title: A computerized global MR image feature analysis scheme to assist diagnosis of breast cancer: a preliminary assessment.
abstract: OBJECTIVE
  To develop a new computer-aided detection scheme to compute a global kinetic image feature from the dynamic contrast enhanced breast magnetic resonance imaging (DCE-MRI) and test the feasibility of using the computerized results for assisting classification between the DCE-MRI examinations associated with malignant and benign tumors.
  
  
  METHODS
  The scheme registers sequential images acquired from each DCE-MRI examination, segments breast areas on all images, searches for a fraction of voxels that have higher contrast enhancement values and computes an average contrast enhancement value of selected voxels. Combination of the maximum contrast enhancement values computed from two post-contrast series in one of two breasts is applied to predict the likelihood of the examination being positive for breast cancer. The scheme performance was evaluated when applying to a retrospectively collected database including 80 malignant and 50 benign cases.
  
  
  RESULTS
  In each of 91% of malignant cases and 66% of benign cases, the average contrast enhancement value computed from the top 0.43% of voxels is higher in the breast depicted suspicious lesions as compared to another negative (lesion-free) breast. In classifying between malignant and benign cases, using the computed image feature achieved an area under a receiver operating characteristic curve of 0.839 with 95% confidence interval of [0.762, 0.898].
  
  
  CONCLUSIONS
  We demonstrated that the global contrast enhancement feature of DCE-MRI can be relatively easily and robustly computed without accurate breast tumor detection and segmentation. This global feature provides supplementary information and a higher discriminatory power in assisting diagnosis of breast cancer.
authors.affiliation: College of Life Information Science and Instrument Engineering, Hangzhou Dianzi University, Hangzhou, 310018, China.
authors.forename: Qian
authors.initials: Q
authors.lastname: Yang
authors.affiliation: College of Life Information Science and Instrument Engineering, Hangzhou Dianzi University, Hangzhou, 310018, China. Electronic address: lilh@hdu.edu.cn.
authors.forename: Lihua
authors.initials: L
authors.lastname: Li
authors.affiliation: Zhejiang Cancer Hospital, Hangzhou, 310010, China.
authors.forename: Juan
authors.initials: J
authors.lastname: Zhang
authors.affiliation: Zhejiang Cancer Hospital, Hangzhou, 310010, China.
authors.forename: Guoliang
authors.initials: G
authors.lastname: Shao
authors.affiliation: College of Life Information Science and Instrument Engineering, Hangzhou Dianzi University, Hangzhou, 310018, China; School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK 73019, USA.
authors.forename: Bin
authors.initials: B
authors.lastname: Zheng
mesh_terms: D000328:Adult; D000465:Algorithms; D001943:Breast Neoplasms / Q000473:pathology*; D003287:Contrast Media; D005240:Feasibility Studies; D005260:Female; D019786:Gadolinium DTPA; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D010865:Pilot Projects; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D003287:Contrast Media; D019786:Gadolinium DTPA
keywords: Breast cancer; Cancer image biomarker; Computer-aided diagnosis (CAD); Dynamic contrast enhanced breast magnetic resonance imaging (DCE-MRI)
references.citation: Invest Radiol. 2005 Jun;40(6):349-54
references.pmid: 15905721
references.citation: Med Phys. 2012 Jan;39(1):353-66
references.pmid: 22225305
references.citation: Acad Radiol. 2008 Dec;15(12):1513-25
references.pmid: 19000868
references.citation: Med Phys. 2004 May;31(5):1076-82
references.pmid: 15191295
references.citation: Magn Reson Med. 2007 Sep;58(3):562-71
references.pmid: 17763361
references.citation: Radiology. 2007 Jul;244(1):94-103
references.pmid: 17507720
references.citation: Acad Radiol. 2007 Feb;14(2):151-61
references.pmid: 17236988
references.citation: Magn Reson Med. 2003 Jul;50(1):92-8
references.pmid: 12815683
references.citation: Br J Radiol. 2000 Aug;73(872):806-18
references.pmid: 11026854
references.citation: Ann Intern Med. 2008 May 6;148(9):671-9
references.pmid: 18458280
references.citation: Ann Fam Med. 2013 Mar-Apr;11(2):106-15
references.pmid: 23508596
references.citation: Radiology. 2011 Jul;260(1):50-60
references.pmid: 21493794
references.citation: Invest Radiol. 2008 Apr;43(4):236-42
references.pmid: 18340247
references.citation: Eur Radiol. 2011 Nov;21(11):2261-7
references.pmid: 21688006
references.citation: Lancet. 2007 Aug 11;370(9586):485-92
references.pmid: 17693177
references.citation: J Magn Reson Imaging. 2007 Jan;25(1):89-95
references.pmid: 17154399
references.citation: Phys Med Biol. 2010 Oct 7;55(19):N473-85
references.pmid: 20858914
references.citation: Radiology. 2010 Mar;254(3):680-90
references.pmid: 20123903
references.citation: Invest Radiol. 2009 Sep;44(9):553-8
references.pmid: 19652611
references.citation: J Comput Assist Tomogr. 2010 May-Jun;34(3):456-64
references.pmid: 20498554