Application of ultrafast gold luminescence to measuring the instrument response function for multispectral multiphoton fluorescence lifetime imaging

When performing multiphoton fluorescence lifetime imaging in multiple spectral emission channels, an instrument response function must be acquired in each channel if accurate measurements of complex fluorescence decays are to be performed. Although this can be achieved using the reference reconvolution technique, it is difficult to identify suitable fluorophores with a mono-exponential fluorescence decay across a broad emission spectrum. We present a solution to this problem by measuring the IRF using the ultrafast luminescence from gold nanorods. We show that ultrafast gold nanorod luminescence allows the IRF to be directly obtained in multiple spectral channels simultaneously across a wide spectral range. We validate this approach by presenting an analysis of multispectral autofluorescence FLIM data obtained from human skin ex vivo

Reflectance confocal microscopy for diagnosising keratinocyte skin cancers in adults

Background Early accurate detection of all skin cancer types is important to guide appropriate management and to improve morbidity and survival. Basal cell carcinoma (BCC) is usually a localised skin cancer but with potential to infiltrate and damage surrounding tissue, whereas squamous cell carcinoma (cSCC) and melanoma are higher risk skin cancers with the potential to metastasise and ultimately lead to death. When used in conjunction with clinical or dermoscopic suspicion of malignancy, or both, reflectance confocal microscopy (RCM) may help to identify those eligible for non-surgical treatment without the need for a diagnostic biopsy, particularly in people with suspected BCC. Any potential benefit must be balanced against the risk of any misdiagnoses. Objectives 1) To determine the diagnostic accuracy of RCM for the detection of BCC, cSCC, or any skin cancer in adults with a) suspicious lesion and b) lesions that are difficult to diagnose (equivocal); and 2) to compare its accuracy with that of usual practice (visual inspection or dermoscopy, or both). Search methods We undertook a comprehensive search of the following databases from inception up to August 2016: Cochrane Central Register of Controlled Trials; MEDLINE; EMBASE; CINAHL; CPCI; Zetoc; Science Citation Index; US National Institutes of Health Ongoing Trials Register; NIHR Clinical Research Network Portfolio Database; and the World Health Organization International Clinical Trials Registry Platform. We studied reference lists and published systematic review articles. Selection criteria Studies of any design that evaluated the accuracy of RCM alone, or RCM in comparison to visual inspection or dermoscopy, or both, in adults with lesions suspicious for skin cancer compared with a reference standard of either histological confirmation or clinical follow-up, or both. Data collection and analysis Two review authors independently extracted all data using a standardised data extraction and quality assessment form (based on QUADAS-2). We contacted authors of included studies where information related to the target condition or diagnostic threshold were missing. We estimated summary sensitivities and specificities using the bivariate hierarchical model. For computation of likely numbers of true positive, false positive, false negative, and true negative findings in the'Summary of findings' tables, summary sensitivity and specificity estimates were applied to lower quartile, median and upper quartiles of the prevalence observed in the study groups. We also investigated the impact of observer experience. Main results Ten studies reporting on a total of 11 study cohorts were included. All 11 cohorts reported data for the detection of BCC, including 2037 lesions (464 with BCC); and four cohorts reported data for the detection of cSCC, including 834 lesions (71 with cSCC). Only one study also reported data for the detection of BCC or cSCC using dermoscopy, limiting comparisons between RCM and dermoscopy. Studies were at high or unclear risk of bias across almost all methodological quality domains, and were of high or unclear concern regarding applicability of the evidence. Selective participant recruitment, unclear blinding of the reference test, and exclusions due to image quality or technical difficulties were observed. It is unclear whether studies are representative of populations eligible for testing with RCM, and test interpretation was often undertaken using images, remotely from the patient and the interpreter blinded to clinical information that would normally be available in practice. Meta-analysis found RCM to be more sensitive but less specific for the detection of BCC in studies of participants with equivocal lesions (sensitivity 94%, 95% CI 79% to 98%; specificity 85%, 95% CI 72% to 92%; n = 3 studies) compared to studies that included any suspicious lesion (sensitivity 76%, 95% CI 45% to 92%; specificity 95%, 95% CI 66% to 99%; n = 4 studies), although confidence intervals were wide. At the median prevalence of disease of 12.5% observed in studies including any suspicious lesion, applying these results to a hypothetical population of 1000 lesions results in 30 BCCs missed with 44 false positive results (lesions misdiagnosed as BCCs). At the median prevalence of disease of 15% observed in studies of equivocal lesions, 9 BCCs would be missed with 128 false positive results in a population of 1000 lesions. Across both sets of studies, up to 15% of these false positive lesions were observed to be melanomas mistaken for BCCs. There was some suggestion of higher sensitivities in studies with more experienced observers. Summary sensitivity and specificity could not be estimated for the detection of cSCC due to paucity of data. Authors' conclusions There is insufficient evidence for the use of RCM for the diagnosis of BCC or cSCC in either population group. A possible role for RCM in clinical practice is as a tool to avoid diagnostic biopsies in lesions with a relatively high clinical suspicion of BCC. The potential for, and consequences of, misclassification of other skin cancers such as melanoma as BCCs requires further research. Importantly, data are lacking that compare RCM to standard clinical practice (with or without dermoscopy)

The clinical application of multispectral fluorescence lifetime imaging of human skin using multiphoton microscopy

The work presented in this thesis employed multiphoton microscopy of tissue autofluorescence to investigate spectrally and fluorescence lifetime resolved images obtained from normal skin and cutaneous malignancies. This was achieved by adapting a commercially available CE-marked multiphoton tomograph (DermaInspect®) to allow fluorescence lifetime imaging (FLIM) simultaneously in four spectral channels and corresponding steady-state hyperspectral images using a prism-based spectrometer to be acquired. The images generated were analysed through the manual identification of morphological criteria and through manual and automatic segmentation of individual cells within FLIM images followed by automated morphological and spectroscopic analysis. The analysis of FLIM images acquired from normal skin ex vivo and in vivo identified subpopulations of cells based on their autofluorescence characteristics and allowed intra- and interpatient variations to be assessed. The mean cellular lifetime was found to decrease between 691-1286 picoseconds (ps) with depth, increase between 199-550 ps with age and a statistically significant decrease between 286-1436 ps with skin phototype (I-IV) was found, depending on spectral channel. The manual identification of morphological features from BCC images acquired ex vivo allowed the correct diagnosis to be made with a sensitivity/specificity of 79%/93%. Cellular fluorescence lifetimes were statistically significantly longer by between 19.9-39.8% compared to normal skin. A linear discriminant analysis combining both spectroscopic and morphological cellular parameters allowed BCCs to be discriminated from normal skin with an AUC of 0.83. Manually identified morphological features were able to distinguish dysplastic naevi from melanomas with a sensitivity and specificity of 75% and 81% respectively from ex vivo FLIM images. However, no contrast in cellular fluorescence lifetime was observed. A motorised stage has also allowed multispectral FLIM image mosaics of depth resolved images from unsectioned skin to be presented for the first time. In conclusion tissue autofluorescence and FLIM detect clinically useful differences in the skin.Open Acces

In vivo measurements of diffuse reflectance and time-resolved autofluorescence emission spectra of basal cell carcinomas

We present a clinical investigation of diffuse reflectance and time-resolved autofluorescence spectra of skin cancer with an emphasis on basal cell carcinoma. A total of 25 patients were measured using a compact steady-state diffuse reflectance/fluorescence spectrometer and a fibre-optic-coupled multispectral time-resolved spectrofluorometer. Measurements were performed in vivo prior to surgical excision of the investigated region. Singular value decomposition was used to reduce the dimensionality of steady state diffuse reflectance and fluorescence spectra. Linear discriminant analysis was then applied to the measurements of basal cell carcinomas (BCCs) and used to predict the tissue disease state with a leave-one-out methodology. This approach was able to correctly diagnose 87% of the BCCs. With 445 nm excitation a decrease in the spectrally averaged fluorescence lifetime was observed between normal tissue and BCC lesions with a mean value of 886 ps. Furthermore, the fluorescence lifetime for BCCs was lower than that of the surrounding healthy tissue in all cases and statistical analysis of the data revealed that this decrease was significant (p = 0.002). (C) 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Multispectral fluorescence intensity and FLIM images acquired from normal skin and BCCs.

<p>(a–i) Fluorescence intensity and false color FLIM images from a single field of view acquired at a depth of 110 µm with all spectral channels taken near a dermal papilla from normal skin. (j–n) FLIM images taken from the green channel only of different depths within a sample of normal skin. (o–u) FLIM images taken from the green channel illustrating visual architectural features seen in BCC using MPT. (v) FLIM image taken from the blue channel of a BCC. (w,x) paired FLIM images taken from the green and blue channels respectively of a BCC nest. KEY SG-Stratum Granulosum, SS- Stratum Spinosum, BCL-Basal Cell Layer, DP-Dermal Papilla. Scale bar 25 µm.</p

The best discriminatory parameters ranked using the area under the curve (AUC).

<p><b>Abbreviations</b> AUC – area under the curve, τ₁ – short fluorescence lifetime decay component, τ₂ – long lifetime component.</p

Exemplar segmented fluorescence intensity images, fitted fluorescence decay and fluorophore emission spectra.

<p>(a) Total fluorescence intensity image, same image with (b) manually and (c) automatically defined cellular regions of interest overlayed. (d) Top – exemplar fluorescence decay from one region of interest (black), biexponential fit to data (green) and instrument response function (blue). (d) Bottom – normalized residuals. (e) The emission spectra from endogenous fluorophores plotted in relation to the four spectral detection channels.</p