New Cluster Analysis Method for Quantitative Dynamic Contrast‐Enhanced MRI Assessing Tumor Heterogeneity Induced by a Tumor‐Microenvironmental Ameliorator (E7130) Treatment to a Breast Cancer Mouse Model
Background Dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) can provide insight into tumor perfusion. However, a method that can quantitatively measure the intra‐tumor distribution of tumor voxel clusters with a distinct range of Ktrans and ve values remains insufficiently explored. Hy...
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creator | Makihara, Kazuyuki Yamaguchi, Masayuki Ito, Ken Sakaguchi, Kazuya Hori, Yusaku Semba, Taro Funahashi, Yasuhiro Fujii, Hirofumi Terada, Yasuhiko |
description | Background
Dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) can provide insight into tumor perfusion. However, a method that can quantitatively measure the intra‐tumor distribution of tumor voxel clusters with a distinct range of Ktrans and ve values remains insufficiently explored.
Hypothesis
Two‐dimensional cluster analysis may quantify the distribution of a tumor voxel subregion with a distinct range of Ktrans and ve values in human breast cancer xenografts.
Study Type
Prospective longitudinal study.
Animal Model
Twenty‐two female athymic nude mice with MCF‐7 xenograft, treated with E7130, a tumor‐microenvironmental ameliorator, or saline.
Field Strength/Sequence
9.4 Tesla, turbo rapid acquisition with relaxation enhancement, and spoiled gradient‐echo sequences.
Assessment
We performed two‐dimensional k‐means clustering to identify tumor voxel clusters with a distinct range of Ktrans and ve values on Days 0, 2, and 5 after treatment, calculated the ratio of the number of tumor voxels in each cluster to the total number of tumor voxels, and measured the normalized distances defined as the ratio of the distance between each tumor voxel and the nearest tumor margin to a tumor radius.
Statistical Tests
Unpaired t‐tests, Dunnett's multiple comparison tests, and Chi‐squared test were used.
Results
The largest and second largest clusters constituted 44.4% and 27.5% of all tumor voxels with cluster centroid values of Ktrans at 0.040 min−1 and 0.116 min−1, and ve at 0.131 and 0.201, respectively. At baseline (Day 0), the average normalized distances for the largest and second largest clusters were 0.33 and 0.24, respectively. E7130‐treated group showed the normalized distance of the initial largest cluster decreasing to 0.25, while that of the second largest cluster increasing to 0.31. Saline‐treated group showed no change.
Data Conclusion
A two‐dimensional cluster analysis might quantify the spatial distribution of a tumor subregion with a distinct range of Ktrans and ve values.
Level of Evidence
1
Technical Efficacy
Stage 1 |
doi_str_mv | 10.1002/jmri.28226 |
format | Article |
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Dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) can provide insight into tumor perfusion. However, a method that can quantitatively measure the intra‐tumor distribution of tumor voxel clusters with a distinct range of Ktrans and ve values remains insufficiently explored.
Hypothesis
Two‐dimensional cluster analysis may quantify the distribution of a tumor voxel subregion with a distinct range of Ktrans and ve values in human breast cancer xenografts.
Study Type
Prospective longitudinal study.
Animal Model
Twenty‐two female athymic nude mice with MCF‐7 xenograft, treated with E7130, a tumor‐microenvironmental ameliorator, or saline.
Field Strength/Sequence
9.4 Tesla, turbo rapid acquisition with relaxation enhancement, and spoiled gradient‐echo sequences.
Assessment
We performed two‐dimensional k‐means clustering to identify tumor voxel clusters with a distinct range of Ktrans and ve values on Days 0, 2, and 5 after treatment, calculated the ratio of the number of tumor voxels in each cluster to the total number of tumor voxels, and measured the normalized distances defined as the ratio of the distance between each tumor voxel and the nearest tumor margin to a tumor radius.
Statistical Tests
Unpaired t‐tests, Dunnett's multiple comparison tests, and Chi‐squared test were used.
Results
The largest and second largest clusters constituted 44.4% and 27.5% of all tumor voxels with cluster centroid values of Ktrans at 0.040 min−1 and 0.116 min−1, and ve at 0.131 and 0.201, respectively. At baseline (Day 0), the average normalized distances for the largest and second largest clusters were 0.33 and 0.24, respectively. E7130‐treated group showed the normalized distance of the initial largest cluster decreasing to 0.25, while that of the second largest cluster increasing to 0.31. Saline‐treated group showed no change.
Data Conclusion
A two‐dimensional cluster analysis might quantify the spatial distribution of a tumor subregion with a distinct range of Ktrans and ve values.
Level of Evidence
1
Technical Efficacy
Stage 1</description><identifier>ISSN: 1053-1807</identifier><identifier>EISSN: 1522-2586</identifier><identifier>DOI: 10.1002/jmri.28226</identifier><identifier>PMID: 35524730</identifier><language>eng</language><publisher>Hoboken, USA: John Wiley & Sons, Inc</publisher><subject>Animal models ; Animals ; anti‐angiogenic drug ; Breast cancer ; breast cancer mouse model ; Breast Neoplasms - diagnostic imaging ; Breast Neoplasms - pathology ; Centroids ; Cluster Analysis ; Clustering ; Contrast Media ; DCE‐MRI ; Dimensional analysis ; Female ; Field strength ; Heterogeneity ; Humans ; Longitudinal Studies ; Magnetic resonance imaging ; Magnetic Resonance Imaging - methods ; Mice ; Mice, Nude ; Prospective Studies ; Spatial distribution ; Statistical analysis ; Statistical tests ; tumor heterogeneity ; Tumors ; Xenografts ; Xenotransplantation</subject><ispartof>Journal of magnetic resonance imaging, 2022-12, Vol.56 (6), p.1820-1831</ispartof><rights>2022 International Society for Magnetic Resonance in Medicine.</rights><rights>2022 International Society for Magnetic Resonance in Medicine</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4236-cb5f0a2dbcde0feaea8a2ca752b39c5937e03b1491712bc627ffddb7750f1bdd3</citedby><cites>FETCH-LOGICAL-c4236-cb5f0a2dbcde0feaea8a2ca752b39c5937e03b1491712bc627ffddb7750f1bdd3</cites><orcidid>0000-0002-8583-3057</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fjmri.28226$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fjmri.28226$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35524730$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Makihara, Kazuyuki</creatorcontrib><creatorcontrib>Yamaguchi, Masayuki</creatorcontrib><creatorcontrib>Ito, Ken</creatorcontrib><creatorcontrib>Sakaguchi, Kazuya</creatorcontrib><creatorcontrib>Hori, Yusaku</creatorcontrib><creatorcontrib>Semba, Taro</creatorcontrib><creatorcontrib>Funahashi, Yasuhiro</creatorcontrib><creatorcontrib>Fujii, Hirofumi</creatorcontrib><creatorcontrib>Terada, Yasuhiko</creatorcontrib><title>New Cluster Analysis Method for Quantitative Dynamic Contrast‐Enhanced MRI Assessing Tumor Heterogeneity Induced by a Tumor‐Microenvironmental Ameliorator (E7130) Treatment to a Breast Cancer Mouse Model</title><title>Journal of magnetic resonance imaging</title><addtitle>J Magn Reson Imaging</addtitle><description>Background
Dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) can provide insight into tumor perfusion. However, a method that can quantitatively measure the intra‐tumor distribution of tumor voxel clusters with a distinct range of Ktrans and ve values remains insufficiently explored.
Hypothesis
Two‐dimensional cluster analysis may quantify the distribution of a tumor voxel subregion with a distinct range of Ktrans and ve values in human breast cancer xenografts.
Study Type
Prospective longitudinal study.
Animal Model
Twenty‐two female athymic nude mice with MCF‐7 xenograft, treated with E7130, a tumor‐microenvironmental ameliorator, or saline.
Field Strength/Sequence
9.4 Tesla, turbo rapid acquisition with relaxation enhancement, and spoiled gradient‐echo sequences.
Assessment
We performed two‐dimensional k‐means clustering to identify tumor voxel clusters with a distinct range of Ktrans and ve values on Days 0, 2, and 5 after treatment, calculated the ratio of the number of tumor voxels in each cluster to the total number of tumor voxels, and measured the normalized distances defined as the ratio of the distance between each tumor voxel and the nearest tumor margin to a tumor radius.
Statistical Tests
Unpaired t‐tests, Dunnett's multiple comparison tests, and Chi‐squared test were used.
Results
The largest and second largest clusters constituted 44.4% and 27.5% of all tumor voxels with cluster centroid values of Ktrans at 0.040 min−1 and 0.116 min−1, and ve at 0.131 and 0.201, respectively. At baseline (Day 0), the average normalized distances for the largest and second largest clusters were 0.33 and 0.24, respectively. E7130‐treated group showed the normalized distance of the initial largest cluster decreasing to 0.25, while that of the second largest cluster increasing to 0.31. Saline‐treated group showed no change.
Data Conclusion
A two‐dimensional cluster analysis might quantify the spatial distribution of a tumor subregion with a distinct range of Ktrans and ve values.
Level of Evidence
1
Technical Efficacy
Stage 1</description><subject>Animal models</subject><subject>Animals</subject><subject>anti‐angiogenic drug</subject><subject>Breast cancer</subject><subject>breast cancer mouse model</subject><subject>Breast Neoplasms - diagnostic imaging</subject><subject>Breast Neoplasms - pathology</subject><subject>Centroids</subject><subject>Cluster Analysis</subject><subject>Clustering</subject><subject>Contrast Media</subject><subject>DCE‐MRI</subject><subject>Dimensional analysis</subject><subject>Female</subject><subject>Field strength</subject><subject>Heterogeneity</subject><subject>Humans</subject><subject>Longitudinal Studies</subject><subject>Magnetic resonance imaging</subject><subject>Magnetic Resonance Imaging - methods</subject><subject>Mice</subject><subject>Mice, Nude</subject><subject>Prospective Studies</subject><subject>Spatial distribution</subject><subject>Statistical analysis</subject><subject>Statistical tests</subject><subject>tumor heterogeneity</subject><subject>Tumors</subject><subject>Xenografts</subject><subject>Xenotransplantation</subject><issn>1053-1807</issn><issn>1522-2586</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kctu1DAUhiMEoqWw4QGQJTYFKcWXOJ4shzDQQR0QaFhHjn3SepTYxXZaZccj8Ga8A0-CQwoLFmx8kb_zHev8WfaU4DOCMX11GLw5oytKy3vZMeGU5pSvyvvpjDnLyQqLo-xRCAeMcVUV_GF2xDinhWD4OPvxAW5R3Y8hgkdrK_spmIB2EK-cRp3z6NMobTRRRnMD6M1k5WAUqp2NXob489v3jb2SVoFGu89btA4BQjD2Eu3HIRWfQ9K6S7Bg4oS2Vo8z2U5ILkCq3xnlHdgb450dwEbZo_UAvXFexmQ43QjC8Au09yDj_I6iS9Wv0zVEVM-tPdq5MUBaNfSPswed7AM8udtPsi9vN_v6PL_4-G5bry9yVVBW5qrlHZZUt0oD7kCCXEmqpOC0ZZXiFROAWUuKighCW1VS0XVat0Jw3JFWa3aSnS7ea---jhBiM5igoO-lhfSbhpYlwSvOKpLQ5_-gBzf6NOpECVYUZYVJmaiXC5XGEYKHrrn2ZpB-aghu5pibOebmd8wJfnanHNsB9F_0T64JIAtwa3qY_qNq3qfcFukv0Pi4PA</recordid><startdate>202212</startdate><enddate>202212</enddate><creator>Makihara, Kazuyuki</creator><creator>Yamaguchi, Masayuki</creator><creator>Ito, Ken</creator><creator>Sakaguchi, Kazuya</creator><creator>Hori, Yusaku</creator><creator>Semba, Taro</creator><creator>Funahashi, Yasuhiro</creator><creator>Fujii, Hirofumi</creator><creator>Terada, Yasuhiko</creator><general>John Wiley & Sons, Inc</general><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>7QO</scope><scope>7TK</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>P64</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-8583-3057</orcidid></search><sort><creationdate>202212</creationdate><title>New Cluster Analysis Method for Quantitative Dynamic Contrast‐Enhanced MRI Assessing Tumor Heterogeneity Induced by a Tumor‐Microenvironmental Ameliorator (E7130) Treatment to a Breast Cancer Mouse Model</title><author>Makihara, Kazuyuki ; Yamaguchi, Masayuki ; Ito, Ken ; Sakaguchi, Kazuya ; Hori, Yusaku ; Semba, Taro ; Funahashi, Yasuhiro ; Fujii, Hirofumi ; Terada, Yasuhiko</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4236-cb5f0a2dbcde0feaea8a2ca752b39c5937e03b1491712bc627ffddb7750f1bdd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Animal models</topic><topic>Animals</topic><topic>anti‐angiogenic drug</topic><topic>Breast cancer</topic><topic>breast cancer mouse model</topic><topic>Breast Neoplasms - diagnostic imaging</topic><topic>Breast Neoplasms - pathology</topic><topic>Centroids</topic><topic>Cluster Analysis</topic><topic>Clustering</topic><topic>Contrast Media</topic><topic>DCE‐MRI</topic><topic>Dimensional analysis</topic><topic>Female</topic><topic>Field strength</topic><topic>Heterogeneity</topic><topic>Humans</topic><topic>Longitudinal Studies</topic><topic>Magnetic resonance imaging</topic><topic>Magnetic Resonance Imaging - methods</topic><topic>Mice</topic><topic>Mice, Nude</topic><topic>Prospective Studies</topic><topic>Spatial distribution</topic><topic>Statistical analysis</topic><topic>Statistical tests</topic><topic>tumor heterogeneity</topic><topic>Tumors</topic><topic>Xenografts</topic><topic>Xenotransplantation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Makihara, Kazuyuki</creatorcontrib><creatorcontrib>Yamaguchi, Masayuki</creatorcontrib><creatorcontrib>Ito, Ken</creatorcontrib><creatorcontrib>Sakaguchi, Kazuya</creatorcontrib><creatorcontrib>Hori, Yusaku</creatorcontrib><creatorcontrib>Semba, Taro</creatorcontrib><creatorcontrib>Funahashi, Yasuhiro</creatorcontrib><creatorcontrib>Fujii, Hirofumi</creatorcontrib><creatorcontrib>Terada, Yasuhiko</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of magnetic resonance imaging</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Makihara, Kazuyuki</au><au>Yamaguchi, Masayuki</au><au>Ito, Ken</au><au>Sakaguchi, Kazuya</au><au>Hori, Yusaku</au><au>Semba, Taro</au><au>Funahashi, Yasuhiro</au><au>Fujii, Hirofumi</au><au>Terada, Yasuhiko</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>New Cluster Analysis Method for Quantitative Dynamic Contrast‐Enhanced MRI Assessing Tumor Heterogeneity Induced by a Tumor‐Microenvironmental Ameliorator (E7130) Treatment to a Breast Cancer Mouse Model</atitle><jtitle>Journal of magnetic resonance imaging</jtitle><addtitle>J Magn Reson Imaging</addtitle><date>2022-12</date><risdate>2022</risdate><volume>56</volume><issue>6</issue><spage>1820</spage><epage>1831</epage><pages>1820-1831</pages><issn>1053-1807</issn><eissn>1522-2586</eissn><abstract>Background
Dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) can provide insight into tumor perfusion. However, a method that can quantitatively measure the intra‐tumor distribution of tumor voxel clusters with a distinct range of Ktrans and ve values remains insufficiently explored.
Hypothesis
Two‐dimensional cluster analysis may quantify the distribution of a tumor voxel subregion with a distinct range of Ktrans and ve values in human breast cancer xenografts.
Study Type
Prospective longitudinal study.
Animal Model
Twenty‐two female athymic nude mice with MCF‐7 xenograft, treated with E7130, a tumor‐microenvironmental ameliorator, or saline.
Field Strength/Sequence
9.4 Tesla, turbo rapid acquisition with relaxation enhancement, and spoiled gradient‐echo sequences.
Assessment
We performed two‐dimensional k‐means clustering to identify tumor voxel clusters with a distinct range of Ktrans and ve values on Days 0, 2, and 5 after treatment, calculated the ratio of the number of tumor voxels in each cluster to the total number of tumor voxels, and measured the normalized distances defined as the ratio of the distance between each tumor voxel and the nearest tumor margin to a tumor radius.
Statistical Tests
Unpaired t‐tests, Dunnett's multiple comparison tests, and Chi‐squared test were used.
Results
The largest and second largest clusters constituted 44.4% and 27.5% of all tumor voxels with cluster centroid values of Ktrans at 0.040 min−1 and 0.116 min−1, and ve at 0.131 and 0.201, respectively. At baseline (Day 0), the average normalized distances for the largest and second largest clusters were 0.33 and 0.24, respectively. E7130‐treated group showed the normalized distance of the initial largest cluster decreasing to 0.25, while that of the second largest cluster increasing to 0.31. Saline‐treated group showed no change.
Data Conclusion
A two‐dimensional cluster analysis might quantify the spatial distribution of a tumor subregion with a distinct range of Ktrans and ve values.
Level of Evidence
1
Technical Efficacy
Stage 1</abstract><cop>Hoboken, USA</cop><pub>John Wiley & Sons, Inc</pub><pmid>35524730</pmid><doi>10.1002/jmri.28226</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-8583-3057</orcidid></addata></record> |
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source | MEDLINE; Wiley Online Library Journals Frontfile Complete |
subjects | Animal models Animals anti‐angiogenic drug Breast cancer breast cancer mouse model Breast Neoplasms - diagnostic imaging Breast Neoplasms - pathology Centroids Cluster Analysis Clustering Contrast Media DCE‐MRI Dimensional analysis Female Field strength Heterogeneity Humans Longitudinal Studies Magnetic resonance imaging Magnetic Resonance Imaging - methods Mice Mice, Nude Prospective Studies Spatial distribution Statistical analysis Statistical tests tumor heterogeneity Tumors Xenografts Xenotransplantation |
title | New Cluster Analysis Method for Quantitative Dynamic Contrast‐Enhanced MRI Assessing Tumor Heterogeneity Induced by a Tumor‐Microenvironmental Ameliorator (E7130) Treatment to a Breast Cancer Mouse Model |
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