Literature DB >> 30953252

CT-derived left ventricular global strain: a head-to-head comparison with speckle tracking echocardiography.

F Ammon1, D Bittner2, M Hell2, H Mansour3, S Achenbach2, M Arnold2, M Marwan2.   

Abstract

We assessed CT-derived left ventricular strain in a cohort of patients referred for transcatheter aortic valve implantation (TAVI) and validated it against 2 dimensional speckle tracking echocardiography as the gold standard. 65 consecutive patients with symptomatic aortic valve stenosis referred for CT imaging prior to TAVI were included in this analysis. For all patients, retrospectively ECG-gated multi-phase functional CT data sets acquired with identical reconstruction parameters were available. All data sets were acquired using a third generation dual source system. In all patients, multiphase reconstructions in increments of 10% of the cardiac cycle were rendered (slice thickness 0.75, increment 0.5 mm, medium smooth reconstruction kernel) and transferred to a dedicated workstation (Ziostation2, Ziosoft Inc., Tokyo, Japan). Additional functional reconstructions for dynamic assessment and quantification of strain were processed. Multiplanar reconstructions (MPR) of the left ventricle similar to standard echocardiographic 4, 2 and apical 3 chamber views were rendered in CT. Similar to echocardiographic longitudinal strain, the perimeter of the left ventricle was manually traced within the myocardium and peak maximal shortening as a parameter representing longitudinal strain was calculated for each view and averaged to obtain a marker for global longitudinal strain (CT perimeter-derived strain). Furthermore, for quantification of 3-dimensional strain, endocardial and epicardial borders of myocardium were marked in six short axis views and peak maximum 3- dimensional strain of the myocardium was calculated in standard six basal, six mid and four apical segments. 3-dimensional strain values of the 16 standard segments as well as perimeter-derived strain values in the three standard windows were averaged to obtain global strain. Echocardiography was performed in all patients before CT data acquisition. Digital loops were acquired from three apical views (four-, two-, and three chamber views). For assessment of 2 dimensional global longitudinal strain (GLS), recordings were processed with acoustic-tracking software allowing offline semiautomated speckle-based strain analyses. The mean age of all 65 patients was 81 ± 5 years. The mean echocardiographic ejection fraction and mean echocardiographic GLS were 50 ± 12% and -13.6 ± 4.5%, respectively. The mean CT-derived peak 3-dimensional global strain and mean peak strain derived by perimeter was 43.2 ± 13.5% and -11.2 ± 3.5%, respectively. Both CTderived global 3D-strain and perimeter derived strain showed a significant correlation to GLS derived by echocardiography (r = -0.8, p < 0.0001 for 3D strain and r = 0.71, p < 0.0001 for perimeter-derived strain). Bland-Altman analysis showed a systematic underestimation (i. e. worse strain values) of CT perimeter-derived strain compared to GLS by echocardiography (mean difference -2.4% with 95% limits of agreement between 4% to -9%). ROC Curve analysis assuming a normal GLS when less than -18% showed that a CT-derived peak 3-dimensional global strain cut-off-value of 45% has a sensitivity of 91% and a specificity of 60% for detecting normal left ventricular strain (AUC 0.81, p = 0.001). For CT perimeter-derived strain, a cut-off value of -12%-assuming a normal echocardiographic GLS when less than -18%-achieved a sensitivity of 82% and a specificity of 61% (AUC of 0.82, p = 0.001) for detecting abnormal left ventricular strain. Using dedicated software, assessment of CT-derived left ventricular strain is feasible and comparable to strain derived by echocardiographic 2 dimensional speckle tracking.

Entities:  

Keywords:  Cardiac CT angiography; Echocardiography; Left ventricular global strain; Speckle tracking

Mesh:

Year:  2019        PMID: 30953252     DOI: 10.1007/s10554-019-01596-8

Source DB:  PubMed          Journal:  Int J Cardiovasc Imaging        ISSN: 1569-5794            Impact factor:   2.357


  11 in total

1.  Cardiovascular imaging 2019 in the International Journal of Cardiovascular Imaging.

Authors:  Johan H C Reiber; Gabriel T R Pereira; Luis A P Dallan; Hiram G Bezerra; Johan De Sutter; Arthur E Stillman; Nico R L Van de Veire; Joachim Lotz
Journal:  Int J Cardiovasc Imaging       Date:  2020-05       Impact factor: 2.357

Review 2.  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

3.  Feasibility of Coronary CT Angiography-derived Left Ventricular Long-Axis Shortening as an Early Marker of Ventricular Dysfunction in Transcatheter Aortic Valve Replacement.

Authors:  Gilberto J Aquino; Josua A Decker; U Joseph Schoepf; Landin Carson; Namrata Paladugu; Basel Yacoub; Verena Brandt; Anna Lena Emrich; Florian Schwarz; Jeremy R Burt; Richard Bayer; Akos Varga-Szemes; Tilman Emrich
Journal:  Radiol Cardiothorac Imaging       Date:  2022-06-30

4.  Clinical impact of cardiac computed tomography derived three-dimensional strain for adult congenital heart disease: a pilot study.

Authors:  Yumi Shiina; Kei Inai; Tatsunori Takahashi; Yamato Shimomiya; Michinobu Nagao
Journal:  Int J Cardiovasc Imaging       Date:  2019-08-30       Impact factor: 2.357

5.  Left ventricular global longitudinal strain in bicupsid aortic valve patients: head-to-head comparison between computed tomography, 4D flow cardiovascular magnetic resonance and speckle-tracking echocardiography.

Authors:  Allard T van den Hoven; Sultan Yilmazer; Raluca G Chelu; Roderick W J van Grootel; Savine C S Minderhoud; Lidia R Bons; An M van Berendoncks; Anthonie L Duijnhouwer; Hans-Marc J Siebelink; Annemien E van den Bosch; Ricardo P J Budde; Jolien W Roos-Hesselink; Alexander Hirsch
Journal:  Int J Cardiovasc Imaging       Date:  2020-05-25       Impact factor: 2.357

6.  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

7.  CT Image Feature Diagnosis on the Basis of Deep Learning Algorithm for Preoperative Patients and Complications of Transcatheter Aortic Valve Implantation.

Authors:  Xiong Zheng; Zhang Qian; Xiaofang Wang; Zhen Zhang; Lei Liu
Journal:  J Healthc Eng       Date:  2021-11-29       Impact factor: 2.682

8.  Quantifying Myocardial Strain of the Left Ventricle in Normal People Using Feature-Tracking Based on Computed Tomography Imaging.

Authors:  Na Li; Tong Liu; Jia Liu; Yukun Cao; Yumin Li; Jie Yu; Xiaoyu Han; Guozhu Shao; Ming Yang; Zhihan Xu; Wenjuan Zeng; Heshui Shi
Journal:  Diagnostics (Basel)       Date:  2022-01-27

9.  Assessment of Global Longitudinal and Circumferential Strain Using Computed Tomography Feature Tracking: Intra-Individual Comparison with CMR Feature Tracking and Myocardial Tagging in Patients with Severe Aortic Stenosis.

Authors:  Emilija Miskinyte; Paulius Bucius; Jennifer Erley; Seyedeh Mahsa Zamani; Radu Tanacli; Christian Stehning; Christopher Schneeweis; Tomas Lapinskas; Burkert Pieske; Volkmar Falk; Rolf Gebker; Gianni Pedrizzetti; Natalia Solowjowa; Sebastian Kelle
Journal:  J Clin Med       Date:  2019-09-10       Impact factor: 4.241

10.  Assessment of regional left ventricular myocardial strain in patients with left anterior descending coronary stenosis using computed tomography feature tracking.

Authors:  Xiaoyu Han; Yukun Cao; Zhiguo Ju; Jia Liu; Na Li; Yumin Li; Tong Liu; Heshui Shi; Jin Gu
Journal:  BMC Cardiovasc Disord       Date:  2020-08-08       Impact factor: 2.298

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.