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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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Chang YC, Chen PT, Hsieh MS, Huang YS, Ko WC, Lin MW, Hsu HH, Chen JS, Chang YC. Discrimination of invasive lung adenocarcinoma from Lung-RADS category 2 nonsolid nodules through visual assessment: a retrospective study. Eur Radiol 2024; 34:3453-3461. [PMID: 37914975 DOI: 10.1007/s00330-023-10317-8] [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: 02/10/2023] [Revised: 09/11/2023] [Accepted: 09/24/2023] [Indexed: 11/03/2023]
Abstract
OBJECTIVES Invasive adenocarcinomas (IADs) have been identified among nonsolid nodules (NSNs) assigned as Lung Imaging Reporting and Data System (Lung-RADS) category 2. This study used visual assessment for differentiating IADs from noninvasive lesions (NILs) in this category. METHODS This retrospective study included 222 patients with 242 NSNs, which were resected after preoperative computed tomography (CT)-guided dye localization. Visual assessment was performed by using the lung and bone window (BW) settings to classify NSNs into BW-visible (BWV) and BW-invisible (BWI) NSNs. In addition, nodule size, shape, border, CT attenuation, and location were evaluated and correlated with histopathological results. Logistic regression was performed for multivariate analysis. A p value of < 0.05 was considered statistically significant. RESULTS A total of 242 NSNs (mean diameter, 7.6 ± 2.8 mm), including 166 (68.6%) BWV and 76 (31.4%) BWI NSNs, were included. IADs accounted for 31% (75) of the nodules. Only 4 (5.3%) IADs were identified in the BWI group and belonged to the lepidic-predominant (n = 3) and acinar-predominant (n = 1) subtypes. In univariate analysis for differentiating IADs from NILs, the nodule size, shape, CT attenuation, and visual classification exhibited statistical significance. Nodule size and visual classification were the significant predictors for IAD in multivariate analysis with logistic regression (p < 0.05). The sensitivity, specificity, positive predictive value, and negative predictive value of visual classification in IAD prediction were 94.7%, 43.1%, 42.8%, and 94.7%, respectively. CONCLUSIONS The window-based visual classification of NSNs is a simple and objective method to discriminate IADs from NILs. CLINICAL RELEVANCE STATEMENT The present study shows that using the bone window to classify nonsolid nodules helps discriminate invasive adenocarcinoma from noninvasive lesions. KEY POINTS • Evidence has shown the presence of lung adenocarcinoma in Lung-RADS category 2 nonsolid nodules. • Nonsolid nodules are classified into the bone window-visible and the bone window-invisible nonsolid nodules, and this classification differentiates invasive adenocarcinoma from noninvasive lesions. • The Lung-RADS category 2 nonsolid nodules are unlikely invasive adenocarcinoma if they show nonvisualization in the bone window.
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Affiliation(s)
- Yu-Chien Chang
- Department of Medical Imaging, National Taiwan University Hospital Hsin-Chu Branch, Hsin-Chu, Taiwan
- Department of Medical Imaging, National Taiwan University Hospital and National Taiwan University College of Medicine, 7 Chung-Shan South Rd., Taipei, 100225, Taiwan
| | - Po-Ting Chen
- Department of Medical Imaging, National Taiwan University Hospital Hsin-Chu Branch, Hsin-Chu, Taiwan
- Department of Medical Imaging, National Taiwan University Hospital and National Taiwan University College of Medicine, 7 Chung-Shan South Rd., Taipei, 100225, Taiwan
| | - Min-Shu Hsieh
- Department of Pathology, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan
| | - Yu-Sen Huang
- Department of Medical Imaging, National Taiwan University Hospital and National Taiwan University College of Medicine, 7 Chung-Shan South Rd., Taipei, 100225, Taiwan
| | - Wei-Chun Ko
- Department of Medical Imaging, National Taiwan University Hospital and National Taiwan University College of Medicine, 7 Chung-Shan South Rd., Taipei, 100225, Taiwan
| | - Mong-Wei Lin
- Department of Surgery, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan
| | - Hsao-Hsun Hsu
- Department of Surgery, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan
| | - Jin-Shing Chen
- Department of Surgery, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan
| | - Yeun-Chung Chang
- Department of Medical Imaging, National Taiwan University Hospital and National Taiwan University College of Medicine, 7 Chung-Shan South Rd., Taipei, 100225, Taiwan.
- Department of Medical Imaging, National Taiwan University Cancer Center, Taipei, Taiwan.
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3
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Wu YJ, Tang EK, Wu FZ. Evaluating Efficiency and Adherence in Asian Lung Cancer Screening: Comparing Self-paid and Clinical Study Approaches in Taiwan. Acad Radiol 2024; 31:2109-2117. [PMID: 38480076 DOI: 10.1016/j.acra.2024.01.045] [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: 12/21/2023] [Revised: 01/17/2024] [Accepted: 01/30/2024] [Indexed: 05/12/2024]
Abstract
RATIONALE AND OBJECTIVES This study aimed to assess how different screening methods, specifically self-paid screening versus participation in clinical studies, affect screening efficiency and adherence in a real-world Asian lung cancer screening population. MATERIALS AND METHODS This study collected 4166 participants from our hospital imaging database who underwent baseline low-dose computed tomography (LDCT) between January 2014 and August 2021. Adherence status was determined by counting CT scans, with one check indicating non-adherence and two or more checks indicating adherence. The primary objective was to investigate adherence to LDCT follow-up schedules among individuals with baseline pure ground-glass nodules (GGNs) based on different screening settings and to evaluate adherence status and CT follow-up clinical profiles. RESULTS Of the 4166 participants in the study, 3619 in the self-paid group and 547 in the clinical study group were men, with an average follow-up period of 4.5 years. Significant differences were observed in the proportions of Lung-RADS 4 lesions, subsolid nodules, and pure GGN lesions between the self-paid and clinical trial groups. A significant difference was found in adherence rates between the self-paid screening group (60.5%) and the clinical study group (84.8%) (p < 0.001). Adherence status rates significantly increased with larger GGN sizes across categories (p < 0.001). Multivariate logistic regression revealed that age (odds ratio [OR], 1.025; p = 0.012), smoking habits (OR, 1.744; p = 0.036), and clinical study screening type (OR, 3.097; p < 0.001) significantly influenced the adherence status. CONCLUSION The disparities in Asian lung cancer screening emphasize the need for increased efficacy, public awareness, and culturally sensitive approaches to mitigate overdiagnosis and enhance adherence among self-paying groups.
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Affiliation(s)
- Yun-Ju Wu
- Department of Radiology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan
| | - En-Kuei Tang
- Department of Surgery, Kaohsiung Veterans General Hospital, Kaohsiung 813414, Taiwan
| | - Fu-Zong Wu
- Department of Radiology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan; Institute of Education, National Sun Yat-sen University, 70, Lien-hai Road, Kaohsiung 80424, Taiwan; Faculty of Medicine, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan; Faculty of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
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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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5
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Hinsen M, Nagel AM, May MS, Wiesmueller M, Uder M, Heiss R. Lung Nodule Detection With Modern Low-Field MRI (0.55 T) in Comparison to CT. Invest Radiol 2024; 59:215-222. [PMID: 37490031 DOI: 10.1097/rli.0000000000001006] [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: 07/26/2023]
Abstract
OBJECTIVES The aim of this study was to evaluate the accuracy of modern low-field magnetic resonance imaging (MRI) for lung nodule detection and to correlate nodule size measurement with computed tomography (CT) as reference. MATERIALS AND METHODS Between November 2020 and July 2021, a prospective clinical trial using low-field MRI at 0.55 T was performed in patients with known pulmonary nodules from a single academic medical center. Every patient underwent MRI and CT imaging on the same day. The primary aim was to evaluate the detection accuracy of pulmonary nodules using MRI with transversal periodically rotated overlapping parallel lines with enhanced reconstruction in combination with coronal half-Fourier acquired single-shot turbo spin-echo MRI sequences. The secondary outcome was the correlation of the mean lung nodule diameter with CT as reference according to the Lung Imaging Reporting and Data System. Nonparametric Mann-Whitney U test, Spearman rank correlation coefficient, and Bland-Altman analysis were applied to analyze the results. RESULTS A total of 46 participants (mean age ± SD, 66 ± 11 years; 26 women) were included. In a blinded analysis of 964 lung nodules, the detection accuracy was 100% for those ≥6 mm (126/126), 80% (159/200) for those ≥4-<6 mm, and 23% (147/638) for those <4 mm in MRI compared with reference CT. Spearman correlation coefficient of MRI and CT size measurement was r = 0.87 ( P < 0.001), and the mean difference was 0.16 ± 0.9 mm. CONCLUSIONS Modern low-field MRI shows excellent accuracy in lesion detection for lung nodules ≥6 mm and a very strong correlation with CT imaging for size measurement, but could not compete with CT in the detection of small nodules.
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Affiliation(s)
- Maximilian Hinsen
- From the Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany (M.H., A.M.N., M.S.M., M.W., M.U., R.H.); and Division of Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany (A.M.N.)
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6
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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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7
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Christensen J, Prosper AE, Wu CC, Chung J, Lee E, Elicker B, Hunsaker AR, Petranovic M, Sandler KL, Stiles B, Mazzone P, Yankelevitz D, Aberle D, Chiles C, Kazerooni E. ACR Lung-RADS v2022: Assessment Categories and Management Recommendations. Chest 2024; 165:738-753. [PMID: 38300206 DOI: 10.1016/j.chest.2023.10.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2024] Open
Abstract
The American College of Radiology created the Lung CT Screening Reporting and Data System (Lung-RADS) in 2014 to standardize the reporting and management of screen-detected pulmonary nodules. Lung-RADS was updated to version 1.1 in 2019 and revised size thresholds for nonsolid nodules, added classification criteria for perifissural nodules, and allowed for short-interval follow-up of rapidly enlarging nodules that may be infectious in etiology. Lung-RADS v2022, released in November 2022, provides several updates including guidance on the classification and management of atypical pulmonary cysts, juxtapleural nodules, airway-centered nodules, and potentially infectious findings. This new release also provides clarification for determining nodule growth and introduces stepped management for nodules that are stable or decreasing in size. This article summarizes the current evidence and expert consensus supporting Lung-RADS v2022.
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Affiliation(s)
- Jared Christensen
- Vice Chair and Professor of Radiology, Department of Radiology, Duke University, Durham, North Carolina; Chair, ACR Lung-RADS Committee.
| | - Ashley Elizabeth Prosper
- Assistant Professor and Section Chief of Cardiothoracic Imaging, Department of Radiological Sciences, University of California, Los Angeles, California
| | - Carol C Wu
- Professor of Diagnostic Imaging, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jonathan Chung
- Professor of Radiology Vice Chair of Quality Section Chief of Cardiopulmonary Imaging, University of Chicago, Chicago, Illinois
| | - Elizabeth Lee
- Clinical Associate Professor, Radiology, Michigan Medicine, Ann Arbor, Michigan
| | - Brett Elicker
- Chief of the Cardiac & Pulmonary Imaging Section, University of California, San Francisco, California
| | - Andetta R Hunsaker
- Brigham and Women's Hospital, Boston, Massachusetts; Associate Professor Harvard Medical School Chief Division of Thoracic Imaging
| | - Milena Petranovic
- Instructor, Radiology, Harvard Medical School Divisional Quality Director, Thoracic Imaging and Intervention, Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Kim L Sandler
- Associate Professor, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Brendon Stiles
- Professor and Chair, Thoracic Surgery and Surgical Oncology, Montefiore Health System, Albert Einstein College of Medicine, Bronx, New York
| | | | | | - Denise Aberle
- Professor of Radiology, Department of Radiological Sciences; David Geffen School of Medicine at UCLA, Los Angeles, California
| | - Caroline Chiles
- Professor of Radiology Director, Lung Screening Program, Atrium Health Wake Forest, Winston-Salem, North Carolina
| | - Ella Kazerooni
- Professor of Radiology & Internal Medicine and Associate Chief Clinical Officer for Diagnostics, Michigan Medicine/University of Michigan Medical School, Ann Arbor, Michigan; Clinical Information Management, University of Michigan Medical Group
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Lahiri R, Rawat SS, Srikant K, Rao S. Intrathoracic Ewing's sarcoma in an adult masquerading as lung abscess. BMJ Case Rep 2024; 17:e256631. [PMID: 38296504 PMCID: PMC10831453 DOI: 10.1136/bcr-2023-256631] [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: 02/05/2024] Open
Abstract
Intrathoracic extraskeletal Ewing's sarcoma (EES) is a relatively uncommon malignant tumour. Here, we present a scenario involving an adult man in his 20s with a large intrathoracic EES that manifested as a lung abscess. Preoperative diagnostic tests were inconclusive; hence, the patient underwent an exploratory thoracotomy for the excision of the mass. Histopathology revealed a small round blue cell tumour, and immunohistochemistry, along with fluorescence in situ hybridisation, confirmed the diagnosis of Ewing's sarcoma. Adjuvant chemoradiotherapy was recommended, but the patient did not comply. A year later, he presented with a recurrence of the intrathoracic mass and subsequently received adjuvant chemotherapy. Currently, he is in remission.
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Affiliation(s)
- Raja Lahiri
- CVTS, All India Institute of Medical Sciences Rishikesh, Rishikesh, Uttarakhand, India
| | - Shubham Singh Rawat
- CVTS, All India Institute of Medical Sciences Rishikesh, Rishikesh, Uttarakhand, India
| | | | - Shalinee Rao
- Pathology and Lab Medicine, All India Institute of Medical Sciences Rishikesh, Rishikesh, Uttarakhand, India
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9
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Salvatore MM, Liu Y, Peng B, Hsu HY, Saqi A, Tsai WY, Leu CS, Jambawalikar S. Comparison of lung cancer occurring in fibrotic versus non-fibrotic lung on chest CT. J Transl Med 2024; 22:67. [PMID: 38229113 PMCID: PMC10792886 DOI: 10.1186/s12967-023-04645-y] [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: 07/02/2023] [Accepted: 10/20/2023] [Indexed: 01/18/2024] Open
Abstract
PURPOSE Evaluate the behavior of lung nodules occurring in areas of pulmonary fibrosis and compare them to pulmonary nodules occurring in the non-fibrotic lung parenchyma. METHODS This retrospective review of chest CT scans and electronic medical records received expedited IRB approval and a waiver of informed consent. 4500 consecutive patients with a chest CT scan report containing the word fibrosis or a specific type of fibrosis were identified using the system M*Model Catalyst (Maplewood, Minnesota, U.S.). The largest nodule was measured in the longest dimension and re-evaluated, in the same way, on the follow-up exam if multiple time points were available. The nodule doubling time was calculated. If the patient developed cancer, the histologic diagnosis was documented. RESULTS Six hundred and nine patients were found to have at least one pulmonary nodule on either the first or the second CT scan. 274 of the largest pulmonary nodules were in the fibrotic tissue and 335 were in the non-fibrotic lung parenchyma. Pathology proven cancer was more common in nodules occurring in areas of pulmonary fibrosis compared to nodules occurring in areas of non-fibrotic lung (34% vs 15%, p < 0.01). Adenocarcinoma was the most common cell type in both groups but more frequent in cancers occurring in non-fibrotic tissue. In the non-fibrotic lung, 1 of 126 (0.8%) of nodules measuring 1 to 6 mm were cancer. In contrast, 5 of 49 (10.2%) of nodules in fibrosis measuring 1 to 6 mm represented biopsy-proven cancer (p < 0.01). The doubling time for squamous cell cancer was shorter in the fibrotic lung compared to non-fibrotic lung, however, the difference was not statistically significant (p = 0.24). 15 incident lung nodules on second CT obtained ≤ 18 months after first CT scan was found in fibrotic lung and eight (53%) were diagnosed as cancer. CONCLUSIONS Nodules occurring in fibrotic lung tissue are more likely to be cancer than nodules in the nonfibrotic lung. Incident pulmonary nodules in pulmonary fibrosis have a high likelihood of being cancer.
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Affiliation(s)
- Mary M Salvatore
- Department of Radiology, Columbia University Irving Medical Center, 622 W 168th Street, New York, NY, 10032, USA.
| | - Yucheng Liu
- Department of Radiology, Columbia University Irving Medical Center, 622 W 168th Street, New York, NY, 10032, USA
| | - Boyu Peng
- Department of Radiology, Columbia University Irving Medical Center, 622 W 168th Street, New York, NY, 10032, USA
| | - Hao Yun Hsu
- Department of Radiology, Columbia University Irving Medical Center, 622 W 168th Street, New York, NY, 10032, USA
| | - Anjali Saqi
- Department of Pathology, Columbia University Irving Medical Center, New York, NY, USA
| | - Wei-Yann Tsai
- Department of Biostatistics, Columbia University, New York, NY, USA
| | - Cheng-Shiun Leu
- Department of Biostatistics, Columbia University, New York, NY, USA
| | - Sachin Jambawalikar
- Department of Radiology, Columbia University Irving Medical Center, 622 W 168th Street, New York, NY, 10032, USA
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Li S, Chen M, Wang Y, Li X, Gao G, Luo X, Tang L, Liu X, Wu N. An Effective Malignancy Prediction Model for Incidentally Detected Pulmonary Subsolid Nodules Based on Current and Prior CT Scans. Clin Lung Cancer 2023; 24:e301-e310. [PMID: 37596166 DOI: 10.1016/j.cllc.2023.08.001] [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: 06/26/2023] [Revised: 07/30/2023] [Accepted: 08/01/2023] [Indexed: 08/20/2023]
Abstract
INTRODUCTION It is challenging to diagnose and manage incidentally detected pulmonary subsolid nodules due to their indolent nature and heterogeneity. The objective of this study is to construct a decision tree-based model to predict malignancy of a subsolid nodule based on radiomics features and evolution over time. MATERIALS AND METHODS We derived a training set (2947 subsolid nodules), a test set (280 subsolid nodules) from a cohort of outpatient CT scans, and a second test set (5171 subsolid nodules) from the National Lung Cancer Screening Trial (NLST). A Computer-Aided Diagnosis system (CADs) automatically extracted 28 preselected radiomics features, and we calculated the feature change rates as the change of the quantitative measure per time unit between the prior and current CT scans. We built classification models based on XGBoost and employed 5-fold cross validation to optimize the parameters. RESULTS The model that combined radiomics features with their change rates performed the best. The Areas Under Curve (AUCs) on the outpatient test set and on the NLST test set were 0.977 (95% CI, 0.958-0.996) and 0.955 (95% CI, 0.930-0.980), respectively. The model performed consistently well on subgroups stratified by nodule diameters, solid components, and CT scan intervals. CONCLUSION This decision tree-based model trained with the outpatient dataset gives promising predictive performance on the malignancy of pulmonary subsolid nodules. Additionally, it can assist clinicians to deliver more accurate diagnoses and formulate more in-depth follow-up strategies.
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Affiliation(s)
- Shaolei Li
- Department of Thoracic Surgery II, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China
| | - Mailin Chen
- Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China
| | - Yaqi Wang
- Department of Thoracic Surgery II, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China
| | - Xiang Li
- Department of Thoracic Surgery II, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China
| | | | | | - Lei Tang
- Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China
| | | | - Nan Wu
- Department of Thoracic Surgery II, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China.
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11
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Kocher Wulfeck M, Plesner S, Herndon JE, Christensen JD, Patz EF. Characterizing Lung-RADS category 4 lesions in a university lung cancer screening program. Lung Cancer 2023; 186:107420. [PMID: 37956610 DOI: 10.1016/j.lungcan.2023.107420] [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: 05/18/2023] [Revised: 09/03/2023] [Accepted: 11/05/2023] [Indexed: 11/15/2023]
Abstract
OBJECTIVES To assess the prevalence of lung cancer in Lung-RADS category 4 patients, and to elucidate if clinical or imaging features help differentiate benign lesions from lung cancer. MATERIALS/METHODS A retrospective review of lung cancer screening (LCS) studies at a single university screening program between January 2018 and December 2021 identified all patients with Lung-RADS category 4 lesions. Patient demographics, symptoms within the prior 6 months, and imaging features were recorded. RESULTS During the defined period, 4819 baseline and annual LCS exams were performed; 7.6 % (n = 368) of exams had category 4 nodules and 59 (1.2 %) patients had biopsy-proven lung cancer. Distribution of Lung-RADS category 4 lesions and lung cancer diagnosis were as follows: 4A - 223 nodules, 6.3 % malignant; 4B - 114 nodules, 20.2 % malignant; and 4X - 31 nodules, 71.0 % malignant. Symptoms were reported in 9.0 % (n = 20) of category 4A (2 were malignant), 15.8 % (n = 18) category 4B (1 was malignant) and 22.6 % (n = 7) category 4X (5 were malignant). Imaging features associated with malignancy included endobronchial obstruction with distal atelectasis, pleural tethering, irregular shape, cavitation, and heterogeneous cystic appearance. Twenty-four nodules increased in size, however, only 7 were biopsy proven. Relative to the risk seen with 4A disease, multivariable logistic analyses showed that the odds of a malignancy increased significantly by 3.8 fold (95 % CI: 1.9, 7.9) and 39.2 fold (95 % CI: 14.9, 103.0) with 4B and 4X disease, respectively (p < 0.0001). A separate analysis involving only category 4A and 4B patients jointly showed that disease category (OR = 3.0; 95 % CI: 1.5, 6.4) and additional imaging features (OR = 3.2; 95 % CI: 1.4, 7.0) were significant predictors of malignancy. The presence of clinical symptoms was not statistically associated with lung cancer. CONCLUSIONS Lung-RADS 4 nodules were found in 7.6% of LCS examinations and 16% of these nodules were lung cancer. The probability of lung cancer increases from category 4A to 4X, and imaging features may help differentiate benign from malignant nodules in this LCS category.
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Affiliation(s)
- Madison Kocher Wulfeck
- Department of Radiology, Duke University Medical Center, 2301 Erwin Road Box 3808, Durham, NC 27710, USA.
| | - Samuel Plesner
- Inland Imaging 801 S Stevens St., Spokane, WA 99204, USA.
| | - James E Herndon
- Department of Radiology, Duke University Medical Center, 2301 Erwin Road Box 3808, Durham, NC 27710, USA.
| | - Jared D Christensen
- Department of Radiology, Duke University Medical Center, 2301 Erwin Road Box 3808, Durham, NC 27710, USA.
| | - Edward F Patz
- Department of Radiology, Duke University Medical Center, 2301 Erwin Road Box 3808, Durham, NC 27710, USA.
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12
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Abstract
Lung cancer represents a large burden on society with a staggering incidence and mortality rate that has steadily increased until recently. The impetus to design an effective screening program for the deadliest cancer in the United States and worldwide began in 1950. It has taken more than 50 years of numerous clinical trials and continued persistence to arrive at the development of modern-day screening program. As the program continues to grow, it is important for clinicians to understand its evolution, track outcomes, and continually assess the impact and bias of screening on the medical, social, and economic systems.
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Affiliation(s)
- Hai V N Salfity
- Division of Thoracic Surgery, Department of Surgery, University of Cincinnati School of Medicine, 231 Albert Sabin Way Suite 2472, Cincinnati, OH 45267, USA.
| | - Betty C Tong
- Division of Thoracic Surgery, Department of Surgery, Duke University School of Medicine, Box 3531 DUMC, Durham, NC 27710, USA
| | - Madison R Kocher
- Division of Cardiothoracic Imaging, Department of Radiology, Duke University School of Medicine, Box 3808 DUMC, Durham, NC 27710, USA
| | - Tina D Tailor
- Division of Cardiothoracic Imaging, Department of Radiology, Duke University School of Medicine, Box 3808 DUMC, Durham, NC 27710, USA
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13
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Irajizad E, Fahrmann JF, Marsh T, Vykoukal J, Dennison JB, Long JP, Do KA, Feng Z, Hanash S, Ostrin EJ. Mortality Benefit of a Blood-Based Biomarker Panel for Lung Cancer on the Basis of the Prostate, Lung, Colorectal, and Ovarian Cohort. J Clin Oncol 2023; 41:4360-4368. [PMID: 37379494 PMCID: PMC10522105 DOI: 10.1200/jco.22.02424] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 04/14/2023] [Accepted: 05/06/2023] [Indexed: 06/30/2023] Open
Abstract
PURPOSE To investigate the utility of integrating a panel of circulating protein biomarkers in combination with a risk model on the basis of subject characteristics to identify individuals at high risk of harboring a lethal lung cancer. METHODS Data from an established logistic regression model that combines four-marker protein panel (4MP) together with the Prostate, Lung, Colorectal, and Ovarian (PLCO) risk model (PLCOm2012) assayed in prediagnostic sera from 552 lung cancer cases and 2,193 noncases from the PLCO cohort were used in this study. Of the 552 lung cancer cases, 387 (70%) died of lung cancer. Cumulative incidence of lung cancer death and subdistributional and cause-specific hazard ratios (HRs) were calculated on the basis of 4MP + PLCOm2012 risk scores at a predefined 1.0% and 1.7% 6-year risk thresholds, which correspond to the current and former US Preventive Services Task Force screening criteria, respectively. RESULTS When considering cases diagnosed within 1 year of blood draw and all noncases, the area under receiver operation characteristics curve estimate of the 4MP + PLCOm2012 model for risk prediction of lung cancer death was 0.88 (95% CI, 0.86 to 0.90). The cumulative incidence of lung cancer death was statistically significantly higher in individuals with 4MP + PLCOm2012 scores above the 1.0% 6-year risk threshold (modified χ2, 166.27; P < .0001). Corresponding subdistributional and lung cancer death-specific HRs for test-positive cases were 9.88 (95% CI, 6.44 to 15.18) and 10.65 (95% CI, 6.93 to 16.37), respectively. CONCLUSION The blood-based biomarker panel in combination with PLCOm2012 identifies individuals at high risk of a lethal lung cancer.
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Affiliation(s)
- Ehsan Irajizad
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Johannes F. Fahrmann
- Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Tracey Marsh
- Biostatistics Program, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Jody Vykoukal
- Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jennifer B. Dennison
- Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - James P. Long
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Kim-Anh Do
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Ziding Feng
- Biostatistics Program, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Samir Hanash
- Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Edwin J. Ostrin
- Department of Pulmonary Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX
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14
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Sandler KL, Henry TS, Amini A, Elojeimy S, Kelly AM, Kuzniewski CT, Lee E, Martin MD, Morris MF, Peterson NB, Raptis CA, Silvestri GA, Sirajuddin A, Tong BC, Wiener RS, Witt LJ, Donnelly EF. ACR Appropriateness Criteria® Lung Cancer Screening: 2022 Update. J Am Coll Radiol 2023; 20:S94-S101. [PMID: 37236754 DOI: 10.1016/j.jacr.2023.02.014] [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] [Received: 02/21/2023] [Accepted: 02/27/2023] [Indexed: 05/28/2023]
Abstract
Lung cancer remains the leading cause of cancer-related mortality for men and women in the United States. Screening for lung cancer with annual low-dose CT is saving lives, and the continued implementation of lung screening can save many more. In 2015, the CMS began covering annual lung screening for those who qualified based on the original United States Preventive Services Task Force (USPSTF) lung screening criteria, which included patients 55 to 77 year of age with a 30 pack-year history of smoking, who were either currently using tobacco or who had smoked within the previous 15 years. In 2021, the USPSTF issued new screening guidelines, decreasing the age of eligibility to 80 years of age and pack-years to 20. Lung screening remains controversial for those who do not meet the updated USPSTF criteria, but who have additional risk factors for the development of lung cancer. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.
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Affiliation(s)
- Kim L Sandler
- Vanderbilt University Medical Center, Nashville, Tennessee.
| | | | - Arya Amini
- City of Hope National Medical Center, Duarte, California; Commission on Radiation Oncology
| | - Saeed Elojeimy
- Medical University of South Carolina, Charleston, South Carolina; Commission on Nuclear Medicine and Molecular Imaging
| | | | | | - Elizabeth Lee
- University of Michigan Health System, Ann Arbor, Michigan
| | - Maria D Martin
- University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | | | - Neeraja B Peterson
- Division of General Internal Medicine and Public Health, Vanderbilt University Medical Center, Nashville, Tennessee, Primary care physician
| | | | - Gerard A Silvestri
- Medical University of South Carolina, Charleston, South Carolina; American College of Chest Physicians
| | | | - Betty C Tong
- Duke University School of Medicine, Durham, North Carolina; The Society of Thoracic Surgeons
| | - Renda Soylemez Wiener
- Boston University School of Medicine and Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Boston, Massachusetts; American College of Chest Physicians
| | - Leah J Witt
- University of California San Francisco, San Francisco, California; American Geriatrics Society
| | - Edwin F Donnelly
- Specialty Chair, Ohio State University Wexner Medical Center, Columbus, Ohio
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15
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Auger C, Moudgalya H, Neely MR, Stephan JT, Tarhoni I, Gerard D, Basu S, Fhied CL, Abdelkader A, Vargas M, Hu S, Hulett T, Liptay MJ, Shah P, Seder CW, Borgia JA. Development of a Novel Circulating Autoantibody Biomarker Panel for the Identification of Patients with 'Actionable' Pulmonary Nodules. Cancers (Basel) 2023; 15:2259. [PMID: 37190187 PMCID: PMC10136536 DOI: 10.3390/cancers15082259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Revised: 04/05/2023] [Accepted: 04/06/2023] [Indexed: 05/17/2023] Open
Abstract
Due to poor compliance and uptake of LDCT screening among high-risk populations, lung cancer is often diagnosed in advanced stages where treatment is rarely curative. Based upon the American College of Radiology's Lung Imaging and Reporting Data System (Lung-RADS) 80-90% of patients screened will have clinically "non-actionable" nodules (Lung-RADS 1 or 2), and those harboring larger, clinically "actionable" nodules (Lung-RADS 3 or 4) have a significantly greater risk of lung cancer. The development of a companion diagnostic method capable of identifying patients likely to have a clinically actionable nodule identified during LDCT is anticipated to improve accessibility and uptake of the paradigm and improve early detection rates. Using protein microarrays, we identified 501 circulating targets with differential immunoreactivities against cohorts characterized as possessing either actionable (n = 42) or non-actionable (n = 20) solid pulmonary nodules, per Lung-RADS guidelines. Quantitative assays were assembled on the Luminex platform for the 26 most promising targets. These assays were used to measure serum autoantibody levels in 841 patients, consisting of benign (BN; n = 101), early-stage non-small cell lung cancer (NSCLC; n = 245), other early-stage malignancies within the lung (n = 29), and individuals meeting United States Preventative Screening Task Force (USPSTF) screening inclusion criteria with both actionable (n = 87) and non-actionable radiologic findings (n = 379). These 841 patients were randomly split into three cohorts: Training, Validation 1, and Validation 2. Of the 26 candidate biomarkers tested, 17 differentiated patients with actionable nodules from those with non-actionable nodules. A random forest model consisting of six autoantibody (Annexin 2, DCD, MID1IP1, PNMA1, TAF10, ZNF696) biomarkers was developed to optimize our classification performance; it possessed a positive predictive value (PPV) of 61.4%/61.0% and negative predictive value (NPV) of 95.7%/83.9% against Validation cohorts 1 and 2, respectively. This panel may improve patient selection methods for lung cancer screening, serving to greatly reduce the futile screening rate while also improving accessibility to the paradigm for underserved populations.
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Affiliation(s)
- Claire Auger
- Department of Anatomy & Cell Biology, Rush University Medical Center, Chicago, IL 60612, USA
| | - Hita Moudgalya
- Department of Anatomy & Cell Biology, Rush University Medical Center, Chicago, IL 60612, USA
| | - Matthew R. Neely
- Department of Anatomy & Cell Biology, Rush University Medical Center, Chicago, IL 60612, USA
| | - Jeremy T. Stephan
- Rush University Medical College, Rush University Medical Center, Chicago, IL 60612, USA
| | - Imad Tarhoni
- Department of Anatomy & Cell Biology, Rush University Medical Center, Chicago, IL 60612, USA
| | - David Gerard
- Department of Anatomy & Cell Biology, Rush University Medical Center, Chicago, IL 60612, USA
| | - Sanjib Basu
- Division of Medical Oncology, Rush University Medical Center, Chicago, IL 60612, USA
| | - Cristina L. Fhied
- Department of Anatomy & Cell Biology, Rush University Medical Center, Chicago, IL 60612, USA
| | - Ahmed Abdelkader
- Department of Anatomy & Cell Biology, Rush University Medical Center, Chicago, IL 60612, USA
| | | | - Shaohui Hu
- CDI Laboratories, Mayagüez, PR 00680, USA
| | | | - Michael J. Liptay
- Department of Cardiovascular and Thoracic Surgery, Rush University Medical Center, Chicago, IL 60612, USA
| | - Palmi Shah
- Department of Diagnostic Radiology, Rush University Medical Center, Chicago, IL 60612, USA
| | - Christopher W. Seder
- Department of Cardiovascular and Thoracic Surgery, Rush University Medical Center, Chicago, IL 60612, USA
| | - Jeffrey A. Borgia
- Department of Anatomy & Cell Biology, Rush University Medical Center, Chicago, IL 60612, USA
- Department of Pathology, Rush University Medical Center, Chicago, IL 60612, USA
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16
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Zhang J, Tang K, Liu L, Guo C, Zhao K, Li S. Management of pulmonary nodules in women with pregnant intention: A review with perspective. Ann Thorac Med 2023; 18:61-69. [PMID: 37323371 PMCID: PMC10263075 DOI: 10.4103/atm.atm_270_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Revised: 09/04/2022] [Accepted: 09/13/2022] [Indexed: 06/17/2023] Open
Abstract
The process for the management of pulmonary nodules in women with pregnant intention remains a challenge. There was a certain proportion of targeted female patients with high-risk lung cancer, and anxiety for suspicious lung cancer in early stage also exists. A comprehensive review of hereditary of lung cancer, effects of sexual hormone on lung cancer, natural history of pulmonary nodules, and computed tomography imaging with radiation exposure based on PubMed search was completed. The heredity of lung cancer and effects of sexual hormone on lung cancer are not the decisive factors, and the natural history of pulmonary nodules and the radiation exposure of imaging should be the main concerns. The management of incidental pulmonary nodules in young women with pregnant intention is an intricate and indecisive problem we have to encounter. The balance between the natural history of pulmonary nodules and the radiation exposure of imaging should be weighed.
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Affiliation(s)
- Jiaqi Zhang
- Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Kun Tang
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China
- Institute of Respiratory Disease of Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Lei Liu
- Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Chao Guo
- Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ke Zhao
- Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shanqing Li
- Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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17
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Yan G, Li H, Fan X, Deng J, Yan J, Qiao F, Yan G, Liu T, Chen J, Wang L, Yang Y, Li Y, Zhao L, Bhetuwal A, McClure MA, Li N, Peng C. Multimodality CT imaging contributes to improving the diagnostic accuracy of solitary pulmonary nodules: a multi-institutional and prospective study. Radiol Oncol 2023; 57:20-34. [PMID: 36795007 PMCID: PMC10039475 DOI: 10.2478/raon-2023-0008] [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: 08/15/2022] [Accepted: 12/05/2022] [Indexed: 02/17/2023] Open
Abstract
BACKGROUND Solitary pulmonary nodules (SPNs) are one of the most common chest computed tomography (CT) abnormalities clinically. We aimed to investigate the value of non-contrast enhanced CT (NECT), contrast enhanced CT (CECT), CT perfusion imaging (CTPI), and dual- energy CT (DECT) used for differentiating benign and malignant SPNs with a multi-institutional and prospective study. PATIENTS AND METHODS Patients with 285 SPNs were scanned with NECT, CECT, CTPI and DECT. Differences between the benign and malignant SPNs on NECT, CECT, CTPI, and DECT used separately (NECT combined with CECT, DECT, and CTPI were methods of A, B, and C) or in combination (Method A + B, A + C, B + C, and A + B + C) were compared by receiver operating characteristic curve analysis. RESULTS Multimodality CT imaging showed higher performances (sensitivities of 92.81% to 97.60%, specificities of 74.58% to 88.14%, and accuracies of 86.32% to 93.68%) than those of single modality CT imaging (sensitivities of 83.23% to 85.63%, specificities of 63.56% to 67.80%, and accuracies of 75.09% to 78.25%, all p < 0.05). CONCLUSIONS SPNs evaluated with multimodality CT imaging contributes to improving the diagnostic accuracy of benign and malignant SPNs. NECT helps to locate and evaluate the morphological characteristics of SPNs. CECT helps to evaluate the vascularity of SPNs. CTPI using parameter of permeability surface and DECT using parameter of normalized iodine concentration at the venous phase both are helpful for improving the diagnostic performance.
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Affiliation(s)
- Gaowu Yan
- Department of Radiology, Suining Central Hospital, Suining, China
| | - Hongwei Li
- Department of Radiology, The Third Hospital of Mianyang and Sichuan Mental Health Center, Mianyang, China
| | - Xiaoping Fan
- Department of Radiology, Suining Central Hospital, Suining, China
| | - Jiantao Deng
- Department of Radiology, Suining Central Hospital, Suining, China
| | - Jing Yan
- Department of Radiology, Suining Central Hospital, Suining, China
| | - Fei Qiao
- Department of CT and MRI, The First Affiliated Hospital, Shihezi University School of Medicine, Shihezi, China
| | - Gaowen Yan
- Department of Radiology, The First People's Hospital of Suining, Suining, China
| | - Tao Liu
- Department of Radiology, Suining Central Hospital, Suining, China
| | - Jiankang Chen
- Department of Radiology, Suining Central Hospital, Suining, China
| | - Lei Wang
- Department of Radiology, Suining Central Hospital, Suining, China
| | - Yang Yang
- Department of Radiology, Suining Central Hospital, Suining, China
| | - Yong Li
- Department of Radiology, Suining Central Hospital, Suining, China
| | - Linwei Zhao
- Department of Radiology, Suining Central Hospital, Suining, China
| | - Anup Bhetuwal
- Sichuan Key Laboratory of Medical Imaging and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Morgan A McClure
- Department of Radiology and Imaging; Institute of Rehabilitation and Development of Brain Function, The Second Clinical Medical College of North Sichuan Medical College Nanchong Central Hospital, Nanchong, China
| | - Na Li
- Department of Oncology, Suining Central Hospital, Suining, China
| | - Chen Peng
- Department of Gastroenterology, The First People's Hospital of Suining, Suining, China
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18
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Affiliation(s)
- Theresa C McLoud
- From the Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 55 Fruit St, MZ-FND 216, Boston, MA 02114-2696 (T.C.M.); and Department of Radiology, Mayo Clinic College of Medicine and Science, Mayo Clinic Florida, Jacksonville, Fla (B.P.L.)
| | - Brent P Little
- From the Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 55 Fruit St, MZ-FND 216, Boston, MA 02114-2696 (T.C.M.); and Department of Radiology, Mayo Clinic College of Medicine and Science, Mayo Clinic Florida, Jacksonville, Fla (B.P.L.)
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19
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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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20
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State of the Art: Lung Cancer Staging Using Updated Imaging Modalities. Bioengineering (Basel) 2022; 9:bioengineering9100493. [PMID: 36290461 PMCID: PMC9598500 DOI: 10.3390/bioengineering9100493] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 09/15/2022] [Accepted: 09/16/2022] [Indexed: 11/17/2022] Open
Abstract
Lung cancer is among the most common mortality causes worldwide. This scientific article is a comprehensive review of current knowledge regarding screening, subtyping, imaging, staging, and management of treatment response for lung cancer. The traditional imaging modality for screening and initial lung cancer diagnosis is computed tomography (CT). Recently, a dual-energy CT was proven to enhance the categorization of variable pulmonary lesions. The National Comprehensive Cancer Network (NCCN) recommends usage of fluorodeoxyglucose positron emission tomography (FDG PET) in concert with CT to properly stage lung cancer and to prevent fruitless thoracotomies. Diffusion MR is an alternative to FDG PET/CT that is radiation-free and has a comparable diagnostic performance. For response evaluation after treatment, FDG PET/CT is a potent modality which predicts survival better than CT. Updated knowledge of lung cancer genomic abnormalities and treatment regimens helps to improve the radiologists’ skills. Incorporating the radiologic experience is crucial for precise diagnosis, therapy planning, and surveillance of lung cancer.
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21
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A Nomogram Incorporating Tumor-Related Vessels for Differentiating Adenocarcinoma In Situ from Minimally Invasive and Invasive Adenocarcinoma Appearing as Subsolid Nodules. Acad Radiol 2022; 30:928-939. [PMID: 36150965 DOI: 10.1016/j.acra.2022.08.024] [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: 05/22/2022] [Revised: 08/08/2022] [Accepted: 08/20/2022] [Indexed: 11/24/2022]
Abstract
OBJECTIVES To develop a nomogram incorporating the quantity of tumor-related vessels (TRVs) and conventional CT features (CCTFs) for the preoperative differentiation of adenocarcinoma in situ (AIS) from minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC) appearing as subsolid nodules. METHODS High-resolution CT target scans of 274 subsolid nodules from 268 patients were included in this study and randomly assigned to the training and validation groups at a ratio of 7:3. A nomogram incorporating CCTFs with the category of TRVs (CTRVs, using TRVs as categorical variables) and a final nomogram combining the number of TRVs (QTRVs) and CCTFs were constructed using multivariable logistic regression analysis. The performance levels of the two nomograms were evaluated and validated on the training and validation datasets and then compared. RESULTS The CCTF-QTRV nomogram incorporating abnormal air bronchogram, density, number of dilated and distorted vessels and number of adherent vessels showed more favorable predictive efficacy than the CCTF-CTRV nomogram (training cohort: area under the curve (AUC) = 0.893 vs. 0.844, validation cohort: AUC = 0.871 vs. 0.807). The net reclassification index (training cohort: 0.188, validation cohort: 0.326) and the integrated discrimination improvement values (training cohort: 0.091, validation cohort: 0.125) indicated that the CCTF-QTRV nomogram performed significantly better discriminative ability than the CCTF-CTRV nomogram (all p-value < 0.05). CONCLUSIONS The nomogram incorporating the QTRVs and CCTFs showed favorable predictive efficacy for differentiating AIS from MIA-IAC appearing as subsolid nodules and may serve as a potential tool to provide individual care for these patients.
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Curti M, Fontana F, Piacentino F, Ossola C, Coppola A, Carcano G, Venturini M. Dual-layer spectral CT fusion imaging for lung biopsies: more accurate targets, diagnostic samplings, and biomarker information? Eur Radiol Exp 2022; 6:34. [PMID: 35965267 PMCID: PMC9376184 DOI: 10.1186/s41747-022-00290-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 06/09/2022] [Indexed: 11/13/2022] Open
Abstract
The increasingly widespread use of computed tomography (CT) has increased the number of detected lung lesions, which are then subjected to needle biopsy to obtain histopathological diagnosis. Obtaining high-quality biopsy specimens is fundamental for diagnosis and biomolecular characterisation that guide therapy decision-making. In order to obtain samples with high diagnostic potential, fusion imaging techniques, such as fusion between positron emission tomography and CT, have been introduced to target the biopsy where there more viable neoplastic cells can be sampled. Nowadays, dual-layer spectral CT represents a novel technology enabling an increased tissue characterisation. In particular, Z-effective images, i.e., colour-coded images based on the effective atomic number of tissue components, provide a higher level of discrimination than usual imaged based on x-ray attenuation in Hounsfield units and offer the potential of a better tissue characterisation. Our hypothesis is based on the future use of data provided by spectral CT, in particular by Z-effective images, as a guide for appropriate biopsy sampling for histopathological and biomolecular characterisation in the era of patient tailored-therapy.
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Bonney A, Malouf R, Marchal C, Manners D, Fong KM, Marshall HM, Irving LB, Manser R. Impact of low-dose computed tomography (LDCT) screening on lung cancer-related mortality. Cochrane Database Syst Rev 2022; 8:CD013829. [PMID: 35921047 PMCID: PMC9347663 DOI: 10.1002/14651858.cd013829.pub2] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND Lung cancer is the most common cause of cancer-related death in the world, however lung cancer screening has not been implemented in most countries at a population level. A previous Cochrane Review found limited evidence for the effectiveness of lung cancer screening with chest radiography (CXR) or sputum cytology in reducing lung cancer-related mortality, however there has been increasing evidence supporting screening with low-dose computed tomography (LDCT). OBJECTIVES: To determine whether screening for lung cancer using LDCT of the chest reduces lung cancer-related mortality and to evaluate the possible harms of LDCT screening. SEARCH METHODS We performed the search in collaboration with the Information Specialist of the Cochrane Lung Cancer Group and included the Cochrane Lung Cancer Group Trial Register, Cochrane Central Register of Controlled Trials (CENTRAL, the Cochrane Library, current issue), MEDLINE (accessed via PubMed) and Embase in our search. We also searched the clinical trial registries to identify unpublished and ongoing trials. We did not impose any restriction on language of publication. The search was performed up to 31 July 2021. SELECTION CRITERIA: Randomised controlled trials (RCTs) of lung cancer screening using LDCT and reporting mortality or harm outcomes. DATA COLLECTION AND ANALYSIS: Two review authors were involved in independently assessing trials for eligibility, extraction of trial data and characteristics, and assessing risk of bias of the included trials using the Cochrane RoB 1 tool. We assessed the certainty of evidence using GRADE. Primary outcomes were lung cancer-related mortality and harms of screening. We performed a meta-analysis, where appropriate, for all outcomes using a random-effects model. We only included trials in the analysis of mortality outcomes if they had at least 5 years of follow-up. We reported risk ratios (RRs) and hazard ratios (HRs), with 95% confidence intervals (CIs) and used the I2 statistic to investigate heterogeneity. MAIN RESULTS: We included 11 trials in this review with a total of 94,445 participants. Trials were conducted in Europe and the USA in people aged 40 years or older, with most trials having an entry requirement of ≥ 20 pack-year smoking history (e.g. 1 pack of cigarettes/day for 20 years or 2 packs/day for 10 years etc.). One trial included male participants only. Eight trials were phase three RCTs, with two feasibility RCTs and one pilot RCT. Seven of the included trials had no screening as a comparison, and four trials had CXR screening as a comparator. Screening frequency included annual, biennial and incrementing intervals. The duration of screening ranged from 1 year to 10 years. Mortality follow-up was from 5 years to approximately 12 years. None of the included trials were at low risk of bias across all domains. The certainty of evidence was moderate to low across different outcomes, as assessed by GRADE. In the meta-analysis of trials assessing lung cancer-related mortality, we included eight trials (91,122 participants), and there was a reduction in mortality of 21% with LDCT screening compared to control groups of no screening or CXR screening (RR 0.79, 95% CI 0.72 to 0.87; 8 trials, 91,122 participants; moderate-certainty evidence). There were probably no differences in subgroups for analyses by control type, sex, geographical region, and nodule management algorithm. Females appeared to have a larger lung cancer-related mortality benefit compared to males with LDCT screening. There was also a reduction in all-cause mortality (including lung cancer-related) of 5% (RR 0.95, 95% CI 0.91 to 0.99; 8 trials, 91,107 participants; moderate-certainty evidence). Invasive tests occurred more frequently in the LDCT group (RR 2.60, 95% CI 2.41 to 2.80; 3 trials, 60,003 participants; moderate-certainty evidence). However, analysis of 60-day postoperative mortality was not significant between groups (RR 0.68, 95% CI 0.24 to 1.94; 2 trials, 409 participants; moderate-certainty evidence). False-positive results and recall rates were higher with LDCT screening compared to screening with CXR, however there was low-certainty evidence in the meta-analyses due to heterogeneity and risk of bias concerns. Estimated overdiagnosis with LDCT screening was 18%, however the 95% CI was 0 to 36% (risk difference (RD) 0.18, 95% CI -0.00 to 0.36; 5 trials, 28,656 participants; low-certainty evidence). Four trials compared different aspects of health-related quality of life (HRQoL) using various measures. Anxiety was pooled from three trials, with participants in LDCT screening reporting lower anxiety scores than in the control group (standardised mean difference (SMD) -0.43, 95% CI -0.59 to -0.27; 3 trials, 8153 participants; low-certainty evidence). There were insufficient data to comment on the impact of LDCT screening on smoking behaviour. AUTHORS' CONCLUSIONS: The current evidence supports a reduction in lung cancer-related mortality with the use of LDCT for lung cancer screening in high-risk populations (those over the age of 40 with a significant smoking exposure). However, there are limited data on harms and further trials are required to determine participant selection and optimal frequency and duration of screening, with potential for significant overdiagnosis of lung cancer. Trials are ongoing for lung cancer screening in non-smokers.
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Affiliation(s)
- Asha Bonney
- Department of Respiratory and Sleep Medicine, Royal Melbourne Hospital, Parkville, Australia
- Department of Medicine, University of Melbourne, Melbourne, Australia
| | - Reem Malouf
- National Perinatal Epidemiology Unit (NPEU), University of Oxford, Oxford, UK
| | | | - David Manners
- Respiratory Medicine, Midland St John of God Public and Private Hospital, Midland, Australia
| | - Kwun M Fong
- Thoracic Medicine Program, The Prince Charles Hospital, Brisbane, Australia
- UQ Thoracic Research Centre, School of Medicine, The University of Queensland, Brisbane, Australia
| | - Henry M Marshall
- School of Medicine, The University of Queensland, Brisbane, Australia
| | - Louis B Irving
- Department of Respiratory and Sleep Medicine, Royal Melbourne Hospital, Parkville, Australia
| | - Renée Manser
- Department of Respiratory and Sleep Medicine, Royal Melbourne Hospital, Parkville, Australia
- Department of Haematology and Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, Australia
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Yang X, Dorrius MD, Jiang W, Nie Z, Vliegenthart R, Groen HJM, Heuvelmans MA, Sidorenkov G, Vonder M, Ye Z, de Bock GH. Association between visual emphysema and lung nodules on low-dose CT scan in a Chinese Lung Cancer Screening Program (Nelcin-B3). Eur Radiol 2022; 32:8162-8170. [PMID: 35678862 DOI: 10.1007/s00330-022-08884-3] [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: 03/25/2022] [Revised: 03/25/2022] [Accepted: 05/13/2022] [Indexed: 11/26/2022]
Abstract
OBJECTIVES This study aimed to evaluate the association between visual emphysema and the presence of lung nodules, and Lung-RADS category with low-dose CT (LDCT). METHODS Baseline LDCT scans of 1162 participants from a lung cancer screening study (Nelcin-B3) performed in a Chinese general population were included. The presence, subtypes, and severity of emphysema (at least trace) were visually assessed by one radiologist. The presence, size, and classification of non-calcified lung nodules (≥ 30 mm3) and Lung-RADS category were independently assessed by another two radiologists. Multivariable logistic regression and stratified analyses were performed to estimate the association between emphysema and lung nodules, Lung-RADS category, after adjusting for age, sex, BMI, smoking status, pack-years, and passive smoking. RESULTS Emphysema and lung nodules were observed in 674 (58.0%) and 424 (36.5%) participants, respectively. Participants with emphysema had a 71% increased risk of having lung nodules (adjusted odds ratios, aOR: 1.71, 95% CI: 1.26-2.31) and 70% increased risk of positive Lung-RADS category (aOR: 1.70, 95% CI: 1.09-2.66) than those without emphysema. Participants with paraseptal emphysema (n = 47, 4.0%) were at a higher risk for lung nodules than those with centrilobular emphysema (CLE) (aOR: 2.43, 95% CI: 1.32-4.50 and aOR: 1.60, 95% CI: 1.23-2.09, respectively). Only CLE was associated with positive Lung-RADS category (p = 0.02). CLE severity was related to a higher risk of lung nodules (ranges aOR: 1.44-2.61, overall p < 0.01). CONCLUSION In a Chinese general population, visual emphysema based on LDCT is independently related to the presence of lung nodules (≥ 30 mm3) and specifically CLE subtype is related to positive Lung-RADS category. The risk of lung nodules increases with CLE severity. KEY POINTS • Participants with emphysema had an increased risk of having lung nodules, especially smokers. • Participants with PSE were at a higher risk for lung nodules than those with CLE, but nodules in participants with CLE had a higher risk of positive Lung-RADS category. • The risk of lung nodules increases with CLE severity.
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Affiliation(s)
- Xiaofei Yang
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, P.O. Box 30 001, FA 40, 9700, RB, Groningen, The Netherlands
| | - Monique D Dorrius
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, P.O. Box 30 001, FA 40, 9700, RB, Groningen, The Netherlands
- Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Wenzhen Jiang
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Huanhuxi Road, Hexi District, Tianjin, 300060, China
| | - Zhenhui Nie
- Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Rozemarijn Vliegenthart
- Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Harry J M Groen
- Department of Pulmonary Diseases, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Marjolein A Heuvelmans
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, P.O. Box 30 001, FA 40, 9700, RB, Groningen, The Netherlands
| | - Grigory Sidorenkov
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, P.O. Box 30 001, FA 40, 9700, RB, Groningen, The Netherlands
| | - Marleen Vonder
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, P.O. Box 30 001, FA 40, 9700, RB, Groningen, The Netherlands
| | - Zhaoxiang Ye
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Huanhuxi Road, Hexi District, Tianjin, 300060, China.
| | - Geertruida H de Bock
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, P.O. Box 30 001, FA 40, 9700, RB, Groningen, The Netherlands.
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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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Tang W, Lu L, Gu JW, Chen HL. Some Thoughts Concerning the Patient Adherence to Lung Computed Tomography Screening Reporting and Data System–Recommended Screening Intervals. J Thorac Oncol 2022; 17:e45-e46. [DOI: 10.1016/j.jtho.2021.11.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 11/13/2021] [Indexed: 10/18/2022]
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Ziegelmayer S, Graf M, Makowski M, Gawlitza J, Gassert F. Cost-Effectiveness of Artificial Intelligence Support in Computed Tomography-Based Lung Cancer Screening. Cancers (Basel) 2022; 14:cancers14071729. [PMID: 35406501 PMCID: PMC8997030 DOI: 10.3390/cancers14071729] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 03/23/2022] [Accepted: 03/23/2022] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Lung cancer screening is already implemented in the USA and strongly recommended by European Radiological and Thoracic societies as well. Upon implementation, the total number of thoracic computed tomographies (CT) is likely to rise significantly. As shown in previous studies, modern artificial intelligence-based algorithms are on-par or even exceed radiologist's performance in lung nodule detection and classification. Therefore, the aim of this study was to evaluate the cost-effectiveness of an AI-based system in the context of baseline lung cancer screening. METHODS In this retrospective study, a decision model based on Markov simulation was developed to estimate the quality-adjusted life-years (QALYs) and lifetime costs of the diagnostic modalities. Literature research was performed to determine model input parameters. Model uncertainty and possible costs of the AI-system were assessed using deterministic and probabilistic sensitivity analysis. RESULTS In the base case scenario CT + AI resulted in a negative incremental cost-effectiveness ratio (ICER) as compared to CT only, showing lower costs and higher effectiveness. Threshold analysis showed that the ICER remained negative up to a threshold of USD 68 for the AI support. The willingness-to-pay of USD 100,000 was crossed at a value of USD 1240. Deterministic and probabilistic sensitivity analysis showed model robustness for varying input parameters. CONCLUSION Based on our results, the use of an AI-based system in the initial low-dose CT scan of lung cancer screening is a feasible diagnostic strategy from a cost-effectiveness perspective.
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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. Radiol Med 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] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [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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May M, Heiss R, Koehnen J, Wetzl M, Wiesmueller M, Treutlein C, Braeuer L, Uder M, Kopp M. Personalized Chest Computed Tomography: Minimum Diagnostic Radiation Dose Levels for the Detection of Fibrosis, Nodules, and Pneumonia. Invest Radiol 2022; 57:148-156. [PMID: 34468413 PMCID: PMC8826613 DOI: 10.1097/rli.0000000000000822] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 07/13/2021] [Accepted: 07/13/2021] [Indexed: 01/08/2023]
Abstract
OBJECTIVES The purpose of this study was to evaluate the minimum diagnostic radiation dose level for the detection of high-resolution (HR) lung structures, pulmonary nodules (PNs), and infectious diseases (IDs). MATERIALS AND METHODS A preclinical chest computed tomography (CT) trial was performed with a human cadaver without known lung disease with incremental radiation dose using tin filter-based spectral shaping protocols. A subset of protocols for full diagnostic evaluation of HR, PN, and ID structures was translated to clinical routine. Also, a minimum diagnostic radiation dose protocol was defined (MIN). These protocols were prospectively applied over 5 months in the clinical routine under consideration of the individual clinical indication. We compared radiation dose parameters, objective and subjective image quality (IQ). RESULTS The HR protocol was performed in 38 patients (43%), PN in 21 patients (24%), ID in 20 patients (23%), and MIN in 9 patients (10%). Radiation dose differed significantly among HR, PN, and ID (5.4, 1.2, and 0.6 mGy, respectively; P < 0.001). Differences between ID and MIN (0.2 mGy) were not significant (P = 0.262). Dose-normalized contrast-to-noise ratio was comparable among all groups (P = 0.087). Overall IQ was perfect for the HR protocol (median, 5.0) and decreased for PN (4.5), ID-CT (4.3), and MIN-CT (2.5). The delineation of disease-specific findings was high in all dedicated protocols (HR, 5.0; PN, 5.0; ID, 4.5). The MIN protocol had borderline IQ for PN and ID lesions but was insufficient for HR structures. The dose reductions were 78% (PN), 89% (ID), and 97% (MIN) compared with the HR protocols. CONCLUSIONS Personalized chest CT tailored to the clinical indications leads to substantial dose reduction without reducing interpretability. More than 50% of patients can benefit from such individual adaptation in a clinical routine setting. Personalized radiation dose adjustments with validated diagnostic IQ are especially preferable for evaluating ID and PN lesions.
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Affiliation(s)
- Matthias May
- From the Department of Radiology, University Hospital Erlangen
| | - Rafael Heiss
- From the Department of Radiology, University Hospital Erlangen
| | - Julia Koehnen
- From the Department of Radiology, University Hospital Erlangen
| | - Matthias Wetzl
- From the Department of Radiology, University Hospital Erlangen
| | | | | | - Lars Braeuer
- Institute of Anatomy, Chair II, Friedrich Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Michael Uder
- From the Department of Radiology, University Hospital Erlangen
| | - Markus Kopp
- From the Department of Radiology, University Hospital Erlangen
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Predictors of Invasive Adenocarcinomas among Pure Ground-Glass Nodules Less Than 2 cm in Diameter. Cancers (Basel) 2021; 13:cancers13163945. [PMID: 34439100 PMCID: PMC8391557 DOI: 10.3390/cancers13163945] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 07/26/2021] [Accepted: 08/02/2021] [Indexed: 12/19/2022] Open
Abstract
Simple Summary Benign lesions, atypical adenomatous hyperplasia, and malignancies such as adenocarcinoma in situ, minimally invasive adenocarcinoma, and invasive adenocarcinoma may feature pure ground-glass nodules on chest CT images, and the prognosis of patients with invasive adenocarcinoma is worse than others. The early detection and adequate management of invasive adenocarcinoma is crucial, but the pathology diagnosis of small nodules is difficult to obtain without surgery. Our study aimed to analyze the CT characteristics of pure ground-glass nodules <2 cm for the identification of invasive adenocarcinomas. A total of 181 nodules in 171 patients were enrolled. The larger size, lobulation, and air cavity were significantly more common in invasive adenocarcinoma. The air cavity is the significant predictor in multivariate analysis. In conclusion, the possibility of invasive adenocarcinoma is higher in a pure ground-glass nodules when it is associated with a larger size, lobulation, and air cavity. Abstract Benign lesions, atypical adenomatous hyperplasia (AAH), and malignancies such as adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IA) may feature a pure ground-glass nodule (pGGN) on a thin-slide computed tomography (CT) image. According to the World Health Organization (WHO) classification for lung cancer, the prognosis of patients with IA is worse than those with AIS and MIA. It is relatively risky to perform a core needle biopsy of a pGGN less than 2 cm to obtain a reliable pathological diagnosis. The early and adequate management of patients with IA may provide a favorable prognosis. This study aimed to disclose suggestive signs of CT to accurately predict IA among the pGGNs. A total of 181 pGGNs of less than 2 cm, in 171 patients who had preoperative CT-guided localization for surgical excision of a lung nodule between December 2013 and August 2019, were enrolled. All had CT images of 0.625 mm slice thickness during CT-guided intervention to confirm that the nodules were purely ground glass. The clinical data, CT images, and pathological reports of those 171 patients were reviewed. The CT findings of pGGNs including the location, the maximal diameter in the long axis (size-L), the maximal short axis diameter perpendicular to the size-L (size-S), and the mean value of long and short axis diameters (size-M), internal content, shape, interface, margin, lobulation, spiculation, air cavity, vessel relationship, and pleural retraction were recorded and analyzed. The final pathological diagnoses of the 181 pGGNs comprised 29 benign nodules, 14 AAHs, 25 AISs, 55 MIAs, and 58 IAs. Statistical analysis showed that there were significant differences among the aforementioned five groups with respect to size-L, size-S, and size-M (p = 0.029, 0.043, 0.025, respectively). In the univariate analysis, there were significant differences between the invasive adenocarcinomas and the non-invasive adenocarcinomas with respect to the size-L, size-S, size-M, lobulation, and air cavity (p = 0.009, 0.016, 0.008, 0.031, 0.004, respectively) between the invasive adenocarcinomas and the non-invasive adenocarcinomas. The receiver operating characteristic (ROC) curve of size for discriminating invasive adenocarcinoma also revealed similar area under curve (AUC) values among size-L (0.620), size-S (0.614), and size-M (0.623). The cut-off value of 7 mm in size-M had a sensitivity of 50.0% and a specificity of 76.4% for detecting IAs. In the multivariate analysis, the presence of air cavity was a significant predictor of IA (p = 0.042). In conclusion, the possibility of IA is higher in a pGGN when it is associated with a larger size, lobulation, and air cavity. The air cavity is the significant predictor of IA.
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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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