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Geppert J, Asgharzadeh A, Brown A, Stinton C, Helm EJ, Jayakody S, Todkill D, Gallacher D, Ghiasvand H, Patel M, Auguste P, Tsertsvadze A, Chen YF, Grove A, Shinkins B, Clarke A, Taylor-Phillips S. Software using artificial intelligence for nodule and cancer detection in CT lung cancer screening: systematic review of test accuracy studies. Thorax 2024:thorax-2024-221662. [PMID: 39322406 DOI: 10.1136/thorax-2024-221662] [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: 03/08/2024] [Accepted: 09/04/2024] [Indexed: 09/27/2024]
Abstract
OBJECTIVES To examine the accuracy and impact of artificial intelligence (AI) software assistance in lung cancer screening using CT. METHODS A systematic review of CE-marked, AI-based software for automated detection and analysis of nodules in CT lung cancer screening was conducted. Multiple databases including Medline, Embase and Cochrane CENTRAL were searched from 2012 to March 2023. Primary research reporting test accuracy or impact on reading time or clinical management was included. QUADAS-2 and QUADAS-C were used to assess risk of bias. We undertook narrative synthesis. RESULTS Eleven studies evaluating six different AI-based software and reporting on 19 770 patients were eligible. All were at high risk of bias with multiple applicability concerns. Compared with unaided reading, AI-assisted reading was faster and generally improved sensitivity (+5% to +20% for detecting/categorising actionable nodules; +3% to +15% for detecting/categorising malignant nodules), with lower specificity (-7% to -3% for correctly detecting/categorising people without actionable nodules; -8% to -6% for correctly detecting/categorising people without malignant nodules). AI assistance tended to increase the proportion of nodules allocated to higher risk categories. Assuming 0.5% cancer prevalence, these results would translate into additional 150-750 cancers detected per million people attending screening but lead to an additional 59 700 to 79 600 people attending screening without cancer receiving unnecessary CT surveillance. CONCLUSIONS AI assistance in lung cancer screening may improve sensitivity but increases the number of false-positive results and unnecessary surveillance. Future research needs to increase the specificity of AI-assisted reading and minimise risk of bias and applicability concerns through improved study design. PROSPERO REGISTRATION NUMBER CRD42021298449.
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Affiliation(s)
- Julia Geppert
- Warwick Screening & Warwick Evidence, Warwick Medical School, University of Warwick, Coventry, UK
| | - Asra Asgharzadeh
- Population Health Science, University of Bristol, Bristol, UK
- Warwick Evidence, Warwick Medical School, University of Warwick, Coventry, UK
| | - Anna Brown
- Warwick Evidence, Warwick Medical School, University of Warwick, Coventry, UK
| | - Chris Stinton
- Warwick Screening & Warwick Evidence, Warwick Medical School, University of Warwick, Coventry, UK
| | - Emma J Helm
- Department of Radiology, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UK
| | - Surangi Jayakody
- Warwick Evidence, Warwick Medical School, University of Warwick, Coventry, UK
| | - Daniel Todkill
- Warwick Evidence, Warwick Medical School, University of Warwick, Coventry, UK
| | - Daniel Gallacher
- Warwick Evidence, Warwick Medical School, University of Warwick, Coventry, UK
| | - Hesam Ghiasvand
- Warwick Evidence, Warwick Medical School, University of Warwick, Coventry, UK
- Research Centre for Healthcare and Communities, Coventry University, Coventry, UK
| | - Mubarak Patel
- Warwick Evidence, Warwick Medical School, University of Warwick, Coventry, UK
| | - Peter Auguste
- Warwick Evidence, Warwick Medical School, University of Warwick, Coventry, UK
| | | | - Yen-Fu Chen
- Warwick Evidence, Warwick Medical School, University of Warwick, Coventry, UK
| | - Amy Grove
- Warwick Evidence, Warwick Medical School, University of Warwick, Coventry, UK
| | - Bethany Shinkins
- Warwick Screening & Warwick Evidence, Warwick Medical School, University of Warwick, Coventry, UK
| | - Aileen Clarke
- Warwick Evidence, Warwick Medical School, University of Warwick, Coventry, UK
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Bidzińska J, Szurowska E. See Lung Cancer with an AI. Cancers (Basel) 2023; 15:1321. [PMID: 36831662 PMCID: PMC9954317 DOI: 10.3390/cancers15041321] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 02/13/2023] [Accepted: 02/17/2023] [Indexed: 02/22/2023] Open
Abstract
A lot has happened in the field of lung cancer screening in recent months. The ongoing discussion and documentation published by the scientific community and policymakers are of great importance to the entire European community and perhaps beyond. Lung cancer is the main worldwide killer. Low-dose computed tomography-based screening, together with smoking cessation, is the only tool to fight lung cancer, as it has already been proven in the United States of America but also European randomized controlled trials. Screening requires a lot of well-organized specialized work, but it can be supported by artificial intelligence (AI). Here we discuss whether and how to use AI for patients, radiologists, pulmonologists, thoracic surgeons, and all hospital staff supporting screening process benefits.
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Affiliation(s)
- Joanna Bidzińska
- Second Department of Radiology, Medical University of Gdansk, 80-210 Gdańsk, Poland
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3
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Single CT Appointment for Double Lung and Colorectal Cancer Screening: Is the Time Ripe? Diagnostics (Basel) 2022; 12:diagnostics12102326. [PMID: 36292015 PMCID: PMC9601268 DOI: 10.3390/diagnostics12102326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Revised: 09/15/2022] [Accepted: 09/21/2022] [Indexed: 12/24/2022] Open
Abstract
Annual screening of lung cancer (LC) with chest low-dose computed tomography (CT) and screening of colorectal cancer (CRC) with CT colonography every 5 years are recommended by the United States Prevention Service Task Force. We review epidemiological and pathological data on LC and CRC, and the features of screening chest low-dose CT and CT colonography comprising execution, reading, radiation exposure and harm, and the cost effectiveness of the two CT screening interventions. The possibility of combining chest low-dose CT and CT colonography examinations for double LC and CRC screening in a single CT appointment is then addressed. We demonstrate how this approach appears feasible and is already reasonable as an opportunistic screening intervention in 50–75-year-old subjects with smoking history and average CRC risk. In addition to the crucial role Computer Assisted Diagnosis systems play in decreasing the test reading times and the need to educate radiologists in screening chest LDCT and CT colonography, in view of a single CT appointment for double screening, the following uncertainties need to be solved: (1) the schedule of the screening CT; (2) the effectiveness of iterative reconstruction and deep learning algorithms affording an ultra-low-dose CT acquisition technique and (3) management of incidental findings. Resolving these issues will imply new cost-effectiveness analyses for LC screening with chest low dose CT and for CRC screening with CT colonography and, especially, for the double LC and CRC screening with a single-appointment CT.
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Lee JH, Hwang EJ, Lim WH, Goo JM. Determination of the optimum definition of growth evaluation for indeterminate pulmonary nodules detected in lung cancer screening. PLoS One 2022; 17:e0274583. [PMID: 36108077 PMCID: PMC9477274 DOI: 10.1371/journal.pone.0274583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 08/30/2022] [Indexed: 11/19/2022] Open
Abstract
Objective
To determine the optimum definition of growth for indeterminate pulmonary nodules detected in lung cancer screening.
Materials and methods
Individuals with indeterminate nodules as defined by volume of 50–500 mm3 (solid nodules) and solid component volume of 50–500 mm3 or average diameter of non-solid component ≥8 mm (part-solid nodules) on baseline lung cancer screening low-dose chest CT (LDCT) were included. The average diameters and volumes of the nodules were measured on baseline and follow-up LDCTs with semi-automated segmentation. Sensitivities and specificities for lung cancer diagnosis of nodule growth defined by a) percentage volume growth ≥25% (defined in the NELSON study); b) absolute diameter growth >1.5 mm (defined in the Lung-RADS version 1.1); and c) subjective decision by a radiologist were evaluated. Sensitivities and specificities of diagnostic referral based on various thresholds of volume doubling time (VDT) were also evaluated.
Results
Altogether, 115 nodules (one nodule per individual; 93 solid and 22 part-solid nodules; 105 men; median age, 68 years) were evaluated (median follow-up interval: 201 days; interquartile range: 127–371 days). Percentage volume growth ≥25% exhibited higher sensitivity but lower specificity than those of diametrical measurement compared to absolute diameter growth >1.5 mm (sensitivity, 69.2% vs. 42.3%, p = 0.023; specificity, 82.0% vs. 96.6%, p = 0.002). The radiologist had an equivalent sensitivity (53.9%; p = 0.289) but higher specificity (98.9%; p = 0.002) compared to those of volume growth, but did not differ from those of diameter growth (p>0.05 both in sensitivity and specificity). Compared to the VDT threshold of 600 days (sensitivity, 61.5%; specificity, 87.6%), VDT thresholds ≤200 and ≤300 days exhibited significantly lower sensitivity (30.8%, p = 0.013) and higher specificity (94.4%, p = 0.041), respectively.
Conclusion
Growth evaluation of screening-detected indeterminate nodules with volumetric measurement exhibited higher sensitivity but lower specificity compared to diametric measurements.
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Affiliation(s)
- Jong Hyuk Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
- Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea
- Cancer Research Institute, Seoul National University, Seoul, Korea
| | - Eui Jin Hwang
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
- Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea
- Cancer Research Institute, Seoul National University, Seoul, Korea
- * E-mail:
| | - Woo Hyeon Lim
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Jin Mo Goo
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
- Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea
- Cancer Research Institute, Seoul National University, Seoul, Korea
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5
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Silva M, Picozzi G, Sverzellati N, Anglesio S, Bartolucci M, Cavigli E, Deliperi A, Falchini M, Falaschi F, Ghio D, Gollini P, Larici AR, Marchianò AV, Palmucci S, Preda L, Romei C, Tessa C, Rampinelli C, Mascalchi M. Low-dose CT for lung cancer screening: position paper from the Italian college of thoracic radiology. LA RADIOLOGIA MEDICA 2022; 127:543-559. [PMID: 35306638 PMCID: PMC8934407 DOI: 10.1007/s11547-022-01471-y] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Accepted: 02/18/2022] [Indexed: 12/24/2022]
Abstract
Smoking is the main risk factor for lung cancer (LC), which is the leading cause of cancer-related death worldwide. Independent randomized controlled trials, governmental and inter-governmental task forces, and meta-analyses established that LC screening (LCS) with chest low dose computed tomography (LDCT) decreases the mortality of LC in smokers and former smokers, compared to no-screening, especially in women. Accordingly, several Italian initiatives are offering LCS by LDCT and smoking cessation to about 10,000 high-risk subjects, supported by Private or Public Health Institutions, envisaging a possible population-based screening program. Because LDCT is the backbone of LCS, Italian radiologists with LCS expertise are presenting this position paper that encompasses recommendations for LDCT scan protocol and its reading. Moreover, fundamentals for classification of lung nodules and other findings at LDCT test are detailed along with international guidelines, from the European Society of Thoracic Imaging, the British Thoracic Society, and the American College of Radiology, for their reporting and management in LCS. The Italian College of Thoracic Radiologists produced this document to provide the basics for radiologists who plan to set up or to be involved in LCS, thus fostering homogenous evidence-based approach to the LDCT test over the Italian territory and warrant comparison and analyses throughout National and International practices.
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Affiliation(s)
- Mario Silva
- Department of Medicine and Surgery (DiMeC), University of Parma, Via Gramsci 14, Parma, Italy.
- Unit of "Scienze Radiologiche", University Hospital of Parma, Pad. Barbieri, Via Gramsci 14, 43126, Parma, Italy.
| | - Giulia Picozzi
- Istituto Di Studio Prevenzione E Rete Oncologica, Firenze, Italy
| | - Nicola Sverzellati
- Department of Medicine and Surgery (DiMeC), University of Parma, Via Gramsci 14, Parma, Italy
- Unit of "Scienze Radiologiche", University Hospital of Parma, Pad. Barbieri, Via Gramsci 14, 43126, Parma, Italy
| | | | | | | | | | | | | | - Domenico Ghio
- IRCCS San Raffaele Scientific Institute, Milan, Italy
| | | | - Anna Rita Larici
- Dipartimento Di Diagnostica Per Immagini, Radioterapia Oncologica ed Ematologia, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Università Cattolica del Sacro Cuore Di Roma, Roma, Italy
| | - Alfonso V Marchianò
- Department of Radiology, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, MI, Italy
| | - Stefano Palmucci
- UOC Radiologia 1, Dipartimento Scienze Mediche Chirurgiche E Tecnologie Avanzate "GF Ingrassia", Università Di Catania, AOU Policlinico "G. Rodolico-San Marco", Catania, Italy
| | - Lorenzo Preda
- IRCCS Fondazione Policlinico San Matteo, Pavia, Italy
- Dipartimento Di Scienze Clinico-Chirurgiche, Diagnostiche E Pediatriche, Università Degli Studi Di Pavia, Pavia, Italy
| | | | - Carlo Tessa
- Radiologia Apuane E Lunigiana, Azienda USL Toscana Nord Ovest, Pisa, Italy
| | | | - Mario Mascalchi
- Istituto Di Studio Prevenzione E Rete Oncologica, Firenze, Italy
- Università Di Firenze, Firenze, Italy
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Community-based Lung Cancer Screening Results in Relation to Patient and Radiologist Characteristics: The PROSPR Consortium. Ann Am Thorac Soc 2022; 19:433-441. [PMID: 34543590 PMCID: PMC8937226 DOI: 10.1513/annalsats.202011-1413oc] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Rationale: Lung-RADS classification was developed to standardize reporting and management of lung cancer screening using low-dose computed tomographic (LDCT) imaging. Although variation in Lung-RADS distribution between healthcare systems has been reported, it is unclear if this is explained by patient characteristics, radiologist experience with lung cancer screening, or other factors. Objectives: Our objective was to determine if patient or radiologist factors are associated with Lung-RADS score. Methods: In the Population-based Research to Optimize the Screening Process (PROSPR) Lung consortium, we conducted a study of patients who received their first screening LDCT imaging at one of the five healthcare systems in the PROSPR Lung Research Center from May 1, 2014, through December 31, 2017. Data on LDCT scans, patient factors, and radiologist characteristics were obtained via electronic health records. LDCT scan findings were categorized using Lung-RADS (negative [1], benign [2], probably benign [3], or suspicious [4]). We used generalized estimating equations with a multinomial distribution to compare the odds of Lung-RADS 3, and separately Lung-RADS 4, versus Lung-RADS 1 or 2 and estimated adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between Lung-RADS assignment and patient and radiologist characteristics. Results: Analyses included 8,556 patients; 24% were assigned Lung-RADS 1, 60% Lung-RADS 2, 10% Lung-RADS 3, and 5% Lung-RADS 4. Age was positively associated with Lung-RADS 3 (OR, 1.02; 95% CI, 1.01-1.03) and 4 (OR, 1.03; 95% CI, 1.01-1.05); chronic obstructive pulmonary disease (COPD) was positively associated with Lung-RADS 4 (OR, 1.78; 95% CI, 1.45-2.20); obesity was inversely associated with Lung-RADS 3 (OR, 0.70; 95% CI, 0.58-0.84) and 4 (OR, 0.58; 95% CI, 0.45-0.75). There was no association between sex, race, ethnicity, education, or smoking status and Lung-RADS assignment. Radiologist volume of interpreting screening LDCT scans, years in practice, and thoracic specialty were also not associated with Lung-RADS assignment. Conclusions: Healthcare systems that are comprised of patients with an older age distribution or higher levels of COPD will have a greater proportion of screening LDCT scans with Lung-RADS 3 or 4 findings and should plan for additional resources to support appropriate and timely management of noted positive findings.
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Zarogoulidis P, Petridis D, Huang H, Bai C, Hohenforst-Schmidt W, Freitag L, Baka S, Drougas D, Vagionas A, Tsakiridis K, Turner JF, Hatzibougias D, Boukovinas I, Zaric B, Kovacevic T, Ioannidis A, Courcoutsakis N, Matthaios D, Sardeli C. Biopsy and re-biopsy for PD-L1 expression in NSCLC. association between PD-L1 and checkpoint inhibitor efficacy through treatment in NSCLC. A pilot study. Expert Rev Respir Med 2021; 15:1483-1491. [PMID: 34591723 DOI: 10.1080/17476348.2021.1987888] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
INTRODUCTION Lung cancer is diagnosed at a late stage due to lack of early disease symptoms. Therefore an efficient treatment is necessary for prolonged disease free survival. PATIENTS AND METHODS In our study we recruited 124 patients NSCLC patients with adenocarcinoma and squamus cell carcinoma. All recuited patients had Programmed death-ligand 1 expression ≥50 (PD-L1)with DAKO technique. Immunotherapy was administered with as first line treatment. Re-biopsies were performed in the main lung lesion every 4 months with the restaging of the patient and also in the metastastic sites in other organs that occurred during treatment. PD-L1 expressed was evaluated in the biopsies of the metastatic sites. RESULTS It appears thereafter that the PD-L1 expression could easily be claimed as a promising bio-index with a cutoff value 65, below which a negative prognosis of the disease progress will be evident and above that value a positive continuation of the disease will be prominent. CONCLUSION The findings of this study suggest that the PD-L1-65 index works adequately either concerning the neo-metastatic sites or the patient disease responses. Re-biopsies in new metastastic sites are necessary since we probably have a new cancer and chemotherapy should be added. More studies should confirm are results and change the NSCLC treatment approach of these patients.
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Affiliation(s)
- Paul Zarogoulidis
- 3rd Department of Surgery, ``ahepa`` University Hospital, Aristotle University of Thessaloniki, Medical School, Thessaloniki, Greece.,Pulmonary Oncology Department, ``Bioclinic`` Private Hospital, Thessaloniki, Greece
| | - Dimitris Petridis
- Department of Food Technology, School of Food Technology and Nutrition, Alexander Technological Educational Institute, Thessaloniki, Greece
| | - Haidong Huang
- Department of Respiratory & Critical Care Medicine, Changhai Hospital, the Second Military Medical University, Shanghai, China
| | - Chong Bai
- Department of Respiratory & Critical Care Medicine, Changhai Hospital, the Second Military Medical University, Shanghai, China
| | - Wolfgang Hohenforst-Schmidt
- Sana Clinic Group Franken, Department of Cardiology/Pulmonology/Intensive Care/Nephrology, "Hof" Clinics, University of Erlangen, Hof, Germany
| | - Lutz Freitag
- Department of Pulmonology, University Hospital Zurich, Zurich, Switzerland
| | - Sofia Baka
- Oncology Department, ``Interbalkan`` European Medical Center, Thessaloniki, Greece
| | - Dimitris Drougas
- Nuclear Medicine Department, ``Bioiatriki`` Private PET-CT Laboratory, Thessaloniki, Greece
| | | | - Kosmas Tsakiridis
- Thoracic Oncology Department, ``Interbalkan`` European Medical Center, Thessaloniki, Greece
| | - J Francis Turner
- Department of Medicine, University of Tennessee Graduate School of Medicine, Knoxville, USA
| | - Dimitris Hatzibougias
- Pulmonary department, Private Pathology Laboratory, "Microdiagnostics", Thessaloniki, Greece
| | - Ioannis Boukovinas
- Oncology Department, ``Bioclinic`` Private Hospital, Thessaloniki, Greece
| | - Bojan Zaric
- Faculty of Medicine, University of Novi Sad, Institute for Pulmonary Diseases of Vojvodina, Novi Sad, Serbia
| | - Tomi Kovacevic
- Faculty of Medicine, University of Novi Sad, Institute for Pulmonary Diseases of Vojvodina, Novi Sad, Serbia
| | - Aris Ioannidis
- Surgery Department, ``genesis`` Private HJospital, Thessaloniki, Greece
| | - Nikolaos Courcoutsakis
- Radiology Department, Democritus University of Thrace, University General Hospital of Alexandroupolis, Alexandroupolis, Greece
| | | | - Chrisanthi Sardeli
- Department of Pharmacology & Clinical Pharmacology, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
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8
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Kim H, Goo JM, Kim TJ, Kim HY, Gu G, Gil B, Kim W, Park SY, Park J, Park J, Park H, Song W, Shin KE, Oh J, Yoon SH, Lee S, Lee Y, Lim WH, Jeong WG, Jung JI, Cha MJ, Choi S, In Choi H, Ham SY, Kim Y. Effectiveness of radiologist training in improving reader agreement for Lung-RADS 4X categorization. Eur Radiol 2021; 31:8147-8159. [PMID: 33884472 DOI: 10.1007/s00330-021-07990-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Revised: 03/11/2021] [Accepted: 04/08/2021] [Indexed: 10/21/2022]
Abstract
OBJECTIVES To identify the agreement on Lung CT Screening Reporting and Data System 4X categorization between radiologists and an expert-adjudicated reference standard and to investigate whether training led to improvement of the agreement measures and diagnostic potential for lung cancer. METHODS Category 4 nodules in the Korean Lung Cancer Screening Project were identified retrospectively, and each 4X nodule was matched with one 4A or 4B nodule. An expert panel re-evaluated the categories and determined the reference standard. Nineteen radiologists were asked to determine the presence of CT features of malignancy and 4X categorization for each nodule. A review was performed in two sessions, and training material was given after session 1. Agreement on 4X categorization between radiologists and the expert-adjudicated reference standard and agreement between radiologist-assessed 4X categorization and lung cancer diagnosis were evaluated. RESULTS The 48 expert-adjudicated 4X nodules and 64 non-4X nodules were evenly distributed in each session. The proportion of category 4X decreased after training (56.4% ± 16.9% vs. 33.4% ± 8.0%; p < 0.001). Cohen's κ indicated poor agreement (0.39 ± 0.16) in session 1, but agreement improved in session 2 (0.47 ± 0.09; p = 0.03). The increase in agreement in session 2 was observed among inexperienced radiologists (p < 0.05), and experienced and inexperienced reviewers exhibited comparable agreement performance in session 2 (p > 0.05). All agreement measures between radiologist-assessed 4X categorization and lung cancer diagnosis increased in session 2 (p < 0.05). CONCLUSION Radiologist training can improve reader agreement on 4X categorization, leading to enhanced diagnostic performance for lung cancer. KEY POINTS • Agreement on 4X categorization between radiologists and an expert-adjudicated reference standard was initially poor, but improved significantly after training. • The mean proportion of 4X categorization by 19 radiologists decreased from 56.4% ± 16.9% in session 1 to 33.4% ± 8.0% in session 2. • All agreement measures between the 4X categorization and lung cancer diagnosis increased significantly in session 2, implying that appropriate training and guidance increased the diagnostic potential of category 4X.
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Affiliation(s)
- Hyungjin Kim
- Department of Radiology, Seoul National University College of Medicine, 101, Daehak-ro, Jongno-gu, Seoul, 03080, South Korea.,Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, South Korea
| | - Jin Mo Goo
- Department of Radiology, Seoul National University College of Medicine, 101, Daehak-ro, Jongno-gu, Seoul, 03080, South Korea. .,Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, South Korea. .,Cancer Research Institute, Seoul National University, Seoul, South Korea.
| | - Tae Jung Kim
- Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | | | - Guanmin Gu
- Pohang St. Mary's Hospital, Pohang, South Korea
| | - Bomi Gil
- Bucheon St. Mary's Hospital, The Catholic University of Korea, Seoul, South Korea
| | - Wooil Kim
- Asan Medical Center, Seoul, South Korea
| | | | - Junghoan Park
- Department of Radiology, Seoul National University College of Medicine, 101, Daehak-ro, Jongno-gu, Seoul, 03080, South Korea
| | - Juil Park
- Department of Radiology, Seoul National University College of Medicine, 101, Daehak-ro, Jongno-gu, Seoul, 03080, South Korea
| | | | | | - Kyung Eun Shin
- SoonChunHyang University Bucheon Hospital, Bucheon, South Korea
| | - Jiseon Oh
- Department of Radiology, Seoul National University College of Medicine, 101, Daehak-ro, Jongno-gu, Seoul, 03080, South Korea
| | - Sung Hyun Yoon
- Seoul National University Bundang Hospital, Seongnam, South Korea
| | | | - Youkyung Lee
- Hanyang University Guri Hospital, Guri, South Korea
| | - Woo Hyeon Lim
- Department of Radiology, Seoul National University College of Medicine, 101, Daehak-ro, Jongno-gu, Seoul, 03080, South Korea
| | - Won Gi Jeong
- Chonnam National University Hwasun Hospital, Hwasun-gun, South Korea
| | - Jung Im Jung
- Seoul St. Mary's Hospital, The Catholic University of Korea, Seoul, South Korea
| | - Min Jae Cha
- Chung-Ang University Hospital, Seoul, South Korea
| | - Sinae Choi
- Wesarang Internal Medicine Clinic, Jeonju, South Korea
| | - Hyoung In Choi
- Korean Armed Forces Capital Hospital, Seongnam, South Korea
| | - Soo-Youn Ham
- Sungkyunkwan University Kangbuk Samsung Hospital, Seoul, South Korea
| | - Yeol Kim
- National Cancer Center, Goyang, South Korea
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9
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Tringali G, Milanese G, Ledda RE, Pastorino U, Sverzellati N, Silva M. Lung Cancer Screening: Evidence, Risks, and Opportunities for Implementation. ROFO-FORTSCHR RONTG 2021; 193:1153-1161. [PMID: 33772489 DOI: 10.1055/a-1382-8648] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
BACKGROUND Lung cancer is the most common cause of cancer death worldwide. Several trials with different screening approaches have recognized the role of lung cancer screening with low-dose CT for reducing lung cancer mortality. The efficacy of lung cancer screening depends on many factors and implementation is still pending in most European countries. METHODS This review aims to portray current evidence on lung cancer screening with a focus on the potential for opportunities for implementation strategies. Pillars of lung cancer screening practice will be discussed according to the most updated literature (PubMed search until November 16, 2020). RESULTS AND CONCLUSION The NELSON trial showed reduction of lung cancer mortality, thus confirming previous results of independent European studies, notably by volume of lung nodules. Heterogeneity in patient recruitment could influence screening efficacy, hence the importance of risk models and community-based screening. Recruitment strategies develop and adapt continuously to address the specific needs of the heterogeneous population of potential participants, the most updated evidence comes from the UK. The future of lung cancer screening is a tailored approach with personalized continuous stratification of risk, aimed at reducing costs and risks. KEY POINTS · Secondary prevention of lung cancer by low-dose computed tomography showed a reduction of lung cancer mortality.. · Semi-automated volume measurement and use of volume doubling time should be the reference method for optimization of risks, namely controlling measurement variability and the false-positive rate.. · A conservative approach with surveillance of subsolid nodules can be one of the strategies to reduce the risk of overdiagnosis and overtreatment.. · The goal of a tailored approach with personalized risk stratification aims to reduce costs and risks. A longer interval between rounds is one option for participants at lower risk.. CITATION FORMAT · Tringali G, Milanese G, Ledda RE et al. Lung Cancer Screening: Evidence, Risks, and Opportunities for Implementation. Fortschr Röntgenstr 2021; 193: 1153 - 1161.
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Affiliation(s)
- Giulia Tringali
- Department of Medicine and Surgery (DiMeC - Scienze Radiologiche), University of Parma, Italy
| | - Gianluca Milanese
- Department of Medicine and Surgery (DiMeC - Scienze Radiologiche), University of Parma, Italy
| | - Roberta Eufrasia Ledda
- Department of Medicine and Surgery (DiMeC - Scienze Radiologiche), University of Parma, Italy
| | - Ugo Pastorino
- Department of Thoracic Surgery, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy
| | - Nicola Sverzellati
- Department of Medicine and Surgery (DiMeC - Scienze Radiologiche), University of Parma, Italy
| | - Mario Silva
- Department of Medicine and Surgery (DiMeC - Scienze Radiologiche), University of Parma, Italy
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