Real-time multi-exposure laser speckle contrast imaging of skin microcirculatory perfusion

Hultman, Martin

doi:10.3384/9789179291068

Cited by 2 publications

(2 citation statements)

References 115 publications

(204 reference statements)

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“…The Doppler histogram H(f) obtained as described in the previous section was converted into multi-exposure contrast K(T) using a mathematical framework that is thoroughly described in Refs. 6 and 25. In short, the electric field autocorrelation function g(1)(τ) was obtained from the Doppler histogram using the Wiener–Khinchine theorem g(1)(τ)=|F−1{H(f)}|,where F−1 is the inverse Fourier transform.…”

Section: Methodsmentioning

confidence: 99%

Speed-resolved perfusion imaging using multi-exposure laser speckle contrast imaging and machine learning

et al. 2023

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Significance: Laser speckle contrast imaging (LSCI) gives a relative measure of microcirculatory perfusion. However, due to the limited information in single-exposure LSCI, models are inaccurate for skin tissue due to complex effects from e.g. static and dynamic scatterers, multiple Doppler shifts, and the speed-distribution of blood. It has been demonstrated how to account for these effects in laser Doppler flowmetry (LDF) using inverse Monte Carlo (MC) algorithms. This allows for a speed-resolved perfusion measure in absolute units %RBC × mm/s, improving the physiological interpretation of the data. Until now, this has been limited to a single-point LDF technique but recent advances in multi-exposure LSCI (MELSCI) enable the analysis in an imaging modality.Aim: To present a method for speed-resolved perfusion imaging in absolute units %RBC × mm/s, computed from multi-exposure speckle contrast images.Approach: An artificial neural network (ANN) was trained on a large simulated dataset of multi-exposure contrast values and corresponding speed-resolved perfusion. The dataset was generated using MC simulations of photon transport in randomized skin models covering a wide range of physiologically relevant geometrical and optical tissue properties. The ANN was evaluated on in vivo data sets captured during an occlusion provocation.Results: Speed-resolved perfusion was estimated in the three speed intervals 0 to 1 mm∕s, 1 to 10 mm∕s, and >10 mm∕s, with relative errors 9.8%, 12%, and 19%, respectively. The perfusion had a linear response to changes in both blood tissue fraction and blood flow speed and was less affected by tissue properties compared with single-exposure LSCI. The image quality was subjectively higher compared with LSCI, revealing previously unseen macro-and microvascular structures. Conclusions:The ANN, trained on modeled data, calculates speed-resolved perfusion in absolute units from multi-exposure speckle contrast. This method facilitates the physiological interpretation of measurements using MELSCI and may increase the clinical impact of the technique.

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Section: Methodsmentioning

confidence: 99%

Speed-resolved perfusion imaging using multi-exposure laser speckle contrast imaging and machine learning

et al. 2023

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“…Although blood flow is measured in arbitrary units, it has been shown to be linear with that of laser Doppler flowmetry which is known as the utmost quantitative optical approach [5]. There are several methods to calculate speckle contrast such as temporal, spatial or spatiotemporal [6] as well as multi-exposure LSCI [7] that depends on the medical application. LSCI offers a wide range of medical applications including burns, neurology and ophthalmology [8].…”

Section: Introductionmentioning

confidence: 99%

Reliability of handheld laser speckle contrast perfusion imaging demonstrated in psoriasis lesions

Chizari¹,

Schaap

Knop

et al. 2022

Photonics in Dermatology and Plastic Surgery 2022

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We assessed the reliability of handheld laser speckle contrast perfusion imaging by evaluating mounted/handheld measurement pairs operated on psoriasis lesions in three steps. First, we made a denoised perfusion map per measurement based on spatial alignment of raw speckle frames and temporal averaging of perfusion frames. Second, we used the measured on-surface speed information to compensate the movement-induced perfusion by extrapolation of the local perfusion values to the value corresponds to zero on-surface speed. Third, we compared mounted/handheld measurement pairs based on perfusion inhomogeneity and increased perilesional perfusion criteria independent of the movement artefact compensation mentioned in the second step. We conclude that after proper post-processing, handheld LSCI measurements can be as reliable as mounted measurements in terms of geometrical distorting, but with challenges to be overcome for correcting perfusion values.

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Real-time multi-exposure laser speckle contrast imaging of skin microcirculatory perfusion

Cited by 2 publications

References 115 publications

Speed-resolved perfusion imaging using multi-exposure laser speckle contrast imaging and machine learning

Speed-resolved perfusion imaging using multi-exposure laser speckle contrast imaging and machine learning

Reliability of handheld laser speckle contrast perfusion imaging demonstrated in psoriasis lesions

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