title: Multiparametric spectroscopic photoacoustic imaging of breast cancer development in a transgenic mouse model.
abstract: OBJECTIVE
  To evaluate the potential of multiparametric spectroscopic photoacoustic imaging using oxygen saturation, total hemoglobin, and lipid content to differentiate among four different breast histologies (normal, hyperplasia, ductal carcinoma in situ (DCIS), and invasive breast carcinoma) in a transgenic mouse model of breast cancer development.
  
  
  METHODS
  Animal studies were approved by the Institutional Administrative Panel on Laboratory Animal Care. Mammary glands (n=251) of a transgenic mouse model of breast cancer development (FVB/N-Tg(MMTV-PyMT)634Mul) were imaged using B-mode ultrasound and spectroscopic photoacoustic imaging, analyzed for oxygen saturation, total hemoglobin, and lipid content, and processed for histological analysis. Statistical analysis was performed using one-way ANOVA, two-sample t-tests, logistic regression, and ROC analysis.
  
  
  RESULTS
  Eighty-two normal, 12 hyperplastic, 96 DCIS, and 61 invasive breast carcinoma mammary glands were analyzed. Based on spectroscopic photoacoustic imaging, the oxygen saturation of hyperplasia (50.6%), DCIS (43.0%), and invasive carcinoma (46.2%) significantly increased compared to normal glands (35.5%, P <0.0001), while both total hemoglobin (P<0.01), and lipid content (P<0.0008) significantly decreased with advancing histology. In differentiating normal and hyperplasia from DCIS and invasive breast carcinoma, multiparametric imaging of oxygen saturation, lipid content, and raw photoacoustic signal at 750 nm provided an AUC value of 0.770.
  
  
  CONCLUSIONS
  Multiparametric spectroscopic photoacoustic imaging is feasible and allows detection of differences in concentration of tissue chromophores among different histologies in a transgenic mouse model of breast cancer development.
authors.affiliation: 1. Department of Radiology, Molecular Imaging Program at Stanford, Stanford University, School of Medicine, Stanford, California, USA;
authors.forename: Katheryne E
authors.initials: KE
authors.lastname: Wilson
authors.affiliation: 1. Department of Radiology, Molecular Imaging Program at Stanford, Stanford University, School of Medicine, Stanford, California, USA;
authors.forename: Sunitha V
authors.initials: SV
authors.lastname: Bachawal
authors.affiliation: 2. Department of Health Research and Policy, Stanford University, School of Medicine, Stanford, California, USA.
authors.forename: Lu
authors.initials: L
authors.lastname: Tian
authors.affiliation: 1. Department of Radiology, Molecular Imaging Program at Stanford, Stanford University, School of Medicine, Stanford, California, USA;
authors.forename: Jürgen K
authors.initials: JK
authors.lastname: Willmann
mesh_terms: D000818:Animals; D001943:Breast Neoplasms / Q000473:pathology*; D044584:Carcinoma, Ductal / Q000473:pathology*; D003952:Diagnostic Imaging / Q000379:methods*; D004195:Disease Models, Animal; D005260:Female; D006454:Hemoglobins / Q000032:analysis; D008055:Lipids / Q000032:analysis; D008822:Mice, Transgenic; D010100:Oxygen / Q000032:analysis; D061088:Photoacoustic Techniques / Q000379:methods*; D013057:Spectrum Analysis / Q000379:methods*; D014463:Ultrasonography / Q000379:methods
chemical_list: D006454:Hemoglobins; D008055:Lipids; D010100:Oxygen
keywords: Breast Cancer; Molecular Imaging; Photoacoustic Imaging; Spectroscopic.