Nailfold capillaroscopy, based on bright-field microscopy, is widely used to diagnose systemic sclerosis (SSc). However it cannot reveal information about venules and arterioles lying deep under the nailfold, nor can it provide detailed data about surface microvasculature when the skin around the nail is thick. These limitations reflect the fact that capillaroscopy is based on microscopy methods whose penetration depth is restricted to about 200 μm. We investigated whether ultra-wideband raster-scan optoacoustic mesoscopy (UWB-RSOM) can resolve small capillaries of the nailfold in healthy volunteers and compared the optoacoustic data to conventional capillaroscopy examinations. We quantified UWB-RSOM-resolved capillary density and capillary diameter as features that relate to SSc biomarkers, and we obtained the first three-dimensional, in vivo images of the deeper arterioles and venules. These results establish the potential of UWB-RSOM for analyzing SSc-relevant markers.

In recent years, several non‐invasive imaging methods have been introduced to facilitate diagnostics and therapy monitoring in dermatology. The microscopic imaging methods are restricted in their penetration depth, while the mesoscopic methods probe deeper but provide only morphological, not functional, information. ‘Raster‐scan optoacoustic mesoscopy’ ( RSOM ), an emerging new imaging technique, combines deep penetration with contrast based on light absorption, which provides morphological, molecular and functional information. Here, we compare the capabilities and limitations of currently available dermatological imaging methods and highlight the principles and unique abilities of RSOM . We illustrate the clinical potential of RSOM , in particular for non‐invasive diagnosis and monitoring of inflammatory and oncological skin diseases.

Melanoma is associated with angiogenesis and vascular changes that may extend through the entire skin depth. Three-dimensional imaging of vascular characteristics in skin lesions could therefore allow diagnostic insights not available by conventional visual inspection. Raster-scan optoacoustic mesoscopy (RSOM) images microvasculature through the entire skin depth with resolutions of tens of micrometers; however, current RSOM implementations are too slow to overcome the strong breathing motions on the upper torso where melanoma lesions commonly occur. To enable high-resolution imaging of melanoma vasculature in humans, we accelerate RSOM scanning using an illumination scheme that is coaxial with a high-sensitivity ultrasound detector path, yielding 15 s single-breath-hold scans that minimize motion artifacts. We apply this Fast RSOM to image 10 melanomas and 10 benign nevi in vivo, showing marked differences between malignant and benign lesions, supporting the possibility to use biomarkers extracted from RSOM imaging of vasculature for lesion characterization to improve diagnostics.

Raster-scan optoacoustic mesoscopy (RSOM) offers high-resolution non-invasive insights into skin pathophysiology, which holds promise for disease diagnosis and monitoring in dermatology and other fields. However, RSOM is quite vulnerable to vertical motion of the skin, which can depend on the part of the body being imaged. Motion correction algorithms have already been proposed, but they are not fully automated, they depend on anatomical segmentation pre-processing steps that might not be performed successfully, and they are not sitespecific. Here, we determined for the first time the magnitude of the micrometric vertical skin displacements at different sites on the body that affect RSOM. The quantification of motion allowed us to develop a site-specific correction algorithm. The algorithm is fully automated and does not need prior anatomical information. We found that the magnitude of the vertical motion depends strongly on the site of imaging and is caused by breathing, heart beating, and arterial pulsation. The developed algorithm resulted in more than 2-fold improvement in the signalto-noise ratio of the reconstructed images at every site tested. Proposing an effective automated motion correction algorithm paves the way for realizing the full clinical potential of RSOM.

No abstract