skip to main content

Title: Mammographic quantitative image analysis and biologic image composition for breast lesion characterization and classification

Purpose: To investigate whether biologic image composition of mammographic lesions can improve upon existing mammographic quantitative image analysis (QIA) in estimating the probability of malignancy. Methods: The study population consisted of 45 breast lesions imaged with dual-energy mammography prior to breast biopsy with final diagnosis resulting in 10 invasive ductal carcinomas, 5 ductal carcinomain situ, 11 fibroadenomas, and 19 other benign diagnoses. Analysis was threefold: (1) The raw low-energy mammographic images were analyzed with an established in-house QIA method, “QIA alone,” (2) the three-compartment breast (3CB) composition measure—derived from the dual-energy mammography—of water, lipid, and protein thickness were assessed, “3CB alone”, and (3) information from QIA and 3CB was combined, “QIA + 3CB.” Analysis was initiated from radiologist-indicated lesion centers and was otherwise fully automated. Steps of the QIA and 3CB methods were lesion segmentation, characterization, and subsequent classification for malignancy in leave-one-case-out cross-validation. Performance assessment included box plots, Bland–Altman plots, and Receiver Operating Characteristic (ROC) analysis. Results: The area under the ROC curve (AUC) for distinguishing between benign and malignant lesions (invasive and DCIS) was 0.81 (standard error 0.07) for the “QIA alone” method, 0.72 (0.07) for “3CB alone” method, and 0.86 (0.04) for “QIA+3CB” combined. The difference inmore » AUC was 0.043 between “QIA + 3CB” and “QIA alone” but failed to reach statistical significance (95% confidence interval [–0.17 to + 0.26]). Conclusions: In this pilot study analyzing the new 3CB imaging modality, knowledge of the composition of breast lesions and their periphery appeared additive in combination with existing mammographic QIA methods for the distinction between different benign and malignant lesion types.« less
Authors:
; ;  [1] ; ; ; ; ;  [2] ;  [3] ;  [4]
  1. Department of Radiology, University of Chicago, Chicago, Illinois 60637 (United States)
  2. Radiology Department, University of California, San Francisco, California 94143 (United States)
  3. Department of Radiology, University of South Florida, Tampa, Florida 33612 (United States)
  4. Department of Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida 33612 (United States)
Publication Date:
OSTI Identifier:
22250960
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 41; Journal Issue: 3; Other Information: (c) 2014 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
62 RADIOLOGY AND NUCLEAR MEDICINE; BIOMEDICAL RADIOGRAPHY; BIOPSY; CARCINOMAS; CLASSIFICATION; DIAGNOSIS; DIAGRAMS; IMAGE PROCESSING; IMAGES; LIPIDS; MAMMARY GLANDS; PROTEINS; THICKNESS