Cerebral edema is a serious complication of ischemic cerebrovascular disease and mannitol is a commonly used dehydrating agent for relieving cerebral edema. However, the edema state and surrounding vascular perfusion level during mannitol treatment remains unclear, which affects the clinical application of the medicine. In this paper, we demonstrated the role of swept-source optical coherence tomography (OCT) in the evaluation of mannitol efficacy using mouse models. The OCT-based angiography and attenuation imaging technology were used to obtain the cerebral vascular perfusion level and cerebral edema state at different times. Vascular parameters and edema parameters were quantified and compared. Experimental results show that mannitol can significantly reduce the water content in the central region of edema, effectively inhibiting the rapid growth of the edema area, and restoring cerebral blood flow. On average, the edema area decreased by 33% after 2 h, and the vascular perfusion density increased by 12% after 5 h. This work helps to provide a valuable theoretical basis and research ideas for the clinical treatment of cerebral edema.

Optical coherence tomography (OCT) attenuation imaging is a technique that uses the optical attenuation coefficient (OAC) to distinguish the types or pathological states of tissues and has been increasingly used in basic research and clinical diagnosis. With the increasing application of swept-source OCT, scholars are increasingly inclined to explore deep tissues. Unfortunately, the accuracy of OAC calculation when exploring deep tissues has yet to be improved. Existing methods generally have the following problems: overestimation error, underestimation error, severe fluctuation, or stripe artifacts in the OAC calculation of the OCT tail signal. The main reason for this is that the influence of the noise floor on the OCT weak signal at the tail-end is not paid enough attention. The noise floor can change the attenuation pattern of the OCT tail signal, which can lead to severe errors in the OAC. In this paper, we proposed a Kalman filter-based OAC optimal algorithm to solve this problem. This algorithm can not only eliminate the influence of the noise floor, but can also effectively protect the weak signal at the tail-end from being lost. The OAC of deep tissues can be calculated accurately and stably. Numerical simulation, phantom, and in vivo experiments were tested to verify the algorithm’s effectiveness in this paper. This technology is expected to play an essential role in disease diagnosis and in the evaluation of the effectiveness of treatment methods.

The virtual lens model has important value in ophthalmic research, clinical diagnosis, and treatment. However, the establishment of personalized lens models and the verification of accommodation accuracy have not been paid much attention. We proposed a personalized lens model establishment and the accommodation accuracy evaluation method based on sweep-source optical coherence tomography (SS-OCT). Firstly, SS-OCT is used to obtain a single lens image in the maximum accommodation state. After refraction correction, boundary detection, and curve fitting, the central curvature radius, thickness, and lens nucleus contour of the anterior and posterior surfaces of the lens were obtained. Secondly, a personalized finite element model improved from Burd’s model was established using these individual parameters, and the adaptation process of the lens model was simulated by pulling the suspensory ligament. Finally, the shape and refractive power changes of the real human lens under different accommodation stimuli were collected and compared with the accommodation process of the finite element model. The results show that the accommodation process of the finite element model is highly consistent with that of the real lens. From the un-accommodation state to the maximum-accommodation state, the difference rate of all geometric and refractive parameters between the two is less than 5%. Thus, the personalized lens finite element model obtained by the calibration and correction of the existing model can accurately simulate the regulation process of a specific human lens. This work helps to provide a valuable theoretical basis and research ideas for the study of clinical diagnosis and treatment of related diseases.

We propose a high-speed all-optic dual-modal system that integrates spectral-domain optical coherence tomography and photoacoustic microscopy (PAM). A [Formula: see text] coupler-based interferometer is used to remotely detect the surface vibration caused by photoacoustic (PA) waves. Three outputs of the interferometer are acquired simultaneously with a multi-channel data acquisition card. One channel data with the highest PA signal detection sensitivity is selected for sensitivity compensation. Experiment on the phantom demonstrates that the proposed method can successfully compensate for the loss of intensity caused by sensitivity variation. The imaging speed of the PAM is improved compared to our previous system. The total time to image a sample with [Formula: see text] pixels is [Formula: see text][Formula: see text]s. Using the proposed system, the microvasculature in the mouse auricle is visualized and the blood flow state is accessed.