title: Inverse finite-element modeling for tissue parameter identification using a rolling indentation probe.
abstract: This paper investigates the use of inverse finite-element modeling (IFEM)-based methods for tissue parameter identification using a rolling indentation probe for surgical palpation. An IFEM-based algorithm is proposed for tissue parameter identification through uniaxial indentation. IFEM-based algorithms are also created for locating and identifying the properties of an embedded tumor through rolling indentation of the soft tissue. Two types of parameter identification for the tissue tumor are investigated (1) identifying the stiffness (μ) of a tumor at a known depth and (2) estimating the depth of the tumor (D) with known mechanical properties. The efficiency of proposed methods has been evaluated through silicone and porcine kidney experiments for both uniaxial indentation and rolling indentation. The results show that both of the proposed IFEM methods for uniaxial indentation and rolling indentation have good robustness and can rapidly converge to the correct results. The tissue properties estimated using the developed method are generic and in good agreement with results obtained from standard material tests. The estimation error of μ through uniaxial indentation is below 3 % for both silicone and kidney; the estimation error of μ for the tumor through rolling indentation is 7-9 %. The estimation error of D through rolling indentation is 1-2 mm.
authors.affiliation: Department of Informatics, Centre for Robotics Research, King's College London, London, UK, hongbin.liu@kcl.ac.uk.
authors.forename: Hongbin
authors.initials: H
authors.lastname: Liu
authors.forename: Kiattisak
authors.initials: K
authors.lastname: Sangpradit
authors.forename: Min
authors.initials: M
authors.lastname: Li
authors.forename: Prokar
authors.initials: P
authors.lastname: Dasgupta
authors.forename: Kaspar
authors.initials: K
authors.lastname: Althoefer
authors.forename: Lakmal D
authors.initials: LD
authors.lastname: Seneviratne
mesh_terms: D000465:Algorithms; D000818:Animals; D001696:Biomechanical Phenomena / Q000502:physiology; D020342:Finite Element Analysis; D010173:Palpation / Q000295:instrumentation* / Q000379:methods*; D013314:Stress, Mechanical; D013552:Swine
references.citation: Med Biol Eng Comput. 2012 Sep;50(9):961-71
references.pmid: 22772733
references.citation: IEEE Trans Biomed Eng. 2010 Feb;57(2):404-14
references.pmid: 19789104
references.citation: IEEE Trans Biomed Eng. 2011 Dec;58(12):3319-27
references.pmid: 21257372
references.citation: IEEE Trans Biomed Eng. 2011 Oct;58(10):2852-9
references.pmid: 21724500
references.citation: Med Biol Eng Comput. 2013 Feb;51(1-2):197-205
references.pmid: 23143477
references.citation: Med Image Anal. 2002 Sep;6(3):275-87
references.pmid: 12270232
references.citation: J Biomech. 2008;41(1):69-77
references.pmid: 17727862
references.citation: J Biomech. 2006;39(7):1279-86
references.pmid: 15907330
references.citation: IEEE Trans Med Imaging. 2006 Oct;25(10):1329-40
references.pmid: 17024836
references.citation: AJNR Am J Neuroradiol. 2000 Feb;21(2):282-9
references.pmid: 10696009
references.citation: Med Eng Phys. 2005 Dec;27(10):893-909
references.pmid: 16271490
references.citation: J Am Coll Surg. 2013 Jun;216(6):1168-73
references.pmid: 23623223
references.citation: Phys Med Biol. 2004 Sep 21;49(18):4395-405
references.pmid: 15509073
references.citation: J Biomech. 2005 Jan;38(1):153-8
references.pmid: 15519351
references.citation: Ultrasound Med Biol. 2008 Jul;34(7):1033-42
references.pmid: 18258350
references.citation: J Appl Clin Med Phys. 2009 Apr 22;10(2):3-10
references.pmid: 19458592
references.citation: Med Image Comput Comput Assist Interv. 2005;8(Pt 2):599-606
references.pmid: 16686009
references.citation: Int J Med Robot. 2008 Mar;4(1):58-68
references.pmid: 18225854
references.citation: Ultrason Imaging. 1998 Oct;20(4):260-74
references.pmid: 10197347
references.citation: Arch Surg. 2001 Feb;136(2):204-8
references.pmid: 11177142