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2D/3D image fusion of X-ray mammograms with breast MRI: visualizing dynamic contrast enhancement in mammograms

Authors :
Pascal A. T. Baltzer
Matthias Dietzel
Nicole V. Ruiter
Torsten Hopp
Werner A. Kaiser
Source :
International Journal of Computer Assisted Radiology and Surgery. 7:339-348
Publication Year :
2011
Publisher :
Springer Science and Business Media LLC, 2011.

Abstract

Breast cancer is the most common cancer among women. The established screening method to detect breast cancer is X-ray mammography. Additionally, MRI is used for diagnosis in clinical routine. Due to complementary diagnostic information, both modalities are often read in combination. Yet, the correlation is challenging due to different dimensionality of images and different patient positioning. In this paper, we describe a method to fuse X-ray mammograms with DCE-MRI. The present study was conducted to evaluate the feasibility of the approach.For the combination of information from both modalities, the images have to be registered using a compression simulation based on a patient-specific biomechanical model. The registered images can be compared directly. The contrast enhancement in the DCE-MRI volume is evaluated using parametric enhancement maps. A projection image of the contrast enhancement is created. The image fusion combines it with X-ray mammograms for intuitive multimodal diagnosis.The image fusion was evaluated using 11 clinical datasets. For 10 of 11 datasets, a good accuracy of the image registration was achieved. The overlap of contrast-enhanced regions with marked lesions in the mammogram is 61%. Lesions are clearly differentiable from surrounding tissue by the DCE-MRI projection in 10 of 11 cases.The described preliminary results are promising, thus we expect the visualization of quantitative information from dynamic MRI together with mammograms to be beneficial for multimodal diagnosis. Because of the use of clinical standard modalities, no additional image acquisition is needed.

Details

ISSN :
18616429 and 18616410
Volume :
7
Database :
OpenAIRE
Journal :
International Journal of Computer Assisted Radiology and Surgery
Accession number :
edsair.doi.dedup.....c83ad466b25231ab3e5201d77b4931c3
Full Text :
https://doi.org/10.1007/s11548-011-0623-z