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Multi-parameter Sub-Hertz Analysis of Viscoelasticity With a Quality Metric for Differentiation of Breast Masses.

Authors
  • Bayat, Mahdi1
  • Nabavizadeh, Alireza1
  • Nayak, Rohit2
  • Webb, Jeremy M2
  • Gregory, Adriana V2
  • Meixner, Duane D2
  • Fazzio, Robert T2
  • Insana, Michael F3
  • Alizad, Azra2
  • Fatemi, Mostafa4
  • 1 Department of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine and Science, Rochester, MN, USA.
  • 2 Department of Radiology, Mayo Clinic College Medicine and Science, Rochester, MN, USA.
  • 3 Department of Bioengineering, University of Illinois Urbana-Champaign, Champaign, IL, USA.
  • 4 Department of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine and Science, Rochester, MN, USA. Electronic address: [email protected]
Type
Published Article
Journal
Ultrasound in medicine & biology
Publication Date
Dec 01, 2020
Volume
46
Issue
12
Pages
3393–3403
Identifiers
DOI: 10.1016/j.ultrasmedbio.2020.08.004
PMID: 32917470
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

We applied sub-Hertz analysis of viscoelasticity (SAVE) to differentiate breast masses in pre-biopsy patients. Tissue response during external ramp-and-hold stress was ultrasonically detected. Displacements were used to acquire tissue viscoelastic parameters. The fast instantaneous response and slow creep-like deformations were modeled as the response of a linear standard solid from which viscoelastic parameters were estimated. These parameters were used in a multi-variable classification framework to differentiate malignant from benign masses identified by pathology. When employing all viscoelasticity parameters, SAVE resulted in 71.43% accuracy in differentiating lesions. When combined with ultrasound features and lesion size, accuracy was 82.24%. Adding a quality metric based on uniaxial motion increased the accuracy to 81.25%. When all three were combined with SAVE, accuracy was 91.3%. These results confirm the utility of SAVE as a robust ultrasound-based diagnostic tool for non-invasive differentiation of breast masses when used as stand-alone biomarkers or in conjunction with ultrasonic features. Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.

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