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Manohar A, Colvert GM, Ortuño JE, Chen Z, Yang J, Colvert BT, Bandettini WP, Chen MY, Ledesma-Carbayo MJ, McVeigh ER. Regional left ventricular endocardial strains estimated from low-dose 4DCT: Comparison with cardiac magnetic resonance feature tracking. Med Phys 2022; 49:5841-5854. [PMID: 35751864 PMCID: PMC9474637 DOI: 10.1002/mp.15818] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 05/31/2022] [Accepted: 06/10/2022] [Indexed: 11/05/2022] Open
Abstract
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( ε c c ) $( {{\epsilon }_{cc}} )$ and longitudinal (ε l l ${\epsilon }_{ll}$ ) 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,ε c c and ε l l ${\epsilon }_{cc}\ {\rm{and\ }}{\epsilon }_{ll}$ 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 (ε c c ${\epsilon }_{cc}$ : r = 0.76, p < 0.001;ε l l ${\epsilon }_{ll}$ : 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 highlight the potential utility of 4DCT in the precise assessment of regional cardiac function for the management of cardiac disease.
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Affiliation(s)
- Ashish Manohar
- Department of Mechanical and Aerospace Engineering, University of California San Diego, La Jolla, California, USA
| | - Gabrielle M Colvert
- Department of Bioengineering, University of California San Diego, La Jolla, California, USA
| | - Juan E Ortuño
- Biomedical Research Networking Centre in Bioengineering, Biomaterials and Nanomedicine, Madrid, Spain
- Biomedical Image Technologies Laboratory, ETSI Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain
| | - Zhennong Chen
- Department of Bioengineering, University of California San Diego, La Jolla, California, USA
| | - James Yang
- Department of Bioengineering, University of California San Diego, La Jolla, California, USA
| | - Brendan T Colvert
- Department of Bioengineering, University of California San Diego, La Jolla, California, USA
| | - W Patricia Bandettini
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Marcus Y Chen
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - María J Ledesma-Carbayo
- Biomedical Research Networking Centre in Bioengineering, Biomaterials and Nanomedicine, Madrid, Spain
- Biomedical Image Technologies Laboratory, ETSI Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain
| | - Elliot R McVeigh
- Department of Bioengineering, University of California San Diego, La Jolla, California, USA
- Department of Radiology, University of California San Diego, La Jolla, California, USA
- Department of Medicine, Cardiovascular Division, University of California San Diego, La Jolla, California, USA
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