Literature DB >> 20095281

Partial scan artifact reduction (PSAR) for the assessment of cardiac perfusion in dynamic phase-correlated CT.

Philip Stenner1, Bernhard Schmidt, Herbert Bruder, Thomas Allmendinger, Ulrike Haberland, Thomas Flohr, Marc Kachelriess.   

Abstract

PURPOSE: Cardiac CT achieves its high temporal resolution by lowering the scan range from 2pi to pi plus fan angle (partial scan). This, however, introduces CT-value variations, depending on the angular position of the pi range. These partial scan artifacts are of the order of a few HU and prevent the quantitative evaluation of perfusion measurements. The authors present the new algorithm partial scan artifact reduction (PSAR) that corrects a dynamic phase-correlated scan without a priori information.
METHODS: In general, a full scan does not suffer from partial scan artifacts since all projections in [0, 2pi] contribute to the data. To maintain the optimum temporal resolution and the phase correlation, PSAR creates an artificial full scan pn(AF) by projectionwise averaging a set of neighboring partial scans pn(P) from the same perfusion examination (typically N approximately 30 phase-correlated partial scans distributed over 20 s and n = 1, ..., N). Corresponding to the angular range of each partial scan, the authors extract virtual partial scans pn(V) from the artificial full scan pn(AF). A standard reconstruction yields the corresponding images fn(P), fn(AF), and fn(V). Subtracting the virtual partial scan image fn(V) from the artificial full scan image fn(AF) yields an artifact image that can be used to correct the original partial scan image: fn(C) = fn(P) - fn(V) + fn(AF), where fn(C) is the corrected image.
RESULTS: The authors evaluated the effects of scattered radiation on the partial scan artifacts using simulated and measured water phantoms and found a strong correlation. The PSAR algorithm has been validated with a simulated semianthropomorphic heart phantom and with measurements of a dynamic biological perfusion phantom. For the stationary phantoms, real full scans have been performed to provide theoretical reference values. The improvement in the root mean square errors between the full and the partial scans with respect to the errors between the full and the corrected scans is up to 54% for the simulations and 90% for the measurements.
CONCLUSIONS: The phase-correlated data now appear accurate enough for a quantitative analysis of cardiac perfusion.

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 20095281     DOI: 10.1118/1.3259734

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  9 in total

1.  A strategy to decrease partial scan reconstruction artifacts in myocardial perfusion CT: phantom and in vivo evaluation.

Authors:  Juan C Ramirez-Giraldo; Lifeng Yu; Birgit Kantor; Erik L Ritman; Cynthia H McCollough
Journal:  Med Phys       Date:  2012-01       Impact factor: 4.071

2.  A new redundancy weighting scheme for nonstationary data for computed tomography.

Authors:  Katsuyuki Taguchi; Jochen Cammin
Journal:  Med Phys       Date:  2015-05       Impact factor: 4.071

3.  Reduction of image noise in low tube current dynamic CT myocardial perfusion imaging using HYPR processing: a time-attenuation curve analysis.

Authors:  Michael A Speidel; Courtney L Bateman; Yinghua Tao; Amish N Raval; Timothy A Hacker; Scott B Reeder; Michael S Van Lysel
Journal:  Med Phys       Date:  2013-01       Impact factor: 4.071

4.  Noise spatial nonuniformity and the impact of statistical image reconstruction in CT myocardial perfusion imaging.

Authors:  Pascal Theriault Lauzier; Jie Tang; Michael A Speidel; Guang-Hong Chen
Journal:  Med Phys       Date:  2012-07       Impact factor: 4.071

Review 5.  Cardiac CT for myocardial ischaemia detection and characterization--comparative analysis.

Authors:  A M Bucher; C N De Cecco; U J Schoepf; R Wang; F G Meinel; S R Binukrishnan; J V Spearman; T J Vogl; B Ruzsics
Journal:  Br J Radiol       Date:  2014-08-19       Impact factor: 3.039

6.  Low dose dynamic CT myocardial perfusion imaging using a statistical iterative reconstruction method.

Authors:  Yinghua Tao; Guang-Hong Chen; Timothy A Hacker; Amish N Raval; Michael S Van Lysel; Michael A Speidel
Journal:  Med Phys       Date:  2014-07       Impact factor: 4.071

7.  Volumetric CT with sparse detector arrays (and application to Si-strip photon counters).

Authors:  A Sisniega; W Zbijewski; J W Stayman; J Xu; K Taguchi; E Fredenberg; Mats Lundqvist; J H Siewerdsen
Journal:  Phys Med Biol       Date:  2015-11-27       Impact factor: 3.609

Review 8.  Myocardial perfusion imaging with cardiac computed tomography: state of the art.

Authors:  Amit R Patel; Nicole M Bhave; Victor Mor-Avi
Journal:  J Cardiovasc Transl Res       Date:  2013-08-21       Impact factor: 4.132

9.  Clinical quantitative cardiac imaging for the assessment of myocardial ischaemia.

Authors:  Marc Dewey; Maria Siebes; Marc Kachelrieß; Klaus F Kofoed; Pál Maurovich-Horvat; Konstantin Nikolaou; Wenjia Bai; Andreas Kofler; Robert Manka; Sebastian Kozerke; Amedeo Chiribiri; Tobias Schaeffter; Florian Michallek; Frank Bengel; Stephan Nekolla; Paul Knaapen; Mark Lubberink; Roxy Senior; Meng-Xing Tang; Jan J Piek; Tim van de Hoef; Johannes Martens; Laura Schreiber
Journal:  Nat Rev Cardiol       Date:  2020-02-24       Impact factor: 32.419

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.