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Intelligent non-invasive modeling of ultrasound-induced temperature in tissue phantoms

2017-03Journal article Restricted access
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dc.contributor.authorFerreira, R.
dc.contributor.authorRuano, M G
dc.contributor.authorRuano, Antonio
dc.date.accessioned2019-11-20T15:07:47Z
dc.date.available2019-11-20T15:07:47Z
dc.date.issued2017-03
dc.description.abstractRaising temperature of human cells (hyperthermia) is an ancient tool for tumor masses reduction and extinction, actually even before the existence of a molecular understanding of cancer cells. Hyperthermia is being increasingly used for patients' rehabilitation and oncological diseases' treatment but still constitutes a major driver for researching more efficient and reliable therapeutic usage aiming at outstanding patients wellbeing and socio-economic benefits. Efficient hyperthermia practice demands knowledge about the exact amount of heating required at a particular tissue location, as well as information concerning the spatial heating distribution. Both of these processes require accurate characterization. Until now, ultrasound heating treatments are being monitored by magnetic resonance imaging (MRI), recognized as being capable of achieving a 0.5 degrees C/cm(3) temperature resolution [1], thereby imposing a gold standard in this field. However, one can notice that MRI-based techniques, besides the inconvenient instrumental cost, obliges the presence of a team of expert clinicians and limits the hyperthermia ultrasound treatment area due to the space restrictions of an MRI examination procedure. This article introduces a novel noninvasive modelling approach of ultrasound-induced temperature propagation in tissues, to be used as a cost effective alternative to MRI monitoring of ultrasound therapeutic techniques, achieving a maximum temperature resolution of 0.26 degrees C/cm(3), clearly inferior to the MRI gold standard resolution of 0.5 degrees C/cm(3). In order to derive the model, and avoiding painful invasive in-vivo sampling, a phantom was employed, whose composition respects the human tissues' reaction to ultrasound beams. In contrast with previous works of the authors, in the present paper we study the possibility of using b-spline neural networks (BSNN) as reliable noninvasive estimator of temperature propagation in phantoms [2,3]. The proposed methodology achieves better results than previous approaches, does not require the use of an Imaging Ultrasound transducer and, as the proposed models are piecewise polynomial models, they can be easily inverted and used in closed-loop control of therapeutic ultrasound instruments. (C) 2016 Elsevier Ltd. All rights reserved.
dc.description.sponsorshipPortuguese Foundation for Science and Technology, through IDMEC, under LAETA [UID/EMS/50022/2013]
dc.identifier.doi10.1016/j.bspc.2016.11.017
dc.identifier.issn1746-8094
dc.identifier.issn1746-8108
dc.identifier.urihttp://hdl.handle.net/10400.1/13216
dc.language.isoeng
dc.peerreviewedyes
dc.publisherElsevier Sci Ltd
dc.titleIntelligent non-invasive modeling of ultrasound-induced temperature in tissue phantoms
dc.typejournal article
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FEMS%2F50022%2F2013/PT
oaire.citation.endPage150
oaire.citation.startPage141
oaire.citation.titleBiomedical Signal Processing and Control
oaire.citation.volume33
oaire.fundingStream5876
person.familyNameRuano
person.familyNameRuano
person.givenNameMaria
person.givenNameAntonio
person.identifier.ciencia-id9811-A0DD-D5A5
person.identifier.orcid0000-0002-0014-9257
person.identifier.orcid0000-0002-6308-8666
person.identifier.ridA-8321-2011
person.identifier.ridB-4135-2008
person.identifier.scopus-author-id7004483805
person.identifier.scopus-author-id7004284159
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsrestrictedAccess
rcaap.typearticle
relation.isAuthorOfPublication61fc8492-d73f-46ca-a3a3-4cd762a784e6
relation.isAuthorOfPublication13813664-b68b-40aa-97a9-91481a31ebf2
relation.isAuthorOfPublication.latestForDiscovery13813664-b68b-40aa-97a9-91481a31ebf2
relation.isProjectOfPublication53083a92-791c-473a-8e29-3007fc4bb131
relation.isProjectOfPublication.latestForDiscovery53083a92-791c-473a-8e29-3007fc4bb131

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