Literature DB >> 29392160

Distinguishing benign and malignant breast tumors: preliminary comparison of kinetic modeling approaches using multi-institutional dynamic contrast-enhanced MRI data from the International Breast MR Consortium 6883 trial.

Anna G Sorace1,2,3, Savannah C Partridge4, Xia Li5, Jack Virostko1,2, Stephanie L Barnes3,6, Daniel S Hippe4, Wei Huang7,8, Thomas E Yankeelov1,2,3,6.   

Abstract

Comparative preliminary analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data collected in the International Breast MR Consortium 6883 multicenter trial was performed to distinguish benign and malignant breast tumors. Prebiopsy DCE-MRI data from 45 patients with suspicious breast lesions were obtained. Semiquantitative mean signal-enhancement ratio ([Formula: see text]) was calculated for all lesions, and quantitative pharmacokinetic, parameters [Formula: see text], [Formula: see text], and [Formula: see text], were calculated for the subset with available [Formula: see text] maps ([Formula: see text]). Diagnostic performance was estimated for DCE-MRI parameters and compared to standard clinical MRI assessment. Quantitative and semiquantitative metrics discriminated benign and malignant lesions, with receiver operating characteristic area under the curve (AUC) values of 0.71, 0.70, and 0.82 for [Formula: see text], [Formula: see text], and [Formula: see text], respectively ([Formula: see text]). At equal 94% sensitivity, the specificity and positive predictive value of [Formula: see text] (53% and 63%, respectively) and Ktrans (42% and 58%) were higher than clinical MRI assessment (32% and 54%). A multivariable model combining [Formula: see text] and clinical MRI assessment had an AUC value of 0.87. Quantitative pharmacokinetic and semiquantitative analyses of DCE-MRI improves discrimination of benign and malignant breast tumors, with our findings suggesting higher diagnostic accuracy using [Formula: see text]. [Formula: see text] has potential to help reduce unnecessary biopsies resulting from routine breast imaging.

Entities:  

Keywords:  Ktrans; breast cancer; dynamic contrast-enhanced MRI; kep; kinetic analysis; signal-enhancement ratio

Year:  2018        PMID: 29392160      PMCID: PMC5777541          DOI: 10.1117/1.JMI.5.1.011019

Source DB:  PubMed          Journal:  J Med Imaging (Bellingham)        ISSN: 2329-4302


  38 in total

1.  Dynamic breast MR imaging: are signal intensity time course data useful for differential diagnosis of enhancing lesions?

Authors:  C K Kuhl; P Mielcareck; S Klaschik; C Leutner; E Wardelmann; J Gieseke; H H Schild
Journal:  Radiology       Date:  1999-04       Impact factor: 11.105

2.  Quantitative pharmacokinetic analysis of DCE-MRI data without an arterial input function: a reference region model.

Authors:  Thomas E Yankeelov; Jeffrey J Luci; Martin Lepage; Rui Li; Laura Debusk; P Charles Lin; Ronald R Price; John C Gore
Journal:  Magn Reson Imaging       Date:  2005-05       Impact factor: 2.546

3.  Utility of magnetic resonance imaging in the management of breast cancer: evidence for improved preoperative staging.

Authors:  L Esserman; N Hylton; L Yassa; J Barclay; S Frankel; E Sickles
Journal:  J Clin Oncol       Date:  1999-01       Impact factor: 44.544

4.  Probability of malignancy for lesions detected on breast MRI: a predictive model incorporating BI-RADS imaging features and patient characteristics.

Authors:  Wendy B Demartini; Brenda F Kurland; Robert L Gutierrez; C Craig Blackmore; Sue Peacock; Constance D Lehman
Journal:  Eur Radiol       Date:  2011-02-27       Impact factor: 5.315

5.  Kinetic Analysis of Benign and Malignant Breast Lesions With Ultrafast Dynamic Contrast-Enhanced MRI: Comparison With Standard Kinetic Assessment.

Authors:  Hiroyuki Abe; Naoko Mori; Keiko Tsuchiya; David V Schacht; Federico D Pineda; Yulei Jiang; Gregory S Karczmar
Journal:  AJR Am J Roentgenol       Date:  2016-08-17       Impact factor: 3.959

6.  A novel AIF tracking method and comparison of DCE-MRI parameters using individual and population-based AIFs in human breast cancer.

Authors:  Xia Li; E Brian Welch; Lori R Arlinghaus; A Bapsi Chakravarthy; Lei Xu; Jaime Farley; Mary E Loveless; Ingrid A Mayer; Mark C Kelley; Ingrid M Meszoely; Julie A Means-Powell; Vandana G Abramson; Ana M Grau; John C Gore; Thomas E Yankeelov
Journal:  Phys Med Biol       Date:  2011-08-12       Impact factor: 3.609

7.  Contrast-Enhanced Magnetic Resonance Imaging to Assess Tumor Histopathology and Angiogenesis in Breast Carcinoma.

Authors:  Laura Esserman; Nola Hylton; Tracy George; Noel Weidner
Journal:  Breast J       Date:  1999-01       Impact factor: 2.431

8.  Pharmacokinetic mapping for lesion classification in dynamic breast MRI.

Authors:  Matthias C Schabel; Glen R Morrell; Karen Y Oh; Cheryl A Walczak; R Brad Barlow; Leigh A Neumayer
Journal:  J Magn Reson Imaging       Date:  2010-06       Impact factor: 4.813

9.  MRI evaluation of the contralateral breast in women with recently diagnosed breast cancer.

Authors:  Constance D Lehman; Constantine Gatsonis; Christiane K Kuhl; R Edward Hendrick; Etta D Pisano; Lucy Hanna; Sue Peacock; Stanley F Smazal; Daniel D Maki; Thomas B Julian; Elizabeth R DePeri; David A Bluemke; Mitchell D Schnall
Journal:  N Engl J Med       Date:  2007-03-28       Impact factor: 91.245

Review 10.  Dynamic contrast-enhanced MRI in clinical oncology: current status and future directions.

Authors:  Anwar R Padhani
Journal:  J Magn Reson Imaging       Date:  2002-10       Impact factor: 4.813

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  8 in total

1.  Dynamic Contrast-enhanced MRI Detects Responses to Stroma-directed Therapy in Mouse Models of Pancreatic Ductal Adenocarcinoma.

Authors:  Jianbo Cao; Stephen Pickup; Cynthia Clendenin; Barbara Blouw; Hoon Choi; David Kang; Mark Rosen; Peter J O'Dwyer; Rong Zhou
Journal:  Clin Cancer Res       Date:  2018-12-26       Impact factor: 12.531

2.  Quantitative transport mapping (QTM) for differentiating benign and malignant breast lesion: Comparison with traditional kinetics modeling and semi-quantitative enhancement curve characteristics.

Authors:  Qihao Zhang; Pascal Spincemaille; Michele Drotman; Christine Chen; Sarah Eskreis-Winkler; Weiyuan Huang; Liangdong Zhou; John Morgan; Thanh D Nguyen; Martin R Prince; Yi Wang
Journal:  Magn Reson Imaging       Date:  2021-11-06       Impact factor: 2.546

3.  A simplified scoring protocol to improve diagnostic accuracy with the breast imaging reporting and data system in breast magnetic resonance imaging.

Authors:  Liuquan Cheng; Xiru Li; Yuting Zhong; Menglu Li; Jingjin Zhu; Boya Zhang; Mei Liu; Zhili Wang; Jiandong Wang; Yiqiong Zheng
Journal:  Quant Imaging Med Surg       Date:  2022-07

4.  Sigmoid model analysis of breast dynamic contrast-enhanced MRI: Distinguishing between benign and malignant breast masses and breast cancer subtype prediction.

Authors:  Norikazu Koori; Tosiaki Miyati; Naoki Ohno; Hiroko Kawashima; Hiroko Nishikawa
Journal:  J Appl Clin Med Phys       Date:  2022-05-20       Impact factor: 2.243

5.  An in silico validation framework for quantitative DCE-MRI techniques based on a dynamic digital phantom.

Authors:  Chengyue Wu; David A Hormuth; Ty Easley; Victor Eijkhout; Federico Pineda; Gregory S Karczmar; Thomas E Yankeelov
Journal:  Med Image Anal       Date:  2021-07-20       Impact factor: 13.828

6.  Multinuclear MRI to disentangle intracellular sodium concentration and extracellular volume fraction in breast cancer.

Authors:  Carlotta Ianniello; Linda Moy; Justin Fogarty; Freya Schnabel; Sylvia Adams; Deborah Axelrod; Leon Axel; Ryan Brown; Guillaume Madelin
Journal:  Sci Rep       Date:  2021-03-04       Impact factor: 4.379

7.  Discrimination of Malignant and Benign Breast Lesions Using Quantitative Multiparametric MRI: A Preliminary Study.

Authors:  Kurt Li; Archana Machireddy; Alina Tudorica; Brendan Moloney; Karen Y Oh; Neda Jafarian; Savannah C Partridge; Xin Li; Wei Huang
Journal:  Tomography       Date:  2020-06

Review 8.  Application of Radiomics and Decision Support Systems for Breast MR Differential Diagnosis.

Authors:  Ioannis Tsougos; Alexandros Vamvakas; Constantin Kappas; Ioannis Fezoulidis; Katerina Vassiou
Journal:  Comput Math Methods Med       Date:  2018-09-23       Impact factor: 2.238

  8 in total

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