The second tissue harmonic signal: from physics principles to clinical application

The second harmonic signals received from organs are due to the non linear properties of tissue which cause distortion of the transmitted signal and are not primarily caused by the transmission of a harmonic frequency. The velocity of ultrasound propagation depends on the density of the insonified material. During the compression phase, the tissue becomes denser, and the ultrasound waves travel faster through the tissue than during the rarefaction phase; the compression phase tends to overtake the rarefaction phase. The ultrasound waveform thus, undergoes a distortion that becomes greater as the distance from the transducer increases. Due to these effects, the tissue tends to generate harmonics and hence shifts energy from the fundamental to the harmonic bands. There are several reasons why harmonic tissue imaging increases the signal-to-noise ratio and facilitates interpretation. In technically difficult patients, there is often a diffuse haze due to distortion of the transmitted beam by shallow surface layers or to reverberations between the skin and ribs. These distortions and reverberations consist almost entirely of ultrasound energy at the fundamental frequency. When the returned signal is filtered at the harmonic so as to reject the fundamental frequency, the clutter and haze are removed and the image becomes more clear and defined. A further reason for the decrease in artifacts and clutter is the side-lobe level reduction in the second harmonic beam. Thus, harmonic beams are narrower and have lower side-lobe levels than fundamental ones. There are several clinical applications of harmonic tissue imaging. These include the correct definition of endocardial borders resulting in an improved assessment of left ventricular function at rest as well as during stress testing, the delineation of the left atrial appendage, the detection of atrial right to left shunting, and left atrial spontaneous echo contrast. Moreover, improved endocardial visualization leads to better endocardial tracking with acoustic quantification and to more segments being interpretable with the anatomic M-mode.