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Brok JS, Shelmerdine S, Damsgaard F, Smets A, Irtan S, Swinson S, Hedayati V, Jacob J, Nair A, Oostveen M, Pritchard-Jones K, Olsen Ø. The clinical impact of observer variability in lung nodule classification in children with Wilms tumour. Pediatr Blood Cancer 2022; 69:e29759. [PMID: 35652617 PMCID: PMC7615195 DOI: 10.1002/pbc.29759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 04/10/2022] [Accepted: 04/18/2022] [Indexed: 11/11/2022]
Abstract
OBJECTIVES To investigate the extent to which observer variability of computed tomography (CT) lung nodule assessment may affect clinical treatment stratification in Wilms tumour (WT) patients, according to the recent Société Internationale d'Oncologie Pédiatrique Renal Tumour Study Group (SIOP-RTSG) UMBRELLA protocol. METHODS I: CT thoraces of children with WT submitted for central review were used to estimate size distribution of lung metastases. II: Scans were selected for blinded review by five radiologists to determine intra- and inter-observer variability. They assessed identical scans on two occasions 6 months apart. III: Monte Carlo simulation (MCMC) was used to predict the clinical impact of observer variation when applying the UMBRELLA protocol size criteria. RESULTS Lung nodules were found in 84 out of 360 (23%) children with WT. For 21 identified lung nodules, inter-observer limits of agreement (LOA) for the five readers were ±2.4 and ±1.4 mm (AP diameter), ±1.9 and ±1.8 mm (TS diameter) and ±2.0 and ±2.4 mm (LS diameter) at assessments 1 and 2. Intra-observer LOA across the three dimensions were ±1.5, ±2.2, ±3.5, ±3.1 and ±2.6 mm (readers 1-5). MCMC demonstrated that 17% of the patients with a 'true' nodule size of ≥3 mm will be scored as <3 mm, and 21% of the patients with a 'true' nodule size of <3 mm will be scored as being ≥3 mm. CONCLUSION A significant intra-inter observer variation was found when measuring lung nodules on CT for patients with WT. This may have significant implications on treatment stratification, and thereby outcome, when applying a threshold of ≥3 mm for a lung nodule to dictate metastatic status.
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Affiliation(s)
- Jesper Sune Brok
- Department of Paediatric Haematology and Oncology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
- UCL Great Ormond Street Institute of Child Health, London, UK
| | - Susan Shelmerdine
- Department of Clinical Radiology, Great Ormond Street Hospital for Children NHS foundation Trust, London, UK
- UCL Great Ormond Street Institute of Child Health, London, UK
| | - Frederikke Damsgaard
- Department of Paediatric Haematology and Oncology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Anne Smets
- Department of Radiology, Amsterdam University Medical Centre, Amsterdam, The Netherlands
| | - Sabine Irtan
- Department of Visceral and Neonatal Paediatric Surgery, Sorbonne University, Armand Trousseau Hospital - APHP, Paris, France
| | | | - Venus Hedayati
- King’s College Hospital NHS Foundation Trust, London, UK
| | - Joseph Jacob
- Centre for Medical Image Computing, University College London, London, UK
- Department of Respiratory Medicine, University College London, London, UK
| | - Arjun Nair
- University College London Hospitals NHS Foundation Trust, London, UK
| | - Minou Oostveen
- UCL Great Ormond Street Institute of Child Health, London, UK
| | | | - Øystein Olsen
- Department of Clinical Radiology, Great Ormond Street Hospital for Children NHS foundation Trust, London, UK
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Liang TI, Lee EY. Pediatric Pulmonary Nodules: Imaging Guidelines and Recommendations. Radiol Clin North Am 2021; 60:55-67. [PMID: 34836566 DOI: 10.1016/j.rcl.2021.08.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Incidental pulmonary nodules are not infrequently identified on computed tomography imaging in the pediatric population and can be a challenge in suggesting appropriate follow-up recommendations. An evidence-based and practical imaging approach for diagnosis and appropriate directed management is essential for optimal patient care. This article provides an up-to-date review of the pediatric pulmonary nodule literature and suggests a practical algorithm to manage pulmonary nodules in the pediatric population.
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Affiliation(s)
- Teresa I Liang
- Department of Radiology & Diagnostic Imaging, Stollery Children's Hospital and University of Alberta, 8440 112 Street NW, Edmonton, AB T6G 2B7, Canada.
| | - Edward Y Lee
- Department of Radiology, Boston Children's Hospital, Harvard Medical School, 330 Longwood Avenue, Boston, MA 02115, USA
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Comparison of 0.3-mSv CT to Standard-Dose CT for Detection of Lung Nodules in Children and Young Adults With Cancer. AJR Am J Roentgenol 2021; 217:1444-1451. [PMID: 34232694 DOI: 10.2214/ajr.21.26183] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Background: CT is the imaging modality of choice to identify lung metastasis. Objective: The purpose of this study was to evaluate the performance of reduced-dose CT for detection of lung nodules in children and young adults with cancer. Methods: This prospective study enrolled patients 4-21 years old with known or suspected malignancy who were undergoing clinically indicated chest CT. Study participants underwent an additional investigational reduced-dose chest CT in the same imaging encounter. Separated deidentified CT examinations were reviewed in blinded fashion by three independent radiologists. One reviewer performed a subsequent secondary review to match nodules between the standard- and reduced-dose examinations. Diagnostic performance was computed for the reduced-dose examinations, using clinical examinations as reference standard. Intraobserver and interobserver agreement were calculated using Cohen's Kappa. Results: A total of 78 patients (44 male, 34 female; mean age 15.2±3.8 years) were enrolled. Mean estimated effective dose was 1.8±1.1 mSv for clinical CT and 0.3±0.1 mSv for reduced-dose CT, an 83% reduction. Forty-five (58%) patients had 162 total lung nodules (mean size 3.4±3.3 mm) detected on the clinical CT examinations. A total of 92% of nodules were visible on reduced-dose CT. Sensitivity and specificity of reduced-dose CT for nodules ranged from 63%-77% and 80%-90% respectively across the three reviewers. Intraobserver agreement between clinical and reduced-dose CT was moderate to substantial for presence of nodules (κ=0.45-0.67), and good to excellent for number of nodules (κ=0.68-0.84) and nodule size (κ=0.69-0.86). Interobserver agreement for the presence of nodules was moderate for both reduced-dose (κ=0.53) and clinical (κ=0.54) CT. A median of 1 nodule was present on clinical CT in patients with a falsely negative reduced-dose CT examination. Conclusion: Reduced-dose CT depicts greater than 90% of lung nodules in children and young adults with cancer. Reviewers identified the presence of nodules with moderate sensitivity and high specificity. Clinical Impact: CT performed at 0.3 mSv mean effective dose has acceptable diagnostic performance for lung nodule detection in children and young adults and has the potential to reduce patient dose or expand CT utilization (e.g., to replace radiography in screening or monitoring protocols).
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Naeem MQ, Darira J, Ahmed MS, Hamid K, Ali M, Shazlee MK. Comparison of Maximum Intensity Projection and Volume Rendering in Detecting Pulmonary Nodules on Multidetector Computed Tomography. Cureus 2021; 13:e14025. [PMID: 33898115 PMCID: PMC8057938 DOI: 10.7759/cureus.14025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
Introduction Lung cancer is the most common cancer overall, and the foremost cause of cancer-related mortality. Almost all lung cancers evolve from pulmonary nodules. As multidetector CT (MDCT) scanners are now widely available, there is an increased rate of detection of pulmonary nodules. It is of utmost importance to evaluate pulmonary nodules to rule out the possibility of neoplastic diseases. With advancements in technology, there are various manual and automatic analytic software providing a wide range of post-processing techniques. Maximum intensity projection (MIP) and volume rendering (VR) techniques have been analyzed previously regarding pulmonary nodules but there is a scarcity of data in terms of low-density nodules. This study aims to delineate the comparison and supremacy of both techniques in terms of low-density nodules. Methodology The current prospective study was conducted from June 2019 to June 2020 in the Radiology Department at Dr. Ziauddin Hospital, Karachi. Chest CT scans were performed on 16 slice MDCT (Alexion 16 Multi-slice, Toshiba Medical System Corporation, Houston, TX). A consultant radiologist of six years experience and a postgraduate trainee of three years experience analyzed each patient on a workstation (Vitrea 6.2.0, Vital Images, Minnetonka, MN). SPSS 23.0 (SPSS Inc., Chicago, IL) was incorporated for data analysis. Data were expressed in the median and interquartile range (IQR). Data collected for this study were analyzed using analyzing the median difference in nodule count using Wilcoxon's signed-rank test. A p-value of <0.05 was considered significant. Results After informed consent, 236 patients were recruited for the study. MIP outperformed VR in terms of nodule detection and low-density nodules at each evaluated slab thicknesses (p<0.001). A 10-mm MIP was superior to all other techniques in terms of detection of pulmonary nodules and low-density nodules (p<0.001). MIP was also considered an easier technique as there was excellent inter-rater reliability and agreement. Conclusion This study is robust evidence regarding the supremacy of MIP. MIP outperformed VR on every slab thicknesses. The 10-mm MIP technique was superior to all others evaluated and was recorded to be an easier analyzing technique.
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Affiliation(s)
| | - Jaideep Darira
- Diagnostic Radiology, Dr. Ziauddin Hospital, Karachi, PAK
| | | | - Kamran Hamid
- Diagnostic Radiology, Dr. Ziauddin Hospital, Karachi, PAK
| | - Muhammad Ali
- Diagnostic Radiology, Dr. Ziauddin Hospital, Karachi, PAK
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Schreuder A, Jacobs C, Scholten ET, van Ginneken B, Schaefer-Prokop CM, Prokop M. Typical CT Features of Intrapulmonary Lymph Nodes: A Review. Radiol Cardiothorac Imaging 2020; 2:e190159. [PMID: 33778597 DOI: 10.1148/ryct.2020190159] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Revised: 04/02/2020] [Accepted: 04/28/2020] [Indexed: 12/26/2022]
Abstract
Several studies investigated the appearance of intrapulmonary lymph nodes (IPLNs) at CT with pathologic correlation. IPLNs are benign lesions and do not require follow-up after initial detection. There are indications that IPLNs represent a considerable portion of incidentally found pulmonary nodules seen at high-resolution CT. The reliable and accurate identification of IPLNs as benign nodules may substantially reduce the number of unnecessary follow-up CT examinations. Typical CT features of IPLNs are a noncalcified solid nodule with sharp margins; a round, oval, or polygonal shape; distanced 15 mm or less from the pleura; and most being located below the level of the carina. The term perifissural nodule (PFN) was coined based on some of these characteristics. Standardization of those CT criteria are a prerequisite for accurate nodule classification. However, four different definitions of PFNs can currently be found in the literature. Furthermore, there is considerable variation in the reported interobserver agreement, malignancy rate, and prevalence of PFNs. The purpose of this review was to provide an overview of what is known about PFNs. In addition, knowledge gaps in defining PFNs will be discussed. A decision tree to guide clinicians in classifying nodules as PFNs is provided. Supplemental material is available for this article. © RSNA, 2020 See also the commentary by White and Rubin in this issue.
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Affiliation(s)
- Anton Schreuder
- Diagnostic Image Analysis Group, Department of Radiology, Nuclear Medicine, and Anatomy, Radboudumc, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands (A.S., C.J., E.T.S., B.v.G., C.M.S.P., M.P.); Fraunhofer MEVIS, Bremen, Germany (C.J., B.v.G.); and Department of Radiology, Meander Medisch Centrum, Amersfoort, the Netherlands (C.M.S.P.)
| | - Colin Jacobs
- Diagnostic Image Analysis Group, Department of Radiology, Nuclear Medicine, and Anatomy, Radboudumc, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands (A.S., C.J., E.T.S., B.v.G., C.M.S.P., M.P.); Fraunhofer MEVIS, Bremen, Germany (C.J., B.v.G.); and Department of Radiology, Meander Medisch Centrum, Amersfoort, the Netherlands (C.M.S.P.)
| | - Ernst T Scholten
- Diagnostic Image Analysis Group, Department of Radiology, Nuclear Medicine, and Anatomy, Radboudumc, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands (A.S., C.J., E.T.S., B.v.G., C.M.S.P., M.P.); Fraunhofer MEVIS, Bremen, Germany (C.J., B.v.G.); and Department of Radiology, Meander Medisch Centrum, Amersfoort, the Netherlands (C.M.S.P.)
| | - Bram van Ginneken
- Diagnostic Image Analysis Group, Department of Radiology, Nuclear Medicine, and Anatomy, Radboudumc, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands (A.S., C.J., E.T.S., B.v.G., C.M.S.P., M.P.); Fraunhofer MEVIS, Bremen, Germany (C.J., B.v.G.); and Department of Radiology, Meander Medisch Centrum, Amersfoort, the Netherlands (C.M.S.P.)
| | - Cornelia M Schaefer-Prokop
- Diagnostic Image Analysis Group, Department of Radiology, Nuclear Medicine, and Anatomy, Radboudumc, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands (A.S., C.J., E.T.S., B.v.G., C.M.S.P., M.P.); Fraunhofer MEVIS, Bremen, Germany (C.J., B.v.G.); and Department of Radiology, Meander Medisch Centrum, Amersfoort, the Netherlands (C.M.S.P.)
| | - Mathias Prokop
- Diagnostic Image Analysis Group, Department of Radiology, Nuclear Medicine, and Anatomy, Radboudumc, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands (A.S., C.J., E.T.S., B.v.G., C.M.S.P., M.P.); Fraunhofer MEVIS, Bremen, Germany (C.J., B.v.G.); and Department of Radiology, Meander Medisch Centrum, Amersfoort, the Netherlands (C.M.S.P.)
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