Three-dimensional static optical coherence elastography based on inverse compositional Gauss-Newton digital volume correlation

High-accuracy optical coherence elastography digital volume correlation methods to measure depth regions with low correlation

The decreasing correlation of optical coherence tomography (OCT) images with depth is an unavoidable problem for the depth measurement of the digital volume correlation (DVC) based optical coherence elastography (OCE) method. We propose an OCE-DVC method to characterize biological tissue deformation in deeper regions. The method proposes a strategy based on reliability layer guided displacement tracking to achieve the OCE-DVC method for the deformation measurement in deep regions of OCT images. Parallel computing solves the computational burden associated with the OCE-DVC method. The layer-by-layer adaptive data reading methods are used to guarantee the parallel computing of high-resolution OCT images. The proposed method shown in this study nearly doubles the depth of quantitative characterization of displacement and strain. At this depth, the standard deviation of displacement and strain measurements is reduced by nearly 78%. Under nonuniform deformation field, OCE-DVC method tracked the displacement with large strain gradient in depth region.

Shear wave imaging the active constitutive parameters of living muscles

Shear wave elastography (SWE) of human skeletal muscles allows for measurement of muscle elastic properties in vivo and has important applications in sports medicine and for the diagnosis and treatment of muscle-related diseases. Existing methods of SWE for skeletal muscles rely on the passive constitutive theory and have so far been unable to provide constitutive parameters describing muscle active behavior. In the present paper, we overcome this limitation by proposing a SWE method for quantitative inference of active constitutive parameters of skeletal muscles in vivo. To this end, we investigate the wave motion in a skeletal muscle described by a constitutive model in which muscle active behavior has been defined by an active parameter. An analytical solution relating shear wave velocities to both passive and active material parameters of muscles is derived, based upon which an inverse approach has been developed to evaluate these parameters. To demonstrate the usefulness of the reported method, in vivo experiments were carried out on 10 volunteers to obtain constitutive parameters, particularly those describing active deformation behaviors of living muscles. The results reveal that the active material parameter of skeletal muscles varies with warm-up, fatigue and rest. STATEMENT OF SIGNIFICANCE: Existing shear wave elastography methods are limited to imaging the passive parameters of muscles. This limitation is addressed in the present paper by developing a method to image the active constitutive parameter of living muscles using shear waves. We derived an analytical solution demonstrating the relationship between constitutive parameters of living muscles and shear waves. Relying on the analytical solution, we proposed an inverse method to infer active parameter of skeletal muscles. We performed in vivo experiments to demonstrate the usefulness of the theory and method; the quantitative variation of the active parameter with muscle states such as warm-up, fatigue and rest has been reported for the first time.

Adaptive denoising of photoacoustic signal and image based on modified Kalman filter

As a burgeoning medical imaging method based on hybrid fusion of light and ultrasound, photoacoustic imaging (PAI) has demonstrated high potential in various biomedical applications, especially in revealing the functional and molecular information to improve diagnostic accuracy. However, stemming from weak amplitude and unavoidable random noise, caused by limited laser power and severe attenuation in deep tissue imaging, PA signals are usually of low signal-to-noise ratio, and reconstructed PA images are of low quality. Despite that conventional Kalman filter (KF) can remove Gaussian noise in time domain, it lacks adaptability in real-time estimation due to its fixed model. Moreover, KF-based denoising algorithm has not been applied in PAI before. In this paper, we propose an adaptive modified KF (MKF) targeted at PAI denoising by tuning system noise matrix Q and measurement noise matrix R in the conventional KF model. Additionally, in order to compensate the signal skewing caused by MKF, we cascade the backward part of Rauch-Tung-Striebel smoother, which utilizes the newly determined Q. Finally, as a supplement, we add a commonly used differential filter to remove in-band reflection artifacts. Experimental results using phantom and ex vivo colorectal tissue are provided to prove validity of the algorithm.

Digital Volume Correlation for large deformations of soft tissues: Pipeline and proof of concept for the application to breast ex vivo deformations

Being able to reposition tumors from prone imaging to supine surgery stances is key for bypassing current invasive marking used for conservative breast surgery. This study aims to demonstrate the feasibility of using Digital Volume Correlation (DVC) to measure the deformation of a female quarter thorax between two different body positioning when subjected to gravity. A segmented multipart mesh (bones, cartilage and tissue) was constructed and a three-step FE-based DVC procedure with heterogeneous elastic regularization was implemented. With the proposed framework, the large displacement field of a hard/soft breast sample was recovered with low registration residuals and small error between the measured and manually determined deformations of phase interfaces. The present study showed the capacity of FE-based DVC to faithfully capture large deformations of hard/soft tissues.

Optical coherence elastography based on inverse compositional Gauss-Newton digital volume correlation with second-order shape function

A digital volume correlation (DVC)-based optical coherence elastography (OCE) method with inverse compositional Gauss-Newton (IC-GN) algorithm and second-order shape function is presented in this study. The systematic measurement errors of displacement and strain from our OCE method were less than 0.2 voxel and 4 × 10^-4, respectively. Second-order shape function could better match complex deformation and decrease speckle rigidity-induced error. Compared to conventional methods, our OCE method could track a larger strain range up to 0.095 and reduce relative error by 30-50%. This OCE method has the potential to become an effective tool in characterising mechanical properties of biological tissue.

A high-accuracy and high-efficiency digital volume correlation method to characterize in-vivo optic nerve head biomechanics from optical coherence tomography

In-vivo optic nerve head (ONH) biomechanics characterization is emerging as a promising way to study eye physiology and pathology. We propose a high-accuracy and high-efficiency digital volume correlation (DVC) method to characterize the in-vivo ONH deformation from optical coherence tomography (OCT) volumes. Using a combination of synthetic tests and analysis of OCTs from monkey ONHs subjected to acutely elevated intraocular pressure, we demonstrate that our proposed methodology overcame several challenges for conventional DVC methods: First, a pre-registration technique was used to remove large ONH rigid body motion in OCT volumes which could lead to analysis failure; second, a modified 3D inverse-compositional Gaussian Newton method was used to ensure sub-voxel accuracy of displacement calculations despite high noise and low image contrast of some OCT volumes; third, a tricubic B-spline interpolation method was applied to improve computational efficiency; fourth, a confidence parameter was introduced to guide the searching path in the displacement calculation; fifth, a confidence-weighted strain calculation method was applied to further improve the accuracy. The proposed DVC method had displacement errors smaller than 0.037 and 0.028 voxels with Gaussian and speckle noises, respectively. The strain errors in the three directions were less than 0.0045 and 0.0018 with Gaussian and speckle noises, respectively. Compared with the conventional DVC method, the proposed method reduced the errors of displacement and strain calculations by up to 70% under large body motions, with 75% lower computation time, while saving about 30% memory. Our study demonstrates the potential of the proposed technique to investigate ONH biomechanics. STATEMENT OF SIGNIFICANCE: The biomechanics of the optic nerve head (ONH) in the posterior pole of the globe play a central role in eye physiology and pathology. The application of digital volume correlation (DVC) to the analysis of optical coherence tomography (OCT) images of the ONH has emerged as a promising way to quantify ONH biomechanics. Conventional DVC methods, however, face several important challenges when analyzing OCT images of the ONH. We introduce a high-accuracy and high-efficiency DVC method to characterize in vivo ONH deformations from OCT volumes. We demonstrate the new method using synthetic tests and actual OCT data from monkey ONHs. The new method also has the potential to be used to study other tissues, as OCT applications continue to expand.

Digital volume correlation using a spherical shell template and cubic element for large rotation measurement

The displacement hypothesis of eight-node cubic elements is selected as the shape function of digital volume correlation (DVC), and the Newton-Raphson iterative method is selected to solve the partial differential equation to measure the displacement field. In order to ensure that the DVC algorithm is usable under the large rotation condition, the spherical shell template matching technique is presented to perform the integer-voxel displacement searching for nodes, which can provide the optimal initial values for the Newton-Raphson iterative method due to the rotation and translation invariance of the spherical shell template. Simulated volume images are used to verify the reliability of the proposed method, and the results show that the proposed DVC method can be used to measure the deformation with an arbitrary rigid body rotation angle. This work is expected to be useful to measure deformation with large rotation of the internal structure of materials.