| Autor: |
Rachel M Taylor, Tomy Varghese, Rashid Al Mukaddim, Ashley M. Weichmann, Thomas Pier, Timothy A. Hacker, Carol Mitchell, Melissa E. Graham |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
2021 IEEE International Ultrasonics Symposium (IUS). |
| Popis: |
Cardiac strain imaging (CSI) using ultrasound radiofrequency (RF) data is more sensitive to subtle myocardial motion abnormalities compared to echocardiographic measurements and envelope-based speckle tracking. Yet, CSI is being actively researched to address challenges from out-of-plane scatter motion due to complex 3D cardiac deformation imaged in 2D. Here, we report on a feasibility study to apply adaptive Bayesian CSI for in vivo apical infarct localization using 2D ultrasound RF data from murine models of ischemia-reperfusion (IR) and myocardial infarction (MI). High frequency ( $\mathrm{f}_{\mathrm{c}}=30\text{MHz}$ ) ultrasound (US) radio-frequency data collected in parasternal short axis view at the apical level were tracked using an adaptive Bayesian regularization incorporated multi-level block matching algorithm. In vivo longitudinal study was designed with five imaging sessions (pre-surgery (BL) and 1,2,7 and 14 days post-surgery). End-systole circumferential strain images and values were compared among three different mouse models - sham, myocardial infarction, and ischemia-reperfusion. Findings from cardiac strain imaging demonstrated good correlation with the findings from ex vivo histopathological image analysis thus showing the feasibility of the proposed method. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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