Finite element model of mechanical imaging of the breast

Purpose: Malignant breast lesions can be distinguished from benign lesions by their mechanical properties. This has been utilized for mechanical imaging in which the stress distribution over the breast is measured. Mechanical imaging has shown the ability to identify benign or normal cases and to re...

Full description

Saved in:
Bibliographic Details
Published inJournal of medical imaging (Bellingham, Wash.) Vol. 9; no. 3; p. 033502
Main Authors Axelsson, Rebecca, Tomic, Hanna, Zackrisson, Sophia, Tingberg, Anders, Isaksson, Hanna, Bakic, Predrag R., Dustler, Magnus
Format Journal Article
LanguageEnglish
Published United States Society of Photo-Optical Instrumentation Engineers 01.05.2022
SPIE
Subjects
Online AccessGet full text
ISSN2329-4302
2329-4310
2329-4310
DOI10.1117/1.JMI.9.3.033502

Cover

Loading…
Abstract Purpose: Malignant breast lesions can be distinguished from benign lesions by their mechanical properties. This has been utilized for mechanical imaging in which the stress distribution over the breast is measured. Mechanical imaging has shown the ability to identify benign or normal cases and to reduce the number of false positives from mammography screening. Our aim was to develop a model of mechanical imaging acquisition for simulation purposes. To that end, we simulated mammographic compression of a computer model of breast anatomy and lesions. Approach: The breast compression was modeled using the finite element method. Two finite element breast models of different sizes were used and solved using linear elastic material properties in open-source virtual clinical trial (VCT) software. A spherical lesion (15 mm in diameter) was inserted into the breasts, and both the location and stiffness of the lesion were varied extensively. The average stress over the breast and the average stress at the lesion location, as well as the relative mean pressure over lesion area (RMPA), were calculated. Results: The average stress varied 6.2–6.5 kPa over the breast surface and 7.8–11.4 kPa over the lesion, for different lesion locations and stiffnesses. These stresses correspond to an RMPA of 0.80 to 1.46. The average stress was 20% to 50% higher at the lesion location compared with the average stress over the entire breast surface. Conclusions: The average stress over the breast and the lesion location corresponded well to clinical measurements. The proposed model can be used in VCTs for evaluation and optimization of mechanical imaging screening strategies.
AbstractList Purpose: Malignant breast lesions can be distinguished from benign lesions by their mechanical properties. This has been utilized for mechanical imaging in which the stress distribution over the breast is measured. Mechanical imaging has shown the ability to identify benign or normal cases and to reduce the number of false positives from mammography screening. Our aim was to develop a model of mechanical imaging acquisition for simulation purposes. To that end, we simulated mammographic compression of a computer model of breast anatomy and lesions. Approach: The breast compression was modeled using the finite element method. Two finite element breast models of different sizes were used and solved using linear elastic material properties in open-source virtual clinical trial (VCT) software. A spherical lesion (15 mm in diameter) was inserted into the breasts, and both the location and stiffness of the lesion were varied extensively. The average stress over the breast and the average stress at the lesion location, as well as the relative mean pressure over lesion area (RMPA), were calculated. Results: The average stress varied 6.2–6.5 kPa over the breast surface and 7.8–11.4 kPa over the lesion, for different lesion locations and stiffnesses. These stresses correspond to an RMPA of 0.80 to 1.46. The average stress was 20% to 50% higher at the lesion location compared with the average stress over the entire breast surface. Conclusions: The average stress over the breast and the lesion location corresponded well to clinical measurements. The proposed model can be used in VCTs for evaluation and optimization of mechanical imaging screening strategies.
Purpose: Malignant breast lesions can be distinguished from benign lesions by their mechanical properties. This has been utilized for mechanical imaging in which the stress distribution over the breast is measured. Mechanical imaging has shown the ability to identify benign or normal cases and to reduce the number of false positives from mammography screening. Our aim was to develop a model of mechanical imaging acquisition for simulation purposes. To that end, we simulated mammographic compression of a computer model of breast anatomy and lesions. Approach: The breast compression was modeled using the finite element method. Two finite element breast models of different sizes were used and solved using linear elastic material properties in open-source virtual clinical trial (VCT) software. A spherical lesion (15 mm in diameter) was inserted into the breasts, and both the location and stiffness of the lesion were varied extensively. The average stress over the breast and the average stress at the lesion location, as well as the relative mean pressure over lesion area (RMPA), were calculated. Results: The average stress varied 6.2–6.5 kPa over the breast surface and 7.8–11.4 kPa over the lesion, for different lesion locations and stiffnesses. These stresses correspond to an RMPA of 0.80 to 1.46. The average stress was 20% to 50% higher at the lesion location compared with the average stress over the entire breast surface. Conclusions: The average stress over the breast and the lesion location corresponded well to clinical measurements. The proposed model can be used in VCTs for evaluation and optimization of mechanical imaging screening strategies.
Approach: The breast compression was modeled using the finite element method. Two finite element breast models of different sizes were used and solved using linear elastic material properties in open-source virtual clinical trial (VCT) software. A spherical lesion (15 mm in diameter) was inserted into the breasts, and both the location and stiffness of the lesion were varied extensively. The average stress over the breast and the average stress at the lesion location, as well as the relative mean pressure over lesion area (RMPA), were calculated.
Malignant breast lesions can be distinguished from benign lesions by their mechanical properties. This has been utilized for mechanical imaging in which the stress distribution over the breast is measured. Mechanical imaging has shown the ability to identify benign or normal cases and to reduce the number of false positives from mammography screening. Our aim was to develop a model of mechanical imaging acquisition for simulation purposes. To that end, we simulated mammographic compression of a computer model of breast anatomy and lesions. The breast compression was modeled using the finite element method. Two finite element breast models of different sizes were used and solved using linear elastic material properties in open-source virtual clinical trial (VCT) software. A spherical lesion (15 mm in diameter) was inserted into the breasts, and both the location and stiffness of the lesion were varied extensively. The average stress over the breast and the average stress at the lesion location, as well as the relative mean pressure over lesion area (RMPA), were calculated. The average stress varied 6.2-6.5 kPa over the breast surface and 7.8-11.4 kPa over the lesion, for different lesion locations and stiffnesses. These stresses correspond to an RMPA of 0.80 to 1.46. The average stress was 20% to 50% higher at the lesion location compared with the average stress over the entire breast surface. The average stress over the breast and the lesion location corresponded well to clinical measurements. The proposed model can be used in VCTs for evaluation and optimization of mechanical imaging screening strategies.
Purpose: Malignant breast lesions can be distinguished from benign lesions by their mechanical properties. This has been utilized for mechanical imaging in which the stress distribution over the breast is measured. Mechanical imaging has shown the ability to identify benign or normal cases and to reduce the number of false positives from mammography screening. Our aim was to develop a model of mechanical imaging acquisition for simulation purposes. To that end, we simulated mammographic compression of a computer model of breast anatomy and lesions. Approach: The breast compression was modeled using the finite element method. Two finite element breast models of different sizes were used and solved using linear elastic material properties in open-source virtual clinical trial (VCT) software. A spherical lesion (15 mm in diameter) was inserted into the breasts, and both the location and stiffness of the lesion were varied extensively. The average stress over the breast and the average stress at the lesion location, as well as the relative mean pressure over lesion area (RMPA), were calculated. Results: The average stress varied 6.2-6.5 kPa over the breast surface and 7.8-11.4 kPa over the lesion, for different lesion locations and stiffnesses. These stresses correspond to an RMPA of 0.80 to 1.46. The average stress was 20% to 50% higher at the lesion location compared with the average stress over the entire breast surface. Conclusions: The average stress over the breast and the lesion location corresponded well to clinical measurements. The proposed model can be used in VCTs for evaluation and optimization of mechanical imaging screening strategies.Purpose: Malignant breast lesions can be distinguished from benign lesions by their mechanical properties. This has been utilized for mechanical imaging in which the stress distribution over the breast is measured. Mechanical imaging has shown the ability to identify benign or normal cases and to reduce the number of false positives from mammography screening. Our aim was to develop a model of mechanical imaging acquisition for simulation purposes. To that end, we simulated mammographic compression of a computer model of breast anatomy and lesions. Approach: The breast compression was modeled using the finite element method. Two finite element breast models of different sizes were used and solved using linear elastic material properties in open-source virtual clinical trial (VCT) software. A spherical lesion (15 mm in diameter) was inserted into the breasts, and both the location and stiffness of the lesion were varied extensively. The average stress over the breast and the average stress at the lesion location, as well as the relative mean pressure over lesion area (RMPA), were calculated. Results: The average stress varied 6.2-6.5 kPa over the breast surface and 7.8-11.4 kPa over the lesion, for different lesion locations and stiffnesses. These stresses correspond to an RMPA of 0.80 to 1.46. The average stress was 20% to 50% higher at the lesion location compared with the average stress over the entire breast surface. Conclusions: The average stress over the breast and the lesion location corresponded well to clinical measurements. The proposed model can be used in VCTs for evaluation and optimization of mechanical imaging screening strategies.
Audience Academic
Author Axelsson, Rebecca
Isaksson, Hanna
Tingberg, Anders
Dustler, Magnus
Bakic, Predrag R.
Tomic, Hanna
Zackrisson, Sophia
Author_xml – sequence: 1
  givenname: Rebecca
  orcidid: 0000-0002-1970-4003
  surname: Axelsson
  fullname: Axelsson, Rebecca
  email: rebecca.axelsson@med.lu.se
  organization: Lund University, Skåne University Hospital, Diagnostic Radiology, Department of Translational Medicine, Department in Imaging and Functional Medicine, Malmö, Sweden
– sequence: 2
  givenname: Hanna
  orcidid: 0000-0002-2914-883X
  surname: Tomic
  fullname: Tomic, Hanna
  email: hanna.tomic@med.lu.se
  organization: Lund University, Skåne University Hospital, Medical Radiation Physics, Department of Translational Medicine, Malmö, Sweden
– sequence: 3
  givenname: Sophia
  surname: Zackrisson
  fullname: Zackrisson, Sophia
  email: sophia.zackrisson@med.lu.se
  organization: Lund University, Skåne University Hospital, Diagnostic Radiology, Department of Translational Medicine, Department in Imaging and Functional Medicine, Malmö, Sweden
– sequence: 4
  givenname: Anders
  orcidid: 0000-0003-3078-0725
  surname: Tingberg
  fullname: Tingberg, Anders
  email: anders.tingberg@med.lu.se
  organization: Lund University, Skåne University Hospital, Medical Radiation Physics, Department of Translational Medicine, Malmö, Sweden
– sequence: 5
  givenname: Hanna
  orcidid: 0000-0002-9690-8907
  surname: Isaksson
  fullname: Isaksson, Hanna
  email: hanna.isaksson@bme.lth.se
  organization: Lund University, Department of Biomedical Engineering, Lund, Sweden
– sequence: 6
  givenname: Predrag R.
  orcidid: 0000-0001-7087-0915
  surname: Bakic
  fullname: Bakic, Predrag R.
  email: predrag.bakic@uphs.upenn.edu
  organization: University of Pennsylvania, Department of Radiology, Philadelphia, Pennsylvania, United States
– sequence: 7
  givenname: Magnus
  orcidid: 0000-0002-5699-9664
  surname: Dustler
  fullname: Dustler, Magnus
  email: magnus.dustler@med.lu.se
  organization: Lund University, Skåne University Hospital, Diagnostic Radiology, Department of Translational Medicine, Department in Imaging and Functional Medicine, Malmö, Sweden
BackLink https://www.ncbi.nlm.nih.gov/pubmed/35647217$$D View this record in MEDLINE/PubMed
https://lup.lub.lu.se/record/df500fc4-9a74-4238-98ee-3b281e749679$$DView record from Swedish Publication Index
oai:portal.research.lu.se:publications/df500fc4-9a74-4238-98ee-3b281e749679$$DView record from Swedish Publication Index
BookMark eNqNks1v1DAQxSNUREvpnROKxIXLBn8lji9IVUWhaBEXOI9sZ7zryomXOCniv6-3u6xYRBGKrFjOb968eN7z4mSIAxbFS0oqSql8S6tPn28qVfGKcF4T9qQ4Y5ypheCUnBz2hJ0WFyndEkIoJTWj4llxyutGSEblWdFe-8FPWGLAHoep7GOHoYyu7NGu9eCtDqXv9coPq-3ptMbSjKjT9KJ46nRIeLF_nxffrt9_vfq4WH75cHN1uVzYWpFpoWRHEamxnBhZ19wQJFQK5YwQBjljpjPONMYR0TjTKd0Y6WqnDJOMW2n4eaF3uukHbmYDmzHbGX9C1B42cZx0gBET6tGuIcyQEDIVsu_JxyFB52pCnBWgtBQgGG9BtYjADWspZiONVLnH8tEeYd7kZfba_yn3bieXtXrsbL7XMds8cn70ZfBrWMU7UJTVeWpZ4M1eYIzfZ0wT9D5ZDEEPGOcErMmXw2rSkIy-3qErHRD84GJWtFscLlvBRSsbsaWqv1D56bD3NsfK-Xx-VPDq9184eP8VnAyQHWDHmNKI7oBQAtt4AoUcT1DAYRfPXNL8UWL99DCmbMaHfxUu9uPZeITbOI9DTtzj_D31HPX2
CitedBy_id crossref_primary_10_1016_j_clinbiomech_2023_106153
Cites_doi 10.1117/12.2564273
10.1109/MMBIA.2001.991694
10.1117/12.2582095
10.1115/1.4005694
10.1088/1361-6560/aaf453
10.1258/ar.2012.120238
10.1016/S1470-2045(13)70134-7
10.3389/fbioe.2015.00201
10.1121/1.406353
10.1002/ijc.22104
10.1016/S0140-6736(12)61611-0
10.1109/TBME.2007.893493
10.1016/j.ultrasmedbio.2008.02.002
10.1007/s00330-016-4723-6
10.1118/1.4862512
10.1088/0031-9155/52/6/002
10.1109/ISBI.2009.5193259
10.3322/caac.21660
10.1118/1.4945275
10.1016/S1470-2045(18)30521-7
10.1093/jnci/djy121
10.1109/TMI.2002.808367
10.1117/12.2216688
10.1118/1.4812418
10.1148/radiol.12121373
10.3233/THC-2007-15404
10.1007/s10549-013-2674-z
10.1118/1.3637500
10.1016/S1076-6332(03)80640-2
10.1117/12.2294935
10.1109/TNS.2005.862983
10.1007/s10549-009-0369-2
10.1001/jamanetworkopen.2018.5474
10.1109/EMBC.2013.6611231
10.1177/0284185120976925
10.1007/978-3-319-07887-8_1
10.1177/016173469802000403
10.1158/1055-9965.EPI-05-0953
10.1001/archsurg.135.2.158
ContentType Journal Article
Copyright The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
2022 The Authors.
COPYRIGHT 2022 SPIE
2022 The Authors 2022 The Authors
Copyright_xml – notice: The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
– notice: 2022 The Authors.
– notice: COPYRIGHT 2022 SPIE
– notice: 2022 The Authors 2022 The Authors
CorporateAuthor Institutioner vid LTH
LUCC: Lunds universitets cancercentrum
Övriga starka forskningsmiljöer
Faculty of Engineering, LTH
Lunds Tekniska Högskola
Institutionen för biomedicinsk teknik
Division for Biomedical Engineering
LTH Profile areas
Radiology Diagnostics, Malmö
Strategiska forskningsområden (SFO)
LTH profilområde: Teknik för hälsa
Medical Radiation Physics, Malmö
LUCC: Lund University Cancer Centre
Medicinska fakulteten
Departments at LTH
Institutionen för translationell medicin
Department of Translational Medicine
Profile areas and other strong research environments
Lunds universitet
LTH profilområden
Lund University
Department of Biomedical Engineering
Diagnostisk radiologi, Malmö
Other Strong Research Environments
LTH Profile Area: Engineering Health
EpiHealth: Epidemiology for Health
LTH profilområde: Avancerade ljuskällor
Faculty of Medicine
LTH Profile Area: Photon Science and Technology
Strategic research areas (SRA)
Medicinsk strålningsfysik, Malmö
Avdelningen för biomedicinsk teknik
Profilområden och andra starka forskningsmiljöer
CorporateAuthor_xml – name: Övriga starka forskningsmiljöer
– name: LTH profilområde: Teknik för hälsa
– name: Strategiska forskningsområden (SFO)
– name: LUCC: Lund University Cancer Centre
– name: Medicinsk strålningsfysik, Malmö
– name: LTH Profile Area: Photon Science and Technology
– name: LTH Profile Area: Engineering Health
– name: EpiHealth: Epidemiology for Health
– name: Strategic research areas (SRA)
– name: Department of Biomedical Engineering
– name: Lunds Tekniska Högskola
– name: Departments at LTH
– name: Faculty of Engineering, LTH
– name: Lund University
– name: Medical Radiation Physics, Malmö
– name: Profile areas and other strong research environments
– name: Institutioner vid LTH
– name: Institutionen för biomedicinsk teknik
– name: Institutionen för translationell medicin
– name: Faculty of Medicine
– name: Medicinska fakulteten
– name: Other Strong Research Environments
– name: Avdelningen för biomedicinsk teknik
– name: Radiology Diagnostics, Malmö
– name: Diagnostisk radiologi, Malmö
– name: LTH profilområde: Avancerade ljuskällor
– name: Lunds universitet
– name: Profilområden och andra starka forskningsmiljöer
– name: LTH Profile areas
– name: LTH profilområden
– name: Division for Biomedical Engineering
– name: Department of Translational Medicine
– name: LUCC: Lunds universitets cancercentrum
DBID AAYXX
CITATION
NPM
7X8
5PM
ADTPV
AGCHP
AOWAS
D8T
D95
ZZAVC
DOI 10.1117/1.JMI.9.3.033502
DatabaseName CrossRef
PubMed
MEDLINE - Academic
PubMed Central (Full Participant titles)
SwePub
SWEPUB Lunds universitet full text
SwePub Articles
SWEPUB Freely available online
SWEPUB Lunds universitet
SwePub Articles full text
DatabaseTitle CrossRef
PubMed
MEDLINE - Academic
DatabaseTitleList


PubMed

MEDLINE - Academic

Database_xml – sequence: 1
  dbid: NPM
  name: PubMed
  url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
DeliveryMethod fulltext_linktorsrc
Discipline Medicine
EISSN 2329-4310
EndPage 033502
ExternalDocumentID oai_portal_research_lu_se_publications_df500fc4_9a74_4238_98ee_3b281e749679
oai_lup_lub_lu_se_df500fc4_9a74_4238_98ee_3b281e749679
PMC9125329
A843487640
35647217
10_1117_1_JMI_9_3_033502
Genre Journal Article
GrantInformation_xml – fundername: Stiftelsen för Cancerforskning vid Onkologiska kliniken vid Universitetssjukhuset MAS
– fundername: Cancerfonden
  funderid: https://doi.org/10.13039/501100002794
– fundername: Swedish Breast Cancer Association
– fundername: European Commission H2020 Marie Skłodowska-Curie Actions Fellowship
  grantid: IF 846540
– fundername: Cancerfonden
GroupedDBID 0R
4.4
ACGFS
ALMA_UNASSIGNED_HOLDINGS
EBS
FQ0
M4X
O9-
OK1
RPM
SPBNH
UT2
0R~
AAYXX
ABJNI
ADMLS
AKROS
CITATION
HYE
EJD
NPM
7X8
5PM
ADTPV
AGCHP
AOWAS
D8T
D95
ZZAVC
ID FETCH-LOGICAL-c590t-97d1ee1bc30b7553b0e01749fb44be322bdbfb6bf046fbd9a6b7f5f9b2723c7b3
ISSN 2329-4302
2329-4310
IngestDate Thu Aug 21 06:47:39 EDT 2025
Thu Jul 03 04:48:48 EDT 2025
Thu Aug 21 18:36:48 EDT 2025
Fri Jul 11 02:17:36 EDT 2025
Wed Jun 18 17:00:35 EDT 2025
Tue Jun 17 03:41:17 EDT 2025
Wed Feb 19 02:23:42 EST 2025
Tue Jul 01 02:15:59 EDT 2025
Thu Apr 24 23:06:07 EDT 2025
Sun Jul 03 12:42:39 EDT 2022
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 3
Keywords breast cancer
mammography
finite element
virtual clinical trial
mechanical imaging
Language English
License 2022 The Authors.
Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
LinkModel OpenURL
MergedId FETCHMERGED-LOGICAL-c590t-97d1ee1bc30b7553b0e01749fb44be322bdbfb6bf046fbd9a6b7f5f9b2723c7b3
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Shared senior authorship.
ORCID 0000-0002-1970-4003
0000-0002-5699-9664
0000-0001-7087-0915
0000-0002-9690-8907
0000-0002-2914-883X
0000-0003-3078-0725
OpenAccessLink oai:portal.research.lu.se:publications/df500fc4-9a74-4238-98ee-3b281e749679
PMID 35647217
PQID 2672325060
PQPubID 23479
PageCount 1
ParticipantIDs gale_infotracacademiconefile_A843487640
swepub_primary_oai_portal_research_lu_se_publications_df500fc4_9a74_4238_98ee_3b281e749679
crossref_primary_10_1117_1_JMI_9_3_033502
swepub_primary_oai_lup_lub_lu_se_df500fc4_9a74_4238_98ee_3b281e749679
proquest_miscellaneous_2672325060
gale_infotracmisc_A843487640
pubmedcentral_primary_oai_pubmedcentral_nih_gov_9125329
spie_journals_10_1117_1_JMI_9_3_033502
pubmed_primary_35647217
crossref_citationtrail_10_1117_1_JMI_9_3_033502
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2022-05-01
PublicationDateYYYYMMDD 2022-05-01
PublicationDate_xml – month: 05
  year: 2022
  text: 2022-05-01
  day: 01
PublicationDecade 2020
PublicationPlace United States
PublicationPlace_xml – name: United States
PublicationTitle Journal of medical imaging (Bellingham, Wash.)
PublicationTitleAlternate J. Med. Imag
PublicationYear 2022
Publisher Society of Photo-Optical Instrumentation Engineers
SPIE
Publisher_xml – name: Society of Photo-Optical Instrumentation Engineers
– name: SPIE
References r2
r3
r4
r5
r6
r7
r8
r9
Lago (r29) 2013
Wellman (r37) 1999
r30
Vorrherr (r47) 1974
r10
r32
r31
r34
r11
r33
r14
r36
r13
r16
r38
r15
r18
r17
r39
r19
Park (r22) 1984
Sarvazyan (r21) 1994
Fung (r44) 1993
Lago (r35) 2013
r41
r40
r43
r20
r42
Bolejko (r12) 2014
r23
r45
r25
r24
r46
r27
r26
r48
r28
r1
References_xml – ident: r33
  doi: 10.1117/12.2564273
– ident: r23
  doi: 10.1109/MMBIA.2001.991694
– start-page: 261
  year: 1993
  ident: r44
– ident: r48
  doi: 10.1117/12.2582095
– ident: r30
  doi: 10.1115/1.4005694
– ident: r34
  doi: 10.1088/1361-6560/aaf453
– ident: r40
  doi: 10.1258/ar.2012.120238
– ident: r5
  doi: 10.1016/S1470-2045(13)70134-7
– year: 1984
  ident: r22
– year: 2013
  ident: r29
  article-title: Modelling of mammographic compression of antropomorphic software breast phantom using FEBio
– ident: r17
  doi: 10.3389/fbioe.2015.00201
– ident: r9
  doi: 10.1121/1.406353
– ident: r31
  doi: 10.1002/ijc.22104
– ident: r2
  doi: 10.1016/S0140-6736(12)61611-0
– ident: r19
  doi: 10.1109/TBME.2007.893493
– year: 1999
  ident: r37
  article-title: Breast tissue stiffness in compression is correlated to histological diagnosis
– ident: r46
  doi: 10.1016/j.ultrasmedbio.2008.02.002
– ident: r11
  doi: 10.1007/s00330-016-4723-6
– ident: r43
  doi: 10.1118/1.4862512
– ident: r45
  doi: 10.1088/0031-9155/52/6/002
– ident: r32
  doi: 10.1109/ISBI.2009.5193259
– ident: r1
  doi: 10.3322/caac.21660
– ident: r18
  doi: 10.1118/1.4945275
– ident: r6
  doi: 10.1016/S1470-2045(18)30521-7
– ident: r7
  doi: 10.1093/jnci/djy121
– ident: r20
  doi: 10.1109/TMI.2002.808367
– start-page: 69
  year: 1994
  ident: r21
  article-title: Elastic imaging as a new modality of medical imaging for cancer detection
– ident: r39
  doi: 10.1117/12.2216688
– ident: r42
  doi: 10.1118/1.4812418
– ident: r4
  doi: 10.1148/radiol.12121373
– ident: r36
  doi: 10.3233/THC-2007-15404
– ident: r41
  doi: 10.1007/s10549-013-2674-z
– ident: r24
  doi: 10.1118/1.3637500
– year: 2014
  ident: r12
  article-title: Psychosocial consequences of false-positive mammography among women attending breast cancer screening. Assessment, prediction, and coping
– ident: r15
  doi: 10.1016/S1076-6332(03)80640-2
– ident: r28
  doi: 10.1117/12.2294935
– ident: r26
  article-title: Tekscan
– year: 2013
  ident: r35
  article-title: A new approach for the in-vivo characterization of the biomechanical behavior of the breast and cornea
– ident: r14
  doi: 10.1109/TNS.2005.862983
– ident: r8
  doi: 10.1007/s10549-009-0369-2
– ident: r25
  doi: 10.1001/jamanetworkopen.2018.5474
– ident: r16
  doi: 10.1109/EMBC.2013.6611231
– ident: r27
  doi: 10.1177/0284185120976925
– ident: r13
  doi: 10.1007/978-3-319-07887-8_1
– year: 1974
  ident: r47
– ident: r10
  doi: 10.1177/016173469802000403
– ident: r3
  doi: 10.1158/1055-9965.EPI-05-0953
– ident: r38
  doi: 10.1001/archsurg.135.2.158
SSID ssj0001105214
Score 2.2056124
Snippet Purpose: Malignant breast lesions can be distinguished from benign lesions by their mechanical properties. This has been utilized for mechanical imaging in...
Malignant breast lesions can be distinguished from benign lesions by their mechanical properties. This has been utilized for mechanical imaging in which the...
Approach: The breast compression was modeled using the finite element method. Two finite element breast models of different sizes were used and solved using...
SourceID swepub
pubmedcentral
proquest
gale
pubmed
crossref
spie
SourceType Open Access Repository
Aggregation Database
Index Database
Enrichment Source
Publisher
StartPage 033502
SubjectTerms breast cancer
Clinical Medicine
finite element
Finite element method
Klinisk medicin
Mammography
mechanical imaging
Medical and Health Sciences
Medicin och hälsovetenskap
Physics of Medical Imaging
Radiologi och bildbehandling
Radiology and Medical Imaging
Radiology, Nuclear Medicine and Medical Imaging
virtual clinical trial
Title Finite element model of mechanical imaging of the breast
URI http://www.dx.doi.org/10.1117/1.JMI.9.3.033502
https://www.ncbi.nlm.nih.gov/pubmed/35647217
https://www.proquest.com/docview/2672325060
https://pubmed.ncbi.nlm.nih.gov/PMC9125329
https://lup.lub.lu.se/record/df500fc4-9a74-4238-98ee-3b281e749679
oai:portal.research.lu.se:publications/df500fc4-9a74-4238-98ee-3b281e749679
Volume 9
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3di9NAEF9qBfFF_DZ6SgRRRNJLspts9rHIHedBffEOjntZdjcbGmzTYlsQX_3Hnf1ompTzOEUfGsImu83u_HYyM5kPhN5IwSqJGYkynRURyWMZFYkgUZrkLC00VqXNtj_5nJ-ck9OL7GIw-NnxWtqs5Uj9uDKu5G-oCm1AVxMl-weUbQeFBjgH-sIRKAzHG9H4uDYS4wftXMBdVRv3wdzE89rlr-e-DJFzBZDGB71nju9IpHP_0WbbB4RPE74Dpz6Y2lReGnVtB9-1mWLTodPOaj2vbfH0E9E0beulUF-Bq_guXxbLab3rAf-zdTYb25CbrkUClNnW_88xLhDSWASCSdzlsqwDJtzhmMlv-LjNBDA6nXwasREexRhncbp7Z_WyYztFhfvsSFM-2_CV5suO2ZOXVRbHlSKcCUo4iJAFZ4XWHMu0SDQlLKfsFrqdgq6Rdkw-1lCXmPhmYosU2nlZP9Z2jttP3wk93H_cnqiz_8LvSDz73rjD1bLWe6lrrbhzdh_d86gIxw50D9BANw_RnYn3xHiECoe90GMvtNgLF1W4w17ocWRaAXuhw95jdH58dPbxJPJVOCKVsXgdMVomWidS4VjSLMMy1sDFCWxxQqSG94EsZSVzWcUkr2TJRC5plVVMpjTFikr8BA2bRaOfoVDIWDClMs1Kk0kPC8mUyApRMJXkuS4CdLhdMK58inpTKWXGnapKecJhiTnjmLslDtD7tsfSpWe55t53hgbcAA1GVcIHoMCzmRxofFwQDOp7TuIAHfTuBI6repdfb6nIzSXjptjoxWbF0xzmnJqcnQF66qjaPhbOTKWGhAaI9ujd3mCh3LvS1FOb8J2BFgJ4C9BbgwzuOdDqmpkeOez0xp5tlvCTfnvcZEcE6PKKcf7Rdnv-Pwd_ge7uONMBGq6_bfRL0B7W8pXd3b8AECIZPA
linkProvider National Library of Medicine
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Finite+element+model+of+mechanical+imaging+of+the+breast&rft.jtitle=Journal+of+medical+imaging+%28Bellingham%2C+Wash.%29&rft.au=Axelsson%2C+Rebecca&rft.au=Tomic%2C+Hanna&rft.au=Zackrisson%2C+Sophia&rft.au=Tingberg%2C+Anders&rft.date=2022-05-01&rft.issn=2329-4310&rft.volume=9&rft.issue=3&rft.spage=1&rft_id=info:doi/10.1117%2F1.JMI.9.3.033502&rft.externalDocID=oai_portal_research_lu_se_publications_df500fc4_9a74_4238_98ee_3b281e749679
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2329-4302&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2329-4302&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2329-4302&client=summon