A simple and convenient model combining multiparametric MRI and clinical features to predict tumour-infiltrating lymphocytes in breast cancer

A simple and convenient model combining multiparametric MRI and clinical features to predict tumour-infiltrating lymphocytes in breast cancer

To develop a simple and convenient method based on multiparametric magnetic resonance imaging (MRI) and clinical features to non-invasively predict tumour-infiltrating lymphocytes (TILs) in breast cancer (BC) and to explore the relationship between TIL levels and disease-free survival (DFS). A total...

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Veröffentlicht in:Clinical radiology 2023-12, Vol.78 (12), p.e1065-e1074
Hauptverfasser: Chen, S., Sui, Y., Ding, S., Chen, C., Liu, C., Zhong, Z., Liang, Y., Kong, Q., Tang, W., Guo, Y.
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container_end_page e1074
container_issue 12
container_start_page e1065
container_title Clinical radiology
container_volume 78
creator Chen, S.
Sui, Y.
Ding, S.
Chen, C.
Liu, C.
Zhong, Z.
Liang, Y.
Kong, Q.
Tang, W.
Guo, Y.
description To develop a simple and convenient method based on multiparametric magnetic resonance imaging (MRI) and clinical features to non-invasively predict tumour-infiltrating lymphocytes (TILs) in breast cancer (BC) and to explore the relationship between TIL levels and disease-free survival (DFS). A total of 172 BC patients were enrolled between November 2017 and June 2021 in this retrospective study. The patients were divided into high (≥10%) and low (
doi_str_mv 10.1016/j.crad.2023.08.029
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A total of 172 BC patients were enrolled between November 2017 and June 2021 in this retrospective study. The patients were divided into high (≥10%) and low (&lt;10%) TIL groups. Clinicopathological data were collected. MRI features were reviewed by two radiologists. Predictors associated with TILs were determined by using multivariable logistic regression analyses. Kaplan–Meier survival curves based on TIL levels were used to estimate DFS. A total of 102 patients with low TILs and 70 patients with high TILs were included in the study. Tumour size (odds ratio [OR], 1.040; 95% confidence interval [CI]: 1.006, 1.075; p=0.020), apparent diffusion coefficient (ADC; OR, 1.003; 95% CI: 1.001, 1.005; p=0.015), clinical axillary lymph node status (CALNS; OR, 3.222; 95% CI: 1.372,7.568; p=0.007), and enhancement pattern (OR, 0.284; 95% CI: 0.143, 0.563; p&lt;0.001) were independently associated with TIL levels. These features were used in the ALSE model (where A is ADC, L is CALNS, S is size, and E is enhancement pattern). High TILs were associated with better DFS (p=0.016). The ALSE model derived from multiparametric MRI and clinical features could non-invasively predict TIL levels in BC, and high TILs were associated with longer DFS, especially in human epidermal growth factor receptor 2 (HER2)-positive BC and triple-negative BC (TNBC). •Our study aims to noninvasively assess TILs in BC.•The ALSE model could predict TIL levels, especially in HER2-positive BC and TNBC.•Significantly better DFS was found in high TILs than in low TILs.</description><identifier>ISSN: 0009-9260</identifier><identifier>EISSN: 1365-229X</identifier><identifier>DOI: 10.1016/j.crad.2023.08.029</identifier><language>eng</language><publisher>Elsevier Ltd</publisher><ispartof>Clinical radiology, 2023-12, Vol.78 (12), p.e1065-e1074</ispartof><rights>2023</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c333t-16b64d94ac16103814ca00f52770b8bcb527941e424ba199b8beeb14e7e07a603</citedby><cites>FETCH-LOGICAL-c333t-16b64d94ac16103814ca00f52770b8bcb527941e424ba199b8beeb14e7e07a603</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0009926023003902$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids></links><search><creatorcontrib>Chen, S.</creatorcontrib><creatorcontrib>Sui, Y.</creatorcontrib><creatorcontrib>Ding, S.</creatorcontrib><creatorcontrib>Chen, C.</creatorcontrib><creatorcontrib>Liu, C.</creatorcontrib><creatorcontrib>Zhong, Z.</creatorcontrib><creatorcontrib>Liang, Y.</creatorcontrib><creatorcontrib>Kong, Q.</creatorcontrib><creatorcontrib>Tang, W.</creatorcontrib><creatorcontrib>Guo, Y.</creatorcontrib><title>A simple and convenient model combining multiparametric MRI and clinical features to predict tumour-infiltrating lymphocytes in breast cancer</title><title>Clinical radiology</title><description>To develop a simple and convenient method based on multiparametric magnetic resonance imaging (MRI) and clinical features to non-invasively predict tumour-infiltrating lymphocytes (TILs) in breast cancer (BC) and to explore the relationship between TIL levels and disease-free survival (DFS). A total of 172 BC patients were enrolled between November 2017 and June 2021 in this retrospective study. The patients were divided into high (≥10%) and low (&lt;10%) TIL groups. Clinicopathological data were collected. MRI features were reviewed by two radiologists. Predictors associated with TILs were determined by using multivariable logistic regression analyses. Kaplan–Meier survival curves based on TIL levels were used to estimate DFS. A total of 102 patients with low TILs and 70 patients with high TILs were included in the study. Tumour size (odds ratio [OR], 1.040; 95% confidence interval [CI]: 1.006, 1.075; p=0.020), apparent diffusion coefficient (ADC; OR, 1.003; 95% CI: 1.001, 1.005; p=0.015), clinical axillary lymph node status (CALNS; OR, 3.222; 95% CI: 1.372,7.568; p=0.007), and enhancement pattern (OR, 0.284; 95% CI: 0.143, 0.563; p&lt;0.001) were independently associated with TIL levels. These features were used in the ALSE model (where A is ADC, L is CALNS, S is size, and E is enhancement pattern). High TILs were associated with better DFS (p=0.016). The ALSE model derived from multiparametric MRI and clinical features could non-invasively predict TIL levels in BC, and high TILs were associated with longer DFS, especially in human epidermal growth factor receptor 2 (HER2)-positive BC and triple-negative BC (TNBC). •Our study aims to noninvasively assess TILs in BC.•The ALSE model could predict TIL levels, especially in HER2-positive BC and TNBC.•Significantly better DFS was found in high TILs than in low TILs.</description><issn>0009-9260</issn><issn>1365-229X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp9kMtq3TAURUVpoLdpfyAjDTOxcyT5CZ2E0EcgpVAa6EzI8nGrix6OJAfuR-SfK3Mz7ui89t5wFiFXDGoGrLs51jqquebARQ1DDXx8Qw5MdG3F-fj7LTkAwFiNvIN35H1Kx31seHMgL7c0GbdapMrPVAf_jN6gz9SFGW1ZuMl44_9Qt9lsVhWVwxyNpt9_3p8ttty1snRBlbeIieZA14iz0ZnmzYUtVsYvxuao8h5kT279G_QpF6nxdIqoUqZaeY3xA7lYlE348bVekscvn3_dfasefny9v7t9qLQQIlesm7pmHhulWcdADKzRCmBped_DNEx6Kt3YMCwfToqNY9khTqzBHqFXHYhLcn3OXWN42jBl6UzSaK3yGLYk-dC3YuBtK4qUn6U6hpQiLnKNxql4kgzkzl4e5c5e7uwlDLKwL6ZPZxOWJ54NRpl0oaoLlYg6yzmY_9n_AYs5kFo</recordid><startdate>202312</startdate><enddate>202312</enddate><creator>Chen, S.</creator><creator>Sui, Y.</creator><creator>Ding, S.</creator><creator>Chen, C.</creator><creator>Liu, C.</creator><creator>Zhong, Z.</creator><creator>Liang, Y.</creator><creator>Kong, Q.</creator><creator>Tang, W.</creator><creator>Guo, Y.</creator><general>Elsevier Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>202312</creationdate><title>A simple and convenient model combining multiparametric MRI and clinical features to predict tumour-infiltrating lymphocytes in breast cancer</title><author>Chen, S. ; Sui, Y. ; Ding, S. ; Chen, C. ; Liu, C. ; Zhong, Z. ; Liang, Y. ; Kong, Q. ; Tang, W. ; Guo, Y.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c333t-16b64d94ac16103814ca00f52770b8bcb527941e424ba199b8beeb14e7e07a603</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, S.</creatorcontrib><creatorcontrib>Sui, Y.</creatorcontrib><creatorcontrib>Ding, S.</creatorcontrib><creatorcontrib>Chen, C.</creatorcontrib><creatorcontrib>Liu, C.</creatorcontrib><creatorcontrib>Zhong, Z.</creatorcontrib><creatorcontrib>Liang, Y.</creatorcontrib><creatorcontrib>Kong, Q.</creatorcontrib><creatorcontrib>Tang, W.</creatorcontrib><creatorcontrib>Guo, Y.</creatorcontrib><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Clinical radiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, S.</au><au>Sui, Y.</au><au>Ding, S.</au><au>Chen, C.</au><au>Liu, C.</au><au>Zhong, Z.</au><au>Liang, Y.</au><au>Kong, Q.</au><au>Tang, W.</au><au>Guo, Y.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A simple and convenient model combining multiparametric MRI and clinical features to predict tumour-infiltrating lymphocytes in breast cancer</atitle><jtitle>Clinical radiology</jtitle><date>2023-12</date><risdate>2023</risdate><volume>78</volume><issue>12</issue><spage>e1065</spage><epage>e1074</epage><pages>e1065-e1074</pages><issn>0009-9260</issn><eissn>1365-229X</eissn><abstract>To develop a simple and convenient method based on multiparametric magnetic resonance imaging (MRI) and clinical features to non-invasively predict tumour-infiltrating lymphocytes (TILs) in breast cancer (BC) and to explore the relationship between TIL levels and disease-free survival (DFS). A total of 172 BC patients were enrolled between November 2017 and June 2021 in this retrospective study. The patients were divided into high (≥10%) and low (&lt;10%) TIL groups. Clinicopathological data were collected. MRI features were reviewed by two radiologists. Predictors associated with TILs were determined by using multivariable logistic regression analyses. Kaplan–Meier survival curves based on TIL levels were used to estimate DFS. A total of 102 patients with low TILs and 70 patients with high TILs were included in the study. Tumour size (odds ratio [OR], 1.040; 95% confidence interval [CI]: 1.006, 1.075; p=0.020), apparent diffusion coefficient (ADC; OR, 1.003; 95% CI: 1.001, 1.005; p=0.015), clinical axillary lymph node status (CALNS; OR, 3.222; 95% CI: 1.372,7.568; p=0.007), and enhancement pattern (OR, 0.284; 95% CI: 0.143, 0.563; p&lt;0.001) were independently associated with TIL levels. These features were used in the ALSE model (where A is ADC, L is CALNS, S is size, and E is enhancement pattern). High TILs were associated with better DFS (p=0.016). The ALSE model derived from multiparametric MRI and clinical features could non-invasively predict TIL levels in BC, and high TILs were associated with longer DFS, especially in human epidermal growth factor receptor 2 (HER2)-positive BC and triple-negative BC (TNBC). •Our study aims to noninvasively assess TILs in BC.•The ALSE model could predict TIL levels, especially in HER2-positive BC and TNBC.•Significantly better DFS was found in high TILs than in low TILs.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.crad.2023.08.029</doi></addata></record>
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title A simple and convenient model combining multiparametric MRI and clinical features to predict tumour-infiltrating lymphocytes in breast cancer
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