Abstract
Compression optical coherence elastography (OCE) provides micro-scale imaging of tissue and biomaterial mechanical properties in three dimensions (3-D), showing promise in a range of biomedical applications. Despite substantial progress, most 3-D OCE techniques do not account for the nonlinear elastic response of tissue, resulting in deformation-dependent variations in estimated Young's modulus within an image that reduce reliability and confound comparison both within and between samples. In this work, we overcome these limitations by explicitly accounting for sample deformation and present the first 3-D images of the nonlinear elastic response of tissue, parameterized into Young's modulus and a nonlinear parameter, a capability not previously achieved in OCE or any other elastography modality. To achieve this, we introduce a volumetric, sparsely sampled, phase-based stretch estimation protocol to quantify finite sample deformation and estimate the nonlinear elastic response from between five and nine volumes. We also use an integrated stress sensing layer to minimize temporally varying friction. We validate these new capabilities on phantoms, demonstrating volumetric estimation of the nonlinear elastic response, with mean errors 50% without the integrated layer. Finally, we apply this technique to ex vivo mouse liver, imaging Young's modulus and the nonlinear parameter in healthy and diseased tissue. This method enables more accurate and reliable mechanical characterization of tissue with potential applications in many areas, including tissue engineering, mechanobiology, and disease diagnostics. STATEMENT OF SIGNIFICANCE: Compression optical coherence elastography (OCE) provides micro-scale imaging of tissue mechanical properties in three dimensions (3-D). However, most 3-D OCE techniques do not account for the nonlinear elastic response of tissue, leading to errors in the reported elasticity. In this work, we overcome these limitations and present a technique to volumetrically image the nonlinear elastic response of tissue, a capability not previously achieved in elastography. By parameterizing the nonlinear elastic response into Young's modulus and a nonlinear parameter, our method enables more accurate mechanical characterization and additional contrast for differentiating tissue microstructure. These results establish a foundation for volumetric imaging of nonlinear tissue elasticity using OCE in a range of biomedical applications, including tissue engineering, mechanobiology, and disease diagnostics.