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Accurate quantification of forces, applied to, or generated by, tissue, is key to understanding many biomechanical processes, fabricating engineered tissues, and diagnosing diseases. Many techniques have been employed to measure forces; in particular, tactile imaging – developed to spatially map palpation-mimicking forces – has shown potential in improving the diagnosis of cancer on the macro-scale. However, tactile imaging often involves the use of discrete force sensors, such as capacitive or piezoelectric sensors, whose spatial resolution is often limited to 1-2 mm. Our group has previously presented a type of tactile imaging, termed optical palpation, in which the change in thickness of a compliant layer in contact with tissue is measured using optical coherence tomography, and surface forces are extracted, with a micro-scale spatial resolution, using a one-dimensional spring model. We have also recently combined optical palpation with compression optical coherence elastography (OCE) to quantify stiffness. A main limitation of this work, however, is that a one-dimensional spring model is insufficient in describing the deformation of mechanically heterogeneous tissue with uneven boundaries, generating significant inaccuracies in measured forces. Here, we present a computational, finite-element method, which we term computational optical palpation. In this technique, by knowing the non-linear mechanical properties of the layer, and from only the axial component of displacement measured by phase-sensitive OCE, we can estimate, not only the axial forces, but the three-dimensional traction forces at the layer-tissue interface. We use a non-linear, three-dimensional model of deformation, which greatly increases the ability to accurately measure force and stiffness in complex tissues.
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