Repeatability of Linear and Nonlinear Elastic Modulus Maps From Repeat Scans in the Breast

• Published in: IEEE transactions on medical imaging Vol. 40; no. 2; pp. 748 - 757
• Main Authors: Gendin, Daniel I., Nayak, Rohit, Wang, Yuqi, Bayat, Mahdi, Fazzio, Robert T., Oberai, Assad A., Hall, Timothy J., Barbone, Paul E., Alizad, Azra, Fatemi, Mostafa
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.02.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Breast; Breast - diagnostic imaging; Breast cancer; Compression; Cross correlation; Data acquisition; Elastic deformation; Elastic Modulus; elastic nonlinearity; Elasticity; Elasticity Imaging Techniques; Elastography; Evaluation; Humans; Image acquisition; Imaging; inverse problem; Inverse problems; Iterative methods; Lesions; Mechanical properties; Modulus of elasticity; Nonlinear systems; Nonlinearity; Optimization; Parameter modification; Phantoms, Imaging; quantitative; Reproducibility; Soft tissues; Strain; Tissues; Tracking; Ultrasonic imaging
• ISSN: 0278-0062; 1558-254X; 1558-254X
• DOI: 10.1109/TMI.2020.3036032

Compression elastography allows the precise measurement of large deformations of soft tissue in vivo. From an image sequence showing tissue undergoing large deformation, an inverse problem for both the linear and nonlinear elastic moduli distributions can be solved. As part of a larger clinical study to evaluate nonlinear elastic modulus maps (NEMs) in breast cancer, we evaluate the repeatability of linear and nonlinear modulus maps from repeat measurements. Within the cohort of subjects scanned to date, 20 had repeat scans. These repeated scans were processed to evaluate NEM repeatability. In vivo data were acquired by a custom-built, digitally controlled, uniaxial compression device with force feedback from the pressure-plate. RF-data were acquired using plane-wave imaging, at a frame-rate of 200 Hz, with a ramp-and-hold compressive force of 8N, applied at 8N/sec. A 2D block-matching algorithm was used to obtain sample-level displacement fields which were then tracked at subsample resolution using 2D cross correlation. Linear and nonlinear elasticity parameters in a modified Veronda-Westmann model of tissue elasticity were estimated using an iterative optimization method. For the repeated scans, B-mode images, strain images, and linear and nonlinear elastic modulus maps are measured and compared. Results indicate that when images are acquired in the same region of tissue and sufficiently high strain is used to recover nonlinearity parameters, then the reconstructed modulus maps are consistent.