Strain-encoded breast MRI in phantom and ex vivo specimens with histological validation: Preliminary results

• Published in: Medical physics (Lancaster) Vol. 39; no. 12; pp. 7710 - 7718
• Main Authors: Haruoni, Ahmed A., Hossain, Jakir, El Khouli, Riham, Matsuda, Kant M., Bluemke, David A., Osman, Nael F., Jacobs, Michael A.
• Format: Journal Article
• Language: English
• Published: United States American Association of Physicists in Medicine 01.12.2012
• Subjects: Algorithms; biomechanics; biomedical MRI; breast MRI; Breast Neoplasms - diagnosis; Breast Neoplasms - physiopathology; Cancer; Clinical applications; compressibility; data acquisition; Data acquisition and logging; data compression; diffusion; Digital computing or data processing equipment or methods, specially adapted for specific applications; elastic constants; Elastic properties; Elasticity Imaging Techniques - instrumentation; Elasticity Imaging Techniques - methods; elastography; Female; Humans; image coding; Image coding, e.g. from bit‐mapped to non bit‐mapped; Image data processing or generation, in general; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; image segmentation; Involving electronic [emr] or nuclear [nmr] magnetic resonance, e.g. magnetic resonance imaging; Magnetic resonance imaging; Magnetic Resonance Physics; Medical image contrast; Medical image noise; medical image processing; Medical imaging; MRI: anatomic, functional, spectral, diffusion; Pattern Recognition, Automated - methods; phantoms; Phantoms, Imaging; Pilot Projects; Reproducibility of Results; Segmentation; SENC; Sensitivity and Specificity; Spatial resolution; strain; Strain measurement; Tissue engineering; Tissues; tumours; Ultrasonography; strain; breast MRI; SENC; elastography; diffusion; cancer
• ISSN: 0094-2405; 2473-4209; 1522-8541; 2473-4209; 0094-2405
• DOI: 10.1118/1.4749963

Purpose: To evaluate the feasibility of using strain-encoded (SENC) breast magnetic resonance images (MRI) for breast cancer detection by examining the compression and relaxation response properties in phantoms andex vivo breast samples. Methods: A tissue phantom was constructed to mimic different sizes of breast masses and tissue stiffness. In addition, five humanex vivo whole breast specimens with and without masses were studied. MR data was acquired on a 3T scanner consisting of T1-weighted, fat suppressed spin echo T2-weighted, and SENC breast images. Mechanical tissue characteristics (strain) of the phantoms and breast tissue samples were measured using SENC imaging in both compression and relaxation modes. The breast tissue specimens were sectioned and stained in the same plane as the MRI for histological evaluation. Results: For the phantom, SENC images showed soft masses with quantitative strain values between 35% and 50%, while harder masses had strain values between 0% and 20%. Combined compression (CMP) and relaxation (REX) breast SENC images separately categorized all masses into three different groups. For breast SENC, the signal intensities betweenex vivo breast mass and breast glandular tissue were significantly different (−7.6 ± 2.6 verses −20.6 ± 5.4 for SENC-CMP, and 4.2 ± 1.5 verses 22.6 ± 5 for SENC-REX, p < 0.05). Conclusions: We have demonstrated that SENC breast MRI can be used to obtain mechanical tissue properties and give quantitative estimates of strain in tumors. This feasibility study provides the basis for future clinical studies.