Literature DB >> 30293819

The role of diffusion weighted imaging as supplement to dynamic contrast enhanced breast MRI: Can it help predict malignancy, histologic grade and recurrence?

Shima Roknsharifi1, Michael D C Fishman1, Monica D Agarwal1, Alexander Brook1, Vritti Kharbanda1, Vandana Dialani1.   

Abstract

RATIONALE AND
OBJECTIVES: To evaluate the value of adding Diffusion Weighted Imaging (DWI) with Apparent Diffusion Coefficient (ADC) mapping to dynamic contrast enhanced (DCE-MRI) to distinguish benign from malignant pathology subtypes and tumor recurrence. METHOD AND MATERIALS: In this retrospective IRB approved study, 956 consecutive patients underwent bilateral breast MRI between 1/2015 and 12/2015, with 156 BIRADS 4, 5, or 6 lesions detected in 111 patients. DWI imaging at B0, B100, B600, B1000 was performed with DCE-MRI. Values for diffusion and ADC images were recorded by two fellowship-trained breast radiologists. Mean ADC and signal intensity (SI) values were correlated with histology, tumor grade, hormone receptors (ER, PR, and HER-2)and Oncotype DX scores, when available. p ≤ 0.05 was considered significant.
RESULTS: Of 156 lesions, there were 59 (38%) benign lesions, 24 (15%) Ductal Carcinoma In-Situ, 47 (30%) Invasive Ductal Carcinoma (IDC), 15 (10%) Invasive Lobular Carcinoma (ILC) and 2 (2%) Mucinous carcinoma (MC), five (5%) mixed IDC and ILC, and four (4%) other, including tubular and rare types of malignancy. Mean ADC values for malignancy were significantly lower than for benign lesions (1085 ± 343 × 10-6 vs 1481 ± 276 × 10-6 mm2/s), which is highly predictive (area under curve = 0.82). In addition, tumors with PR negativity and Oncotype score ≥18 (intermediate to high risk for recurrence) demonstrated significantly lower ADC values. SI at B100 and B600 was helpful in distinguishing benign versus IDC. There was no significant correlation between ADC values and tumor grade or ER/HER2 status.
CONCLUSION: ADC value is important factor in distinguishing malignancy, differentiating tumors with higher Oncotype score, and PR negativity. Therefore, it can be used as an important tool to assist appropriate treatment selection.
Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Apparent Diffusion Coefficient; Breast Cancer; Diffusion weighted MRI; Oncotype Score; Pathology; Recurrence

Mesh:

Substances:

Year:  2018        PMID: 30293819     DOI: 10.1016/j.acra.2018.09.003

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  9 in total

1.  Diffusion-Weighted Imaging of Different Breast Cancer Molecular Subtypes: A Systematic Review and Meta-Analysis.

Authors:  Hans-Jonas Meyer; Andreas Wienke; Alexey Surov
Journal:  Breast Care (Basel)       Date:  2021-02-23       Impact factor: 2.860

2.  Can apparent diffusion coefficient (ADC) distinguish breast cancer from benign breast findings? A meta-analysis based on 13 847 lesions.

Authors:  Alexey Surov; Hans Jonas Meyer; Andreas Wienke
Journal:  BMC Cancer       Date:  2019-10-15       Impact factor: 4.430

3.  Apparent diffusion coefficient cannot predict molecular subtype and lymph node metastases in invasive breast cancer: a multicenter analysis.

Authors:  Alexey Surov; Yun-Woo Chang; Lihua Li; Laura Martincich; Savannah C Partridge; Jin You Kim; Andreas Wienke
Journal:  BMC Cancer       Date:  2019-11-05       Impact factor: 4.430

4.  Quantitative Parameters of Diffusion Spectrum Imaging: HER2 Status Prediction in Patients With Breast Cancer.

Authors:  Chunping Mao; Wei Jiang; Jiayi Huang; Mengzhu Wang; Xu Yan; Zehong Yang; Dongye Wang; Xiang Zhang; Jun Shen
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5.  Assessment of Suspected Breast Lesions in Early-Stage Triple-Negative Breast Cancer during Follow-Up after Breast-Conserving Surgery Using Multiparametric MRI.

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6.  XGboost Prediction Model Based on 3.0T Diffusion Kurtosis Imaging Improves the Diagnostic Accuracy of MRI BiRADS 4 Masses.

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Journal:  Front Oncol       Date:  2022-03-17       Impact factor: 6.244

7.  Prediction of Prognostic Factors and Genotypes in Patients With Breast Cancer Using Multiple Mathematical Models of MR Diffusion Imaging.

Authors:  Weiwei Wang; Xindong Zhang; Laimin Zhu; Yueqin Chen; Weiqiang Dou; Fan Zhao; Zhe Zhou; Zhanguo Sun
Journal:  Front Oncol       Date:  2022-01-31       Impact factor: 6.244

8.  Efficacy of high-resolution, 3-D diffusion-weighted imaging in the detection of breast cancer compared to dynamic contrast-enhanced magnetic resonance imaging.

Authors:  Pratiksha Yadav; Saumya Harit; Dileep Kumar
Journal:  Pol J Radiol       Date:  2021-05-10

9.  Apparent diffusion coefficient values in borderline breast lesions upgraded and not upgraded at definitive histopathological examination after surgical excision.

Authors:  Corrado Tagliati; Paola Piccinni; Paola Ercolani; Elisabetta Marconi; Barbara Franca Simonetti; Gian Marco Giuseppetti; Andrea Giovagnoni
Journal:  Pol J Radiol       Date:  2021-04-30
  9 in total

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