June 2020 - Characterization of Myocardial Infarct Size from 4D Ultrasound

This is a recording from a LIVE webinar conducted on June 18, 2020 presented by Arvin Soepriatna, PhD, Postdoctoral Researcher at the Center for Biomedical Engineering at Brown University in Rhode Island.

Coronary artery disease remains the leading cause of death in the world. Despite a strong positive correlation between infarct size and mortality rates, longitudinal monitoring of infarct expansion remains challenging. A reliable, noninvasive, and label-free method to quantitatively measure infarct size from 4D ultrasound data is therefore crucial in the study of infarct expansion.

In this presentation, two different methods to estimate infarct size, a strained-based and geometry-based approach, will be discussed. Taken together, the presented work provides an infarct sizing workflow that enables infarct expansion studies, an important component when assessing post-MI remodeling.

Topics discussed during this webinar:

● Coronary artery Disease (CAD) is the leading cause of death in western society and is associated with plaque formation and clot disruption, leading to occlusion of the coronary arteries
● Without reopening the pathway you will get a significant myocardial infarction (MI), which eventually leads to wall thinning and scar expansion
● Infarct sizes determines remodeling outcomes, 20% of patients with larger infarcts go into heart failure within 5 years of the ischemic event
● Most studies rely on histology and/or MRI to determine the size of the infarct but histology requires sacrificing the animal so no real longitudinal imaging (terminal timepoints). MRI is expensive and utilizes contrast reagents such as gadolinium for enhanced imaging
● GOAL: develop a non-invasive and label-free way to quantify the infarct size.
● 4D acquisitions were accomplished with both the 2100 and 3100; however, images with the 2100 required extra matlab scripts and image reconstruction to get a 4D image. This is very time consuming and can take up to 30 mins to acquire the images due to the EKVs required at each 3D slice point
● Image acquisition is considerably faster with the 3100 (going from mins to secs for each EKV), so the total acquisition time can be as short as 2 mins
● The authors use a permanent ligation (PL) model, ischemia reperfusion model (I/R model), and sham surgery to evaluate the software and technology.
● 4D, 2D SAX and LAX images, Color Doppler imaging, and E/A ratio analysis at days 1, 3, 7, 28 days post infarct
● Use VevoLAB to get a sense of geometrics but then reconstruct data at isotropic voxels (60um) in Matlab, segmenting out the sternum since it presents a considerable shadow complicated the data analysis, then pass the data over to 4D strain algorithms that they developed
● Use a bullseye map technique to examine the strain profile. The center of the bullseye is representative of the apex. Yellow areas = high strain, blue is lower strain
● The IR group presented with a localized region of damage whereas the PL has dilation of the scar tissue, resulting in EDV 3x higher than sham groups.
● Similarly, the PL group had lower EFs and E/A ratios (diastolic dysfunction only exists in the PL group, not the IR group)
● In order to get infarct size from their data with the 2100, the need to reorient the heart so that the data has a true LV geometry
● Tissue was considered infarcted if it presented with a thickness less than 0.5mm in systole (well published figure)
● They then segmented the heart into 30 degree regions, interpolated the sigmoidal signal where the sternum shadow lies
● The authors point out the importance of using 4D imaging because there is no consistency in the infarct production even in the hands of the same well-trained surgeon
● Wall thinning approach can complicate the first 5 days of infarct sizing because you don’t have any sig remodeling during that time, just stunted motion
● Correlated their findings with collagen quantification histology data and found that it does correspond with the strain values they got in their strain software
● Found that infarct size is better correlated with the strain approach, than the dilation/wall thinning approach
● Also showed that Vevo Lab can be used to obtain 4D infarct sizes by tracing both the endocardial and epicardial wall, and subtracting the 2 volumetric measurements to get a true volumetric size of the myocardium.
● Then use the diameter measurement of 0.5mm as exclusion criteria to trace the ROI for this tissue,which can be used to get a true infarct size
● Also showed that Vevo Lab and 4D imaging on the 3100 can be used to look at other disease states (i.e. TAC) to get true myocardial sizing

Conclusions: Integrated 4D US with 3D strain enables in vivo quantification of infarct size. Infarct estimation from wall thinning approach, more appropriate for estimating infarct size of mature infarcts. Vevo LAB can be used to determine large infarct sizes in the absence of histology. Vevo LAB can also be used in other CVD models to quantify myocardial size consistently and more accurately than other approaches. ● Long-term clinical impact: use these softwares to predict the final infarct size, early identification of patients at risk for late stage HF