Breast Cancer Research and Treatment

, Volume 104, Issue 2, pp 181–189

MR-determined metabolic phenotype of breast cancer in prediction of lymphatic spread, grade, and hormone status

  • Tone F. Bathen
  • Line R. Jensen
  • Beathe Sitter
  • Hans E. Fjösne
  • Jostein Halgunset
  • David E. Axelson
  • Ingrid S. Gribbestad
  • Steinar Lundgren
Article

DOI: 10.1007/s10549-006-9400-z

Cite this article as:
Bathen, T.F., Jensen, L.R., Sitter, B. et al. Breast Cancer Res Treat (2007) 104: 181. doi:10.1007/s10549-006-9400-z

Abstract

The purpose of the study was to evaluate the use of metabolic phenotype, described by high-resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS), as a tool for prediction of histological grade, hormone status, and axillary lymphatic spread in breast cancer patients. Biopsies from breast cancer (n = 91) and adjacent non-involved tissue (n = 48) were excised from patients (n = 77) during surgery. HR MAS MR spectra of intact samples were acquired. Multivariate models relating spectral data to histological grade, lymphatic spread, and hormone status were designed. The multivariate methods applied were variable reduction by principal component analysis (PCA) or partial least-squares regression-uninformative variable elimination (PLS-UVE), and modelling by PLS, probabilistic neural network (PNN), or cascade correlation neural network. In the end, model verification by prediction of blind samples (n = 12) was performed. Validation of PNN training resulted in sensitivity and specificity ranging from 83 to 100% for all predictions. Verification of models by blind sample testing showed that hormone status was well predicted by both PNN and PLS (11 of 12 correct), lymphatic spread was best predicted by PLS (8 of 12), whereas PLS-UVE PNN was the best approach for predicting grade (9 of 12 correct). MR-determined metabolic phenotype may have a future role as a supplement for clinical decision-making-concerning adjuvant treatment and the adaptation to more individualised treatment protocols.

Keywords

Breast cancer HR MAS MRS Metabolomics MR spectroscopy Predictive factors 

Copyright information

© Springer Science+Business Media, LLC 2006

Authors and Affiliations

  • Tone F. Bathen
    • 1
  • Line R. Jensen
    • 1
  • Beathe Sitter
    • 1
  • Hans E. Fjösne
    • 2
  • Jostein Halgunset
    • 3
  • David E. Axelson
    • 4
  • Ingrid S. Gribbestad
    • 1
  • Steinar Lundgren
    • 5
    • 6
  1. 1.Department of Circulation and Medical ImagingNorwegian University of Science and Technology (NTNU)TrondheimNorway
  2. 2.Department of SurgerySt. Olavs University HospitalTrondheimNorway
  3. 3.Department of Laboratory Medicine, Children’s and Women’s HealthNorwegian University of Science and Technology (NTNU)TrondheimNorway
  4. 4.MRi_ConsultingKingstonCanada
  5. 5.St. Olavs University Hospital, Cancer ClinicTrondheimNorway
  6. 6.Department of Cancer Research and Molecular MedicineNorwegian University of Science and Technology (NTNU)TrondheimNorway

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