Tissue motion and elasticity imaging

Abstract

The idea of using soft tissue mechanical propertiesto diagnose diseaseoccurred to ancient Greek physicians more than 2000 years ago.Hippocrates and colleagues reportedly invented manual palpation as ameans for detecting occult breast tumours before the advanced phase ofthis disease negated the effectiveness of surgical treatment. Simplepalpation is still used today for early cancer detection of the prostateand breast. We now know that tissues stiffen as some tumours form andgrow because of inflammation and desmoplasia, a dense cellular reactionspecific to malignant breast lesions with highly cross-linkedcollagenous fibres. The development of elasticity imaging is driven, inpart, by the need to improve the detection and differentiation of earlymalignant disease. However, elasticity imaging can also provide importantnew information in other clinical examinations, including visualizationof myocardial dynamics to assess tissue viability following ischaemia andskeletal muscle force generation. Methods and applications of thesetopics are addressed in the following twenty papers.The approaches to elasticity imaging vary widely but always involve theapplication of medical imaging technologies - often ultrasound andmagnetic resonance because of their high sensitivity to small tissuemovements - to track natural and applied deformations. We see fromthepapers in this special issue that elasticity is a term that applies to abroad range of parametric imaging for describing spatial and temporalvariations in tissue viscoelasticity. Static methods apply ultrasound or magnetic resonance signals inprocedures that are best described as palpation by remote sensing. Theyare considered static because the data acquisition time (1/frame rate)is much faster than the tissue deformation rate. The same signalprocessing concepts involved in measuring velocity vectors inapplications from radar tracking to blood flow imaging are used toestimate local displacement fields from echo signals recorded whilestraining body surfaces or vessel lumen mechanically or by radiationforce. From displacement estimates, images of strain (elastograms),viscosity or stimulated acoustic emission are formed. The parameterselected for display in an image depends on the diagnostic task and themeasurement geometry. Several papers in this issue discuss control oftissue movement, signal processing for parameter estimation and theircombined effects on errors and image quality. Dynamic methods are for imaging tissues strained at rates equal to orgreater than the acquisition frame rate. Some methods estimate thedistribution of shear moduli from images of low-frequency acoustic shearwaves propagating in the body. These methods, referred to assonoelasticity and magnetic resonance elastography, have been used todetect lesions and assess force generation in skeletal muscle. Also,planar tagged MR imaging is an exciting approach to the evaluation ofcardiac dynamics that visualizes strain and strain rate during thecardiac cycle. Methods and applications of dynamic elasticity imagingare also presented.Clearly, most of the approaches described in this issue are targetedtoward clinical medicine. Each has strengths and weakness that vary withapplications. However, many of these same ideas may be scaled down insize to study cell mechanics and mechano-transduction (two exciting newareas of basic research at the frontier of molecular biology), functionalgenomics and systems engineering. Perhaps the most promising aspect ofthese investigations is the interdisciplinary nature, which, in the truespirit of biomedical engineering, teaches us the value of research teamswith expertize in physiology, biomechanics, signals and systems,radiation physics and medicine. We look forward to the progress thesenew methods will bring to clinical and basic biomedical research, andwhat they will teach us about complex biological systems and diseaseprocesses.