title: Potential of computer-aided diagnosis of high spectral and spatial resolution (HiSS) MRI in the classification of breast lesions.
abstract: OBJECTIVE
  To compare the performance of computer-aided diagnosis (CADx) analysis of precontrast high spectral and spatial resolution (HiSS) MRI to that of clinical dynamic contrast-enhanced MRI (DCE-MRI) in the diagnostic classification of breast lesions.
  
  
  METHODS
  Thirty-four malignant and seven benign lesions were scanned using two-dimensional (2D) HiSS and clinical 4D DCE-MRI protocols. Lesions were automatically segmented. Morphological features were calculated for HiSS, whereas both morphological and kinetic features were calculated for DCE-MRI. After stepwise feature selection, Bayesian artificial neural networks merged selected features, and receiver operating characteristic (ROC) analysis evaluated the performance with leave-one-lesion-out validation.
  
  
  RESULTS
  AUC (area under the ROC curve) values of 0.92 ± 0.06 and 0.90 ± 0.05 were obtained using CADx on HiSS and DCE-MRI, respectively, in the task of classifying benign and malignant lesions. While we failed to show that the higher HiSS performance was significantly better than DCE-MRI, noninferiority testing confirmed that HiSS was not worse than DCE-MRI.
  
  
  CONCLUSIONS
  CADx of HiSS (without contrast) performed similarly to CADx on clinical DCE-MRI; thus, computerized analysis of HiSS may provide sufficient information for diagnostic classification. The results are clinically important for patients in whom contrast agent is contra-indicated. Even in the limited acquisition mode of 2D single slice HiSS, by using quantitative image analysis to extract characteristics from the HiSS images, similar performance levels were obtained as compared with those from current clinical 4D DCE-MRI. As HiSS acquisitions become possible in 3D, CADx methods can also be applied. Because HiSS and DCE-MRI are based on different contrast mechanisms, the use of the two protocols in combination may increase diagnostic accuracy.
authors.affiliation: The University of Chicago, Department of Radiology, Chicago, Illinois, USA.
authors.forename: Neha
authors.initials: N
authors.lastname: Bhooshan
authors.forename: Maryellen
authors.initials: M
authors.lastname: Giger
authors.forename: Milica
authors.initials: M
authors.lastname: Medved
authors.forename: Hui
authors.initials: H
authors.lastname: Li
authors.forename: Abbie
authors.initials: A
authors.lastname: Wood
authors.forename: Yading
authors.initials: Y
authors.lastname: Yuan
authors.forename: Li
authors.initials: L
authors.lastname: Lan
authors.forename: Angelica
authors.initials: A
authors.lastname: Marquez
authors.forename: Greg
authors.initials: G
authors.lastname: Karczmar
authors.forename: Gillian
authors.initials: G
authors.lastname: Newstead
mesh_terms: D000465:Algorithms; D019540:Area Under Curve; D001499:Bayes Theorem; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000473:pathology; D003287:Contrast Media / Q000737:chemistry; D003936:Diagnosis, Computer-Assisted; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007091:Image Processing, Computer-Assisted; D008099:Liver / Q000187:drug effects; D008279:Magnetic Resonance Imaging; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated; D010865:Pilot Projects; D012372:ROC Curve; D015203:Reproducibility of Results
chemical_list: D003287:Contrast Media
keywords: breast cancer, dynamic contrast enhanced MRI (DCE-MRI); computer-aided diagnosis (CADx); contrast-agent induced nephrotoxicity; high spectral and spatial resolution (HiSS) MRI
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