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Open AccessArticle

Deep Learning Versus Iterative Reconstruction for CT Pulmonary Angiography in the Emergency Setting: Improved Image Quality and Reduced Radiation Dose

1
Department of Neuroradiology and Emergency Radiology, François-Mitterrand University Hospital, 14 Rue Paul Gaffarel, BP 77908, 21079 Dijon, France
2
Department of Cardiovascular and Interventional Radiology, ImViA Laboratory-EA 7535, François-Mitterrand University Hospital, 14 Rue Paul Gaffarel, BP 77908, 21079 Dijon, France
3
Computed Tomography Division, Canon Medical Systems France, 24 Quai Gallieni, 92150 Suresnes, France
*
Author to whom correspondence should be addressed.
Diagnostics 2020, 10(8), 558; https://doi.org/10.3390/diagnostics10080558
Received: 16 July 2020 / Revised: 1 August 2020 / Accepted: 2 August 2020 / Published: 4 August 2020
(This article belongs to the Special Issue Assessment of Radiation Dose in X-ray and CT Exams)
To compare image quality and the radiation dose of computed tomography pulmonary angiography (CTPA) subjected to the first deep learning-based image reconstruction (DLR) (50%) algorithm, with images subjected to the hybrid-iterative reconstruction (IR) technique (50%). One hundred forty patients who underwent CTPA for suspected pulmonary embolism (PE) between 2018 and 2019 were retrospectively reviewed. Image quality was assessed quantitatively (image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR)) and qualitatively (on a 5-point scale). Radiation dose parameters (CT dose index, CTDIvol; and dose-length product, DLP) were also recorded. Ninety-three patients were finally analyzed, 48 with hybrid-IR and 45 with DLR images. The image noise was significantly lower and the SNR (24.4 ± 5.9 vs. 20.7 ± 6.1) and CNR (21.8 ± 5.8 vs. 18.6 ± 6.0) were significantly higher on DLR than hybrid-IR images (p < 0.01). DLR images received a significantly higher score than hybrid-IR images for image quality, with both soft (4.4 ± 0.7 vs. 3.8 ± 0.8) and lung (4.1 ± 0.7 vs. 3.6 ± 0.9) filters (p < 0.01). No difference in diagnostic confidence level for PE between both techniques was found. CTDIvol (4.8 ± 1.4 vs. 4.0 ± 1.2 mGy) and DLP (157.9 ± 44.9 vs. 130.8 ± 41.2 mGy∙cm) were lower on DLR than hybrid-IR images. DLR both significantly improved the image quality and reduced the radiation dose of CTPA examinations as compared to the hybrid-IR technique. View Full-Text
Keywords: computed tomography angiography; pulmonary embolism; artificial intelligence; image reconstruction; deep learning computed tomography angiography; pulmonary embolism; artificial intelligence; image reconstruction; deep learning
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MDPI and ACS Style

Lenfant, M.; Chevallier, O.; Comby, P.-O.; Secco, G.; Haioun, K.; Ricolfi, F.; Lemogne, B.; Loffroy, R. Deep Learning Versus Iterative Reconstruction for CT Pulmonary Angiography in the Emergency Setting: Improved Image Quality and Reduced Radiation Dose. Diagnostics 2020, 10, 558.

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