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Modeling breast biomechanics for multi‐modal image analysis—successes and challenges

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Biomechanical modeling of the breast is a burgeoning research field that has potential uses across a wide range of healthcare applications. This review describes recent developments regarding multi‐modal breast image analysis, and outlines some of the key challenges that researchers face in introducing the models into the clinical arena. Deformable breast models have demonstrated capabilities across a wide range of breast cancer diagnoses and treatments. Specific applications include magnetic resonance (MR) image guided surgery, registration of x‐ray and MR images, and breast reduction/augmentation surgery planning. Challenges lie in improving the fidelity of these models, which are presently simplistic and use many unverified parameters. Specific challenges include characterization of individual‐specific mechanical properties of breast tissues, precise representation of loading and boundary constraints during different clinical procedures, and validation of modeling techniques used to represent key mechanical aspects such as the suspensory Cooper's ligaments. Scientists must also work towards translating their research tools into the clinical setting by developing efficient tools with user‐friendly interactivity. Widespread adoption of such techniques has the potential to significantly reduce the numbers of misdiagnosed breast cancers and enhance surgical planning for patient treatment. Copyright © 2009 John Wiley & Sons, Inc.

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Figure 1.

Anatomy of the breast (Adapted and reprinted with permission from Dronkers et al. Practice of Mammography. Copyright 2002 Thieme Medical Publishers Inc.).

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Figure 2.

Left: MR image slice of the breast in the prone orientation. Right: A geometric model fitted to the prone MR image set using hexahedral finite elements with cubic-Hermite interpolation functions.

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Figure 3.

Estimating the unloaded state of the breast. (a) MR image slice of the breast of a volunteer in the prone gravity-loaded state. (b) Prone MR image slice embedded in a finite element model that was fitted to the 3D prone MR dataset. (c) Predicted unloaded shape of the breast with prone image warped to unloaded shape. (d) Synthetic MR image slice of the predicted unloaded configuration of the breast acquired using the biomechanical model. (e) MR image slice of the neutrally buoyant breast immersed in water (represented by the white block in the image). An indication of tissue displacement between this neutral buoyancy image and prone gravity-loaded image in (a) is given by the distance between nipple and pectoral muscle surface.

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