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Mapping electrical properties heterogeneity of tumor using boundary informed electrical properties tomography (BIEPT) at 7T
Purposes To develop and evaluate a boundary informed electrical properties tomography (BIEPT) technique for high‐resolution imaging of tumor electrical properties (EPs) heterogeneity on a rodent tumor xenograft model. Methods Tumor EP distributions were inferred from a reference area external to the...
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Published in: | Magnetic resonance in medicine 2019-01, Vol.81 (1), p.393-409 |
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creator | Wang, Yicun Shao, Qi Van de Moortele, Pierre‐Francois Racila, Emilian Liu, Jiaen Bischof, John He, Bin |
description | Purposes
To develop and evaluate a boundary informed electrical properties tomography (BIEPT) technique for high‐resolution imaging of tumor electrical properties (EPs) heterogeneity on a rodent tumor xenograft model.
Methods
Tumor EP distributions were inferred from a reference area external to the tumor, as well as internal EP spatial variations derived from a plurality of relative transmit B1 measurements at 7T. Edge sparsity constraint was enforced to enhance numerical stability. Phantom experiments were performed to determine the imaging accuracy and sensitivity for structures of various EP values, as well as geometrical sizes down to 1.5 mm. Numerical simulation of a realistic rodent model was used to quantify the algorithm performance in the presence of noise. Eleven athymic rats with human breast cancer xenograft were imaged in vivo, and representative pathological samples were acquired for comparison.
Results
Reconstructed EPs of the phantoms correspond well to the ground truth acquired from dielectric probe measurements, with the smallest structure reliably detectable being 3 mm. EPs heterogeneity inside a tumor is successfully retrieved in both simulated and experimental cases. In vivo tumor imaging results demonstrate similar local features and spatial patterns to anatomical MRI and pathological slides. The imaged conductivity of necrotic tissue is higher than that of viable tissues, which agrees with our expectation.
Conclusion
BIEPT enables robust detection of tumor EPs heterogeneity with high accuracy and sensitivity to small structures. The retrieved quantitative EPs reflect tumor pathological features (e.g., necrosis). These results provide strong rationale to further expand BIEPT studies toward pathological conditions where EPs may yield valuable, non‐invasive biomarkers. |
doi_str_mv | 10.1002/mrm.27414 |
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fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2137754113</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2137754113</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4544-b15456fd0a93afdd0a49adb39016b917114efc97163b5bd77bc05f172aea39e93</originalsourceid><addsrcrecordid>eNp1kLFOwzAQhi0EoqUw8ALIEgsd0tqxHcsjVAUqUYFQmSMnubSpmjjYiVDEy-OSwtbpX7777u5H6JqSCSUknJa2nISSU36ChlSEYRAKxU_RkEhOAkYVH6AL57aEEKUkP0cDRkJGIsKG6Hup67qo1hh2kDa2SPUO19bUYJsCHN5AA9asoYKi6bDJcdOWxuLW7UcS01aZth0uqtzYErIjksaUZm11venw3cNi_rYaY91gubpEZ7neObg65Ah9PM5Xs-fg5fVpMbt_CVIuOA8SKriI8oxoxXSe-eRKZwlThEaJopJSDnmqJI1YIpJMyiQlIqcy1KCZAsVG6Lb3-ps-W3BNvDWtrfzKOKRMSsEpZZ4a91RqjXMW8ri2RenfiymJ9zXHvub4t2bP3hyMbeL__if_evXAtAe-ih10x03x8n3ZK38AHNeIjw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2137754113</pqid></control><display><type>article</type><title>Mapping electrical properties heterogeneity of tumor using boundary informed electrical properties tomography (BIEPT) at 7T</title><source>Wiley-Blackwell Read & Publish Collection</source><creator>Wang, Yicun ; Shao, Qi ; Van de Moortele, Pierre‐Francois ; Racila, Emilian ; Liu, Jiaen ; Bischof, John ; He, Bin</creator><creatorcontrib>Wang, Yicun ; Shao, Qi ; Van de Moortele, Pierre‐Francois ; Racila, Emilian ; Liu, Jiaen ; Bischof, John ; He, Bin</creatorcontrib><description>Purposes
To develop and evaluate a boundary informed electrical properties tomography (BIEPT) technique for high‐resolution imaging of tumor electrical properties (EPs) heterogeneity on a rodent tumor xenograft model.
Methods
Tumor EP distributions were inferred from a reference area external to the tumor, as well as internal EP spatial variations derived from a plurality of relative transmit B1 measurements at 7T. Edge sparsity constraint was enforced to enhance numerical stability. Phantom experiments were performed to determine the imaging accuracy and sensitivity for structures of various EP values, as well as geometrical sizes down to 1.5 mm. Numerical simulation of a realistic rodent model was used to quantify the algorithm performance in the presence of noise. Eleven athymic rats with human breast cancer xenograft were imaged in vivo, and representative pathological samples were acquired for comparison.
Results
Reconstructed EPs of the phantoms correspond well to the ground truth acquired from dielectric probe measurements, with the smallest structure reliably detectable being 3 mm. EPs heterogeneity inside a tumor is successfully retrieved in both simulated and experimental cases. In vivo tumor imaging results demonstrate similar local features and spatial patterns to anatomical MRI and pathological slides. The imaged conductivity of necrotic tissue is higher than that of viable tissues, which agrees with our expectation.
Conclusion
BIEPT enables robust detection of tumor EPs heterogeneity with high accuracy and sensitivity to small structures. The retrieved quantitative EPs reflect tumor pathological features (e.g., necrosis). These results provide strong rationale to further expand BIEPT studies toward pathological conditions where EPs may yield valuable, non‐invasive biomarkers.</description><identifier>ISSN: 0740-3194</identifier><identifier>EISSN: 1522-2594</identifier><identifier>DOI: 10.1002/mrm.27414</identifier><identifier>PMID: 30230603</identifier><language>eng</language><publisher>United States: Wiley Subscription Services, Inc</publisher><subject>Algorithms ; Animals ; Biomarkers ; Biomarkers, Tumor ; Brain - diagnostic imaging ; Breast cancer ; Computer Simulation ; Electric Conductivity ; Electrical properties ; electrical properties tomography (EPT) ; Electrical resistivity ; electromagnetic simulation ; Female ; Ground truth ; Heterogeneity ; Humans ; Magnetic Resonance Imaging ; Mathematical models ; Medical imaging ; Models, Theoretical ; Monte Carlo Method ; multi‐channel B1 mapping ; Necrosis ; Neoplasm Transplantation ; Normal Distribution ; Numerical stability ; Phantoms, Imaging ; Radio Waves ; Rats ; Robustness (mathematics) ; Sensitivity ; Software ; Spatial distribution ; Spatial variations ; Tomography ; Tomography, X-Ray Computed ; tumor heterogeneity ; Tumors ; ultra‐high‐field MRI ; Xenografts ; Xenotransplantation</subject><ispartof>Magnetic resonance in medicine, 2019-01, Vol.81 (1), p.393-409</ispartof><rights>2018 International Society for Magnetic Resonance in Medicine</rights><rights>2018 International Society for Magnetic Resonance in Medicine.</rights><rights>2019 International Society for Magnetic Resonance in Medicine</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4544-b15456fd0a93afdd0a49adb39016b917114efc97163b5bd77bc05f172aea39e93</citedby><cites>FETCH-LOGICAL-c4544-b15456fd0a93afdd0a49adb39016b917114efc97163b5bd77bc05f172aea39e93</cites><orcidid>0000-0003-2944-8602</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30230603$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wang, Yicun</creatorcontrib><creatorcontrib>Shao, Qi</creatorcontrib><creatorcontrib>Van de Moortele, Pierre‐Francois</creatorcontrib><creatorcontrib>Racila, Emilian</creatorcontrib><creatorcontrib>Liu, Jiaen</creatorcontrib><creatorcontrib>Bischof, John</creatorcontrib><creatorcontrib>He, Bin</creatorcontrib><title>Mapping electrical properties heterogeneity of tumor using boundary informed electrical properties tomography (BIEPT) at 7T</title><title>Magnetic resonance in medicine</title><addtitle>Magn Reson Med</addtitle><description>Purposes
To develop and evaluate a boundary informed electrical properties tomography (BIEPT) technique for high‐resolution imaging of tumor electrical properties (EPs) heterogeneity on a rodent tumor xenograft model.
Methods
Tumor EP distributions were inferred from a reference area external to the tumor, as well as internal EP spatial variations derived from a plurality of relative transmit B1 measurements at 7T. Edge sparsity constraint was enforced to enhance numerical stability. Phantom experiments were performed to determine the imaging accuracy and sensitivity for structures of various EP values, as well as geometrical sizes down to 1.5 mm. Numerical simulation of a realistic rodent model was used to quantify the algorithm performance in the presence of noise. Eleven athymic rats with human breast cancer xenograft were imaged in vivo, and representative pathological samples were acquired for comparison.
Results
Reconstructed EPs of the phantoms correspond well to the ground truth acquired from dielectric probe measurements, with the smallest structure reliably detectable being 3 mm. EPs heterogeneity inside a tumor is successfully retrieved in both simulated and experimental cases. In vivo tumor imaging results demonstrate similar local features and spatial patterns to anatomical MRI and pathological slides. The imaged conductivity of necrotic tissue is higher than that of viable tissues, which agrees with our expectation.
Conclusion
BIEPT enables robust detection of tumor EPs heterogeneity with high accuracy and sensitivity to small structures. The retrieved quantitative EPs reflect tumor pathological features (e.g., necrosis). These results provide strong rationale to further expand BIEPT studies toward pathological conditions where EPs may yield valuable, non‐invasive biomarkers.</description><subject>Algorithms</subject><subject>Animals</subject><subject>Biomarkers</subject><subject>Biomarkers, Tumor</subject><subject>Brain - diagnostic imaging</subject><subject>Breast cancer</subject><subject>Computer Simulation</subject><subject>Electric Conductivity</subject><subject>Electrical properties</subject><subject>electrical properties tomography (EPT)</subject><subject>Electrical resistivity</subject><subject>electromagnetic simulation</subject><subject>Female</subject><subject>Ground truth</subject><subject>Heterogeneity</subject><subject>Humans</subject><subject>Magnetic Resonance Imaging</subject><subject>Mathematical models</subject><subject>Medical imaging</subject><subject>Models, Theoretical</subject><subject>Monte Carlo Method</subject><subject>multi‐channel B1 mapping</subject><subject>Necrosis</subject><subject>Neoplasm Transplantation</subject><subject>Normal Distribution</subject><subject>Numerical stability</subject><subject>Phantoms, Imaging</subject><subject>Radio Waves</subject><subject>Rats</subject><subject>Robustness (mathematics)</subject><subject>Sensitivity</subject><subject>Software</subject><subject>Spatial distribution</subject><subject>Spatial variations</subject><subject>Tomography</subject><subject>Tomography, X-Ray Computed</subject><subject>tumor heterogeneity</subject><subject>Tumors</subject><subject>ultra‐high‐field MRI</subject><subject>Xenografts</subject><subject>Xenotransplantation</subject><issn>0740-3194</issn><issn>1522-2594</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNp1kLFOwzAQhi0EoqUw8ALIEgsd0tqxHcsjVAUqUYFQmSMnubSpmjjYiVDEy-OSwtbpX7777u5H6JqSCSUknJa2nISSU36ChlSEYRAKxU_RkEhOAkYVH6AL57aEEKUkP0cDRkJGIsKG6Hup67qo1hh2kDa2SPUO19bUYJsCHN5AA9asoYKi6bDJcdOWxuLW7UcS01aZth0uqtzYErIjksaUZm11venw3cNi_rYaY91gubpEZ7neObg65Ah9PM5Xs-fg5fVpMbt_CVIuOA8SKriI8oxoxXSe-eRKZwlThEaJopJSDnmqJI1YIpJMyiQlIqcy1KCZAsVG6Lb3-ps-W3BNvDWtrfzKOKRMSsEpZZ4a91RqjXMW8ri2RenfiymJ9zXHvub4t2bP3hyMbeL__if_evXAtAe-ih10x03x8n3ZK38AHNeIjw</recordid><startdate>201901</startdate><enddate>201901</enddate><creator>Wang, Yicun</creator><creator>Shao, Qi</creator><creator>Van de Moortele, Pierre‐Francois</creator><creator>Racila, Emilian</creator><creator>Liu, Jiaen</creator><creator>Bischof, John</creator><creator>He, Bin</creator><general>Wiley Subscription Services, Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>M7Z</scope><scope>P64</scope><orcidid>https://orcid.org/0000-0003-2944-8602</orcidid></search><sort><creationdate>201901</creationdate><title>Mapping electrical properties heterogeneity of tumor using boundary informed electrical properties tomography (BIEPT) at 7T</title><author>Wang, Yicun ; Shao, Qi ; Van de Moortele, Pierre‐Francois ; Racila, Emilian ; Liu, Jiaen ; Bischof, John ; He, Bin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4544-b15456fd0a93afdd0a49adb39016b917114efc97163b5bd77bc05f172aea39e93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Algorithms</topic><topic>Animals</topic><topic>Biomarkers</topic><topic>Biomarkers, Tumor</topic><topic>Brain - diagnostic imaging</topic><topic>Breast cancer</topic><topic>Computer Simulation</topic><topic>Electric Conductivity</topic><topic>Electrical properties</topic><topic>electrical properties tomography (EPT)</topic><topic>Electrical resistivity</topic><topic>electromagnetic simulation</topic><topic>Female</topic><topic>Ground truth</topic><topic>Heterogeneity</topic><topic>Humans</topic><topic>Magnetic Resonance Imaging</topic><topic>Mathematical models</topic><topic>Medical imaging</topic><topic>Models, Theoretical</topic><topic>Monte Carlo Method</topic><topic>multi‐channel B1 mapping</topic><topic>Necrosis</topic><topic>Neoplasm Transplantation</topic><topic>Normal Distribution</topic><topic>Numerical stability</topic><topic>Phantoms, Imaging</topic><topic>Radio Waves</topic><topic>Rats</topic><topic>Robustness (mathematics)</topic><topic>Sensitivity</topic><topic>Software</topic><topic>Spatial distribution</topic><topic>Spatial variations</topic><topic>Tomography</topic><topic>Tomography, X-Ray Computed</topic><topic>tumor heterogeneity</topic><topic>Tumors</topic><topic>ultra‐high‐field MRI</topic><topic>Xenografts</topic><topic>Xenotransplantation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Yicun</creatorcontrib><creatorcontrib>Shao, Qi</creatorcontrib><creatorcontrib>Van de Moortele, Pierre‐Francois</creatorcontrib><creatorcontrib>Racila, Emilian</creatorcontrib><creatorcontrib>Liu, Jiaen</creatorcontrib><creatorcontrib>Bischof, John</creatorcontrib><creatorcontrib>He, Bin</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biochemistry Abstracts 1</collection><collection>Biotechnology and BioEngineering Abstracts</collection><jtitle>Magnetic resonance in medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Yicun</au><au>Shao, Qi</au><au>Van de Moortele, Pierre‐Francois</au><au>Racila, Emilian</au><au>Liu, Jiaen</au><au>Bischof, John</au><au>He, Bin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Mapping electrical properties heterogeneity of tumor using boundary informed electrical properties tomography (BIEPT) at 7T</atitle><jtitle>Magnetic resonance in medicine</jtitle><addtitle>Magn Reson Med</addtitle><date>2019-01</date><risdate>2019</risdate><volume>81</volume><issue>1</issue><spage>393</spage><epage>409</epage><pages>393-409</pages><issn>0740-3194</issn><eissn>1522-2594</eissn><abstract>Purposes
To develop and evaluate a boundary informed electrical properties tomography (BIEPT) technique for high‐resolution imaging of tumor electrical properties (EPs) heterogeneity on a rodent tumor xenograft model.
Methods
Tumor EP distributions were inferred from a reference area external to the tumor, as well as internal EP spatial variations derived from a plurality of relative transmit B1 measurements at 7T. Edge sparsity constraint was enforced to enhance numerical stability. Phantom experiments were performed to determine the imaging accuracy and sensitivity for structures of various EP values, as well as geometrical sizes down to 1.5 mm. Numerical simulation of a realistic rodent model was used to quantify the algorithm performance in the presence of noise. Eleven athymic rats with human breast cancer xenograft were imaged in vivo, and representative pathological samples were acquired for comparison.
Results
Reconstructed EPs of the phantoms correspond well to the ground truth acquired from dielectric probe measurements, with the smallest structure reliably detectable being 3 mm. EPs heterogeneity inside a tumor is successfully retrieved in both simulated and experimental cases. In vivo tumor imaging results demonstrate similar local features and spatial patterns to anatomical MRI and pathological slides. The imaged conductivity of necrotic tissue is higher than that of viable tissues, which agrees with our expectation.
Conclusion
BIEPT enables robust detection of tumor EPs heterogeneity with high accuracy and sensitivity to small structures. The retrieved quantitative EPs reflect tumor pathological features (e.g., necrosis). These results provide strong rationale to further expand BIEPT studies toward pathological conditions where EPs may yield valuable, non‐invasive biomarkers.</abstract><cop>United States</cop><pub>Wiley Subscription Services, Inc</pub><pmid>30230603</pmid><doi>10.1002/mrm.27414</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0003-2944-8602</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Animals Biomarkers Biomarkers, Tumor Brain - diagnostic imaging Breast cancer Computer Simulation Electric Conductivity Electrical properties electrical properties tomography (EPT) Electrical resistivity electromagnetic simulation Female Ground truth Heterogeneity Humans Magnetic Resonance Imaging Mathematical models Medical imaging Models, Theoretical Monte Carlo Method multi‐channel B1 mapping Necrosis Neoplasm Transplantation Normal Distribution Numerical stability Phantoms, Imaging Radio Waves Rats Robustness (mathematics) Sensitivity Software Spatial distribution Spatial variations Tomography Tomography, X-Ray Computed tumor heterogeneity Tumors ultra‐high‐field MRI Xenografts Xenotransplantation |
title | Mapping electrical properties heterogeneity of tumor using boundary informed electrical properties tomography (BIEPT) at 7T |
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