Literature DB >> 25252273

Strain analysis from 4-D cardiac CT image data.

Yechiel Lamash, Anath Fischer, Shemy Carasso, Jonathan Lessick.   

Abstract

Strain is a discriminative parameter of regional myocardial dysfunction. Despite the large body of research on myocardial strain analysis in echocardiography and MR images, such techniques have not often been applied to cardiac CT data. Reasons for this include the challenges of sparse image deformation clues and the low temporal resolution. In the current study, we propose an algorithm that uses cardiac CT data to evaluate the mechanical function of the left ventricle. The algorithm is based on a deformable LV model that contains both the myocardium and the blood pool regions and that accounts for the elasticity and incompressibility of the myocardium with the rapid contraction of the blood pool. Our algorithm uses the image intensities of the trabeculle and papillary muscles as well as the border edges in an optical flow manner to extract the 3-D velocities. The resulting strains and rotational values derived from a set of normal patients correlate highly with values from the research literature. We validated our algorithm against 2-D speckle tracking analysis and against visual scores obtained by an expert. Our study shows that strain analysis using CT data can be used in clinical practice.

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Year:  2014        PMID: 25252273     DOI: 10.1109/TBME.2014.2359244

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  9 in total

Review 1.  Comparison of Echocardiography, Cardiac Magnetic Resonance, and Computed Tomographic Imaging for the Evaluation of Left Ventricular Myocardial Function: Part 2 (Diastolic and Regional Assessment).

Authors:  Menhel Kinno; Prashant Nagpal; Stephen Horgan; Alfonso H Waller
Journal:  Curr Cardiol Rep       Date:  2017-01       Impact factor: 2.931

2.  Automated 4-dimensional regional myocardial strain evaluation using cardiac computed tomography.

Authors:  Zvi Peled; Yechiel Lamash; Shemy Carasso; Anath Fischer; Yoram Agmon; Diab Mutlak; Doron Aronson; Gil Bolotin; Jonathan Lessick
Journal:  Int J Cardiovasc Imaging       Date:  2019-09-19       Impact factor: 2.357

Review 3.  Functional cardiac CT-Going beyond Anatomical Evaluation of Coronary Artery Disease with Cine CT, CT-FFR, CT Perfusion and Machine Learning.

Authors:  Joyce Peper; Dominika Suchá; Martin Swaans; Tim Leiner
Journal:  Br J Radiol       Date:  2020-08-12       Impact factor: 3.039

4.  Regional left ventricular endocardial strains estimated from low-dose 4DCT: Comparison with cardiac magnetic resonance feature tracking.

Authors:  Ashish Manohar; Gabrielle M Colvert; Juan E Ortuño; Zhennong Chen; James Yang; Brendan T Colvert; W Patricia Bandettini; Marcus Y Chen; María J Ledesma-Carbayo; Elliot R McVeigh
Journal:  Med Phys       Date:  2022-07-06       Impact factor: 4.506

5.  Semi-Automated Extraction of Crohns Disease MR Imaging Markers using a 3D Residual CNN with Distance Prior.

Authors:  Yechiel Lamash; Sila Kurugol; Simon K Warfield
Journal:  Deep Learn Med Image Anal Multimodal Learn Clin Decis Support (2018)       Date:  2018-09-20

6.  Hyperparameter optimisation and validation of registration algorithms for measuring regional ventricular deformation using retrospective gated computed tomography images.

Authors:  Orod Razeghi; Mattias Heinrich; Thomas E Fastl; Cesare Corrado; Rashed Karim; Adelaide De Vecchi; Tom Banks; Patrick Donnelly; Jonathan M Behar; Justin Gould; Ronak Rajani; Christopher A Rinaldi; Steven Niederer
Journal:  Sci Rep       Date:  2021-03-11       Impact factor: 4.379

7.  Feasibility of CT-derived myocardial strain measurement in patients with advanced cardiac valve disease.

Authors:  Marius Vach; Johanna Vogelhuber; Marcel Weber; Alois M Sprinkart; Claus C Pieper; Wolfgang Block; Daniel Kuetting; Ulrike I Attenberger; Julian A Luetkens
Journal:  Sci Rep       Date:  2021-04-22       Impact factor: 4.379

8.  Detection of left ventricular wall motion abnormalities from volume rendering of 4DCT cardiac angiograms using deep learning.

Authors:  Zhennong Chen; Francisco Contijoch; Gabrielle M Colvert; Ashish Manohar; Andrew M Kahn; Hari K Narayan; Elliot McVeigh
Journal:  Front Cardiovasc Med       Date:  2022-07-28

9.  A Patient-Specific 3Dt Coronary Artery Motion Modeling Method Using Hierarchical Deformation with Electrocardiogram.

Authors:  Siyeop Yoon; Changhwan Yoon; Eun Ju Chun; Deukhee Lee
Journal:  Sensors (Basel)       Date:  2020-10-05       Impact factor: 3.576

  9 in total

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