Tissue motion and elasticity imaging.

The idea of using soft tissue mechanical properties to diagnose disease occurred to ancient Greek physicians more than 2000 years ago. Hippocrates and colleagues reportedly invented manual palpation as a means for detecting occult breast tumours before the advanced phase of this disease negated the effectiveness of surgical treatment. Simple palpation is still used today for early cancer detection of the prostate and breast. We now know that tissues stiffen as some tumours form and grow because of inflammation and desmoplasia, a dense cellular reaction specific to malignant breast lesions with highly cross-linked collagenous fibres. The development of elasticity imaging is driven, in part, by the need to improve the detection and differentiation of early malignant disease. However, elasticity imaging can also provide important new information in other clinical examinations, including visualization of myocardial dynamics to assess tissue viability following ischaemia and skeletal muscle force generation. Methods and applications of these topics are addressed in the following twenty papers. The approaches to elasticity imaging vary widely but always involve the application of medical imaging technologies - often ultrasound and magnetic resonance because of their high sensitivity to small tissue movements - to track natural and applied deformations. We see from the papers in this special issue that elasticity is a term that applies to a broad range of parametric imaging for describing spatial and temporal variations in tissue viscoelasticity. Static methods apply ultrasound or magnetic resonance signals in procedures that are best described as palpation by remote sensing. They are considered static because the data acquisition time (1/frame rate) is much faster than the tissue deformation rate. The same signal processing concepts involved in measuring velocity vectors in applications from radar tracking to blood flow imaging are used to estimate local displacement fields from echo signals recorded while straining body surfaces or vessel lumen mechanically or by radiation force. From displacement estimates, images of strain (elastograms), viscosity or stimulated acoustic emission are formed. The parameter selected for display in an image depends on the diagnostic task and the measurement geometry. Several papers in this issue discuss control of tissue movement, signal processing for parameter estimation and their combined effects on errors and image quality. Dynamic methods are for imaging tissues strained at rates equal to or greater than the acquisition frame rate. Some methods estimate the distribution of shear moduli from images of low-frequency acoustic shear waves propagating in the body. These methods, referred to as sonoelasticity and magnetic resonance elastography, have been used to detect lesions and assess force generation in skeletal muscle. Also, planar tagged MR imaging is an exciting approach to the evaluation of cardiac dynamics that visualizes strain and strain rate during the cardiac cycle. Methods and applications of dynamic elasticity imaging are also presented. Clearly, most of the approaches described in this issue are targeted toward clinical medicine. Each has strengths and weakness that vary with applications. However, many of these same ideas may be scaled down in size to study cell mechanics and mechano-transduction (two exciting new areas of basic research at the frontier of molecular biology), functional genomics and systems engineering. Perhaps the most promising aspect of these investigations is the interdisciplinary nature, which, in the true spirit of biomedical engineering, teaches us the value of research teams with expertize in physiology, biomechanics, signals and systems, radiation physics and medicine. We look forward to the progress these new methods will bring to clinical and basic biomedical research, and what they will teach us about complex biological systems and disease processes.