Related Experiment Video
Updated: Sep 2, 2026
Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Independent component analysis for the examination of dynamic contrast-enhanced breast magnetic resonance imaging
Seung-Schik Yoo1, Byung Gil Choi, Ji-Youn Han
1Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA. yoo@bwh.harvard.edu
Rationale And Objective:
An application of independent component analysis (ICA) is reported for the detection and characterization of breast lesions in dynamic contrast-enhanced MRI. The ICA technique, which uses a novel statistical algorithm to separate mixed signal sources of unknown nature, enables the extraction of spatial and temporal features of dynamic MRI data.
Materials And Methods:
Six patients with confirmed lesion diagnosis (three with malignancy and three with benign condition) participated in this study. T1-weighted MRI covering both breast volumes was dynamically acquired in every 90 seconds after the bolus injection of contrast media using three-dimensional fast low-angle shot sequence (3-D FLASH).
Results:
With the application of the ICA, differential signal responses were delineated from benign and malignant lesions, and areas with high temporal correlations with the extracted signal components were selectively visualized.
Conclusions:
The results suggest that ICA allowed for an identification of lesion morphology and lesion-specific dynamic enhancement patterns.
