CT pulmonary angiography: dose reduction via a next generation iterative reconstruction algorithm.


Journal

Acta radiologica (Stockholm, Sweden : 1987)
ISSN: 1600-0455
Titre abrégé: Acta Radiol
Pays: England
ID NLM: 8706123

Informations de publication

Date de publication:
Apr 2019
Historique:
pubmed: 24 6 2018
medline: 9 4 2019
entrez: 24 6 2018
Statut: ppublish

Résumé

Computed tomography pulmonary angiography (CTPA) is the standard imaging modality for detection or rule out of pulmonary embolism (PE); however, radiation exposure is a serious concern. With iterative reconstruction algorithms a distinct dose reduction could be achievable. To evaluate a next generation iterative reconstruction algorithm for detection or rule-out of PE in simulated low-dose CTPA. Low-dose CT datasets with 50%, 25%, and 12.5% of the original tube current were simulated based on CTPA examinations of 92 patients with suspected PE. All datasets were reconstructed with two reconstruction algorithms: standard filtered back-projection (FBP) and iterative model reconstruction (IMR). In total, 736 CTPA datasets were evaluated by three blinded radiologists regarding image quality, diagnostic confidence, and detectability of PE. Furthermore, contrast-to-noise ratio (CNR) was calculated. Images reconstructed with IMR showed better detectability of PE than images reconstructed with FBP, especially at lower dose levels. With IMR, sensitivity was over 95% for central and segmental PE down to a dose level of 25%. Significantly higher subjective image quality was shown at lower dose levels (25% and 12.5%) for IMR images whereas it was higher for FBP images at higher dose levels. FBP was rated as showing less artificial image appearance. CNR was significantly higher with IMR at all dose levels. By using IMR, a dose reduction of up to 50% while maintaining satisfactory image quality seems feasible in standard clinical situations, resulting in a mean effective dose of 1.38 mSv for CTPA.

Sections du résumé

BACKGROUND BACKGROUND
Computed tomography pulmonary angiography (CTPA) is the standard imaging modality for detection or rule out of pulmonary embolism (PE); however, radiation exposure is a serious concern. With iterative reconstruction algorithms a distinct dose reduction could be achievable.
PURPOSE OBJECTIVE
To evaluate a next generation iterative reconstruction algorithm for detection or rule-out of PE in simulated low-dose CTPA.
MATERIAL AND METHODS METHODS
Low-dose CT datasets with 50%, 25%, and 12.5% of the original tube current were simulated based on CTPA examinations of 92 patients with suspected PE. All datasets were reconstructed with two reconstruction algorithms: standard filtered back-projection (FBP) and iterative model reconstruction (IMR). In total, 736 CTPA datasets were evaluated by three blinded radiologists regarding image quality, diagnostic confidence, and detectability of PE. Furthermore, contrast-to-noise ratio (CNR) was calculated.
RESULTS RESULTS
Images reconstructed with IMR showed better detectability of PE than images reconstructed with FBP, especially at lower dose levels. With IMR, sensitivity was over 95% for central and segmental PE down to a dose level of 25%. Significantly higher subjective image quality was shown at lower dose levels (25% and 12.5%) for IMR images whereas it was higher for FBP images at higher dose levels. FBP was rated as showing less artificial image appearance. CNR was significantly higher with IMR at all dose levels.
CONCLUSION CONCLUSIONS
By using IMR, a dose reduction of up to 50% while maintaining satisfactory image quality seems feasible in standard clinical situations, resulting in a mean effective dose of 1.38 mSv for CTPA.

Identifiants

pubmed: 29933714
doi: 10.1177/0284185118784976
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

478-487

Auteurs

Andreas Sauter (A)

1 Department of diagnostic and interventional Radiology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.

Thomas Koehler (T)

2 Philips GmbH Innovative Technologies, Research Laboratories, Hamburg, Germany.

Bernhard Brendel (B)

2 Philips GmbH Innovative Technologies, Research Laboratories, Hamburg, Germany.

Juliane Aichele (J)

1 Department of diagnostic and interventional Radiology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.

Jan Neumann (J)

1 Department of diagnostic and interventional Radiology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.

Peter B Noël (PB)

1 Department of diagnostic and interventional Radiology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.

Ernst J Rummeny (EJ)

1 Department of diagnostic and interventional Radiology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.

Daniela Muenzel (D)

1 Department of diagnostic and interventional Radiology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.

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