Literature DB >> 31711024

Lung cancer screening with submillisievert chest CT: Potential pitfalls of pulmonary findings in different readers with various experience levels.

Katharina Martini1, Thorsten Ottilinger2, Bettina Serrallach2, Stefan Markart2, Nicola Glaser-Gallion2, Christian Blüthgen1, Sebastian Leschka3, Ralf W Bauer4, Simon Wildermuth2, Michael Messerli5.   

Abstract

PURPOSE: To assess the interreader variability of submillisievert CT for lung cancer screening in radiologists with various experience levels.
METHOD: Six radiologists with different degrees of clinical experience in radiology (range, 1-15 years), rated 100 submillisievert CT chest studies as either negative screening finding (no nodules, benign nodules, nodules <5 mm), indeterminate finding (nodules 5-10 mm), positive finding (nodules >10 mm). Each radiologist interpreted scans randomly ordered and reading time was recorded. Interobserver agreement was assessed with ak statistic. Reasons for differences in nodule classification were analysed on a case-by-case basis. Reading time was correlated with reader experience using Pearson correlation (r).
RESULTS: The overall interobserver agreement between all readers was moderate (k = 0.454; p < 0.001). In 57 patients, all radiologists agreed on the differentiation of negative and indeterminate/positive finding. In 64 cases disagreement between readers led to different nodule classification. In 8 cases some readers rated the nodule as benign, whereas others scored the case as positive. Overall, disagreement in nodule classification was mostly due to failure in identification of target lesion (n = 40), different lesion measurement (n = 44) or different classification (n = 26). Mean overall reading time per scan was of 2 min 2 s (range: 7s-7 min 45 s) and correlated with reader-experience (r = -0.824).
CONCLUSIONS: Our study showed substantial interobserver variability for the detection and classification of pulmonary nodules in submillisievert CT. This highlights the importance for careful standardisation of screening programs with the objective of harmonizing efforts of involved radiologists across different institutions by defining and assuring quality standards.
Copyright © 2019. Published by Elsevier B.V.

Entities:  

Keywords:  CT; Iterative reconstruction; Low dose; Lung cancer; Radiation dosage; Screening

Mesh:

Year:  2019        PMID: 31711024     DOI: 10.1016/j.ejrad.2019.108720

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  7 in total

1.  Community-based Lung Cancer Screening Results in Relation to Patient and Radiologist Characteristics: The PROSPR Consortium.

Authors:  Andrea N Burnett-Hartman; Nikki M Carroll; Stacey A Honda; Caroline Joyce; Nandita Mitra; Christine Neslund-Dudas; Oluwatosin Olaiya; Katharine A Rendle; Mitchell D Schnall; Anil Vachani; Debra P Ritzwoller
Journal:  Ann Am Thorac Soc       Date:  2022-03

2.  Observer Performance for Detection of Pulmonary Nodules at Chest CT over a Large Range of Radiation Dose Levels.

Authors:  Joel G Fletcher; David L Levin; Anne-Marie G Sykes; Rebecca M Lindell; Darin B White; Ronald S Kuzo; Vighnesh Suresh; Lifeng Yu; Shuai Leng; David R Holmes; Akitoshi Inoue; Matthew P Johnson; Rickey E Carter; Cynthia H McCollough
Journal:  Radiology       Date:  2020-09-29       Impact factor: 11.105

3.  Low-dose CT with tin filter combined with iterative metal artefact reduction for guiding lung biopsy.

Authors:  Jing Zhang; Meiling Liu; Daihong Liu; Xiaoqin Li; Meng Lin; Yong Tan; Yuesheng Luo; Xiangfei Zeng; Hong Yu; Hesong Shen; Xiaoxia Wang; Leilei Liu; Yuchuan Tan; Jiuquan Zhang
Journal:  Quant Imaging Med Surg       Date:  2022-02

Review 4.  Latest CT technologies in lung cancer screening: protocols and radiation dose reduction.

Authors:  Marleen Vonder; Monique D Dorrius; Rozemarijn Vliegenthart
Journal:  Transl Lung Cancer Res       Date:  2021-02

5.  Personalized Chest Computed Tomography: Minimum Diagnostic Radiation Dose Levels for the Detection of Fibrosis, Nodules, and Pneumonia.

Authors:  Matthias May; Rafael Heiss; Julia Koehnen; Matthias Wetzl; Marco Wiesmueller; Christoph Treutlein; Lars Braeuer; Michael Uder; Markus Kopp
Journal:  Invest Radiol       Date:  2022-03-01       Impact factor: 6.016

6.  Lung cancer screening by volume computed tomography: thriving to high performance.

Authors:  Eline Schillebeeckx; Kevin Lamote
Journal:  Breathe (Sheff)       Date:  2021-12

7.  Higher agreement between readers with deep learning CAD software for reporting pulmonary nodules on CT.

Authors:  H L Hempel; M P Engbersen; J Wakkie; B J van Kelckhoven; W de Monyé
Journal:  Eur J Radiol Open       Date:  2022-08-02
  7 in total

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