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Cai J, Vonder M, Pelgrim GJ, Rook M, Kramer G, Groen HJM, de Bock GH, Vliegenthart R. Distribution of Solid Lung Nodules Presence and Size by Age and Sex in a Northern European Nonsmoking Population. Radiology 2024; 312:e231436. [PMID: 39136567 DOI: 10.1148/radiol.231436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/27/2024]
Abstract
Background Most of the data regarding prevalence and size distribution of solid lung nodules originates from lung cancer screening studies that target high-risk populations or from Asian general cohorts. In recent years, the identification of lung nodules in non-high-risk populations, scanned for clinical indications, has increased. However, little is known about the presence of solid lung nodules in the Northern European nonsmoking population. Purpose To study the prevalence and size distribution of solid lung nodules by age and sex in a nonsmoking population. Materials and Methods Participants included nonsmokers (never or former smokers) from the population-based Imaging in Lifelines study conducted in the Northern Netherlands. Participants (age ≥ 45 years) with completed lung function tests underwent chest low-dose CT scans. Seven trained readers registered the presence and size of solid lung nodules measuring 30 mm3 or greater using semiautomated software. The prevalence and size of lung nodules (≥30 mm3), clinically relevant lung nodules (≥100 mm3), and actionable nodules (≥300 mm3) are presented by 5-year categories and by sex. Results A total of 10 431 participants (median age, 60.4 years [IQR, 53.8-70.8 years]; 56.6% [n = 5908] female participants; 46.1% [n = 4812] never smokers and 53.9% [n = 5619] former smokers) were included. Of these, 42.0% (n = 4377) had at least one lung nodule (male participants, 47.5% [2149 of 4523]; female participants, 37.7% [2228 of 5908]). The prevalence of lung nodules increased from age 45-49.9 years (male participants, 39.4% [219 of 556]; female participants, 27.7% [236 of 851]) to age 80 years or older (male participants, 60.7% [246 of 405]; female participants, 50.9% [163 of 320]). Clinically relevant lung nodules were present in 11.1% (1155 of 10 431) of participants, with prevalence increasing with age (male participants, 8.5%-24.4%; female participants, 3.7%-15.6%), whereas actionable nodules were present in 1.1%-6.4% of male participants and 0.6%-4.9% of female participants. Conclusion Lung nodules were present in a substantial proportion of all age groups in the Northern European nonsmoking population, with slightly higher prevalence for male participants than female participants. © RSNA, 2024 Supplemental material is available for this article.
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Affiliation(s)
- Jiali Cai
- From the Departments of Epidemiology (J.C., M.V., G.H.d.B.), Radiology (G.J.P., G.K., R.V.), and Pulmonology (H.J.M.G.), University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands; Department of Radiology, Medisch Spectrum Twente, University of Twente, the Netherlands (G.J.P.); and Department of Radiology, Martini Hospital Groningen, Groningen, the Netherlands (M.R., G.K.)
| | - Marleen Vonder
- From the Departments of Epidemiology (J.C., M.V., G.H.d.B.), Radiology (G.J.P., G.K., R.V.), and Pulmonology (H.J.M.G.), University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands; Department of Radiology, Medisch Spectrum Twente, University of Twente, the Netherlands (G.J.P.); and Department of Radiology, Martini Hospital Groningen, Groningen, the Netherlands (M.R., G.K.)
| | - Gert Jan Pelgrim
- From the Departments of Epidemiology (J.C., M.V., G.H.d.B.), Radiology (G.J.P., G.K., R.V.), and Pulmonology (H.J.M.G.), University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands; Department of Radiology, Medisch Spectrum Twente, University of Twente, the Netherlands (G.J.P.); and Department of Radiology, Martini Hospital Groningen, Groningen, the Netherlands (M.R., G.K.)
| | - Mieneke Rook
- From the Departments of Epidemiology (J.C., M.V., G.H.d.B.), Radiology (G.J.P., G.K., R.V.), and Pulmonology (H.J.M.G.), University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands; Department of Radiology, Medisch Spectrum Twente, University of Twente, the Netherlands (G.J.P.); and Department of Radiology, Martini Hospital Groningen, Groningen, the Netherlands (M.R., G.K.)
| | - Gerdien Kramer
- From the Departments of Epidemiology (J.C., M.V., G.H.d.B.), Radiology (G.J.P., G.K., R.V.), and Pulmonology (H.J.M.G.), University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands; Department of Radiology, Medisch Spectrum Twente, University of Twente, the Netherlands (G.J.P.); and Department of Radiology, Martini Hospital Groningen, Groningen, the Netherlands (M.R., G.K.)
| | - Harry J M Groen
- From the Departments of Epidemiology (J.C., M.V., G.H.d.B.), Radiology (G.J.P., G.K., R.V.), and Pulmonology (H.J.M.G.), University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands; Department of Radiology, Medisch Spectrum Twente, University of Twente, the Netherlands (G.J.P.); and Department of Radiology, Martini Hospital Groningen, Groningen, the Netherlands (M.R., G.K.)
| | - Geertruida H de Bock
- From the Departments of Epidemiology (J.C., M.V., G.H.d.B.), Radiology (G.J.P., G.K., R.V.), and Pulmonology (H.J.M.G.), University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands; Department of Radiology, Medisch Spectrum Twente, University of Twente, the Netherlands (G.J.P.); and Department of Radiology, Martini Hospital Groningen, Groningen, the Netherlands (M.R., G.K.)
| | - Rozemarijn Vliegenthart
- From the Departments of Epidemiology (J.C., M.V., G.H.d.B.), Radiology (G.J.P., G.K., R.V.), and Pulmonology (H.J.M.G.), University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands; Department of Radiology, Medisch Spectrum Twente, University of Twente, the Netherlands (G.J.P.); and Department of Radiology, Martini Hospital Groningen, Groningen, the Netherlands (M.R., G.K.)
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Chelala L, Hossain R, Jeudy J, Nader Z, Kastner J, White C. Lung-Reporting and Data System 2.0: Impact of the Updated Approach to Juxtapleural Nodules During Lung Cancer Screening Using the National Lung Cancer Screening Trial Data Set. J Thorac Imaging 2024; 39:241-246. [PMID: 37889546 DOI: 10.1097/rti.0000000000000756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
PURPOSE To determine the frequency of malignancy of nonperifissural juxtapleural nodules (JPNs) measuring 6 to < 10 mm in a subset of low-dose chest computed tomographies from the National Lung Cancer Screening Trial and the rate of down-classification of such nodules in Lung-Reporting and Data System (RADS) 2.0 compared with Lung-RADS 1.1. MATERIALS AND METHODS A secondary analysis of a subset of the National Lung Screening Trial was performed. An exemption was granted by the Institutional Review Board. The dominant noncalcified nodule measuring 6 to <10 mm was identified on all available prevalence computed tomographies. Nodules were categorized as pleural or nonpleural. Benign or malignant morphology was recorded. Initial and updated categories based on Lung-RADS 1.1 and Lung-RADS 2.0 were assigned, respectively. The impact of the down-classification of JPN was assessed. Both classification schemes were compared using the McNemar test ( P < 0.01). RESULTS A total of 2813 patients (62 ± 5 y, 1717 men) with 4408 noncalcified nodules were studied. One thousand seventy-three dominant nodules measuring 6 to <10 mm were identified. Three hundred forty-eight (32.4%) were JPN. The updated scheme allowed down-classification of 310 JPN from categories 3 (n = 198) and 4A (n = 112) to category 2. We, therefore, estimate a 4.8% rate of down-classification to category 2 in the entire National Lung Screening Trial screening group. Two/348 (0.57%) JPN were malignant, both nonbenign in morphology. The false-positive rate decreased in the updated classification ( P < 0.01). CONCLUSION This study demonstrates the low malignant potential of benign morphology JPN measuring 6 mm to <10 mm. The Lung-RADS 2.0 approach to JPN is estimated to reduce short-term follow-ups and false-positive results.
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Affiliation(s)
- Lydia Chelala
- Department of Radiology, University of Chicago Medicine, Chicago, IL
| | - Rydhwana Hossain
- Department of Radiology, University of Maryland Medical Center, Baltimore MD
| | - Jean Jeudy
- Department of Radiology, University of Maryland Medical Center, Baltimore MD
| | - Ziad Nader
- Department of executive education, Paris Dauphine University, Paris, France
| | - Julia Kastner
- Department of Radiology, University of Maryland Medical Center, Baltimore MD
| | - Charles White
- Department of Radiology, University of Maryland Medical Center, Baltimore MD
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Hammer MM, Hunsaker AR. Risk of Lung Cancer in Peripheral Pulmonary Nodules. Acad Radiol 2024:S1076-6332(24)00380-5. [PMID: 38945743 DOI: 10.1016/j.acra.2024.06.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2024] [Revised: 06/14/2024] [Accepted: 06/17/2024] [Indexed: 07/02/2024]
Abstract
PURPOSE To determine the risk of lung cancer and inter-observer agreement for small pulmonary nodules either touching or near the pleura. METHODS Nodules were derived from two cohorts: patients from the National Lung Screening Trial with a solid nodule measuring 6-9.5 mm; and patients with incidental pulmonary nodules in our healthcare system with a solid nodule measuring 1-8 mm. Only the dominant nodule was evaluated for each patient. All malignant nodules as well as a random sample of 200 benign nodules from each cohort were included. Two fellowship-trained thoracic radiologists independently reviewed each case to record nodule morphology (compatible with lymph node or not) and nodule location (pleural-based, septal connection to the pleura, or neither). One radiologist measured the distance to the pleura. RESULTS After exclusion criteria were applied, a total of 434 nodules were included, of which 45 were lung cancers. Considering all pleural-based nodules with lymph node morphology as benign, 0-7% of cancers were misclassified as benign, specificity 33%, and κ = 0.69. Considering subpleural nodules and those with septal connection to the pleura, 7-11% of cancers were misclassified (p = 0.16-0.25 versus pleural-based), specificity 40-52% (p < .0001), and κ = 0.60. Considering nodules with lymph node morphology ≤ 2 mm from the pleura, 2-7% of cancers were misclassified (p = 1 versus pleural-based), specificity 41-36% (p < .0001), and κ = 0.78. CONCLUSION Considering nodules with lymph node morphology with septal connection, or those ≤ 2 mm from the pleura, as benign does not lead to significant misclassification of lung cancers as benign.
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Affiliation(s)
- Mark M Hammer
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA.
| | - Andetta R Hunsaker
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA
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4
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Jhala K, Byrne SC, Hammer MM. Interpreting Lung Cancer Screening CTs: Practical Approach to Lung Cancer Screening and Application of Lung-RADS. Clin Chest Med 2024; 45:279-293. [PMID: 38816088 DOI: 10.1016/j.ccm.2023.08.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2024]
Abstract
Lung cancer screening via low-dose computed tomography (CT) reduces mortality from lung cancer, and eligibility criteria have recently been expanded to include patients aged 50 to 80 with at least 20 pack-years of smoking history. Lung cancer screening CTs should be interepreted with use of Lung Imaging Reporting and Data System (Lung-RADS), a reporting guideline system that accounts for nodule size, density, and growth. The revised version of Lung-RADS includes several important changes, such as expansion of the definition of juxtapleural nodules, discussion of atypical pulmonary cysts, and stepped management for suspicious nodules. By using Lung-RADS, radiologists and clinicians can adopt a uniform approach to nodules detected during CT lung cancer screening and reduce false positives.
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Affiliation(s)
- Khushboo Jhala
- Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02215, USA
| | - Suzanne C Byrne
- Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02215, USA
| | - Mark M Hammer
- Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02215, USA.
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Sourlos N, Pelgrim G, Wisselink HJ, Yang X, de Jonge G, Rook M, Prokop M, Sidorenkov G, van Tuinen M, Vliegenthart R, van Ooijen PMA. Effect of emphysema on AI software and human reader performance in lung nodule detection from low-dose chest CT. Eur Radiol Exp 2024; 8:63. [PMID: 38764066 PMCID: PMC11102890 DOI: 10.1186/s41747-024-00459-9] [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: 12/01/2023] [Accepted: 03/18/2024] [Indexed: 05/21/2024] Open
Abstract
BACKGROUND Emphysema influences the appearance of lung tissue in computed tomography (CT). We evaluated whether this affects lung nodule detection by artificial intelligence (AI) and human readers (HR). METHODS Individuals were selected from the "Lifelines" cohort who had undergone low-dose chest CT. Nodules in individuals without emphysema were matched to similar-sized nodules in individuals with at least moderate emphysema. AI results for nodular findings of 30-100 mm3 and 101-300 mm3 were compared to those of HR; two expert radiologists blindly reviewed discrepancies. Sensitivity and false positives (FPs)/scan were compared for emphysema and non-emphysema groups. RESULTS Thirty-nine participants with and 82 without emphysema were included (n = 121, aged 61 ± 8 years (mean ± standard deviation), 58/121 males (47.9%)). AI and HR detected 196 and 206 nodular findings, respectively, yielding 109 concordant nodules and 184 discrepancies, including 118 true nodules. For AI, sensitivity was 0.68 (95% confidence interval 0.57-0.77) in emphysema versus 0.71 (0.62-0.78) in non-emphysema, with FPs/scan 0.51 and 0.22, respectively (p = 0.028). For HR, sensitivity was 0.76 (0.65-0.84) and 0.80 (0.72-0.86), with FPs/scan of 0.15 and 0.27 (p = 0.230). Overall sensitivity was slightly higher for HR than for AI, but this difference disappeared after the exclusion of benign lymph nodes. FPs/scan were higher for AI in emphysema than in non-emphysema (p = 0.028), while FPs/scan for HR were higher than AI for 30-100 mm3 nodules in non-emphysema (p = 0.009). CONCLUSIONS AI resulted in more FPs/scan in emphysema compared to non-emphysema, a difference not observed for HR. RELEVANCE STATEMENT In the creation of a benchmark dataset to validate AI software for lung nodule detection, the inclusion of emphysema cases is important due to the additional number of FPs. KEY POINTS • The sensitivity of nodule detection by AI was similar in emphysema and non-emphysema. • AI had more FPs/scan in emphysema compared to non-emphysema. • Sensitivity and FPs/scan by the human reader were comparable for emphysema and non-emphysema. • Emphysema and non-emphysema representation in benchmark dataset is important for validating AI.
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Affiliation(s)
- Nikos Sourlos
- Department of Radiology, University Medical Center of Groningen, Groningen, 9713GZ, The Netherlands
| | - GertJan Pelgrim
- Department of Radiology, University Medical Center of Groningen, Groningen, 9713GZ, The Netherlands
- Department of Oral Surgery of the Medical Spectrum Twente (MST), Enschede, 7500KA, The Netherlands
| | - Hendrik Joost Wisselink
- Department of Radiology, University Medical Center of Groningen, Groningen, 9713GZ, The Netherlands
- DataScience Center in Health (DASH), University Medical Center Groningen, Groningen, 9713GZ, The Netherlands
| | - Xiaofei Yang
- Department of Epidemiology, University Medical Center Groningen, Groningen, 9713GZ, The Netherlands
| | - Gonda de Jonge
- Department of Radiology, University Medical Center of Groningen, Groningen, 9713GZ, The Netherlands
| | - Mieneke Rook
- Department of Radiology, Martini Hospital, Groningen, 9728NT, The Netherlands
| | - Mathias Prokop
- Department of Radiology, University Medical Center of Groningen, Groningen, 9713GZ, The Netherlands
| | - Grigory Sidorenkov
- Department of Radiology, University Medical Center of Groningen, Groningen, 9713GZ, The Netherlands
- Department of Epidemiology, University Medical Center Groningen, Groningen, 9713GZ, The Netherlands
| | - Marcel van Tuinen
- Department of Radiology, University Medical Center of Groningen, Groningen, 9713GZ, The Netherlands
| | - Rozemarijn Vliegenthart
- Department of Radiology, University Medical Center of Groningen, Groningen, 9713GZ, The Netherlands
- DataScience Center in Health (DASH), University Medical Center Groningen, Groningen, 9713GZ, The Netherlands
| | - Peter M A van Ooijen
- DataScience Center in Health (DASH), University Medical Center Groningen, Groningen, 9713GZ, The Netherlands.
- Department of Radiation Oncology, University Medical Center Groningen, Groningen, 9713GZ, The Netherlands.
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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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Mao Y, Cai J, Heuvelmans MA, Vliegenthart R, Groen HJM, Oudkerk M, Vonder M, Dorrius MD, de Bock GH. Performance of Lung-RADS in different target populations: a systematic review and meta-analysis. Eur Radiol 2024; 34:1877-1892. [PMID: 37646809 PMCID: PMC10873443 DOI: 10.1007/s00330-023-10049-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 06/12/2023] [Accepted: 06/15/2023] [Indexed: 09/01/2023]
Abstract
OBJECTIVES Multiple lung cancer screening studies reported the performance of Lung CT Screening Reporting and Data System (Lung-RADS), but none systematically evaluated its performance across different populations. This systematic review and meta-analysis aimed to evaluate the performance of Lung-RADS (versions 1.0 and 1.1) for detecting lung cancer in different populations. METHODS We performed literature searches in PubMed, Web of Science, Cochrane Library, and Embase databases on October 21, 2022, for studies that evaluated the accuracy of Lung-RADS in lung cancer screening. A bivariate random-effects model was used to estimate pooled sensitivity and specificity, and heterogeneity was explored in stratified and meta-regression analyses. RESULTS A total of 31 studies with 104,224 participants were included. For version 1.0 (27 studies, 95,413 individuals), pooled sensitivity was 0.96 (95% confidence interval [CI]: 0.90-0.99) and pooled specificity was 0.90 (95% CI: 0.87-0.92). Studies in high-risk populations showed higher sensitivity (0.98 [95% CI: 0.92-0.99] vs. 0.84 [95% CI: 0.50-0.96]) and lower specificity (0.87 [95% CI: 0.85-0.88] vs. 0.95 (95% CI: 0.92-0.97]) than studies in general populations. Non-Asian studies tended toward higher sensitivity (0.97 [95% CI: 0.91-0.99] vs. 0.91 [95% CI: 0.67-0.98]) and lower specificity (0.88 [95% CI: 0.85-0.90] vs. 0.93 [95% CI: 0.88-0.96]) than Asian studies. For version 1.1 (4 studies, 8811 individuals), pooled sensitivity was 0.91 (95% CI: 0.83-0.96) and specificity was 0.81 (95% CI: 0.67-0.90). CONCLUSION Among studies using Lung-RADS version 1.0, considerable heterogeneity in sensitivity and specificity was noted, explained by population type (high risk vs. general), population area (Asia vs. non-Asia), and cancer prevalence. CLINICAL RELEVANCE STATEMENT Meta-regression of lung cancer screening studies using Lung-RADS version 1.0 showed considerable heterogeneity in sensitivity and specificity, explained by the different target populations, including high-risk versus general populations, Asian versus non-Asian populations, and populations with different lung cancer prevalence. KEY POINTS • High-risk population studies showed higher sensitivity and lower specificity compared with studies performed in general populations by using Lung-RADS version 1.0. • In non-Asian studies, the diagnostic performance of Lung-RADS version 1.0 tended to be better than in Asian studies. • There are limited studies on the performance of Lung-RADS version 1.1, and evidence is lacking for Asian populations.
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Affiliation(s)
- Yifei Mao
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, 9700 RB, Groningen, the Netherlands
| | - Jiali Cai
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, 9700 RB, Groningen, the Netherlands
| | - Marjolein A Heuvelmans
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, 9700 RB, Groningen, the Netherlands
| | - Rozemarijn Vliegenthart
- Department of Radiology, University Medical Center Groningen, University of Groningen, 9700 RB, Groningen, the Netherlands
| | - Harry J M Groen
- Department of Pulmonary Diseases, University Medical Center Groningen, University of Groningen, 9700 RB, Groningen, the Netherlands
| | - Matthijs Oudkerk
- Institute for Diagnostic Accuracy, Prof. Wiersmastraat 5, 9713 GH, Groningen, the Netherlands
| | - Marleen Vonder
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, 9700 RB, Groningen, the Netherlands
| | - Monique D Dorrius
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, 9700 RB, Groningen, the Netherlands
- Department of Radiology, University Medical Center Groningen, University of Groningen, 9700 RB, Groningen, the Netherlands
| | - Geertruida H de Bock
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, 9700 RB, Groningen, the Netherlands.
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8
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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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9
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Zhu Y, Yip R, Zhang J, Cai Q, Sun Q, Li P, Paksashvili N, Triphuridet N, Henschke CI, Yankelevitz DF. Radiologic Features of Nodules Attached to the Mediastinal or Diaphragmatic Pleura at Low-Dose CT for Lung Cancer Screening. Radiology 2024; 310:e231219. [PMID: 38165250 PMCID: PMC10831475 DOI: 10.1148/radiol.231219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 11/08/2023] [Accepted: 11/16/2023] [Indexed: 01/03/2024]
Abstract
Background Pulmonary noncalcified nodules (NCNs) attached to the fissural or costal pleura with smooth margins and triangular or lentiform, oval, or semicircular (LOS) shapes at low-dose CT are recommended for annual follow-up instead of immediate workup. Purpose To determine whether management of mediastinal or diaphragmatic pleura-attached NCNs (M/DP-NCNs) with the same features as fissural or costal pleura-attached NCNs at low-dose CT can follow the same recommendations. Materials and Methods This retrospective study reviewed chest CT examinations in participants from two databases. Group A included 1451 participants who had lung cancer that was first present as a solid nodule with an average diameter of 3.0-30.0 mm. Group B included 345 consecutive participants from a lung cancer screening program who had at least one solid nodule with a diameter of 3.0-30.0 mm at baseline CT and underwent at least three follow-up CT examinations. Radiologists reviewed CT images to identify solid M/DP-NCNs, defined as nodules 0 mm in distance from the mediastinal or diaphragmatic pleura, and recorded average diameter, margin, and shape. General descriptive statistics were used. Results Among the 1451 participants with lung cancer in group A, 163 participants (median age, 68 years [IQR, 61.5-75.0 years]; 92 male participants) had 164 malignant M/DP-NCNs 3.0-30.0 mm in average diameter. None of the 164 malignant M/DP-NCNs had smooth margins and triangular or LOS shapes (upper limit of 95% CI of proportion, 0.02). Among the 345 consecutive screening participants in group B, 146 participants (median age, 65 years [IQR, 59-71 years]; 81 female participants) had 240 M/DP-NCNs with average diameter 3.0-30.0 mm. None of the M/DP-NCNs with smooth margins and triangular or LOS shapes were malignant after a median follow-up of 57.8 months (IQR, 46.3-68.1 months). Conclusion For solid M/DP-NCNs with smooth margins and triangular or LOS shapes at low-dose CT, the risk of lung cancer is extremely low, which supports the recommendation of Lung Imaging Reporting and Data System version 2022 for annual follow-up instead of immediate workup. © RSNA, 2024 See also the editorial by Goodman and Baruah in this issue.
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Affiliation(s)
- Yeqing Zhu
- From the Department of Radiology, Icahn School of Medicine at Mount
Sinai, 1 Gustave L. Levy Pl, New York, NY 10029 (Y.Z., R.Y., J.Z., Q.C., Q.S.,
P.L., N.P., N.T., C.I.H., D.F.Y.); Department of Radiology, Shanxi Provincial
People’s Hospital, Taiyuan, China (Q.C.); Department of Radiology, Harbin
Medical University Cancer Hospital, Harbin, China (Q.S., P.L.); and Department
of Pulmonary Medicine, Faculty of Medicine and Public Health, HRH Princess
Chulabhorn College of Medical Science, Chulabhorn Royal Academy, Bangkok,
Thailand (N.T.)
| | - Rowena Yip
- From the Department of Radiology, Icahn School of Medicine at Mount
Sinai, 1 Gustave L. Levy Pl, New York, NY 10029 (Y.Z., R.Y., J.Z., Q.C., Q.S.,
P.L., N.P., N.T., C.I.H., D.F.Y.); Department of Radiology, Shanxi Provincial
People’s Hospital, Taiyuan, China (Q.C.); Department of Radiology, Harbin
Medical University Cancer Hospital, Harbin, China (Q.S., P.L.); and Department
of Pulmonary Medicine, Faculty of Medicine and Public Health, HRH Princess
Chulabhorn College of Medical Science, Chulabhorn Royal Academy, Bangkok,
Thailand (N.T.)
| | - Jiafang Zhang
- From the Department of Radiology, Icahn School of Medicine at Mount
Sinai, 1 Gustave L. Levy Pl, New York, NY 10029 (Y.Z., R.Y., J.Z., Q.C., Q.S.,
P.L., N.P., N.T., C.I.H., D.F.Y.); Department of Radiology, Shanxi Provincial
People’s Hospital, Taiyuan, China (Q.C.); Department of Radiology, Harbin
Medical University Cancer Hospital, Harbin, China (Q.S., P.L.); and Department
of Pulmonary Medicine, Faculty of Medicine and Public Health, HRH Princess
Chulabhorn College of Medical Science, Chulabhorn Royal Academy, Bangkok,
Thailand (N.T.)
| | - Qiang Cai
- From the Department of Radiology, Icahn School of Medicine at Mount
Sinai, 1 Gustave L. Levy Pl, New York, NY 10029 (Y.Z., R.Y., J.Z., Q.C., Q.S.,
P.L., N.P., N.T., C.I.H., D.F.Y.); Department of Radiology, Shanxi Provincial
People’s Hospital, Taiyuan, China (Q.C.); Department of Radiology, Harbin
Medical University Cancer Hospital, Harbin, China (Q.S., P.L.); and Department
of Pulmonary Medicine, Faculty of Medicine and Public Health, HRH Princess
Chulabhorn College of Medical Science, Chulabhorn Royal Academy, Bangkok,
Thailand (N.T.)
| | - Qi Sun
- From the Department of Radiology, Icahn School of Medicine at Mount
Sinai, 1 Gustave L. Levy Pl, New York, NY 10029 (Y.Z., R.Y., J.Z., Q.C., Q.S.,
P.L., N.P., N.T., C.I.H., D.F.Y.); Department of Radiology, Shanxi Provincial
People’s Hospital, Taiyuan, China (Q.C.); Department of Radiology, Harbin
Medical University Cancer Hospital, Harbin, China (Q.S., P.L.); and Department
of Pulmonary Medicine, Faculty of Medicine and Public Health, HRH Princess
Chulabhorn College of Medical Science, Chulabhorn Royal Academy, Bangkok,
Thailand (N.T.)
| | - Pengfei Li
- From the Department of Radiology, Icahn School of Medicine at Mount
Sinai, 1 Gustave L. Levy Pl, New York, NY 10029 (Y.Z., R.Y., J.Z., Q.C., Q.S.,
P.L., N.P., N.T., C.I.H., D.F.Y.); Department of Radiology, Shanxi Provincial
People’s Hospital, Taiyuan, China (Q.C.); Department of Radiology, Harbin
Medical University Cancer Hospital, Harbin, China (Q.S., P.L.); and Department
of Pulmonary Medicine, Faculty of Medicine and Public Health, HRH Princess
Chulabhorn College of Medical Science, Chulabhorn Royal Academy, Bangkok,
Thailand (N.T.)
| | - Natela Paksashvili
- From the Department of Radiology, Icahn School of Medicine at Mount
Sinai, 1 Gustave L. Levy Pl, New York, NY 10029 (Y.Z., R.Y., J.Z., Q.C., Q.S.,
P.L., N.P., N.T., C.I.H., D.F.Y.); Department of Radiology, Shanxi Provincial
People’s Hospital, Taiyuan, China (Q.C.); Department of Radiology, Harbin
Medical University Cancer Hospital, Harbin, China (Q.S., P.L.); and Department
of Pulmonary Medicine, Faculty of Medicine and Public Health, HRH Princess
Chulabhorn College of Medical Science, Chulabhorn Royal Academy, Bangkok,
Thailand (N.T.)
| | - Natthaya Triphuridet
- From the Department of Radiology, Icahn School of Medicine at Mount
Sinai, 1 Gustave L. Levy Pl, New York, NY 10029 (Y.Z., R.Y., J.Z., Q.C., Q.S.,
P.L., N.P., N.T., C.I.H., D.F.Y.); Department of Radiology, Shanxi Provincial
People’s Hospital, Taiyuan, China (Q.C.); Department of Radiology, Harbin
Medical University Cancer Hospital, Harbin, China (Q.S., P.L.); and Department
of Pulmonary Medicine, Faculty of Medicine and Public Health, HRH Princess
Chulabhorn College of Medical Science, Chulabhorn Royal Academy, Bangkok,
Thailand (N.T.)
| | - Claudia I. Henschke
- From the Department of Radiology, Icahn School of Medicine at Mount
Sinai, 1 Gustave L. Levy Pl, New York, NY 10029 (Y.Z., R.Y., J.Z., Q.C., Q.S.,
P.L., N.P., N.T., C.I.H., D.F.Y.); Department of Radiology, Shanxi Provincial
People’s Hospital, Taiyuan, China (Q.C.); Department of Radiology, Harbin
Medical University Cancer Hospital, Harbin, China (Q.S., P.L.); and Department
of Pulmonary Medicine, Faculty of Medicine and Public Health, HRH Princess
Chulabhorn College of Medical Science, Chulabhorn Royal Academy, Bangkok,
Thailand (N.T.)
| | - David F. Yankelevitz
- From the Department of Radiology, Icahn School of Medicine at Mount
Sinai, 1 Gustave L. Levy Pl, New York, NY 10029 (Y.Z., R.Y., J.Z., Q.C., Q.S.,
P.L., N.P., N.T., C.I.H., D.F.Y.); Department of Radiology, Shanxi Provincial
People’s Hospital, Taiyuan, China (Q.C.); Department of Radiology, Harbin
Medical University Cancer Hospital, Harbin, China (Q.S., P.L.); and Department
of Pulmonary Medicine, Faculty of Medicine and Public Health, HRH Princess
Chulabhorn College of Medical Science, Chulabhorn Royal Academy, Bangkok,
Thailand (N.T.)
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10
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Borgheresi A, Agostini A, Pierpaoli L, Bruno A, Valeri T, Danti G, Bicci E, Gabelloni M, De Muzio F, Brunese MC, Bruno F, Palumbo P, Fusco R, Granata V, Gandolfo N, Miele V, Barile A, Giovagnoni A. Tips and Tricks in Thoracic Radiology for Beginners: A Findings-Based Approach. Tomography 2023; 9:1153-1186. [PMID: 37368547 DOI: 10.3390/tomography9030095] [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: 05/05/2023] [Revised: 06/03/2023] [Accepted: 06/12/2023] [Indexed: 06/29/2023] Open
Abstract
This review has the purpose of illustrating schematically and comprehensively the key concepts for the beginner who approaches chest radiology for the first time. The approach to thoracic imaging may be challenging for the beginner due to the wide spectrum of diseases, their overlap, and the complexity of radiological findings. The first step consists of the proper assessment of the basic imaging findings. This review is divided into three main districts (mediastinum, pleura, focal and diffuse diseases of the lung parenchyma): the main findings will be discussed in a clinical scenario. Radiological tips and tricks, and relative clinical background, will be provided to orient the beginner toward the differential diagnoses of the main thoracic diseases.
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Affiliation(s)
- Alessandra Borgheresi
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Via Tronto 10/a, 60126 Ancona, Italy
- Department of Radiology, University Hospital "Azienda Ospedaliero Universitaria delle Marche", Via Conca 71, 60126 Ancona, Italy
| | - Andrea Agostini
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Via Tronto 10/a, 60126 Ancona, Italy
- Department of Radiology, University Hospital "Azienda Ospedaliero Universitaria delle Marche", Via Conca 71, 60126 Ancona, Italy
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy
| | - Luca Pierpaoli
- School of Radiology, University Politecnica delle Marche, Via Tronto 10/a, 60126 Ancona, Italy
| | - Alessandra Bruno
- School of Radiology, University Politecnica delle Marche, Via Tronto 10/a, 60126 Ancona, Italy
| | - Tommaso Valeri
- School of Radiology, University Politecnica delle Marche, Via Tronto 10/a, 60126 Ancona, Italy
| | - Ginevra Danti
- Department of Radiology, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy
| | - Eleonora Bicci
- Department of Radiology, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy
| | - Michela Gabelloni
- Nuclear Medicine Unit, Department of Translational Research, University of Pisa, 56126 Pisa, Italy
| | - Federica De Muzio
- Department of Medicine and Health Sciences V. Tiberio, University of Molise, 86100 Campobasso, Italy
| | - Maria Chiara Brunese
- Department of Medicine and Health Sciences V. Tiberio, University of Molise, 86100 Campobasso, Italy
| | - Federico Bruno
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy
- Department of Diagnostic Imaging, Area of Cardiovascular and Interventional Imaging, Abruzzo Health, Unit 1, 67100 L'Aquila, Italy
| | - Pierpaolo Palumbo
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy
- Department of Diagnostic Imaging, Area of Cardiovascular and Interventional Imaging, Abruzzo Health, Unit 1, 67100 L'Aquila, Italy
| | - Roberta Fusco
- Medical Oncology Division, Igea SpA, 80013 Naples, Italy
| | - Vincenza Granata
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, 80131 Naples, Italy
| | - Nicoletta Gandolfo
- Diagnostic Imaging Department, Villa Scassi Hospital-ASL 3, 16149 Genoa, Italy
| | - Vittorio Miele
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy
- Department of Radiology, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy
| | - Antonio Barile
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, 67100 L'Aquila, Italy
| | - Andrea Giovagnoni
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Via Tronto 10/a, 60126 Ancona, Italy
- Department of Radiology, University Hospital "Azienda Ospedaliero Universitaria delle Marche", Via Conca 71, 60126 Ancona, Italy
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11
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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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12
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Adams SJ, Stone E, Baldwin DR, Vliegenthart R, Lee P, Fintelmann FJ. Lung cancer screening. Lancet 2023; 401:390-408. [PMID: 36563698 DOI: 10.1016/s0140-6736(22)01694-4] [Citation(s) in RCA: 89] [Impact Index Per Article: 89.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 07/26/2022] [Accepted: 08/25/2022] [Indexed: 12/24/2022]
Abstract
Randomised controlled trials, including the National Lung Screening Trial (NLST) and the NELSON trial, have shown reduced mortality with lung cancer screening with low-dose CT compared with chest radiography or no screening. Although research has provided clarity on key issues of lung cancer screening, uncertainty remains about aspects that might be critical to optimise clinical effectiveness and cost-effectiveness. This Review brings together current evidence on lung cancer screening, including an overview of clinical trials, considerations regarding the identification of individuals who benefit from lung cancer screening, management of screen-detected findings, smoking cessation interventions, cost-effectiveness, the role of artificial intelligence and biomarkers, and current challenges, solutions, and opportunities surrounding the implementation of lung cancer screening programmes from an international perspective. Further research into risk models for patient selection, personalised screening intervals, novel biomarkers, integrated cardiovascular disease and chronic obstructive pulmonary disease assessments, smoking cessation interventions, and artificial intelligence for lung nodule detection and risk stratification are key opportunities to increase the efficiency of lung cancer screening and ensure equity of access.
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Affiliation(s)
- Scott J Adams
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
| | - Emily Stone
- Faculty of Medicine, University of New South Wales and Department of Lung Transplantation and Thoracic Medicine, St Vincent's Hospital, Sydney, NSW, Australia
| | - David R Baldwin
- Respiratory Medicine Unit, David Evans Research Centre, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | | | - Pyng Lee
- Division of Respiratory and Critical Care Medicine, National University Hospital and National University of Singapore, Singapore
| | - Florian J Fintelmann
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
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13
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Jin GY. [Lung Imaging Reporting and Data System (Lung-RADS) in Radiology: Strengths, Weaknesses and Improvement]. JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY 2023; 84:34-50. [PMID: 36818696 PMCID: PMC9935959 DOI: 10.3348/jksr.2022.0136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Revised: 12/05/2022] [Accepted: 12/27/2022] [Indexed: 06/18/2023]
Abstract
In 2019, the American College of Radiology announced Lung CT Screening Reporting & Data System (Lung-RADS) 1.1 to reduce lung cancer false positivity compared to that of Lung-RADS 1.0 for effective national lung cancer screening, and in December 2022, announced the new Lung-RADS 1.1, Lung-RADS® 2022 improvement. The Lung-RADS® 2022 measures the nodule size to the first decimal place compared to that of the Lung-RADS 1.0, to category 2 until the juxtapleural nodule size is < 10 mm, increases the size criterion of the ground glass nodule to 30 mm in category 2, and changes categories 4B and 4X to extremely suspicious. The category was divided according to the airway nodules location and shape or wall thickness of atypical pulmonary cysts. Herein, to help radiologists understand the Lung-RADS® 2022, this review will describe its advantages, disadvantages, and future improvements.
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14
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Nam JG, Goo JM. Evaluation and Management of Indeterminate Pulmonary Nodules on Chest Computed Tomography in Asymptomatic Subjects: The Principles of Nodule Guidelines. Semin Respir Crit Care Med 2022; 43:851-861. [PMID: 35803268 DOI: 10.1055/s-0042-1753474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
With the rapidly increasing number of chest computed tomography (CT) examinations, the question of how to manage lung nodules found in asymptomatic patients has become increasingly important. Several nodule management guidelines have been developed that can be applied to incidentally found lung nodules (the Fleischner Society guideline), nodules found during lung cancer screening (International Early Lung Cancer Action Program protocol [I-ELCAP] and Lung CT Screening Reporting and Data System [Lung-RADS]), or both (American College of Chest Physicians guideline [ACCP], British Thoracic Society guideline [BTS], and National Comprehensive Cancer Network guideline [NCCN]). As the radiologic nodule type (solid, part-solid, and pure ground glass) and size are significant predictors of a nodule's nature, most guidelines categorize nodules in terms of these characteristics. Various methods exist for measuring the size of nodules, and the method recommended in each guideline should be followed. The diameter can be manually measured as a single maximal diameter or as an average of two-dimensional diameters, and software can be used to obtain volumetric measurements. It is important to properly evaluate and measure nodules and familiarize ourselves with the relevant guidelines to appropriately utilize medical resources and minimize unnecessary radiation exposure to patients.
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Affiliation(s)
- Ju G Nam
- Department of Radiology, Seoul National University Hospital and College of Medicine, Seoul, Republic of Korea
| | - Jin Mo Goo
- Department of Radiology, Seoul National University Hospital and College of Medicine, Seoul, Republic of Korea.,Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea.,Cancer Research Institute, Seoul National University, Seoul, Republic of Korea
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15
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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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16
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Ko JP, Bagga B, Gozansky E, Moore WH. Solitary Pulmonary Nodule Evaluation: Pearls and Pitfalls. Semin Ultrasound CT MR 2022; 43:230-245. [PMID: 35688534 DOI: 10.1053/j.sult.2022.01.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Lung nodules are frequently encountered while interpreting chest CTs and are challenging to detect, characterize, and manage given they can represent both benign or malignant etiologies. An understanding of features associated with malignancy and causes of interpretive pitfalls is helpful to avoid misdiagnoses. This review addresses pertinent topics related to the etiologies for missed lung nodules on radiography and CT. Additionally, CT imaging technical pitfalls and challenges in addition to issues in the evaluation of nodule morphology, attenuation, and size will be discussed. Nodule management guidelines will be addressed as well as recent investigations that further our understanding of lung nodules.
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Affiliation(s)
- Jane P Ko
- Department of Radiology, NYU Langone Health, NYU Grossman School of Medicine, New York, NY.
| | - Barun Bagga
- Department of Radiology, NYU Langone Health, NYU Grossman School of Medicine, New York, NY
| | - Elliott Gozansky
- Department of Radiology, NYU Langone Health, NYU Grossman School of Medicine, New York, NY
| | - William H Moore
- Department of Radiology, NYU Langone Health, NYU Grossman School of Medicine, New York, NY
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17
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Zhu Y, Yip R, You N, Cai Q, Henschke CI, Yankelevitz DF. Characterization of Newly Detected Costal Pleura-attached Noncalcified Nodules at Annual Low-Dose CT Screenings. Radiology 2021; 301:724-731. [PMID: 34546130 DOI: 10.1148/radiol.2021210807] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background Solid costal pleura-attached noncalcified nodules (CP-NCNs) less than 10.0 mm with lentiform, oval, or semicircular (LOS) or triangular shapes and smooth margins on baseline low-dose CT scans from the Mount Sinai Early Lung and Cardiac Action Program (MS-ELCAP) were reviewed, and it was determined that they can be followed up at the first annual screening rather than having a shorter-term work-up. Purpose To determine whether the same criteria could be used for solid CP-NCNs newly identified at annual screening examinations. Materials and Methods With use of the same MS-ELCAP database, all new solid CP-NCNs measuring 30.0 mm or less were identified at 4425 annual screening examinations between 2010 and 2019. In addition, to ensure that no malignant CP-NCNs met the criteria, all solid malignant CP-NCNs of 30.0 mm or less in the International Early Lung Cancer Action Program, or I-ELCAP, database of 111 102 annual screening examinations from the 76 participating institutions between 1992 and 2019 were identified; Mount Sinai is one of these institutions. All identified solid CP-NCNs were reviewed-with the radiologists blinded to diagnosis-for shape (triangular, LOS, polygonal, round, or irregular), margin (smooth or nonsmooth), pleural attachment (broad or narrow), and the presence of emphysema and/or fibrosis within 10.0 mm of each CP-NCN. Intra- and interreader readings were performed, and agreements were determined by using the B-statistic. Results Of the 76 new solid CP-NCNs, 21 were lung cancers. Benign CP-NCNs were smaller than malignant ones (median diameter, 4.2 mm vs 11 mm; P < .001), had a different shape distributions, more frequently had smooth margins (67% vs 14%; P < .001), and less frequently had emphysema (38% vs 81%; P = .003) or fibrosis (3.6% vs 19%; P = .045) within a 10.0 mm radius. All 22 solid CP-NCNs less than 10.0 mm in average diameter with triangular or LOS shapes and smooth margins were benign, and none of the 21 solid malignant CP-NCNs had these characteristics. Intra- and interobserver agreement for triangular or LOS-shaped CP-NCNs with smooth margins was almost perfect (0.77 and 0.69, respectively). Conclusion The same follow-up recommendation developed for baseline costal pleura-attached noncalcified nodules (CP-NCNs) can be used for CP-NCNs newly identified at annual screening rounds. © RSNA, 2021.
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Affiliation(s)
- Yeqing Zhu
- From the Department of Radiology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Pl, New York, NY 10029 (Y.Z., R.Y., N.Y., Q.C., C.I.H., D.F.Y.); and Department of Radiology, Shanxi Provincial People's Hospital, Taiyuan, Shanxi, China (Q.C.)
| | - Rowena Yip
- From the Department of Radiology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Pl, New York, NY 10029 (Y.Z., R.Y., N.Y., Q.C., C.I.H., D.F.Y.); and Department of Radiology, Shanxi Provincial People's Hospital, Taiyuan, Shanxi, China (Q.C.)
| | - Nan You
- From the Department of Radiology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Pl, New York, NY 10029 (Y.Z., R.Y., N.Y., Q.C., C.I.H., D.F.Y.); and Department of Radiology, Shanxi Provincial People's Hospital, Taiyuan, Shanxi, China (Q.C.)
| | - Qiang Cai
- From the Department of Radiology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Pl, New York, NY 10029 (Y.Z., R.Y., N.Y., Q.C., C.I.H., D.F.Y.); and Department of Radiology, Shanxi Provincial People's Hospital, Taiyuan, Shanxi, China (Q.C.)
| | - Claudia I Henschke
- From the Department of Radiology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Pl, New York, NY 10029 (Y.Z., R.Y., N.Y., Q.C., C.I.H., D.F.Y.); and Department of Radiology, Shanxi Provincial People's Hospital, Taiyuan, Shanxi, China (Q.C.)
| | - David F Yankelevitz
- From the Department of Radiology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Pl, New York, NY 10029 (Y.Z., R.Y., N.Y., Q.C., C.I.H., D.F.Y.); and Department of Radiology, Shanxi Provincial People's Hospital, Taiyuan, Shanxi, China (Q.C.)
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- From the Department of Radiology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Pl, New York, NY 10029 (Y.Z., R.Y., N.Y., Q.C., C.I.H., D.F.Y.); and Department of Radiology, Shanxi Provincial People's Hospital, Taiyuan, Shanxi, China (Q.C.)
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18
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Azour L, Ko JP, Washer SL, Lanier A, Brusca-Augello G, Alpert JB, Moore WH. Incidental Lung Nodules on Cross-sectional Imaging: Current Reporting and Management. Radiol Clin North Am 2021; 59:535-549. [PMID: 34053604 DOI: 10.1016/j.rcl.2021.03.005] [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: 11/26/2022]
Abstract
Pulmonary nodules are the most common incidental finding in the chest, particularly on computed tomographs that include a portion or all of the chest, and may be encountered more frequently with increasing utilization of cross-sectional imaging. Established guidelines address the reporting and management of incidental pulmonary nodules, both solid and subsolid, synthesizing nodule and patient features to distinguish benign nodules from those of potential clinical consequence. Standard nodule assessment is essential for the accurate reporting of nodule size, attenuation, and morphology, all features with varying risk implications and thus management recommendations.
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Affiliation(s)
- Lea Azour
- Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, Center for Biomedical Imaging, 660 First Avenue, New York, NY 10016, USA.
| | - Jane P Ko
- Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, Center for Biomedical Imaging, 660 First Avenue, New York, NY 10016, USA
| | - Sophie L Washer
- Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, Center for Biomedical Imaging, 660 First Avenue, New York, NY 10016, USA
| | - Amelia Lanier
- Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, Center for Biomedical Imaging, 660 First Avenue, New York, NY 10016, USA
| | - Geraldine Brusca-Augello
- Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, Center for Biomedical Imaging, 660 First Avenue, New York, NY 10016, USA
| | - Jeffrey B Alpert
- Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, Center for Biomedical Imaging, 660 First Avenue, New York, NY 10016, USA
| | - William H Moore
- Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, Center for Biomedical Imaging, 660 First Avenue, New York, NY 10016, USA
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19
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Kastner J, Hossain R, Jeudy J, Dako F, Mehta V, Dalal S, Dharaiya E, White C. Lung-RADS Version 1.0 versus Lung-RADS Version 1.1: Comparison of Categories Using Nodules from the National Lung Screening Trial. Radiology 2021; 300:199-206. [PMID: 33944631 DOI: 10.1148/radiol.2021203704] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Background The American College of Radiology updated Lung Imaging Reporting and Data System (Lung-RADS) version 1.0 to version 1.1 in May 2019, with the two key changes involving perifissural nodules (PFNs) and ground-glass nodules (GGNs) now designated as a negative screening result. This study examines the effects of these changes using National Lung Screening Trial (NLST) data. Purpose To determine the frequency of PFNs and GGNs reclassified from category 3 or 4A to the more benign category 2 in the updated Lung-RADS version 1.1, as compared with Lung-RADS version 1.0, using CT scans from the NLST. Materials and Methods In this secondary analysis of the NLST, the authors studied all noncalcified nodules (NCNs) found on the incident scan. Nodules were evaluated using criteria from both Lung-RADS version 1.0 and version 1.1, which were compared to determine changes in the number of nodules deemed benign. A McNemar test was used to assess statistical significance. Results A total of 2813 patients (mean age ± standard deviation, 62 years ± 5; 1717 men) with 4408 NCNs were studied. Of the largest 1092 solid NCNs measuring at least 6 mm but less than 10 mm, 216 (19.8%) were deemed PFNs (category 2) using Lung-RADS version 1.1. Eleven of the 1092 solid NCNs (1.0%) were malignant, but none were PFNs. Of 161 GGNs, three (1.9%) were category 3 according to Lung-RADS version 1.0, of which two (66.7%) were down-classified to category 2 with version 1.1. One of the three down-categorized GGNs (version 1.1) proved to be malignant (false-negative finding). Statistically significant improvement for Lung-RADS version 1.1 was found for total nodules (P < .01) and PFNs (P < .01), but not GGNs (P = .48). Conclusion This secondary analysis of National Lung Screening Trial data shows that Lung Imaging Reporting and Data System version 1.1 decreased the number of false-positive results. This was related to the down-classification of perifissural nodules in the range of 6 up to 10 mm. The increase in allowable nodule size for ground-glass nodules in category 2 from 20 mm (version 1.0) to 30 mm (version 1.1) showed no benefit. © RSNA, 2021 See also the editorial by Mayo and Lam in this issue.
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Affiliation(s)
- Julia Kastner
- From the Department of Diagnostic Radiology, University of Maryland, 22 S Greene St, Baltimore, MD 21136 (J.K., R.H., J.J., F.D., V.M., C.W.); Philips Research North America, Cambridge, Mass (S.D.); and Philips Healthcare, Highland Heights, Ohio (E.D.)
| | - Rydhwana Hossain
- From the Department of Diagnostic Radiology, University of Maryland, 22 S Greene St, Baltimore, MD 21136 (J.K., R.H., J.J., F.D., V.M., C.W.); Philips Research North America, Cambridge, Mass (S.D.); and Philips Healthcare, Highland Heights, Ohio (E.D.)
| | - Jean Jeudy
- From the Department of Diagnostic Radiology, University of Maryland, 22 S Greene St, Baltimore, MD 21136 (J.K., R.H., J.J., F.D., V.M., C.W.); Philips Research North America, Cambridge, Mass (S.D.); and Philips Healthcare, Highland Heights, Ohio (E.D.)
| | - Farouk Dako
- From the Department of Diagnostic Radiology, University of Maryland, 22 S Greene St, Baltimore, MD 21136 (J.K., R.H., J.J., F.D., V.M., C.W.); Philips Research North America, Cambridge, Mass (S.D.); and Philips Healthcare, Highland Heights, Ohio (E.D.)
| | - Varun Mehta
- From the Department of Diagnostic Radiology, University of Maryland, 22 S Greene St, Baltimore, MD 21136 (J.K., R.H., J.J., F.D., V.M., C.W.); Philips Research North America, Cambridge, Mass (S.D.); and Philips Healthcare, Highland Heights, Ohio (E.D.)
| | - Sandeep Dalal
- From the Department of Diagnostic Radiology, University of Maryland, 22 S Greene St, Baltimore, MD 21136 (J.K., R.H., J.J., F.D., V.M., C.W.); Philips Research North America, Cambridge, Mass (S.D.); and Philips Healthcare, Highland Heights, Ohio (E.D.)
| | - Ekta Dharaiya
- From the Department of Diagnostic Radiology, University of Maryland, 22 S Greene St, Baltimore, MD 21136 (J.K., R.H., J.J., F.D., V.M., C.W.); Philips Research North America, Cambridge, Mass (S.D.); and Philips Healthcare, Highland Heights, Ohio (E.D.)
| | - Charles White
- From the Department of Diagnostic Radiology, University of Maryland, 22 S Greene St, Baltimore, MD 21136 (J.K., R.H., J.J., F.D., V.M., C.W.); Philips Research North America, Cambridge, Mass (S.D.); and Philips Healthcare, Highland Heights, Ohio (E.D.)
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20
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Mayo JR, Lam S. Doing Too Much or Not Enough: Striking a Balance. Radiology 2021; 300:207-208. [PMID: 33949897 DOI: 10.1148/radiol.2021210774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- John R Mayo
- From the Department of Radiology, Vancouver General Hospital, 899 W 12th Ave, Vancouver, BC, Canada V5Z 1M9 (J.R.M.); and Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada (S.L.)
| | - Stephen Lam
- From the Department of Radiology, Vancouver General Hospital, 899 W 12th Ave, Vancouver, BC, Canada V5Z 1M9 (J.R.M.); and Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada (S.L.)
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21
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Su Y, Li D, Chen X. Lung Nodule Detection based on Faster R-CNN Framework. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 200:105866. [PMID: 33309304 DOI: 10.1016/j.cmpb.2020.105866] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Accepted: 11/17/2020] [Indexed: 06/12/2023]
Abstract
BACKGROUND Lung cancer is a worldwide high-risk disease, and lung nodules are the main manifestation of early lung cancer. Automatic detection of lung nodules reduces the workload of radiologists, the rate of misdiagnosis and missed diagnosis. For this purpose, we propose a Faster R-CNN algorithm for the detection of these lung nodules. METHOD Faster R-CNN algorithm can detect lung nodules, and the training set is used to prove the feasibility of this technique. In theory, parameter optimization can improve network structure, as well as detection accuracy. RESULT Through experiments, the best parameters are that the basic learning rate is 0.001, step size is 70,000, attenuation coefficient is 0.1, the value of Dropout is 0.5, and the value of Batch Size is 64. Compared with other networks for detecting lung nodules, the optimized and improved algorithm proposed in this paper generally improves detection accuracy by more than 20% when compared with the other traditional algorithms. CONCLUSION Our experimental results have proved that the method of detecting lung nodules based on Faster R-CNN algorithm has good accuracy and therefore, presents potential clinical value in lung disease diagnosis. This method can further assist radiologists, and also for researchers in the design and development of the detection system for lung nodules.
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Affiliation(s)
- Ying Su
- Department of Nursing, Shengjing Hospital of China Medical University, Shenyang, Liaoning, 110000, China
| | - Dan Li
- Department of Nursing, Shengjing Hospital of China Medical University, Shenyang, Liaoning, 110000, China
| | - Xiaodong Chen
- Department of Oncology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, 110000, China.
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22
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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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23
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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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24
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Mo L, Adler B, Green C, Brims FJH. Malignant mesothelioma presenting as a solitary perifissural nodule. Intern Med J 2020; 50:1592-1594. [PMID: 33354873 DOI: 10.1111/imj.15120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2019] [Accepted: 12/16/2019] [Indexed: 11/29/2022]
Affiliation(s)
- Lin Mo
- Department of Respiratory Medicine, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia.,Department of Respiratory Medicine, Fiona Stanley Hospital, Perth, Western Australia, Australia
| | - Brendan Adler
- Envision Medical Imaging, Perth, Western Australia, Australia
| | - Celia Green
- PathWest Laboratory Medicine, Perth, Western Australia, Australia
| | - Fraser J H Brims
- Department of Respiratory Medicine, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia.,Curtin Medical School, Curtin University, Perth, Western Australia, Australia
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25
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Han D, Heuvelmans M, Rook M, Dorrius M, van Houten L, Price NW, Pickup LC, Novotny P, Oudkerk M, Declerck J, Gleeson F, van Ooijen P, Vliegenthart R. Evaluation of a novel deep learning-based classifier for perifissural nodules. Eur Radiol 2020; 31:4023-4030. [PMID: 33269413 PMCID: PMC8128854 DOI: 10.1007/s00330-020-07509-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2020] [Revised: 09/10/2020] [Accepted: 11/11/2020] [Indexed: 11/26/2022]
Abstract
Objectives To evaluate the performance of a novel convolutional neural network (CNN) for the classification of typical perifissural nodules (PFN). Methods Chest CT data from two centers in the UK and The Netherlands (1668 unique nodules, 1260 individuals) were collected. Pulmonary nodules were classified into subtypes, including “typical PFNs” on-site, and were reviewed by a central clinician. The dataset was divided into a training/cross-validation set of 1557 nodules (1103 individuals) and a test set of 196 nodules (158 individuals). For the test set, three radiologically trained readers classified the nodules into three nodule categories: typical PFN, atypical PFN, and non-PFN. The consensus of the three readers was used as reference to evaluate the performance of the PFN-CNN. Typical PFNs were considered as positive results, and atypical PFNs and non-PFNs were grouped as negative results. PFN-CNN performance was evaluated using the ROC curve, confusion matrix, and Cohen’s kappa. Results Internal validation yielded a mean AUC of 91.9% (95% CI 90.6–92.9) with 78.7% sensitivity and 90.4% specificity. For the test set, the reader consensus rated 45/196 (23%) of nodules as typical PFN. The classifier-reader agreement (k = 0.62–0.75) was similar to the inter-reader agreement (k = 0.64–0.79). Area under the ROC curve was 95.8% (95% CI 93.3–98.4), with a sensitivity of 95.6% (95% CI 84.9–99.5), and specificity of 88.1% (95% CI 81.8–92.8). Conclusion The PFN-CNN showed excellent performance in classifying typical PFNs. Its agreement with radiologically trained readers is within the range of inter-reader agreement. Thus, the CNN-based system has potential in clinical and screening settings to rule out perifissural nodules and increase reader efficiency. Key Points • Agreement between the PFN-CNN and radiologically trained readers is within the range of inter-reader agreement. • The CNN model for the classification of typical PFNs achieved an AUC of 95.8% (95% CI 93.3–98.4) with 95.6% (95% CI 84.9–99.5) sensitivity and 88.1% (95% CI 81.8–92.8) specificity compared to the consensus of three readers. Supplementary Information The online version contains supplementary material available at 10.1007/s00330-020-07509-x.
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Affiliation(s)
- Daiwei Han
- University Medical Center Groningen, Department of Radiology, University of Groningen, Groningen, The Netherlands
| | - Marjolein Heuvelmans
- University Medical Center Groningen, Department of Epidemiology, University of Groningen, Groningen, The Netherlands.
- Department of Pulmonology, Medisch Spectrum Twente, Enschede, The Netherlands.
| | - Mieneke Rook
- University Medical Center Groningen, Department of Radiology, University of Groningen, Groningen, The Netherlands
- Department of Radiology, Martini Ziekenhuis, Groningen, The Netherlands
| | - Monique Dorrius
- University Medical Center Groningen, Department of Radiology, University of Groningen, Groningen, The Netherlands
| | - Luutsen van Houten
- University Medical Center Groningen, Department of Radiology, University of Groningen, Groningen, The Netherlands
| | | | | | | | - Matthijs Oudkerk
- Faculty of Medical Sciences, University of Groningen, Groningen, the Netherlands
- Institute for Diagnostic Accuracy, Groningen, The Netherlands
| | | | - Fergus Gleeson
- National Consortium of Intelligent Medical Imaging, Oxford University, Oxford, Great Britain, UK
| | - Peter van Ooijen
- University Medical Center Groningen, Department of Radiotherapy, University of Groningen, Groningen, The Netherlands
| | - Rozemarijn Vliegenthart
- University Medical Center Groningen, Department of Radiology, University of Groningen, Groningen, The Netherlands
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26
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Dyer SC, Bartholmai BJ, Koo CW. Implications of the updated Lung CT Screening Reporting and Data System (Lung-RADS version 1.1) for lung cancer screening. J Thorac Dis 2020; 12:6966-6977. [PMID: 33282402 PMCID: PMC7711402 DOI: 10.21037/jtd-2019-cptn-02] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Lung cancer remains the leading cause of cancer death in the United States. Screening with low-dose computed tomography (LDCT) has been proven to aid in early detection of lung cancer and reduce disease specific mortality. In 2014, the American College of Radiology (ACR) released version 1.0 of the Lung CT Screening Reporting and Data System (Lung-RADS) as a quality tool to standardize the reporting of lung cancer screening LDCT. In 2019, 5 years after the implementation of Lung-RADS version 1.0 the ACR released the updated Lung-RADS version 1.1 which incorporates initial experience with lung cancer screening. In this review, we outline the implications of the changes and additions in Lung-RADS version 1.1 and examine relevant literature for many of the updates. We also highlight several challenges and opportunities as Lung-RADS version 1.1 is implemented in lung cancer screening programs.
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Affiliation(s)
- Spencer C Dyer
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | - Chi Wan Koo
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
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27
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Lam S, Bryant H, Donahoe L, Domingo A, Earle C, Finley C, Gonzalez AV, Hergott C, Hung RJ, Ireland AM, Lovas M, Manos D, Mayo J, Maziak DE, McInnis M, Myers R, Nicholson E, Politis C, Schmidt H, Sekhon HS, Soprovich M, Stewart A, Tammemagi M, Taylor JL, Tsao MS, Warkentin MT, Yasufuku K. Management of screen-detected lung nodules: A Canadian partnership against cancer guidance document. CANADIAN JOURNAL OF RESPIRATORY CRITICAL CARE AND SLEEP MEDICINE 2020. [DOI: 10.1080/24745332.2020.1819175] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Affiliation(s)
- Stephen Lam
- British Columbia Cancer Agency & the University of British Columbia, Vancouver, British Columbia, Canada
| | - Heather Bryant
- Screening and Early Detection, Canadian Partnership Against Cancer, Toronto, Ontario, Canada
| | - Laura Donahoe
- Division of Thoracic Surgery, Department of Surgery, University Health Network, Toronto, Ontario, Canada
| | - Ashleigh Domingo
- Screening and Early Detection, Canadian Partnership Against Cancer, Toronto, Ontario, Canada
| | - Craig Earle
- Screening and Early Detection, Canadian Partnership Against Cancer, Toronto, Ontario, Canada
| | - Christian Finley
- Department of Thoracic Surgery, St. Joseph's Healthcare, McMaster University, Hamilton, Ontario, Canada
| | - Anne V. Gonzalez
- Division of Respiratory Medicine, McGill University, Montreal, Quebec, Canada
| | - Christopher Hergott
- Division of Respiratory Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Rayjean J. Hung
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Ontario, Canada
| | - Anne Marie Ireland
- Patient and Family Advocate, Canadian Partnership Against Cancer, Toronto, Ontario, Canada
| | - Michael Lovas
- Patient and Family Advocate, Canadian Partnership Against Cancer, Toronto, Ontario, Canada
| | - Daria Manos
- Department of Diagnostic Radiology, Dalhousie University, Halifax, Nova Scotia, Canada
| | - John Mayo
- Department of Radiology, Vancouver Coastal Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - Donna E. Maziak
- Surgical Oncology Division of Thoracic Surgery, Ottawa Hospital, Ottawa, Ontario, Canada
| | - Micheal McInnis
- Joint Department of Medical Imaging, University Health Network, Toronto, Ontario, Canada
| | - Renelle Myers
- British Columbia Cancer Agency & the University of British Columbia, Vancouver, British Columbia, Canada
| | - Erika Nicholson
- Screening and Early Detection, Canadian Partnership Against Cancer, Toronto, Ontario, Canada
| | - Christopher Politis
- Screening and Early Detection, Canadian Partnership Against Cancer, Toronto, Ontario, Canada
| | - Heidi Schmidt
- University Health Network and Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Harman S. Sekhon
- Department of Pathology and Laboratory Medicine, University of Ottawa, The Ottawa Hospital, Ottawa, Ontario, Canada
| | - Marie Soprovich
- Patient and Family Advocate, Canadian Partnership Against Cancer, Toronto, Ontario, Canada
| | - Archie Stewart
- Patient and Family Advocate, Canadian Partnership Against Cancer, Toronto, Ontario, Canada
| | - Martin Tammemagi
- Department of Health Sciences, Brock University, St. Catharines, Ontario, Canada
| | - Jana L. Taylor
- Department of Radiology, McGill University, Montreal, Quebec, Canada
| | - Ming-Sound Tsao
- Department of Laboratory Medicine and Pathobiology, University Health Network and Princess Margaret Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Matthew T. Warkentin
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Ontario, Canada
| | - Kazuhiro Yasufuku
- Division of Thoracic Surgery, Department of Surgery and Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto General Hospital, University Health Network, Toronto, Ontario, Canada
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28
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Godoy MCB. Conservative Management of Juxtapleural Nodules at Low-Dose CT Lung Cancer Screening: Is This Prudent? Radiology 2020; 297:719-720. [PMID: 33026290 DOI: 10.1148/radiol.2020203703] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Myrna C B Godoy
- From the Department of Thoracic Imaging, University of Texas M.D. Anderson Cancer Center, 1515 Holcombe Blvd, Unit 371, Houston, TX 77030
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29
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Zhu Y, Yip R, You N, Henschke CI, Yankelevitz DF. Management of Nodules Attached to the Costal Pleura at Low-Dose CT Screening for Lung Cancer. Radiology 2020; 297:710-718. [PMID: 33021893 DOI: 10.1148/radiol.2020202388] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Background Pulmonary nodule features have been used to differentiate benign from malignant nodules. Purpose To determine the frequency of solid noncalcified nodules attached to the costal pleura (CP-NCNs) at baseline low-dose CT and to identify key features of benignity. Materials and Methods A retrospective review was performed of baseline low-dose CT scans obtained in 8730 participants in the Mount Sinai Early Lung and Cardiac Action Program screening cohort between 1992 and 2019. Participants with one or more solid CP-NCNs between 3.0 mm and 30.0 mm in average diameter were included. For each CP-NCN, the size, location, shape (lentiform, oval, or semicircular [LOS]; triangular; polygonal; round; or irregular), margin (smooth or nonsmooth), and attachment to the costal pleura (broad or narrow) were documented. The manifestation of emphysema and fibrosis within a 10-mm radius of the CP-NCN was determined. Multivariable logistic regression analysis, with synthetic minority oversampling techniques, was used. Results The 569 eligible participants (average age, 62 years ± 9 [standard deviation]; 343 women) had 943 solid CP-NCNs, of which 934 (99.0%) were benign and nine (1.0%) were malignant. Multivariable analysis showed that five shapes could be consolidated into three (LOS and/or triangular, round and/or polygonal, and irregular shape); pleural attachment was not a significant independent predictor (odds ratio, 1.24; P = .70); and interaction terms of size with shape (odds ratio, 0.73; P = .005) and margin were significant (odds ratio, 0.80; P = .001). All 603 CP-NCNs less than 10.0 mm with LOS or triangular shapes and smooth margins were benign. Conclusion All baseline noncalcified solid nodules attached to the costal pleura less than 10.0 mm in average diameter with lentiform, oval, semicircular, or triangular shapes and smooth margins were benign; thus, for these nodules, an annual repeat scan in 1 year, rather than a more immediate work-up, is recommended. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Godoy in this issue.
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Affiliation(s)
- Yeqing Zhu
- From the Department of Radiology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1234, New York, NY 10029-6574
| | - Rowena Yip
- From the Department of Radiology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1234, New York, NY 10029-6574
| | - Nan You
- From the Department of Radiology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1234, New York, NY 10029-6574
| | - Claudia I Henschke
- From the Department of Radiology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1234, New York, NY 10029-6574
| | - David F Yankelevitz
- From the Department of Radiology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1234, New York, NY 10029-6574
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Schreuder A, Jacobs C, Scholten ET, van Ginneken B, Schaefer-Prokop CM, Prokop M. Typical CT Features of Intrapulmonary Lymph Nodes: A Review. Radiol Cardiothorac Imaging 2020; 2:e190159. [PMID: 33778597 DOI: 10.1148/ryct.2020190159] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Revised: 04/02/2020] [Accepted: 04/28/2020] [Indexed: 12/26/2022]
Abstract
Several studies investigated the appearance of intrapulmonary lymph nodes (IPLNs) at CT with pathologic correlation. IPLNs are benign lesions and do not require follow-up after initial detection. There are indications that IPLNs represent a considerable portion of incidentally found pulmonary nodules seen at high-resolution CT. The reliable and accurate identification of IPLNs as benign nodules may substantially reduce the number of unnecessary follow-up CT examinations. Typical CT features of IPLNs are a noncalcified solid nodule with sharp margins; a round, oval, or polygonal shape; distanced 15 mm or less from the pleura; and most being located below the level of the carina. The term perifissural nodule (PFN) was coined based on some of these characteristics. Standardization of those CT criteria are a prerequisite for accurate nodule classification. However, four different definitions of PFNs can currently be found in the literature. Furthermore, there is considerable variation in the reported interobserver agreement, malignancy rate, and prevalence of PFNs. The purpose of this review was to provide an overview of what is known about PFNs. In addition, knowledge gaps in defining PFNs will be discussed. A decision tree to guide clinicians in classifying nodules as PFNs is provided. Supplemental material is available for this article. © RSNA, 2020 See also the commentary by White and Rubin in this issue.
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Affiliation(s)
- Anton Schreuder
- Diagnostic Image Analysis Group, Department of Radiology, Nuclear Medicine, and Anatomy, Radboudumc, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands (A.S., C.J., E.T.S., B.v.G., C.M.S.P., M.P.); Fraunhofer MEVIS, Bremen, Germany (C.J., B.v.G.); and Department of Radiology, Meander Medisch Centrum, Amersfoort, the Netherlands (C.M.S.P.)
| | - Colin Jacobs
- Diagnostic Image Analysis Group, Department of Radiology, Nuclear Medicine, and Anatomy, Radboudumc, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands (A.S., C.J., E.T.S., B.v.G., C.M.S.P., M.P.); Fraunhofer MEVIS, Bremen, Germany (C.J., B.v.G.); and Department of Radiology, Meander Medisch Centrum, Amersfoort, the Netherlands (C.M.S.P.)
| | - Ernst T Scholten
- Diagnostic Image Analysis Group, Department of Radiology, Nuclear Medicine, and Anatomy, Radboudumc, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands (A.S., C.J., E.T.S., B.v.G., C.M.S.P., M.P.); Fraunhofer MEVIS, Bremen, Germany (C.J., B.v.G.); and Department of Radiology, Meander Medisch Centrum, Amersfoort, the Netherlands (C.M.S.P.)
| | - Bram van Ginneken
- Diagnostic Image Analysis Group, Department of Radiology, Nuclear Medicine, and Anatomy, Radboudumc, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands (A.S., C.J., E.T.S., B.v.G., C.M.S.P., M.P.); Fraunhofer MEVIS, Bremen, Germany (C.J., B.v.G.); and Department of Radiology, Meander Medisch Centrum, Amersfoort, the Netherlands (C.M.S.P.)
| | - Cornelia M Schaefer-Prokop
- Diagnostic Image Analysis Group, Department of Radiology, Nuclear Medicine, and Anatomy, Radboudumc, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands (A.S., C.J., E.T.S., B.v.G., C.M.S.P., M.P.); Fraunhofer MEVIS, Bremen, Germany (C.J., B.v.G.); and Department of Radiology, Meander Medisch Centrum, Amersfoort, the Netherlands (C.M.S.P.)
| | - Mathias Prokop
- Diagnostic Image Analysis Group, Department of Radiology, Nuclear Medicine, and Anatomy, Radboudumc, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands (A.S., C.J., E.T.S., B.v.G., C.M.S.P., M.P.); Fraunhofer MEVIS, Bremen, Germany (C.J., B.v.G.); and Department of Radiology, Meander Medisch Centrum, Amersfoort, the Netherlands (C.M.S.P.)
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Schreuder A, Jacobs C, Scholten ET, Prokop M, van Ginneken B, Lynch DA, Schaefer-Prokop CM. Association between the number and size of intrapulmonary lymph nodes and chronic obstructive pulmonary disease severity. PeerJ 2020; 8:e9166. [PMID: 32685283 PMCID: PMC7337033 DOI: 10.7717/peerj.9166] [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: 10/15/2019] [Accepted: 04/19/2020] [Indexed: 11/20/2022] Open
Abstract
Purpose One of the main pathophysiological mechanisms of chronic obstructive pulmonary disease is inflammation, which has been associated with lymphadenopathy. Intrapulmonary lymph nodes can be identified on CT as perifissural nodules (PFN). We investigated the association between the number and size of PFNs and measures of COPD severity. Materials and Methods CT images were obtained from COPDGene. 50 subjects were randomly selected per GOLD stage (0 to 4), GOLD-unclassified, and never-smoker groups and allocated to either "Healthy," "Mild," or "Moderate/severe" groups. 26/350 (7.4%) subjects had missing images and were excluded. Supported by computer-aided detection, a trained researcher prelocated non-calcified opacities larger than 3 mm in diameter. Included lung opacities were classified independently by two radiologists as either "PFN," "not a PFN," "calcified," or "not a nodule"; disagreements were arbitrated by a third radiologist. Ordinal logistic regression was performed as the main statistical test. Results A total of 592 opacities were included in the observer study. A total of 163/592 classifications (27.5%) required arbitration. A total of 17/592 opacities (2.9%) were excluded from the analysis because they were not considered nodular, were calcified, or all three radiologists disagreed. A total of 366/575 accepted nodules (63.7%) were considered PFNs. A maximum of 10 PFNs were found in one image; 154/324 (47.5%) contained no PFNs. The number of PFNs per subject did not differ between COPD severity groups (p = 0.50). PFN short-axis diameter could significantly distinguish between the Mild and Moderate/severe groups, but not between the Healthy and Mild groups (p = 0.021). Conclusions There is no relationship between PFN count and COPD severity. There may be a weak trend of larger intrapulmonary lymph nodes among patients with more advanced stages of COPD.
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Affiliation(s)
- Anton Schreuder
- Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, The Netherlands
| | - Colin Jacobs
- Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, The Netherlands.,Fraunhofer MEVIS, Bremen, Germany
| | - Ernst T Scholten
- Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, The Netherlands
| | - Mathias Prokop
- Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, The Netherlands
| | - Bram van Ginneken
- Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, The Netherlands.,Fraunhofer MEVIS, Bremen, Germany
| | - David A Lynch
- Department of Radiology, National Jewish Medical and Research Center, Denver, CO, United States of America
| | - Cornelia M Schaefer-Prokop
- Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, The Netherlands.,Department of Radiology, Meander Medisch Centrum, Amersfoort, The Netherlands
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Gierada DS, Black WC, Chiles C, Pinsky PF, Yankelevitz DF. Low-Dose CT Screening for Lung Cancer: Evidence from 2 Decades of Study. Radiol Imaging Cancer 2020; 2:e190058. [PMID: 32300760 PMCID: PMC7135238 DOI: 10.1148/rycan.2020190058] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Revised: 10/15/2019] [Accepted: 11/20/2019] [Indexed: 12/17/2022]
Abstract
Lung cancer remains the overwhelmingly greatest cause of cancer death in the United States, accounting for more annual deaths than breast, prostate, and colon cancer combined. Accumulated evidence since the mid to late 1990s, however, indicates that low-dose CT screening of high-risk patients enables detection of lung cancer at an early stage and can reduce the risk of dying from lung cancer. CT screening is now a recommended clinical service in the United States, subject to guidelines and reimbursement requirements intended to standardize practice and optimize the balance of benefits and risks. In this review, the evidence on the effectiveness of CT screening will be summarized and the current guidelines and standards will be described in the context of knowledge gained from lung cancer screening studies. In addition, an overview of the potential advances that may improve CT screening will be presented, and the need to better understand the performance in clinical practice outside of the research trial setting will be discussed. © RSNA, 2020.
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Affiliation(s)
- David S. Gierada
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S. Kingshighway Blvd, St Louis, MO 63110 (D.S.G.); Department of Radiology, Dartmouth-Hitchcock Medical Center, Lebanon, NH (W.C.B.); Department of Radiology, Wake Forest University School of Medicine, Winston-Salem, NC (C.C.); Division of Cancer Prevention, National Cancer Institute, Bethesda, Md (P.F.P.); and Department of Radiology, Mount Sinai School of Medicine, New York, NY (D.F.Y.)
| | - William C. Black
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S. Kingshighway Blvd, St Louis, MO 63110 (D.S.G.); Department of Radiology, Dartmouth-Hitchcock Medical Center, Lebanon, NH (W.C.B.); Department of Radiology, Wake Forest University School of Medicine, Winston-Salem, NC (C.C.); Division of Cancer Prevention, National Cancer Institute, Bethesda, Md (P.F.P.); and Department of Radiology, Mount Sinai School of Medicine, New York, NY (D.F.Y.)
| | - Caroline Chiles
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S. Kingshighway Blvd, St Louis, MO 63110 (D.S.G.); Department of Radiology, Dartmouth-Hitchcock Medical Center, Lebanon, NH (W.C.B.); Department of Radiology, Wake Forest University School of Medicine, Winston-Salem, NC (C.C.); Division of Cancer Prevention, National Cancer Institute, Bethesda, Md (P.F.P.); and Department of Radiology, Mount Sinai School of Medicine, New York, NY (D.F.Y.)
| | - Paul F. Pinsky
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S. Kingshighway Blvd, St Louis, MO 63110 (D.S.G.); Department of Radiology, Dartmouth-Hitchcock Medical Center, Lebanon, NH (W.C.B.); Department of Radiology, Wake Forest University School of Medicine, Winston-Salem, NC (C.C.); Division of Cancer Prevention, National Cancer Institute, Bethesda, Md (P.F.P.); and Department of Radiology, Mount Sinai School of Medicine, New York, NY (D.F.Y.)
| | - David F. Yankelevitz
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S. Kingshighway Blvd, St Louis, MO 63110 (D.S.G.); Department of Radiology, Dartmouth-Hitchcock Medical Center, Lebanon, NH (W.C.B.); Department of Radiology, Wake Forest University School of Medicine, Winston-Salem, NC (C.C.); Division of Cancer Prevention, National Cancer Institute, Bethesda, Md (P.F.P.); and Department of Radiology, Mount Sinai School of Medicine, New York, NY (D.F.Y.)
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Han D, Heuvelmans MA, van der Aalst CM, van Smoorenburg LH, Dorrius MD, Rook M, Nackaerts K, Walter JE, Groen HJM, Vliegenthart R, de Koning HJ, Oudkerk M. New Fissure-Attached Nodules in Lung Cancer Screening: A Brief Report From The NELSON Study. J Thorac Oncol 2020; 15:125-129. [PMID: 31606605 DOI: 10.1016/j.jtho.2019.09.193] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Revised: 09/03/2019] [Accepted: 09/06/2019] [Indexed: 11/18/2022]
Abstract
INTRODUCTION In incidence lung cancer screening rounds, new pulmonary nodules are regular findings. They have a higher lung cancer probability than baseline nodules. Previous studies have shown that baseline perifissural nodules (PFNs) represent benign lesions. Whether this is also the case for incident PFNs is unknown. This study evaluated newly detected nodules in the Dutch-Belgian randomized-controlled NELSON study with respect to incidence of fissure-attached nodules, their classification, and lung cancer probability. METHODS Within the NELSON trial, 7557 participants underwent baseline screening between April 2004 and December 2006. Participants with new nodules detected after baseline were included. Nodules were classified based on location and attachment. Fissure-attached nodules were re-evaluated to be classified as typical, atypical, or non-PFN by two radiologists without knowledge of participant lung cancer status. RESULTS One thousand four hundred eighty-four new nodules were detected in 949 participants (77.4% male, median age 59 years [interquartile range: 55-63 years]) in the second, third, and final NELSON screening round. Based on 2-year follow-up or pathology, 1393 nodules (93.8%) were benign. In total, 97 (6.5%) were fissure-attached, including 10 malignant nodules. None of the new fissure-attached malignant nodules was classified as typical or atypical PFN. CONCLUSIONS In the NELSON study, 6.5% of incident lung nodules were fissure-attached. None of the lung cancers that originated from a new fissure-attached nodule in the incidence lung cancer screening rounds was classified as a typical or atypical PFN. Our results suggest that also in the case of a new PFN, it is highly unlikely that these PFNs will be diagnosed as lung cancer.
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Affiliation(s)
- Daiwei Han
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Marjolein A Heuvelmans
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands; Department of Pulmonology, Medisch Spectrum Twente, Enschede, Netherlands.
| | - Carlijn M van der Aalst
- Department of Public Health, Erasmus MC - University Medical Center Rotterdam, Rotterdam, Netherlands
| | | | - Monique D Dorrius
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Mieneke Rook
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands; Department of Radiology, Martini Hospital, Groningen, Netherlands
| | - Kristiaan Nackaerts
- Department of Pulmonary Medicine, KU Leuven, University Hospitals Leuven, Leuven, Belgium
| | - Joan E Walter
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Harry J M Groen
- Department of Pulmonology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Rozemarijn Vliegenthart
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Harry J de Koning
- Department of Public Health, Erasmus MC - University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Matthijs Oudkerk
- Faculty of Medical Sciences, University of Groningen, Groningen, Netherlands; iDNA B.V., Groningen, the Netherlands
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Abstract
Parallel and often unrelated developments in health care and technology have all been necessary to bring about early detection of lung cancer and the opportunity to decrease mortality from lung cancer through early detection of the disease by computed tomography. Lung cancer screening programs provide education for patients and clinicians, support smoking cessation as primary prevention for lung cancer, and facilitate health care for tobacco-associated diseases, including cardiovascular and chronic lung diseases. Guidelines for lung cancer screening will need to continue to evolve as additional risk factors and screening tests are developed. Data collection from lung cancer screening programs is vital to the further development of fiscally responsible guidelines to increase detection of lung cancer, which may include small groups with elevated risk for reasons other than tobacco exposure.
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Affiliation(s)
- Francine L Jacobson
- Departments of Radiology and Thoracic Surgery, Brigham and Women's Hospital, Boston, MA 02115; ,
| | - Michael T Jaklitsch
- Departments of Radiology and Thoracic Surgery, Brigham and Women's Hospital, Boston, MA 02115; ,
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Trinidad López C, Delgado Sánchez-Gracián C, Utrera Pérez E, Jurado Basildo C, Sepúlveda Villegas C. Incidental pulmonary nodules: Characterization and management. RADIOLOGIA 2019. [DOI: 10.1016/j.rxeng.2019.06.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Ludwig M, Chipon E, Cohen J, Reymond E, Medici M, Cole A, Moreau Gaudry A, Ferretti G. Detection of pulmonary nodules: a clinical study protocol to compare ultra-low dose chest CT and standard low-dose CT using ASIR-V. BMJ Open 2019; 9:e025661. [PMID: 31420379 PMCID: PMC6701577 DOI: 10.1136/bmjopen-2018-025661] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
INTRODUCTION Lung cancer screening in individuals at risk has been recommended by various scientific institutions. One of the main concerns for CT screening is repeated radiation exposure, with the risk of inducing malignancies in healthy individuals. Therefore, lowering the radiation dose is one of the main objectives for radiologists. The aim of this study is to demonstrate that an ultra-low dose (ULD) chest CT protocol, using recently introduced hybrid iterative reconstruction (ASiR-V, GE medical Healthcare, Milwaukee, Wisconsin, USA), is as performant as a standard 'low dose' (LD) CT to detect non-calcified lung nodules ≥4 mm. METHODS AND ANALYSIS The total number of patients to include is 150. Those are referred for non-enhanced chest CT for detection or follow-up of lung nodule and will undergo an additional unenhanced ULD CT acquisition, the dose of which is on average 10 times lower than the conventional LD acquisition. Total dose of the entire exam (LD+ULD) is lower than the French diagnostic reference level for a chest CT (6.65 millisievert). ULD CT images will be reconstructed with 50% and 100% ASiR-V and LD CT with 50%. The three sets of images will be read in random order by two pair of radiologists, in a blind test, where patient identification and study outcomes are concealed. Detection rate (sensitivity) is the primary outcome. Secondary outcomes will include concordance of nodule characteristics; interobserver reproducibility; influence of subjects' characteristics, nodule location and nodule size; and concordance of emphysema, coronary calcifications evaluated by visual scoring and bronchial alterations between LD and ULD CT. In case of discordance, a third radiologist will arbitrate. ETHICS AND DISSEMINATION The study was approved by the relevant ethical committee. Each study participant will sign an informed consent form. TRIAL REGISTRATION NUMBER NCT03305978; Pre-results.
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Affiliation(s)
- Marie Ludwig
- Service de radiologie et imagerie médicale, pôle imagerie, Centre Hospitalier Universitaire Grenoble Alpes, Grenoble, France
- Faculte de Medecine, Universite Grenoble Alpes, La Tronche, France
| | - Emilie Chipon
- CIC 1406, INSERM, Grenoble, France
- Pôle recherche, Centre Hospitalier Universitaire Grenoble Alpes, Grenoble, France
| | - Julien Cohen
- Service de radiologie et imagerie médicale, pôle imagerie, Centre Hospitalier Universitaire Grenoble Alpes, Grenoble, France
- Faculte de Medecine, Universite Grenoble Alpes, La Tronche, France
| | - Emilie Reymond
- Service de radiologie et imagerie médicale, pôle imagerie, Centre Hospitalier Universitaire Grenoble Alpes, Grenoble, France
| | - Maud Medici
- CIC 1406, INSERM, Grenoble, France
- Pôle recherche, Centre Hospitalier Universitaire Grenoble Alpes, Grenoble, France
| | - Anthony Cole
- Service de radiologie et imagerie médicale, pôle imagerie, Centre Hospitalier Universitaire Grenoble Alpes, Grenoble, France
- Faculte de Medecine, Universite Grenoble Alpes, La Tronche, France
| | - Alexandre Moreau Gaudry
- CIC 1406, INSERM, Grenoble, France
- Pôle recherche, Centre Hospitalier Universitaire Grenoble Alpes, Grenoble, France
| | - Gilbert Ferretti
- Service de radiologie et imagerie médicale, pôle imagerie, Centre Hospitalier Universitaire Grenoble Alpes, Grenoble, France
- Faculte de Medecine, Universite Grenoble Alpes, La Tronche, France
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Golia Pernicka JS, Hayes SA, Schor-Bardach R, Sharma R, Zheng J, Moskowitz C, Ginsberg MS. Clinical significance of perifissural nodules in the oncologic population. Clin Imaging 2019; 57:110-114. [PMID: 31207563 DOI: 10.1016/j.clinimag.2019.05.017] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Revised: 04/18/2019] [Accepted: 05/30/2019] [Indexed: 12/12/2022]
Abstract
PURPOSE To evaluate for stability of perifissural nodules (PFNs) in a dedicated oncologic population. METHODS A retrospective review of 500 computed tomography (CT) chests from oncologic patients at our tertiary care cancer center with at least a three year follow up yielded 76 patients with PFNs. Patients with metastases on baseline CT chest were excluded (n = 14) as the presence of a PFN would not be clinically relevant, thus our final patient cohort was 62 patients with a total of 112 PFNs. PFN features, clinical features, and ancillary information was recorded from the CT and the electronic medical record for all patients. The two patient cohorts-stable or decreased PFN vs. increased PFN-were then compared. RESULTS 112 PFNs were examined in 62 patients with a median follow up interval of 5.7 years. Of 62 patients, 59 (95.2%, 95% CI: 86.5, 99.0) had decreased/stable PFNs on follow up scan (median follow up 5.6 years) and 3 (4.8%, 95% CI: 1.0, 13.5%) had enlarged PFNs (median follow up 6.3 years). None of the PFN features, clinical features, nor ancillary information from the CT proved to be statistically significant. CONCLUSIONS Despite the lack of statistically significant distinguishing features to predict growth, our results are reassuring, since the majority of PFNs in our oncology patients were decreased or unchanged in size which is comparable to previously published data on PFNs in non-oncologic patients. Thus, we can similarly presume these nodules are most likely benign and can provide reassurance to our oncologic colleagues and our patients. Larger studies are warranted to further evaluate PFNs in the oncologic population which also examines the nodules by cancer type.
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Affiliation(s)
| | - Sara A Hayes
- Departments of Radiology, Cancer Center, New York, NY, United States of America
| | | | - Richa Sharma
- Departments of Radiology, Cancer Center, New York, NY, United States of America
| | - Junting Zheng
- Epidemiology & Biostatistics, Memorial Sloan Kettering, Cancer Center, New York, NY, United States of America
| | - Chaya Moskowitz
- Epidemiology & Biostatistics, Memorial Sloan Kettering, Cancer Center, New York, NY, United States of America
| | - Michelle S Ginsberg
- Departments of Radiology, Cancer Center, New York, NY, United States of America
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Trinidad López C, Delgado Sánchez-Gracián C, Utrera Pérez E, Jurado Basildo C, Sepúlveda Villegas CA. Incidental pulmonary nodules: characterization and management. RADIOLOGIA 2019; 61:357-369. [PMID: 31072604 DOI: 10.1016/j.rx.2019.03.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2018] [Revised: 03/14/2019] [Accepted: 03/22/2019] [Indexed: 12/17/2022]
Abstract
This update covers the management of solitary or multiple pulmonary nodules detected incidentally in imaging studies done for other reasons. It describes the most appropriate computed tomography technique for the evaluation of these nodules, how they are classified, and how the different types of nodules are measured. It also reviews the patient-related and nodule-related criteria for determining the risk of malignancy. It discusses the recommendations in the guidelines recently published by the Fleischner Society for the management and follow-up of each type of nodules according to its size and risk of malignancy.
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Affiliation(s)
- C Trinidad López
- Departamento de Radiodiagnóstico, Hospital POVISA, Vigo, Pontevedra, España.
| | | | - E Utrera Pérez
- Departamento de Radiodiagnóstico, Hospital POVISA, Vigo, Pontevedra, España
| | - C Jurado Basildo
- Departamento de Radiodiagnóstico, Hospital POVISA, Vigo, Pontevedra, España
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Black WC. The Complementary Roles of the Vancouver Risk Calculator and Lung-RADS in Lung Cancer Screening. Radiology 2019; 291:212-213. [DOI: 10.1148/radiol.2019182891] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- William C. Black
- From the Department of Radiology, Dartmouth-Hitchcock Medical Center, One Medical Center Dr, Lebanon, NH 03756
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Cheng YI, Davies MPA, Liu D, Li W, Field JK. Implementation planning for lung cancer screening in China. PRECISION CLINICAL MEDICINE 2019; 2:13-44. [PMID: 35694700 PMCID: PMC8985785 DOI: 10.1093/pcmedi/pbz002] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Revised: 12/19/2018] [Accepted: 12/24/2018] [Indexed: 02/05/2023] Open
Abstract
Lung cancer is the leading cause of cancer-related deaths in China, with over 690 000 lung cancer deaths estimated in 2018. The mortality has increased about five-fold from the mid-1970s to the 2000s. Lung cancer low-dose computerized tomography (LDCT) screening in smokers was shown to improve survival in the US National Lung Screening Trial, and more recently in the European NELSON trial. However, although the predominant risk factor, smoking contributes to a lower fraction of lung cancers in China than in the UK and USA. Therefore, it is necessary to establish Chinese-specific screening strategies. There have been 23 associated programmes completed or still ongoing in China since the 1980s, mainly after 2000; and one has recently been planned. Generally, their entry criteria are not smoking-stringent. Most of the Chinese programmes have reported preliminary results only, which demonstrated a different high-risk subpopulation of lung cancer in China. Evidence concerning LDCT screening implementation is based on results of randomized controlled trials outside China. LDCT screening programmes combining tobacco control would produce more benefits. Population recruitment (e.g. risk-based selection), screening protocol, nodule management and cost-effectiveness are discussed in detail. In China, the high-risk subpopulation eligible for lung cancer screening has not as yet been confirmed, as all the risk parameters have not as yet been determined. Although evidence on best practice for implementation of lung cancer screening has been accumulating in other countries, further research in China is urgently required, as China is now facing a lung cancer epidemic.
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Affiliation(s)
- Yue I Cheng
- Lung Cancer Research Group, Department of Molecular and Clinical Cancer Medicine, Institute of Translational Medicine, University of Liverpool, William Henry Duncan Building, 6 West Derby Street, Liverpool, United Kingdom
| | - Michael P A Davies
- Lung Cancer Research Group, Department of Molecular and Clinical Cancer Medicine, Institute of Translational Medicine, University of Liverpool, William Henry Duncan Building, 6 West Derby Street, Liverpool, United Kingdom
| | - Dan Liu
- Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Weimin Li
- Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - John K Field
- Lung Cancer Research Group, Department of Molecular and Clinical Cancer Medicine, Institute of Translational Medicine, University of Liverpool, William Henry Duncan Building, 6 West Derby Street, Liverpool, United Kingdom
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Loverdos K, Fotiadis A, Kontogianni C, Iliopoulou M, Gaga M. Lung nodules: A comprehensive review on current approach and management. Ann Thorac Med 2019; 14:226-238. [PMID: 31620206 PMCID: PMC6784443 DOI: 10.4103/atm.atm_110_19] [Citation(s) in RCA: 77] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
In daily clinical practice, radiologists and pulmonologists are faced with incidental radiographic findings of pulmonary nodules. Deciding how to manage these findings is very important as many of them may be benign and require no further action, but others may represent early disease and importantly early-stage lung cancer and require prompt diagnosis and definitive treatment. As the diagnosis of pulmonary nodules includes invasive procedures which can be relatively minimal, such as bronchoscopy or transthoracic aspiration or biopsy, but also more invasive procedures such as thoracic surgical biopsies, and as these procedures are linked to anxiety and to cost, it is important to have clearly defined algorithms for the description, management, and follow-up of these nodules. Clear algorithms for the imaging protocols and the management of positive findings should also exist in lung cancer screening programs, which are already established in the USA and which will hopefully be established worldwide. This article reviews current knowledge on nodule definition, diagnostic evaluation, and management based on literature data and mainly recent guidelines.
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Affiliation(s)
| | - Andreas Fotiadis
- 7th Respiratory Medicine Department, Athens Chest Hospital, Athens, Greece
| | | | | | - Mina Gaga
- 7th Respiratory Medicine Department, Athens Chest Hospital, Athens, Greece
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42
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Tammemagi M, Ritchie AJ, Atkar-Khattra S, Dougherty B, Sanghera C, Mayo JR, Yuan R, Manos D, McWilliams AM, Schmidt H, Gingras M, Pasian S, Stewart L, Tsai S, Seely JM, Burrowes P, Bhatia R, Haider EA, Boylan C, Jacobs C, van Ginneken B, Tsao MS, Lam S. Predicting Malignancy Risk of Screen-Detected Lung Nodules-Mean Diameter or Volume. J Thorac Oncol 2018; 14:203-211. [PMID: 30368011 DOI: 10.1016/j.jtho.2018.10.006] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2018] [Revised: 10/07/2018] [Accepted: 10/09/2018] [Indexed: 11/29/2022]
Abstract
OBJECTIVE In lung cancer screening practice low-dose computed tomography, diameter, and volumetric measurement have been used in the management of screen-detected lung nodules. The aim of this study was to compare the performance of nodule malignancy risk prediction tools using diameter or volume and between computer-aided detection (CAD) and radiologist measurements. METHODS Multivariable logistic regression models were prepared by using data from two multicenter lung cancer screening trials. For model development and validation, baseline low-dose computed tomography scans from the Pan-Canadian Early Detection of Lung Cancer Study and a subset of National Lung Screening Trial (NLST) scans with lung nodules 3 mm or more in mean diameter were analyzed by using the CIRRUS Lung Screening Workstation (Radboud University Medical Center, Nijmegen, the Netherlands). In the NLST sample, nodules with cancer had been matched on the basis of size to nodules without cancer. RESULTS Both CAD-based mean diameter and volume models showed excellent discrimination and calibration, with similar areas under the receiver operating characteristic curves of 0.947. The two CAD models had predictive performance similar to that of the radiologist-based model. In the NLST validation data, the CAD mean diameter and volume models also demonstrated excellent discrimination: areas under the curve of 0.810 and 0.821, respectively. These performance statistics are similar to those of the Pan-Canadian Early Detection of Lung Cancer Study malignancy probability model with use of these data and radiologist-measured maximum diameter. CONCLUSION Either CAD-based nodule diameter or volume can be used to assist in predicting a nodule's malignancy risk.
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Affiliation(s)
- Martin Tammemagi
- Department of Health Sciences, Brock University, St. Catharine's, Ontario, Canada
| | - Alex J Ritchie
- Royal Brisbane and Women's Hospital, Brisbane, Australia
| | | | | | - Calvin Sanghera
- British Columbia Cancer, Vancouver, British Columbia, Canada
| | - John R Mayo
- Department of Radiology, Vancouver Coastal Health, Vancouver, British Columbia, Canada
| | - Ren Yuan
- British Columbia Cancer, Vancouver, British Columbia, Canada
| | - Daria Manos
- Dalhousie University, Halifax, Nova Scotia, Canada
| | - Annette M McWilliams
- Fiona Stanley Hospital and Sir Charles Gairdner Hospital, Perth, Western Australia, Australia
| | - Heidi Schmidt
- University Health Network and Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Michel Gingras
- University Institute of Cardiology and Pneumology of Quebec, Quebec, Canada
| | - Sergio Pasian
- University Institute of Cardiology and Pneumology of Quebec, Quebec, Canada
| | - Lori Stewart
- Department of Diagnostic Imaging, Henderson Hospital, Hamilton, Ontario, Canada
| | - Scott Tsai
- Department of Diagnostic Imaging, Henderson Hospital, Hamilton, Ontario, Canada
| | - Jean M Seely
- Ottawa Hospital Research Institute and the University of Ottawa, Ottawa, Ontario, Canada
| | - Paul Burrowes
- University of Calgary, Foothills Medical Centre, Calgary, Alberta, Canada
| | - Rick Bhatia
- Memorial University, St. John's, Newfoundland, Canada
| | - Ehsan A Haider
- Department of Diagnostic Imaging, Henderson Hospital, Hamilton, Ontario, Canada
| | - Colm Boylan
- Department of Diagnostic Imaging, Henderson Hospital, Hamilton, Ontario, Canada
| | - Colin Jacobs
- Radboud University Medical Center, Nijmegen, The Netherlands
| | | | - Ming-Sound Tsao
- University Health Network and Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Stephen Lam
- British Columbia Cancer, Vancouver, British Columbia, Canada.
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Schreuder A, van Ginneken B, Scholten ET, Jacobs C, Prokop M, Sverzellati N, Desai SR, Devaraj A, Schaefer-Prokop CM. Classification of CT Pulmonary Opacities as Perifissural Nodules: Reader Variability. Radiology 2018; 288:867-875. [DOI: 10.1148/radiol.2018172771] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
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Sánchez M, Benegas M, Vollmer I. Management of incidental lung nodules <8 mm in diameter. J Thorac Dis 2018; 10:S2611-S2627. [PMID: 30345098 DOI: 10.21037/jtd.2018.05.86] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Due to the increase of incidentally detected pulmonary nodules and the information obtained from several screening programs, updated guidelines with new recommendations for the management of small pulmonary nodules have been proposed. These international guidelines coincide in proposing periodic follow-up for small nodules, less than 8 mm of diameter. Fleischner and British Thoracic Society guidelines are the most recent and popular guidelines for incidental pulmonary nodules management. They have specific recommendations according to nodule characteristics (density and size) and cancer risk of the patient. Both guidelines separate recommendations for solid and subsolid nodules. Predictive risk models have been developed to improve the nodule management. In certain cases follow up may not be the best option. We discuss the scenarios and options to achieve a histologic diagnosis of these tiny pulmonary nodules.
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Affiliation(s)
- Marcelo Sánchez
- Radiology Department, Diagnostic Imaging Center, Hospital Clínic Barcelona, University of Barcelona, Barcelona, Spain
| | - Mariana Benegas
- Radiology Department, Diagnostic Imaging Center, Hospital Clínic Barcelona, University of Barcelona, Barcelona, Spain
| | - Ivan Vollmer
- Radiology Department, Diagnostic Imaging Center, Hospital Clínic Barcelona, University of Barcelona, Barcelona, Spain
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45
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Affiliation(s)
- Jin Mo Goo
- From the Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, 101 Daehak-ro, Jongno-gu, Seoul 110-744, Korea
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46
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Nair A, Devaraj A, Callister MEJ, Baldwin DR. The Fleischner Society 2017 and British Thoracic Society 2015 guidelines for managing pulmonary nodules: keep calm and carry on. Thorax 2018. [DOI: 10.1136/thoraxjnl-2018-211764] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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47
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Vlahos I, Stefanidis K, Sheard S, Nair A, Sayer C, Moser J. Lung cancer screening: nodule identification and characterization. Transl Lung Cancer Res 2018; 7:288-303. [PMID: 30050767 DOI: 10.21037/tlcr.2018.05.02] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The accurate identification and characterization of small pulmonary nodules at low-dose CT is an essential requirement for the implementation of effective lung cancer screening. Individual reader detection performance is influenced by nodule characteristics and technical CT parameters but can be improved by training, the application of CT techniques, and by computer-aided techniques. However, the evaluation of nodule detection in lung cancer screening trials differs from the assessment of individual readers as it incorporates multiple readers, their inter-observer variability, reporting thresholds, and reflects the program accuracy in identifying lung cancer. Understanding detection and interpretation errors in screening trials aids in the implementation of lung cancer screening in clinical practice. Indeed, as CT screening moves to ever lower radiation doses, radiologists must be cognisant of new technical challenges in nodule assessment. Screen detected lung cancers demonstrate distinct morphological features from incidentally or symptomatically detected lung cancers. Hence characterization of screen detected nodules requires an awareness of emerging concepts in early lung cancer appearances and their impact on radiological assessment and malignancy prediction models. Ultimately many nodules remain indeterminate, but further imaging evaluation can be appropriate with judicious utilization of contrast enhanced CT or MRI techniques or functional evaluation by PET-CT.
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Affiliation(s)
- Ioannis Vlahos
- St George's NHS Foundation Hospitals Trust and School of Medicine, London, UK
| | | | | | - Arjun Nair
- Guy's and St Thomas' Hospital NHS Foundation Trust, London, UK
| | - Charles Sayer
- Brighton and Sussex University Hospitals Trust, Haywards Heath, UK
| | - Joanne Moser
- St George's NHS Foundation Hospitals Trust and School of Medicine, London, UK
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48
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49
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Godoy MCB, Odisio EGLC, Truong MT, de Groot PM, Shroff GS, Erasmus JJ. Pulmonary Nodule Management in Lung Cancer Screening: A Pictorial Review of Lung-RADS Version 1.0. Radiol Clin North Am 2018; 56:353-363. [PMID: 29622071 DOI: 10.1016/j.rcl.2018.01.003] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The number of screening-detected lung nodules is expected to increase as low-dose computed tomography screening is implemented nationally. Standardized guidelines for image acquisition, interpretation, and screen-detected nodule workup are essential to ensure a high standard of medical care and that lung cancer screening is implemented safely and cost effectively. In this article, we review the current guidelines for pulmonary nodule management in the lung cancer screening setting.
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Affiliation(s)
- Myrna C B Godoy
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Unit 371, Houston, TX 77030, USA.
| | - Erika G L C Odisio
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Unit 371, Houston, TX 77030, USA
| | - Mylene T Truong
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Unit 371, Houston, TX 77030, USA
| | - Patricia M de Groot
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Unit 371, Houston, TX 77030, USA
| | - Girish S Shroff
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Unit 371, Houston, TX 77030, USA
| | - Jeremy J Erasmus
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Unit 371, Houston, TX 77030, USA
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50
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Abstract
The incidental pulmonary nodule is commonly encountered when interpreting chest CTs. The management of pulmonary nodules requires a multidisciplinary approach entailing integration of nodule size and features, clinical risk factors, and patient preference and comorbidities. Guidelines have been issued for the management of both solid and subsolid nodules, with the Fleischner Society issuing revised guidelines in 2017. This article focuses on the CT imaging characteristics and clinical behavior of pulmonary nodules, with review of the current management guidelines that reflect this knowledge.
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Affiliation(s)
- Jane P Ko
- Department of Radiology, NYU Langone Health, New York, NY.
| | - Lea Azour
- Department of Radiology, NYU Langone Health, New York, NY
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