Literature DB >> 15936495

Comparative evaluation of strain-based and model-based modulus elastography.

Marvin M Doyley1, Seshadri Srinivasan, Sarah A Pendergrass, Ziji Wu, Jonathan Ophir.   

Abstract

Elastography based on strain imaging currently endures mechanical artefacts and limited contrast transfer efficiency. Solving the inverse elasticity problem (IEP) should obviate these difficulties; however, this approach to elastography is often fraught with problems because of the ill-posed nature of the IEP. The aim of the present study was to determine how the quality of modulus elastograms computed by solving the IEP compared with those produced using standard strain imaging methodology. Strain-based modulus elastograms (i.e., modulus elastograms computed by simply inverting strain elastograms based on the assumption of stress uniformity) and model-based modulus elastograms (i.e., modulus elastograms computed by solving the IEP) were computed from a common cohort of simulated and gelatin-based phantoms that contained inclusions of varying size and modulus contrast. The ensuing elastograms were evaluated by employing the contrast-to-noise ratio (CNR(e)) and the contrast transfer efficiency (CTE(e)) performance metrics. The results demonstrated that, at a fixed spatial resolution, the CNR(e) of strain-based modulus elastograms was statistically equivalent to those computed by solving the IEP. At low modulus contrast, the CTE(e) of both elastographic imaging approaches was comparable; however, at high modulus, the CTE(e) of model-based modulus elastograms was superior.

Mesh:

Year:  2005        PMID: 15936495     DOI: 10.1016/j.ultrasmedbio.2005.02.005

Source DB:  PubMed          Journal:  Ultrasound Med Biol        ISSN: 0301-5629            Impact factor:   2.998


  17 in total

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Authors:  Armen Sarvazyan; Timothy J Hall; Matthew W Urban; Mostafa Fatemi; Salavat R Aglyamov; Brian S Garra
Journal:  Curr Med Imaging Rev       Date:  2011-11

2.  Visualizing the stress distribution within vascular tissues using intravascular ultrasound elastography: a preliminary investigation.

Authors:  Michael S Richards; Renato Perucchio; Marvin M Doyley
Journal:  Ultrasound Med Biol       Date:  2015-03-31       Impact factor: 2.998

3.  Effects of frequency- and direction-dependent elastic materials on linearly elastic MRE image reconstructions.

Authors:  I M Perreard; A J Pattison; M Doyley; M D J McGarry; Z Barani; E E Van Houten; J B Weaver; K D Paulsen
Journal:  Phys Med Biol       Date:  2010-10-28       Impact factor: 3.609

4.  Quantitative sparse array vascular elastography: the impact of tissue attenuation and modulus contrast on performance.

Authors:  Steven Huntzicker; Rohit Nayak; Marvin M Doyley
Journal:  J Med Imaging (Bellingham)       Date:  2014-07-04

Review 5.  Medical ultrasound: imaging of soft tissue strain and elasticity.

Authors:  Peter N T Wells; Hai-Dong Liang
Journal:  J R Soc Interface       Date:  2011-06-16       Impact factor: 4.118

6.  Elastography: general principles and clincial applications.

Authors:  M M Doyley; K J Parker
Journal:  Ultrasound Clin       Date:  2014-01

7.  Shear modulus reconstruction by ultrasonically measured strain ratio.

Authors:  Chikayoshi Sumi; Hidenori Matsuzawa
Journal:  J Med Ultrason (2001)       Date:  2007-12-14       Impact factor: 1.314

8.  Model-based elastography: a survey of approaches to the inverse elasticity problem.

Authors:  M M Doyley
Journal:  Phys Med Biol       Date:  2012-01-06       Impact factor: 3.609

9.  Elastographic Assessment of Xenograft Pancreatic Tumors.

Authors:  Hexuan Wang; Michael D Nieskoski; Kayla Marra; Jason R Gunn; Stuart B Trembly; Brian W Pogue; Marvin M Doyley
Journal:  Ultrasound Med Biol       Date:  2017-09-28       Impact factor: 2.998

10.  Learning hidden elasticity with deep neural networks.

Authors:  Chun-Teh Chen; Grace X Gu
Journal:  Proc Natl Acad Sci U S A       Date:  2021-08-03       Impact factor: 11.205

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