New spatiotemporal features for improved discrimination of benign and malignant lesions in dynamic contrast-enhanced-magnetic resonance imaging of the breast

Gal, Yaniv, Mehnert, Andrew, Bradley, Andrew, Kennedy, Dominic and Crozier, Stuart (2011) New spatiotemporal features for improved discrimination of benign and malignant lesions in dynamic contrast-enhanced-magnetic resonance imaging of the breast. Journal of Computer Assisted Tomography, 35 5: 645-652. doi:10.1097/RCT.0b013e318224234f

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Author Gal, Yaniv
Mehnert, Andrew
Bradley, Andrew
Kennedy, Dominic
Crozier, Stuart
Title New spatiotemporal features for improved discrimination of benign and malignant lesions in dynamic contrast-enhanced-magnetic resonance imaging of the breast
Journal name Journal of Computer Assisted Tomography   Check publisher's open access policy
ISSN 0363-8715
1532-3145
Publication date 2011-09-01
Sub-type Article (original research)
DOI 10.1097/RCT.0b013e318224234f
Volume 35
Issue 5
Start page 645
End page 652
Total pages 8
Place of publication New York, NY, U.S.A.
Publisher Lippincott Williams & Wilkins
Language eng
Formatted abstract
Objectives: The objective of this study was to measure the efficacy of 7 new spatiotemporal features for discriminating between benign and malignant lesions in dynamic contrast-enhanced-magnetic resonance imaging (MRI) of the breast.

Methods: A total of 48 breast lesions from 39 patients were used: 25 malignant and 23 benign. Lesions were acquired using 1.5-T MRI machines in 3 different protocols. Two experiments were performed: (i) selection of the most discriminatory subset of features drawn from the new features and features from the literature and (ii) validation of classification performance of the selected subset of features.

Results: Results of the feature selection experiment show that the subset comprising 2 of the new features is the most useful for automatic classification of suspicious lesions in the breast: (i) gradient correlation of maximum intensity and (ii) mean wash-in rate. Results of the validation experiment show that using these 2 features, unseen data can be classified with an area under the receiver operating characteristic curve of 0.91 ± 0.06.

Conclusions: Results of the experiments suggest that suspicious lesions in dynamic contrast-enhanced-MRI of the breast can be classified, with high accuracy, using only 2 of the proposed spatiotemporal features. The selected features indicate heterogeneity of enhancement and speed of enhancement in a tissue. High values of these indicators are likely to be correlated with malignancy.
Keyword Breast cancer
Magnetic resonance imaging
Automatic classification
Feature selection
Feature extraction
MR-images
Diagnosis
Classification
Pattern
Cancer
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Publication date: September/October 2011.

 
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