Literature DB >> 16794155

A new automated software system to evaluate breast MR examinations: improved specificity without decreased sensitivity.

Constance D Lehman1, Sue Peacock, Wendy B DeMartini, Xiaoming Chen.   

Abstract

OBJECTIVE: We sought to compare the accuracy of breast MRI interpretations with and without a new software application (CADstream) that provides automated evaluations of breast MR examinations.
MATERIALS AND METHODS: Thirty-three consecutive lesions seen only on MRI (nine malignant, 24 benign) were evaluated with and without the automated software system. Automated analyses of kinetic enhancement for each lesion were recorded at 50%, 80%, and 100% enhancement thresholds. Computer-assisted analyses included presence or absence of "significant" enhancement and classification of enhancement patterns into percent volumes of washout, plateau, and persistent enhancement. Fisher's exact tests were performed to compare the likelihood of malignancy based on the presence of software-defined significant enhancement at the three thresholds. Enhancement profiles of malignant versus benign lesions were compared using the Student's t test.
RESULTS: All malignant lesions showed significant enhancement at all thresholds. Compared with the unassisted interpretations, the computer-assisted analyses yielded false-positive rates that were reduced by 25% at a 50% threshold (not significant [NS]), 33% at an 80% threshold (p = 0.05), and 50% at a 100% threshold for enhancement (p < 0.01). There were no significant differences between enhancement profiles of benign and malignant lesions, with all lesions showing a wide range of washout, plateau, and persistent patterns of enhancement.
CONCLUSION: New automated software applied to interpret breast MR examinations accurately showed significant enhancement in all the malignant lesions while depicting 12 of 24 benign lesions as showing insignificant enhancement. If these results are validated by a larger study, the number of unnecessary biopsies of MR lesions could be reduced without a concomitant decrease in cancer detection.

Entities:  

Mesh:

Substances:

Year:  2006        PMID: 16794155     DOI: 10.2214/AJR.05.0269

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  27 in total

Review 1.  Principles and methods for automatic and semi-automatic tissue segmentation in MRI data.

Authors:  Lei Wang; Teodora Chitiboi; Hans Meine; Matthias Günther; Horst K Hahn
Journal:  MAGMA       Date:  2016-01-11       Impact factor: 2.310

2.  Dynamic breast MR imaging: is parametric mapping superior to image subtraction in lesion detection?

Authors:  Kathinka D Kurz; Hans-Jörg Wittsack; Reinhart Willers; Dirk Blondin; Ulrich Mödder; Andreas Saleh
Journal:  Eur Radiol       Date:  2007-06-16       Impact factor: 5.315

3.  Computer-aided segmentation system for breast MRI tumour using modified automatic seeded region growing (BMRI-MASRG).

Authors:  Ali Qusay Al-Faris; Umi Kalthum Ngah; Nor Ashidi Mat Isa; Ibrahim Lutfi Shuaib
Journal:  J Digit Imaging       Date:  2014-02       Impact factor: 4.056

4.  A Java-based fMRI processing pipeline evaluation system for assessment of univariate general linear model and multivariate canonical variate analysis-based pipelines.

Authors:  Jing Zhang; Lichen Liang; Jon R Anderson; Lael Gatewood; David A Rottenberg; Stephen C Strother
Journal:  Neuroinformatics       Date:  2008-05-28

5.  MRI patterns of invasive lobular cancer: T1 and T2 features.

Authors:  G Levrini; C A Mori; R Vacondio; G Borasi; F Nicoli
Journal:  Radiol Med       Date:  2008-09-18       Impact factor: 3.469

6.  Current Status and New Developments in Breast MRI.

Authors:  Katja C Siegmann; Bernhard Krämer; Claus Claussen
Journal:  Breast Care (Basel)       Date:  2011-04-29       Impact factor: 2.860

7.  Size assessment of breast lesions by means of a computer-aided detection (CAD) system for magnetic resonance mammography.

Authors:  G Levrini; R Sghedoni; C Mori; A Botti; R Vacondio; A Nitrosi; M Iori; F Nicoli
Journal:  Radiol Med       Date:  2011-03-19       Impact factor: 3.469

8.  Evaluation of Kinetic Entropy of Breast Masses Initially Found on MRI using Whole-lesion Curve Distribution Data: Comparison with the Standard Kinetic Analysis.

Authors:  Akiko Shimauchi; Hiroyuki Abe; David V Schacht; Jian Yulei; Federico D Pineda; Sanaz A Jansen; Rajiv Ganesh; Gillian M Newstead
Journal:  Eur Radiol       Date:  2015-02-20       Impact factor: 5.315

9.  Comparing performance of the CADstream and the DynaCAD breast MRI CAD systems : CADstream vs. DynaCAD in breast MRI.

Authors:  Joann Pan; Basak E Dogan; Selin Carkaci; Lumarie Santiago; Elsa Arribas; Scott B Cantor; Wei Wei; R Jason Stafford; Gary J Whitman
Journal:  J Digit Imaging       Date:  2013-10       Impact factor: 4.056

10.  Effect of the enhancement threshold on the computer-aided detection of breast cancer using MRI.

Authors:  Jacob E D Levman; Petrina Causer; Ellen Warner; Anne L Martel
Journal:  Acad Radiol       Date:  2009-06-09       Impact factor: 3.173

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.