Fluorescence spectroscopy of neoplastic and non-neoplastic tissues

Fluorescence images of skin lesions and automated diagnosis using convolutional neural networks

In recent years, interest in applying deep learning (DL) to medical diagnosis has rapidly increased, driven primarily by the development of Convolutional Neural Networks and Transformers. Despite advancements in DL, the automated diagnosis of skin cancer remains a significant challenge. Emulating dermatologists, deep learning approaches using clinical images acquired from smartphones and considering patient lesion information have achieved performance levels close to those of specialists. While including clinical information, such as whether the lesion bleeds, hurts, or itches, improves diagnostic metrics, it is insufficient for correctly differentiating some major skin cancer lesions. An alternate technology for diagnosing skin cancer is fluorescence widefield imaging, where the skin lesion is illuminated with excitation light, causing it to emit fluorescence. Since there is no public dataset of fluorescence images for skin lesions, to the best of our knowledge, an effort has been made and resulted in 1,563 fluorescence images of major skin lesions taken by smartphones using the handheld LED wieldfield fluorescence device. The collected images were annotated and analyzed, creating a new dataset named FLUO-SC. Convolutional neural networks were then applied to classify skin lesions using these fluorescence images. Experimental results indicate that fluorescence images are competitive with clinical images (baseline) for classifying major skin lesions and show promising potential for discrimination.

Impact of ambient conditions on the minor nutrients content in spirulina "Arthrospira platensis" (AP) extracted from Lake Chad revealed by fluorescence spectroscopy coupled with chemometric methods

In this study, the technique of fluorescence spectroscopy coupled with chemometric methods is used to analyse samples of Lake Chad Spirulina "Arthrospira platensis" (AP), either harvested and conditioned by using the traditional method at different seasons or industrially processed. The content of minor fluorescent nutrients is investigated. To this end, fluorescence excitation-emission matrices (EEMs) of 46 AP samples are recorded in aqueous solution. Synchronous fluorescence (SF) spectra are extracted from these EEMs and their important features are compared to those of PARAFAC methods. Synchronous fluorescence scanning allows different AP samples to be characterized in a single scan. The SF and PARAFAC methods yielded two groups of fluorescent compounds; the first group, consisting of vitamin-like molecules, shows excitation/emission (ex/em) peaks at 340/460, 390/462, 370/440 and 450/526 nm, attributed to caffeic acid, vitamin K, E and riboflavins respectively, while the second group, consisting of pigments, shows ex/em peaks at 610/654, 590/630 and 570/644 nm, attributed to phycocyanins, C-phycocyanin and allophycocyanin. Our fluorescence data showed that while both vitamins and pigments are present in AP during the rainy season, only fluorescent components of vitamin-like compounds are present during the dry season. PCA methods allowed classifying different AP samples according to their geographic origin and harvesting season. Fluorescence spectroscopy therefore appears to be a powerful technique for rapidly assessing the chemical composition of AP.

Dual-mode OCT/fluorescence system for monitoring the morphology and metabolism of laser-printed 3D full-thickness skin equivalents

The 3D structure of native human skin is fundamental for studying skin health, diseases, wound healing, and for testing the safety of skin care products, as well as personalized treatments for skin conditions. Tissue regeneration, driven by tissue engineering, often involves creating full-thickness skin equivalents (FSE), which are widely used for developing both healthy and diseased skin models. In this study, we utilized human skin cell lines to create FSE. We designed high-resolution 3D scaffolds to support the growth and maturation of these skin models. Additionally, we developed and validated a cost-effective, custom-built system combining fluorescence spectroscopy (FS) and optical coherence tomography (OCT) for non-destructive analysis of the metabolism and morphology of 3D FSEs. This system proved highly sensitive in detecting fluorescence from key metabolic co-enzymes (NADH and FAD) in solutions and cell suspensions, while OCT provided adequate resolution to observe the morphology of FSEs. As a result, both the 3D FSE model and the dual-mode optical system hold significant potential for use in 3D bioprinting of biological tissues, as well as in the development of cosmetics, drugs, and in monitoring their maturation over time.

Spatially Resolved Fibre-Optic Probe for Cervical Precancer Detection Using Fluorescence Spectroscopy and PCA-ANN-Based Classification Algorithm: An In Vitro Study

Cervical cancer can be detected at an early stage through the changes occurring in biochemical and morphological properties of epithelium layer. Fluorescence spectroscopy has the ability to identify these subtle changes non-invasively and in real time with good accuracy in comparison with conventional techniques. In this paper, we report the usage of a custom designed spatially resolved fibre-optic probe (SRFOP), which consists of 77 fibres in two concentric rings, for the detection of cervical cancer using fluorescence spectroscopy technique. The aim of this study is to classify different grades of cervical precancer on the basis of their fluorescence spectra followed by a robust classification algorithm. Fluorescence spectra of 28 cervical tissue samples of different categories have been recorded using six detector fibres of FOP at different spatial locations with the source fibre (SF). A 405 nm laser diode source has been utilised to excite the samples and a USB 4000 Ocean Optics spectrometer to collect the output spectra in the wavelength range 400-700 nm. Principal component analysis (PCA) was applied to the collected spectra to reduce the dimensionality of the data while preserving the most significant features for classification. The first 10 principal components, which captured the majority of the variance in the spectra, were selected as input features for the classification model. Classification was then performed using an artificial neural network (ANN) with a specific architecture, including an input layer, hidden layers, and a softmax activation function in the output layer. Experimental and classification results both demonstrate that proximal fibres (PFs) perform better than distal fibres (DFs) in capturing the discriminatory features present in the epithelium layer of cervical tissue samples as PF collect most of the signal from the epithelium layer. The combined approach of spatially resolved fluorescence spectroscopy and PCA-ANN classification techniques is able to discriminate different grades of cervical precancer and normal with an average sensitivity, specificity and accuracy of 93.33%, 96.67% and 95.57%, respectively.

Biogenic and Anthropogenic Secondary Organic Aerosols Become Fluorescent after Highly Acidic Aging

Primary biological aerosol particles (PBAPs) and secondary organic aerosol (SOA) both contain organic compounds that share similar chemical and optical properties. Fluorescence is often used to characterize PBAPs; however, this may be hindered due to interferences from fluorophores in SOA. Despite extensive efforts to understand the aging of SOA under elevated particle acidity conditions, little is known about how these processes affect the fluorescence of SOA and thereby their interference with the measurements of PBAPs. The objective of this study is to investigate the fluorescence of SOA and understand the influence of acidity on the optical properties of organic aerosols and potential interference for the analysis of bioaerosols. The SOA was generated by O3- or OH-initiated oxidation of d-limonene or α-pinene, as well as by OH-initiated oxidation of toluene or xylene. The SOA compounds were then aged by exposure to varying concentrations of aqueous H2SO4 for 2 days. Absorption and fluorescence spectrophotometry were used to examine the changes in the optical properties before and after aging. The key observation was the appearance of strongly light-absorbing and fluorescent compounds at pH = ∼-1, suggesting that acidity is a major driver of SOA aging. The aged SOA from biogenic precursors (d-limonene and α-pinene) resulted in stronger fluorescence than the aged SOA from toluene and xylene. The absorption spectra of the aged SOA changed drastically in shape upon dilution, whereas the shapes of the fluorescence spectra remained the same, suggesting that the fluorophores and chromophores in SOA are separate sets of species. The fluorescence spectra of aged SOA overlapped with the fluorescence spectra of PBAPs, suggesting that SOA exposed to highly acidic conditions can be confused with PBAPs detected by fluorescence-based methods. These processes are likely to play a role in the atmospheric regions where high concentrations of H2SO4 persist, such as the upper troposphere and lower stratosphere.

AutoMitoNetwork: Software for analyzing mitochondrial networks in autofluorescence images to enable label-free cell classification

High-resolution mitochondria imaging in combination with image analysis tools have significantly advanced our understanding of cellular function in health and disease. However, most image analysis tools for mitochondrial studies have been designed to work with fluorescently labeled images only. Additionally, efforts to integrate features describing mitochondrial networks with machine learning techniques for the differentiation of cell types have been limited. Herein, we present AutoMitoNetwork software for image-based assessment of mitochondrial networks in label-free autofluorescence images using a range of interpretable morphological, intensity, and textural features. To demonstrate its utility, we characterized unstained mitochondrial networks in healthy retinal cells and in retinal cells exposed to two types of treatments: rotenone, which directly inhibited mitochondrial respiration and ATP production, and iodoacetic acid, which had a milder impact on mitochondrial networks via the inhibition of anaerobic glycolysis. For both cases, our multi-dimensional feature analysis combined with a support vector machine classifier distinguished between healthy cells and those treated with rotenone or iodoacetic acid. Subtle changes in morphological features were measured including increased fragmentation in the treated retinal cells, pointing to an association with metabolic mechanisms. AutoMitoNetwork opens new options for image-based machine learning in label-free imaging, diagnostics, and mitochondrial disease drug development.

Recent advancements to increase success in assisted reproductive technologies in cattle

Assisted reproductive technologies (ART) are fundamental for cattle breeding and sustainable food production. Together with genomic selection, these technologies contribute to reducing the generation interval and accelerating genetic progress. In this paper, we discuss advancements in technologies used in the fertility evaluation of breeding animals, and the collection, processing, and preservation of the gametes. It is of utmost importance for the breeding industry to select dams and sires of the next generation as young as possible, as is the efficient and timely collection of gametes. There is a need for reliable and easily applicable methods to evaluate sexual maturity and fertility. Although gametes processing and preservation have been improved in recent decades, challenges are still encountered. The targeted use of sexed semen and beef semen has obliterated the production of surplus replacement heifers and bull calves from dairy breeds, markedly improving animal welfare and ethical considerations in production practices. Parallel with new technologies, many well-established technologies remain relevant, although with evolving applications. In vitro production (IVP) has become the predominant method of embryo production. Although fundamental improvements in IVP procedures have been established, the quality of IVP embryos remains inferior to their in vivo counterparts. Improvements to facilitate oocyte maturation and development of new culture systems, e.g. microfluidics, are presented in this paper. New non-invasive and objective tools are needed to select embryos for transfer. Cryopreservation of semen and embryos plays a pivotal role in the distribution of genetics, and we discuss the challenges and opportunities in this field. Finally, machine learning (ML) is gaining ground in agriculture and ART. This paper delves into the utilization of emerging technologies in ART, along with the current status, key challenges, and future prospects of ML in both research and practical applications within ART.

Targeting DNMT3A-mediated oxidative phosphorylation to overcome ibrutinib resistance in mantle cell lymphoma

The use of Bruton tyrosine kinase (BTK) inhibitors such as ibrutinib achieves a remarkable clinical response in mantle cell lymphoma (MCL). Acquired drug resistance, however, is significant and affects long-term survival of MCL patients. Here, we demonstrate that DNA methyltransferase 3A (DNMT3A) is involved in ibrutinib resistance. We find that DNMT3A expression is upregulated upon ibrutinib treatment in ibrutinib-resistant MCL cells. Genetic and pharmacological analyses reveal that DNMT3A mediates ibrutinib resistance independent of its DNA-methylation function. Mechanistically, DNMT3A induces the expression of MYC target genes through interaction with the transcription factors MEF2B and MYC, thus mediating metabolic reprogramming to oxidative phosphorylation (OXPHOS). Targeting DNMT3A with low-dose decitabine inhibits the growth of ibrutinib-resistant lymphoma cells both in vitro and in a patient-derived xenograft mouse model. These findings suggest that targeting DNMT3A-mediated metabolic reprogramming to OXPHOS with decitabine provides a potential therapeutic strategy to overcome ibrutinib resistance in relapsed/refractory MCL.

Computer-Aided Multiphoton Microscopy Diagnosis of 5 Different Primary Architecture Subtypes of Meningiomas

Meningiomas rank among the most common intracranial tumors, and surgery stands as the primary treatment modality for meningiomas. The precise subtyping and diagnosis of meningiomas, both before and during surgery, play a pivotal role in enabling neurosurgeons choose the optimal surgical program. In this study, we utilized multiphoton microscopy (MPM) based on 2-photon excited fluorescence and second-harmonic generation to identify 5 common meningioma subtypes. The morphological features of these subtypes were depicted using the MPM multichannel mode. Additionally, we developed 2 distinct programs to quantify collagen content and blood vessel density. Furthermore, the lambda mode of the MPM characterized architectural and spectral features, from which 3 quantitative indicators were extracted. Moreover, we employed machine learning to differentiate meningioma subtypes automatically, achieving high classification accuracy. These findings demonstrate the potential of MPM as a noninvasive diagnostic tool for meningioma subtyping and diagnosis, offering improved accuracy and resolution compared with traditional methods.

EARLY STAGES OF COLORECTAL CANCER CHARACTERIZATION BY AUTOFLUORESCENCE 3D MICROSCOPY: A PRELIMINARY STUDY

BACKGROUND

Colorectal cancer is one of the most prevalent pathologies worldwide whose prognosis is linked to early detection. Colonoscopy is the gold standard for screening, and diagnosis is usually made histologically from biopsies. Aiming to reduce the inspection and diagnostic time as well as the biopsies and resources involved, other techniques are being promoted to conduct accurate in vivo colonoscopy assessments. Optical biopsy aims to detect normal and neoplastic tissues analysing the autofluorescence spectrum based on the changes in the distribution and concentration of autofluorescent molecules caused by colorectal cancer. Therefore, the autofluorescence contribution analysed by image processing techniques could be an approach to a faster characterization of the target tissue.

OBJECTIVE

Quantify intensity parameters through digital processing of two data sets of three-dimensional widefield autofluorescence microscopy images, acquired by fresh colon tissue samples from a colorectal cancer murine model. Additionally, analyse the autofluorescence data to provide a characterization over a volume of approximately 50 µm of the colon mucosa for each image, at second (2nd), fourth (4th) and eighth (8th) weeks after colorectal cancer induction.

METHODS

Development of a colorectal cancer murine model using azoxymethane/dextran sodium sulphate induction, and data sets acquisition of Z-stack images by widefield autofluorescence microscopy, from control and colorectal cancer induced animals. Pre-processing steps of intensity value adjustments followed by quantification and characterization procedures using image processing workflow automation by Fiji's macros, and statistical data analysis.

RESULTS

The effectiveness of the colorectal cancer induction model was corroborated by a histological assessment to correlate and validate the link between histological and autofluorescence changes. The image digital processing methodology proposed was then performed on the three-dimensional images from control mice and from the 2nd, 4th, and 8th weeks after colorectal cancer chemical induction, for each data set. Statistical analyses found significant differences in the mean, standard deviation, and minimum parameters between control samples and those of the 2nd week after induction with respect to the 4th week of the first experimental study. This suggests that the characteristics of colorectal cancer can be detected after the 2nd week post-induction.

CONCLUSION

The use of autofluorescence still exhibits levels of variability that prevent greater systematization of the data obtained during the progression of colorectal cancer. However, these preliminary outcomes could be considered an approach to the three-dimensional characterization of the autofluorescence of colorectal tissue, describing the autofluorescence features of samples coming from dysplasia to colorectal cancer.

BACKGROUND

• A new digital image processing method was developed to measure intensity in 3D autofluorescence images of colorectal samples using a CRC mouse model.

BACKGROUND

• This method showed that autofluorescence intensity in colon mucosa is similar in healthy tissue but changes significantly in tumor development.

BACKGROUND

• Statistical analysis revealed CRC traits detectable from the second week post-induction, aiding in early CRC detection.

BACKGROUND

• The study provides a basis for 3D autofluorescence characterization in colorectal tissue from dysplasia to cancer, although variability in autofluorescence limits data systematization during cancer progression.

Cervical pre-cancer classification using entropic features and CNN: In vivo validation with a handheld fluorescence probe

Cervical cancer is one of the most prevalent forms of cancer, with a lengthy latent period and a gradual onset phase. Conventional techniques are found to be severely lacking in real time detection of disease progression which can greatly enhance the cure rate. Due to their high sensitivity and specificity, optical techniques are emerging as reliable tools, particularly in case of cancer. It has been seen that biochemical changes are better highlighted through intrinsic fluorescence devoid of interference from absorption and scattering. Its effectiveness in in-vivo conditions is affected by the fact that the intrinsic spectral signatures vary from patient to patient, as well as in different population groups. Here, we overcome this limitation by collectively enumerating the subtle changes in the spectral profiles and correlations through an information theory based entropic approach, which significantly amplifies the minute spectral variations. In conjunction with artificial intelligence (AI)/machine learning (ML) tools, it yields high specificity and sensitivity with a small dataset from patients in clinical conditions, without artificial augmentation. We have used an in-house developed handheld probe (i-HHP) for extracting intrinsic fluorescence spectra of human cervix from 110 different subjects drawn from diverse population groups. The average classification accuracy of the proposed methodology using 10-fold cross validation is 93.17%. A combination of polarised fluorescence spectra from i-HHP and the proposed classifier is proven to be minimally invasive with the ability to diagnose patients in real time. This paves the way for effective use of relatively smaller sized sensitive fluorescence data with advanced AI/ML tools for early cervical cancer detection in clinics.

5-ALA induced PpIX fluorescence spectroscopy in neurosurgery: a review

The review begins with an overview of the fundamental principles/physics underlying light, fluorescence, and other light-matter interactions in biological tissues. It then focuses on 5-aminolevulinic acid (5-ALA)-induced protoporphyrin IX (PpIX) fluorescence spectroscopy methods used in neurosurgery (e.g., intensity, time-resolved) and in so doing, describe their specific features (e.g., hardware requirements, main processing methods) as well as their strengths and limitations. Finally, we review current clinical applications and future directions of 5-ALA-induced protoporphyrin IX (PpIX) fluorescence spectroscopy in neurosurgery.

A blinded study using laser induced endogenous fluorescence spectroscopy to differentiate ex vivo spine tumor, healthy muscle, and healthy bone

Ten patients undergoing surgical resection for spinal tumors were selected. Samples of tumor, muscle, and bone were resected, de-identified by the treating surgeon, and then scanned with the TumorID technology ex vivo. This study investigates whether TumorID technology is able to differentiate three different human clinical fresh tissue specimens: spine tumor, normal muscle, and normal bone. The TumorID technology utilizes a 405 nm excitation laser to target endogenous fluorophores, thereby allowing for the detection of tissue based on emission spectra. Metabolic profiles of tumor and healthy tissue vary, namely NADH (bound and free emission peak, respectively: 487 nm, 501 nm) and FAD (emission peak: 544) are endogenous fluorophores with distinct concentrations in tumor and healthy tissue. Emission spectra analyzed consisted of 74 scans of spine tumor, 150 scans of healthy normal bone, and 111 scans of healthy normal muscle. An excitation wavelength of 405 nm was used to obtain emission spectra from tissue as previously described. Emission spectra consisted of approximately 1400 wavelength intensity pairs between 450 and 750 nm. Kruskal-Wallis tests were conducted comparing AUC distributions for each treatment group, α = 0.05. Spectral signatures varied amongst the three different tissue types. All pairwise comparisons among tissues for Free NADH were statistically significant (Tumor vs. Muscle: p = 0.0006, Tumor vs. Bone: p < 0.0001, Bone vs. Muscle: p = 0.0357). The overall comparison of tissues for FAD (506.5-581.5 nm) was also statistically significant (p < 0.0001), with two pairwise comparisons being statistically significant (Tumor vs. Muscle: p < 0.0001, Tumor vs. Bone: p = 0.0045, Bone vs. Muscle: p = 0.249). These statistically significant differences were maintained when stratifying tumor into metastatic carcinoma (N = 57) and meningioma (N = 17). TumorID differentiates tumor tissue from normal bone and normal muscle providing further clinical evidence of its efficacy as a tissue identification tool. Future studies should evaluate TumorID's ability to serve as an adjunctive tool for intraoperative assessment of surgical margins and surgical decision-making.

Femtosecond laser-induced fluorescence for rapid monitoring of cardiac troponin 1 as a cardiovascular disease biomarker

Medical diagnosis usually requires blood analysis of various biomarkers which are essential for disease detection and health status monitoring. Cardiac troponin 1 (cTn1) is a protein member of the cardiac troponin complex used for the diagnosis of several pathologies associated with cardiomyocyte necrosis. Laser-induced fluorescence (LIF) is a technique with high sensitivity and specificity, and it is one of the most significant developments used as an analytical tool for qualitative and quantitative analysis. The current study investigated the potential application of femtosecond LIF as a novel detection technique for rapid monitoring of cTn1 in clinical analysis. In the present study, the cTn1 (8 ng/ml) was excited over wavelengths ranging from 350 to 400 nm, and the LIF spectra were recorded. The results demonstrated that the maximum fluorescence intensity was observed at an excitation wavelength of 350 nm, with an emitted fluorescence peak centeredat 494 nm. At an excitation wavelength of 350 nm, different concentrations of cTn1 have been investigated and LIF spectra were obtained. The results revealed that the fluorescence peak intensity is concentration-dependent and increases linearly with increasing cTn1 concentration. These findings show that femtosecond LIF presents a unique, highly selective, precise, and direct approach to monitoring cTn1.

Effect of fluorescein dye concentration in oral cancer tissue: Statistical and spectroscopic analysis

Oral cancer screening with exogenous agents is highly demanding due to high sensitivity, as the early diagnosis plays a vital role in achieving favorable outcomes for oral squamous cell carcinomas (OSCC) by facilitating prompt detection and comprehensive surgical removal. Optical techniques utilizing the local application of fluorescein dye or fluorescence-guided surgery offer potential for early OSCC detection. The use of fluorescein dye in oral cancer is significantly less, and there is a need to inspect the local application of fluorescein dye in oral cancer patients. Concentration-based investigations of the dye with OSCC patients are essential to ensure accurate fluorescence-guided surgery and screening with fluorescein labeling and to mitigate possible adverse effects. Additionally, analyzing the dye distribution within OSCC tissues can provide insights into their heterogeneity, a critical indicator of malignancy. The present study includes a concentration-based statistical and spectroscopic analysis of fluorescein dye in ex-vivo and in-vivo OSCC patients. In the ex-vivo examination of OSCC tissues, five concentrations (18.66 ± 0.06, 9.51 ±    0.02, 6.38 ± 0.01, 4.80 ± 0.004, and 3.85 ± 0.002 millimolar) are employed for optical analysis. The ex-vivo OSCC tissues are analyzed for multiple statistical parameters at all concentrations, and the results are thoroughly described. Additionally, spectroscopic analysis is conducted on all concentrations for a comprehensive evaluation. Following optical analysis of all five concentrations in the ex-vivo study, two concentrations, 6.38 ± 0.01 and 4.80 ± 0.004 millimolar, are identified as suitable for conducting in-vivo investigations of oral cancer. A detailed spectroscopic and statistical study of OSCC tissues in-vivo has been done using these two concentrations.

Laser induced fluorescence spectroscopy analysis of kidney tissues: A pilot study for the identification of renal cell carcinoma

The 325 nm-excited autofluorescence spectra from cancerous and normal renal tissues were collected ex vivo biopsy tissue samples, through an optical fiber probe-based system. Noticeable changes in intensity/wavelength were observed in the fluorescence emissions from endogenous fluorophores such as collagen, Nicotinamide adenine dinucleotide (NADH), Vitamin A (retinol), and flavin adenine dinucleotide, in pathological conditions with respect to the normal state. The energy metabolism involved in clear cell renal cell carcinoma (ccRCC) and chromophobe renal cell carcinoma (chRCC) are reflected in the fluorescence emission band at 445 nm due to bound NADH attributed to enhanced oxidative phosphorylation in chRCC and emission at 465 nm contributed by free NADH showing higher glycolytic action in ccRCC. The principal component analysis and one-way ANOVA effectively discriminate ccRCC from chRCC. It is shown that laser induced fluorescence technique with 325 nm excitation can be a suitable technique for optical pathology and in vivo surgical boundary demarcation in renal cell carcinoma.

Advancing 2D fluorescence online monitoring in microtiter plates by separating scattered light and fluorescence measurement, using a tunable emission monochromator

Online fluorescence monitoring has become a key technology in modern bioprocess development, as it provides in-depth process knowledge at comparably low costs. In particular, the technology is widely established for high-throughput microbioreactor cultivation systems, due to its noninvasive character. For microtiter plates, previously also multi-wavelength 2D fluorescence monitoring was developed. To overcome an observed limitation of fluorescence sensitivity, this study presents a modified spectroscopic setup, including a tunable emission monochromator. The new optical component enables the separation of the scattered and fluorescent light measurements, which allows for the adjustment of integration times of the charge-coupled device detector. The resulting increased fluorescence sensitivity positively affected the performance of principal component analysis for spectral data of Escherichia coli batch cultivation experiments with varying sorbitol concentration supplementation. In direct comparison with spectral data recorded at short integration times, more biologically consistent signal dynamics were calculated. Furthermore, during partial least square regression for E. coli cultivation experiments with varying glucose concentrations, improved modeling performance was observed. Especially, for the growth-uncoupled acetate concentration, a considerable improvement of the root-mean-square error from 0.25 to 0.17 g/L was achieved. In conclusion, the modified setup represents another important step in advancing 2D fluorescence monitoring in microtiter plates.

Pancreatic Islet Viability Assessment Using Hyperspectral Imaging of Autofluorescence

Islets prepared for transplantation into type 1 diabetes patients are exposed to compromising intrinsic and extrinsic factors that contribute to early graft failure, necessitating repeated islet infusions for clinical insulin independence. A lack of reliable pre-transplant measures to determine islet viability severely limits the success of islet transplantation and will limit future beta cell replacement strategies. We applied hyperspectral fluorescent microscopy to determine whether we could non-invasively detect islet damage induced by oxidative stress, hypoxia, cytokine injury, and warm ischaemia, and so predict transplant outcomes in a mouse model. In assessing islet spectral signals for NAD(P)H, flavins, collagen-I, and cytochrome-C in intact islets, we distinguished islets compromised by oxidative stress (ROS) (AUC = 1.00), hypoxia (AUC = 0.69), cytokine exposure (AUC = 0.94), and warm ischaemia (AUC = 0.94) compared to islets harvested from pristine anaesthetised heart-beating mouse donors. Significantly, with unsupervised assessment we defined an autofluorescent score for ischaemic islets that accurately predicted the restoration of glucose control in diabetic recipients following transplantation. Similar results were obtained for islet single cell suspensions, suggesting translational utility in the context of emerging beta cell replacement strategies. These data show that the pre-transplant hyperspectral imaging of islet autofluorescence has promise for predicting islet viability and transplant success.

Intrinsic Fluorescence Markers for Food Characteristics, Shelf Life, and Safety Estimation: Advanced Analytical Approach

Food is a complex matrix of proteins, fats, minerals, vitamins, and other components. Various analytical methods are currently used for food testing. However, most of the used methods require sample preprocessing and expensive chemicals. New analytical methods are needed for quick and economic measurement of food quality and safety. Fluorescence spectroscopy is a simple and quick method to measure food quality, without sample preprocessing. This technique has been developed for food samples due to the application of a front-face measuring setup. Fluorescent compounds-fluorophores in the food samples are highly sensitive to their environment. Information about molecular structure and changes in food samples is obtained by the measurement of excitation-emission matrices of the endogenous fluorophores and by applying multivariate chemometric tools. Synchronous fluorescence spectroscopy is an advantageous screening mode used in food analysis. The fluorescent markers in food are amino acids tryptophan and tyrosine; the structural proteins collagen and elastin; the enzymes and co-enzymes NADH and FAD; vitamins; lipids; porphyrins; and mycotoxins in certain food types. The review provides information on the principles of the fluorescence measurements of food samples and the advantages of this method over the others. An analysis of the fluorescence spectroscopy applications in screening the various food types is provided.

Comparative study of in-vitro autofluorescence of normal versus non-melanoma-skin-cancer cells at different excitation wavelengths

In this experimental study the autofluorescence of squamous carcinoma cells, stimulated by 6 different excitation wavelengths in the range 280-533 nm, has been compared with the autofluorescence of normal control keratinocytes. Skin cells were cultivated in vitro, to isolate their characteristic autofluorescence form the more complex one that would be originated by the complete skin tissue. Autofluorescence spectra in the visible range were complemented by absorption measurements. It was observed that the control cells showed characteristic emission (and absorption) structures due to typical endogenous chromophores [FAD and NAD(P)H, lipo-pigments, porphyrins], that were severely dumped in pathological cells. The autofluorescence spectra were then elaborated by multivariate analysis: after a first exploratory data analysis by means of Principal Component Analysis, the whole dataset was used to develop classification models using partial least squares-discriminant analysis, to differentiate between normal and pathological cells. This permitted us to identify the most suitable fluorescence spectral interval, in the 550-670 nm range, to discriminate between normal and pathological behavior, independently on the excitation wavelength.

Point-of-care devices based on fluorescence imaging and spectroscopy for tumor margin detection during breast cancer surgery: Towards breast conservation treatment

OBJECTIVE

Fluorescence-based methods are highly specific and sensitive and have potential in breast cancer detection. Simultaneous fluorescence imaging and spectroscopy during intraoperative procedures of breast cancer have great advantages in detection of tumor margin as well as in classification of tumor to healthy tissues. Intra-operative real-time confirmation of breast cancer tumor margin is the aim of surgeons, and therefore, there is an urgent need for such techniques and devices which fulfill the surgeon's priorities.

METHODS

In this article, we propose the development of fluorescence-based smartphone imaging and spectroscopic point-of-care multi-modal devices for detection of invasive ductal carcinoma in tumor margin during removal of tumor. These multimodal devices are portable, cost-effective, noninvasive, and user-friendly. Molecular level sensitivity of fluorescence process shows different behavior in normal, cancerous and marginal tissues. We observed significant spectral changes, such as, red-shift, full-width half maximum (FWHM), and increased intensity as we go towards tumor center from normal tissue. High contrast in fluorescence images and spectra are also recorded for cancer tissues compared to healthy tissues. Preliminary results for the initial trial of the devices are reported in this article.

RESULTS

A total 44 spectra from 11 patients of invasive ductal carcinoma (11 spectra for invasive ductal carcinoma and rest are normal and negative margins) are used. Principle component analysis is used for the classification of invasive ductal carcinoma with an accuracy of 93%, specificity of 75% and sensitivity of 92.8%. We obtained an average 6.17 ± 1.66 nm red shift for IDC with respect to normal tissue. The red shift and maximum fluorescence intensity indicates p < 0.01. These results described here are supported by histopathological examination of the same sample.

CONCLUSION

In the present manuscript, simultaneous fluorescence-based imaging and spectroscopy is accomplished for the classification of IDC tissues and breast cancer margin detection.

Dual-Fluorophore and Dual-Site Multifunctional Fluorescence Sensor for Visualizing the Metabolic Process of GHS to SO2 and the SO2 Toxicological Mechanism by Two-Photon Imaging

As a momentous gas signal molecule, sulfur dioxide (SO₂) participates in diverse physiological activities. Excess SO₂ will cause an apparent decrease in the level of intracellular glutathione (GSH), thereby damaging the body's antioxidant defense system. In addition, endogenous SO₂ can be generated from GSH by reacting with thiosulfate (S₂O₃^2-) and enzymatically reduced to cysteine (Cys), a synthetic precursor of GSH. In view of their close correlation, a two-photon (TP) mitochondria-targeted multifunctional fluorescence sensor Mito-Na-BP was rationally designed and synthesized for detecting SO₂ and GSH simultaneously. Under single-wavelength excitation, the sensor responded to GSH-SO₂ and SO₂-GSH continuously with blue-shifted and green fluorescence-enhanced signal modes, respectively, not just to GSH (enhanced) and SO₂ (quenched) at 638 nm with a completely converse response tendency. Given its favorable spectral performance (high sensitivity, superior selectivity, and fast response rate) at physiological pH, Mito-Na-BP has been successfully applied in monitoring the level fluctuation of GSH affected from high-dose SO₂ and visualizing in real time the metabolic process of GSH to SO₂ by TP imaging. It is expected that this research will provide a convenient and efficient tool for elucidating intricate relationships of GSH and SO₂ and facilitate further exploration of their functions in biomedicine.

Screening of neoplastic diseases by statistical analysis of urine fluorescence spectroscopic data. Application of multivariate techniques for enhancing classification

The composition of human fluids is modified during the course of neoplastic diseases. Urine analysis offers the advantage of being a noninvasive method for which samples are easily and routinely collected from patients. In this work, urine fluorescence spectra recorded upon excitation at 405 nm were obtained from healthy volunteers and individuals with different oncologic pathologies. A large number of indexes, i.e., parameters obtained from spectral data which assist spectral features characterization, were developed to classify healthy and pathological populations. The discrimination ability of simple predictive indexes, obtained from spectra pretreated with different normalization procedures and by taking their derivatives, was statistically assessed. In addition, multivariate methods, such as principal component analysis and multivariate curve resolution by alternating least squares, were used to develop more elaborate indexes for distinguishing between healthy and pathological populations. All indexes were systematically evaluated on a statistical basis by in lab-developed routines capable of detecting outliers, judging the normal distribution of the indexes, evaluating variance homogeneity, testing the difference between the means of healthy and pathological populations, as well as performing a receiver operator curve analysis to assess the classification power of each index. Those indexes with the best performances were further combined to perform a linear discriminant analysis, which yielded a powerful classification algorithm with an area under the receiver operator curve of 0.986, a sensitivity of 97.7%, a specificity of 100%, and an overall accuracy of 98.8%. The present study shows that the statistical analysis of urine fluorescence data with a proper combination of multivariate techniques bears a high potential to develop massive screening tests for the early detection of oncologic pathologies.

Solvent-Dependent Fluorescence Properties of CH2-bis(BODIPY)s

Biocompatible luminophores based on organic dyes, which have fluorescence characteristics that are highly sensitive to the properties of the solvating medium, are of particular interest as highly sensitive, selective, and easy-to-use analytical agents. We found that BODIPY dimers (2,2'-, 2,3'-3,3'-CH₂-bis(BODIPY) (1-3)) demonstrate fluorescence characteristics with a high sensitivity to the presence of polar solvents. The intense fluorescence of 1-3 in nonpolar/low-polarity solvents is dramatically quenched in polar media (acetone, DMF, and DMSO). It has been established that the main reason for CH₂-bis(BODIPY) fluorescence quenching is the specific solvation of dyes by electron-donating molecules (Solv) with the formation of stable supramolecular CH₂-bis(BODIPY)·2Solv structures. Using steady-state absorption and fluorescence spectroscopy, time-resolved fluorescence spectroscopy, and computational modeling, the formation mechanism, composition, and structure of CH₂-bis(BODIPY)·2Solv supramolecular complexes have been substantiated, and their stability has been evaluated. The results show the promise of developing fluorescent probes based on CH₂-bis(BODIPY)s for detecting toxic N/O-containing compounds in solutions.

Online 2D Fluorescence Monitoring in Microtiter Plates Allows Prediction of Cultivation Parameters and Considerable Reduction in Sampling Efforts for Parallel Cultivations of Hansenula polymorpha

Multi-wavelength (2D) fluorescence spectroscopy represents an important step towards exploiting the monitoring potential of microtiter plates (MTPs) during early-stage bioprocess development. In combination with multivariate data analysis (MVDA), important process information can be obtained, while repetitive, cost-intensive sample analytics can be reduced. This study provides a comprehensive experimental dataset of online and offline measurements for batch cultures of Hansenula polymorpha. In the first step, principal component analysis (PCA) was used to assess spectral data quality. Secondly, partial least-squares (PLS) regression models were generated, based on spectral data of two cultivation conditions and offline samples for glycerol, cell dry weight, and pH value. Thereby, the time-wise resolution increased 12-fold compared to the offline sampling interval of 6 h. The PLS models were validated using offline samples of a shorter sampling interval. Very good model transferability was shown during the PLS model application to the spectral data of cultures with six varying initial cultivation conditions. For all the predicted variables, a relative root-mean-square error (RMSE) below 6% was obtained. Based on the findings, the initial experimental strategy was re-evaluated and a more practical approach with minimised sampling effort and elevated experimental throughput was proposed. In conclusion, the study underlines the high potential of multi-wavelength (2D) fluorescence spectroscopy and provides an evaluation workflow for PLS modelling in microtiter plates.

Development of multimodal micro-endoscopic system with oblique illumination for simultaneous fluorescence imaging and spectroscopy of oral cancer

Multimodality of an optical system implies the use of one or more optical techniques to improve the system's overall performance and maximum utility. In this article, we demonstrate a multimodal system with oblique illumination that combines two different techniques; fluorescence micro-endoscopy and spectroscopy simultaneously and can be utilized to obtain diverse information from the same location of biological sample. In present system, use of graded index (GRIN) rod-lens makes it highly compact and oblique incidence decouples illumination geometry with collection geometry, preventing CCD cameras from saturation and reduces number of optical elements, thereby making system further miniaturized and field-portable. It also overcomes the disadvantages of undesired reflections from different optical elements. The experimental results of simultaneous imaging and spectroscopy of the biological samples are presented along with quantitative spectroscopic parameters; peak wavelength shift, area under the curve and full width half maximum (FWHM). The spatial resolution, spectral resolution and field of view of the system are found to be 4.38 μm, 0.5 nm and 2.071×1.548mm2 , respectively. Furthermore, we have obtained the red shift for cancerous oral tissue with respect to normal oral tissue 5.79 ± 1.071 nm. This could be important indicator for oral cancer screening.

Pterygium and Ocular Surface Squamous Neoplasia: Optical Biopsy Using a Novel Autofluorescence Multispectral Imaging Technique

In this study, differentiation of pterygium vs. ocular surface squamous neoplasia based on multispectral autofluorescence imaging technique was investigated. Fifty (N = 50) patients with histopathological diagnosis of pterygium (PTG) and/or ocular surface squamous neoplasia (OSSN) were recruited. Fixed unstained biopsy specimens were imaged by multispectral microscopy. Tissue autofluorescence images were obtained with a custom-built fluorescent microscope with 59 spectral channels, each with specific excitation and emission wavelength ranges, suitable for the most abundant tissue fluorophores such as elastin, flavins, porphyrin, and lipofuscin. Images were analyzed using a new classification framework called fused-classification, designed to minimize interpatient variability, as an established support vector machine learning method. Normal, PTG, and OSSN regions were automatically detected and delineated, with accuracy evaluated against expert assessment by a specialist in OSSN pathology. Signals from spectral channels yielding signals from elastin, flavins, porphyrin, and lipofuscin were significantly different between regions classified as normal, PTG, and OSSN (p < 0.01). Differential diagnosis of PTG/OSSN and normal tissue had accuracy, sensitivity, and specificity of 88 ± 6%, 84 ± 10% and 91 ± 6%, respectively. Our automated diagnostic method generated maps of the reasonably well circumscribed normal/PTG and OSSN interface. PTG and OSSN margins identified by our automated analysis were in close agreement with the margins found in the H&E sections. Such a map can be rapidly generated on a real time basis and potentially used for intraoperative assessment.

Fluorescence lifetime needle optical biopsy discriminates hepatocellular carcinoma

This work presents results of in vivo and in situ measurements of hepatocellular carcinoma by a developed optical biopsy system. Here, we describe the technical details of the implementation of fluorescence lifetime and diffuse reflectance measurements by the system, equipped with an original needle optical probe, compatible with the 17.5G biopsy needle standard. The fluorescence lifetime measurements observed by the setup were verified in fresh solutions of NADH and FAD⁺⁺, and then applied in a murine model for the characterisation of inoculated hepatocellular carcinoma (HCC) and adjacent liver tissue. The technique, applied in vivo and in situ and supplemented by measurements of blood oxygen saturation, made it possible to reveal statistically significant transformation in the set of measured parameters linked with the cellular pools of NADH and NADPH. In the animal model, we demonstrate that the characteristic changes in registered fluorescent parameters can be used to reliably distinguish the HCC tissue, liver tissue in the control, and the metabolically changed liver tissues of animals with the developed HCC tumour. For further transition to clinical applications, the optical biopsy system was tested during the routing procedure of the PNB in humans with suspected HCC. The comparison of the data from murine and human HCC tissues suggests that the tested animal model is generally representative in the sense of the registered fluorescence lifetime parameters, while statistically significant differences between their absolute values can still be observed.

UV excited fluorescence image-based non-destructive method for early detection of strawberry (Fragaria × ananassa) spoilage

The soon spoiled strawberries need to be classified from healthy fruits in an early stage. In this research, a machine vision system is proposed for inspecting the quality of strawberries using ultraviolet (UV) light based on the excitation-emission matrix (EEM) results. Among the 100 fruits which were harvested and stored under 10 °C condition for 7 days, 7 fruits were confirmed to be spoiled by using a firmness meter. The EEM results show the fluorescence compound contributes to a whitish surface on the spoiled fruits. Based on the EEM results, UV fluorescence images from the bottom view of strawberries were used to classify the spoiled fruits and healthy fruits within 1 day after harvest. These results demonstrate the UV fluorescence imaging can be a fast, non-destructive, and low-cost method for inspecting the soon spoiled fruits. The proposed index related to the spoiling time can be a new indicator for qualifying strawberry.

Three-dimensional morphological characterization of colorectal pits from label-free microscopy images

The prognosis of colorectal cancer (CRC), one of the most prevalent pathologies worldwide, is linked to early detection. Kudo's pit pattern classification states morphological pit patterns of the Lieberkühn crypts by analyzing the superficial mucosa, predicting the histology of colorectal lesions. Its use as a highly accurate two-dimensional diagnostic criterion has increased, mostly involving expert endoscopists' judgment. The processing of autofluorescence images could allow the diagnostic, bypassing staining techniques and decreasing the biopsies, resources and times involved in the inspection. That criterion could be extended by data of the pit three-dimensional (3D) morphology. Thus, this work was aimed at obtaining 3D morphological information by quantifying geometrical and shape descriptors through software processing and analysis of widefield autofluorescence microscopy image stacks acquired by fresh colon tissue samples from a murine model of CRC. Statistical analyses included pits from control mice and from the second (2nd), fourth (4th), and eighth (8th) weeks of treatment. Statistically significant differences were found for almost all parameters between the pits from control and from the 4th treated week, stating that the major morphological changes begin after the 2nd week. In particular, pits from control or initial treatment time points were more tubular, straighter and less rough than the ones from later treatment points. Therefore, they may be more associated to normal or non-neoplastic crypt lumens than linked to adenomas or even cancer crypts. These preliminary outcomes could be considered an advance in 3D pit morphology characterization.

Information entropy of quantitative chemometric endogenous fluorescence improves photonic lung cancer diagnosis

Quantitative chemometric widefield endogenous fluorescence microscopy (CFM) maps the endogenous absolute chromophore concentration and spatial distribution in cells and tissue sections label-free from fluorescence color images under broadband excitation and detection. By quantifying the endogenous chromophores, including tryptophan, elastin, reduced nicotinamide adenine dinucleotide [NAD(P)H], and flavin adenine dinucleotide (FAD), CFM reveals the biochemical environment and subcellular structure. Here we show that the chromophore information entropy, marking its spatial distribution pattern of quantitative chemometric endogenous fluorescence at the microscopic scale, improves photonic lung cancer diagnosis with independent diagnostic power to the cellular metabolism biomarker. NAD(P)H and FAD's information entropy is found to decrease from normal to perilesional to cancerous tissue, whereas the information entropy for the redox ratios [FAD/tryptophan and FAD/NAD(P)H] is smaller for the normal tissue than both perilesional and cancerous tissue. CFM imaging of the specimen's inherent biochemical and structural properties eliminates the dependence on measurement details and facilitates robust, accurate diagnosis. The synergy of quantifying absolute chromophore concentration and information entropy achieves high accuracies for a three-class classification of lung tissue into normal, perilesional, and cancerous ones and a three-class classification of lung cancers into grade 1, grade 2, and grade 3 using a support vector machine, outperforming the chromophore concentration biomarkers.

Preoperative AI-Driven Fluorescence Diagnosis of Non-Melanoma Skin Cancer

The diagnosis and treatment of non-melanoma skin cancer remain urgent problems. Histological examination of biopsy material—the gold standard of diagnosis—is an invasive procedure that requires a certain amount of time to perform. The ability to detect abnormal cells using fluorescence spectroscopy (FS) has been shown in many studies. This technique is rapidly expanding due to its safety, relative cost-effectiveness, and efficiency. However, skin lesion FS-based diagnosis is challenging due to a number of single overlapping spectra emitted by fluorescent molecules, making it difficult to distinguish changes in the overall spectrum and the molecular basis for it. We applied deep learning (DL) algorithms to quantitatively assess the ability of FS to differentiate between pathologies and normal skin. A total of 137 patients with various forms of primary and recurrent basal cell carcinoma (BCC) were observed by a multispectral laser-based device with a built-in neural network (NN) “DSL-1”. We measured the fluorescence spectra of suspected non-melanoma skin cancers and compared them with “normal” skin spectra. These spectra were input into DL algorithms to determine whether the skin is normal, pigmented normal, benign, or BCC. The preoperative differential AI-driven fluorescence diagnosis method correctly predicted the BCC lesions. We obtained an average sensitivity of 62% and average specificity of 83% in our experiments. Thus, the presented “DSL-1” diagnostic device can be a viable tool for the real-time diagnosis and guidance of non-melanoma skin cancer resection.

Parameters to identify good quality oocytes and embryos in cattle

Oocyte/embryo selection methodologies are either invasive or noninvasive and can be applied at various stages of development from the oocyte to cleaved embryos and up to the blastocyst stage. Morphology and the proportion of embryos developing to the blastocyst stage are important criteria to assess developmental competence. Evaluation of morphology remains the method of choice for selecting viable oocytes for IVP or embryos prior to transfer. Although non-invasive approaches are improving, invasive ones have been extremely helpful in finding candidate genes to determine oocyte/embryo quality. There is still a strong need for further refinement of existing oocyte and embryo selection methods and quality parameters. The development of novel, robust and non-invasive procedures will ensure that only embryos with the highest developmental potential are chosen for transfer. In the present review, various methods for assessing the quality of oocytes and preimplantation embryos, particularly in cattle, are considered. These methods include assessment of morphology including different staining procedures, transcriptomic and proteomic analyses, metabolic profiling, as well as the use of artificial intelligence technologies.

Raman and Fluorescence Profiles Modifications of Muscular and Adipose Tissues Exposed to Low Energy X-ray Beams

This work aims to investigate changes induced by low-energy radiation in adipose and muscular tissues employing autofluorescence and Raman spectroscopic techniques. X-ray beams expositions with 25 and 35 kV at 0.11, 1.1, and 2.1 Gy radiation dose levels were applied. Changes in Raman line intensities at specific bands assigned to collagen, proteins, and lipids were observed. Autofluorescent analysis exhibit variations in the collagen and nicotinamide adenine dinucleotide emission (NADH), resulting from the structural modifications, variations on the reduced/oxidized fluorophores equilibrium followed by radiation exposure. Results show that Raman and fluorescence spectroscopy are suitable techniques to evaluate radiation effects on biomolecules even at low radiation doses and energies.

Simulations of fluorescence imaging in the oral cavity

We describe an end-to-end image systems simulation that models a device capable of measuring fluorescence in the oral cavity. Our software includes a 3D model of the oral cavity and excitation-emission matrices of endogenous fluorophores that predict the spectral radiance of oral mucosal tissue. The predicted radiance is transformed by a model of the optics and image sensor to generate expected sensor image values. We compare simulated and real camera data from tongues in healthy individuals and show that the camera sensor chromaticity values can be used to quantify the fluorescence from porphyrins relative to the bulk fluorescence from multiple fluorophores (elastin, NADH, FAD, and collagen). Validation of the simulations supports the use of soft-prototyping in guiding system design for fluorescence imaging.

Differences in Spectroscopic Properties of Saliva Taken From Normal Subjects and Oral Cancer Patients: Comparison Studies

Oral cancer disease is among the most common cancers in the world and are associated with mortality and morbidity. The characterization of saliva samples may help to distinguish patients with oral cancer disease from normal subjects. To characterize spectra of saliva samples from normal subjects and oral cancer patients by use of fluorescence, absorption, and 1H-NMR spectroscopy. Whole unstimulated saliva samples were collected from patients with oral cancer disease and normal subjects. The saliva samples were analyzed by absorption, fluorescence and 1H-NMR spectroscopic techniques. The characteristic spectra of saliva samples from patients with oral cancer disease and normal subjects were compared. For fluorescence spectroscopic studies, six fluorophores were found in saliva samples. Autofluorescence emission spectra and synchronous spectra of saliva were different between normal subjects and oral cancer patients. For absorption spectroscopic studies, the typical absorption spectra of saliva samples from normal subjects and oral cancer patients were also different in absorption intensity, 1st and 2nd derivative of absorption spectra values. For 1H-NMR studies, nine metabolites and four metabolites were found in saliva samples taken from normal subjects and oral cancer patients, respectively. The metabolic profiles of saliva samples from normal subjects and oral cancer patients were not similar. The characteristic spectra of saliva samples from normal subjects and oral cancer patients were found. These results showed differences in the spectra of saliva samples between both that groups. The spectra from each spectroscopic techniques could determine a candidate saliva biomarkers for distinguishing patients with oral cancer disease from normal subjects.

Intravital Metabolic Autofluorescence Imaging Captures Macrophage Heterogeneity Across Normal and Cancerous Tissue

Macrophages are dynamic immune cells that govern both normal tissue function and disease progression. However, standard methods to measure heterogeneity in macrophage function within tissues require tissue excision and fixation, which limits our understanding of diverse macrophage function in vivo. Two-photon microscopy of the endogenous metabolic co-enzymes NAD(P)H and flavin adenine dinucleotide (FAD) (metabolic autofluorescence imaging) enables dynamic imaging of mouse models in vivo. Here, we demonstrate metabolic autofluorescence imaging to assess cell-level macrophage heterogeneity in response to normal and cancerous tissue microenvironments in vivo. NAD(P)H and FAD fluorescence intensities and lifetimes were measured for both tissue-resident macrophages in mouse ear dermis and tumor-associated macrophages in pancreatic flank tumors. Metabolic and spatial organization of macrophages were determined by performing metabolic autofluorescence imaging and single macrophage segmentation in mice engineered for macrophage-specific fluorescent protein expression. Tumor-associated macrophages exhibited decreased optical redox ratio [NAD(P)H divided by FAD intensity] compared to dermal macrophages, indicating that tumor-associated macrophages are more oxidized than dermal macrophages. The mean fluorescence lifetimes of NAD(P)H and FAD were longer in dermal macrophages than in tumor-associated macrophages, which reflects changes in NAD(P)H and FAD protein-binding activities. Dermal macrophages had greater heterogeneity in optical redox ratio, NAD(P)H mean lifetime, and FAD mean lifetime compared to tumor-associated macrophages. Similarly, standard markers of macrophage phenotype (CD206 and CD86) assessed by immunofluorescence revealed greater heterogeneity in dermal macrophages compared to tumor-associated macrophages. Ultimately, metabolic autofluorescence imaging provides a novel tool to assess tissue-specific macrophage behavior and cell-level heterogeneity in vivo in animal models.

Cancerous Tissue Diagnosis by LIF Spectroscopy Derived From Body-Compatible Fluorophores

Introduction: The laser-induced fluorescence (LIF) method as molecular emission spectroscopy is used to diagnose cancerous tissues. According to the previous reports, the red-shift in the fluorescence spectrum from Rhodamine 6G (Rd6G)-stained cancerous tissues compared to healthy ones impregnated with the same dye provides the feasibility for diagnosis. In this paper, we have employed the LIF emissions as a diagnostic method to distinguish between cancerous and healthy tissues infiltrated by a body-compatible fluorophore to avoid the toxicity and hazard of Rd6G dye. Methods: Biological tissue specimens are stained with sodium fluorescein (NaFl) dye and then irradiated by the blue CW diode laser (405 nm) to examine the spectral properties that are effective in detecting cancerous tissues. Results: The spectral shift and the intensity difference of fluorescence are keys to diagnosing in vitro cancerous breast, colon, and thyroid tissues for clinical applications. The notable tubular densities in the breast and colon tissues and the space between the papillae in the thyroid ones cause the cancerous tissues to be prominently heterogeneous, providing numerous micro-cavities and thus more room for dye molecules. Conclusion: Here, we have assessed the spectral shift and intensity difference of fluorescence as a diagnostic method to distinguish between cancerous and healthy tissues for clinical applications.

Use of digital photography to identify neoplastic skin lesions after labelling by ALA-derived protoporphyrin

Actinic keratosis is a premalignant skin lesion that develops into non-melanoma skin cancer. Various imaging techniques have been developed to find the actinic keratosis lesion. In this clinical study, the feasibility of a nonspectroscopic fluorescence imaging system is investigated for spatial assessment of the actinic keratosis lesion. Six patients between the ages of 70 and 80 years old are diagnosed with actinic keratosis by a board-certified dermatologist to obtain biopsy-proven clinical images. The patients were treated with 5-aminolevulinic acid, which is transformed into the protoporphyrin IX. After illuminating ultraviolet-A light on facial lesions, the protoporphyrin IX produces the exogenous fluorescence. The fluorescence is measured using both a hyperspectral camera and an RGB color camera to obtain spectroscopic and nonspectroscopic fluorescence images, respectively. It is found that fluorescence intensity of the actinic keratosis lesion is higher than that of normal skin. Based on combined fluorescence and physiological characteristics, the actinic keratosis lesion is distinguished from the adjacent normal skin area. For delineation of the actinic keratosis lesion, a linear unmixing algorithm is applied to spectroscopic image data and an erythema index is calculated from nonspectroscopic image data. Then, two extracted actinic keratosis lesions are compared for cross-validation. As a result, both spectroscopic and nonspectroscopic fluorescence images demarcate an identical lesion of actinic keratosis. Given the affordability and simplicity, an RGB camera and a 5-ALA photosensitizer can be used as a cost-effective nonspectroscopic imaging modality for accurate assessment of actinic keratosis margins.

Combined total internal reflection AF spectral-imaging and Raman spectroscopy for fast assessment of surgical margins during breast cancer surgery

The standard treatment for breast cancer is surgical removal mainly through breast-conserving surgery (BCS). We developed a new technique based on auto-fluorescence (AF) spectral imaging and Raman spectroscopy for fast intraoperative assessment of excision margins in BCS. A new wide-field AF imaging unit based on total internal reflection (TIR) was combined with a Raman spectroscopy microscope equipped with a 785 nm laser. The wavelength of the AF excitation was optimized to 365 nm in order to maximize the discrimination of adipose tissue. This approach allows for the non-adipose regions of tissue, which are at a higher risk of containing a tumor, to be targeted more efficiently by the Raman spectroscopy measurements. The integrated TIR-AF-Raman was tested on small tissue samples as well as fresh wide local excisions, delivering the analysis of the entire cruciate surface of BCS specimens (5.1 × 7.6 cm²) in less than 45 minutes and also providing information regarding the location of the tumor in the specimen. Full automation of the instrument and selection of a faster translation stage would allow for the measurement of BCS specimens within an intraoperative time scale (20 minutes). This study demonstrates that the TIR-AF Raman microscope represents a feasible step towards the development of a technique for intraoperative assessment of large WLE within intraoperative timescales.

Fluorescence and Multiphoton Imaging for Tissue Characterization of a Model of Postmenopausal Ovarian Cancer

BACKGROUND AND OBJECTIVES

To determine the efficacy of targeted fluorescent biomarkers and multiphoton imaging to characterize early changes in ovarian tissue with the onset of cancer.

STUDY DESIGN/MATERIALS AND METHODS

A transgenic TgMISIIR-TAg mouse was used as an animal model for ovarian cancer. Mice were injected with fluorescent dyes to bind to the folate receptor α, matrix metalloproteinases, and integrins. Half of the mice were treated with 4-vinylcyclohexene diepoxide (VCD) to simulate menopause. Widefield fluorescence imaging (WFI) and multiphoton imaging of the ovaries and oviducts were conducted at 4 and 8 weeks of age. The fluorescence signal magnitude was quantified, and texture features were derived from multiphoton imaging. Linear discriminant analysis was then used to classify mouse groups.

RESULTS

Imaging features from both fluorescence imaging and multiphoton imaging show significant changes (P < 0.01) with age, VCD treatment, and genotype. The classification model is able to classify different groups to accuracies of 75.53%, 69.53%, and 86.76%, for age, VCD treatment, and genotype, respectively. Building a classification model using features from multiple modalities shows marked improvement over individual modalities.

CONCLUSIONS

This study demonstrates that using WFI with targeted biomarkers, and multiphoton imaging with endogenous contrast shows promise for detecting early changes in ovarian tissue with the onset of cancer. The results indicate that multimodal imaging can provide higher sensitivity for classifying tissue types than using single modalities alone. Lasers Surg. Med. © 2020 Wiley Periodicals, Inc.

Multimodal widefield fluorescence imaging with nonlinear optical microscopy workflow for noninvasive oral epithelial neoplasia detection: a preclinical study

SIGNIFICANCE

Early detection of epithelial cancers and precancers/neoplasia in the presence of benign lesions is challenging due to the lack of robust in vivo imaging and biopsy guidance techniques. Label-free nonlinear optical microscopy (NLOM) has shown promise for optical biopsy through the detection of cellular and extracellular signatures of neoplasia. Although in vivo microscopy techniques continue to be developed, the surface area imaged in microscopy is limited by the field of view. FDA-approved widefield fluorescence (WF) imaging systems that capture autofluorescence signatures of neoplasia provide molecular information at large fields of view, which may complement the cytologic and architectural information provided by NLOM.

AIM

A multimodal imaging approach with high-sensitivity WF and high-resolution NLOM was investigated to identify and distinguish image-based features of neoplasia from normal and benign lesions.

APPROACH

In vivo label-free WF imaging and NLOM was performed in preclinical hamster models of oral neoplasia and inflammation. Analyses of WF imaging, NLOM imaging, and dual modality (WF combined with NLOM) were performed.

RESULTS

WF imaging showed increased red-to-green autofluorescence ratio in neoplasia compared to inflammation and normal oral mucosa (p  <  0.01). In vivo assessment of the mucosal tissue with NLOM revealed subsurface cytologic (nuclear pleomorphism) and architectural (remodeling of extracellular matrix) atypia in histologically confirmed neoplastic tissue, which were not observed in inflammation or normal mucosa. Univariate and multivariate statistical analysis of macroscopic and microscopic image-based features indicated improved performance (94% sensitivity and 97% specificity) of a multiscale approach over WF alone, even in the presence of benign lesions (inflammation), a common confounding factor in diagnostics.

CONCLUSIONS

A multimodal imaging approach integrating strengths from WF and NLOM may be beneficial in identifying oral neoplasia. Our study could guide future studies on human oral neoplasia to further evaluate merits and limitations of multimodal workflows and inform the development of multiscale clinical imaging systems.

Non-Invasive Diagnostic System Based on Light for Detecting Early-Stage Oral Cancer and High-Risk Precancerous Lesions-Potential for Dentistry

Simple Summary

The early detection of oral cancer and oral potentially malignant disorders can facilitate minimum intervention and subsequent improvements in prognosis and quality of life after treatment. Recently, several non-invasive adjunctive fluorescence-based detection systems have improved the accuracy of detection and diagnosis of oral cancer and oral potentially malignant disorders. This article summarizes current knowledge about fluorescence-based diagnostic methods and discusses their benefits and drawbacks from a clinical viewpoint.

Abstract

Oral health promotion and examinations have contributed to the early detection of oral cancer and oral potentially malignant disorders, leading to the adaptation of minimally invasive therapies and subsequent improvements in the prognosis/maintenance of the quality of life after treatments. However, the accurate detection of early-stage oral cancer and oral epithelial dysplasia is particularly difficult for conventional oral examinations because these lesions sometimes resemble benign lesions or healthy oral mucosa tissues. Although oral biopsy has been considered the gold standard for accurate diagnosis, it is deemed invasive for patients. For this reason, most clinicians are looking forward to the development of non-invasive diagnostic technologies to detect and distinguish between cancerous and benign lesions. To date, several non-invasive adjunctive fluorescence-based detection systems have improved the accuracy of the detection and diagnosis of oral mucosal lesions. Autofluorescence-based systems can detect lesions as a loss of autofluorescence through irradiation with blue-violet lights. Photodynamic diagnosis using 5-aminolevulinic acid (ALA-PDD) shows the presence of very early oral cancers and oral epithelial dysplasia as a red fluorescent area. In this article, currently used fluorescence-based diagnostic methods are introduced and discussed from a clinical point of view.

Molecular margins in head and neck cancer: Current techniques and future directions

Complete tumor extirpation with clear surgical margins remains a central tenet of oncologic head and neck surgery. Rates of locoregional recurrence and survival are both significantly worse when clear margins are unable to be obtained. Current clinical practice relies on the use of frozen sections intra-operatively, followed by traditional histopathologic analysis post-operatively to assess the surgical margin. However, with improved understanding of tumor biology and advances in technology, new techniques have emerged to analyze margins at a molecular level. Such molecular margin analysis interrogates tissue for genetic, epigenetic, or proteomic changes that may belie tumor presence or aggressive features not captured by standard histopathologic techniques. Intra-operatively, this information may be used to guide resection, while post-operatively, it may help to stratify patients for adjuvant treatment. In this review, we summarize the current state of molecular margin analysis and describe directions for future research.

Real time detection and characterisation of bioaerosol emissions from wastewater treatment plants

Bioaerosol emissions from wastewater treatment plants may pose adverse health impact on workers and nearby communities. To detect and characterise bioaerosol emissions from wastewater treatment plant (WWTP), a novel real-time bioaerosol sensor, Spectral Intensity Bioaerosol Sensor (SIBS) was employed at a WWTP and a background site. The SIBS records a range of data (size, shape, and fluorescence emission across 16 wavelength bands from 298 to 735 nm for two excitation wavelengths (285 nm and 370 nm)) on single particles in real time. Additionally, excitation-emission matrix (EEM) of wastewater samples obtained by a spectrofluorometer was compared with SIBS spectra from WWTP. The results showed that the average number concentrations of total particles (NT) and fluorescence particles (NF) were both higher at the WWTP (NT = 2.01 cm^-3, NF = 1.13 cm^-3) than the background site (NT = 1.79 cm^-3, NF = 1.01 cm^-3). The temporal variation of NF and NT was highly variable at the WWTP and the concentration peaks were consistent with on-site activities. Moreover, the time-resolved number-size distribution of fluorescent particles revealed the predominance of fine scale particles (<1 μm) and the time-series channel by channel number concentrations demonstrated the temporal variability of dominant bio-fluorophores. Furthermore, the overall and size-segregated fluorescence spectra at two sites were multimodal. In particular, the fluorescence intensity increases with increasing particle size in WWTP spectra, which is not present in the background spectra. In addition, the highly resolved SIBS fluorescence spectra were broadly similar to EEM of wastewater. These findings confirmed that the spectrally resolved fluorescence detected by SIBS is capable of providing reliable bio-fluorophores information of bioaerosol emissions generated from wastewater, thus holding the potential for better characterisation of bioaerosols in real time.

An experimental and algorithm-based study of the spectral features of breast cancer patients by a photodiagnosis approach

In the present study, the spectral diagnosis of blood plasma samples of breast cancer patients and an equal number of normal controls was investigated. A set of ratio parameters was acquired by employing SXS and FES. The samples were also analyzed statistically by employing Welch two-sample t-tests, and the effects of three ratio parameters, R₁, R₂, and R₃, were also studied by plotting them against the subject numbers. A linear discriminant was also applied to verify the exact classification of normal control and breast cancer patients. It was observed that the levels of biofluorophores such as porphyrin, NADH, tryptophan and flavins were elevated 2- to 3-fold for breast cancer patients compared to normal controls, with an accuracy of approximately 100 %. We have also confirmed the validity of the obtained experimental results by using an advanced robust diagnostic algorithm. The experimental results of the current study may have a vital and substantial impact on the detection and screening protocols used for future breast cancer patients. The spectral analysis of body fluid could be of great value to add to and enhance the current procedures with an accuracy of approximately 100 % with limited number of samples. The results and objectives of this preliminary study were encouraging and useful for the discrimination of the features of breast cancer patients compared to those of normal controls.

Real-time multispectral fluorescence lifetime imaging using Single Photon Avalanche Diode arrays

Autofluorescence spectroscopy has emerged in recent years as a powerful tool to report label-free contrast between normal and diseased tissues, both in vivo and ex vivo. We report the development of an instrument employing Single Photon Avalanche Diode (SPAD) arrays to realize real-time multispectral autofluorescence lifetime imaging at a macroscopic scale using handheld single-point fibre optic probes, under bright background conditions. At the detection end, the fluorescence signal is passed through a transmission grating and both spectral and temporal information are encoded in the SPAD array. This configuration allows interrogation in the spectral range of interest in real time. Spatial information is provided by an external camera together with a guiding beam that provides a visual reference that is tracked in real-time. Through fast image processing and data analysis, fluorescence lifetime maps are augmented on white light images to provide feedback of the measurements in real-time. We validate and demonstrate the practicality of this technique in the reference fluorophores and in articular cartilage samples mimicking the degradation that occurs in osteoarthritis. Our results demonstrate that SPADs together with fibre probes can offer means to report autofluorescence spectral and lifetime contrast in real-time and thus are suitable candidates for in situ tissue diagnostics.