title: Magnetic resonance imaging texture analysis classification of primary breast cancer.
abstract: OBJECTIVE
  Patient-tailored treatments for breast cancer are based on histological and immunohistochemical (IHC) subtypes. Magnetic Resonance Imaging (MRI) texture analysis (TA) may be useful in non-invasive lesion subtype classification.
  
  
  METHODS
  Women with newly diagnosed primary breast cancer underwent pre-treatment dynamic contrast-enhanced breast MRI. TA was performed using co-occurrence matrix (COM) features, by creating a model on retrospective training data, then prospectively applying to a test set. Analyses were blinded to breast pathology. Subtype classifications were performed using a cross-validated k-nearest-neighbour (k = 3) technique, with accuracy relative to pathology assessed and receiver operator curve (AUROC) calculated. Mann-Whitney U and Kruskal-Wallis tests were used to assess raw entropy feature values.
  
  
  RESULTS
  Histological subtype classifications were similar across training (n = 148 cancers) and test sets (n = 73 lesions) using all COM features (training: 75%, AUROC = 0.816; test: 72.5%, AUROC = 0.823). Entropy features were significantly different between lobular and ductal cancers (p < 0.001; Mann-Whitney U). IHC classifications using COM features were also similar for training and test data (training: 57.2%, AUROC = 0.754; test: 57.0%, AUROC = 0.750). Hormone receptor positive and negative cancers demonstrated significantly different entropy features. Entropy features alone were unable to create a robust classification model.
  
  
  CONCLUSIONS
  Textural differences on contrast-enhanced MR images may reflect underlying lesion subtypes, which merits testing against treatment response.
  
  
  CONCLUSIONS
  • MR-derived entropy features, representing heterogeneity, provide important information on tissue composition. • Entropy features can differentiate between histological and immunohistochemical subtypes of breast cancer. • Differing entropy features between breast cancer subtypes implies differences in lesion heterogeneity. • Texture analysis of breast cancer potentially provides added information for decision making.
authors.affiliation: Department of Medical Physics, Ninewells Hospital and Medical School, Ninewells Avenue, Dundee, DD1 9SY, UK. shelley.waugh@nhs.net.
authors.forename: S A
authors.initials: SA
authors.lastname: Waugh
authors.affiliation: Department of Pathology, Ninewells Hospital and Medical School, Dundee, DD1 9SY, UK.
authors.forename: C A
authors.initials: CA
authors.lastname: Purdie
authors.affiliation: Department of Pathology, Ninewells Hospital and Medical School, Dundee, DD1 9SY, UK.
authors.forename: L B
authors.initials: LB
authors.lastname: Jordan
authors.affiliation: Division of Imaging and Technology, Ninewells Hospital and Medical School, University of Dundee, Dundee, DD1 9SY, UK.
authors.forename: S
authors.initials: S
authors.lastname: Vinnicombe
authors.affiliation: Department of Medical Physics, Ninewells Hospital and Medical School, Ninewells Avenue, Dundee, DD1 9SY, UK.
authors.forename: R A
authors.initials: RA
authors.lastname: Lerski
authors.affiliation: Department of Clinical Radiology, Ninewells Hospital and Medical School, Dundee, DD1 9SY, UK.
authors.forename: P
authors.initials: P
authors.lastname: Martin
authors.affiliation: Department of Surgical Oncology, University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Houston, TX, 77030, USA.
authors.forename: A M
authors.initials: AM
authors.lastname: Thompson
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001943:Breast Neoplasms / Q000175:diagnosis*; D019277:Entropy; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods; D008875:Middle Aged; D011446:Prospective Studies; D012189:Retrospective Studies
keywords: Breast cancer; Classification; Histological subtypes and immunohistochemical profiles; Magnetic Resonance Imaging (MRI); Texture analysis (TA)