Performance of ultralow-dose CT with iterative reconstruction in lung cancer screening: limiting radiation exposure to the equivalent of conventional chest ... View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-10

AUTHORS

Adrian Huber, Julia Landau, Lukas Ebner, Yanik Bütikofer, Lars Leidolt, Barbara Brela, Michelle May, Johannes Heverhagen, Andreas Christe

ABSTRACT

OBJECTIVE: To investigate the detection rate of pulmonary nodules in ultralow-dose CT acquisitions. MATERIALS AND METHODS: In this lung phantom study, 232 nodules (115 solid, 117 ground-glass) of different sizes were randomly distributed in a lung phantom in 60 different arrangements. Every arrangement was acquired once with standard radiation dose (100 kVp, 100 references mAs) and once with ultralow radiation dose (80 kVp, 6 mAs). Iterative reconstruction was used with optimized kernels: I30 for ultralow-dose, I70 for standard dose and I50 for CAD. Six radiologists examined the axial 1-mm stack for solid and ground-glass nodules. During a second and third step, three radiologists used maximum intensity projection (MIPs), finally checking with computer-assisted detection (CAD), while the others first used CAD, finally checking with the MIPs. RESULTS: The detection rate was 95.5 % with standard dose (DLP 126 mGy*cm) and 93.3 % with ultralow-dose (DLP: 9 mGy*cm). The additional use of either MIP reconstructions or CAD software could compensate for this difference. A combination of both MIP reconstructions and CAD software resulted in a maximum detection rate of 97.5 % with ultralow-dose. CONCLUSION: Lung cancer screening with ultralow-dose CT using the same radiation dose as a conventional chest X-ray is feasible. KEY POINTS: • 93.3 % of all lung nodules were detected with ultralow-dose CT. • A sensitivity of 97.5 % is possible with additional image post-processing. • The radiation dose is comparable to a standard radiography in two planes. • Lung cancer screening with ultralow-dose CT is feasible. More... »

PAGES

3643-3652

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00330-015-4192-3

DOI

http://dx.doi.org/10.1007/s00330-015-4192-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1048521719

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/26813670


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    "description": "OBJECTIVE: To investigate the detection rate of pulmonary nodules in ultralow-dose CT acquisitions.\nMATERIALS AND METHODS: In this lung phantom study, 232 nodules (115 solid, 117 ground-glass) of different sizes were randomly distributed in a lung phantom in 60 different arrangements. Every arrangement was acquired once with standard radiation dose (100 kVp, 100 references mAs) and once with ultralow radiation dose (80 kVp, 6 mAs). Iterative reconstruction was used with optimized kernels: I30 for ultralow-dose, I70 for standard dose and I50 for CAD. Six radiologists examined the axial 1-mm stack for solid and ground-glass nodules. During a second and third step, three radiologists used maximum intensity projection (MIPs), finally checking with computer-assisted detection (CAD), while the others first used CAD, finally checking with the MIPs.\nRESULTS: The detection rate was 95.5\u00a0% with standard dose (DLP 126\u00a0mGy*cm) and 93.3\u00a0% with ultralow-dose (DLP: 9\u00a0mGy*cm). The additional use of either MIP reconstructions or CAD software could compensate for this difference. A combination of both MIP reconstructions and CAD software resulted in a maximum detection rate of 97.5\u00a0% with ultralow-dose.\nCONCLUSION: Lung cancer screening with ultralow-dose CT using the same radiation dose as a conventional chest X-ray is feasible.\nKEY POINTS: \u2022 93.3\u00a0% of all lung nodules were detected with ultralow-dose CT. \u2022 A sensitivity of 97.5\u2009% is possible with additional image post-processing. \u2022 The radiation dose is comparable to a standard radiography in two planes. \u2022 Lung cancer screening with ultralow-dose CT is feasible.", 
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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

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curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s00330-015-4192-3'

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Turtle is a human-readable linked data format.

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RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00330-015-4192-3'


 

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