Literature DB >> 26382845

Background parenchymal enhancement in breast MRI before and after neoadjuvant chemotherapy: correlation with tumour response.

H Preibsch1, L Wanner2, S D Bahrs2, B M Wietek2, K C Siegmann-Luz3, E Oberlecher4, M Hahn4, A Staebler5, K Nikolaou2, B Wiesinger2.   

Abstract

OBJECTIVES: To correlate the decrease in background parenchymal enhancement (BPE) and tumour response measured with MRI in breast cancer patients treated with neoadjuvant chemotherapy (NAC).
METHODS: One hundred and forty-six MRI examinations of 73 patients with 80 biopsy-proven breast cancers who underwent breast MRI before and after NAC were retrospectively analysed. All images were reviewed by two blinded readers, who classified BPE into categories (BEC; 1 = minimal, 2 = mild, 3 = moderate, 4 = marked) before and after NAC. Histopathological and morphological tumour responses were analysed and compared.
RESULTS: The distribution of BEC 1/2/3/4 was 25/46/18/11 % before and 78/20/2/0 % after NAC. On average, BPE decreased by 0.87 BEC. Cohen's kappa showed substantial agreement (k = 0.73-0.77) before and moderate agreement (k = 0.43-0.60) after NAC and moderate agreement (k = 0.62-0.60) concerning the change in BEC. Correlating the change in BPE with tumour response, the average decrease in BEC was 1.3 in cases of complete remission, 0.83 in cases with partial response, 0.85 in cases with stable disease and 0.40 in cases with progressive disease. Correlation analysis showed a significant correlation between the decrease in BEC and tumour response (r = -0.24, p = 0.03).
CONCLUSIONS: BPE decreased by, on average, 0.87 BEC following NAC for breast cancer. The degree of BPE reduction seemed to correlate with tumour response. KEY POINTS: • BPE decreases by an average of 0.87 categories under neoadjuvant chemotherapy. • The reduction of BPE following neoadjuvant chemotherapy correlates with the tumour response. • The classification of the BPE shows good agreement among trained readers.

Entities:  

Keywords:  Background enhancement; Breast MRI; Breast cancer; Chemotherapy; Tumour response

Mesh:

Substances:

Year:  2015        PMID: 26382845     DOI: 10.1007/s00330-015-4011-x

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  26 in total

1.  Impact of menopausal status on background parenchymal enhancement and fibroglandular tissue on breast MRI.

Authors:  Valencia King; Yajia Gu; Jennifer B Kaplan; Jennifer D Brooks; Malcolm C Pike; Elizabeth A Morris
Journal:  Eur Radiol       Date:  2012-07-04       Impact factor: 5.315

2.  Updates and revisions to the BI-RADS magnetic resonance imaging lexicon.

Authors:  Sonya D Edwards; Jafi A Lipson; Debra M Ikeda; Janie M Lee
Journal:  Magn Reson Imaging Clin N Am       Date:  2013-05-14       Impact factor: 2.266

3.  Background parenchymal signal enhancement ratio at preoperative MR imaging: association with subsequent local recurrence in patients with ductal carcinoma in situ after breast conservation surgery.

Authors:  Sun-Ah Kim; Nariya Cho; Eun Bi Ryu; Mirinae Seo; Min Sun Bae; Jung Min Chang; Woo Kyung Moon
Journal:  Radiology       Date:  2013-10-28       Impact factor: 11.105

4.  Does background parenchymal enhancement on MRI affect the rate of positive resection margin in breast cancer patients?

Authors:  S Y Park; D K Kang; T H Kim
Journal:  Br J Radiol       Date:  2014-11-27       Impact factor: 3.039

5.  Normal parenchymal enhancement patterns in women undergoing MR screening of the breast.

Authors:  Sanaz A Jansen; Vicky C Lin; Maryellen L Giger; Hui Li; Gregory S Karczmar; Gillian M Newstead
Journal:  Eur Radiol       Date:  2011-02-17       Impact factor: 5.315

6.  Breast MRI fibroglandular volume and parenchymal enhancement in BRCA1 and BRCA2 mutation carriers before and immediately after risk-reducing salpingo-oophorectomy.

Authors:  Michael J DeLeo; Susan M Domchek; Despina Kontos; Emily Conant; Jinbo Chen; Susan Weinstein
Journal:  AJR Am J Roentgenol       Date:  2015-03       Impact factor: 3.959

7.  Correlation between breast density in mammography and background enhancement in MR mammography.

Authors:  R Cubuk; N Tasali; B Narin; F Keskiner; L Celik; S Guney
Journal:  Radiol Med       Date:  2010-01-15       Impact factor: 3.469

8.  Enhancement parameters on dynamic contrast enhanced breast MRI: do they correlate with prognostic factors and subtypes of breast cancers?

Authors:  Ji Youn Kim; Sung Hun Kim; Yun Ju Kim; Bong Joo Kang; Yeong Yi An; A Won Lee; Byung Joo Song; Yong Soo Park; Han Bi Lee
Journal:  Magn Reson Imaging       Date:  2014-08-29       Impact factor: 2.546

9.  Effects of tamoxifen and aromatase inhibitors on breast tissue enhancement in dynamic contrast-enhanced breast MR imaging: a longitudinal intraindividual cohort study.

Authors:  Simone Schrading; Hans Schild; Marietta Kühr; Christiane Kuhl
Journal:  Radiology       Date:  2013-12-10       Impact factor: 11.105

10.  Background parenchymal enhancement in breast MRIs of breast cancer patients: impact on tumor size estimation.

Authors:  Ji Eun Baek; Sung Hun Kim; Ah Won Lee
Journal:  Eur J Radiol       Date:  2014-05-16       Impact factor: 3.528

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  27 in total

1.  Heterogeneous Enhancement Patterns of Tumor-adjacent Parenchyma at MR Imaging Are Associated with Dysregulated Signaling Pathways and Poor Survival in Breast Cancer.

Authors:  Jia Wu; Bailiang Li; Xiaoli Sun; Guohong Cao; Daniel L Rubin; Sandy Napel; Debra M Ikeda; Allison W Kurian; Ruijiang Li
Journal:  Radiology       Date:  2017-07-14       Impact factor: 11.105

Review 2.  Evaluation of background parenchymal enhancement on breast MRI: a systematic review.

Authors:  Bianca Bignotti; Alessio Signori; Francesca Valdora; Federica Rossi; Massimo Calabrese; Manuela Durando; Giovanna Mariscotto; Alberto Tagliafico
Journal:  Br J Radiol       Date:  2016-12-07       Impact factor: 3.039

3.  Relationship between background parenchymal enhancement on breast MRI and pathological tumor response in breast cancer patients receiving neoadjuvant chemotherapy.

Authors:  Seon Jeong Oh; Eun Young Chae; Joo Hee Cha; Hee Jung Shin; Woo Jung Choi; Hak Hee Kim
Journal:  Br J Radiol       Date:  2018-06-05       Impact factor: 3.039

4.  Automated Semi-Quantitative Analysis of Breast MRI: Potential Imaging Biomarker for the Prediction of Tissue Response to Neoadjuvant Chemotherapy.

Authors:  Matthias Dietzel; Clemens Kaiser; Katja Pinker; Evelyn Wenkel; Matthias Hammon; Michael Uder; Barbara Bennani Baiti; Paola Clauser; Rüdiger Schulz-Wendtland; Pascal Baltzer
Journal:  Breast Care (Basel)       Date:  2017-08-29       Impact factor: 2.860

5.  Identifying relations between imaging phenotypes and molecular subtypes of breast cancer: Model discovery and external validation.

Authors:  Jia Wu; Xiaoli Sun; Jeff Wang; Yi Cui; Fumi Kato; Hiroki Shirato; Debra M Ikeda; Ruijiang Li
Journal:  J Magn Reson Imaging       Date:  2017-02-08       Impact factor: 4.813

Review 6.  Background parenchymal enhancement on breast MRI: A comprehensive review.

Authors:  Geraldine J Liao; Leah C Henze Bancroft; Roberta M Strigel; Rhea D Chitalia; Despina Kontos; Linda Moy; Savannah C Partridge; Habib Rahbar
Journal:  J Magn Reson Imaging       Date:  2019-04-19       Impact factor: 4.813

7.  Background parenchymal enhancement in contrast-enhanced MR imaging suggests systemic effects of intrauterine contraceptive devices.

Authors:  Luisa Charlotte Huck; Daniel Truhn; Caroline Wilpert; Eloisa Zanderigo; Vanessa Raaff; Ebba Dethlefsen; Maike Bode; Christiane Katharina Kuhl
Journal:  Eur Radiol       Date:  2022-05-07       Impact factor: 5.315

8.  Multivariable Models Based on Baseline Imaging Features and Clinicopathological Characteristics to Predict Breast Pathologic Response after Neoadjuvant Chemotherapy in Patients with Breast Cancer.

Authors:  Peixian Chen; Chuan Wang; Ruiliang Lu; Ruilin Pan; Lewei Zhu; Dan Zhou; Guolin Ye
Journal:  Breast Care (Basel)       Date:  2021-12-23       Impact factor: 2.268

9.  The rate of breast fibroglandular enhancement during dynamic contrast-enhanced MRI reflects response to neoadjuvant therapy.

Authors:  John Virostko; Garrett Kuketz; Erin Higgins; Chengyue Wu; Anna G Sorace; Julie C DiCarlo; Sarah Avery; Debra Patt; Boone Goodgame; Thomas E Yankeelov
Journal:  Eur J Radiol       Date:  2021-01-09       Impact factor: 3.528

10.  Contrast-Enhanced Spectral Mammography-Based Radiomics Nomogram for the Prediction of Neoadjuvant Chemotherapy-Insensitive Breast Cancers.

Authors:  Zhongyi Wang; Fan Lin; Heng Ma; Yinghong Shi; Jianjun Dong; Ping Yang; Kun Zhang; Na Guo; Ran Zhang; Jingjing Cui; Shaofeng Duan; Ning Mao; Haizhu Xie
Journal:  Front Oncol       Date:  2021-02-22       Impact factor: 6.244

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