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Wang VY, Tartibi M, Zhang Y, Selvaganesan K, Haraldsson H, Auger DA, Faraji F, Spaulding K, Takaba K, Collins A, Aguayo E, Saloner D, Wallace AW, Weinsaft JW, Epstein FH, Guccione J, Ge L, Ratcliffe MB. A kinematic model-based analysis framework for 3D Cine-DENSE-validation with an axially compressed gel phantom and application in sheep before and after antero-apical myocardial infarction. Magn Reson Med 2021; 86:2105-2121. [PMID: 34096083 DOI: 10.1002/mrm.28775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 02/24/2021] [Accepted: 02/25/2021] [Indexed: 11/06/2022]
Abstract
PURPOSE Myocardial strain is increasingly used to assess left ventricular (LV) function. Incorporation of LV deformation into finite element (FE) modeling environment with subsequent strain calculation will allow analysis to reach its full potential. We describe a new kinematic model-based analysis framework (KMAF) to calculate strain from 3D cine-DENSE (displacement encoding with stimulated echoes) MRI. METHODS Cine-DENSE allows measurement of 3D myocardial displacement with high spatial accuracy. The KMAF framework uses cine cardiovascular magnetic resonance (CMR) to facilitate cine-DENSE segmentation, interpolates cine-DENSE displacement, and kinematically deforms an FE model to calculate strain. This framework was validated in an axially compressed gel phantom and applied in 10 healthy sheep and 5 sheep after myocardial infarction (MI). RESULTS Excellent Bland-Altman agreement of peak circumferential (Ecc ) and longitudinal (Ell ) strain (mean difference = 0.021 ± 0.04 and -0.006 ± 0.03, respectively), was found between KMAF estimates and idealized FE simulation. Err had a mean difference of -0.014 but larger variation (±0.12). Cine-DENSE estimated end-systolic (ES) Ecc , Ell and Err exhibited significant spatial variation for healthy sheep. Displacement magnitude was reduced on average by 27%, 42%, and 56% after MI in the remote, adjacent and MI regions, respectively. CONCLUSIONS The KMAF framework allows accurate calculation of 3D LV Ecc and Ell from cine-DENSE.
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Affiliation(s)
- Vicky Y Wang
- Veterans Affairs Medical Center, San Francisco, California, USA
| | - Mehrzad Tartibi
- Veterans Affairs Medical Center, San Francisco, California, USA
| | - Yue Zhang
- Veterans Affairs Medical Center, San Francisco, California, USA
| | - Kartiga Selvaganesan
- Department of Biomedical Engineering, University of Berkeley, Berkeley, California, USA
| | - Henrik Haraldsson
- Veterans Affairs Medical Center, San Francisco, California, USA.,Department of Radiology, University of California, San Francisco, California, USA
| | - Daniel A Auger
- Department of Radiology and Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.,Medical Metrics, Inc., Houston, Texas, USA
| | - Farshid Faraji
- Veterans Affairs Medical Center, San Francisco, California, USA.,Department of Radiology, University of California, San Francisco, California, USA
| | | | - Kiyoaki Takaba
- Veterans Affairs Medical Center, San Francisco, California, USA
| | | | - Esteban Aguayo
- Veterans Affairs Medical Center, San Francisco, California, USA
| | - David Saloner
- Veterans Affairs Medical Center, San Francisco, California, USA.,Department of Radiology, University of California, San Francisco, California, USA
| | - Arthur W Wallace
- Veterans Affairs Medical Center, San Francisco, California, USA.,Department of Bioengineering, University of California, San Francisco, California, USA.,Department of Anesthesia, University of California, San Francisco, California, USA
| | | | - Frederick H Epstein
- Department of Radiology and Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Julius Guccione
- Veterans Affairs Medical Center, San Francisco, California, USA.,Department of Bioengineering, University of California, San Francisco, California, USA.,Department of Surgery, University of California, San Francisco, California, USA
| | - Liang Ge
- Veterans Affairs Medical Center, San Francisco, California, USA.,Department of Bioengineering, University of California, San Francisco, California, USA.,Department of Surgery, University of California, San Francisco, California, USA
| | - Mark B Ratcliffe
- Veterans Affairs Medical Center, San Francisco, California, USA.,Department of Bioengineering, University of California, San Francisco, California, USA.,Department of Surgery, University of California, San Francisco, California, USA.,Department of Medicine, University of California, San Francisco, California, USA
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