Abstract

Elastic Modulus Imaging (EMI) is an emerging and exciting suite of medical imaging techniques. The goal of biomechanical imaging is to map the mechanical properties, for example Young's Modulus, of soft tissues. Physicians find elastography very appealing, in as much as it provides a visual and quantitative representation of what they are trained to detect with their fingertips. Furthermore, it has the potential to see smaller, deeper, and softer inclusions than might be detectable by touch. Medical researchers have identified a myriad of potential applications for elastography, including the diagnosis and treatment of deep vein thrombosis, breast, prostate, and liver cancers, local and diffuse coronary disease, fibrosis, edema and cirrhosis. In this contribution, we report preliminary results of our novel image registration strategies to sequences of clinically obtained ultrasound images. Our ""Least-squares Intensity difference Finite Element"" (LIFE) image registration algorithm uses a Gauss-Newton local search strategy to minimize its objective function, and so requires an excellent initialization to converge to the global minimum. The robustness of a novel initialization method in handling clinically data was evaluated here. The longer-term motivation is to evaluate the performance of EMI at diagnosing the severity and degree of radiation induced breast fibrosis, an occasional side-effect of radiation treatment of breast cancer. Image acquisitions were performed as part of a routine ultrasound examination using freehand contact scanning. The ultrasound imaging probe wa guided to gently palpate the breast through a compliant gel pad of known, tissue-equivalent elastic modulus. The ultrasound scanner (Acuson XP10, 7.5MHz) provided radio frequency (RF) frame sequences corresponding to a compression and shear s manuallypalpation cycle. Off-line processing of the RF frames by the LIFE algorithm was used to evaluate the deformation of breast tissue and of the calibration pad. Registration accuracy was monitored via a (RF) frame sequences corresponding to a compression and shear palpation cycle. Off-line processing of the RF frames by the LIFE algorithm was used to evaluate the deformation of breast tissue and of the calibration pad. Registration accuracy was monitored via a ""Registration Quality Indicator (RQI),"" as described below. In about 2/3 of 107 image sequences, the advancing front initialization provided a suficiently precise initial guess that the LIFE algorithm clearly found the global minimum (as assessed by the RQI). The remaining cases were often characterized by large frame-to-frame motions, low signal-to-noise ratio images, and/or out-of-plane deformations. Most sequences that were acceptable had no poor quality frames, but occasionally large frame-to-frame displacements would result in poor matching of isolated frames, any such frames could be identified via the RQI and removed from the measured deformation data. The advancing front initialization method is a suficiently robust initialization strategy to accommodate clinical data. Monitoring registration accuracy via RQI or similar method is critical to identify (un)reliable deformation measurements.

Notes

Poster presented at the Thrust R1A Nonlinear and Dual Wave Probes Conference

Keywords

breast cancer, Elastic Modulus Imaging

Subject Categories

Diagnostic imaging

Disciplines

Biomedical Engineering and Bioengineering

Publisher

Bernard M. Gordon Center for Subsurface Sensing and Imaging Systems (Gordon-CenSSIS)

Publication Date

2006

Rights Holder

Bernard M. Gordon Center for Subsurface Sensing and Imaging Systems (Gordon-CenSSIS)


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