Literature DB >> 16926079

Dynamic enhanced MRI predicts chemosensitivity in breast cancer patients.

Takeshi Nagashima1, Masahiro Sakakibara, Rikiya Nakamura, Manabu Arai, Masami Kadowaki, Toshiki Kazama, Yukio Nakatani, Keiji Koda, Masaru Miyazaki.   

Abstract

BACKGROUND: Primary chemotherapy for breast cancer is effective as postoperative adjuvant therapy. However, one of the critical disadvantages was a treatment delay for patients with progressive disease. The present study attempts to clarify quantitative parameters on MRI which can be used to predict the sensitivity to treatment in breast cancer patients.
METHODS: The subjects consisted of 26 patients with invasive ductal breast cancer who received primary chemotherapy before surgery. The mean maximum tumor dimension was 3.3cm, and 21 cases had nodal involvements. Three cases demonstrated histological grade 3. Dynamic enhanced MRI was evaluated at three different time periods; prior to, in the midst of preoperative chemotherapy, and just before the initial operation. The signal intensity ratio (SIR) and early contrast uptake (ECU) were calculated, as well as the correlation between these dynamic data and the tumor reduction rates were analyzed retrospectively. P-values of less than 0.05 were considered to indicate statistically significant.
RESULTS: Responders to chemotherapy had the significantly higher SIR and ECU values than non-responders (p=0.0454 and 0.0334, respectively). ECU value significantly decreased as tumor reduction by chemotherapy (p=0.0028). Pathological tumor dimension was significantly correlated with the tumor size estimated on presurgical MRI (p<0.0001).
CONCLUSIONS: Our current series demonstrated the significant correlation between pretreatment MRI data and tumor reduction by chemotherapy in breast cancer patients. With these results, it seems possible to define good and non-responders prior to treatment.

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Year:  2006        PMID: 16926079     DOI: 10.1016/j.ejrad.2006.07.014

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


  13 in total

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Authors:  Gunnar Brix; Jürgen Griebel; Fabian Kiessling; Frederik Wenz
Journal:  Eur J Nucl Med Mol Imaging       Date:  2010-08       Impact factor: 9.236

2.  Dynamic contrast-enhanced MRI-based biomarkers of therapeutic response in triple-negative breast cancer.

Authors:  Daniel I Golden; Jafi A Lipson; Melinda L Telli; James M Ford; Daniel L Rubin
Journal:  J Am Med Inform Assoc       Date:  2013-06-19       Impact factor: 4.497

3.  Surrounding rim formation and reduction in size after radiofrequency ablation for primary breast cancer.

Authors:  Takeshi Nagashima; Masahiro Sakakibara; Takafumi Sangai; Toshiki Kazama; Hiroshi Fujimoto; Masaru Miyazaki
Journal:  Jpn J Radiol       Date:  2009-06-25       Impact factor: 2.374

Review 4.  Pre-treatment differences and early response monitoring of neoadjuvant chemotherapy in breast cancer patients using magnetic resonance imaging: a systematic review.

Authors:  R Prevos; M L Smidt; V C G Tjan-Heijnen; M van Goethem; R G Beets-Tan; J E Wildberger; M B I Lobbes
Journal:  Eur Radiol       Date:  2012-09-16       Impact factor: 5.315

5.  Characterizing and eliminating errors in enhancement and subtraction artifacts in dynamic contrast-enhanced breast MRI: Chemical shift artifact of the third kind.

Authors:  Jamal J Derakhshan; Elizabeth S McDonald; Evan S Siegelman; Mitchell D Schnall; Felix W Wehrli
Journal:  Magn Reson Med       Date:  2017-08-24       Impact factor: 4.668

6.  Statistical comparison of dynamic contrast-enhanced MRI pharmacokinetic models in human breast cancer.

Authors:  Xia Li; E Brian Welch; A Bapsi Chakravarthy; Lei Xu; Lori R Arlinghaus; Jaime Farley; Ingrid A Mayer; Mark C Kelley; Ingrid M Meszoely; Julie Means-Powell; Vandana G Abramson; Ana M Grau; John C Gore; Thomas E Yankeelov
Journal:  Magn Reson Med       Date:  2011-11-29       Impact factor: 4.668

7.  Retrospective study assessing the role of MRI in the diagnostic procedures for early breast carcinoma: a correlation of new foci in the MRI with tumor pathological features.

Authors:  I Calvo-Plaza; L Ugidos; C Miró; P Quevedo; M Parras; C Márquez; J J de la Cruz; A Suárez-Gauthier; F J Pérez; M Herrero; M Marcos; M García-Aranda; M Hidalgo; L G Estévez
Journal:  Clin Transl Oncol       Date:  2012-08-08       Impact factor: 3.405

8.  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

9.  A nonrigid registration algorithm for longitudinal breast MR images and the analysis of breast tumor response.

Authors:  Xia Li; Benoit M Dawant; E Brian Welch; A Bapsi Chakravarthy; Darla Freehardt; Ingrid Mayer; Mark Kelley; Ingrid Meszoely; John C Gore; Thomas E Yankeelov
Journal:  Magn Reson Imaging       Date:  2009-06-13       Impact factor: 2.546

10.  Background Parenchymal Enhancement of the Contralateral Normal Breast: Association with Tumor Response in Breast Cancer Patients Receiving Neoadjuvant Chemotherapy.

Authors:  Jeon Hor Chen; Hon J Yu; Christine Hsu; Rita S Mehta; Philip M Carpenter; Min Ying Su
Journal:  Transl Oncol       Date:  2015-06       Impact factor: 4.243

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