Literature DB >> 27556407

Correlation Between MRI and the Level of Tumor-Infiltrating Lymphocytes in Patients With Triple-Negative Breast Cancer.

You Jin Ku1,2, Hak Hee Kim1, Joo Hee Cha1, Hee Jung Shin1, Soo Heui Baek1, Hee Jin Lee3, Gyungyub Gong3.   

Abstract

OBJECTIVE: Increased levels of tumor-infiltrating lymphocytes (TILs) positively correlate with the pathologic complete response rate and increased survival in patients with triple-negative breast cancer (TNBC). The purpose of this study was to investigate associations between TIL levels and MRI findings in patients with TNBC.
MATERIALS AND METHODS: From February 2006 through December 2014, a total of 112 women with TNBC were selected for inclusion in the study. All lesions were evaluated by radiologists in accordance with the BI-RADS lexicon. Lymph node involvement and multifocality were also assessed. Tumors were divided into two groups: those with a TIL level of less than 50% were included in the group with low TIL levels (hereafter referred to as the "low-TIL group"), and those with a TIL level of 50% or more were included in the group with high TIL levels (hereafter referred to as the "high-TIL group"). Associations between TIL levels and imaging features were evaluated.
RESULTS: Tumors in the high-TIL group had a more round shape (46.0%), a circumscribed margin (76.0%), homogeneous enhancement (32.0%), and absence of multifocality (88.0%) (p < 0.005). Tumors in the low-TIL group had a more irregular shape (69.3%), no circumscribed margin (79.0%), heterogeneous enhancement (75.8%), and multifocality (70.9%) (p < 0.005).
CONCLUSION: The well-known typical features of TNBC on MRI, including a round shape, a circumscribed margin, homogeneous enhancement, and lack of multifocality, are a major pattern of TNBC with high TIL levels. This information could provide added diagnostic benefit for the identification of tumors with a good prognosis, which could further assist in optimal pretreatment planning.

Entities:  

Keywords:  MRI; optimal planning; prognosis; triple-negative breast cancer; tumor-infiltrating lymphocytes

Mesh:

Substances:

Year:  2016        PMID: 27556407     DOI: 10.2214/AJR.16.16248

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  15 in total

1.  Usefulness of imaging findings in predicting tumor-infiltrating lymphocytes in patients with breast cancer.

Authors:  Filiz Çelebi; Filiz Agacayak; Alper Ozturk; Serkan Ilgun; Muhammed Ucuncu; Zeynep Erdogan Iyigun; Çetin Ordu; Kezban Nur Pilanci; Gul Alco; Serap Gultekin; Emetullah Cindil; Gursel Soybir; Fatma Aktepe; Vahit Özmen
Journal:  Eur Radiol       Date:  2019-12-10       Impact factor: 5.315

2.  Pretreatment prediction of immunoscore in hepatocellular cancer: a radiomics-based clinical model based on Gd-EOB-DTPA-enhanced MRI imaging.

Authors:  Shuling Chen; Shiting Feng; Jingwei Wei; Fei Liu; Bin Li; Xin Li; Yang Hou; Dongsheng Gu; Mimi Tang; Han Xiao; Yingmei Jia; Sui Peng; Jie Tian; Ming Kuang
Journal:  Eur Radiol       Date:  2019-01-21       Impact factor: 5.315

3.  Comparison of MRI and US in Tumor Size Evaluation of Breast Cancer Patients Receiving Neoadjuvant Chemotherapy.

Authors:  Onur Taydaş; Gamze Durhan; Meltem Gülsün Akpınar; Figen Başaran Demirkazık
Journal:  Eur J Breast Health       Date:  2019-04-01

4.  Changes in Diffuse Optical Tomography Images During Early Stages of Neoadjuvant Chemotherapy Correlate with Tumor Response in Different Breast Cancer Subtypes.

Authors:  Mirella L Altoe; Kevin Kalinsky; Alessandro Marone; Hyun K Kim; Hua Guo; Hanina Hibshoosh; Mariella Tejada; Katherine D Crew; Melissa K Accordino; Meghna S Trivedi; Dawn L Hershman; Andreas H Hielscher
Journal:  Clin Cancer Res       Date:  2021-01-15       Impact factor: 12.531

Review 5.  Integrated imaging and molecular analysis to decipher tumor microenvironment in the era of immunotherapy.

Authors:  Jia Wu; Aaron T Mayer; Ruijiang Li
Journal:  Semin Cancer Biol       Date:  2020-12-05       Impact factor: 17.012

6.  Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI.

Authors:  Nathaniel M Braman; Maryam Etesami; Prateek Prasanna; Christina Dubchuk; Hannah Gilmore; Pallavi Tiwari; Donna Plecha; Anant Madabhushi
Journal:  Breast Cancer Res       Date:  2017-05-18       Impact factor: 6.466

7.  Rim sign and histogram analysis of apparent diffusion coefficient values on diffusion-weighted MRI in triple-negative breast cancer: Comparison with ER-positive subtype.

Authors:  Yangsean Choi; Sung Hun Kim; In Kyung Youn; Bong Joo Kang; Woo-Chan Park; Ahwon Lee
Journal:  PLoS One       Date:  2017-05-18       Impact factor: 3.240

8.  Association of Peritumoral Radiomics With Tumor Biology and Pathologic Response to Preoperative Targeted Therapy for HER2 (ERBB2)-Positive Breast Cancer.

Authors:  Nathaniel Braman; Prateek Prasanna; Jon Whitney; Salendra Singh; Niha Beig; Maryam Etesami; David D B Bates; Katherine Gallagher; B Nicolas Bloch; Manasa Vulchi; Paulette Turk; Kaustav Bera; Jame Abraham; William M Sikov; George Somlo; Lyndsay N Harris; Hannah Gilmore; Donna Plecha; Vinay Varadan; Anant Madabhushi
Journal:  JAMA Netw Open       Date:  2019-04-05

9.  Correlation Between Mammographic Radiomics Features and the Level of Tumor-Infiltrating Lymphocytes in Patients With Triple-Negative Breast Cancer.

Authors:  Hongwei Yu; Xianqi Meng; Huang Chen; Xiaowei Han; Jingfan Fan; Wenwen Gao; Lei Du; Yue Chen; Yige Wang; Xiuxiu Liu; Lu Zhang; Guolin Ma; Jian Yang
Journal:  Front Oncol       Date:  2020-04-15       Impact factor: 6.244

10.  Computer-aided evaluation of the correlation between MRI morphology and immunohistochemical biomarkers or molecular subtypes in breast cancer.

Authors:  Sen Jiang; You-Jia Hong; Fan Zhang; Yang-Kang Li
Journal:  Sci Rep       Date:  2017-10-23       Impact factor: 4.379

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