Feature tracking computed tomography-derived left ventricular global longitudinal strain in patients with aortic stenosis: a comparative analysis with echocardiographic measurements

Gegenava, T; Bijl, Pieter van der; Hirasawa, Kensuke; Vollema, E. Mara; Rosendael, Alexander van; Kley, Frank van der; Weger, Arend de; Hautemann, David; Reiber, Johan H. C.; Marsan, Nina Ajmone; Bax, Jeroen J.; Delgado, Victoria

doi:10.1016/j.jcct.2019.11.004

Cited by 18 publications

(9 citation statements)

References 22 publications

(24 reference statements)

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“…CCT consistently overestimated volumetric variables (LV EDV, RV EDA and LA ESV) and underestimated (resulting in less negative values) LV-and LA GLS compared to STE. Previous studies, comparing both modalities also reported an underestimation of LV-and LA GLS in CCT but described a higher agreement between modalities compared to our findings 28,[34][35][36][37] . However, these studies systematically excluded a large number of patients with poor IQ in STE (up to about 50% of patients) and, besides Buss et al 28 , increments of every 10% of the cardiac cycle were rendered, resulting in only 10 J o u r n a l P r e -p r o o f reconstructions per cardiac cycle.…”

Section: Lower Reproducibility Of Ste Derived LV Gcs and Grs In Comparison To Gls Was Alreadycontrasting

confidence: 68%

Reproducibility of 4D cardiac computed tomography feature tracking myocardial strain and comparison against speckle-tracking echocardiography in patients with severe aortic stenosis

Bernhard

Grogg

Zurkirchen

et al. 2022

Journal of Cardiovascular Computed Tomography

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Section: Lower Reproducibility Of Ste Derived LV Gcs and Grs In Comparison To Gls Was Alreadycontrasting

confidence: 68%

Reproducibility of 4D cardiac computed tomography feature tracking myocardial strain and comparison against speckle-tracking echocardiography in patients with severe aortic stenosis

Bernhard

Grogg

Zurkirchen

et al. 2022

Journal of Cardiovascular Computed Tomography

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“…Previous studies have used 4DCT to estimate regional LV strain [17][18][19][20][21] ; however, these studies are based on smooth contours that represent the endocardium and the epicardium. The new method proposed in this work takes advantage of the region within the CT image volume with the greatest contrast and quantity of fiducial markers: the boundary between the endocardium and the contrast-enhanced blood pool.…”

Section: Comparison With Other 4dct Strain Estimation Methodsmentioning

confidence: 99%

“…Previous studies have used 4DCT to estimate LV myocardial function. [17][18][19][20][21] Lamash et al used a deformable LV model to estimate regional and global myocardial strains from 3D velocity fields which were extracted via a novel optical flow technique. 17 The model was then used to successfully differentiate between normal and abnormal myocardial segments in a cohort of 93 subjects with cardiac 4DCT scans.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2022

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Background Estimates of regional left ventricular (LV) strains provide additional information to global function parameters such as ejection fraction (EF) and global longitudinal strain (GLS) and are more sensitive in detecting abnormal regional cardiac function. The accurate and reproducible assessment of regional cardiac function has implications in the management of various cardiac diseases such as heart failure, myocardial ischemia, and dyssynchrony. Purpose To develop a method that yields highly reproducible, high‐resolution estimates of regional endocardial strains from 4DCT images. Methods A method for estimating regional LV endocardial circumferential false(εccfalse)$( {{\epsilon }_{cc}} )$ and longitudinal (εll${\epsilon }_{ll}$) strains from 4DCT was developed. Point clouds representing the LV endocardial surface were extracted for each time frame of the cardiac cycle from 4DCT images. 3D deformation fields across the cardiac cycle were obtained by registering the end diastolic point cloud to each subsequent point cloud in time across the cardiac cycle using a 3D point‐set registration technique. From these deformation fields, εccandεll${\epsilon }_{cc}\ {\rm{and\ }}{\epsilon }_{ll}$ were estimated over the entire LV endocardial surface by fitting an affine transformation with maximum likelihood estimation. The 4DCT‐derived strains were compared with strains estimated in the same subjects by cardiac magnetic resonance (CMR); twenty‐four subjects had CMR scans followed by 4DCT scans acquired within a few hours. Regional LV circumferential and longitudinal strains were estimated from the CMR images using a commercially available feature tracking software (cvi42). Global circumferential strain (GCS) and global longitudinal strain (GLS) were calculated as the mean of the regional strains across the entire LV for both modalities. Pearson correlation coefficients and Bland‐Altman analyses were used for comparisons. Intraclass correlation coefficients (ICC) were used to assess the inter‐ and intraobserver reproducibility of the 4DCT‐derived strains. Results The 4DCT‐derived regional strains correlated well with the CMR‐derived regional strains (εcc${\epsilon }_{cc}$: r = 0.76, p < 0.001; εll${\epsilon }_{ll}$: r = 0.64, p < 0.001). A very strong correlation was found between 4DCT‐derived GCS and 4DCT‐derived EF (r = −0.96; p < 0.001). The 4DCT‐derived strains were also highly reproducible, with very low inter‐ and intraobserver variability (intraclass correlation coefficients in the range of [0.92, 0.99]). Conclusions We have developed a novel method to estimate high‐resolution regional LV endocardial circumferential and longitudinal strains from 4DCT images. Except for the definition of the mitral valve and LV outflow tract planes, the method is completely user independent, thus yielding highly reproducible estimates of endocardial strain. The 4DCT‐derived strains correlated well with those estimated using a commercial CMR feature tracking software. The promising results reported in this study highli...

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“…5 ). 38 CT-GLS was measured using a novel tissue-tracking software and dynamic CCT datasets. Mean GLS on echocardiography was −13.91 ± 4.32%, whereas mean feature tracking CT-GLS was −12.46 ± 3.97%.…”

Section: Structural Heart Diseasementioning

confidence: 99%

The Journal of Cardiovascular Computed Tomography: 2020 Year in review

Villines

Al’Aref

Andreini

et al. 2021

Journal of Cardiovascular Computed Tomography

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Feature tracking computed tomography-derived left ventricular global longitudinal strain in patients with aortic stenosis: a comparative analysis with echocardiographic measurements

Cited by 18 publications

References 22 publications

Reproducibility of 4D cardiac computed tomography feature tracking myocardial strain and comparison against speckle-tracking echocardiography in patients with severe aortic stenosis

Reproducibility of 4D cardiac computed tomography feature tracking myocardial strain and comparison against speckle-tracking echocardiography in patients with severe aortic stenosis

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

The Journal of Cardiovascular Computed Tomography: 2020 Year in review

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