Concurrent Reflectance Confocal Microscopy and Laser Doppler Flowmetry to Improve Skin Cancer Imaging: A Monte Carlo Model and Experimental Validation.
Optical interrogation of suspicious skin lesions is standard care in the management of skin cancer worldwide. Morphological and functional markers of malignancy are often combined to improve expert human diagnostic power. We propose the evaluation of the combination of two independent optical biomarkers of skin tumours concurrently. The morphological modality of reflectance confocal microscopy (RCM) is combined with the functional modality of laser Doppler flowmetry, which is capable of quantifying tissue perfusion. To realize the idea, we propose laser feedback interferometry as an implementation of RCM, which is able to detect the Doppler signal in addition to the confocal reflectance signal. Based on the proposed technique, we study numerical models of skin tissue incorporating two optical biomarkers of malignancy: (i) abnormal red blood cell velocities and concentrations and (ii) anomalous optical properties manifested through tissue confocal reflectance, using Monte Carlo simulation. We also conduct a laboratory experiment on a microfluidic channel containing a dynamic turbid medium, to validate the efficacy of the technique. We quantify the performance of the technique by examining a signal to background ratio (SBR) in both the numerical and experimental models, and it is shown that both simulated and experimental SBRs improve consistently using this technique. This work indicates the feasibility of an optical instrument, which may have a role in enhanced imaging of skin malignancies.
School of Information Technology and Electrical Engineering, The University of Queensland, St. Lucia, Brisbane 4072, Australia. a.mowla@uq.edu.au.
Alireza
A
Mowla
School of Mathematics and Physics, The University of Queensland, St. Lucia, Brisbane 4072, Australia. t.taimre@uq.edu.au.
Thomas
T
Taimre
School of Information Technology and Electrical Engineering, The University of Queensland, St. Lucia, Brisbane 4072, Australia. ylim@itee.uq.edu.au.
Yah Leng
YL
Lim
School of Information Technology and Electrical Engineering, The University of Queensland, St. Lucia, Brisbane 4072, Australia. bertling@itee.uq.edu.au.
Karl
K
Bertling
School of Information Technology and Electrical Engineering, The University of Queensland, St. Lucia, Brisbane 4072, Australia. wilson@itee.uq.edu.au.
Stephen J
SJ
Wilson
Dermatology Research Centre, The University of Queensland, School of Medicine, Translational Research Institute, Brisbane 4102, Australia. t.prow@uq.edu.au.
Tarl W
TW
Prow
Dermatology Research Centre, The University of Queensland, School of Medicine, Translational Research Institute, Brisbane 4102, Australia. p.soyer@uq.edu.au.
H Peter
HP
Soyer
School of Information Technology and Electrical Engineering, The University of Queensland, St. Lucia, Brisbane 4072, Australia. rakic@itee.uq.edu.au.
Aleksandar D
AD
Rakić
D003952:Diagnostic Imaging; D006801:Humans; D007368:Interferometry; D017078:Laser-Doppler Flowmetry / Q000379:methods*; D018613:Microscopy, Confocal / Q000379:methods*; D009010:Monte Carlo Method; D009716:Numerical Analysis, Computer-Assisted; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D012878:Skin Neoplasms / Q000175:diagnosis*
Monte Carlo modelling; laser Doppler flowmetry; laser feedback interferometry; reflectance confocal microscopy; skin cancer detection