title: Predictive performance of BI-RADS magnetic resonance imaging descriptors in the context of suspicious (category 4) findings.
abstract: OBJECTIVE
  To determine the positive predictive value (PPV) and likelihood ratio for magnetic resonance imaging (MRI) characteristics of category 4 lesions, as described in the Breast Imaging Reporting and Data System (BI-RADS(®)) lexicon, as well as to test the predictive performance of the descriptors using multivariate analysis and the area under the curve derived from a receiver operating characteristic (ROC) curve.
  
  
  METHODS
  This was a double-blind review study of 121 suspicious findings from 98 women examined between 2009 and 2013. The terminology was based on the 2013 edition of the BI-RADS.
  
  
  RESULTS
  Of the 121 suspicious findings, 53 (43.8%) were proven to be malignant lesions, with no significant difference between mass and non-mass enhancement (p = 0.846). The PPVs were highest for masses with a spiculated margin (71%) and round shape (63%), whereas segmental distribution achieved a high PPV (80%) for non-mass enhancement. Kinetic analyses performed poorly, except for type 3 curves applied to masses (PPV of 73%). Logistic regression models were significant for both patterns, although the results were better for masses, particularly when kinetic assessments were included (p = 0.015; pseudo R(2) = 0.48; area under the curve = 90%).
  
  
  CONCLUSIONS
  Some BI-RADS MRI descriptors have high PPV and good predictive performance-as demonstrated by ROC curve and multivariate analysis-when applied to BI-RADS category 4 findings. This may allow future stratification of this category.
authors.affiliation: PhD, Physician, Department of Diagnostic Imaging, Clínica de Assistência à Mulher (CAM), Salvador, BA, Brazil.
authors.forename: João Ricardo Maltez
authors.initials: JR
authors.lastname: de Almeida
authors.affiliation: Physician, Department of Diagnostic Imaging, Clínica de Assistência à Mulher (CAM), Salvador, BA, Brazil.
authors.forename: André Boechat
authors.initials: AB
authors.lastname: Gomes
authors.affiliation: Professor, Biomedical Scientist, Escola Bahiana de Medicina e Saúde Pública, Salvador, BA, Brazil.
authors.forename: Thomas Pitangueiras
authors.initials: TP
authors.lastname: Barros
authors.affiliation: Physician, Department of Pathology, Clínica de Assistência à Mulher (CAM), Salvador, BA, Brazil.
authors.forename: Paulo Eduardo
authors.initials: PE
authors.lastname: Fahel
authors.affiliation: PhD, Assistant Professor of Medicine, Escola Bahiana de Medicina e Saúde Pública, Salvador, BA, Brazil.
authors.forename: Mário de Seixas
authors.initials: Mde S
authors.lastname: Rocha
keywords: Breast neoplasms; Likelihood functions; Magnetic resonance imaging; Predictive value of tests