Handheld versus mounted laser speckle contrast perfusion imaging demonstrated in psoriasis lesions

Enhancement of vascular visualization in laser speckle contrast imaging based on image algorithms

Significance

In practical biomedical applications, obtaining clear and focused speckle images through laser speckle contrast imaging (LSCI) presents significant challenges. These challenges are often compounded by motion artifacts and image noise, which can adversely affect the effectiveness of vascular visualization in LSCI.

Aim

We improved the visualization of blood flow in LSCI by focusing on three aspects: image registration, image denoising, and multi-focus image fusion.

Approach

We employed the Lucas-Kanade (LK) optical flow pyramid method alongside block matching and three-dimensional filtering (BM3D) algorithm based on guided filtering with total variation regularization to effectively mitigate motion artifacts and noise. Furthermore, we proposed a multi-focus image fusion technique based on the multi-scale image contrast amplification (MUSICA) algorithm, aimed at enhancing high-frequency signals and minimizing the effects of defocusing in LSCI.

Results

The LK optical flow registration algorithm demonstrates improvements in both average peak signal-to-noise ratio and imaging quality compared with non-registration methods. The improved BM3D method outperforms classical denoising algorithms in various image evaluation parameters within LSCI. In the case of using the multi-focus image fusion method based on the MUSICA method, the image quality assessment of the sum of modulus of gray difference squared showed an improvement of nearly six times compared with the defocused images without the use of the MUSICA method.

Conclusions

Improvements in image processing algorithms, specifically in the areas of registration, denoising, and multi-focus image fusion, have significantly enhanced the visualization of blood flow in the vessels during practical applications of LSCI.

Lightweight denoising speckle contrast image GAN for real-time denoising of laser speckle imaging of blood flow

To tackle real-time denoising of noisy laser speckle blood flow images, a novel lightweight denoising speckle contrast image generative adversarial network (LDSCI-GAN) is proposed. In the framework, a lightweight denoiser removes noise from the original image, and a discriminator compares the denoised result with the reference one, enabling efficient learning and optimization of the denoising process. With a multi-scale loss function in the log-transformed domain, the training process significantly improves accuracy and denoising by using only five frames of raw speckle images while well-preserving the overall pixel distribution and vascular contours. Animal and phantom experimental results indicate that the LDSCI-GAN can eliminate vascular artifacts while retaining the accuracy of relative blood flow velocity. In terms of peak signal-to-noise ratio (PSNR), mean structural similarity index (MSSIM), and Pearson correlation coefficient (R), the LDSCI-GAN outperforms other deep-learning methods by 3.07 dB, 0.10 (p < 0.001), and 0.09 (p = 0.023), respectively. It has been successfully applied to the real-time monitoring of laser-induced thrombosis. Through conducting tests on the denoising performance of blood flow images of a moving subject, our proposed method achieved enhancements of 23.6% in PSNR, 30% in MSSIM, and 6.5% in the metric R, respectively, when compared to DRSNet. This means that the LDSCI-GAN also shows possible application in handheld devices, offering a potent tool for investigating blood flow and thrombosis dynamics more efficiently and conveniently.

Mitigation of Motion Artifacts in Handheld Laser Speckle Contrast Imaging Illustrated on Psoriasis Lesions

BACKGROUND

Handheld laser speckle contrast imaging (LSCI) is crucial in clinical settings, but motion artifacts (MA) can compromise perfusion image reliability. Current prevention and suppression methods are often impractical or complex. Machine vision techniques, promising in medical imaging, could improve signal quality, but their use in suppressing MA is still unexplored.

OBJECTIVE

We propose an innovative method based on linear regression for MA correction (MAC) in LSCI and validate it in vivo.

METHODS

We performed paired handheld and mounted LSCI measurements on 14 subjects with psoriasis using the previously validated handheld perfusion imager (HAPI). By marking lesion boundaries for clinical purposes, the HAPI used a monochromatic camera for both speckle imaging and motion detection, simplifying hardware requirements. Accurate estimation of relative displacements between the test object and LSCI probe allowed us to apply MAC to the perfusion images.

RESULTS

Local perfusion values correlated with applied speed were used to calculate and correct MA. The difference between mean perfusion in handheld and mounted modes after MAC significantly decreased (median error 14.2 perfusion units (p.u.) on lesions before correction (p 0.0005) and 0.5 p.u. after correction (p=0.2)).

CONCLUSION

The findings provide evidence for robust handheld LSCI and validate the MA technique in psoriasis case. Of the two causes of MA-on-surface speeds and wavefront tilt-we address the former and correct mean perfusion, assuming constant temporal perfusion at each location.

SIGNIFICANCE

We describe a practical, non-contact, marker-free technique for reliable handheld perfusion imaging, supporting further clinical translation in plastic surgery and burns.

Patient-specific arterial input function for accurate perfusion assessment in intraoperative fluorescence imaging

Significance

The arterial input function (AIF) plays a crucial role in correcting the time-dependent concentration of the contrast agent within the arterial system, accounting for variations in agent injection parameters (speed, timing, etc.) across patients. Understanding the significance of the AIF can enhance the accuracy of tissue vascular perfusion assessment through indocyanine green-based dynamic contrast-enhanced fluorescence imaging (DCE-FI).

Aim

We evaluate the impact of the AIF on perfusion assessment through DCE-FI.

Approach

A total of 144 AIFs were acquired from 110 patients using a pulse dye densitometer. Simulation and patient intraoperative imaging were conducted to validate the significance of AIF for perfusion assessment based on kinetic parameters extracted from fluorescence images before and after AIF correction. The kinetic model accuracy was evaluated by assessing the variability of kinetic parameters using individual AIF versus population-based AIF.

Results

Individual AIF can reduce the variability in kinetic parameters, and population-based AIF can potentially replace individual AIF for estimating wash-out rate (k ep ), maximum intensity (I max ), ingress slope with lower differences compared with those in estimating blood flow, volume transfer constant (K trans ), and time to peak.

Conclusions

Individual AIF can provide the most accurate perfusion assessment compared with assessment without AIF or based on population-based AIF correction.

Theoretical and experimental investigations of speckle features based on free-space surface scattering

Speckle is a significant challenge for laser imaging systems, as it degrades the image quality. In this study, an improved theoretical model is established to describe the speckle features in free-space optical path. The model quantitatively defines the relationship between speckle contrast and five parameters: wavelength, screen surface roughness, light-spot diameter, incidence angle, and observation angle. Subsequently, the theoretical results are experimentally verified. This study enhances the theory of speckle suppression in free-space optical path, and thus enriches the existing speckle suppression theory. The speckle features based on free-space surface-scattered fields have the potential for applications related to non-imaging optics.

Advances in laser speckle imaging: From qualitative to quantitative hemodynamic assessment

Laser speckle imaging (LSI) techniques have emerged as a promising method for visualizing functional blood vessels and tissue perfusion by analyzing the speckle patterns generated by coherent light interacting with living biological tissue. These patterns carry important biophysical tissue information including blood flow dynamics. The noninvasive, label-free, and wide-field attributes along with relatively simple instrumental schematics make it an appealing imaging modality in preclinical and clinical applications. The review outlines the fundamentals of speckle physics and the three categories of LSI techniques based on their degree of quantification: qualitative, semi-quantitative and quantitative. Qualitative LSI produces microvascular maps by capturing speckle contrast variations between blood vessels containing moving red blood cells and the surrounding static tissue. Semi-quantitative techniques provide a more accurate analysis of blood flow dynamics by accounting for the effect of static scattering on spatiotemporal parameters. Quantitative LSI such as optical speckle image velocimetry provides quantitative flow velocity measurements, which is inspired by the particle image velocimetry in fluid mechanics. Additionally, discussions regarding the prospects of future innovations in LSI techniques for optimizing the vascular flow quantification with associated clinical outlook are presented.

Applications of Laser Speckle Contrast Imaging Technology in Dermatology

Laser speckle contrast imaging or laser speckle imaging (LSI) is a noninvasive imaging technology that can detect areas of dynamic perfusion or vascular flow. Thus, LSI has shown increasing diagnostic utility in various pathologies and has been employed for intraoperative, postoperative, and long-term monitoring in many medical specialties. Recently, LSI has gained traction in clinical dermatology because it can be effective in the assessment of pathologies that are associated with increased perfusion and hypervascularity compared with that of normal tissue. To date, LSI has been found to be highly accurate in monitoring skin graft reperfusion, determining the severity of burns, evaluating neurosurgical revascularization, assessing persistent perfusion in capillary malformations after laser therapy, and differentiating malignant and benign skin lesions. LSI affords the advantage of noninvasively assessing lesions before more invasive methods of diagnosis, such as tissue biopsy, while remaining inexpensive and exhibiting no adverse events to date. However, potential obstacles to its clinical use include tissue movement artifact, primarily qualitative data, and unclear impact on clinical practice given the lack of superiority data compared with the current standard-of-care diagnostic methods. In this review, we discuss the clinical applications of LSI in dermatology for use in the diagnosis and monitoring of vascular, neoplastic, and inflammatory skin conditions.

Prediction of motion artifacts caused by translation in handheld laser speckle contrast imaging

Significance

In handheld laser speckle contrast imaging (LSCI), motion artifacts (MA) are inevitable. Suppression of MA leads to a valid and objective assessment of tissue perfusion in a wide range of medical applications including dermatology and burns. Our study shines light on the sources of these artifacts, which have not yet been explored. We propose a model based on optical Doppler effect to predict speckle contrast drop as an indication of MA.

Aim

We aim to theoretically model MA when an LSCI system measuring on static scattering media is subject to translational displacements. We validate the model using both simulation and experiments. This is the crucial first step toward creating robustness against MA.

Approach

Our model calculates optical Doppler shifts in order to predict intensity correlation function and contrast of the time-integrated intensity as functions of applied speed based on illumination and detection wavevectors. To validate the theoretical predictions, computer simulation of the dynamic speckles has been carried out. Then experiments are performed by both high-speed and low-framerate imaging. The employed samples for the experiments are a highly scattering matte surface and a Delrin plate of finite scattering level in which volume scattering occurs.

Results

An agreement has been found between theoretical prediction, simulation, and experimental results of both intensity correlation functions and speckle contrast. Coefficients in the proposed model have been linked to the physical parameters according to the experimental setups.

Conclusions

The proposed model provides a quantitative description of the influence of the types of illumination and media in the creation of MA. The accurate prediction of MA caused by translation based on Doppler shifts makes our model suitable to study the influence of rotation. Also the model can be extended for the case of dynamic media, such as live tissue.

Perfusion measured by laser speckle contrast imaging as a predictor for expansion of psoriasis lesions

Background

Skin microvasculature changes are crucial in psoriasis development and correlate with perfusion. The noninvasive Handheld Perfusion Imager (HAPI) examines microvascular skin perfusion in large body areas using laser speckle contrast imaging (LSCI).

Objectives

To (i) assess whether increased perilesional perfusion and perfusion inhomogeneity are predictors for expansion of psoriasis lesions and (ii) assess feasibility of the HAPI system in a mounted modality.

Methods

In this interventional pilot study in adults with unstable plaque psoriasis, HAPI measurements and color photographs were performed for lesions present on one body region at week 0, 2, 4, 6 and 8. The presence of increased perilesional perfusion and perfusion inhomogeneity was determined. Clinical outcome was categorized as increased, stable or decreased lesion surface between visits. Patient feedback was collected on a 10‐point scale.

Results

In total, 110 lesions with a median follow‐up of 6 (IQR 6.0) weeks were assessed in 6 patients with unstable plaque psoriasis. Perfusion data was matched to 281 clinical outcomes after two weeks. A mixed multinomial logistic regression model revealed a predictive value of perilesional increased perfusion (OR 9.90; p < 0.001) and perfusion inhomogeneity (OR 2.39; p = 0.027) on lesion expansion after two weeks compared to lesion stability. HAPI measurements were considered fast, patient‐friendly and important by patients.

Conclusion

Visualization of increased perilesional perfusion and perfusion inhomogeneity by noninvasive whole field LSCI holds potential for prediction of psoriatic lesion expansion. Furthermore, the HAPI is a feasible and patient‐friendly tool.