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Recurrence-free survival in breast cancer is associated with MRI tumor enhancement dynamics quantified using computer algorithms.

Publication ,  Journal Article
Mazurowski, MA; Grimm, LJ; Zhang, J; Marcom, PK; Yoon, SC; Kim, C; Ghate, SV; Johnson, KS
Published in: Eur J Radiol
November 2015

PURPOSE: The purpose of this study is to investigate the association between breast cancer recurrence-free survival and breast magnetic resonance imaging (MRI) tumor enhancement dynamics which are quantified semi-automatically using computer algorithms. METHODS: In this retrospective IRB-approved study, we analyzed data from 275 breast cancer patients at a single institution. Recurrence-free survival data were obtained from the medical record. Routine clinical pre-operative breast MRIs were performed in all patients. The tumors were marked on the MRIs by fellowship-trained breast radiologists. A previously developed computer algorithm was applied to the marked tumors to quantify the enhancement dynamics relative to the automatically assessed background parenchymal enhancement. To establish whether the contrast enhancement feature quantified by the algorithm was associated with recurrence-free survival, we constructed a Cox proportional hazards regression model with the computer-extracted feature as a covariate. We controlled for tumor grade and size (major axis length), patient age, patient race/ethnicity, and menopausal status. RESULTS: The analysis showed that the semi-automatically obtained feature quantifying MRI tumor enhancement dynamics was independently predictive of recurrence-free survival (p=0.024). CONCLUSION: Semi-automatically quantified tumor enhancement dynamics on MRI are predictive of recurrence-free survival in breast cancer patients.

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Published In

Eur J Radiol

DOI

EISSN

1872-7727

Publication Date

November 2015

Volume

84

Issue

11

Start / End Page

2117 / 2122

Location

Ireland

Related Subject Headings

  • Retrospective Studies
  • Proportional Hazards Models
  • Prognosis
  • Predictive Value of Tests
  • Pattern Recognition, Automated
  • Nuclear Medicine & Medical Imaging
  • Neoplasm Recurrence, Local
  • Middle Aged
  • Magnetic Resonance Imaging
  • Image Interpretation, Computer-Assisted
 

Citation

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Mazurowski, M. A., Grimm, L. J., Zhang, J., Marcom, P. K., Yoon, S. C., Kim, C., … Johnson, K. S. (2015). Recurrence-free survival in breast cancer is associated with MRI tumor enhancement dynamics quantified using computer algorithms. Eur J Radiol, 84(11), 2117–2122. https://doi.org/10.1016/j.ejrad.2015.07.012
Mazurowski, Maciej A., Lars J. Grimm, Jing Zhang, P Kelly Marcom, Sora C. Yoon, Connie Kim, Sujata V. Ghate, and Karen S. Johnson. “Recurrence-free survival in breast cancer is associated with MRI tumor enhancement dynamics quantified using computer algorithms.Eur J Radiol 84, no. 11 (November 2015): 2117–22. https://doi.org/10.1016/j.ejrad.2015.07.012.
Mazurowski MA, Grimm LJ, Zhang J, Marcom PK, Yoon SC, Kim C, et al. Recurrence-free survival in breast cancer is associated with MRI tumor enhancement dynamics quantified using computer algorithms. Eur J Radiol. 2015 Nov;84(11):2117–22.
Mazurowski, Maciej A., et al. “Recurrence-free survival in breast cancer is associated with MRI tumor enhancement dynamics quantified using computer algorithms.Eur J Radiol, vol. 84, no. 11, Nov. 2015, pp. 2117–22. Pubmed, doi:10.1016/j.ejrad.2015.07.012.
Mazurowski MA, Grimm LJ, Zhang J, Marcom PK, Yoon SC, Kim C, Ghate SV, Johnson KS. Recurrence-free survival in breast cancer is associated with MRI tumor enhancement dynamics quantified using computer algorithms. Eur J Radiol. 2015 Nov;84(11):2117–2122.
Journal cover image

Published In

Eur J Radiol

DOI

EISSN

1872-7727

Publication Date

November 2015

Volume

84

Issue

11

Start / End Page

2117 / 2122

Location

Ireland

Related Subject Headings

  • Retrospective Studies
  • Proportional Hazards Models
  • Prognosis
  • Predictive Value of Tests
  • Pattern Recognition, Automated
  • Nuclear Medicine & Medical Imaging
  • Neoplasm Recurrence, Local
  • Middle Aged
  • Magnetic Resonance Imaging
  • Image Interpretation, Computer-Assisted