Literature DB >> 28880152

An Open Benchmark Challenge for Motion Correction of Myocardial Perfusion MRI.

Beau Pontre, Brett R Cowan, Edward DiBella, Sancgeetha Kulaseharan, Devavrat Likhite, Nils Noorman, Lennart Tautz, Nicholas Tustison, Gert Wollny, Alistair A Young, Avan Suinesiaputra.   

Abstract

Cardiac magnetic resonance perfusion examinations enable noninvasive quantification of myocardial blood flow. However, motion between frames due to breathing must be corrected for quantitative analysis. Although several methods have been proposed, there is a lack of widely available benchmarks to compare different algorithms. We sought to compare many algorithms from several groups in an open benchmark challenge. Nine clinical studies from two different centers comprising normal and diseased myocardium at both rest and stress were made available for this study. The primary validation measure was regional myocardial blood flow based on the transfer coefficient (Ktrans), which was computed using a compartment model and the myocardial perfusion reserve (MPR) index. The ground truth was calculated using contours drawn manually on all frames by a single observer, and visually inspected by a second observer. Six groups participated and 19 different motion correction algorithms were compared. Each method used one of three different motion models: rigid, global affine, or local deformation. The similarity metric also varied with methods employing either sum-of-squared differences, mutual information, or cross correlation. There were no significant differences in Ktrans or MPR compared across different motion models or similarity metrics. Compared with the ground truth, only Ktrans for the sum-of-squared differences metric, and for local deformation motion models, had significant bias. In conclusion, the open benchmark enabled evaluation of clinical perfusion indices over a wide range of methods. In particular, there was no benefit of nonrigid registration techniques over the other methods evaluated in this study. The benchmark data and results are available from the Cardiac Atlas Project ( www.cardiacatlas.org).

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Year:  2017        PMID: 28880152      PMCID: PMC5658235          DOI: 10.1109/JBHI.2016.2597145

Source DB:  PubMed          Journal:  IEEE J Biomed Health Inform        ISSN: 2168-2194            Impact factor:   5.772


  35 in total

1.  On the theory of the indicator-dilution method for measurement of blood flow and volume.

Authors:  P MEIER; K L ZIERLER
Journal:  J Appl Physiol       Date:  1954-06       Impact factor: 3.531

2.  In-line automated tracking for ventricular function with magnetic resonance imaging.

Authors:  Bo Li; Yingmin Liu; Christopher J Occleshaw; Brett R Cowan; Alistair A Young
Journal:  JACC Cardiovasc Imaging       Date:  2010-08

3.  Fully automated motion correction in first-pass myocardial perfusion MR image sequences.

Authors:  Julien Milles; Rob J van der Geest; Michael Jerosch-Herold; Johan H C Reiber; Boudewijn P F Lelieveldt
Journal:  IEEE Trans Med Imaging       Date:  2008-11       Impact factor: 10.048

4.  A Gauss-Newton approach to joint image registration and intensity correction.

Authors:  Mehran Ebrahimi; Anthony Lausch; Anne L Martel
Journal:  Comput Methods Programs Biomed       Date:  2013-08-22       Impact factor: 5.428

Review 5.  MR myocardial perfusion imaging.

Authors:  Otavio R Coelho-Filho; Carsten Rickers; Raymond Y Kwong; Michael Jerosch-Herold
Journal:  Radiology       Date:  2013-03       Impact factor: 11.105

6.  Exploiting quasiperiodicity in motion correction of free-breathing myocardial perfusion MRI.

Authors:  Gert Wollny; Maria J Ledesma-Carbayo; Peter Kellman; Andres Santos
Journal:  IEEE Trans Med Imaging       Date:  2010-05-03       Impact factor: 10.048

7.  Long-term prognostic value of 13N-ammonia myocardial perfusion positron emission tomography added value of coronary flow reserve.

Authors:  Bernhard A Herzog; Lars Husmann; Ines Valenta; Oliver Gaemperli; Patrick T Siegrist; Fabian M Tay; Nina Burkhard; Christophe A Wyss; Philipp A Kaufmann
Journal:  J Am Coll Cardiol       Date:  2009-07-07       Impact factor: 24.094

8.  Explicit B-spline regularization in diffeomorphic image registration.

Authors:  Nicholas J Tustison; Brian B Avants
Journal:  Front Neuroinform       Date:  2013-12-23       Impact factor: 4.081

9.  The Insight ToolKit image registration framework.

Authors:  Brian B Avants; Nicholas J Tustison; Michael Stauffer; Gang Song; Baohua Wu; James C Gee
Journal:  Front Neuroinform       Date:  2014-04-28       Impact factor: 4.081

10.  Hyperemic stress myocardial perfusion cardiovascular magnetic resonance in mice at 3 Tesla: initial experience and validation against microspheres.

Authors:  Roy Jogiya; Markus Makowski; Alkystsis Phinikaridou; Ashish S Patel; Christian Jansen; Niloufar Zarinabad; Amedeo Chiribiri; Rene Botnar; Eike Nagel; Sebastian Kozerke; Sven Plein
Journal:  J Cardiovasc Magn Reson       Date:  2013-07-21       Impact factor: 5.364

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  8 in total

1.  Robust Non-Rigid Motion Compensation of Free-Breathing Myocardial Perfusion MRI Data.

Authors:  Cian M Scannell; Adriana D M Villa; Jack Lee; Marcel Breeuwer; Amedeo Chiribiri
Journal:  IEEE Trans Med Imaging       Date:  2019-02-01       Impact factor: 10.048

2.  ANHIR: Automatic Non-Rigid Histological Image Registration Challenge.

Authors:  Jiri Borovec; Jan Kybic; Ignacio Arganda-Carreras; Dmitry V Sorokin; Gloria Bueno; Alexander V Khvostikov; Spyridon Bakas; Eric I-Chao Chang; Stefan Heldmann; Kimmo Kartasalo; Leena Latonen; Johannes Lotz; Michelle Noga; Sarthak Pati; Kumaradevan Punithakumar; Pekka Ruusuvuori; Andrzej Skalski; Nazanin Tahmasebi; Masi Valkonen; Ludovic Venet; Yizhe Wang; Nick Weiss; Marek Wodzinski; Yu Xiang; Yan Xu; Yan Yan; Paul Yushkevich; Shengyu Zhao; Arrate Munoz-Barrutia
Journal:  IEEE Trans Med Imaging       Date:  2020-04-07       Impact factor: 10.048

3.  Quantitative 3D myocardial perfusion with an efficient arterial input function.

Authors:  Jason Kraig Mendes; Ganesh Adluru; Devavrat Likhite; Merlin J Fair; Peter D Gatehouse; Ye Tian; Apoorva Pedgaonkar; Brent Wilson; Edward V R DiBella
Journal:  Magn Reson Med       Date:  2019-10-31       Impact factor: 4.668

4.  Automated detection of left ventricle in arterial input function images for inline perfusion mapping using deep learning: A study of 15,000 patients.

Authors:  Hui Xue; Ethan Tseng; Kristopher D Knott; Tushar Kotecha; Louise Brown; Sven Plein; Marianna Fontana; James C Moon; Peter Kellman
Journal:  Magn Reson Med       Date:  2020-05-07       Impact factor: 3.737

5.  Feasibility of free-breathing quantitative myocardial perfusion using multi-echo Dixon magnetic resonance imaging.

Authors:  Cian M Scannell; Teresa Correia; Adriana D M Villa; Torben Schneider; Jack Lee; Marcel Breeuwer; Amedeo Chiribiri; Markus Henningsson
Journal:  Sci Rep       Date:  2020-07-29       Impact factor: 4.379

6.  Groupwise Non-Rigid Registration with Deep Learning: An Affordable Solution Applied to 2D Cardiac Cine MRI Reconstruction.

Authors:  Elena Martín-González; Teresa Sevilla; Ana Revilla-Orodea; Pablo Casaseca-de-la-Higuera; Carlos Alberola-López
Journal:  Entropy (Basel)       Date:  2020-06-19       Impact factor: 2.524

7.  Automatic in-line quantitative myocardial perfusion mapping: Processing algorithm and implementation.

Authors:  Hui Xue; Louise A E Brown; Sonia Nielles-Vallespin; Sven Plein; Peter Kellman
Journal:  Magn Reson Med       Date:  2019-08-23       Impact factor: 4.668

8.  A fast navigator (fastNAV) for prospective respiratory motion correction in first-pass myocardial perfusion imaging.

Authors:  Ronald Mooiweer; Radhouene Neji; Sarah McElroy; Muhummad Sohaib Nazir; Reza Razavi; Amedeo Chiribiri; Sébastien Roujol
Journal:  Magn Reson Med       Date:  2020-12-03       Impact factor: 3.737

  8 in total

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