The analysis of images is also heavily technology driven as resolving the diseases of the heart require a rather detailed representation of everything that moves (cardiac muscles, valves, blood) within the heart. Thus – there is a need for many specialized ultrasound modes and applications for medical doctors to do this type of analysis.

For the analysis of valves and blood flow, the various ultrasound Doppler approaches are the most common tools.

For the analysis of regional cardiac muscle function, however, there are several different approaches.

For global left ventricular systolic and diastolic function, tissue Doppler has emerged as an important application, and normal values has recently been established by the research group in the HUNT population study. Tissue Doppler is also used in clinical studies into cardiac and metabolic disease and exercise training.

Analysis of regional contraction is very important for coronary artery diseases (diseases related to the blood supply of the heart) and rhythmic disorders (diseases related to the heart rhythm). The most common approach so far has been the visual assessment of the cardiac ultrasound images. But this is an operator dependant and non quantitative method. Thus, for the previous 15-20 years, the ultrasound research community and the cardiac ultrasound scanner vendors have kept on introducing new methodologies for quantitative analysis of regional cardiac function.is called deformation imaging or strain rate imaging. This is feasible both with tissue Doppler and speckle tracking. Normal values have been established in the HUNT population study. At present, the development seems to focus on combination with 3-dimensional ultrasound.

The main technological challenge in the actual imaging is to achieve the frame rate/temporal resolution and spatial resolution needed in the final video loops to resolve all cardiac details.

Tissue Doppler imaging (TDI)

(also known as Tissue Velocity Imaging (TVI), Doppler Myocardial Imaging, Myocardial Velocity Imaging)

The first commercial possibilities for measuring strains in the cardiac muscle became available on cardiac ultrasound scanners in the 90ies. The ultrasound technology research group in Trondheim made important contributions to this innovation. The basic technology of this approach was that velocities were estimated by Doppler related methods and strain was calculated based on the spatial velocity gradients. The medical research doctors were thrilled to be able to quantify the function of the left ventricle and a large research effort was made in testing this new technology. The doctors of the ultrasound group in Trondheim especially contributed by doing large studies. However, since this method could only estimate velocities and strains in the directions of the ultrasound beam, one major limitation of the method was found to be “out-of-beam-direction” and “out-of-plane” motion.

Speckle tracking

(also known as block matching, 2D strain)

One alternative approach to Tissue Doppler imaging is doing image motion analysis to follow how various structures in the ultrasound image move from frame to frame. In ultrasound this is partly made easier by the images containing “speckles” that move together with the underlying structures. The main difference between the two methods thus are that the block matching methods rely on image analysis of regular gray-scale ultrasound recordings while the Doppler based methods use a separate special acquisition and special processing. The researchers in Trondheim have been involved both in validation [6] and development of new methods. Especially, the group is known for methods combining both TDI and speckle tracking [7].

3D strain

(also known as 4D strain)

While the speckle tracking approach on 2D gray scale images can deliver 2D motion estimates, the problem of “out-of-plane” motion is still an issue. The ultrasound research community and the ultrasound scanner vendors have therefore started exploring 3D block matching and similar approaches on 3D datasets. The Trondheim ultrasound group has also contributed to these efforts [8].