The principles of second harmonic imaging are simple. For harmonic imaging the system transmits at a lower frequency, referred to as the fundamental, and then receives and processes signals at twice the fundamental signal, referred to as the second harmonic. Of course the complexity comes in understanding how fundamental signals are converted into harmonic signals and ,more importantly, in understanding the benefits and limitations of harmonic imaging.

There is a nonlinear response of tissue to the compression and rarefaction of sound waves. During compression, the density of the tissue molecules increases, resulting in a slight increase in propagation speed, whereas during rarefaction, the density decreases such that there is a slight decrease in the propagation velocity. The result is that the wave becomes distorted (Fig. 4.4) as it propagates through the tissue, introducing harmonic energy into the wave. The harmonics are not limited to second harmonics, but as of now, ultrasound systems are not processing higher-order harmonics as each higher harmonic signal becomes weaker and are currently too weak for adequate image generation. The generation of harmonic energy is very nonlinear with the beam intensity (related to the parameter called the mechanical index (MI)). In essence, a slightly lower intensity (lower MI) can result in significantly less harmonic signal generation. For this reason, harmonic imaging is very sensitive to where the beam focus is placed as well to the overall transmit power used.

Making use of the harmonic signals generated by nonlinear propagation requires transducers with enough bandwidth (range of frequencies over which the transducer can operate) so that the transducer can transmit at the fundamental frequency and receive signals at twice the fundamental frequency (the second harmonic signal). Modern transducers capable of such large dynamic range are commonly referred to as ultra-wide bandwidth transducers. When the system processes the returning echoes, a filter is applied to look at just the second harmonic bandwidth, explicitly attempting to not overlap with the transmit bandwidth. Any overlap between the fundamental and harmonic bandwidths allows for the clutter from the fundamental to degrade the image quality of the harmonic signal. In order to reduce the overlap between fundamental and harmonic bandwidth, longer transmit pulses are commonly used which result in a narrower bandwidth fundamental. As discussed earlier, a longer transmit pulse (spatial pulse length) results in degraded axial resolution. For this reason, conventional harmonics generally have worse axial resolution and is generally not ideal for axial measurements (measurements made in depth) such as IMT measurements. Some systems now offer novel techniques to get around the narrow banding issue such as pulse inversion and pulse-modulated harmonics. In essence, these techniques allow for the separation of the fundamental and harmonic bandwidths without using a longer transmit pulse that results in degraded axial resolution.

The benefits of harmonic imaging are primarily a reduction of clutter artifacts. Since harmonic beams are inherently narrower than the fundamental beams, lateral resolution is improved. Additionally, since the beam intensity is generally low in the near field before the beam has converged to the focus, harmonic generation is generally low in the near field. Since most imaging artifacts result from strong reflectors in the near field (clutter signals), lower-level harmonic signals in the near field result in fewer imaging artifacts, improving image quality (Fig. 4.5). Again since harmonic generation drops precipitously with lower beam intensities (lower MI), using harmonics when trying to image very deep in a large patient is not recommended as the harmonic signal will offer inadequate sensitivity. In these deep cases, using fundamental imaging is the correct approach.

Compound imag ing (known as multi-angle imaging , Sono CT or Crossbeam technology by some manufacturers) is a frame averaging technique, which can significantly improve image quality through increased signal-to-noise ratio and by decreasing the presence of artifacts. The angle dependency of ultrasound reflection is reduced by imaging the same region from different directions and “compounding” the resulting multiple frames into one image. Like all averaging techniques, the signal-to-noise ratio is improved when the desired signal does not change or changes slowly relatively to the rate of frame acquisition. In cases where the signal is changing slowly, the signal in each of the frames has the same phase such that adding together the frames results in the signal amplitude increasing by a factor equal to the number of samples. For example, adding four signals with an amplitude of 3 V, each would result in a combined signal with an amplitude of 12 V. In contrast, the noise which exists within the image is random from frame to frame, implying that although the noise amplitude also grows with averaging, it grows at a slower rate than the signal. In fact, the noise generally grows by the rate of the square root of the number of frames used in the average. Using the same example, imagine that the noise level is 1 mV (milli Volt), averaging four frames together would result in the noise becoming bigger by the square root of four, or 2 × 1 mV equal to 2 mV. Therefore, the signal grew four times larger, whereas the noise grew only twice as large, implying that the signal-to-noise ratio increased by a factor of 4 divided by 2, or 2 times. In other words averaging improves the signal-to-noise ratio by the square root of the number of samples in the average.

In addition to averaging, compound image varies the image steering from frame to frame. Recall that specular reflection is very angle dependent. Combining this fact with the fact that most imaging artifacts are caused by specular reflection, it should be clear that compound imaging results in artifacts tending to “average out.” The net result is that compound imaging generally results in images with better signal to noise (improved sensitivity) and fewer artifacts as seen in Fig. 4.6.

Also, because of the angle dependency of ultrasound reflection, by imaging from several angles, the circumference of arteries in cross section becomes more visible with compound imaging compared to single-angle imaging (conventional ultrasound imaging technique).

Image optimization requires a comprehensive knowledge of the many system controls discussed above. There are no set rules which always govern when one technology should be applied or another disabled other than understanding the trade-offs as well as the underlying principles of each technology and control relative to the imaging situation. In general, the starting point for good image quality is to ensure adequate signal strength by appropriate transducer frequency selection, focal/foci depth, and imaging window. With respect to identification of artifacts, it is important to vary the incident angle (by electronically steering the image or physically angling the transducer) while looking for changes within the image. When the relative locations of structures vary with varying angle, imaging artifacts are present. Once the appropriate signal strength (signal-to-noise ratio) is achieved, the receiver gain and time gain compensation (TGCs) should be adjusted so that the full range of existing signals are visible relative to the ambient light and so that similar tissues at differing depths are displayed with similar brightness. Periodically, the compression should be adjusted to vary the contrast resolution so as to make certain that no signals such as fresh thrombus or masses are not being obscured by inappropriate contrast. Newer technologies such as harmonics and compound imaging often provide significant improvement but are at times inappropriate based on the trade-offs of the technologies. Finally, many systems now offer adaptive processing which attempts to perform image optimization based on internal algorithms. There are times when these adaptive processes will generate better image quality than even the most seasoned sonographer. However, there are other times when a talented sonographer will produce significantly better images than the adaptive processes. For this reason, the best use of these adaptive processes is to first optimize the image by hand and activate the adaptive process and then compare. It is then useful to optimize again by hand starting with the settings chosen by the adaptive processing technique. If the image only degrades by further manipulation, then reactivating the adaptive process will return the image to the “optimal” quality. By employing this approach, the sonographer can be pretty certain that he or she achieves optimal image qual ity.

In recent years carotid intima-media thickness (IMT) measurements have been used as an indicator for atherosclerotic disease with the intent of predicting likelihood of myocardial infarction and stroke. The ability to both accurately and repeatedly measure a vessel’s wall thickness is highly dependent on technique and ultrasound system settings. This section outlines those parameters which should be considered when performing IMT measurements . Realizing that equipment from different manufacturers will have different ideal settings, the purpose of this section is to make the reader aware of the potential issues, not to create a standard for measurement. Measurement standards require significant research and potentially may need to vary for different equipment design.