Keywords:
Cardiac, Computer applications, Molecular imaging, Echocardiography, Echocardiography (transoesophageal), Image manipulation / Reconstruction, Acceptance testing, Biopsy, Ablation procedures, Blood, Image verification, Pathology
Authors:
M. Karvandi, S. Ranjbar; Tehran/IR
Methods and Materials
Force imaging with stimulated Matlab 7.0.4 (MathWorks,
Natick,
MA) software provides high spatial resolution measurement of three-dimensional myocardial points tracking (Lagrangian displacement) over the entire cardiac cycle.
Echocardiography was performed on 70 healthy volunteers.
Data evaluated included: velocity (radial,
longitudinal,
rotational and vector point),
displacement (longitudinal and rotational),
strain rate (longitudinal and circumferential) and strain (radial,
longitudinal and circumferential) of all 16 LV myocardial segments that were prospectively acquired on Vivid E9 with 4V probe (GH Healthcare,
Horton,
N).
The medical ethics committee of Shahid Beheshti Medical University approved this study.
All procedures were in accordance with the Helsinki declaration,
and no harm was experienced by the participants.
All data sets comprise a force vector field from end diastole to the end systole,
when the myocardium contraction is at its maximum (Figure 3 A and B)
The data set that covers the entire left ventricle consists of short-axis (SA) images captured from the heart of 70 volunteers.
The vector position of spatially designated muscle volume elements was mapped with a starting time at end diastole and time steps 70 ms apart.
These positions were captured and registered relative to the positions of these elements at the end systole.
The end systole time was determined through echocardiographic images and for this subject was 380 ms after QRS complex.
The imaging parameters are as follows: repetition time =3.1 ms,
mixing time =250 ms,
flip angle = 90°,
in-plane displacement encoding strength = 6.25 mm/π ,
out-of-plane displacement encoding strength = 3.21 mm/π ,
number of averages =3,
number of phases = 3,
in-plane resolution = 1.5 * 1.5 ,
slice thickness =5mm,
and distance factor = 50%.
Using the MATLAB view software,
the three-dimensional force vector field was generated in a matrix format.
Segmentation was then performed by masking all parts of the anatomy except for the myocardium.
For this study,
we have masked regions of the heart outside the left ventricle.
Phase unwrapping was then performed on the segmented images by scanning the myocardium area while searching for sudden changes in the force magnitude.
These phase wrappings were later unwrapped by adding or sub- tracting the force correction vector value,
which corresponds to the 2π radiant changes in phase.
This step was repeated separately for all three directions of force vector; MATLAB was used for the calculations.
In (Figure 4),
we can present arbitrary numbers SA slices of the heart at end systole along with arrows that show the force vector during the contraction that spans from end diastole to end systole.
By having data points across the left ventricle wall,
depending on the wall thickness,
we are able to calculate the transmural changes of the thickening and shortening index across the wall and orientation of vectors are better illustrated in (Figure 4),
It should be noted that the direction of these vectors represents the force directions that resulted from the contraction of many myofibers.
Therefore,
vector directions are not necessarily aligned in the muscle fiber directions at each myocardium point.
The reduction of the left ventricle volume in systole,
and therefore its pumping function,
is mostly caused by wall thickening ,
which is the effect of tangential shortening of the myocardium.
Therefore,
these two dependent quantities can be used as the quantitative characteristics for the local contribution of the left ventricle myocardium to global heart function.
The spatial distribution of regions that contribute the most to cardiac function acts as a functional macrostructure for the myocardium.
The mere existence of such a distinct structure and the knowledge of its normal morphology will facilitate a more effective modeling of left ventricle function.