Literature DB >> 33327532

Pharmacokinetic Analysis of Dynamic Contrast-Enhanced Magnetic Resonance Imaging at 7T for Breast Cancer Diagnosis and Characterization.

R Elena Ochoa-Albiztegui1, Varadan Sevilimedu2, Joao V Horvat1, Sunitha B Thakur1,3, Thomas H Helbich4, Siegfried Trattnig5, Elizabeth A Morris1, Jeffrey S Reiner1, Katja Pinker1,4.   

Abstract

The purpose of this study was to investigate whether ultra-high-field dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast at 7T using quantitative pharmacokinetic (PK) analysis can differentiate between benign and malignant breast tumors for improved breast cancer diagnosis and to predict molecular subtypes, histologic grade, and proliferation rate in breast cancer. In this prospective study, 37 patients with 43 lesions suspicious on mammography or ultrasound underwent bilateral DCE-MRI of the breast at 7T. PK parameters (KTrans, kep, Ve) were evaluated with two region of interest (ROI) approaches (2D whole-tumor ROI or 2D 10 mm standardized ROI) manually drawn by two readers (senior reader, R1, and R2) independently. Histopathology served as the reference standard. PK parameters differentiated benign and malignant lesions (n = 16, 27, respectively) with good accuracy (AUCs = 0.655-0.762). The addition of quantitative PK analysis to subjective BI-RADS classification improved breast cancer detection from 88.4% to 97.7% for R1 and 86.04% to 97.67% for R2. Different ROI approaches did not influence diagnostic accuracy for both readers. Except for KTrans for whole-tumor ROI for R2, none of the PK parameters were valuable to predict molecular subtypes, histologic grade, or proliferation rate in breast cancer. In conclusion, PK-enhanced BI-RADS is promising for the noninvasive differentiation of benign and malignant breast tumors.

Entities:  

Keywords:  breast cancer; histologic grade; immunohistochemistry; molecular subtypes; proliferation rate; quantitative pharmacokinetics; ultra-high-field magnetic resonance imaging

Year:  2020        PMID: 33327532      PMCID: PMC7765071          DOI: 10.3390/cancers12123763

Source DB:  PubMed          Journal:  Cancers (Basel)        ISSN: 2072-6694            Impact factor:   6.639


  47 in total

1.  Measurement of the blood-brain barrier permeability and leakage space using dynamic MR imaging. 1. Fundamental concepts.

Authors:  P S Tofts; A G Kermode
Journal:  Magn Reson Med       Date:  1991-02       Impact factor: 4.668

2.  Evaluation of the kinetic properties of background parenchymal enhancement throughout the phases of the menstrual cycle.

Authors:  Alana R Amarosa; Jason McKellop; Ana Paula Klautau Leite; Melanie Moccaldi; Tess V Clendenen; James S Babb; Anne Zeleniuch-Jacquotte; Linda Moy; Sungheon Kim
Journal:  Radiology       Date:  2013-05-08       Impact factor: 11.105

Review 3.  Meta-analysis of magnetic resonance imaging in detecting residual breast cancer after neoadjuvant therapy.

Authors:  Michael L Marinovich; Nehmat Houssami; Petra Macaskill; Francesco Sardanelli; Les Irwig; Eleftherios P Mamounas; Gunter von Minckwitz; Meagan E Brennan; Stefano Ciatto
Journal:  J Natl Cancer Inst       Date:  2013-01-07       Impact factor: 13.506

4.  Correlation of perfusion parameters on dynamic contrast-enhanced MRI with prognostic factors and subtypes of breast cancers.

Authors:  Hye Ryoung Koo; Nariya Cho; In Chan Song; Hyeonjin Kim; Jung Min Chang; Ann Yi; Bo La Yun; Woo Kyung Moon
Journal:  J Magn Reson Imaging       Date:  2012-03-05       Impact factor: 4.813

5.  Feasibility of 7 Tesla breast magnetic resonance imaging determination of intrinsic sensitivity and high-resolution magnetic resonance imaging, diffusion-weighted imaging, and (1)H-magnetic resonance spectroscopy of breast cancer patients receiving neoadjuvant therapy.

Authors:  Mies A Korteweg; Wouter B Veldhuis; Fredy Visser; Peter R Luijten; Willem P Th M Mali; Paul J van Diest; Maurice A A J van den Bosch; Dennis J Klomp
Journal:  Invest Radiol       Date:  2011-06       Impact factor: 6.016

6.  Subtyping of breast cancer by immunohistochemistry to investigate a relationship between subtype and short and long term survival: a collaborative analysis of data for 10,159 cases from 12 studies.

Authors:  Fiona M Blows; Kristy E Driver; Marjanka K Schmidt; Annegien Broeks; Flora E van Leeuwen; Jelle Wesseling; Maggie C Cheang; Karen Gelmon; Torsten O Nielsen; Carl Blomqvist; Päivi Heikkilä; Tuomas Heikkinen; Heli Nevanlinna; Lars A Akslen; Louis R Bégin; William D Foulkes; Fergus J Couch; Xianshu Wang; Vicky Cafourek; Janet E Olson; Laura Baglietto; Graham G Giles; Gianluca Severi; Catriona A McLean; Melissa C Southey; Emad Rakha; Andrew R Green; Ian O Ellis; Mark E Sherman; Jolanta Lissowska; William F Anderson; Angela Cox; Simon S Cross; Malcolm W R Reed; Elena Provenzano; Sarah-Jane Dawson; Alison M Dunning; Manjeet Humphreys; Douglas F Easton; Montserrat García-Closas; Carlos Caldas; Paul D Pharoah; David Huntsman
Journal:  PLoS Med       Date:  2010-05-25       Impact factor: 11.069

7.  Quantitative Sodium MR Imaging at 7 T: Initial Results and Comparison with Diffusion-weighted Imaging in Patients with Breast Tumors.

Authors:  Olgica Zaric; Katja Pinker; Stefan Zbyn; Bernhard Strasser; Simon Robinson; Lenka Minarikova; Stephan Gruber; Alex Farr; Christian Singer; Thomas H Helbich; Siegfried Trattnig; Wolfgang Bogner
Journal:  Radiology       Date:  2016-01-27       Impact factor: 11.105

8.  Application of whole-lesion histogram analysis of pharmacokinetic parameters in dynamic contrast-enhanced MRI of breast lesions with the CAIPIRINHA-Dixon-TWIST-VIBE technique.

Authors:  Zhiwei Li; Tao Ai; Yiqi Hu; Xu Yan; Marcel Dominik Nickel; Xiao Xu; Liming Xia
Journal:  J Magn Reson Imaging       Date:  2017-06-03       Impact factor: 4.813

9.  Quantitative analysis of 3-Tesla magnetic resonance imaging in the differential diagnosis of breast lesions.

Authors:  Zhen-Shen Ma; DA-Wei Wang; Xiu-Bin Sun; Hao Shi; Tao Pang; Gui-Qing Dong; Cheng-Qi Zhang
Journal:  Exp Ther Med       Date:  2014-12-22       Impact factor: 2.447

10.  Personalizing the treatment of women with early breast cancer: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013.

Authors:  A Goldhirsch; E P Winer; A S Coates; R D Gelber; M Piccart-Gebhart; B Thürlimann; H-J Senn
Journal:  Ann Oncol       Date:  2013-08-04       Impact factor: 32.976

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  2 in total

Review 1.  A Comprehensive Survey on Deep-Learning-Based Breast Cancer Diagnosis.

Authors:  Muhammad Firoz Mridha; Md Abdul Hamid; Muhammad Mostafa Monowar; Ashfia Jannat Keya; Abu Quwsar Ohi; Md Rashedul Islam; Jong-Myon Kim
Journal:  Cancers (Basel)       Date:  2021-12-04       Impact factor: 6.639

2.  Predictive Value of Preoperative Dynamic Contrast-Enhanced MRI Imaging Features in Breast Cancer Patients with Postoperative Recurrence Time.

Authors:  Zhangqiang Wu; Shaoli Gao; Yefeng Yao; Li Yi; Jianjun Wang; Fei Liu
Journal:  Emerg Med Int       Date:  2022-08-02       Impact factor: 1.621

  2 in total

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