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

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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.

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Acknowledgment

This work was sponsored by the Norwegian Women’s Public Health Association, Trondheim, Norway.

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Authors and Affiliations

  1. Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), 7489 , Trondheim, Norway

    Tone F. Bathen, Line R. Jensen, Beathe Sitter & Ingrid S. Gribbestad

  2. Department of Surgery, St. Olavs University Hospital, 7006 , Trondheim, Norway

    Hans E. Fjösne

  3. Department of Laboratory Medicine, Children’s and Women’s Health, Norwegian University of Science and Technology (NTNU), 7489 , Trondheim, Norway

    Jostein Halgunset

  4. MRi_Consulting, Kingston, Ontario, Canada

    David E. Axelson

  5. St. Olavs University Hospital, Cancer Clinic, 7006 , Trondheim, Norway

    Steinar Lundgren

  6. Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), 7489, Trondheim, Norway

    Steinar Lundgren

Authors
  1. Tone F. Bathen
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  2. Line R. Jensen
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  3. Beathe Sitter
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  4. Hans E. Fjösne
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  5. Jostein Halgunset
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  6. David E. Axelson
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  7. Ingrid S. Gribbestad
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  8. Steinar Lundgren
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Correspondence to Tone F. Bathen.

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Bathen, T.F., Jensen, L.R., Sitter, B. et al. MR-determined metabolic phenotype of breast cancer in prediction of lymphatic spread, grade, and hormone status. Breast Cancer Res Treat 104, 181–189 (2007). https://doi.org/10.1007/s10549-006-9400-z

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  • DOI: https://doi.org/10.1007/s10549-006-9400-z

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