Literature DB >> 27566960

The Accuracy of Breast MR Imaging for Measuring the Size of a Breast Cancer: Analysis of the Histopathologic Factors.

Woo Jung Choi1, Joo Hee Cha2, Hak Hee Kim1, Hee Jung Shin1, Eun Young Chae1.   

Abstract

BACKGROUND: The objective of the study was to compare the accuracy of different magnetic resonance (MR) sequences for measuring tumor size and to evaluate whether the imaging and histopathologic features affect the accuracy of the tumor size estimation on the MR sequence. PATIENTS AND METHODS: Eight hundred women were included. The maximum diameter of the tumor was measured on T2-weighted (T2W) sequences, early-subtracted dynamic contrast-enhanced (DCE) T1-weighted (T1W) sequences, and maximal intensity projection (MIP) reconstructions. Agreement between the MR imaging and pathology-determined size were analyzed. Using the best MR sequence to measure the tumor size, the relationship between the accuracy and the imaging and histopathologic features were evaluated.
RESULTS: Tumor measurement showed a good agreement with the pathology-determined size, and with the best results using MIP (k = 0.805) compared with the early-subtracted DCE T1W sequence (k = 0.802) and the T2W sequence (k = 0.779). On MIP, the tumors of patients with minimal or mild background parenchymal enhancement, a mass, invasive ductal carcinoma (IDC), pathology-determined size < 2 cm, positive estrogen receptor, negative HER2, luminal A type, nuclear and histologic grade 1, negative nodal status, negative lymphovascular invasion, and negative extensive intraductal component were significantly more accurately estimated. The independent factors associated with the accuracy of tumor measurement were a mass, IDC, and the pathology-determined size < 2 cm.
CONCLUSION: Our study showed that tumor size is most accurately measured on MIP, especially for IDC appearing as a mass on MR imaging and with the pathology-determined size < 2 cm.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Breast cancer; Histopathological findings; MR sequence; Magnetic resonance imaging; Tumor size

Mesh:

Substances:

Year:  2016        PMID: 27566960     DOI: 10.1016/j.clbc.2016.07.007

Source DB:  PubMed          Journal:  Clin Breast Cancer        ISSN: 1526-8209            Impact factor:   3.225


  7 in total

1.  Radiological Underestimation of Tumor Size Influences the Success Rate of Re-Excision after Breast-conserving Surgery.

Authors:  Duncan Simpson; Jennifer Allan; Brendan McFall
Journal:  Eur J Breast Health       Date:  2021-10-04

2.  Tumor size estimation of the breast cancer molecular subtypes using imaging techniques.

Authors:  Gulten Sezgın; Melda Apaydın; Demet Etıt; Murat Kemal Atahan
Journal:  Med Pharm Rep       Date:  2020-07-22

3.  Contrast enhanced digital mammography versus magnetic resonance imaging for accurate measurement of the size of breast cancer.

Authors:  Inyoung Youn; SeonHyeong Choi; Yoon Jung Choi; Ju Hee Moon; Hee Jin Park; Soo-Youn Ham; Chan Heun Park; Eun Young Kim; Shin Ho Kook
Journal:  Br J Radiol       Date:  2019-04-24       Impact factor: 3.039

4.  Combination of DCE-MRI and DWI in Predicting the Treatment Effect of Concurrent Chemoradiotherapy in Esophageal Carcinoma.

Authors:  Changmin Liu; Roger Sun; Jing Wang; Fangling Ning; Zhenbo Wang; Judong Luo; Shaoshui Chen; Shuanghu Yuan
Journal:  Biomed Res Int       Date:  2020-06-16       Impact factor: 3.411

Review 5.  Imaging in Locoregional Management of Breast Cancer.

Authors:  Christiane K Kuhl; Constance Lehman; Isabelle Bedrosian
Journal:  J Clin Oncol       Date:  2020-05-22       Impact factor: 44.544

6.  Predicting the molecular subtypes of breast cancer using nomograms based on three-dimensional ultrasonography characteristics.

Authors:  Xiaojing Xu; Liren Lu; Luoxi Zhu; Yanjuan Tan; Lifang Yu; Lingyun Bao
Journal:  Front Oncol       Date:  2022-08-19       Impact factor: 5.738

7.  Agreement between dynamic contrast-enhanced magnetic resonance imaging and pathologic tumour size of breast cancer and analysis of the correlation with BI-RADS descriptors.

Authors:  Aysegul Akdogan Gemici; Ercan Inci
Journal:  Pol J Radiol       Date:  2019-12-27
  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.