Noise reduction and motion elimination in low-dose 4D myocardial computed tomography perfusion (CTP): preliminary clinical evaluation of the ASTRA4D algorithm.
Aged
Algorithms
Artifacts
Coronary Artery Disease
/ diagnostic imaging
Female
Four-Dimensional Computed Tomography
/ methods
Humans
Magnetic Resonance Imaging
/ methods
Male
Middle Aged
Motion
Myocardial Ischemia
/ diagnostic imaging
Myocardial Perfusion Imaging
/ methods
Perfusion
Radiographic Image Interpretation, Computer-Assisted
/ methods
Sensitivity and Specificity
Signal-To-Noise Ratio
Computed tomography myocardial perfusion imaging
Coronary artery disease
Deformable registration
Motion artifacts
Temporal averaging
Journal
European radiology
ISSN: 1432-1084
Titre abrégé: Eur Radiol
Pays: Germany
ID NLM: 9114774
Informations de publication
Date de publication:
Sep 2019
Sep 2019
Historique:
received:
27
06
2018
accepted:
20
11
2018
revised:
15
10
2018
pubmed:
5
2
2019
medline:
4
12
2019
entrez:
5
2
2019
Statut:
ppublish
Résumé
To propose and evaluate a four-dimensional (4D) algorithm for joint motion elimination and spatiotemporal noise reduction in low-dose dynamic myocardial computed tomography perfusion (CTP). Thirty patients with suspected or confirmed coronary artery disease were prospectively included and underwent dynamic contrast-enhanced 320-row CTP. A novel deformable image registration method based on the principal component analysis (PCA) of the ante hoc temporally smoothed voxel-wise time-attenuation curves (ASTRA4D) is presented. Quantitative (standard deviation, signal-to-noise ratio (SNR), temporal variation, volumetric deformation) and qualitative (motion, contrast, contour sharpness [1, poor; 5, excellent]) measures of CTP quality were assessed for the original and motion-compensated sequences (without and with temporal filtering, PCA/ASTRA4D). Following myocardial perfusion deficit detection by two readers, diagnostic accuracy was evaluated using magnetic resonance myocardial perfusion imaging (MR-MPI) as the reference standard in 15 patients. Registration using ASTRA4D was successful in all 30 patients and resulted in comparison with the benchmark PCA in significantly (p < 0.001) reduced noise over time (- 83%, 178.5 vs 29.9) and spatially (- 34%, 21.4 vs 14.1) as well as improved SNR (+ 47%, 3.6 vs 5.3) and subjective image quality (motion, contrast, contour sharpness [+ 1.0, + 1.0, + 0.5]). ASTRA4D had significantly improved per-segment sensitivity of 91% (58/64) and similar specificity of 96% (429/446) compared with PCA (52%, 33/64; 98%, 435/446; p = 0.011) in the visual detection of perfusion deficits. The ASTRA4D registration algorithm improved the spatiotemporal noise profile and CTP sequence image quality, resulting in significantly improved sensitivity of 4D CTP in the detection of myocardial ischemia. • ASTRA4D combines local temporal regression and deformable image registration. • Quantitative and qualitative measures of CTP quality are improved compared to PCA. • Improved spatiotemporal differentiation of ischemic regions leads to an excellent perfusion deficit concordance of ASTRA4D with MRI.
Identifiants
pubmed: 30715584
doi: 10.1007/s00330-018-5899-8
pii: 10.1007/s00330-018-5899-8
doi:
Types de publication
Evaluation Study
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
4572-4582Subventions
Organisme : Deutsche Forschungsgemeinschaft
ID : DE 1361/14-1
Organisme : Berlin Institute of Health
ID : Digital Health Accelerator 2017
Références
Int J Cardiovasc Imaging. 2002 Feb;18(1):539-42
pubmed: 12135124
Phys Med Biol. 2007 Sep 7;52(17):5147-56
pubmed: 17762077
Invest Radiol. 2007 Dec;42(12):815-22
pubmed: 18007153
JACC Cardiovasc Imaging. 2011 Aug;4(8):905-16
pubmed: 21835384
Radiology. 2011 Sep;260(3):689-98
pubmed: 21846761
Eur Radiol. 2012 Jan;22(1):39-50
pubmed: 21938441
Med Image Anal. 2012 Jul;16(5):1015-28
pubmed: 22465078
Eur Radiol. 2012 Sep;22(9):1881-95
pubmed: 22527375
Int J Cardiovasc Imaging. 2013 Feb;29(2):435-42
pubmed: 22714549
J Biomed Sci Eng. 2012 Dec;5(12A):871-877
pubmed: 23936584
PLoS One. 2013 Oct 09;8(10):e75263
pubmed: 24130697
Med Image Anal. 2014 Feb;18(2):301-13
pubmed: 24322575
JACC Cardiovasc Imaging. 2014 Mar;7(3):267-77
pubmed: 24529887
Eur Radiol. 2014 Jul;24(7):1547-56
pubmed: 24744200
Circ Cardiovasc Imaging. 2015 Jan;8(1):null
pubmed: 25596143
AJR Am J Roentgenol. 2015 Mar;204(3):487-97
pubmed: 25714277
PLoS One. 2015 May 06;10(5):e0125943
pubmed: 25945924
Med Phys. 2016 Jan;43(1):347
pubmed: 26745928
Med Image Anal. 2016 Apr;29:65-78
pubmed: 26802910
Clin Radiol. 2016 Aug;71(8):739-49
pubmed: 27091433
Eur Radiol. 2017 Mar;27(3):1114-1124
pubmed: 27334015
Med Phys. 2016 Aug;43(8):4821
pubmed: 27487900
Sci Rep. 2016 Sep 29;6:34461
pubmed: 27681452
Int J Cardiovasc Imaging. 2017 Mar;33(3):371-382
pubmed: 27832419
Eur Radiol. 2017 Jul;27(7):2957-2968
pubmed: 27864607
Med Phys. 2017 Jul;44(7):3464-3482
pubmed: 28437011
J Med Imaging (Bellingham). 2017 Apr;4(2):026002
pubmed: 28523283
Radiology. 2018 Feb;286(2):461-470
pubmed: 28956734