Predrag Bakic
Associate Professor
Classification of galactograms with ramification matrices : Preliminary results
Author
Summary, in English
Rationale and Objectives. The poor specificity of galactography, the imaging modality generally indicated in cases of nipple discharge, has led to a large number of biopsies with negative results. A quantitative scheme for classifying galactographic findings might help reduce the number of such biopsies in the future. As a first step toward that goal, the authors have studied one quantitative method for describing the branching of ducts by using ramification matrices (R matrices), and the correlation of the values of the matrix elements with clinical findings. Materials and Methods. The ductal trees were manually segmented for 25 galactographic views from 15 patients, and corresponding R matrices were calculated. Patients were divided into two groups: those with no reported galactographic findings (NF) and those with reported findings (RF) of ductal ectasia, cysts, or papilloma. In a leave-one-out fashion, the authors evaluated a classification scheme that was based on R-matrix coefficients and used a Bayesian decision rule. The effects of segmentation were tested by successively removing each of the terminal ducts and computing the corresponding matrices of the pruned trees. Results. With use of a single R-matrix element, 92% and 62% of NF and RF cases were correctly classified, respectively (P = .007). With use of two elements, 83% and 77% of NF and RF cases were correctly classified, but this result was not statistically significant (P = .108). In a test of robustness, an analysis of pruned trees yielded an average root-mean- square fractional difference of 9.7% between the elements of the original and the R matrix averaged over all pruned trees. Conclusion. The preliminary analysis indicates that it may be possible to identify cases with reported galactographic findings by using R matrices.
Publishing year
2003-02-01
Language
English
Pages
198-204
Publication/Series
Academic Radiology
Volume
10
Issue
2
Document type
Journal article
Publisher
Elsevier
Topic
- Medical Image Processing
Keywords
- Breast neoplasms, diagnosis
- Breast, ducts
- Galactography
Status
Published
ISBN/ISSN/Other
- ISSN: 1076-6332