Is photoacoustic imaging clinically safe: evaluation of possible thermal damage due to laser-tissue interaction

Photoacoustic imaging is a breakthrough imaging modality that combines the spatial resolution of ultrasound imaging with the contrast of optical imaging. This imaging technique is being pushed towards clinical acceptance for many applications, such as noninvasive diagnosis and management of a multitude of neoplastic lesions. However, a rigorous evaluation of the tissue thermal response to the laser illumination is required prior to the clinical translation. In this study, we assessed the temperature rise profile and microstructural damage of the skin due to the laser-tissue interaction using in-vivo mouse models. We compared the effect of two different laser frequencies (10 Hz and 30 Hz) on the skin and studied if the use of a cooling method could be clinically useful in preventing tissue necrosis. Two biopsies were taken from each mouse 48 hours after laser exposure; one from the skin directly exposed to the laser and one from neighboring healthy tissue. When the lower frequency laser was used, no necrosis was found on histologic analysis. However, when the higher frequency laser was used, necrosis was noted in the epidermis, dermal collagen, and hair follicles at the site of laser exposure. Use of the cooling method with the higher frequency laser led to no tissue necrosis. Overall, it appears that photoacoustic imaging is likely safe when lower frequency lasers are used, and the implementation of the cooling method seems to mitigate necrosis when the use of a higher frequency laser is warranted. This opens up exciting new possibilities for a noninvasive way of diagnosing and evaluating a variety of lesions, including malignant tumors. However, some further studies are needed before photoacoustic imaging can be clinically used in human subjects

The power of light and sound: optoacoustic skin imaging for diabetes progression monitoring

Abstract Diabetes progression is marked by damage to vascular and neural networks. Raster-scan optoacoustic mesoscopy holds the potential to measure extent of diabetes progression by analyzing changes in skin vasculature

Couplants in Acoustic Biosensing Systems

Acoustic biosensors are widely used in physical, chemical, and biosensing applications. One of the major concerns in acoustic biosensing is the delicacy of the medium through which acoustic waves propagate and reach acoustic sensors. Even a small airgap diminishes acoustic signal strengths due to high acoustic impedance mismatch. Therefore, the presence of a coupling medium to create a pathway for an efficient propagation of acoustic waves is essential. Here, we have reviewed the chemical, physical, and acoustic characteristics of various coupling material (liquid, gel-based, semi-dry, and dry) and present a guide to determine a suitable application-specific coupling medium

Skin Imaging Using Optical Coherence Tomography and Photoacoustic Imaging: A Mini-Review

This article provides an overview of the progress made in skin imaging using two emerging imaging modalities, optical coherence tomography (OCT) and photoacoustic imaging (PAI). Over recent years, these technologies have significantly advanced our understanding of skin structure and function, offering non-invasive and high-resolution insights previously unattainable. The review begins by briefly describing the fundamental principles of how OCT and PAI capture images. It then explores the evolving applications of OCT in dermatology, ranging from diagnosing skin disorders to monitoring treatment responses. This article continues by briefly describing the capabilities of PAI imaging, and how PAI has been used for melanoma and non-melanoma skin cancer detection and characterization, vascular imaging, and more. The third section describes the development of multimodal skin imaging systems that include OCT, PAI, or both modes. A comparative analysis between OCT and PAI is presented, elucidating their respective strengths, limitations, and synergies in the context of skin imaging

Tutorial on Development of 3D Vasculature Digital Phantoms for Evaluation of Photoacoustic Image Reconstruction Algorithms

A synthetic phantom model is typically utilized to evaluate the initial performance of a photoacoustic image reconstruction algorithm. The characteristics of the phantom model (structural, optical, and acoustic) are required to be very similar to those of the biological tissue. Typically, generic two-dimensional shapes are used as imaging targets to calibrate reconstruction algorithms. However, these structures are not representative of complex biological tissue, and therefore the artifacts that exist in reconstructed images of biological tissue vasculature are ignored. Real data from 3D MRI/CT volumes can be extrapolated to create high-quality phantom models; however, these sometimes involve complicated pre-processing and mostly are challenging, due to the inaccessibility of these datasets or the requirement for approval to utilize the data. Therefore, it is necessary to develop a 3D tissue-mimicking phantom model consisting of different compartments with characteristics that can be easily modified. In this tutorial, we present an optimized development process of a generic 3D complex digital vasculature phantom model in Blender. The proposed workflow is such that an accurate and easily editable digital phantom can be developed. Other workflows for creating the same phantom will take much longer to set up and require more time to edit. We have made a few examples of editable 3D phantom models, which are publicly available to test and modify

Tutorial on Development of 3D Vasculature Digital Phantoms for Evaluation of Photoacoustic Image Reconstruction Algorithms

A synthetic phantom model is typically utilized to evaluate the initial performance of a photoacoustic image reconstruction algorithm. The characteristics of the phantom model (structural, optical, and acoustic) are required to be very similar to those of the biological tissue. Typically, generic two-dimensional shapes are used as imaging targets to calibrate reconstruction algorithms. However, these structures are not representative of complex biological tissue, and therefore the artifacts that exist in reconstructed images of biological tissue vasculature are ignored. Real data from 3D MRI/CT volumes can be extrapolated to create high-quality phantom models; however, these sometimes involve complicated pre-processing and mostly are challenging, due to the inaccessibility of these datasets or the requirement for approval to utilize the data. Therefore, it is necessary to develop a 3D tissue-mimicking phantom model consisting of different compartments with characteristics that can be easily modified. In this tutorial, we present an optimized development process of a generic 3D complex digital vasculature phantom model in Blender. The proposed workflow is such that an accurate and easily editable digital phantom can be developed. Other workflows for creating the same phantom will take much longer to set up and require more time to edit. We have made a few examples of editable 3D phantom models, which are publicly available to test and modify