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The Pan-Cytokeratin Staining Intensity and Fractal Computational Analysis of Breast Tumor Malignant Growth Patterns Prognosticate the Occurrence of Distant Metastasis
Improved prognosis of breast cancer outcome could prolong patient survival by reliable identification of patients at high risk of metastasis occurrence which could benefit from more aggressive treatments. Based on such clinical need, we prognostically evaluated the malignant cells in breast tumors,...
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Published in: | Frontiers in oncology 2018-08, Vol.8, p.348-348 |
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description | Improved prognosis of breast cancer outcome could prolong patient survival by reliable identification of patients at high risk of metastasis occurrence which could benefit from more aggressive treatments. Based on such clinical need, we prognostically evaluated the malignant cells in breast tumors, as the obvious potential source of unexploited prognostic information. The patient group was homogeneous, without any systemic treatments or lymph node spread, with smaller tumor size (pT1/2) and a long follow-up. Epithelial cells were labeled with AE1/AE3 pan-cytokeratin antibody cocktail and comprehensively analyzed. Monofractal and multifractal analyses were applied for quantification of distribution, shape, complexity and texture of malignant cell clusters, while
and
were measures of the pan-cytokeratin immunostaining intensity. The results surprisingly indicate that simple binary images and monofractal analysis provided better prognostic information then grayscale images and multifractal analysis. The key findings were that shapes and distribution of malignant cell clusters (by
; AUC = 0.29), their contour shapes (by outline fractal dimension; AUC = 0.31) and intensity of the pan-cytokeratin immunostaining (by
; AUC = 0.30) offered significant performance in metastasis risk prognostication. The results reveal an association between the lower pan-cytokeratin staining intensity and the high metastasis risk. Another interesting result was that multivariate analysis could confirm the prognostic independence only for fractal but not for immunostaining intensity features. The obtained results reveal several novel and unexpected findings highlighting the independent prognostic efficacy of malignant cell cluster distribution and contour shapes in breast tumors. |
doi_str_mv | 10.3389/fonc.2018.00348 |
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and
were measures of the pan-cytokeratin immunostaining intensity. The results surprisingly indicate that simple binary images and monofractal analysis provided better prognostic information then grayscale images and multifractal analysis. The key findings were that shapes and distribution of malignant cell clusters (by
; AUC = 0.29), their contour shapes (by outline fractal dimension; AUC = 0.31) and intensity of the pan-cytokeratin immunostaining (by
; AUC = 0.30) offered significant performance in metastasis risk prognostication. The results reveal an association between the lower pan-cytokeratin staining intensity and the high metastasis risk. Another interesting result was that multivariate analysis could confirm the prognostic independence only for fractal but not for immunostaining intensity features. The obtained results reveal several novel and unexpected findings highlighting the independent prognostic efficacy of malignant cell cluster distribution and contour shapes in breast tumors.</description><identifier>ISSN: 2234-943X</identifier><identifier>EISSN: 2234-943X</identifier><identifier>DOI: 10.3389/fonc.2018.00348</identifier><identifier>PMID: 30214894</identifier><language>eng</language><publisher>Switzerland: Frontiers Media S.A</publisher><subject>breast cancer ; fractal ; image analysis ; metastasis ; Oncology ; prognosis ; tumor</subject><ispartof>Frontiers in oncology, 2018-08, Vol.8, p.348-348</ispartof><rights>Copyright © 2018 Rajković, Li, Plataniotis, Kanjer, Radulovic and Milošević. 2018 Rajković, Li, Plataniotis, Kanjer, Radulovic and Milošević</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c525t-c39040b8db5a7f175ef0a0662dab248509e9c7e407de4dcf36c7adb535c1cf383</citedby><cites>FETCH-LOGICAL-c525t-c39040b8db5a7f175ef0a0662dab248509e9c7e407de4dcf36c7adb535c1cf383</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6125390/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6125390/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30214894$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Rajković, Nemanja</creatorcontrib><creatorcontrib>Li, Xingyu</creatorcontrib><creatorcontrib>Plataniotis, Konstantinos N</creatorcontrib><creatorcontrib>Kanjer, Ksenija</creatorcontrib><creatorcontrib>Radulovic, Marko</creatorcontrib><creatorcontrib>Milošević, Nebojša T</creatorcontrib><title>The Pan-Cytokeratin Staining Intensity and Fractal Computational Analysis of Breast Tumor Malignant Growth Patterns Prognosticate the Occurrence of Distant Metastasis</title><title>Frontiers in oncology</title><addtitle>Front Oncol</addtitle><description>Improved prognosis of breast cancer outcome could prolong patient survival by reliable identification of patients at high risk of metastasis occurrence which could benefit from more aggressive treatments. Based on such clinical need, we prognostically evaluated the malignant cells in breast tumors, as the obvious potential source of unexploited prognostic information. The patient group was homogeneous, without any systemic treatments or lymph node spread, with smaller tumor size (pT1/2) and a long follow-up. Epithelial cells were labeled with AE1/AE3 pan-cytokeratin antibody cocktail and comprehensively analyzed. Monofractal and multifractal analyses were applied for quantification of distribution, shape, complexity and texture of malignant cell clusters, while
and
were measures of the pan-cytokeratin immunostaining intensity. The results surprisingly indicate that simple binary images and monofractal analysis provided better prognostic information then grayscale images and multifractal analysis. The key findings were that shapes and distribution of malignant cell clusters (by
; AUC = 0.29), their contour shapes (by outline fractal dimension; AUC = 0.31) and intensity of the pan-cytokeratin immunostaining (by
; AUC = 0.30) offered significant performance in metastasis risk prognostication. The results reveal an association between the lower pan-cytokeratin staining intensity and the high metastasis risk. Another interesting result was that multivariate analysis could confirm the prognostic independence only for fractal but not for immunostaining intensity features. The obtained results reveal several novel and unexpected findings highlighting the independent prognostic efficacy of malignant cell cluster distribution and contour shapes in breast tumors.</description><subject>breast cancer</subject><subject>fractal</subject><subject>image analysis</subject><subject>metastasis</subject><subject>Oncology</subject><subject>prognosis</subject><subject>tumor</subject><issn>2234-943X</issn><issn>2234-943X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNpVkk1vEzEQhlcIRKvSMzfkI5dN_bnxXpBKSkukVq1EkLhZE-9s4rKxg-0F5Q_xO3GaUrU-2DP2O8-Mpbeq3jM6EUK3Z33wdsIp0xNKhdSvqmPOhaxbKX68fhYfVacp3dOyGkUZFW-rI0E5k7qVx9XfxRrJHfh6tsvhJ0bIzpNvGZx3fkXmPqNPLu8I-I5cRrAZBjILm-2YizL4kp2XbZdcIqEnnyNCymQxbkIkNzC4lQefyVUMf_K6tMkZo0_kLoaVDyk7CxlJLhPcWjvGiN7iHnPhUt7X3WAuOCjwd9WbHoaEp4_nSfX98sti9rW-vr2az86va6u4yrUVLZV0qbulgmnPpgp7CrRpeAdLLrWiLbZ2ipJOO5Sd7UVjp1DEQllWMi1OqvmB2wW4N9voNhB3JoAzDxchrgzEMveApqg7anukSmvJeq17pnjf6JZiyyVjhfXpwNqOyw12Fn2OMLyAvnzxbm1W4bdpGFflIwXw8REQw68RUzYblywOA3gMYzKcUUUlo40o0rOD1MaQUsT-qQ2jZm8WszeL2ZvFPJilVHx4Pt2T_r81xD9sXL-d</recordid><startdate>20180830</startdate><enddate>20180830</enddate><creator>Rajković, Nemanja</creator><creator>Li, Xingyu</creator><creator>Plataniotis, Konstantinos N</creator><creator>Kanjer, Ksenija</creator><creator>Radulovic, Marko</creator><creator>Milošević, Nebojša T</creator><general>Frontiers Media S.A</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20180830</creationdate><title>The Pan-Cytokeratin Staining Intensity and Fractal Computational Analysis of Breast Tumor Malignant Growth Patterns Prognosticate the Occurrence of Distant Metastasis</title><author>Rajković, Nemanja ; Li, Xingyu ; Plataniotis, Konstantinos N ; Kanjer, Ksenija ; Radulovic, Marko ; Milošević, Nebojša T</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c525t-c39040b8db5a7f175ef0a0662dab248509e9c7e407de4dcf36c7adb535c1cf383</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>breast cancer</topic><topic>fractal</topic><topic>image analysis</topic><topic>metastasis</topic><topic>Oncology</topic><topic>prognosis</topic><topic>tumor</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Rajković, Nemanja</creatorcontrib><creatorcontrib>Li, Xingyu</creatorcontrib><creatorcontrib>Plataniotis, Konstantinos N</creatorcontrib><creatorcontrib>Kanjer, Ksenija</creatorcontrib><creatorcontrib>Radulovic, Marko</creatorcontrib><creatorcontrib>Milošević, Nebojša T</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Directory of Open Access Journals</collection><jtitle>Frontiers in oncology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rajković, Nemanja</au><au>Li, Xingyu</au><au>Plataniotis, Konstantinos N</au><au>Kanjer, Ksenija</au><au>Radulovic, Marko</au><au>Milošević, Nebojša T</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Pan-Cytokeratin Staining Intensity and Fractal Computational Analysis of Breast Tumor Malignant Growth Patterns Prognosticate the Occurrence of Distant Metastasis</atitle><jtitle>Frontiers in oncology</jtitle><addtitle>Front Oncol</addtitle><date>2018-08-30</date><risdate>2018</risdate><volume>8</volume><spage>348</spage><epage>348</epage><pages>348-348</pages><issn>2234-943X</issn><eissn>2234-943X</eissn><abstract>Improved prognosis of breast cancer outcome could prolong patient survival by reliable identification of patients at high risk of metastasis occurrence which could benefit from more aggressive treatments. Based on such clinical need, we prognostically evaluated the malignant cells in breast tumors, as the obvious potential source of unexploited prognostic information. The patient group was homogeneous, without any systemic treatments or lymph node spread, with smaller tumor size (pT1/2) and a long follow-up. Epithelial cells were labeled with AE1/AE3 pan-cytokeratin antibody cocktail and comprehensively analyzed. Monofractal and multifractal analyses were applied for quantification of distribution, shape, complexity and texture of malignant cell clusters, while
and
were measures of the pan-cytokeratin immunostaining intensity. The results surprisingly indicate that simple binary images and monofractal analysis provided better prognostic information then grayscale images and multifractal analysis. The key findings were that shapes and distribution of malignant cell clusters (by
; AUC = 0.29), their contour shapes (by outline fractal dimension; AUC = 0.31) and intensity of the pan-cytokeratin immunostaining (by
; AUC = 0.30) offered significant performance in metastasis risk prognostication. The results reveal an association between the lower pan-cytokeratin staining intensity and the high metastasis risk. Another interesting result was that multivariate analysis could confirm the prognostic independence only for fractal but not for immunostaining intensity features. The obtained results reveal several novel and unexpected findings highlighting the independent prognostic efficacy of malignant cell cluster distribution and contour shapes in breast tumors.</abstract><cop>Switzerland</cop><pub>Frontiers Media S.A</pub><pmid>30214894</pmid><doi>10.3389/fonc.2018.00348</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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title | The Pan-Cytokeratin Staining Intensity and Fractal Computational Analysis of Breast Tumor Malignant Growth Patterns Prognosticate the Occurrence of Distant Metastasis |
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