Engineering approaches for characterizing soft tissue mechanical properties: A review.
Area Under Curve
Bioengineering
/ methods
Biomechanical Phenomena
Brain Neoplasms
/ surgery
Breast
/ diagnostic imaging
Cell Membrane
/ ultrastructure
Diagnostic Imaging
Elasticity
Elasticity Imaging Techniques
Equipment Design
Female
Fiber Optic Technology
Humans
Liver
/ diagnostic imaging
Machine Learning
Male
Microscopy, Atomic Force
Neoplasms
/ diagnostic imaging
Prostate
/ diagnostic imaging
Robotic Surgical Procedures
Stomach
/ diagnostic imaging
Tomography, Optical Coherence
Vagina
/ diagnostic imaging
Catheters
Elastic modulus
Elastography
Indentation
Machine learning
Journal
Clinical biomechanics (Bristol, Avon)
ISSN: 1879-1271
Titre abrégé: Clin Biomech (Bristol, Avon)
Pays: England
ID NLM: 8611877
Informations de publication
Date de publication:
10 2019
10 2019
Historique:
received:
31
12
2018
revised:
14
03
2019
accepted:
15
07
2019
pubmed:
26
7
2019
medline:
21
7
2020
entrez:
26
7
2019
Statut:
ppublish
Résumé
From cancer diagnosis to detailed characterization of arterial wall biomechanics, the elastic property of tissues is widely studied as an early sign of disease onset. The fibrous structural features of tissues are a direct measure of its health and functionality. Alterations in the structural features of tissues are often manifested as local stiffening and are early signs for diagnosing a disease. These elastic properties are measured ex vivo in conventional mechanical testing regimes, however, the heterogeneous microstructure of tissues can be accurately resolved over relatively smaller length scales with enhanced spatial resolution using techniques such as micro-indentation, microelectromechanical (MEMS) based cantilever sensors and optical catheters which also facilitate in vivo assessment of mechanical properties. In this review, we describe several probing strategies (qualitative and quantitative) based on the spatial scale of mechanical assessment and also discuss the potential use of machine learning techniques to compute the mechanical properties of soft tissues. This work details state of the art advancement in probing strategies, associated challenges toward quantitative characterization of tissue biomechanics both from an engineering and clinical standpoint.
Identifiants
pubmed: 31344655
pii: S0268-0033(18)31069-6
doi: 10.1016/j.clinbiomech.2019.07.016
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
127-140Informations de copyright
Copyright © 2019 Elsevier Ltd. All rights reserved.