Fast raster-scan optoacoustic mesoscopy enables assessment of human melanoma microvasculature in vivo

High-frequency photoacoustic and ultrasound imaging for skin evaluation: Pilot study for the assessment of a chemical burn

Skin architecture and its underlying vascular structure could be used to assess the health status of skin. A non-invasive, high resolution and deep imaging modality able to visualize skin subcutaneous layers and vasculature structures could be useful for determining and characterizing skin disease and trauma. In this study, a multispectral high-frequency, linear array-based photoacoustic/ultrasound (PAUS) probe is developed and implemented for the imaging of rat skin in vivo. The study seeks to demonstrate the probe capabilities for visualizing the skin and its underlying structures, and for monitoring changes in skin structure and composition during a 5-day course of a chemical burn. We analayze composition of lipids, water, oxy-hemoglobin, and deoxy-hemoglobin (for determination of oxygen saturation) in the skin tissue. The study successfully demonstrated the high-frequency PAUS imaging probe was able to provide 3D images of the rat skin architecture, underlying vasculature structures, and oxygen saturation, water, lipids and total hemoglobin.

Machine Learning Analysis of Human Skin by Optoacoustic Mesoscopy for Automated Extraction of Psoriasis and Aging Biomarkers

Ultra-wideband raster-scan optoacoustic mesoscopy (RSOM) is a novel modality that has demonstrated unprecedented ability to visualize epidermal and dermal structures in-vivo. However, an automatic and quantitative analysis of three-dimensional RSOM datasets remains unexplored. In this work we present our framework: Deep Learning RSOM Analysis Pipeline (DeepRAP), to analyze and quantify morphological skin features recorded by RSOM and extract imaging biomarkers for disease characterization. DeepRAP uses a multi-network segmentation strategy based on convolutional neural networks with transfer learning. This strategy enabled the automatic recognition of skin layers and subsequent segmentation of dermal microvasculature with an accuracy equivalent to human assessment. DeepRAP was validated against manual segmentation on 25 psoriasis patients under treatment and our biomarker extraction was shown to characterize disease severity and progression well with a strong correlation to physician evaluation and histology. In a unique validation experiment, we applied DeepRAP in a time series sequence of occlusion-induced hyperemia from 10 healthy volunteers. We observe how the biomarkers decrease and recover during the occlusion and release process, demonstrating accurate performance and reproducibility of DeepRAP. Furthermore, we analyzed a cohort of 75 volunteers and defined a relationship between aging and microvascular features in-vivo. More precisely, this study revealed that fine microvascular features in the dermal layer have the strongest correlation to age. The ability of our newly developed framework to enable the rapid study of human skin morphology and microvasculature in-vivo promises to replace biopsy studies, increasing the translational potential of RSOM.

Correction of high-rate motion for photoacoustic microscopy by orthogonal cross-correlation

Photoacoustic imaging is a promising technology for in vivo imaging. However, its imaging performance can be hampered by motion artifacts, especially when dealing with high-rate motion. In this paper, we propose an orthogonal motion correction method that utilizes cross-correlation along orthogonal scan directions to extract accurate motion displacements from the photoacoustic data. The extracted displacements are then applied to remove artifacts and compensate for motion-induced distortions. Phantom experiments demonstrate that the proposed method can extract the motion information and the structural similarity index measurement after correction is increased by 26.5% and 11.2% compared to no correction and the previous correction method. Then the effectiveness of our method is evaluated in vivo imaging of a mouse brain. Our method shows a stable and effective performance under high-rate motion. The high accuracy of the motion correction method makes it valuable in improving the accuracy of photoacoustic imaging.

Metabolic and molecular imaging in inflammatory arthritis

It is known that metabolic shifts and tissue remodelling precede the development of visible inflammation and structural organ damage in inflammatory rheumatic diseases such as the inflammatory arthritides. As such, visualising and measuring metabolic tissue activity could be useful to identify biomarkers of disease activity already in a very early phase. Recent advances in imaging have led to the development of so-called 'metabolic imaging' tools that can detect these changes in metabolism in an increasingly accurate manner and non-invasively.Nuclear imaging techniques such as 18F-D-glucose and fibroblast activation protein inhibitor-labelled positron emission tomography are increasingly used and have yielded impressing results in the visualisation (including whole-body staging) of inflammatory changes in both early and established arthritis. Furthermore, optical imaging-based bedside techniques such as multispectral optoacoustic tomography and fluorescence optical imaging are advancing our understanding of arthritis by identifying intra-articular metabolic changes that correlate with the onset of inflammation with high precision and without the need of ionising radiation.Metabolic imaging holds great potential for improving the management of patients with inflammatory arthritis by contributing to early disease interception and improving diagnostic accuracy, thereby paving the way for a more personalised approach to therapy strategies including preventive strategies. In this narrative review, we discuss state-of-the-art metabolic imaging methods used in the assessment of arthritis and inflammation, and we advocate for more extensive research endeavours to elucidate their full field of application in rheumatology.

Photoacoustic imaging for cutaneous melanoma assessment: a comprehensive review

Significance

Cutaneous melanoma (CM) has a high morbidity and mortality rate, but it can be cured if the primary lesion is detected and treated at an early stage. Imaging techniques such as photoacoustic (PA) imaging (PAI) have been studied and implemented to aid in the detection and diagnosis of CM.

Aim

Provide an overview of different PAI systems and applications for the study of CM, including the determination of tumor depth/thickness, cancer-related angiogenesis, metastases to lymph nodes, circulating tumor cells (CTCs), virtual histology, and studies using exogenous contrast agents.

Approach

A systematic review and classification of different PAI configurations was conducted based on their specific applications for melanoma detection. This review encompasses animal and preclinical studies, offering insights into the future potential of PAI in melanoma diagnosis in the clinic.

Results

PAI holds great clinical potential as a noninvasive technique for melanoma detection and disease management. PA microscopy has predominantly been used to image and study angiogenesis surrounding tumors and provide information on tumor characteristics. Additionally, PA tomography, with its increased penetration depth, has demonstrated its ability to assess melanoma thickness. Both modalities have shown promise in detecting metastases to lymph nodes and CTCs, and an all-optical implementation has been developed to perform virtual histology analyses. Animal and human studies have successfully shown the capability of PAI to detect, visualize, classify, and stage CM.

Conclusions

PAI is a promising technique for assessing the status of the skin without a surgical procedure. The capability of the modality to image microvasculature, visualize tumor boundaries, detect metastases in lymph nodes, perform fast and label-free histology, and identify CTCs could aid in the early diagnosis and classification of CM, including determination of metastatic status. In addition, it could be useful for monitoring treatment efficacy noninvasively.

Quantitative classification of melasma with photoacoustic microscopy: a pilot study

Significance

The classification of melasma is critical for correct clinical diagnosis, treatment selection, and postoperative measures. However, preoperative quantitative determination of melasma type remains challenging using conventional Wood's lamp and optical dermoscopy techniques.

Aim

Using photoacoustic microscopy (PAM) to simultaneously obtain the two diagnostic indicators of melanin and blood vessels for melasma classification and perform quantitative analysis to finally achieve accurate classification, rather than relying solely on physicians' experience.

Approach

First, the patients were classified by experienced dermatologists with Wood's lamp and optical dermoscopy. Next, the patients were examined in vivo using the PAM imaging system. Further, the horizontal section images (X - Y plane) of epidermal melanin and dermal vascular involvement were extracted from the 3D photoacoustic imaging results, which are important basis for PAM to quantitatively classify melasma.

Results

PAM can quantitatively reveal epidermal thickness and dermal vascular morphology in each case and obtain the quantitative diagnostic indicators of melanin and blood vessels. The mean vascular diameter in lesional skin (223.2    μ m ) of epidermal M+V-type was much larger than that in non-lesional skin (131.6    μ m ), and the mean vascular density in lesional skin was more than three times that in non-lesional skin. Importantly, vascular diameter and density are important parameters for distinguishing M type from M+V type.

Conclusions

PAM can obtain the data of epidermal thickness, pigment depth, subcutaneous vascular diameter, and vascular density, and realize the dual standard quantitative melasma classification by combining the parameters of melanin and blood vessels. In addition, PAM can provide new diagnostic information for uncertain melasma types and further refine the typing.

In vivo liver function reserve assessments in alcoholic liver disease by scalable photoacoustic imaging

We present a rapid and high-resolution photoacoustic imaging method for evaluating the liver function reserve (LFR). To validate its accuracy, we establish alcoholic liver disease (ALD) models and employ dual-wavelength spectral unmixing to assess oxygen metabolism. An empirical mathematical model fits the photoacoustic signals, obtaining liver metabolism curve and LFR parameters. Liver oxygen metabolism significantly drops in ALD with the emergence of abnormal hepatic lobular structure. ICG half-life remarkably extends from 241 to 568 s in ALD. A significant decline in LFR occurs in terminal region compared to central region, indicated by a 106.9 s delay in ICG half-life, likely due to hepatic artery and vein damage causing hypoxia and inadequate nutrition. Reduced glutathione repairs LFR with a 43% improvement by reducing alcohol-induced oxidative damage. Scalable photoacoustic imaging shows immense potential for assessing LFR in alcoholic-related diseases, providing assistance to early detection and management of liver disease.

Dermal features derived from optoacoustic tomograms via machine learning correlate microangiopathy phenotypes with diabetes stage

Skin microangiopathy has been associated with diabetes. Here we show that skin-microangiopathy phenotypes in humans can be correlated with diabetes stage via morphophysiological cutaneous features extracted from raster-scan optoacoustic mesoscopy (RSOM) images of skin on the leg. We obtained 199 RSOM images from 115 participants (40 healthy and 75 with diabetes), and used machine learning to segment skin layers and microvasculature to identify clinically explainable features pertaining to different depths and scales of detail that provided the highest predictive power. Features in the dermal layer at the scale of detail of 0.1-1 mm (such as the number of junction-to-junction branches) were highly sensitive to diabetes stage. A 'microangiopathy score' compiling the 32 most-relevant features predicted the presence of diabetes with an area under the receiver operating characteristic curve of 0.84. The analysis of morphophysiological cutaneous features via RSOM may allow for the discovery of diabetes biomarkers in the skin and for the monitoring of diabetes status.

Hair-Reinforced Elastomer Matrix Composites: Formulation, Mechanical Testing, and Advanced Microstructural Characterization

Epoxy matrix composites reinforced with high-performance fibers, such as carbon, Kevlar, and glass, exhibit excellent specific stiffness and strength in many mechanical applications. However, these composites are disappointingly non-recyclable and are usually disposed of in landfill sites, with no realistic prospect for biodegradation in a reasonable time. In contrast, moldable composites with carbonized elastomeric matrices developed in the last decades possess attractive mechanical properties in final net-shape products and can also be incinerated or recycled. Many carbon and inorganic fillers have recently been evaluated to adjust the properties of carbonized elastomeric composites. Renewable organic fillers, such as human or animal hair, offer an attractive fibrous material with substantial potential for reinforcing composites with elastomeric matrices. Samples of unidirectional fiber composites (with hair volume fractions up to 7%) and quasi-isotropic short fiber composites (with hair volume fractions up to 20%) of human hair-reinforced nitrile butadiene rubbers (HH-NBRs) were produced in the peroxide-cured and carbonized states. The samples were characterized using scanning electron microscopy (SEM), Raman spectroscopy, and photoacoustic microscopy. Mechanical tests were performed under tension using a miniature universal testing machine. The expected effect of fiber reinforcement on the overall mechanical performance was demonstrated for both cured and carbonized composites. Considerable enhancement of the elastic modulus (up to ten times), ultimate tensile strength (up to three times), and damage tolerance was achieved. The evidence of satisfactory interfacial bonding between hair and rubber was confirmed via SEM imaging of fracture surfaces. The suitability of photoacoustic microscopy was assessed for 3D reconstructions of the fiber sub-system's spatial distribution and non-destructive testing.

Opening a window to skin biomarkers for diabetes stage with optoacoustic mesoscopy

Being the largest and most accessible organ of the human body, the skin could offer a window to diabetes-related complications on the microvasculature. However, skin microvasculature is typically assessed by histological analysis, which is not suited for applications to large populations or longitudinal studies. We introduce ultra-wideband raster-scan optoacoustic mesoscopy (RSOM) for precise, non-invasive assessment of diabetes-related changes in the dermal microvasculature and skin micro-anatomy, resolved with unprecedented sensitivity and detail without the need for contrast agents. Providing unique imaging contrast, we explored a possible role for RSOM as an investigational tool in diabetes healthcare and offer the first comprehensive study investigating the relationship between different diabetes complications and microvascular features in vivo. We applied RSOM to scan the pretibial area of 95 participants with diabetes mellitus and 48 age-matched volunteers without diabetes, grouped according to disease complications, and extracted six label-free optoacoustic biomarkers of human skin, including dermal microvasculature density and epidermal parameters, based on a novel image-processing pipeline. We then correlated these biomarkers to disease severity and found statistically significant effects on microvasculature parameters as a function of diabetes complications. We discuss how label-free RSOM biomarkers can lead to a quantitative assessment of the systemic effects of diabetes and its complications, complementing the qualitative assessment allowed by current clinical metrics, possibly leading to a precise scoring system that captures the gradual evolution of the disease.

Functional photoacoustic imaging: from nano- and micro- to macro-scale

Functional photoacoustic imaging is a promising biological imaging technique that offers such unique benefits as scalable resolution and imaging depth, as well as the ability to provide functional information. At nanoscale, photoacoustic imaging has provided super-resolution images of the surface light absorption characteristics of materials and of single organelles in cells. At the microscopic and macroscopic scales. photoacoustic imaging techniques have precisely measured and quantified various physiological parameters, such as oxygen saturation, vessel morphology, blood flow, and the metabolic rate of oxygen, in both human and animal subjects. This comprehensive review provides an overview of functional photoacoustic imaging across multiple scales, from nano to macro, and highlights recent advances in technology developments and applications. Finally, the review surveys the future prospects of functional photoacoustic imaging in the biomedical field.

Transrectal Absorber Guide Raster-Scanning Optoacoustic Mesoscopy for Label-Free In Vivo Assessment of Colitis

Optoacoustic imaging (OAI) enables microscale imaging of endogenous chromophores such as hemoglobin at significantly higher penetration depths compared to other optical imaging technologies. Raster-scanning optoacoustic mesoscopy (RSOM) has recently been shown to identify superficial microvascular changes associated with human skin pathologies. In animal models, the imaging depth afforded by RSOM can enable entirely new capabilities for noninvasive imaging of vascular structures in the gastrointestinal tract, but exact localization of intra-abdominal organs is still elusive. Herein the development and application of a novel transrectal absorber guide for RSOM (TAG-RSOM) is presented to enable accurate transabdominal localization and assessment of colonic vascular networks in vivo. The potential of TAG-RSOM is demonstrated through application during mild and severe acute colitis in mice. TAG-RSOM enables visualization of transmural vascular networks, with changes in colon wall thickness, blood volume, and OAI signal intensities corresponding to colitis-associated inflammatory changes. These findings suggest TAG-RSOM can provide a novel monitoring tool in preclinical IBD models, refining animal procedures and underlines the capabilities of such technologies to address inflammatory bowel diseases in humans.