Chapter

Acoustical Imaging

Volume 21 of the series Acoustical Imaging pp 223-240

Biophysical Bases of Elasticity Imaging

  • A. P. SarvazyanAffiliated withDepartment of Chemistry, Rutgers University
  • , A. R. SkovorodaAffiliated withInstitute of Mathematical Problems of Biology, Russian Academy of Sciences
  • , S. Y. EmelianovAffiliated withInstitute of Mathematical Problems of Biology, Russian Academy of SciencesDepartment of Radiology, University of Michigan Medical CenterDepartment of Electrical Engineering and Computer Science and Bioengineering Program, University of Michigan
  • , J. B. FowlkesAffiliated withDepartment of Radiology, University of Michigan Medical Center
  • , J. G. PipeAffiliated withDepartment of Radiology, University of Michigan Medical Center
  • , R. S. AdlerAffiliated withDepartment of Radiology, University of Michigan Medical Center
  • , R. B. BuxtonAffiliated withDepartment of Radiology, University of California at San Diego
  • , P. L. CarsonAffiliated withDepartment of Radiology, University of Michigan Medical Center

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Abstract

Elasticity imaging is based on two processes. The first is the evaluation of the mechanical response of a stressed tissue using imaging modalities, e.g. ultrasound, magnetic resonance imaging (MRI), computed tomography (CT) scans and Doppler ultrasound. The second step is depiction of the elastic properties of internal tissue structures by mathematical solution of the inverse mechanical problem. The evaluation of elastic properties of tissues has the potential for being an important diagnostic tool in the detection of cancer as well as other injuries and diseases. The success of breast self-examination in conjunction with mammography for detection and continuous monitoring of lesions has resulted in early diagnosis and institution of therapy. Self-examination is based on the manually palpable texture difference of the lesion relative to adjacent tissue and, as such, is limited to lesions located relatively near the skin surface and increased lesion hardness with respect to the surrounding tissue. Imaging of tissue “hardness” should allow more sensitive detection of abnormal structures deeper within tissue. Tissue hardness can actually be quantified in terms of the tissue elastic moduli and may provide good contrast between normal and abnormal tissues based on the large relative variation in shear (or Young’s) elastic modulus.