observed dose levels may be considered as typical values for lung screening scans on similar types of scanners for an equivalent participant cohort. ADVANCES IN KNOWLEDGE Presentation of typical radiation dose levels for CT lung screening examinations in a large UK trial. Effective radiation doses can be of the order of 1 mSv for standard sized participants. Lifetime attributable cancer risks resulting from a single low-dose CT scan did not exceed 0.006%.
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Affiliation(s)
- Gareth R Iball
- Faculty of Health Studies, University of Bradford, Richmond Road, Bradford, BD7 1DP, United Kingdom
- Department of Medical Physics & Engineering, Leeds Teaching Hospitals NHS Trust, Leeds, West Yorkshire, LS1 3EX, United Kingdom
| | - Charlotte E Beeching
- Department of Medical Physics & Engineering, Leeds Teaching Hospitals NHS Trust, Leeds, West Yorkshire, LS1 3EX, United Kingdom
| | - Rhian Gabe
- Wolfson Institute of Preventive Medicine, Queen Mary University of London, EC1M 6BQ, United Kingdom
| | - Hui Zhen Tam
- Barts Clinical Trials Unit, Wolfson Institute of Population Health, Queen Mary University of London, EC1M 6BQ, United Kingdom
| | - Michael Darby
- Department of Radiology, Leeds Teaching Hospitals NHS Trust, Leeds, LS1 3EX, United Kingdom
| | - Philip A J Crosbie
- Division of Infection, Immunity & Respiratory Medicine, University of Manchester, M13 9NT, United Kingdom
| | - Matthew E J Callister
- Department of Respiratory Medicine, Leeds Teaching Hospitals NHS Trust, Leeds, LS1 3EX, United Kingdom
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9
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Xu D, de la Hoz RE, Steinberger SR, Doucette J, Pagano AM, Wolf A, Chung M, Jacobi A. Postoperative CT surveillance in the evaluation of local recurrence after sub-lobar resection of neoplastic lesions of the lung. Clin Imaging 2024; 106:110030. [PMID: 38150854 DOI: 10.1016/j.clinimag.2023.110030] [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: 06/13/2023] [Revised: 11/03/2023] [Accepted: 11/13/2023] [Indexed: 12/29/2023]
Abstract
OBJECTIVE As indications for sub-lobar resections increase, it will become more important to identify risk factors for postsurgical recurrence. We investigated retrospectively the association between local recurrence after sub-lobar resection of neoplastic lung lesions and pre- and post-operative CT imaging and pathologic features. MATERIALS AND METHODS We reviewed retrospectively neoplastic lung lesions with postoperative chest CT surveillance of sub-lobar resections in 2006-2016. We defined "suspicious" findings as nodularity ≥3 mm or soft tissue thickening ≥4 mm along the suture line and/or progression and explored their association with local recurrence. Primary lung cancer stage, tumoral invasion of lymphatics, visceral pleura or large vessels, bronchial and vascular margin distance were also assessed. RESULTS Our study group included 45 cases of sub-lobar resection took for either primary (n = 37) or metastatic (n = 8) lung tumors. Local recurrence was observed in 16 of those patients. New nodularity ≥3 mm or soft tissue thickening ≥4 mm along the suture line on surveillance CT was significantly associated with local recurrence (p = 0.037). Additionally, solid nodule (p = 0.005), age at surgery ≤60 years (p = 0.006), two or more sites of invasion (p < 0.0001) and poor histologic differentiation (p = 0.0001) were also significantly associated with local tumor recurrence. Of 16 patients with surveillance post-surgical PET-CT, 15 had elevated FDG uptake. CONCLUSION The postoperative changes along the suture line should follow a predictable time course demonstrating a pattern of stability, thinning or resolution on CT surveillance. New or increasing postoperative nodularity ≥3 mm or soft tissue thickening ≥4 mm along the suture line requires close diagnostic work-up. Surgical pathology characteristics added prognostic value on postoperative recurrence surveillance.
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Affiliation(s)
- Dongming Xu
- University of Pennsylvania, Radiology, 3400 Spruce Street, Philadelphia, PA 19104, USA.
| | - Rafael E de la Hoz
- Departments of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - John Doucette
- Icahn School of Medicine at Mount Sinai, Environmental Medicine and Public Health, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Andrew Michael Pagano
- Memorial Sloan Kettering Cancer Center, Radiology, 1275 York Ave., New York, NY 10065, USA
| | - Andrea Wolf
- Icahn School of Medicine at Mount Sinai, Thoracic Surgery, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Michael Chung
- Icahn School of Medicine at Mount Sinai, Department of Radiology, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Adam Jacobi
- Icahn School of Medicine at Mount Sinai, Department of Radiology, One Gustave L. Levy Place, New York, NY 10029, USA
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10
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Karita R, Suzuki H, Onozato Y, Kaiho T, Inage T, Ito T, Tanaka K, Sakairi Y, Yoshino I. A simple nomogram for predicting occult lymph node metastasis of non-small cell lung cancer from preoperative computed tomography findings, including the volume-doubling time. Surg Today 2024; 54:31-40. [PMID: 37129682 DOI: 10.1007/s00595-023-02695-9] [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: 01/30/2023] [Accepted: 04/10/2023] [Indexed: 05/03/2023]
Abstract
PURPOSE Latent lymph node metastasis is a clinical concern in the surgical treatment of non-small cell lung cancer (NSCLC). The present study identified a simple tool, including the volume-doubling time (VDT), for evaluating the risk of nodal metastasis. METHODS We reviewed, retrospectively, 560 patients who underwent radical resection for cN0M0 NSCLC. The whole tumor VDT and solid component VDT (SVDT) for differentiating the histological type and adenocarcinoma subtype were analyzed and a nomogram was constructed using variables selected through a stepwise selection method. The model was assessed through a calibration curve and decision curve analysis (DCA). RESULTS Lymph node metastases were detected in 89 patients (15.9%). The SVDT tended to be longer in patients with adenocarcinoma (294.5 days, p < 0.0001) than in those with other histological types of NSCLC, but was shorter when the solid/micropapillary component was predominant (127.0 days, p < 0.0001). The selected variables (tumor location, solid component diameter, consolidation tumor ratio, SVDT, and carcinoembryonic antigen) demonstrated significant differences and were used for the nomogram. The calibration curve indicated consistency, and the DCA showed validity across most threshold ranges from 0 to 68%. CONCLUSIONS The established nomogram is a useful tool for the preoperative prediction of lymph node metastasis, and the SVDT was the most influential factor in the nomogram.
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Affiliation(s)
- Ryo Karita
- Department of General Thoracic Surgery, Chiba University Graduate School of Medicine, 1-8-1, Inohana, Chuo-Ku, Chiba, 260-8670, Japan
- Department of Thoracic Surgery, International University of Health and Welfare School of Medicine, Chiba, Japan
| | - Hidemi Suzuki
- Department of General Thoracic Surgery, Chiba University Graduate School of Medicine, 1-8-1, Inohana, Chuo-Ku, Chiba, 260-8670, Japan.
| | - Yuki Onozato
- Department of General Thoracic Surgery, Chiba University Graduate School of Medicine, 1-8-1, Inohana, Chuo-Ku, Chiba, 260-8670, Japan
- Department of Thoracic Surgery, International University of Health and Welfare School of Medicine, Chiba, Japan
| | - Taisuke Kaiho
- Department of General Thoracic Surgery, Chiba University Graduate School of Medicine, 1-8-1, Inohana, Chuo-Ku, Chiba, 260-8670, Japan
| | - Terunaga Inage
- Department of General Thoracic Surgery, Chiba University Graduate School of Medicine, 1-8-1, Inohana, Chuo-Ku, Chiba, 260-8670, Japan
| | - Takamasa Ito
- Department of General Thoracic Surgery, Chiba University Graduate School of Medicine, 1-8-1, Inohana, Chuo-Ku, Chiba, 260-8670, Japan
| | - Kazuhisa Tanaka
- Department of General Thoracic Surgery, Chiba University Graduate School of Medicine, 1-8-1, Inohana, Chuo-Ku, Chiba, 260-8670, Japan
| | - Yuichi Sakairi
- Department of General Thoracic Surgery, Chiba University Graduate School of Medicine, 1-8-1, Inohana, Chuo-Ku, Chiba, 260-8670, Japan
| | - Ichiro Yoshino
- Department of General Thoracic Surgery, Chiba University Graduate School of Medicine, 1-8-1, Inohana, Chuo-Ku, Chiba, 260-8670, Japan
- Department of Thoracic Surgery, International University of Health and Welfare School of Medicine, Chiba, Japan
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11
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Hammer MM, Gupta S, Byrne SC. Volume Doubling Times of Benign and Malignant Nodules in Lung Cancer Screening. Curr Probl Diagn Radiol 2023; 52:515-518. [PMID: 37451949 PMCID: PMC10592400 DOI: 10.1067/j.cpradiol.2023.06.014] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 06/28/2023] [Accepted: 06/28/2023] [Indexed: 07/18/2023]
Abstract
The purpose of this study was to measure the fractions of benign and malignant nodules in lung cancer screening that grow on follow-up, and to measure the volume doubling time (VDT) of those that grow. In this retrospective study, we included nodules from CT lung cancer screening in our healthcare network, for which a follow-up CT performed at least 2 months later showed the nodule to be persistent. The nodules were measured using semiautomated volumetric segmentation software at both timepoints. Growth was defined as an increase in volume by 25%. VDTs were calculated, and the fraction <400 days was recorded. Categorical variables were compared with Fisher's exact test, and continuous variables by the Wilcoxon test. The study included 153 nodules, of which 44 were malignant and 109 benign. Thirty (68%) of malignant nodules and 36 (33%) of benign nodules grew (P < 0.001). For growing nodules, VDT was 318 days for malignant nodules and 389 for benign nodules (P = 0.21). For growing solid nodules, VDT was 204 days for malignant nodules and 386 days for benign nodules (P = 0.01); of these, VDT was <400 days for 12/13 (92%) of malignant nodules and 15/26 (58%) of benign nodules. In conclusion, malignant nodules were more likely to grow, and solid malignant nodules grew faster, than benign nodules. However, there was substantial overlap between benign and malignant nodules. This limits the utility of volume doubling time in determining malignant nodules.
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Affiliation(s)
- Mark M Hammer
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
| | - Sumit Gupta
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Suzanne C Byrne
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
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12
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Park S, Lee SM, Choe J, Choi S, Kim S, Do KH, Seo JB. Sublobar resection in non-small cell lung cancer: patient selection criteria and risk factors for recurrence. Br J Radiol 2023; 96:20230143. [PMID: 37561432 PMCID: PMC10546461 DOI: 10.1259/bjr.20230143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 07/03/2023] [Accepted: 07/11/2023] [Indexed: 08/11/2023] Open
Abstract
OBJECTIVE To validate selection criteria for sublobar resection in patients with lung cancer with respect to recurrence, and to investigate predictors for recurrence in patients for whom the criteria are not suitable. METHODS Patients who underwent sublobar resection for lung cancer between July 2010 and December 2018 were retrospectively included. The criteria for curative sublobar resection were consolidation-to-tumor ratio ≤0.50 and size ≤3.0 cm in tumors with a ground-glass opacity (GGO) component (GGO group), and size of ≤2.0 cm and volume doubling time ≥400 days in solid tumors (solid group). Cox regression was used to identify predictors for time-to-recurrence (TTR) in tumors outside of these criteria (non-curative group). RESULTS Out of 530 patients, 353 were classified into the GGO group and 177 into the solid group. In the GGO group, the 2-year recurrence rates in curative and non-curative groups were 2.1 and 7.7%, respectively (p = 0.054). In the solid group, the 2-year recurrence rates in curative and non-curative groups were 0.0 and 28.6%, respectively (p = 0.03). Predictors of 2-year TTR after non-curative sublobar resection were pathological nodal metastasis (hazard ratio [HR], 6.63; p = 0.02) and lymphovascular invasion (LVI; HR, 3.28; p = 0.03) in the GGO group, and LVI (HR, 4.37; p < 0.001) and fibrosis (HR, 3.18; p = 0.006) in the solid group. CONCLUSION The current patient selection criteria for sublobar resection are satisfactory. LVI was a predictor for recurrence after non-curative resection. ADVANCES IN KNOWLEDGE This result supports selection criteria of patients for sublobar resection. LVI may help predict recurrence after non-curative sublobar resection.
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Affiliation(s)
- Sohee Park
- Department of Radiology, Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - Sang Min Lee
- Department of Radiology, Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - Jooae Choe
- Department of Radiology, Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - Sehoon Choi
- Department of Cardiothoracic Surgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - Sehee Kim
- Department of Medical Statistics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - Kyung-Hyun Do
- Department of Radiology, Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - Joon Beom Seo
- Department of Radiology, Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
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13
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Yoshiyasu N, Kojima F, Hayashi K, Yamada D, Bando T. Low-Dose CT Screening of Persistent Subsolid Lung Nodules: First-Order Features in Radiomics. Thorac Cardiovasc Surg 2023. [PMID: 37607686 DOI: 10.1055/a-2158-1364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
BACKGROUND Nondisappearing subsolid nodules requiring follow-up are often detected during lung cancer screening, but changes in their invasiveness can be overlooked owing to slow growth. We aimed to develop a method for automatic identification of invasive tumors among subsolid nodules during multiple health checkups using radiomics technology based on low-dose computed tomography (LD-CT) and examine its effectiveness. METHODS We examined patients who underwent LD-CT screening from 2014 to 2019 and had lung adenocarcinomas resected after 5-year follow-ups. They were categorized into the invasive or less-invasive group; the annual growth/change rate (Δ) of the nodule voxel histogram using three-dimensional CT (e.g., tumor volume, solid volume percentage, mean CT value, variance, kurtosis, skewness, and entropy) was assessed. A discriminant model was designed through multivariate regression analysis with internal validation to compare its efficacy with that of a volume doubling time of < 400 days. RESULTS The study included 47 tumors (23 invasive, 24 less invasive), with no significant difference in the initial tumor volumes. Δskewness was identified as an independent predictor of invasiveness (adjusted odds ratio, 0.021; p = 0.043), and when combined with Δvariance, it yielded high accuracy in detecting invasive lesions (88% true-positive, 80% false-positive). The detection model indicated surgery 2 years earlier than the volume doubling time, maintaining accuracy (median 3 years vs.1 year before actual surgery, p = 0.011). CONCLUSION LD-CT radiomics showed promising potential in ensuring timely detection and monitoring of subsolid nodules that warrant follow-up over time.
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Affiliation(s)
- Nobuyuki Yoshiyasu
- Department of Thoracic Surgery, St. Luke's International Hospital, Tokyo, Japan
| | - Fumitsugu Kojima
- Department of Thoracic Surgery, St. Luke's International Hospital, Tokyo, Japan
| | - Kuniyoshi Hayashi
- Graduate School of Public Health, St. Luke's International University, Tokyo, Japan
| | - Daisuke Yamada
- Department of Radiology, St. Luke's International Hospital, Tokyo, Japan
| | - Toru Bando
- Department of Thoracic Surgery, St. Luke's International Hospital, Tokyo, Japan
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14
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Liu CC, Cheng YF, Ke PC, Chen YL, Lin CM, Wang BY. Prediction of Surgical Outcome by Tumor Volume Doubling Time via Stereo Imaging Software in Early Non-Small Cell Lung Cancer. Cancers (Basel) 2023; 15:3952. [PMID: 37568768 PMCID: PMC10417538 DOI: 10.3390/cancers15153952] [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: 06/25/2023] [Revised: 07/28/2023] [Accepted: 08/01/2023] [Indexed: 08/13/2023] Open
Abstract
BACKGROUND Volume doubling time (VDT) has been proven to be a powerful predictor of lung cancer progression. In non-small cell lung cancer patients receiving sublobar resection, the discussion of correlation between VDT and surgery was absent. We proposed to investigate the surgical outcomes according to VDT. METHODS We retrospectively studied 96 cases post sublobar resection from 2012 to 2018, collecting two chest CT scans preoperatively of each case and calculating the VDT. The receiver operating characteristic curve was constructed to identify the optimal cut-off point of VDTs as 133 days. We divided patients into two groups: VDT < 133 days and VDT ≥ 133 days. Univariable and multivariable analyses were performed for comparative purposes. RESULTS Univariable and multivariable analyses revealed that the consolidation and tumor diameter ratio was the factor of overall survival (OS), and VDT was the only factor of disease-free survival (DFS). The five year OS rates of patients with VDTs ≥ 133 days and VDTs < 133 days, respectively, were 89.9% and 71.9%, and the five year DFS rates were 95.9% and 61.5%. CONCLUSION As VDT serves as a powerful prognostic predictor and provides an essential role in planning surgical procedures, the evaluation of VDT preoperatively is highly suggested.
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Affiliation(s)
- Chia-Chi Liu
- Division of Thoracic Surgery, Department of Surgery, Changhua Christian Hospital, Changhua 50006, Taiwan; (C.-C.L.); (Y.-F.C.); (P.-C.K.); (C.-M.L.)
| | - Ya-Fu Cheng
- Division of Thoracic Surgery, Department of Surgery, Changhua Christian Hospital, Changhua 50006, Taiwan; (C.-C.L.); (Y.-F.C.); (P.-C.K.); (C.-M.L.)
| | - Pei-Cing Ke
- Division of Thoracic Surgery, Department of Surgery, Changhua Christian Hospital, Changhua 50006, Taiwan; (C.-C.L.); (Y.-F.C.); (P.-C.K.); (C.-M.L.)
| | - Yi-Ling Chen
- Surgery Clinical Research Center, Changhua Christian Hospital, Changhua 50006, Taiwan;
| | - Ching-Min Lin
- Division of Thoracic Surgery, Department of Surgery, Changhua Christian Hospital, Changhua 50006, Taiwan; (C.-C.L.); (Y.-F.C.); (P.-C.K.); (C.-M.L.)
| | - Bing-Yen Wang
- Division of Thoracic Surgery, Department of Surgery, Changhua Christian Hospital, Changhua 50006, Taiwan; (C.-C.L.); (Y.-F.C.); (P.-C.K.); (C.-M.L.)
- Surgery Clinical Research Center, Changhua Christian Hospital, Changhua 50006, Taiwan;
- Department of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taichung 40227, Taiwan
- School of Medicine, Chung Shan Medical University, Taichung 40201, Taiwan
- School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 80756, Taiwan
- Institute of Genomics and Bioinformatics, National Chung Hsing University, Taichung 40227, Taiwan
- Center for General Education, Ming Dao University, Changhua 52345, Taiwan
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15
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Jiang X, Liu MW, Zhang X, Dong JY, Miao L, Sun ZH, Dong SS, Zhang L, Yang L, Li M. Observational Study of the Natural Growth History of Peripheral Small-Cell Lung Cancer on CT Imaging. Diagnostics (Basel) 2023; 13:2560. [PMID: 37568923 PMCID: PMC10417025 DOI: 10.3390/diagnostics13152560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 07/18/2023] [Accepted: 07/24/2023] [Indexed: 08/13/2023] Open
Abstract
BACKGROUND This study aimed to investigate the natural growth history of peripheral small-cell lung cancer (SCLC) using CT imaging. METHODS A retrospective study was conducted on 27 patients with peripheral SCLC who underwent at least two CT scans. Two methods were used: Method 1 involved direct measurement of nodule dimensions using a calliper, while Method 2 involved tumour lesion segmentation and voxel volume calculation using the "py-radiomics" package in Python. Agreement between the two methods was assessed using the intraclass correlation coefficient (ICC). Volume doubling time (VDT) and growth rate (GR) were used as evaluation indices for SCLC growth, and growth distribution based on GR and volume measurements were depicted. We collected potential factors related to imaging VDT and performed a differential analysis. Patients were classified into slow-growing and fast-growing groups based on a VDT cut-off point of 60 days, and univariate analysis was used to identify factors influencing VDT. RESULTS Median VDT calculated by the two methods were 61 days and 71 days, respectively, with strong agreement. All patients had continuously growing tumours, and none had tumours that decreased in size or remained unchanged. Eight patients showed possible growth patterns, with six possibly exhibiting exponential growth and two possibly showing Gompertzian growth. Tumours deeper in the lung grew faster than those adjacent to the pleura. CONCLUSIONS Peripheral SCLC tumours grow rapidly and continuously without periods of nongrowth or regression. Tumours located deeper in the lung tend to grow faster, but further research is needed to confirm this finding.
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Affiliation(s)
- Xu Jiang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; (X.J.); (M.-W.L.); (X.Z.); (L.M.); (L.Z.)
| | - Meng-Wen Liu
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; (X.J.); (M.-W.L.); (X.Z.); (L.M.); (L.Z.)
| | - Xue Zhang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; (X.J.); (M.-W.L.); (X.Z.); (L.M.); (L.Z.)
| | - Ji-Yan Dong
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; (J.-Y.D.); (Z.-H.S.)
| | - Lei Miao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; (X.J.); (M.-W.L.); (X.Z.); (L.M.); (L.Z.)
| | - Zi-Han Sun
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; (J.-Y.D.); (Z.-H.S.)
| | - Shu-Shan Dong
- Clinical Science, Philips Healthcare, Beijing 100600, China;
| | - Li Zhang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; (X.J.); (M.-W.L.); (X.Z.); (L.M.); (L.Z.)
| | - Lin Yang
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; (J.-Y.D.); (Z.-H.S.)
| | - Meng Li
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; (X.J.); (M.-W.L.); (X.Z.); (L.M.); (L.Z.)
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16
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Wang B, Zhang H, Li W, Fu S, Li Y, Gao X, Wang D, Yang X, Xu S, Wang J, Hou D. Neural network-based model for evaluating inert nodules and volume doubling time in T1 lung adenocarcinoma: a nested case-control study. Front Oncol 2023; 13:1037052. [PMID: 37293594 PMCID: PMC10244560 DOI: 10.3389/fonc.2023.1037052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 05/09/2023] [Indexed: 06/10/2023] Open
Abstract
Objective The purpose of this study is to establish model for assessing inert nodules predicting nodule volume-doubling. Methods A total of 201 patients with T1 lung adenocarcinoma were analysed retrospectively pulmonary nodule information was predicted by an AI pulmonary nodule auxiliary diagnosis system. The nodules were classified into two groups: inert nodules (volume-doubling time (VDT)>600 days n=152) noninert nodules (VDT<600 days n=49). Then taking the clinical imaging features obtained at the first examination as predictive variables the inert nodule judgement model <sn</sn>>(INM) volume-doubling time estimation model (VDTM) were constructed based on a deep learning-based neural network. The performance of the INM was evaluated by the area under the curve (AUC) obtained from receiver operating characteristic (ROC) analysis the performance of the VDTM was evaluated by R2(determination coefficient). Results The accuracy of the INM in the training and testing cohorts was 81.13% and 77.50%, respectively. The AUC of the INM in the training and testing cohorts was 0.7707 (95% CI 0.6779-0.8636) and 0.7700 (95% CI 0.5988-0.9412), respectively. The INM was effective in identifying inert pulmonary nodules; additionally, the R2 of the VDTM in the training cohort was 0.8008, and that in the testing cohort was 0.6268. The VDTM showed moderate performance in estimating the VDT, which can provide some reference during a patients' first examination and consultation. Conclusion The INM and the VDTM based on deep learning can help radiologists and clinicians distinguish among inert nodules and predict the nodule volume-doubling time to accurately treat patients with pulmonary nodules.
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Affiliation(s)
- Bing Wang
- Department of Radiology, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, China
| | - Hui Zhang
- Department of Medical Oncology, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, China
| | - Wei Li
- Cancer Research Center, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Siyun Fu
- Department of Radiology, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, China
| | - Ye Li
- Department of Radiology, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, China
| | - Xiang Gao
- Cancer Research Center, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Dongpo Wang
- Department of Radiology, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, China
| | - Xinjie Yang
- Department of Medical Oncology, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, China
| | - Shaofa Xu
- Cancer Research Center, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Jinghui Wang
- Department of Medical Oncology, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, China
| | - Dailun Hou
- Department of Radiology, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, China
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Walder JR, Faiz SA, Sandoval M. Lung cancer in the emergency department. EMERGENCY CANCER CARE 2023; 2:3. [PMID: 38799792 PMCID: PMC11116267 DOI: 10.1186/s44201-023-00018-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 02/13/2023] [Indexed: 05/29/2024]
Abstract
Background Though decreasing in incidence and mortality in the USA, lung cancer remains the deadliest of all cancers. For a significant number of patients, the emergency department (ED) provides the first pivotal step in lung cancer prevention, diagnosis, and management. As screening recommendations and treatments advance, ED providers must stay up-to-date with the latest lung cancer recommendations. The purpose of this review is to identify the many ways that emergency providers may intersect with the disease spectrum of lung cancer and provide an updated array of knowledge regarding detection, management, complications, and interdisciplinary care. Findings Lung cancer, encompassing 10-12% of cancer-related emergency department visits and a 66% admission rate, is the most fatal malignancy in both men and women. Most patients presenting to the ED have not seen a primary care provider or undergone screening. Ultimately, half of those with a new lung cancer diagnosis in the ED die within 1 year. Incidental findings on computed tomography are mostly benign, but emergency staff must be aware of the factors that make them high risk. Radiologic presentations range from asymptomatic nodules to diffuse metastatic lesions with predominately pulmonary symptoms, and some may present with extra-thoracic manifestations including neurologic. The short-term prognosis for ED lung cancer patients is worse than that of other malignancies. Screening offers new hope through earlier diagnosis but is underutilized which may be due to racial and socioeconomic disparities. New treatments provide optimism but lead to new complications, some long-term. Multidisciplinary care is essential, and emergency medicine is responsible for the disposition of patients to the appropriate specialists at inpatient and outpatient centers. Conclusion ED providers are intimately involved in all aspects of lung cancer care. Risk factor modification and referral for lung cancer screening are opportunities to further enhance patient care. In addition, with the advent of newer cancer therapies, ED providers must stay vigilant and up-to-date with all aspects of lung cancer including disparities, staging, symptoms of disease, prognosis, treatment, and therapy-related complications.
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Affiliation(s)
- Jeremy R. Walder
- Divisions of Critical Care, Pulmonary and Sleep Medicine, McGovern Medical School at UTHealth, 6431 Fannin St., Ste. MSB 1.282, Houston, TX 77030 USA
| | - Saadia A. Faiz
- Department of Pulmonary Medicine, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1462, Houston, TX 77030 USA
| | - Marcelo Sandoval
- Department of Emergency Medicine, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1468, Houston, TX 77030 USA
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Contextualizing the Role of Volumetric Analysis in Pulmonary Nodule Assessment: AJR Expert Panel Narrative Review. AJR Am J Roentgenol 2023; 220:314-329. [PMID: 36129224 DOI: 10.2214/ajr.22.27830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Pulmonary nodules are managed on the basis of their size and morphologic characteristics. Radiologists are familiar with assessing nodule size by measuring diameter using manually deployed electronic calipers. Size may also be assessed with 3D volumetric measurements (referred to as volumetry) obtained with software. Nodule size and growth are more accurately assessed with volumetry than on the basis of diameter, and the evidence supporting clinical use of volumetry has expanded, driven by its use in lung cancer screening nodule management algorithms in Europe. The application of volumetry has the potential to reduce recommendations for imaging follow-up of indeterminate solid nodules without impacting cancer detection. Although changes in scanning conditions and volumetry software packages can lead to variation in volumetry results, ongoing technical advances have improved the reliability of calculated volumes. Volumetry is now the primary method for determining size of solid nodules in the European lung cancer screening position statement and British Thoracic Society recommendations. The purposes of this article are to review technical aspects, advantages, and limitations of volumetry and, by considering specific scenarios, to contextualize the use of volumetry with respect to its importance in morphologic evaluation, its role in predicting malignancy in risk models, and its practical impact on nodule management. Implementation challenges and areas requiring further evidence are also highlighted.
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19
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Pozzessere C, von Garnier C, Beigelman-Aubry C. Radiation Exposure to Low-Dose Computed Tomography for Lung Cancer Screening: Should We Be Concerned? Tomography 2023; 9:166-177. [PMID: 36828367 PMCID: PMC9964027 DOI: 10.3390/tomography9010015] [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: 11/29/2022] [Revised: 01/13/2023] [Accepted: 01/17/2023] [Indexed: 01/26/2023] Open
Abstract
Lung cancer screening (LCS) programs through low-dose Computed Tomography (LDCT) are being implemented in several countries worldwide. Radiation exposure of healthy individuals due to prolonged CT screening rounds and, eventually, the additional examinations required in case of suspicious findings may represent a concern, thus eventually reducing the participation in an LCS program. Therefore, the present review aims to assess the potential radiation risk from LDCT in this setting, providing estimates of cumulative dose and radiation-related risk in LCS in order to improve awareness for an informed and complete attendance to the program. After summarizing the results of the international trials on LCS to introduce the benefits coming from the implementation of a dedicated program, the screening-related and participant-related factors determining the radiation risk will be introduced and their burden assessed. Finally, future directions for a personalized screening program as well as technical improvements to reduce the delivered dose will be presented.
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Affiliation(s)
- Chiara Pozzessere
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV), 1011 Lausanne, Switzerland
- Faculty of Biology and Medicine, University of Lausanne (UNIL), 1011 Lausanne, Switzerland
- Correspondence:
| | - Christophe von Garnier
- Faculty of Biology and Medicine, University of Lausanne (UNIL), 1011 Lausanne, Switzerland
- Division of Pulmonology, Department of Medicine, Lausanne University Hospital (CHUV), 1011 Lausanne, Switzerland
| | - Catherine Beigelman-Aubry
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV), 1011 Lausanne, Switzerland
- Faculty of Biology and Medicine, University of Lausanne (UNIL), 1011 Lausanne, Switzerland
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20
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Wang P, Chapron J, Bennani S, Revel MP, Wislez M. [Lung cancer screening: Update, news and perspectives]. Bull Cancer 2023; 110:42-54. [PMID: 36496261 DOI: 10.1016/j.bulcan.2022.11.006] [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: 10/11/2022] [Revised: 11/15/2022] [Accepted: 11/16/2022] [Indexed: 12/12/2022]
Abstract
Lung cancer is the leading cause of cancer death in France and worldwide (20 % of cancer deaths). This mortality is partly linked to an overrepresentation of metastatic stages at diagnosis (approximately 55 % of lung cancers at diagnosis). Low-dose chest CT in a target population to detect early forms accessible to radical treatment has been evaluated through multiple randomized trials (NLST, NELSON, MILD, DANTE…). These trials demonstrated a reduction in lung cancer specific mortality. The current problem is to integrate a CT screening policy CT at a national level, which should be both efficient and cost-effective, while presenting the least harms for the eligible population. Finally, it is necessary to optimize the participation of the eligible population and particularly in the most deprived areas and ensure the proper implementation of smoking cessation measures.
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Affiliation(s)
- Pascal Wang
- AP-HP, hôpital Cochin, université Paris Cité, unité d'oncologie thoracique, service de pneumologie, 75014 Paris, France
| | - Jeanne Chapron
- AP-HP, hôpital Cochin, université Paris Cité, unité d'oncologie thoracique, service de pneumologie, 75014 Paris, France
| | - Souhail Bennani
- AP-HP, hôpital Cochin, Université Paris Cité, service de radiologie, 75014 Paris, France
| | - Marie-Pierre Revel
- AP-HP, hôpital Cochin, Université Paris Cité, service de radiologie, 75014 Paris, France
| | - Marie Wislez
- AP-HP, hôpital Cochin, université Paris Cité, unité d'oncologie thoracique, service de pneumologie, 75014 Paris, France; Université de Paris, centre de recherche des cordeliers, sorbonne université, Inserm, Team Inflammation, Complement, and Cancer, 75006 Paris, France.
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21
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Abstract
Lung cancer is a leading cause of cancer death in the United States and globally with the majority of lung cancer cases attributable to cigarette smoking. Given the high societal and personal cost of a diagnosis of lung cancer including that most cases of lung cancer when diagnosed are found at a late stage, work over the past 40 years has aimed to detect lung cancer earlier when curative treatment is possible. Screening trials using chest radiography and sputum failed to show a reduction in lung cancer mortality however multiple studies using low dose CT have shown the ability to detect lung cancer early and a survival benefit to those screened. This review will discuss the history of lung cancer screening, current recommendations and screening guidelines, and implementation and components of a lung cancer screening program.
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22
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Byrne SC, Hammer MM. Malignant Nodules Detected on Lung Cancer Screening CT: Yield of Short-Term Follow-Up CT in Showing Nodule Growth. AJR Am J Roentgenol 2022; 219:735-741. [PMID: 35674352 PMCID: PMC10831801 DOI: 10.2214/ajr.22.27869] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND. Lung-RADS recommends 3-month follow-up for category 4A nodules and downgrading to category 2 of all category 3 or 4 nodules that are unchanged for 3 months or longer, indicating benign behavior. This guidance may be problematic considering the potential for slow-growing cancers in that lack of nodule growth, particularly at short follow-up intervals, may provide false reassurance. OBJECTIVE. The purpose of this study was to evaluate the yield of short-term follow-up CT in showing growth among malignant nodules detected on lung cancer screening CT. METHODS. This retrospective study included 76 patients (53 women, 23 men; median age, 68 years) with a positive lung cancer screening CT result (Lung-RADS category ≥ 3) between June 2015 and May 2021 with a subsequent lung cancer diagnosis and at least one follow-up CT examination at least 3 months before diagnostic or therapeutic intervention. Semiautomated software was used for linear and volumetric nodule measurements. Diameter was defined as the mean of short- and long-axis measurements. For solid nodules, growth was defined as an at least 1.5-mm increase in mean diameter or an at least 25% increase in volume; part-solid nodules, an at least 1.5-mm increase in solid-component mean diameter or an at least 25% increase in volume; and ground-glass nodules, an at least 3-mm increase in mean diameter or development of a new solid component within the nodule. RESULTS. Median time to growth was 13 months by linear and 11 months by volumetric measurement. Frequency of growth at 3 months was 5% by linear and 7% by volumetric measurement. By linear measurement, median time to growth and frequency of growth at 3 months were 13 months and 7% (solid nodules), 18 months and 6% (part-solid nodules), not reached and 0% (ground-glass nodules), not reached and 0% (category 3 nodules), 13 months and 6% (category 4A nodule)s, 6 months and 11% (category 4B nodules), and 12 months and 10% (category 4X nodules). CONCLUSION. Malignant nodules manifest growth slowly on follow-up CT, and 3-month follow-up CT has very low yield. Stability at 3-month follow-up should not instill high confidence in benignancy, and downgrading all such nodules to Lung-RADS category 2 may be problematic. CLINICAL IMPACT. This study highlights the possibility of slow-growing malignancy and associated challenges in application of Lung-RADS to management of unchanged nodules on follow-up imaging.
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Affiliation(s)
- Suzanne C Byrne
- Department of Radiology, Harvard Medical School, Brigham and Women's Hospital, 75 Francis St, Boston, MA 02115
| | - Mark M Hammer
- Department of Radiology, Harvard Medical School, Brigham and Women's Hospital, 75 Francis St, Boston, MA 02115
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23
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Hammer MM, Hunsaker AR. Strategies for Reducing False-Positive Screening Results for Intermediate-Size Nodules Evaluated Using Lung-RADS: A Secondary Analysis of National Lung Screening Trial Data. AJR Am J Roentgenol 2022; 219:397-405. [PMID: 35319912 PMCID: PMC9398972 DOI: 10.2214/ajr.22.27595] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
BACKGROUND. Lung-RADS version 1.1 (v1.1) classifies all solid nodules less than 6 mm as category 2. Lung-RADS v1.1 also classifies solid intermediate-size (6 to < 10 mm) nodules as category 2 if they are perifissural and have a triangular, polygonal, or ovoid shape (indicative of intrapulmonary lymph nodes). Additional category 2 criteria could reduce false-positive results of screening examinations. OBJECTIVE. The purpose of this study was to evaluate the impact of proposed strategies for reducing false-positive results for intermediate-size nodules on lung cancer screening CT evaluated using Lung-RADS v1.1. METHODS. This retrospective study entailed secondary analysis of National Lung Screening Trial (NLST) data. Of 1387 solid nodules measuring 6.0-9.5 mm on baseline screening CT examinations in the NLST, all 38 nodules in patients who developed cancer and a random sample of 200 nodules in patients who did not develop cancer were selected for further evaluation. Cancers were required to correspond with the baseline nodule on manual review. After exclusions, the sample included 223 patients (median age, 62 years; 143 men, 80 women; 196 benign nodules, 27 malignant nodules). Two thoracic radiologists independently reviewed baseline examinations to record nodule diameter and volume using semiautomated software and to determine whether nodules had perifissural location; other subpleural location; and triangular, polygonal, or ovoid shape. Different schemes for category 2 assignment were compared. RESULTS. Across readers, standard Lung-RADS v1.1 had sensitivity of 89-93% and specificity of 26-31%. A modification assigning nodules less than 10 mm with triangular, polygonal, or ovoid shape in other subpleural locations (vs only perifissural location) as category 2 had sensitivity of 85-93% and specificity of 47-51%. Lung-RADS v1.1 using volume cutoffs had sensitivity of 89-93% and specificity of 37% (both readers). The sensitivity of both modified Lung-RADS v1.1 and Lung-RADS v1.1 with volume cutoffs was not significantly different from standard Lung-RADS v1.1 (all p > .05). However, both schemes' specificity was significantly better than standard Lung-RADS v1.1 (all p < .05). Combining the two strategies yielded sensitivity of 85-93% and specificity of 58-59%. CONCLUSION. Classifying intermediate-size nodules with triangular, polygonal, or ovoid shape in any subpleural (not just perifissural) location as category 2 and using volume- rather than diameter-based measurements improves Lung-RADS specificity without decreased sensitivity. CLINICAL IMPACT. The findings can help reduce false-positive results, decreasing 6-month follow-up examinations for benign findings.
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Affiliation(s)
- Mark M Hammer
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115
| | - Andetta R Hunsaker
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115
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24
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Bonney A, Malouf R, Marchal C, Manners D, Fong KM, Marshall HM, Irving LB, Manser R. Impact of low-dose computed tomography (LDCT) screening on lung cancer-related mortality. Cochrane Database Syst Rev 2022; 8:CD013829. [PMID: 35921047 PMCID: PMC9347663 DOI: 10.1002/14651858.cd013829.pub2] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND Lung cancer is the most common cause of cancer-related death in the world, however lung cancer screening has not been implemented in most countries at a population level. A previous Cochrane Review found limited evidence for the effectiveness of lung cancer screening with chest radiography (CXR) or sputum cytology in reducing lung cancer-related mortality, however there has been increasing evidence supporting screening with low-dose computed tomography (LDCT). OBJECTIVES: To determine whether screening for lung cancer using LDCT of the chest reduces lung cancer-related mortality and to evaluate the possible harms of LDCT screening. SEARCH METHODS We performed the search in collaboration with the Information Specialist of the Cochrane Lung Cancer Group and included the Cochrane Lung Cancer Group Trial Register, Cochrane Central Register of Controlled Trials (CENTRAL, the Cochrane Library, current issue), MEDLINE (accessed via PubMed) and Embase in our search. We also searched the clinical trial registries to identify unpublished and ongoing trials. We did not impose any restriction on language of publication. The search was performed up to 31 July 2021. SELECTION CRITERIA: Randomised controlled trials (RCTs) of lung cancer screening using LDCT and reporting mortality or harm outcomes. DATA COLLECTION AND ANALYSIS: Two review authors were involved in independently assessing trials for eligibility, extraction of trial data and characteristics, and assessing risk of bias of the included trials using the Cochrane RoB 1 tool. We assessed the certainty of evidence using GRADE. Primary outcomes were lung cancer-related mortality and harms of screening. We performed a meta-analysis, where appropriate, for all outcomes using a random-effects model. We only included trials in the analysis of mortality outcomes if they had at least 5 years of follow-up. We reported risk ratios (RRs) and hazard ratios (HRs), with 95% confidence intervals (CIs) and used the I2 statistic to investigate heterogeneity. MAIN RESULTS: We included 11 trials in this review with a total of 94,445 participants. Trials were conducted in Europe and the USA in people aged 40 years or older, with most trials having an entry requirement of ≥ 20 pack-year smoking history (e.g. 1 pack of cigarettes/day for 20 years or 2 packs/day for 10 years etc.). One trial included male participants only. Eight trials were phase three RCTs, with two feasibility RCTs and one pilot RCT. Seven of the included trials had no screening as a comparison, and four trials had CXR screening as a comparator. Screening frequency included annual, biennial and incrementing intervals. The duration of screening ranged from 1 year to 10 years. Mortality follow-up was from 5 years to approximately 12 years. None of the included trials were at low risk of bias across all domains. The certainty of evidence was moderate to low across different outcomes, as assessed by GRADE. In the meta-analysis of trials assessing lung cancer-related mortality, we included eight trials (91,122 participants), and there was a reduction in mortality of 21% with LDCT screening compared to control groups of no screening or CXR screening (RR 0.79, 95% CI 0.72 to 0.87; 8 trials, 91,122 participants; moderate-certainty evidence). There were probably no differences in subgroups for analyses by control type, sex, geographical region, and nodule management algorithm. Females appeared to have a larger lung cancer-related mortality benefit compared to males with LDCT screening. There was also a reduction in all-cause mortality (including lung cancer-related) of 5% (RR 0.95, 95% CI 0.91 to 0.99; 8 trials, 91,107 participants; moderate-certainty evidence). Invasive tests occurred more frequently in the LDCT group (RR 2.60, 95% CI 2.41 to 2.80; 3 trials, 60,003 participants; moderate-certainty evidence). However, analysis of 60-day postoperative mortality was not significant between groups (RR 0.68, 95% CI 0.24 to 1.94; 2 trials, 409 participants; moderate-certainty evidence). False-positive results and recall rates were higher with LDCT screening compared to screening with CXR, however there was low-certainty evidence in the meta-analyses due to heterogeneity and risk of bias concerns. Estimated overdiagnosis with LDCT screening was 18%, however the 95% CI was 0 to 36% (risk difference (RD) 0.18, 95% CI -0.00 to 0.36; 5 trials, 28,656 participants; low-certainty evidence). Four trials compared different aspects of health-related quality of life (HRQoL) using various measures. Anxiety was pooled from three trials, with participants in LDCT screening reporting lower anxiety scores than in the control group (standardised mean difference (SMD) -0.43, 95% CI -0.59 to -0.27; 3 trials, 8153 participants; low-certainty evidence). There were insufficient data to comment on the impact of LDCT screening on smoking behaviour. AUTHORS' CONCLUSIONS: The current evidence supports a reduction in lung cancer-related mortality with the use of LDCT for lung cancer screening in high-risk populations (those over the age of 40 with a significant smoking exposure). However, there are limited data on harms and further trials are required to determine participant selection and optimal frequency and duration of screening, with potential for significant overdiagnosis of lung cancer. Trials are ongoing for lung cancer screening in non-smokers.
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Affiliation(s)
- Asha Bonney
- Department of Respiratory and Sleep Medicine, Royal Melbourne Hospital, Parkville, Australia
- Department of Medicine, University of Melbourne, Melbourne, Australia
| | - Reem Malouf
- National Perinatal Epidemiology Unit (NPEU), University of Oxford, Oxford, UK
| | | | - David Manners
- Respiratory Medicine, Midland St John of God Public and Private Hospital, Midland, Australia
| | - Kwun M Fong
- Thoracic Medicine Program, The Prince Charles Hospital, Brisbane, Australia
- UQ Thoracic Research Centre, School of Medicine, The University of Queensland, Brisbane, Australia
| | - Henry M Marshall
- School of Medicine, The University of Queensland, Brisbane, Australia
| | - Louis B Irving
- Department of Respiratory and Sleep Medicine, Royal Melbourne Hospital, Parkville, Australia
| | - Renée Manser
- Department of Respiratory and Sleep Medicine, Royal Melbourne Hospital, Parkville, Australia
- Department of Haematology and Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, Australia
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25
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Wood DE, Kazerooni EA, Aberle D, Berman A, Brown LM, Eapen GA, Ettinger DS, Ferguson JS, Hou L, Kadaria D, Klippenstein D, Kumar R, Lackner RP, Leard LE, Lennes IT, Leung ANC, Mazzone P, Merritt RE, Midthun DE, Onaitis M, Pipavath S, Pratt C, Puri V, Raz D, Reddy C, Reid ME, Sandler KL, Sands J, Schabath MB, Studts JL, Tanoue L, Tong BC, Travis WD, Wei B, Westover K, Yang SC, McCullough B, Hughes M. NCCN Guidelines® Insights: Lung Cancer Screening, Version 1.2022. J Natl Compr Canc Netw 2022; 20:754-764. [PMID: 35830884 DOI: 10.6004/jnccn.2022.0036] [Citation(s) in RCA: 51] [Impact Index Per Article: 25.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
The NCCN Guidelines for Lung Cancer Screening recommend criteria for selecting individuals for screening and provide recommendations for evaluation and follow-up of lung nodules found during initial and subsequent screening. These NCCN Guidelines Insights focus on recent updates to the NCCN Guidelines for Lung Cancer Screening.
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Affiliation(s)
- Douglas E Wood
- Fred Hutchinson Cancer Research Center/Seattle Cancer Care Alliance
| | | | | | - Abigail Berman
- Abramson Cancer Center at the University of Pennsylvania
| | | | | | | | | | - Lifang Hou
- Robert H. Lurie Comprehensive Cancer Center of Northwestern University
| | - Dipen Kadaria
- St. Jude Children's Research Hospital/The University of Tennessee Health Science Center
| | | | | | | | | | | | | | - Peter Mazzone
- Case Comprehensive Cancer Center/University Hospitals Seidman Cancer Center and Cleveland Clinic Taussig Cancer Institute
| | - Robert E Merritt
- The Ohio State University Comprehensive Cancer Center - James Cancer Hospital and Solove Research Institute
| | | | - Mark Onaitis
- Fred Hutchinson Cancer Research Center/Seattle Cancer Care Alliance
| | | | | | - Varun Puri
- Siteman Cancer Center at Barnes-Jewish Hospital and Washington University School of Medicine
| | - Dan Raz
- City of Hope National Medical Center
| | | | | | | | - Jacob Sands
- Dana-Farber/Brigham and Women's Cancer Center
| | | | | | | | | | | | | | | | - Stephen C Yang
- The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins
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26
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Yoon DW, Kim CH, Hwang S, Choi YL, Cho JH, Kim HK, Choi YS, Kim J, Shim YM, Shin S, Lee HY. Reappraising the clinical usability of consolidation-to-tumor ratio on CT in clinical stage IA lung cancer. Insights Imaging 2022; 13:103. [PMID: 35715654 PMCID: PMC9206049 DOI: 10.1186/s13244-022-01235-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Accepted: 05/12/2022] [Indexed: 11/25/2022] Open
Abstract
Objectives Ground-glass opacity (GGO) on computed tomography is associated with prognosis in early-stage non-small cell lung cancer (NSCLC) patients. However, the stratification of the prognostic value of GGO is controversial. We aimed to evaluate clinicopathologic characteristics of early-stage NSCLC based on the consolidation-to-tumor ratio (CTR), conduct multi-pronged analysis, and stratify prognosis accordingly. Methods We retrospectively investigated 944 patients with clinical stage IA NSCLC, who underwent curative-intent lung resection between August 2018 and January 2020. The CTR was measured and used to categorize patients into six groups (1, 0%; 2, 0–25%; 3, 25–50%; 4, 50–75%; 5, 75–100%; and 6, 100%). Results Pathologic nodal upstaging was found in 1.8% (group 4), 9.0% (group 5), and 17.4% (group 6), respectively. The proportion of patients with a high grade of tumor-infiltrating lymphocytes tended to decrease as the CTR increased. In a subtype analysis of patients with adenocarcinoma, all of the patients with predominant micro-papillary patterns were in the CTR > 50% groups, and most of the patients with predominant solid patterns were in group 6 (47/50, 94%). The multivariate analysis demonstrated that CTR 75–100% (hazard ratio [HR], 3.85; 95% confidence interval [CI], 1.58–9.36) and CTR 100% (HR, 5.58; 95% CI, 2.45–12.72) were independent prognostic factors for DFS, regardless of tumor size. Conclusion We demonstrated that the CTR could provide various noninvasive clinicopathological information. A CTR of more than 75% is the factor associated with a poor prognosis and should be considered when making therapeutic plans for patients with early-stage NSCLC.
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Affiliation(s)
- Dong Woog Yoon
- Department of Thoracic and Cardiovascular Surgery, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Korea
| | - Chu Hyun Kim
- Center for Health Promotion, Samsung Medical Center, Seoul, Korea
| | - Soohyun Hwang
- Department of Pathology and Translational Genomics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Yoon-La Choi
- Department of Pathology and Translational Genomics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Jong Ho Cho
- Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-Gu, Seoul, 06351, Korea
| | - Hong Kwan Kim
- Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-Gu, Seoul, 06351, Korea
| | - Yong Soo Choi
- Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-Gu, Seoul, 06351, Korea
| | - Jhingook Kim
- Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-Gu, Seoul, 06351, Korea
| | - Young Mog Shim
- Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-Gu, Seoul, 06351, Korea
| | - Sumin Shin
- Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-Gu, Seoul, 06351, Korea. .,Department of Thoracic and Cardiovascular Surgery, School of Medicine, Ewha Womans University, Mok-dong Hospital, Seoul, Korea.
| | - Ho Yun Lee
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-Gu, Seoul, 06351, Korea. .,Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, 06351, Korea.
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27
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Darçot E, Jreige M, Rotzinger DC, Gidoin Tuyet Van S, Casutt A, Delacoste J, Simons J, Long O, Buela F, Ledoux JB, Prior JO, Lovis A, Beigelman-Aubry C. Comparison Between Magnetic Resonance Imaging and Computed Tomography in the Detection and Volumetric Assessment of Lung Nodules: A Prospective Study. Front Med (Lausanne) 2022; 9:858731. [PMID: 35573012 PMCID: PMC9096346 DOI: 10.3389/fmed.2022.858731] [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: 01/20/2022] [Accepted: 03/25/2022] [Indexed: 11/22/2022] Open
Abstract
Rationale and Objectives Computed tomography (CT) lung nodule assessment is routinely performed and appears very promising for lung cancer screening. However, the radiation exposure through time remains a concern. With the overall goal of an optimal management of indeterminate lung nodules, the objective of this prospective study was therefore to evaluate the potential of optimized ultra-short echo time (UTE) MRI for lung nodule detection and volumetric assessment. Materials and Methods Eight (54.9 ± 13.2 years) patients with at least 1 non-calcified nodule ≥4 mm were included. UTE under high-frequency non-invasive ventilation (UTE-HF-NIV) and in free-breathing at tidal volume (UTE-FB) were investigated along with volumetric interpolated breath-hold examination at full inspiration (VIBE-BH). Three experienced readers assessed the detection rate of nodules ≥4 mm and ≥6 mm, and reported their location, 2D-measurements and solid/subsolid nature. Volumes were measured by two experienced readers. Subsequently, two readers assessed the detection and volume measurements of lung nodules ≥4mm in gold-standard CT images with soft and lung kernel reconstructions. Volumetry was performed with lesion management software (Carestream, Rochester, New York, USA). Results UTE-HF-NIV provided the highest detection rate for nodules ≥4 mm (n = 66) and ≥6 mm (n = 32) (35 and 50%, respectively). No dependencies were found between nodule detection and their location in the lung with UTE-HF-NIV (p > 0.4), such a dependency was observed for two readers with VIBE-BH (p = 0.002 and 0.03). Dependencies between the nodule's detection and their size were noticed among readers and techniques (p < 0.02). When comparing nodule volume measurements, an excellent concordance was observed between CT and UTE-HF-NIV, with an overestimation of 13.2% by UTE-HF-NIV, <25%-threshold used for nodule's growth, conversely to VIBE-BH that overestimated the nodule volume by 28.8%. Conclusion UTE-HF-NIV is not ready to replace low-dose CT for lung nodule detection, but could be used for follow-up studies, alternating with CT, based on its volumetric accuracy.
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Affiliation(s)
- Emeline Darçot
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland.,Faculty of Biology and Medicine, University of Lausanne (UNIL), Lausanne, Switzerland
| | - Mario Jreige
- Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - David C Rotzinger
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland.,Faculty of Biology and Medicine, University of Lausanne (UNIL), Lausanne, Switzerland
| | - Stacey Gidoin Tuyet Van
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Alessio Casutt
- Department of Pulmonology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Jean Delacoste
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland.,Faculty of Biology and Medicine, University of Lausanne (UNIL), Lausanne, Switzerland
| | - Julien Simons
- Department of Physiotherapy, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Olivier Long
- Department of Physiotherapy, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Flore Buela
- Department of Physiotherapy, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Jean-Baptiste Ledoux
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland.,Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - John O Prior
- Faculty of Biology and Medicine, University of Lausanne (UNIL), Lausanne, Switzerland.,Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Alban Lovis
- Faculty of Biology and Medicine, University of Lausanne (UNIL), Lausanne, Switzerland.,Department of Pulmonology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Catherine Beigelman-Aubry
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland.,Faculty of Biology and Medicine, University of Lausanne (UNIL), Lausanne, Switzerland
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[Chinese Experts Consensus on Artificial Intelligence Assisted Management for
Pulmonary Nodule (2022 Version)]. ZHONGGUO FEI AI ZA ZHI = CHINESE JOURNAL OF LUNG CANCER 2022; 25:219-225. [PMID: 35340198 PMCID: PMC9051301 DOI: 10.3779/j.issn.1009-3419.2022.102.08] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Low-dose computed tomography (CT) for lung cancer screening has been proven to reduce lung cancer deaths in the screening group compared with the control group. The increasing number of pulmonary nodules being detected by CT scans significantly increase the workload of the radiologists for scan interpretation. Artificial intelligence (AI) has the potential to increase the efficiency of pulmonary nodule discrimination and has been tested in preliminary studies for nodule management. As more and more artificial AI products are commercialized, the consensus statement has been organized in a collaborative effort by Thoracic Surgery Committee, Department of Simulated Medicine, Wu Jieping Medical Foundation to aid clinicians in the application of AI-assisted management for pulmonary nodules.
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Kerpel-Fronius A, Monostori Z, Kovacs G, Ostoros G, Horvath I, Solymosi D, Pipek O, Szatmari F, Kovacs A, Markoczy Z, Rojko L, Renyi-Vamos F, Hoetzenecker K, Bogos K, Megyesfalvi Z, Dome B. Nationwide lung cancer screening with low-dose computed tomography: implementation and first results of the HUNCHEST screening program. Eur Radiol 2022; 32:4457-4467. [PMID: 35247089 DOI: 10.1007/s00330-022-08589-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 12/20/2021] [Accepted: 01/13/2022] [Indexed: 12/24/2022]
Abstract
OBJECTIVES Lung cancer (LC) kills more people than any other cancer in Hungary. Hence, there is a clear rationale for considering a national screening program. The HUNCHEST pilot program primarily aimed to investigate the feasibility of a population-based LC screening in Hungary, and determine the incidence and LC probability of solitary pulmonary nodules. METHODS A total of 1890 participants were assigned to undergo low-dose CT (LDCT) screening, with intervals of 1 year between procedures. Depending on the volume, growth, and volume doubling time (VDT), screenings were defined as negative, indeterminate, or positive. Non-calcified lung nodules with a volume > 500 mm3 and/or a VDT < 400 days were considered positive. LC diagnosis was based on histology. RESULTS At baseline, the percentage of negative, indeterminate, and positive tests was 81.2%, 15.1%, and 3.7%, respectively. The frequency of positive and indeterminate LDCT results was significantly higher in current smokers (vs. non-smokers or former smokers; p < 0.0001) and in individuals with COPD (vs. those without COPD, p < 0.001). In the first screening round, 1.2% (n = 23) of the participants had a malignant lesion, whereas altogether 1.5% (n = 29) of the individuals were diagnosed with LC. The overall positive predictive value of the positive tests was 31.6%. Most lung malignancies were diagnosed at an early stage (86.2% of all cases). CONCLUSIONS In terms of key characteristics, our prospective cohort study appears consistent to that of comparable studies. Altogether, the results of the HUNCHEST pilot program suggest that LDCT screening may facilitate early diagnosis and thus curative-intent treatment in LC. KEY POINTS • The HUNCHEST pilot study is the first nationwide low-dose CT screening program in Hungary. • In the first screening round, 1.2% of the participants had a malignant lesion, whereas altogether 1.5% of the individuals were diagnosed with lung cancer. • The overall positive predictive value of the positive tests in the HUNCHEST screening program was 31.6%.
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Affiliation(s)
- Anna Kerpel-Fronius
- National Koranyi Institute of Pulmonology, Korányi Frigyes út 1, Budapest, 1121, Hungary
| | - Zsuzsanna Monostori
- National Koranyi Institute of Pulmonology, Korányi Frigyes út 1, Budapest, 1121, Hungary
| | - Gabor Kovacs
- National Koranyi Institute of Pulmonology, Korányi Frigyes út 1, Budapest, 1121, Hungary
| | - Gyula Ostoros
- National Koranyi Institute of Pulmonology, Korányi Frigyes út 1, Budapest, 1121, Hungary
| | - Istvan Horvath
- Affidea Diagnostics Hungary, Szent Margit and Nyiro Gyula Hospitals, Budapest, Hungary
| | - Diana Solymosi
- National Koranyi Institute of Pulmonology, Korányi Frigyes út 1, Budapest, 1121, Hungary
| | - Orsolya Pipek
- Department of Physics of Complex Systems, Eotvos Lorand University, Budapest, Hungary
| | - Ferenc Szatmari
- Affidea Diagnostics Hungary, Petz Aladar Hospital, Gyor, Hungary
| | - Anita Kovacs
- Department of Radiology, Albert Szent-Gyorgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Zsolt Markoczy
- National Koranyi Institute of Pulmonology, Korányi Frigyes út 1, Budapest, 1121, Hungary
| | - Livia Rojko
- National Koranyi Institute of Pulmonology, Korányi Frigyes út 1, Budapest, 1121, Hungary
| | - Ferenc Renyi-Vamos
- National Koranyi Institute of Pulmonology, Korányi Frigyes út 1, Budapest, 1121, Hungary.,Department of Thoracic Surgery, Semmelweis University and National Institute of Oncology, Budapest, Hungary
| | - Konrad Hoetzenecker
- Department of Thoracic Surgery, Comprehensive Cancer Center, Medical University of Vienna, Waehringer Guertel 18-20, A-1090, Vienna, Austria
| | - Krisztina Bogos
- National Koranyi Institute of Pulmonology, Korányi Frigyes út 1, Budapest, 1121, Hungary.
| | - Zsolt Megyesfalvi
- National Koranyi Institute of Pulmonology, Korányi Frigyes út 1, Budapest, 1121, Hungary.,Department of Thoracic Surgery, Semmelweis University and National Institute of Oncology, Budapest, Hungary.,Department of Thoracic Surgery, Comprehensive Cancer Center, Medical University of Vienna, Waehringer Guertel 18-20, A-1090, Vienna, Austria
| | - Balazs Dome
- National Koranyi Institute of Pulmonology, Korányi Frigyes út 1, Budapest, 1121, Hungary. .,Department of Thoracic Surgery, Semmelweis University and National Institute of Oncology, Budapest, Hungary. .,Department of Thoracic Surgery, Comprehensive Cancer Center, Medical University of Vienna, Waehringer Guertel 18-20, A-1090, Vienna, Austria.
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Lung Cancer Imaging: Screening Result and Nodule Management. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19042460. [PMID: 35206646 PMCID: PMC8874950 DOI: 10.3390/ijerph19042460] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 02/08/2022] [Accepted: 02/14/2022] [Indexed: 02/07/2023]
Abstract
Background: Lung cancer (LC) represents the main cause of cancer-related deaths worldwide, especially because the majority of patients present with an advanced stage of the disease at the time of diagnosis. This systematic review describes the evidence behind screening results and the current guidelines available to manage lung nodules. Methods: This review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. The following electronic databases were searched: PubMed, EMBASE, and the Web of Science. Results: Five studies were included in the systematic review. The study cohort included 46,364 patients, and, in this case series, LC was detected in 9028 patients. Among the patients with detected LC, 1261 died of lung cancer, 3153 died of other types of cancers and 4614 died of other causes. Conclusions: This systematic review validates the use of CT in LC screening follow-ups, and bids for future integration and implementation of nodule management protocols to improve LC screening, avoid missed cancers and to reduce the number of unnecessary investigations.
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Du Y, Sidorenkov G, Heuvelmans MA, Vliegenthart R, Groen HJ, Greuter MJ, de Bock GH. Lung cancer screening with low-dose CT: simulating the effect of starting screening at a younger age in women. Eur J Radiol 2022; 148:110182. [DOI: 10.1016/j.ejrad.2022.110182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Revised: 01/17/2022] [Accepted: 01/26/2022] [Indexed: 11/03/2022]
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Dudurych I, Garcia-Uceda A, Saghir Z, Tiddens HAWM, Vliegenthart R, de Bruijne M. Creating a training set for artificial intelligence from initial segmentations of airways. Eur Radiol Exp 2021; 5:54. [PMID: 34841480 PMCID: PMC8627914 DOI: 10.1186/s41747-021-00247-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 10/04/2021] [Indexed: 12/02/2022] Open
Abstract
Airways segmentation is important for research about pulmonary disease but require a large amount of time by trained specialists. We used an openly available software to improve airways segmentations obtained from an artificial intelligence (AI) tool and retrained the tool to get a better performance. Fifteen initial airway segmentations from low-dose chest computed tomography scans were obtained with a 3D-Unet AI tool previously trained on Danish Lung Cancer Screening Trial and Erasmus-MC Sophia datasets. Segmentations were manually corrected in 3D Slicer. The corrected airway segmentations were used to retrain the 3D-Unet. Airway measurements were automatically obtained and included count, airway length and luminal diameter per generation from the segmentations. Correcting segmentations required 2–4 h per scan. Manually corrected segmentations had more branches (p < 0.001), longer airways (p < 0.001) and smaller luminal diameters (p = 0.004) than initial segmentations. Segmentations from retrained 3D-Unets trended towards more branches and longer airways compared to the initial segmentations. The largest changes were seen in airways from 6th generation onwards. Manual correction results in significantly improved segmentations and is potentially a useful and time-efficient method to improve the AI tool performance on a specific hospital or research dataset.
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Affiliation(s)
- Ivan Dudurych
- Department of Radiology, University of Groningen, University Medical Centre Groningen, Groningen, Netherlands.
| | - Antonio Garcia-Uceda
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands.,Department of Paediatric Pulmonology and Allergology, Erasmus MC-Sophia Children Hospital, Rotterdam, Netherlands
| | - Zaigham Saghir
- Department of Medicine, Section of Pulmonary Medicine, Herlev-Gentofte Hospital, Hellerup, Denmark.,Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Harm A W M Tiddens
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands.,Department of Paediatric Pulmonology and Allergology, Erasmus MC-Sophia Children Hospital, Rotterdam, Netherlands
| | - Rozemarijn Vliegenthart
- Department of Radiology, University of Groningen, University Medical Centre Groningen, Groningen, Netherlands
| | - Marleen de Bruijne
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands.,Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
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Abstract
Background: Nodules may have different lung cancer risks when new on follow-up CT versus when present on an earlier CT ("existing" nodules). Diameter-based Lung-RADS and volume-based NELSON categories have shown variable performance in nodule risk assessment. Objective: To assess Lung-RADS and NELSON classifications for nodules detected on follow-up lung cancer screening CT examinations. Methods: This retrospective study included 185 patients (100 women, 85 men; median age, 66 years) who underwent lung cancer screening CT examinations for which a prior CT was available. Stratified random sampling was performed to enrich the sample with suspicious nodules, yielding 50, 45, 47, 30, and 13 nodules with Lung-RADS categories 2, 3, 4A, 4B, and 4X, respectively. Lung-RADS categories were recorded from clinical reports. Nodules' linear measurements were extracted from clinical reports to generate Lung-RADS categories using strict criteria. Two radiologists used a semiautomated tool to obtain nodule volumes, which were used to generate NELSON categories. Lung cancer risk was assessed. ROC analysis was performed. Percentages were weighted by Lung-RADS category frequencies in the underlying screening cohort. Results: Twenty-nine cancers were diagnosed. Weighted cancer risk was 5% for new nodules, 1% for stable existing nodules, and 44% for growing existing nodules. No clinical category 2 nodule was cancer. Using strict Lung-RADS, 34 nodules, including 7 cancers, were downgraded to category 2. AUC for cancer was 0.96 for clinical Lung-RADS, 0.81 for strict Lung-RADS, 0.71-0.84 for NELSON (two readers), and 0.89 for nodule diameter. Clinical Lung-RADS achieved weighted sensitivity and specificity of 100% and 85% in the entire sample, 100% and 41% in new nodules, and 100% and 94% in existing nodules. Optimal diameter threshold was 8 mm for existing nodules, versus 6 mm for new nodules. Conclusions: Lung-RADS, as applied by radiologists in clinical practice, achieved excellent performance on follow-up screening examinations. Strict Lung-RADS downgraded some cancers to category 2. Volumetric assessments had weaker performance than clinical Lung-RADS. New nodules warrant smaller size thresholds than existing nodules. Clinical Impact: The findings provide insight into radiologists' management of nodules detected on follow-up screening examinations.
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Using Electronic Medical Records to Identify Potentially Eligible Study Subjects for Lung Cancer Screening with Biomarkers. Cancers (Basel) 2021; 13:cancers13215449. [PMID: 34771612 PMCID: PMC8582572 DOI: 10.3390/cancers13215449] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 10/18/2021] [Accepted: 10/19/2021] [Indexed: 11/18/2022] Open
Abstract
Simple Summary Recent cancer screening trials have found that using low-dose computed tomography (LDCT), compared to chest radiography, resulted in a significant reduction in lung cancer mortality. To effectively carry out this intervention, individuals at a high risk of developing lung cancer are targeted. However, accurately identifying and retaining these groups can be challenging. As electronic medical records (EMRs) contain important demographic and clinical information, they could be used to accurately identify subjects for screening. To determine whether EMRs can be used for this purpose, this paper examines the evidence around the use of EMRs in screening trials and the information contained in them that could be used to aid researchers in identifying eligible subjects. Abstract Lung cancer screening trials using low-dose computed tomography (LDCT) show reduced late-stage diagnosis and mortality rates. These trials have identified high-risk groups that would benefit from screening. However, these sub-populations can be difficult to access and retain in trials. Implementation of national screening programmes further suggests that there is poor uptake in eligible populations. A new approach to participant selection may be more effective. Electronic medical records (EMRs) are a viable alternative to population-based or health registries, as they contain detailed clinical and demographic information. Trials have identified that e-screening using EMRs has improved trial retention and eligible subject identification. As such, this paper argues for greater use of EMRs in trial recruitment and screening programmes. Moreover, this opinion paper explores the current issues in and approaches to lung cancer screening, whether records can be used to identify eligible subjects for screening and the challenges that researchers face when using EMR data.
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Defining growth in small pulmonary nodules using volumetry: results from a "coffee-break" CT study and implications for current nodule management guidelines. Eur Radiol 2021; 32:1912-1920. [PMID: 34580748 PMCID: PMC8831344 DOI: 10.1007/s00330-021-08302-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 08/10/2021] [Accepted: 08/24/2021] [Indexed: 12/17/2022]
Abstract
Objectives
An increase in lung nodule volume on serial CT may represent true growth or measurement variation. In nodule guidelines, a 25% increase in nodule volume is frequently used to determine that growth has occurred; this is based on previous same-day, test–retest (coffee-break) studies examining metastatic nodules. Whether results from prior studies apply to small non-metastatic nodules is unknown. This study aimed to establish the interscan variability in the volumetric measurements of small-sized non-metastatic nodules. Methods Institutional review board approval was obtained for this study. Between March 2019 and January 2021, 45 adults (25 males; mean age 65 years, range 37–84 years) with previously identified pulmonary nodules (30–150 mm3) requiring surveillance, without a known primary tumour, underwent two same-day CT scans. Non-calcified solid nodules were measured using commercial volumetry software, and interscan variability of volume measurements was assessed using a Bland–Altman method and limits of agreement. Results One hundred nodules (range 28–170 mm3; mean 81.1 mm3) were analysed. The lower and upper limits of agreement for the absolute volume difference between the two scans were − 14.2 mm3 and 12.0 mm3 respectively (mean difference 1.09 mm3, range − 33–12 mm3). The lower and upper limits of agreement for relative volume difference were − 16.4% and 14.6% respectively (mean difference 0.90%, range − 24.1–32.8%). Conclusions The interscan volume variability in this cohort of small non-metastatic nodules was smaller than that in previous studies involving lung metastases of varying sizes. An increase of 15% in nodule volume on sequential CT may represent true growth, and closer surveillance of these nodules may be warranted. Key Points • In current pulmonary nodule management guidelines, a threshold of 25% increase in volume is required to determine that true growth of a pulmonary nodule has occurred. • This test–retest (coffee break) study has demonstrated that a smaller threshold of 15% increase in volume may represent true growth in small non-metastatic nodules. • Closer surveillance of some small nodules growing 15–25% over a short interval may be appropriate.
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Iball GR, Darby M, Gabe R, Crosbie PAJ, Callister MEJ. Establishing scanning protocols for a CT lung cancer screening trial in the UK. Br J Radiol 2021; 94:20201343. [PMID: 34555954 DOI: 10.1259/bjr.20201343] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVES To develop a CT scanning protocol for lung cancer screening which achieved low radiation dose and a high level of objectively assessed image quality. METHODS An anthropomorphic chest phantom and a commercially available lung screening image quality phantom were scanned on a series of scan protocols from a previous UK lung screening pilot and on an alternative protocol. The chest phantom scans were used to assess the CT dose metrics on community-based mobile CT scanners and comparisons were made with published recommended doses. Scans of the image quality phantom were objectively assessed against the RSNA Quantitative Imaging Biomarkers Alliance (QIBA) recommendations. Protocol adjustments were made to ensure that the recommended dose and image quality levels were both achieved. RESULTS The alternative scan protocol yielded doses up to 72% lower than on the previously used protocols with a CTDIvol of 0.6mGy for the 55 kg equivalent phantom and 1.3mGy with an additional 6 cm of tissue equivalent material in place. Scans on the existing protocols failed on two of the QIBA image quality metrics (edge enhancement and 3D resolution aspect ratio). Following adjustments to the reconstruction parameters of the resulting image quality met all six QIBA recommendations. Radiologist review of phantom images with this scan protocol deemed them suitable for a lung screening trial. CONCLUSIONS Scan protocols yielding low radiation doses and high levels of objectively assessed image quality which meet published criteria can be established through the use of specific anthropomorphic and image quality phantoms, and are deliverable in community-based lung cancer screening. ADVANCES IN KNOWLEDGE Development of a standard methodology for establishing CT lung screening scanning protocolsUse of QIBA recommendations as objective image quality metricsStandardised lung phantoms are essential tools for setting up lung screening protocols.
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Affiliation(s)
- Gareth R Iball
- Department of Medical Physics & Engineering, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
| | - Michael Darby
- Department of Radiology, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
| | - Rhian Gabe
- Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, United Kingdom
| | - Philip A J Crosbie
- Division of Infection, Immunity & Respiratory Medicine, University of Manchester, England, United Kingdom
| | - Matthew E J Callister
- Department of Respiratory Medicine, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
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Erdoğu V, Çitak N, Yerlioğlu A, Aksoy Y, Emetli Y, Pekçolaklar A, Saydam Ö, Metin M. Is the Yedikule-solitary pulmonary nodule malignancy risk score sufficient to predict malignancy? An internal validation study. Interact Cardiovasc Thorac Surg 2021; 33:258-265. [PMID: 33792653 PMCID: PMC8691517 DOI: 10.1093/icvts/ivab083] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 01/27/2021] [Accepted: 02/18/2021] [Indexed: 12/26/2022] Open
Abstract
OBJECTIVES We aimed to develop a malignancy risk score model for solitary pulmonary nodules (SPNs) using the demographic, radiological and clinical characteristics of patients in our centre. The model was then internally validated for malignancy risk estimation. METHODS A total of 270 consecutive patients who underwent surgery for SPN between June 2017 and May 2019 were retrospectively analysed. Using the receiver operating characteristic curve analysis, cut-off values were determined for radiological tumour diameter, maximum standardized uptake value and the Brock University probability of malignancy (BU-PM) model. The Yedikule-SPN malignancy risk model was developed using these cut-off values and demographic, radiological and clinical criteria in the first 180 patients (study cohort) and internally validated with the next 90 patients (validation cohort). The Yedikule-SPN model was then compared with the BU-PM model in terms of malignancy prediction. RESULTS Malignancy was reported in 171 patients (63.3%). Maximum standardized uptake value and BU-PM scores were sufficient to predict malignancy (P < 0.001 for both), while the effectiveness of nodule size determined on thoracic computed tomography did not reach statistical significance (P = 0.09). When the Yedikule-SPN model developed with the study cohort was applied to the validation cohort, it significantly predicted malignancy (area under the receiver operating characteristic curve: 0.883, 95% confidence interval: 0.827-0.957, P < 0.001). Comparison of patients in the validation group with Yedikule-SPN scores above (n = 53) and below (n = 37) the cut-off value of 65.75 showed that the malignancy rate was significantly higher among patients with Yedikule-SPN score over 65.75 (86.8% vs 21.6%, P < 0.001, odds ratio = 23.821, 95% confidence interval: 7.805-72.701). When compared with the BU-PM model in all patients, the Yedikule-SPN model tended to be a better predictor of malignancy (P = 0.06). CONCLUSIONS The internally validated Yedikule-SPN model is also a good predictor of the malignancy of SPN(s). Prospective and multicentre external validation studies with large patients' cohorts are needed.
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Affiliation(s)
- Volkan Erdoğu
- Department of Thoracic Surgery, Yedikule Chest Diseases and Thoracic Surgery Training and Research Hospital, Istanbul, Turkey
| | - Necati Çitak
- Thoracic Surgery Department, Bakirkoy Dr Sadi Konuk Training and Research Hospital, Istanbul, Turkey
| | - Aynur Yerlioğlu
- Department of Thoracic Surgery, Yedikule Chest Diseases and Thoracic Surgery Training and Research Hospital, Istanbul, Turkey
| | - Yunus Aksoy
- Department of Thoracic Surgery, Yedikule Chest Diseases and Thoracic Surgery Training and Research Hospital, Istanbul, Turkey
| | - Yasemin Emetli
- Department of Thoracic Surgery, Yedikule Chest Diseases and Thoracic Surgery Training and Research Hospital, Istanbul, Turkey
| | - Atilla Pekçolaklar
- Thoracic Surgery Department, Bursa City Hospital Thoracic Surgery Department, Bursa, Turkey
| | - Özkan Saydam
- Department of Thoracic Surgery, Yedikule Chest Diseases and Thoracic Surgery Training and Research Hospital, Istanbul, Turkey
| | - Muzaffer Metin
- Department of Thoracic Surgery, Yedikule Chest Diseases and Thoracic Surgery Training and Research Hospital, Istanbul, Turkey
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Goudemant C, Durieux V, Grigoriu B, Berghmans T. [Lung cancer screening with low dose computed tomography : a systematic review]. Rev Mal Respir 2021; 38:489-505. [PMID: 33994043 DOI: 10.1016/j.rmr.2021.04.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Accepted: 02/26/2021] [Indexed: 12/24/2022]
Abstract
INTRODUCTION Bronchial cancer, often diagnosed at a late stage, is the leading cause of cancer death. As early detection could potentially lead to curative treatment, several studies have evaluated low-dose chest CT (LDCT) as a screening method. The main objective of this work is to determine the impact of LDCT screening on overall mortality of a smoking population. METHODS Systematic review of randomised controlled screening trials comparing LDCT with no screening or chest x-ray. RESULTS Thirteen randomised controlled trials were identified, seven of which reported mortality results. NSLT showed a significant reduction of 6.7% in overall mortality and 20% in lung cancer mortality after 6.5 years of follow-up. NELSON showed a significant reduction in lung cancer mortality of 24% at 10 years among men. LUSI and MILD showed a reduction in lung cancer mortality of 69% at 8 years among women and 39% at 10 years, respectively. CONCLUSION Screening for bronchial cancer is a complex issue. Clarification is needed regarding the selection of individuals, the definition of a positive result and the attitude towards a suspicious nodule.
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Affiliation(s)
- C Goudemant
- Département des soins intensifs & urgences oncologiques et clinique d'oncologie thoracique, institut Jules-Bordet, Rue Héger-Bordet 1, 1000 Bruxelles, Belgique.
| | - V Durieux
- Bibliothèque des Sciences de la Santé, Université libre de Bruxelles
| | - B Grigoriu
- Département des soins intensifs & urgences oncologiques et clinique d'oncologie thoracique, institut Jules-Bordet, Rue Héger-Bordet 1, 1000 Bruxelles, Belgique
| | - T Berghmans
- Département des soins intensifs & urgences oncologiques et clinique d'oncologie thoracique, institut Jules-Bordet, Rue Héger-Bordet 1, 1000 Bruxelles, Belgique
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Snoeckx A, Franck C, Silva M, Prokop M, Schaefer-Prokop C, Revel MP. The radiologist's role in lung cancer screening. Transl Lung Cancer Res 2021; 10:2356-2367. [PMID: 34164283 PMCID: PMC8182709 DOI: 10.21037/tlcr-20-924] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Lung cancer is still the deadliest cancer in men and women worldwide. This high mortality is related to diagnosis in advanced stages, when curative treatment is no longer an option. Large randomized controlled trials have shown that lung cancer screening (LCS) with low-dose computed tomography (CT) can detect lung cancers at earlier stages and reduce lung cancer-specific mortality. The recent publication of the significant reduction of cancer-related mortality by 26% in the Dutch-Belgian NELSON LCS trial has increased the likelihood that implementation of LCS in Europe will move forward. Radiologists are important stakeholders in numerous aspects of the LCS pathway. Their role goes beyond nodule detection and nodule management. Being part of a multidisciplinary team, radiologists are key players in numerous aspects of implementation of a high quality LCS program. In this non-systematic review we discuss the multifaceted role of radiologists in LCS.
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Affiliation(s)
- Annemiek Snoeckx
- Department of Radiology, Antwerp University Hospital and University of Antwerp, Edegem, Belgium
| | - Caro Franck
- Department of Radiology, Antwerp University Hospital and University of Antwerp, Edegem, Belgium
| | - Mario Silva
- Scienze Radiologiche, Department of Medicine and Surgery (DiMeC), University of Parma, Parma, Italy
| | - Mathias Prokop
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | | | - Marie-Pierre Revel
- Department of Radiology, Cochin Hospital, APHP Centre, Université de Paris, Paris, France
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Silva M, Milanese G, Ledda RE, Pastorino U, Sverzellati N. Screen-detected solid nodules: from detection of nodule to structured reporting. Transl Lung Cancer Res 2021; 10:2335-2346. [PMID: 34164281 PMCID: PMC8182712 DOI: 10.21037/tlcr-20-296] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Lung cancer screening (LCS) is gaining some interest worldwide after positive results from International trials. Unlike other screening practices, LCS is performed by an extremely sensitive test, namely low-dose computed tomography (LDCT) that can detect the smallest nodules in lung parenchyma. Up-to-date detection approaches, such as computer aided detection systems, have been increasingly employed for lung nodule automatic identification and are largely used in most LCS programs as a complementary tool to visual reading. Solid nodules of any size are represented in the vast majority of subjects undergoing LDCT. However, less than 1% of solid nodules will be diagnosed lung cancer. This fact calls for specific characterization of nodules to avoid false positives, overinvestigation, and reduce the risks associated with nodule work up. Recent research has been exploring the potential of artificial intelligence, including deep learning techniques, to enhance the accuracy of both detection and characterisation of lung nodule. Computer aided detection and diagnosis algorithms based on artificial intelligence approaches have demonstrated the ability to accurately detect and characterize parenchymal nodules, reducing the number of false positives, and to outperform some of the currently used risk models for prediction of lung cancer risk, potentially reducing the proportion of surveillance CT scans. These forthcoming approaches will eventually integrate a new reasoning for development of future guidelines, which are expected to evolve into precision and personalized stratification of lung cancer risk stratification by continuous fashion, as opposed to the current format with a limited number of risk classes within fixed thresholds of nodule size. This review aims to detail the standard of reference for optimal management of solid nodules by low-dose computed and its projection into the fine selection of candidates for work up.
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Affiliation(s)
- Mario Silva
- Scienze Radiologiche, Department of Medicine and Surgery (DiMeC), University of Parma, Parma, Italy
| | - Gianluca Milanese
- Scienze Radiologiche, Department of Medicine and Surgery (DiMeC), University of Parma, Parma, Italy
| | - Roberta E Ledda
- Scienze Radiologiche, Department of Medicine and Surgery (DiMeC), University of Parma, Parma, Italy
| | - Ugo Pastorino
- Section of Thoracic Surgery, IRCCS Istituto Nazionale Tumori, Milano, Italy
| | - Nicola Sverzellati
- Scienze Radiologiche, Department of Medicine and Surgery (DiMeC), University of Parma, Parma, Italy
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Bradley SH, Shinkins B, Kennedy MP. What is the balance of benefits and harms for lung cancer screening with low-dose computed tomography? J R Soc Med 2021; 114:164-170. [PMID: 33715495 PMCID: PMC8091370 DOI: 10.1177/0141076821991108] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Affiliation(s)
- Stephen H Bradley
- Leeds Institute of Health Sciences, 4468University of Leeds, Leeds LS2 9JT, UK
| | - Bethany Shinkins
- Test Evaluation Group, Academic Unit of Health Economics, 4468University of Leeds, Leeds LS2 9JT, UK
| | - Martyn Pt Kennedy
- Department of Respiratory Medicine, 4472Leeds Teaching Hospitals NHS Trust, Leeds LS9 7TF, UK
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Jonas DE, Reuland DS, Reddy SM, Nagle M, Clark SD, Weber RP, Enyioha C, Malo TL, Brenner AT, Armstrong C, Coker-Schwimmer M, Middleton JC, Voisin C, Harris RP. Screening for Lung Cancer With Low-Dose Computed Tomography: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force. JAMA 2021; 325:971-987. [PMID: 33687468 DOI: 10.1001/jama.2021.0377] [Citation(s) in RCA: 218] [Impact Index Per Article: 72.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
IMPORTANCE Lung cancer is the leading cause of cancer-related death in the US. OBJECTIVE To review the evidence on screening for lung cancer with low-dose computed tomography (LDCT) to inform the US Preventive Services Task Force (USPSTF). DATA SOURCES MEDLINE, Cochrane Library, and trial registries through May 2019; references; experts; and literature surveillance through November 20, 2020. STUDY SELECTION English-language studies of screening with LDCT, accuracy of LDCT, risk prediction models, or treatment for early-stage lung cancer. DATA EXTRACTION AND SYNTHESIS Dual review of abstracts, full-text articles, and study quality; qualitative synthesis of findings. Data were not pooled because of heterogeneity of populations and screening protocols. MAIN OUTCOMES AND MEASURES Lung cancer incidence, lung cancer mortality, all-cause mortality, test accuracy, and harms. RESULTS This review included 223 publications. Seven randomized clinical trials (RCTs) (N = 86 486) evaluated lung cancer screening with LDCT; the National Lung Screening Trial (NLST, N = 53 454) and Nederlands-Leuvens Longkanker Screenings Onderzoek (NELSON, N = 15 792) were the largest RCTs. Participants were more likely to benefit than the US screening-eligible population (eg, based on life expectancy). The NLST found a reduction in lung cancer mortality (incidence rate ratio [IRR], 0.85 [95% CI, 0.75-0.96]; number needed to screen [NNS] to prevent 1 lung cancer death, 323 over 6.5 years of follow-up) with 3 rounds of annual LDCT screening compared with chest radiograph for high-risk current and former smokers aged 55 to 74 years. NELSON found a reduction in lung cancer mortality (IRR, 0.75 [95% CI, 0.61-0.90]; NNS to prevent 1 lung cancer death of 130 over 10 years of follow-up) with 4 rounds of LDCT screening with increasing intervals compared with no screening for high-risk current and former smokers aged 50 to 74 years. Harms of screening included radiation-induced cancer, false-positive results leading to unnecessary tests and invasive procedures, overdiagnosis, incidental findings, and increases in distress. For every 1000 persons screened in the NLST, false-positive results led to 17 invasive procedures (number needed to harm, 59) and fewer than 1 person having a major complication. Overdiagnosis estimates varied greatly (0%-67% chance that a lung cancer was overdiagnosed). Incidental findings were common, and estimates varied widely (4.4%-40.7% of persons screened). CONCLUSIONS AND RELEVANCE Screening high-risk persons with LDCT can reduce lung cancer mortality but also causes false-positive results leading to unnecessary tests and invasive procedures, overdiagnosis, incidental findings, increases in distress, and, rarely, radiation-induced cancers. Most studies reviewed did not use current nodule evaluation protocols, which might reduce false-positive results and invasive procedures for false-positive results.
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Affiliation(s)
- Daniel E Jonas
- RTI International, University of North Carolina at Chapel Hill Evidence-based Practice Center
- Department of Internal Medicine, The Ohio State University, Columbus
| | - Daniel S Reuland
- Department of Medicine, University of North Carolina at Chapel Hill
- Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill
| | - Shivani M Reddy
- RTI International, University of North Carolina at Chapel Hill Evidence-based Practice Center
- RTI International, Research Triangle Park, North Carolina
| | - Max Nagle
- Michigan Medicine, University of Michigan, Ann Arbor
| | - Stephen D Clark
- Department of Internal Medicine, Virginia Commonwealth University, Richmond
| | - Rachel Palmieri Weber
- RTI International, University of North Carolina at Chapel Hill Evidence-based Practice Center
- Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill
| | - Chineme Enyioha
- Department of Family Medicine, University of North Carolina at Chapel Hill
| | - Teri L Malo
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill
| | - Alison T Brenner
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill
| | - Charli Armstrong
- RTI International, University of North Carolina at Chapel Hill Evidence-based Practice Center
- Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill
| | - Manny Coker-Schwimmer
- RTI International, University of North Carolina at Chapel Hill Evidence-based Practice Center
- Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill
| | - Jennifer Cook Middleton
- RTI International, University of North Carolina at Chapel Hill Evidence-based Practice Center
- Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill
| | - Christiane Voisin
- RTI International, University of North Carolina at Chapel Hill Evidence-based Practice Center
- Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill
| | - Russell P Harris
- Department of Medicine, University of North Carolina at Chapel Hill
- Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill
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Couraud S, Ferretti G, Milleron B, Cortot A, Girard N, Gounant V, Laurent F, Leleu O, Quoix E, Revel MP, Wislez M, Westeel V, Zalcman G, Scherpereel A, Khalil A. [Recommendations of French specialists on screening for lung cancer]. Rev Mal Respir 2021; 38:310-325. [PMID: 33637394 DOI: 10.1016/j.rmr.2021.02.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Accepted: 01/25/2021] [Indexed: 12/17/2022]
Affiliation(s)
- S Couraud
- Service de pneumologie aiguë spécialisée et cancérologie thoracique, hospices civils de Lyon, hôpital Lyon Sud, Pierre-Bénite, France; Intergroupe francophone de cancérologie thoracique, Paris, France.
| | - G Ferretti
- Intergroupe francophone de cancérologie thoracique, Paris, France; Service de radiologie diagnostique et interventionnel, CHU de Grenoble-Alpes, Grenoble, France
| | - B Milleron
- Intergroupe francophone de cancérologie thoracique, Paris, France
| | - A Cortot
- Intergroupe francophone de cancérologie thoracique, Paris, France; Service de pneumologie et oncologie thoracique, CHU de Lille, Lille, France
| | - N Girard
- Intergroupe francophone de cancérologie thoracique, Paris, France; Unité d'oncologie thoracique, institut Curie, Paris, France
| | - V Gounant
- Intergroupe francophone de cancérologie thoracique, Paris, France; Service d'oncologie thoracique, groupe hospitalier Bichat-Claude-Bernard, AP-HP, Paris, France
| | - F Laurent
- Service de radiologie, CHU de Bordeaux, Pessac, France
| | - O Leleu
- Intergroupe francophone de cancérologie thoracique, Paris, France; Service de pneumologie, centre hospitalier Abbeville, Abbeville, France
| | - E Quoix
- Intergroupe francophone de cancérologie thoracique, Paris, France; Service de pneumologie, CHRU Strasbourg, Strasbourg, France
| | - M-P Revel
- Service de radiologie, hôpital Cochin, Paris, France
| | - M Wislez
- Intergroupe francophone de cancérologie thoracique, Paris, France; Service d'oncologie thoracique, hôpital Cochin, Paris, France
| | - V Westeel
- Intergroupe francophone de cancérologie thoracique, Paris, France; Service de pneumologie et cancérologie thoracique, CHU de Besançon, Besançon, France
| | - G Zalcman
- Intergroupe francophone de cancérologie thoracique, Paris, France; Service d'oncologie thoracique, groupe hospitalier Bichat-Claude-Bernard, AP-HP, Paris, France
| | - A Scherpereel
- Intergroupe francophone de cancérologie thoracique, Paris, France; Service de pneumologie et oncologie thoracique, CHU de Lille, Lille, France
| | - A Khalil
- Intergroupe francophone de cancérologie thoracique, Paris, France; Service de radiologie, groupe hospitalier Bichat-Claude-Bernard, AP-HP, Paris, France
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Intergroupe francophone de cancérologie thoracique, Société de pneumologie de langue française, and Société d'imagerie thoracique statement paper on lung cancer screening. Diagn Interv Imaging 2021; 102:199-211. [PMID: 33648872 DOI: 10.1016/j.diii.2021.01.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 01/21/2021] [Accepted: 01/29/2021] [Indexed: 12/17/2022]
Abstract
Following the American National Lung Screening Trial results in 2011 a consortium of French experts met to edit a statement. Recent results of other randomized trials gave the opportunity for our group to meet again in order to edit updated guidelines. After literature review, we provide here a new update on lung cancer screening in France. Notably, in accordance with all international guidelines, the experts renew their recommendation in favor of individual screening for lung cancer in France as per the conditions laid out in this document. In addition, the experts recommend the very rapid organization and funding of prospective studies, which, if conclusive, will enable the deployment of lung cancer screening organized at the national level.
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Lambert L, Janouskova L, Novak M, Bircakova B, Meckova Z, Votruba J, Michalek P, Burgetova A. Early detection of lung cancer in Czech high-risk asymptomatic individuals (ELEGANCE): A study protocol. Medicine (Baltimore) 2021; 100:e23878. [PMID: 33592843 PMCID: PMC7870244 DOI: 10.1097/md.0000000000023878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Accepted: 11/24/2020] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Lung cancer screening in high-risk population increases the proportion of patients diagnosed at a resectable stage. AIMS To optimize the selection criteria and quality indicators for lung cancer screening by low-dose CT (LDCT) in the Czech population of high-risk individuals. To compare the influence of screening on the stage of lung cancer at the time of the diagnosis with the stage distribution in an unscreened population. To estimate the impact on life-years lost according to the stage-specific cancer survival and stage distribution in the screened population. To calculate the cost-effectiveness of the screening program. METHODS Based on the evidence from large national trials - the National Lung Screening Trial in the USA (NLST), the NELSON study, the recent recommendations of the Fleischner society, the American College of Radiology, and I-ELCAP action group, we developed a protocol for a single-arm prospective study in the Czech Republic for the screening of high-risk asymptomatic individuals. The study commenced in August 2020. RESULTS The inclusion criteria are: age 55 to 74 years; smoking: ≥30 pack-years; smoker or ex-smoker <15 years; performance status (0-1). The screening timepoints are at baseline and 1 year. The LDCT acquisition has a target CTDIvol ≤0.5mGy and effective dose ≤0.2mSv for a standard-size patient. The interpretation of findings is primarily based on nodule volumetry, volume doubling time (and related risk of malignancy). The management includes follow-up LDCT, contrast enhanced CT, PET/CT, tissue sampling. The primary outcome is the number of cancers detected at a resectable stage, secondary outcomes include the average cost per diagnosis of lung cancer, the number, cost, complications of secondary examinations, and the number of potentially important secondary findings. CONCLUSIONS A study protocol for early detection of lung cancer in Czech high-risk asymptomatic individuals (ELEGANCE) study using LDCT has been described.
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Affiliation(s)
| | | | | | | | | | - Jiri Votruba
- 1st Department of Tuberculosis and Respiratory Diseases
| | - Pavel Michalek
- Department of Anesthesiology and Intensive Care, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
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Bartlett EC, Silva M, Callister ME, Devaraj A. False-Negative Results in Lung Cancer Screening-Evidence and Controversies. J Thorac Oncol 2021; 16:912-921. [PMID: 33545386 DOI: 10.1016/j.jtho.2021.01.1607] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 12/22/2020] [Accepted: 01/05/2021] [Indexed: 12/17/2022]
Abstract
Identifying false-negative cases is an important quality metric in lung cancer screening, but it has been infrequently and variably reported in previous studies. Although as a proportion of all screening participants, false-negative cases are uncommon, such cases may constitute a substantial proportion of all lung cancers diagnosed (up to 15%) within a screening program. This article reviews the impact and causes of false-negative lung cancer screening tests, including those related to radiologic evaluation, nodule management protocols, and management decisions made by multidisciplinary teams. Following a review of data from international screening studies, this article discusses the controversies within the screening literature surrounding the definition and classification of a false-negative lung cancer screening test and how data on false-negative rates should be captured and recorded. Challenges, such as avoiding overly cautious surveillance of lung nodules while minimizing overdiagnosis and investigation of indolent or benign lesions, are considered. Finally, the advantages and disadvantages of different approaches to dealing with false-negative results in lung cancer screening are discussed.
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Affiliation(s)
- Emily C Bartlett
- Department of Radiology, Royal Brompton Hospital, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Mario Silva
- Section of "Scienze Radiologiche," Department of Medicine and Surgery, University of Parma, Parma, Italy
| | - Matthew E Callister
- St James's University Hospital, The Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
| | - Anand Devaraj
- Department of Radiology, Royal Brompton Hospital, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom.
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47
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Zheng S, Cornelissen LJ, Cui X, Jing X, Veldhuis RNJ, Oudkerk M, van Ooijen PMA. Deep convolutional neural networks for multiplanar lung nodule detection: Improvement in small nodule identification. Med Phys 2021; 48:733-744. [PMID: 33300162 PMCID: PMC7986069 DOI: 10.1002/mp.14648] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 11/23/2020] [Accepted: 11/30/2020] [Indexed: 12/12/2022] Open
Abstract
PURPOSE Early detection of lung cancer is of importance since it can increase patients' chances of survival. To detect nodules accurately during screening, radiologists would commonly take the axial, coronal, and sagittal planes into account, rather than solely the axial plane in clinical evaluation. Inspired by clinical work, the paper aims to develop an accurate deep learning framework for nodule detection by a combination of multiple planes. METHODS The nodule detection system is designed in two stages, multiplanar nodule candidate detection, multiscale false positive (FP) reduction. At the first stage, a deeply supervised encoder-decoder network is trained by axial, coronal, and sagittal slices for the candidate detection task. All possible nodule candidates from the three different planes are merged. To further refine results, a three-dimensional multiscale dense convolutional neural network that extracts multiscale contextual information is applied to remove non-nodules. In the public LIDC-IDRI dataset, 888 computed tomography scans with 1186 nodules accepted by at least three of four radiologists are selected to train and evaluate our proposed system via a tenfold cross-validation scheme. The free-response receiver operating characteristic curve is used for performance assessment. RESULTS The proposed system achieves a sensitivity of 94.2% with 1.0 FP/scan and a sensitivity of 96.0% with 2.0 FPs/scan. Although it is difficult to detect small nodules (i.e., <6 mm), our designed CAD system reaches a sensitivity of 93.4% (95.0%) of these small nodules at an overall FP rate of 1.0 (2.0) FPs/scan. At the nodule candidate detection stage, results show that the system with a multiplanar method is capable to detect more nodules compared to using a single plane. CONCLUSION Our approach achieves good performance not only for small nodules but also for large lesions on this dataset. This demonstrates the effectiveness of our developed CAD system for lung nodule detection.
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Affiliation(s)
- Sunyi Zheng
- Department of Radiation OncologyUniversity Medical Center GroningenUniversity of Groningen9713 AVGroningenThe Netherlands
| | - Ludo J. Cornelissen
- Department of Radiation OncologyUniversity Medical Center GroningenUniversity of Groningen9713 AVGroningenThe Netherlands
| | - Xiaonan Cui
- Department of RadiologyTianjin Medical University Cancer Institute and HospitalNational Clinical Research Centre of Cancer300060TianjinChina
| | - Xueping Jing
- Department of Radiation OncologyUniversity Medical Center GroningenUniversity of Groningen9713 AVGroningenThe Netherlands
| | | | - Matthijs Oudkerk
- Faculty of Medical ScienceUniversity of Groningen9713 AVGroningenThe Netherlands
| | - Peter M. A. van Ooijen
- Department of Radiation OncologyUniversity Medical Center GroningenUniversity of Groningen9713 AVGroningenThe Netherlands
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48
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Dziadziuszko K, Szurowska E. Pulmonary nodule radiological diagnostic algorithm in lung cancer screening. Transl Lung Cancer Res 2021; 10:1124-1135. [PMID: 33718050 PMCID: PMC7947388 DOI: 10.21037/tlcr-20-755] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Publications of the final results of the two largest randomized lung cancer screening (LCS) trials in the United States and Europe confirmed the reduction in the mortality rate associated with the use of screening with low-dose computed tomography (LDCT). Results of these trials led to widespread acceptance of LCS in properly defined high-risk populations, and its implementation in the clinical practice. Many countries started preparation for national LCS and refreshed still open debate about lung nodule management. Detection of lung cancer in the early stage with a reduction of lung cancer mortality requires dedicated programs with optimized protocols, including a specified pulmonary nodule diagnostic algorithm. The screening protocol should be clear with a precise nodule diameter or volume threshold, based on which a positive screen result is defined. The application of risk-prediction models and the introduction of the semiautomated assessment of detected nodules improves screening accuracy and should be applied in LCS protocols as verified tools to aid radiological diagnosis. In this review, we have summarized recent data about the radiological protocols from the most important LCS programs and pulmonary diagnostic algorithms. These protocols should be taken into consideration in the ongoing and planned LCS programs.
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Affiliation(s)
| | - Edyta Szurowska
- II Department of Radiology, Medical University of Gdańsk, Gdańsk, Poland
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Vonder M, Dorrius MD, Vliegenthart R. Latest CT technologies in lung cancer screening: protocols and radiation dose reduction. Transl Lung Cancer Res 2021; 10:1154-1164. [PMID: 33718053 PMCID: PMC7947397 DOI: 10.21037/tlcr-20-808] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The aim of this review is to provide clinicians and technicians with an overview of the development of CT protocols in lung cancer screening. CT protocols have evolved from pre-fixed settings in early lung cancer screening studies starting in 2004 towards automatic optimized settings in current international guidelines. The acquisition protocols of large lung cancer screening studies and guidelines are summarized. Radiation dose may vary considerably between CT protocols, but has reduced gradually over the years. Ultra-low dose acquisition can be achieved by applying latest dose reduction techniques. The use of low tube current or tin-filter in combination with iterative reconstruction allow to reduce the radiation dose to a submilliSievert level. However, one should be cautious in reducing the radiation dose to ultra-low dose settings since performed studies lacked generalizability. Continuous efforts are made by international radiology organizations to streamline the CT data acquisition and image quality assurance and to keep track of new developments in CT lung cancer screening. Examples like computer-aided diagnosis and radiomic feature extraction are discussed and current limitations are outlined. Deep learning-based solutions in post-processing of CT images are provided. Finally, future perspectives and recommendations are provided for lung cancer screening CT protocols.
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Affiliation(s)
- Marleen Vonder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Monique D Dorrius
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.,Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Rozemarijn Vliegenthart
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
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50
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Lung-RADS Version 1.1: Challenges and a Look Ahead, From the AJR Special Series on Radiology Reporting and Data Systems. AJR Am J Roentgenol 2021; 216:1411-1422. [PMID: 33470834 DOI: 10.2214/ajr.20.24807] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
In 2014, the American College of Radiology (ACR) created Lung-RADS 1.0. The system was updated to Lung-RADS 1.1 in 2019, and further updates are anticipated as additional data become available. Lung-RADS provides a common lexicon and standardized nodule follow-up management paradigm for use when reporting lung cancer screening (LCS) low-dose CT (LDCT) chest examinations and serves as a quality assurance and outcome monitoring tool. The use of Lung-RADS is intended to improve LCS performance and lead to better patient outcomes. To date, the ACR's Lung Cancer Screening Registry is the only LCS registry approved by the Centers for Medicare & Medicaid Services and requires the use of Lung-RADS categories for reimbursement. Numerous challenges have emerged regarding the use of Lung-RADS in clinical practice, including the timing of return to LCS after planned follow-up diagnostic evaluation; potential substitution of interval diagnostic CT for future LDCT; role of volumetric analysis in assessing nodule size; assessment of nodule growth; assessment of cavitary, subpleural, and category 4X nodules; and variability in reporting of the S modifier. This article highlights the major updates between versions 1.0 and 1.1 of Lung-RADS, describes the system's ongoing challenges, and summarizes current evidence and recommendations.
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