Literature DB >> 27842670

Computer-aided detection (CAD) of solid pulmonary nodules in chest x-ray equivalent ultralow dose chest CT - first in-vivo results at dose levels of 0.13mSv.

Michael Messerli1, Thomas Kluckert2, Meinhard Knitel2, Fabian Rengier3, René Warschkow4, Hatem Alkadhi5, Sebastian Leschka6, Simon Wildermuth2, Ralf W Bauer2.   

Abstract

OBJECTIVES: To determine the value of computer-aided detection (CAD) for solid pulmonary nodules in ultralow radiation dose single-energy computed tomography (CT) of the chest using third-generation dual-source CT at 100kV and fixed tube current at 70 mAs with tin filtration.
METHODS: 202 consecutive patients undergoing clinically indicated standard dose chest CT (1.8±0.7 mSv) were prospectively included and scanned with an additional ultralow dose CT (0.13±0.01 mSv) in the same session. Standard of reference (SOR) was established by consensus reading of standard dose CT by two radiologists. CAD was performed in standard dose and ultralow dose CT with two different reconstruction kernels. CAD detection rate of nodules was evaluated including subgroups of different nodule sizes (<5, 5-7, >7mm). Sensitivity was further analysed in multivariable mixed effects logistic regression.
RESULTS: The SOR included 279 solid nodules (mean diameter 4.3±3.4mm, range 1-24mm). There was no significant difference in per-nodule sensitivity of CAD in standard dose with 70% compared to 68% in ultralow dose CT both overall and in different size subgroups (all p>0.05). CAD led to a significant increase of sensitivity for both radiologists reading the ultralow dose CT scans (all p<0.001). In multivariable analysis, the use of CAD (p<0.001), and nodule size (p<0.0001) were independent predictors for nodule detection, but not BMI (p=0.933) and the use of contrast agents (p=0.176).
CONCLUSIONS: Computer-aided detection of solid pulmonary nodules using ultralow dose CT with chest X-ray equivalent radiation dose has similar sensitivities to those from standard dose CT. Adding CAD in ultralow dose CT significantly improves the sensitivity of radiologists.
Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Computed tomography; Iterative reconstruction; Pulmonary nodule; Radiation dosage; Tin filtration

Mesh:

Substances:

Year:  2016        PMID: 27842670     DOI: 10.1016/j.ejrad.2016.10.006

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


  10 in total

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Authors:  Mario Silva; Gianluca Milanese; Valeria Seletti; Alarico Ariani; Nicola Sverzellati
Journal:  Br J Radiol       Date:  2018-01-12       Impact factor: 3.039

2.  Differential Diagnosis of Preinvasive Lesions in Small Pulmonary Nodules by Dual Source Computed Tomography Imaging.

Authors:  Hongjun Yan; Ye Hua; Tingcui Zhang; Wen Liu
Journal:  Comput Math Methods Med       Date:  2022-07-04       Impact factor: 2.809

3.  Cascaded deep learning classifiers for computer-aided diagnosis of COVID-19 and pneumonia diseases in X-ray scans.

Authors:  Mohamed Esmail Karar; Ezz El-Din Hemdan; Marwa A Shouman
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4.  Diagnostic accuracy of chest X-ray dose-equivalent CT for assessing calcified atherosclerotic burden of the thoracic aorta.

Authors:  Michael Messerli; Andreas A Giannopoulos; Sebastian Leschka; René Warschkow; Simon Wildermuth; Lukas Hechelhammer; Ralf W Bauer
Journal:  Br J Radiol       Date:  2017-10-03       Impact factor: 3.039

5.  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

6.  Diagnostic validation of a deep learning nodule detection algorithm in low-dose chest CT: determination of optimized dose thresholds in a virtual screening scenario.

Authors:  Alan A Peters; Adrian T Huber; Verena C Obmann; Johannes T Heverhagen; Andreas Christe; Lukas Ebner
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7.  Early detection of lung cancer in Czech high-risk asymptomatic individuals (ELEGANCE): A study protocol.

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Review 9.  Innovations in thoracic imaging: CT, radiomics, AI and x-ray velocimetry.

Authors:  Rozemarijn Vliegenthart; Andreas Fouras; Colin Jacobs; Nickolas Papanikolaou
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10.  Pelvic bone CT: can tin-filtered ultra-low-dose CT and virtual radiographs be used as alternative for standard CT and digital radiographs?

Authors:  Christoph Stern; Stefan Sommer; Christoph Germann; Julien Galley; Christian W A Pfirrmann; Benjamin Fritz; Reto Sutter
Journal:  Eur Radiol       Date:  2021-03-12       Impact factor: 5.315

  10 in total

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