Literature DB >> 33454460

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

John Virostko1, Garrett Kuketz2, Erin Higgins2, Chengyue Wu2, Anna G Sorace3, Julie C DiCarlo4, Sarah Avery5, Debra Patt6, Boone Goodgame7, Thomas E Yankeelov8.   

Abstract

PURPOSE: This study assesses the rate of enhancement of breast fibroglandular tissue after administration of a magnetic resonance imaging (MRI) gadolinium-based contrast agent and determines its relationship with response to neoadjuvant therapy (NAT) in women with breast cancer.
METHOD: Women with locally advanced breast cancer (N = 19) were imaged four times over the course of NAT. Dynamic contrast-enhanced (DCE) MRI was acquired after administration of a gadolinium-based contrast agent with a temporal resolution of 7.27 s. The tumor, fibroglandular tissue, and adipose tissue were semi-automatically segmented using a manually drawn region of interest encompassing the tumor followed by fuzzy c-means clustering. The rate and relative intensity of signal enhancement were calculated for each voxel within the tumor and fibroglandular tissue.
RESULTS: The rate of fibroglandular tissue enhancement after contrast agent injection declined by an average of 29 % over the course of NAT. This decline was present in 16 of the 19 patients in the study. The rate of enhancement is significantly higher in women who achieve pathological complete response (pCR) after both 1 cycle (68 % higher, p < 0.05) and after 3-5 cycles of NAT (58 % higher; p < 0.05). The relative intensity of fibroglandular enhancement correlates with the rate of enhancement (R2 = 0.64, p < 0.001) and is higher in women who achieve pCR after both 1 cycle and after 3-5 cycles of NAT (p < 0.05, both timepoints).
CONCLUSION: The rate of fibroglandular tissue enhancement declines over the course of therapy, provides novel information not reflected by tumoral measures, and may predict pathological response early in the course of therapy, with smaller declines in enhancement in women who achieve favorable response.
Copyright © 2021 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  BPE; Breast cancer; Fibroglandular; Ipsilateral; NAT

Mesh:

Substances:

Year:  2021        PMID: 33454460      PMCID: PMC7897312          DOI: 10.1016/j.ejrad.2021.109534

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  24 in total

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Authors:  Laura J Esserman; Donald A Berry; Angela DeMichele; Lisa Carey; Sarah E Davis; Meredith Buxton; Cliff Hudis; Joe W Gray; Charles Perou; Christina Yau; Chad Livasy; Helen Krontiras; Leslie Montgomery; Debasish Tripathy; Constance Lehman; Minetta C Liu; Olufunmilayo I Olopade; Hope S Rugo; John T Carpenter; Lynn Dressler; David Chhieng; Baljit Singh; Carolyn Mies; Joseph Rabban; Yunn-Yi Chen; Dilip Giri; Laura van 't Veer; Nola Hylton
Journal:  J Clin Oncol       Date:  2012-05-29       Impact factor: 44.544

2.  Locally advanced breast cancer: MR imaging for prediction of response to neoadjuvant chemotherapy--results from ACRIN 6657/I-SPY TRIAL.

Authors:  Nola M Hylton; Jeffrey D Blume; Wanda K Bernreuter; Etta D Pisano; Mark A Rosen; Elizabeth A Morris; Paul T Weatherall; Constance D Lehman; Gillian M Newstead; Sandra Polin; Helga S Marques; Laura J Esserman; Mitchell D Schnall
Journal:  Radiology       Date:  2012-06       Impact factor: 11.105

3.  Breast MRI phenotype and background parenchymal enhancement may predict tumor response to neoadjuvant endocrine therapy.

Authors:  Talal Hilal; Matthew Covington; Heidi E Kosiorek; Christine Zwart; Idris T Ocal; Barbara A Pockaj; Donald W Northfelt; Bhavika K Patel
Journal:  Breast J       Date:  2018-07-31       Impact factor: 2.431

4.  Topographic enhancement mapping of the cancer-associated breast stroma using breast MRI.

Authors:  Nima Nabavizadeh; Catherine Klifa; David Newitt; Ying Lu; Yunn-Yi Chen; Howard Hsu; Clark Fisher; Taku Tokayasu; Adam B Olshen; Paul Spellman; Joe W Gray; Nola Hylton; Catherine C Park
Journal:  Integr Biol (Camb)       Date:  2011-03-18       Impact factor: 2.192

Review 5.  MR imaging of the breast for the detection, diagnosis, and staging of breast cancer.

Authors:  S G Orel; M D Schnall
Journal:  Radiology       Date:  2001-07       Impact factor: 11.105

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.  Breast stromal enhancement on MRI is associated with response to neoadjuvant chemotherapy.

Authors:  Jona Hattangadi; Catherine Park; James Rembert; Catherine Klifa; Jimmy Hwang; Jessica Gibbs; Nola Hylton
Journal:  AJR Am J Roentgenol       Date:  2008-06       Impact factor: 3.959

8.  Features of MRI stromal enhancement with neoadjuvant chemotherapy: a subgroup analysis of the ACRIN 6657/I-SPY TRIAL.

Authors:  Adam Olshen; Denise Wolf; Ella F Jones; David Newitt; Laura J van ‘t Veer; Christina Yau; Laura Esserman; Julia D Wulfkuhle; Rosa I Gallagher; Lisa Singer; Emanuel F Petricoin; Nola Hylton; Catherine C Park
Journal:  J Med Imaging (Bellingham)       Date:  2017-12-23

9.  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

10.  Radiomics: Images Are More than Pictures, They Are Data.

Authors:  Robert J Gillies; Paul E Kinahan; Hedvig Hricak
Journal:  Radiology       Date:  2015-11-18       Impact factor: 11.105

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  2 in total

Review 1.  Quantitative magnetic resonance imaging and tumor forecasting of breast cancer patients in the community setting.

Authors:  Angela M Jarrett; Anum S Kazerouni; Chengyue Wu; John Virostko; Anna G Sorace; Julie C DiCarlo; David A Hormuth; David A Ekrut; Debra Patt; Boone Goodgame; Sarah Avery; Thomas E Yankeelov
Journal:  Nat Protoc       Date:  2021-09-22       Impact factor: 13.491

2.  Development and Internal Validation of a Preoperative Prediction Model for Sentinel Lymph Node Status in Breast Cancer: Combining Radiomics Signature and Clinical Factors.

Authors:  Chunhua Wang; Xiaoyu Chen; Hongbing Luo; Yuanyuan Liu; Ruirui Meng; Min Wang; Siyun Liu; Guohui Xu; Jing Ren; Peng Zhou
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  2 in total

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