Discontinuity third harmonic generation microscopy for label-free imaging and quantification of intraepidermal nerve fibers

Label-free imaging methodologies for nerve fibers rely on spatial signal continuity to identify fibers and fail to image free intraepidermal nerve endings (FINEs). Here, we present an imaging methodology-called discontinuity third harmonic generation (THG) microscopy (dTHGM)-that detects three-dimensional discontinuities in THG signals as the contrast. We describe the mechanism and design of dTHGM and apply it to reveal the bead-string characteristics of unmyelinated FINEs. We confirmed the label-free capability of dTHGM through a comparison study with the PGP9.5 immunohistochemical staining slides and a longitudinal spared nerve injury study. An intraepidermal nerve fiber (IENF) index based on a discontinuous-dot-connecting algorithm was developed to facilitate clinical applications of dTHGM. A preliminary clinical study confirmed that the IENF index was highly correlated with skin-biopsy-based IENF density (Pearson's correlation coefficient R = 0.98) and could achieve differential identification of small-fiber neuropathy (p = 0.0102) in patients with diabetic peripheral neuropathy.

Detection of NADH and NADPH levels in vivo identifies shift of glucose metabolism in cancer to energy production

Profound changes in the metabolism of cancer cells have been known for almost 100 years, and many aspects of these changes have continued to be actively studied and discussed. Differences in the results of various studies can be explained by the diversity of tumours, which have differing processes of energy metabolism, and by limitations in the methods used. Here, using fluorescence lifetime needle optical biopsy in a hepatocellular carcinoma (HCC) mouse model and patients with HCC, we measured reduced nicotinamide adenine dinucleotide (NADH) and reduced nicotinamide adenine dinucleotide phosphate (NADPH) in control liver, and in HCC tumours and their adjacent regions. We found that NADH level (mostly responsible for energy metabolism) is increased in tumours but also in adjacent regions of the same liver. NADPH level is significantly decreased in the tumours of patients but increased in the HCC mouse model. However, in the ex vivo tumour slices of mouse HCC, reactive oxygen species production and glutathione level (both dependent on NADPH) were significantly suppressed. Thus, glucose-dependent NADH and NADPH production in tumours changed but with a more pronounced shift to energy production (NADH), rather than NADPH synthesis for redox balance.

Femtosecond optical Kerr effect in normal and grades of cancerous breast tissues as a new optical biopsy method

This study reports on the first use of the optical Kerr effect (OKE) in breast cancer tissue. This proposed optical biopsy method utilizes a Femtosecond Optical Kerr Gate to detect changes in dielectric relaxation and conductivity created by a cancerous infection. Here, the temporal behavior of the OKE is tracked in normal and cancerous samples of human and mouse breast. These tissues display a double peaked temporal structure and its decay rate changes depending on the tissue's infection status. The decay of the secondary peak, attributed to ultrafast plasma response, indicates that the tissue's conductivity has doubled once infected. A slower molecular contribution to the Kerr effect can also be observed in healthy tissues. These findings suggest two possible biomarkers for the use of OKE in optical biopsy. Both markers arise from alterations in the infected tissue's cellular structure, which changes the rate at which electronic and molecular processes occur.

Femtosecond Optical Kerr Gate in tissues

The Optical Kerr Effect is investigated for the first time in biological tissues. This nonlinear effect was explored in both human brain and avian breast tissues using a time-resolved femtosecond pump-probe Optical Kerr Gate that looks for phase changes that arise in the probe from the pump induced Kerr refractive index change. The tissue samples produced a unique ultrafast (700-800 fs) doubled peaked temporal signal, which is indicative of interplay between the different ultrafast mechanisms (electronic plasma and molecular) that make up the Kerr index. The unique profile was replicated in theoretical simulations. The properties of the temporal profile varied between samples suggesting that it could be used as a new diagnostic. Understanding this behavior can help improve the scientific understanding of nonlinear spectral diagnostic techniques and potentially create a new Kerr-based optical biopsy method.

Articular Cartilage-From Basic Science Structural Imaging to Non-Invasive Clinical Quantitative Molecular Functional Information for AI Classification and Prediction

This review presents the changes that the imaging of articular cartilage has undergone throughout the last decades. It highlights that the expectation is no longer to image the structure and associated functions of articular cartilage but, instead, to devise methods for generating non-invasive, function-depicting images with quantitative information that is useful for detecting the early, pre-clinical stage of diseases such as primary or post-traumatic osteoarthritis (OA/PTOA). In this context, this review summarizes (a) the structure and function of articular cartilage as a molecular imaging target, (b) quantitative MRI for non-invasive assessment of articular cartilage composition, microstructure, and function with the current state of medical diagnostic imaging, (c), non-destructive imaging methods, (c) non-destructive quantitative articular cartilage live-imaging methods, (d) artificial intelligence (AI) classification of degeneration and prediction of OA progression, and (e) our contribution to this field, which is an AI-supported, non-destructive quantitative optical biopsy for early disease detection that operates on a digital tissue architectural fingerprint. Collectively, this review shows that articular cartilage imaging has undergone profound changes in the purpose and expectations for which cartilage imaging is used; the image is becoming an AI-usable biomarker with non-invasive quantitative functional information. This may aid in the development of translational diagnostic applications and preventive or early therapeutic interventions that are yet beyond our reach.

Multispectral Raman Differentiation of Malignant Skin Neoplasms In Vitro: Search for Specific Biomarkers and Optimal Wavelengths

Confocal scanning Raman and photoluminescence (PL) microspectroscopy is a structure-sensitive optical method that allows the non-invasive analysis of biomarkers in the skin tissue. We used it to perform in vitro diagnostics of different malignant skin neoplasms at several excitation wavelengths (532, 785 and 1064 nm). Distinct spectral differences were noticed in the Raman spectra of basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), compared with healthy skin. Our analysis of Raman/PL spectra at the different excitation wavelengths enabled us to propose two novel wavelength-independent spectral criteria (intensity ratios for 1302 cm-1 and 1445 cm-1 bands, 1745 cm-1 and 1445 cm-1 bands), related to the different vibrational "fingerprints" of cell membrane lipids as biomarkers, which was confirmed by the multivariate curve resolution (MCR) technique. These criteria allowed us to differentiate healthy skin from BCC and SCC with sensitivity and specificity higher than 95%, demonstrating high clinical importance in the differential diagnostics of skin tumors.

Deconvolution of the fluorescence spectra measured through a needle probe to assess the functional state of the liver

OBJECTIVES

Currently, one of the most pressing issues for surgeons in the treatment of obstructive jaundice is the ability to assess the functional state of the liver and to detect and determine the degree of liver failure in a timely manner with simple and objective techniques. In this regard, the use of fluorescence spectroscopy method can be considered as one of the ways to improve the informativity of existing diagnostic algorithms in clinical practice and to introduce new diagnostic tools. Thus, the aim of the work was to study in vivo the functional state of liver parenchyma by the method of fluorescence spectroscopy implemented through a needle probe and assess the contribution of the main tissue fluorophores to reveal new diagnostic criteria.

MATERIALS AND METHODS

We compared data from 20 patients diagnosed with obstructive jaundice and 11 patients without this syndrome. Measurements were performed using a fluorescence spectroscopy method at excitation wavelengths of 365 and 450 nm. Data were collected using a 1 mm fiber optic needle probe. The analysis was based on the comparison of the results of deconvolution with the combinations of Gaussian curves reflecting the contribution of the pure fluorophores in the liver tissues.

RESULTS

The results showed a statistically significant increase in the contribution of curves reflecting NAD(P)H fluorescence, bilirubin, and flavins in the group of patients with obstructive jaundice. This and the calculated redox ratio values indicated that the energy metabolism of the hepatocytes may have shifted to glycolysis due to hypoxia. An increase in vitamin A fluorescence was also observed. It may also serve as a marker of liver damage, indicating impaired vitamin A mobilization from the liver due to cholestasis.

CONCLUSIONS

The results obtained reflect changes associated with shifts in the content of the main fluorophores characterizing hepatocyte dysfunction caused by accumulation of bilirubin and bile acids and after disturbance of oxygen utilization. The contributions of NAD(P)H, flavins, and bilirubin as well as vitamin A can be used for further studies as promising diagnostic and prognostic markers for the course of liver failure. Further work will include collecting fluorescence spectroscopy data in patients with different clinical effects of obstructive jaundice on postoperative clinical outcome after biliary decompression.

Design and test of a rigid endomicroscopic system for multimodal imaging and femtosecond laser ablation

Significance

Conventional diagnosis of laryngeal cancer is normally made by a combination of endoscopic examination, a subsequent biopsy, and histopathology, but this requires several days and unnecessary biopsies can increase pathologist workload. Nonlinear imaging implemented through endoscopy can shorten this diagnosis time, and localize the margin of the cancerous area with high resolution.

Aim

Develop a rigid endomicroscope for the head and neck region, aiming for in-vivo multimodal imaging with a large field of view (FOV) and tissue ablation.

Approach

Three nonlinear imaging modalities, which are coherent anti-Stokes Raman scattering, two-photon excitation fluorescence, and second harmonic generation, as well as the single photon fluorescence of indocyanine green, are applied for multimodal endomicroscopic imaging. High-energy femtosecond laser pulses are transmitted for tissue ablation.

Results

This endomicroscopic system consists of two major parts, one is the rigid endomicroscopic tube 250 mm in length and 6 mm in diameter, and the other is the scan-head (10 × 12 × 6    cm 3 in size) for quasi-static scanning imaging. The final multimodal image accomplishes a maximum FOV up to 650    μ m , and a resolution of 1    μ m is achieved over 560    μ m FOV. The optics can easily guide sub-picosecond pulses for ablation.

Conclusions

The system exhibits large potential for helping real-time tissue diagnosis in surgery, by providing histological tissue information with a large FOV and high resolution, label-free. By guiding high-energy fs laser pulses, the system is even able to remove suspicious tissue areas, as has been shown for thin tissue sections in this study.

Dynamic real-time optical microscopy of oral mucosal lesions using confocal laser endomicroscopy

OBJECTIVES

Confocal laser endomicroscopy (CLE) is a novel non-invasive point-of-care optical biopsy technology that enables real-time in vivo microscopic visualisation of cellular and tissue architecture. In this study, we assessed the diagnostic accuracy of a hand-held fluorescence single-fibre distal-scanning CLE (fsdCLE) platform for diagnosing oral epithelial dysplasia (OED) and oral squamous cell carcinoma (OSCC).

MATERIALS AND METHODS

Forty-seven patients presenting with 63 distinct oral mucosal lesions were subjected to optical biopsy using a miniaturised fsdCLE system (ViewnVivo®, Optiscan Imaging Ltd) and topical exogenous acriflavine hydrochloride contrast agent before undergoing tissue biopsy and histopathological consensus review by four pathologists. CLE images were captured in vivo in real-time during clinical examination and assessed on-the-fly for the presence of cellular and architectural features of OED/OSCC offering an instantaneous diagnosis. Predicted optical diagnoses were compared to definitive consensus tissue histopathology. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy were calculated for the presence/absence of dysplasia/malignancy on optical biopsy. Percentage agreement, Fleiss' kappa, and intraclass correlation coefficient (ICC) were calculated for each assessment stage during the consensus histopathology process.

RESULTS

Diagnostic accuracy was extremely high at 88.9%. Other metrics were sensitivity 86.8%, specificity 92%, PPV 94.3% and NPV 82.1%. One hundred percent of carcinoma cases were detected accurately using CLE in the clinic.

CONCLUSION

fsdCLE is a highly accurate, easy-to-use, rapid and slide-free point-of-care in vivo optical technology for diagnosing OED/OSCC and discriminating between dysplastic and non-dysplastic pathology. It demonstrates near-perfect agreement with traditional consensus histopathology without the need for physical tissue biopsy.

Application of Indocyanine Green Fluorescence Imaging in Assisting Biopsy of Musculoskeletal Tumors

(1) Background: Biopsies are the gold standard for the diagnosis of musculoskeletal tumors. In this study, we aimed to explore whether indocyanine green near-infrared fluorescence imaging can assist in the biopsy of bone and soft tissue tumors and improve the success rate of biopsy. (2) Method: We recruited patients with clinically considered bone and soft tissue tumors and planned biopsies. In the test group, indocyanine green (0.3 mg/kg) was injected. After identifying the lesion, a near-infrared fluorescence camera system was used to verify the ex vivo specimens of the biopsy in real time. If the biopsy specimens were not developed, we assumed that we failed to acquire lesions, so the needle track and needle position were adjusted for the supplementary biopsy, and then real-time imaging was performed again. Finally, we conducted a pathological examination. In the control group, normal biopsy was performed. (3) Results: The total diagnosis rate of musculoskeletal tumors in the test group was 94.92% (56/59) and that in the control group was 82.36% (42/51). In the test group, 14 cases were not developed, as seen from real-time fluorescence in the core biopsy, and then underwent the supplementary biopsy after changing the puncture direction and the location of the needle channel immediately, of which 7 cases showed new fluorescence. (4) Conclusions: Using the near-infrared fluorescence real-time development technique to assist the biopsy of musculoskeletal tumors may improve the accuracy of core biopsy and help to avoid missed diagnoses, especially for some selected tumors.

An optical system for noninvasive microscopy of psoriatic mice in vivo

Psoriasis is a chronic inflammatory skin disease involved with both complex morphological changes of skin and immune processes. The clinical diagnostics and research of psoriasis often require invasive biopsy which lacks their real-time dynamics in vivo. Here we report a noninvasive microscopic system developed by combining in vivo fluorescent microscopy, optical clearing, and immunolabeling to enable real-time imaging of immune cells and cytokines in blood flow in psoriatic animal models. The vascular morphology and time-lapse kinetics of interleukin (IL)-23, IL-17, tumor necrosis factor-α, and CD4+ cells in blood are captured at submicron resolution through the thickening epidermis and opaque scales during the development of psoriasis in vivo. Our data suggest IL-23 recruits CD4+ cells to release IL-17 in blood that further leaks out in the psoriatic skin area. This optical system enables noninvasive and real-time assessment of immune molecules and cells in vivo, providing good potential for medical researches on psoriasis.

Raman spectroscopy in chronic heart failure diagnosis based on human skin analysis

This work aims at studying Raman spectroscopy in combination with chemometrics as an alternative fast noninvasive method to detect chronic heart failure (CHF) cases. Optical analysis is focused on the changes in the spectral features associated with the biochemical composition changes of skin tissues. A portable spectroscopy setup with the 785 nm excitation wavelength was used to record skin Raman features. In this in vivo study, 127 patients and 57 healthy volunteers were involved in measuring skin spectral features by Raman spectroscopy. The spectral data were analyzed with a projection on the latent structures and discriminant analysis. 202 skin spectra of patients with CHF and 90 skin spectra of healthy volunteers were classified with 0.888 ROC AUC for the 10-fold cross validated algorithm. To identify CHF cases, the performance of the proposed classifier was verified by means of a new test set that is equal to 0.917 ROC AUC.

Site-Coded Oral Squamous Cell Carcinoma Evaluation by Optical Coherence Tomography (OCT): A Descriptive Pilot Study

Optical Coherence Tomography (OCT) is an emerging non-invasive method for oral diagnostics, proving to be a practicable device for epithelial and subepithelial evaluation. The potential validity of OCT in oral cancer assessment has been explored but, to date, there are very few investigations conducted with a systematic comparison between clinical/histological and OCT parameters, especially in strict reference to the anatomical site-codification of the oral mucosa. In this regard, our study performed a two-steps evaluation (in vivo OCT and histological investigations) of suspected OSCCs, progressively recruited, using as references the OCT images of the same site-coded healthy mucosa, to provide as much as possible site-specific determinants. Thirty histologically confirmed OSCCs were recruited. Specific OCT mucosal features (SEL-Stratified Epithelial Layer; BM-Basement Membrane; LP-Lamina Propria) were registered and processed using the SRQR (Standards for Reporting Qualitative Research) statement. The systematic dual descriptive OCT analysis revealed that OSCC scans present a complete alteration of epithelial (KL, SEL) and subepithelial (BM, LP) layers with a site-specificity characteristic; moreover, peculiar OCT configurations such as "icicle-like" structures could be strongly suggestive of neoplastic infiltration. This study supports the OCT use for the development of more specific optical structural models applied to oral carcinogenesis.

Precision Surgery Guided by Intraoperative Molecular Imaging

Intraoperative molecular imaging (IMI) has recently emerged as an important tool in the armamentarium of surgical oncologists. IMI allows real-time assessment of oncologic resection quality, margin assessment, and occult disease detection during real-time surgery. Numerous tracers have now been developed for use in IMI-guided tissue sampling. Fluorochromes localize to the tumor by taking advantage of their disorganized capillary milieu, overexpressed receptors, or upregulated enzymes. Although fluorescent tracers can suffer from issues of autofluorescence and lack of depth penetration, these challenges are being addressed through hybrid radioactive/fluorescent tracers and new tracers that fluoresce in the near-infrared (NIR-II [wavelength > 1,000 nm]) range. IMI is already being used to treat numerous cancers, with demonstrated improvement in cancer recurrence and patient outcomes without incurring significant burden on either clinicians or patients. In this comprehensive review, we discuss history, mechanism, current oncologic applications, and future directions of IMI-guided optical biopsy.

Use of advanced endoscopic technology for optical characterization of neoplasia in patients with ulcerative colitis: Systematic review

OBJECTIVES

Advances in endoscopic technology, including magnifying and image-enhanced techniques, have been attracting increasing attention for the optical characterization of colorectal lesions. These techniques are being implemented into clinical practice as cost-effective and real-time approaches. Additionally, with the recent progress in endoscopic interventions, endoscopic resection is gaining acceptance as a treatment option in patients with ulcerative colitis (UC). Therefore, accurate preoperative characterization of lesions is now required. However, lesion characterization in patients with UC may be difficult because UC is often affected by inflammation, and it may be characterized by a distinct "bottom-up" growth pattern, and even expert endoscopists have relatively little experience with such cases. In this systematic review, we assessed the current status and limitations of the use of optical characterization of lesions in patients with UC.

METHODS

A literature search of online databases (MEDLINE via PubMed and CENTRAL via the Cochrane Library) was performed from 1 January 2000 to 30 November 2021.

RESULTS

The database search initially identified 748 unique articles. Finally, 25 studies were included in the systematic review: 23 focused on differentiation of neoplasia from non-neoplasia, one focused on differentiation of UC-associated neoplasia from sporadic neoplasia, and one focused on differentiation of low-grade dysplasia from high-grade dysplasia and cancer.

CONCLUSIONS

Optical characterization of neoplasia in patients with UC, even using advanced endoscopic technology, is still challenging and several issues remain to be addressed. We believe that the information revealed in this review will encourage researchers to commit to the improvement of optical diagnostics for UC-associated lesions.

Depth estimation of tumor invasion in early gastric cancer using scattering of circularly polarized light: Monte Carlo Simulation study

Quantitative depth estimation of tumor invasion in early gastric cancer by scattering of circularly polarized light is computationally investigated using the Monte Carlo method. Using the optical parameters of the human stomach wall and its carcinoma, the intensity and circular polarization of light scattered from pseudo-healthy and cancerous tissues were calculated over a wide spectral range. Large differences in the circular polarization with opposite signs, together with the large intensity, are obtained at wavelengths 600 nm and 950 nm. At these two wavelengths, the sampling depth of the biological tissues can be modulated by tuning the detection angle. In bi-layered pseudo-tissues with a cancerous layer on a healthy layer and vice versa, the degree of circular polarization of scattered light shows systematic changes depending on the thickness and depth of the cancerous layer, which indicates the feasibility of in vivo quantitative estimation of cancer progression in early gastric cancer.

In vivo detection of head and neck tumors by hyperspectral imaging combined with deep learning methods

Currently, there are no fast and accurate screening methods available for head and neck cancer, the eighth most common tumor entity. For this study, we used hyperspectral imaging, an imaging technique for quantitative and objective surface analysis, combined with deep learning methods for automated tissue classification. As part of a prospective clinical observational study, hyperspectral datasets of laryngeal, hypopharyngeal and oropharyngeal mucosa were recorded in 98 patients before surgery in vivo. We established an automated data interpretation pathway that can classify the tissue into healthy and tumorous using convolutional neural networks with 2D spatial or 3D spatio-spectral convolutions combined with a state-of-the-art Densenet architecture. Using 24 patients for testing, our 3D spatio-spectral Densenet classification method achieves an average accuracy of 81%, a sensitivity of 83% and a specificity of 79%.

Toward cardiac tissue characterization using machine learning and light-scattering spectroscopy

SIGNIFICANCE

The non-destructive characterization of cardiac tissue composition provides essential information for both planning and evaluating the effectiveness of surgical interventions such as ablative procedures. Although several methods of tissue characterization, such as optical coherence tomography and fiber-optic confocal microscopy, show promise, many barriers exist that reduce effectiveness or prevent adoption, such as time delays in analysis, prohibitive costs, and limited scope of application. Developing a rapid, low-cost non-destructive means of characterizing cardiac tissue could improve planning, implementation, and evaluation of cardiac surgical procedures.

AIM

To determine whether a new light-scattering spectroscopy (LSS) system that analyzes spectra via neural networks is capable of predicting the nuclear densities (NDs) of ventricular tissues.

APPROACH

We developed an LSS system with a fiber-optics probe and applied it for measurements on cardiac tissues from an ovine model. We quantified the ND in the cardiac tissues using fluorescent labeling, confocal microscopy, and image processing. Spectra acquired from the same cardiac tissues were analyzed with spectral clustering and convolutional neural networks (CNNs) to assess the feasibility of characterizing the ND of tissue via LSS.

RESULTS

Spectral clustering revealed distinct groups of spectra correlated to ranges of ND. CNNs classified three groups of spectra with low, medium, or high ND with an accuracy of 95.00  ±  11.77  %   (mean and standard deviation). Our analyses revealed the sensitivity of the classification accuracy to wavelength range and subsampling of spectra.

CONCLUSIONS

LSS and machine learning are capable of assessing ND in cardiac tissues. We suggest that the approach is useful for the diagnosis of cardiac diseases associated with changes of ND, such as hypertrophy and fibrosis.

Towards Intraoperative Quantification of Atrial Fibrosis Using Light-Scattering Spectroscopy and Convolutional Neural Networks

Light-scattering spectroscopy (LSS) is an established optical approach for characterization of biological tissues. Here, we investigated the capabilities of LSS and convolutional neural networks (CNNs) to quantitatively characterize the composition and arrangement of cardiac tissues. We assembled tissue constructs from fixed myocardium and the aortic wall with a thickness similar to that of the atrial free wall. The aortic sections represented fibrotic tissue. Depth, volume fraction, and arrangement of these fibrotic insets were varied. We gathered spectra with wavelengths from 500–1100 nm from the constructs at multiple locations relative to a light source. We used single and combinations of two spectra for training of CNNs. With independently measured spectra, we assessed the accuracy of the CNNs for the classification of tissue constructs from single spectra and combined spectra. Combined spectra, including the spectra from fibers distal from the illumination fiber, typically yielded the highest accuracy. The maximal classification accuracy of the depth detection, volume fraction, and permutated arrangements was (mean ± standard deviation (stddev)) 88.97 ± 2.49%, 76.33 ± 1.51%, and 84.25 ± 1.88%, respectively. Our studies demonstrate the reliability of quantitative characterization of tissue composition and arrangements using a combination of LSS and CNNs. The potential clinical applications of the developed approach include intraoperative quantification and mapping of atrial fibrosis, as well as the assessment of ablation lesions.

Analysis on the Characterization of Multiphoton Microscopy Images for Malignant Neoplastic Colon Lesion Detection under Deep Learning Methods

Background:

Colorectal cancer has a high incidence rate worldwide, with over 1.8 million new cases and 880,792 deaths in 2018. Fortunately, its early detection significantly increases the survival rate, reaching a cure rate of 90% when diagnosed at a localized stage. Colonoscopy is the gold standard technique for detection and removal of colorectal lesions with potential to evolve into cancer. When polyps are found in a patient, the current procedure is their complete removal. However, in this process, gastroenterologists cannot assure complete resection and clean margins which are given by the histopathology analysis of the removed tissue, which is performed at laboratory.

Aims:

In this paper, we demonstrate the capabilities of multiphoton microscopy (MPM) technology to provide imaging biomarkers that can be extracted by deep learning techniques to identify malignant neoplastic colon lesions and distinguish them from healthy, hyperplastic, or benign neoplastic tissue, without the need for histopathological staining.

Materials and Methods:

To this end, we present a novel MPM public dataset containing 14,712 images obtained from 42 patients and grouped into 2 classes. A convolutional neural network is trained on this dataset and a spatially coherent predictions scheme is applied for performance improvement.

Results:

We obtained a sensitivity of 0.8228 ± 0.1575 and a specificity of 0.9114 ± 0.0814 on detecting malignant neoplastic lesions. We also validated this approach to estimate the self-confidence of the network on its own predictions, obtaining a mean sensitivity of 0.8697 and a mean specificity of 0.9524 with the 18.67% of the images classified as uncertain.

Conclusions:

This work lays the foundations for performing in vivo optical colon biopsies by combining this novel imaging technology together with deep learning algorithms, hence avoiding unnecessary polyp resection and allowing in situ diagnosis assessment.

Correlation between Autofluorescence Intensity and Histopathological Features in Non-Melanoma Skin Cancer: An Ex Vivo Study

Simple Summary

Non-melanoma skin cancers (NMSC) are the most prevalent neoplasms worldwide, especially in the Caucasian population. Radical surgical excision is considered the therapeutic gold standard, while incomplete tumor removal is invariably associated with recurrence and the need for reintervention. Autofluorescence (AF) spectroscopy has recently been investigated for early diagnosis of NMSC and assessment of tumor margins. Understanding changes in AF intensity in association with peculiar histological features could improve the diagnostic accuracy of skin fluorescence spectroscopy. The main goal of our work was to investigate the correlation between the intensity of cutaneous AF and the histopathological features of NMSC. The intensity of fluorescence emission in tissues obtained from NMSC samples was approximately 4 times lower than that in healthy conditions. In fact, mean AF intensity for BCC group was 4.5 and 4.4 for SCCs, with further variability being recorded according to histopathologic subtypes. Histopathological features such as hyperkeratosis, neoangiogenesis, fibrosis and elastosis are statistically associated with a decrease in AF intensity. Our data suggest that such tissue alterations could be responsible for the difference in AF emission between neoplastic and healthy tissue. These results support the potential application of AF as a useful non-invasive diagnostic tool for NMSCs.

Abstract

Non-melanoma skin cancer (NMSC) is the most common malignant tumor affecting fair-skinned people. Increasing incidence rates of NMSC have been reported worldwide, which is an important challenge in terms of public health management. Surgical excision with pre-operatively identified margins is one of the most common and effective treatment strategies. Incomplete tumor removal is associated with a very high risk of recurrence and re-excision. Biological tissues can absorb and re-emit specific light wave-lengths, detectable through spectrophotometric devices. Such a phenomenon is known as autofluorescence (AF). AF spectroscopy has been widely explored for non-invasive, early detection of NMSC as well as for evaluation of surgical margins before excision. Fluorescence-aided diagnosis is based on differences in spectral characteristics between healthy and neoplastic skin. Understanding the biological basis of such differences and correlating AF intensity to histological features could improve the diagnostic accuracy of skin fluorescence spectroscopy. The primary objective of the present pre-clinical ex vivo study is to investigate the correlation between the intensity of cutaneous AF and the histopathological features of NMSC. Ninety-eight lesions suggestive for NMSCs were radically excised from 75 patients (46 M; 29 F; mean age: 79 years). After removal, 115 specific reference points on lesions (“cases”; 59 on BBC, 53 on SCC and 3 on other lesions) and on peri-lesional healthy skin (controls; 115 healthy skin) were identified and marked through suture stitches. Such reference points were irradiated at 400–430 nm wavelength, and resulting emission AF spectra were acquired through spectrophotometry. For each case, AFIR (autofluorescence intensity ratio) was measured as the ratio between the number of photons emitted at a wavelength ranging between 450 and 700 nm (peak: 500 nm) in the healthy skin and that was captured in the pathological tissue. At the histological level, hyperkeratosis, neoangiogenesis, cellular atypia, epithelial thickening, fibrosis and elastosis were quantified by light microscopy and were assessed through a previously validated grading system. Statistical correlation between histologic variables and AFIR was calculated through linear regression. Spectrometric evaluation was performed on 230 (115 cases + 115 controls) reference points. The mean AFIR for BCC group was 4.5, while the mean AFIR for SCC group was 4.4 and the fluorescence peaks at 500 nm were approximately 4 times lower (hypo-fluorescent) in BCCs and in SCCs than in healthy skin. Histological variables significantly associated with alteration of AFIR were fibrosis and elastosis (p < 0.05), neoangiogenesis, hyperkeratosis and epithelial thickening. Cellular atypia was not significantly associated with alteration of AFIR. The intensity of fluorescence emission in neoplastic tissues was approximately 4 times lower than that in healthy tissues. Histopathological features such as hyperkeratosis, neoangiogenesis, fibrosis and elastosis are statistically associated with the decrease in AFIR. We hypothesize that such tissue alterations are among the possible biophysical and biochemical bases of difference in emission AF between neoplastic and healthy tissue. The results of the present evaluation highlighted the possible usefulness of autofluorescence as diagnostic, non-invasive and real-time tool for NMSCs.

Probe-based confocal laser endomicroscopy in COVID-19

Probe-based confocal laser endomicroscopy (pCLE) is a method that produces microscopic imaging of a lung tissue during bronchoscopy. We report a case ot a patient with negative nasopharyngeal swabs and suspected lung cancer who underwent pCLE. The diagnosis of COVID-19 was confirmed by PCR analyses of lavage fluid and transbrohial biopsy. The pCLE image shows density of alveolar thickened fibres, disorganization of elastin network, and multiple large drops of intraalveolar secretions. As far as we know, this is the first pCLE image discribed in patient with COVID-19 at that moment.

Fluorescein-Guided Panendoscopy for Head and Neck Cancer Using Handheld Probe-Based Confocal Laser Endomicroscopy: A Pilot Study

Background

White-light endoscopy and microscopy combined with histological analysis is currently the mainstay for intraprocedural tissue diagnosis during panendoscopy for head and neck cancer. However, taking biopsies leads to selection bias, ex vivo histopathology is time-consuming, and the advantages of in-vivo intraoperative decision making cannot be used. Confocal laser endomicroscopy (CLE) has the potential for a rapid and histological assessment in the head and neck operating room.

Methods

Between July 2019 and January 2020, 13 patients (69% male, median age: 61 years) with newly diagnosed head and neck cancer (T3/T4: 46%) underwent fluorescein-guided panendoscopy. CLE was performed from both the tumor and margins followed by biopsies from the CLE spots. The biopsies were processed for histopathology. The CLE images were ex vivo classified blinded with a CLE cancer score (DOC score). The classification was compared to the histopathological results.

Results

Median additional time for CLE during surgery was 9 min. A total of 2,565 CLE images were taken (median CLE images: 178 per patient; 68 per biopsy; evaluable 87.5%). The concordance between histopathology and CLE images varied between the patients from 82.5 to 98.6%. The sensitivity, specificity, and accuracy to detect cancer using the classified CLE images was 87.5, 80.0, and 84.6%, respectively. The positive and negative predictive values were 87.0 and 80.0%, respectively.

Conclusion

CLE with a rigid handheld probe is easy and intuitive to handle during panendoscopy. As next step, the high accuracy of ex vivo CLE image classification for tumor tissue suggests the validation of CLE in vivo. This will evolve CLE as a complementary tool for in vivo intraoperative diagnosis during panendoscopy.

Using FDA-approved drugs as off-label fluorescent dyes for optical biopsies: from in silico design toex vivoproof-of-concept

Optical biopsies bring the microscope to the patient rather than the tissue to the microscope, and may complement or replace the tissue-harvesting component of the traditional biopsy process with its associated risks. In general, optical biopsies are limited by the lack of endogenous tissue contrast and the small number of clinically approvedin vivodyes. This study tests multiple FDA-approved drugs that have structural similarity to research dyes as off-labelin situfluorescent alternatives to standardex vivohematoxylin & eosin tissue stain. Numerous drug-dye combinations shown here may facilitate relatively safe and fastin situor possiblyin vivostaining of tissue, enabling real-time optical biopsies and other advanced microscopy technologies, which have implications for the speed and performance of tissue- and cellular-level diagnostics.

Revision of Commonly Accepted Warburg Mechanism of Cancer Development: Redox-Sensitive Mitochondrial Cytochromes in Breast and Brain Cancers by Raman Imaging

We used Raman imaging to monitor changes in the redox state of the mitochondrial cytochromes in ex vivo human brain and breast tissues, surgically resected specimens of human tissues and in vitro human brain cells of normal astrocytes (NHA), astrocytoma (CRL-1718), glioblastoma (U87-MG) and medulloblastoma (Daoy), and human breast cells of normal cells (MCF 10A), slightly malignant cells (MCF7) and highly aggressive cells (MDA-MB-231) by means of Raman microspectroscopy at 532 nm. We visualized localization of cytochromes by Raman imaging in the major organelles in cancer cells. We demonstrated that the "redox state Raman marker" of the ferric low-spin heme in cytochrome c at 1584 cm^-1 can serve as a sensitive indicator of cancer aggressiveness. We compared concentration of reduced cytochrome c and the grade of cancer aggressiveness in cancer tissues and single cells and specific organelles in cells: nucleous, mitochondrium, lipid droplets, cytoplasm and membrane. We found that the concentration of reduced cytochrome c becomes abnormally high in human brain tumors and breast cancers in human tissues. Our results reveal the universality of Raman vibrational characteristics of mitochondrial cytochromes in metabolic regulation in cancers that arise from epithelial breast cells and brain glial cells.

Intraoperative molecular imaging clinical trials: a review of 2020 conference proceedings

SIGNIFICANCE

Surgery is often paramount in the management of many solid organ malignancies because optimal resection is a major factor in disease-specific survival. Cancer surgery has multiple challenges including localizing small lesions, ensuring negative surgical margins around a tumor, adequately staging patients by discriminating positive lymph nodes, and identifying potential synchronous cancers. Intraoperative molecular imaging (IMI) is an emerging potential tool proposed to address these issues. IMI is the process of injecting patients with fluorescent-targeted contrast agents that highlight cancer cells prior to surgery. Over the last 5 to 7 years, enormous progress has been achieved in tracer development, near-infrared camera approvals, and clinical trials. Therefore, a second biennial conference was organized at the University of Pennsylvania to gather surgical oncologists, scientists, and experts to discuss new investigative findings in the field. Our review summarizes the discussions from the conference and highlights findings in various clinical and scientific trials.

AIM

Recent advances in IMI were presented, and the importance of each clinical trial for surgical oncology was critically assessed. A major focus was to elaborate on the clinical endpoints that were being utilized in IMI trials to advance the respective surgical subspecialties.

APPROACH

Principal investigators presenting at the Perelman School of Medicine Abramson Cancer Center's second clinical trials update on IMI were selected to discuss their clinical trials and endpoints.

RESULTS

Multiple phase III, II, and I trials were discussed during the conference. Since the approval of 5-ALA for commercial use in neurosurgical malignancies, multiple tracers and devices have been developed to address common challenges faced by cancer surgeons across numerous specialties. Discussants also presented tracers that are being developed for delineation of normal anatomic structures that can serve as an adjunct during surgical procedures.

CONCLUSIONS

IMI is increasingly being recognized as an improvement to standard oncologic surgical resections and will likely advance the art of cancer surgery in the coming years. The endpoints in each individual surgical subspecialty are varied depending on how IMI helps each specialty solve their clinical challenges.

Using the Method of "Optical Biopsy" of Prostatic Tissue to Diagnose Prostate Cancer

Simple Summary

Analytical discrimination models of Raman spectra of prostate cancer tissue were constructed by using the projections onto latent structures data analysis (PLS-DA) method for different wavelengths of exciting radiation—532 and 785 nm. These models allowed us to divide the Raman spectra of prostate cancer and the spectra of hyperplasia sites for validation datasets with the accuracy of 70–80%, depending on the specificity value. Meanwhile, for the calibration datasets, the accuracy values reached 100% for the excitation of a laser with a wavelength of 785 nm. Due to the registration of Raman “fingerprints”, the main features of cellular metabolism occurring in the tissue of a malignant prostate tumor were confirmed, namely the absence of aerobic glycolysis, over-expression of markers, and a strong increase in the concentration of cholesterol and its esters, as well as fatty acids and glutamic acid.

Abstract

The possibilities of using optical spectroscopy methods in the differential diagnosis of prostate cancer were investigated. Analytical discrimination models of Raman spectra of prostate tissue were constructed by using the projections onto latent structures data analysis(PLS-DA) method for different wavelengths of exciting radiation—532 and 785 nm. These models allowed us to divide the Raman spectra of prostate cancer and the spectra of hyperplasia sites for validation datasets with the accuracy of 70–80%, depending on the specificity value. Meanwhile, for the calibration datasets, the accuracy values reached 100% for the excitation of a laser with a wavelength of 785 nm. Due to the registration of Raman “fingerprints”, the main features of cellular metabolism occurring in the tissue of a malignant prostate tumor were confirmed, namely the absence of aerobic glycolysis, over-expression of markers (FASN, SREBP1, stearoyl-CoA desaturase, etc.), and a strong increase in the concentration of cholesterol and its esters, as well as fatty acids and glutamic acid. The presence of an ensemble of Raman peaks with increased intensity, inherent in fatty acid, beta-glucose, glutamic acid, and cholesterol, is a fundamental factor for the identification of prostate cancer.

Pose estimation of a markerless fiber bundle for endoscopic optical biopsy

Purpose: We present a markerless vision-based method for on-the-fly three-dimensional (3D) pose estimation of a fiberscope instrument to target pathologic areas in the endoscopic view during exploration. Approach: A 2.5-mm-diameter fiberscope is inserted through the endoscope's operating channel and connected to an additional camera to perform complementary observation of a targeted area such as a multimodal magnifier. The 3D pose of the fiberscope is estimated frame-by-frame by maximizing the similarity between its silhouette (automatically detected in the endoscopic view using a deep learning neural network) and a cylindrical shape bound to a kinematic model reduced to three degrees-of-freedom. An alignment of the cylinder axis, based on Plücker coordinates from the straight edges detected in the image, makes convergence faster and more reliable. Results: The performance on simulations has been validated with a virtual trajectory mimicking endoscopic exploration and on real images of a chessboard pattern acquired with different endoscopic configurations. The experiments demonstrated a good accuracy and robustness of the proposed algorithm with errors of 0.33 ± 0.68    mm in distance position and 0.32 ± 0.11   deg in axis orientation for the 3D pose estimation, which reveals its superiority over previous approaches. This allows multimodal image registration with sufficient accuracy of < 3    pixels . Conclusion: Our pose estimation pipeline was executed on simulations and patterns; the results demonstrate the robustness of our method and the potential of fiber-optical instrument image-based tracking for pose estimation and multimodal registration. It can be fully implemented in software and therefore easily integrated into a routine clinical environment.

Angular optimization for cancer identification with circularly polarized light

Depolarization of circularly polarized light scattered from biological tissues depends on structural changes in cell nuclei, which can provide valuable information for differentiating cancer tissues concealed in healthy tissues. In this study, we experimentally verified the possibility of cancer identification using scattering of circularly polarized light. We investigated the polarization of light scattered from a sliced biological tissue with various optical configurations. A significant difference between circular polarizations of light scattered from cancerous and healthy tissues is observed, which is sufficient to distinguish a cancerous region. The line-scanning experiments along a region incorporating healthy and cancerous parts indicate step-like behaviors in the degree of circular polarization corresponding to the state of tissues, whether cancerous or normal. An oblique and perpendicular incidence induces different resolutions for identifying cancerous tissues, which indicates that the optical arrangement can be selected according to the priority of resolution.

Feedforward Artificial Neural Network-Based Colorectal Cancer Detection Using Hyperspectral Imaging: A Step towards Automatic Optical Biopsy

Simple Summary

Detection of colorectal carcinoma is performed visually by investigators and is confirmed pathologically. With hyperspectral imaging, an expanded spectral range of optical information is now available for analysis. The acquired recordings were analyzed with a neural network, and it was possible to differentiate tumor from healthy mucosa in colorectal carcinoma by automatic classification with high reliability. Classification and visualization were performed based on a four-layer perceptron neural network. Based on a neural network, the classification of CA or AD resulted in a sensitivity of 86% and a specificity of 95%, by means of leave-one-patient-out cross-validation. Additionally, significant differences in terms of perfusion parameters (e.g., oxygen saturation) related to tumor staging and neoadjuvant therapy were observed. This is a step towards optical biopsy.

Abstract

Currently, colorectal cancer (CRC) is mainly identified via a visual assessment during colonoscopy, increasingly used artificial intelligence algorithms, or surgery. Subsequently, CRC is confirmed through a histopathological examination by a pathologist. Hyperspectral imaging (HSI), a non-invasive optical imaging technology, has shown promising results in the medical field. In the current study, we combined HSI with several artificial intelligence algorithms to discriminate CRC. Between July 2019 and May 2020, 54 consecutive patients undergoing colorectal resections for CRC were included. The tumor was imaged from the mucosal side with a hyperspectral camera. The image annotations were classified into three groups (cancer, CA; adenomatous margin around the central tumor, AD; and healthy mucosa, HM). Classification and visualization were performed based on a four-layer perceptron neural network. Based on a neural network, the classification of CA or AD resulted in a sensitivity of 86% and a specificity of 95%, by means of leave-one-patient-out cross-validation. Additionally, significant differences in terms of perfusion parameters (e.g., oxygen saturation) related to tumor staging and neoadjuvant therapy were observed. Hyperspectral imaging combined with automatic classification can be used to differentiate between CRC and healthy mucosa. Additionally, the biological changes induced by chemotherapy to the tissue are detectable with HSI.

Redox Imbalance and Biochemical Changes in Cancer by Probing Redox-Sensitive Mitochondrial Cytochromes in Label-Free Visible Resonance Raman Imaging

Simple Summary

Gliomas comprise around 30% of human brain tumors, while invasive ductal carcinoma (IDC) comprises around 80% of human breast cancers. The aim of our study was to show that cancerogenesis affects the redox status of mitochondrial cytochromes, which can be tracked by using Raman spectroscopy and imaging. Our results confirmed that human breast cancer and brain tumor demonstrate a redox imbalance compared to normal tissues. We have shown the correlation between the intensity of cytochromes Raman bands at 750, 1126, 1337 and 1584 cm⁻¹ and malignancy grade for brain and breast cancers.

Abstract

To monitor redox state changes and biological mechanisms occurring in mitochondrial cytochromes in cancers improving methods are required. We used Raman spectroscopy and Raman imaging to monitor changes in the redox state of the mitochondrial cytochromes in ex vivo human brain and breast tissues at 532 nm, 633 nm, 785 nm. We identified the oncogenic processes that characterize human infiltrating ductal carcinoma (IDC) and human brain tumors: gliomas; astrocytoma and medulloblastoma based on the quantification of cytochrome redox status by exploiting the resonance-enhancement effect of Raman scattering. We visualized localization of cytochromes by Raman imaging in the breast and brain tissues and analyzed cytochrome c vibrations at 750, 1126, 1337 and 1584 cm⁻¹ as a function of malignancy grade. We found that the concentration of reduced cytochrome c becomes abnormally high in human brain tumors and breast cancers and correlates with the grade of cancer. We showed that Raman imaging provides additional insight into the biology of astrocytomas and breast ductal invasive cancer, which can be used for noninvasive grading, differential diagnosis.

In vivo diagnosis of skin cancer with a portable Raman spectroscopic device

In this study, we performed in vivo diagnosis of skin cancer based on implementation of a portable low-cost spectroscopy setup combining analysis of Raman and autofluorescence spectra in the near-infrared region (800-915 nm). We studied 617 cases of skin neoplasms (615 patients, 70 melanomas, 122 basal cell carcinomas, 12 squamous cell carcinomas and 413 benign tumors) in vivo with a portable setup. The studies considered the patients examined by GPs in local clinics and directed to a specialized Oncology Dispensary with suspected skin cancer. Each sample was histologically examined after excisional biopsy. The spectra were classified with a projection on latent structures and discriminant analysis. To check the classification models stability, a 10-fold cross-validation was performed. We obtained ROC AUCs of 0.75 (0.71-0.79; 95% CI), 0.69 (0.63-0.76; 95% CI) and 0.81 (0.74-0.87; 95% CI) for classification of a) malignant and benign tumors, b) melanomas and pigmented tumors and c) melanomas and seborrhoeic keratosis, respectively. The positive and negative predictive values ranged from 20% to 52% and from 73% to 99%, respectively. The biopsy ratio varied from 0.92:1 to 4.08:1 (at sensitivity levels from 90% to 99%). The accuracy of automatic analysis with the proposed system is higher than the accuracy of GPs and trainees, and is comparable or less to the accuracy of trained dermatologists. The proposed approach may be combined with other optical techniques of skin lesion analysis, such as dermoscopy- and spectroscopy-based computer-assisted diagnosis systems to increase accuracy of neoplasms classification.

Intraoperative Confocal Laser Endomicroscopy Ex Vivo Examination of Tissue Microstructure During Fluorescence-Guided Brain Tumor Surgery

Background

Noninvasive intraoperative optical biopsy that provides real-time imaging of histoarchitectural (cell resolution) features of brain tumors, especially at the margin of invasive tumors, would be of great value. To assess clinical-grade confocal laser endomicroscopy (CLE) and to prepare for its use intraoperatively in vivo, we performed an assessment of CLE ex vivo imaging in brain lesions.

Methods

Tissue samples from patients who underwent intracranial surgeries with fluorescein sodium (FNa)–based wide-field fluorescence guidance were acquired for immediate intraoperative ex vivo optical biopsies with CLE. Hematoxylin-eosin–stained frozen section analysis of the same specimens served as the gold standard for blinded neuropathology comparison. FNa 2 to 5 mg/kg was administered upon induction of anesthesia, and FNa 5 mg/kg was injected for CLE contrast improvement. Histologic features were identified, and the diagnostic accuracy of CLE was assessed.

Results

Of 77 eligible patients, 47 patients with 122 biopsies were enrolled, including 32 patients with gliomas and 15 patients with other intracranial lesions. The positive predictive value of CLE optical biopsies was 97% for all specimens and 98% for gliomas. The specificity of CLE was 90% for all specimens and 94% for gliomas. The second FNa injection in seven patients, a mean of 2.6 h after the first injection, improved image quality and increased the percentage of accurately diagnosed images from 67% to 93%. Diagnostic CLE features of lesional glioma biopsies and normal brain were identified. Seventeen histologic features were identified.

Conclusions

Results demonstrated high specificity and positive predictive value of ex vivo intraoperative CLE optical biopsies and justify an in vivo intraoperative trial. This new portable, noninvasive intraoperative imaging technique provides diagnostic features to discriminate lesional tissue with high specificity and is feasible for incorporation into the fluorescence-guided surgery workflow, particularly for patients with invasive brain tumors.

Novel input polarisation independent endoscopic cross-polarised optical coherence tomography probe

Lead by the original idea to perform noninvasive optical biopsies of various tissues, optical coherence tomography found numerous medical applications within the last two decades. The interference based imaging technique opens the possibility to visualise subcellular morphology up to an imaging depth of 3 mm and up to micron level axial and lateral resolution. The birefringence properties of the tissue are visualised with enhanced contrast using polarisation sensitive or cross-polarised optical coherence tomography (OCT) techniques. Although, it requires strict control over the polarisation states, resulting in several polarisation controlling elements. In this work, we propose a novel input-polarisation independent endoscopic system based on cross-polarised OCT. We tested the feasibility of our approach by measuring the polarisation change from a quarter-wave plate for different rotational angles. Further performance tests reveal a lateral resolution of 30 μm and a sensitivity of 103 dB. Images of the human nail bed and cow muscle tissue demonstrate the potential of the system to measure structural and birefringence properties of the tissue endoscopically.

Comparison of Noninvasive Imagery Methods to Observe Healthy and Degenerated Olfactory Epithelium in Mice for the Early Diagnosis of Neurodegenerative Diseases

Olfactory dysfunction could be an early and reliable indicator for the diagnosis of neurodegenerative disorders such as Alzheimer and Parkinson's diseases. In this paper, we compare the potential of different noninvasive medical imaging modalities (optical coherence tomography, confocal microscopy, and fluorescence endomicroscopy) to distinguish how the olfactory epithelium, both at the cellular and the structural levels, is altered. Investigations were carried out on three experimental groups: two pathological groups (mice models with deliberately altered olfactory epithelium and Alzheimer's disease transgenic mice models) were compared with healthy mice models. As histological staining, the three tested noninvasive imaging tools demonstrated the general tubular organization of the olfactory epithelium on healthy mice. Contrary to OCT, confocal microscopy, and endomicroscopy allowed visualizing the inner structure of olfactory epithelium as well as its morphological or functional changes on pathological models, alterations classically observed with histological assessment. The results could lead to relevant development of imaging tools for noninvasive and early diagnosis of neurodegenerative diseases through the in situ characterization of the olfactory epithelium.

Optical Biopsy of the Upper GI Tract Using Fluorescence Lifetime and Spectra

Screening and surveillance for gastrointestinal (GI) cancers by endoscope guided biopsy is invasive, time consuming, and has the potential for sampling error. Tissue endogenous fluorescence spectra contain biochemical and physiological information, which may enable real-time, objective diagnosis. We first briefly reviewed optical biopsy modalities for GI cancer diagnosis with a focus on fluorescence-based techniques. In an ex vivo pilot clinical study, we measured fluorescence spectra and lifetime on fresh biopsy specimens obtained during routine upper GI screening procedures. Our results demonstrated the feasibility of rapid acquisition of time-resolved fluorescence (TRF) spectra from fresh GI mucosal specimens. We also identified spectroscopic signatures that can differentiate between normal mucosal samples obtained from the esophagus, stomach, and duodenum.

Optical Biopsy: Automated Classification of Airway Endoscopic Findings Using a Convolutional Neural Network

OBJECTIVES/HYPOTHESIS

Create an autonomous computational system to classify endoscopy findings.

STUDY DESIGN

Computational analysis of vocal fold images at an academic, tertiary-care laryngology practice.

METHODS

A series of normal and abnormal vocal fold images were obtained from the image database of an academic tertiary care laryngology practice. The benign images included normals, nodules, papilloma, polyps, and webs. A separate set of carcinoma and leukoplakia images comprised a single malignant-premalignant class. All images were classified with their existing labels. Images were randomly withheld from each class for testing. The remaining images were used to train and validate a neural network for classifying vocal fold lesions. Two classifiers were developed. A multiclass system classified the five categories of benign lesions. A separate analysis was performed using a binary classifier trained to distinguish malignant-premalignant from benign lesions.

RESULTS

Precision ranged from 71.7% (polyps) to 89.7% (papilloma), and recall ranged from 70.0% (papilloma) to 88.0% (nodules) for the benign classifier. Overall accuracy for the benign classifier was 80.8%. The binary classifier correctly identified 92.0% of the malignant-premalignant lesions with an overall accuracy of 93.0%.

CONCLUSIONS

Autonomous classification of endoscopic images with artificial intelligence technology is possible. Better network implementations and larger datasets will continue to improve classifier accuracy. A clinically useful optical cancer screening system may require a multimodality approach that incorporates nonvisual spectra.

LEVEL OF EVIDENCE

NA Laryngoscope, 2020.

Value of Full-Field Optical Coherence Tomography Imaging for the Histological Assessment of Head and Neck Cancer

BACKGROUND AND OBJECTIVES

In head and neck surgery, intraoperative and postoperative evaluation of tumor margins is achieved by histopathological assessment, which is a multistep process. Intraoperative analysis of tumor margins to obtain a preliminary diagnosis is usually carried out on frozen sections. Analysis of frozen sections is challenging due to technical difficulties in processing. Full-field optical coherence tomography (FFOCT) provides ex vivo images of fresh tissue samples at a microscopic scale without tissue processing. The objectives of our study were to define the diagnostic criteria required to interpret head and neck FFOCT images and to evaluate the reliability of a histological diagnosis made on an "optical biopsy" produced by head and neck FFOCT imaging compared with conventional histology.

STUDY DESIGN/MATERIALS AND METHODS

First, we established an atlas of comparative images (FFOCT/standard histology) and defined the diagnostic criteria based on FFOCT images. Two pathologists subsequently performed a blinded review on 57 FFOCT images (32 patients). Specificity and sensitivity were measured by comparison with the standard histological diagnosis. The primary endpoint was major concordance, defined as two classifications leading to the same therapeutic decision (treatment/no treatment).

RESULTS

Pathologists identified four main criteria for tissue diagnosis on FFOCT images: heterogeneous cell distribution, stromal reaction, coiling, and keratinization abnormalities. The correlation study showed good results, with sensitivity from 88% to 90% and specificity from 81% to 87%, regardless of whether the FFOCT image review was performed by a pathologist with or without previous experience in optical imaging.

CONCLUSIONS

Our results demonstrate that FFOCT images can be used by pathologists for differential diagnosis, and that high-resolution FFOCT imaging can provide an assessment of microscopic architecture in head and neck tissues without tissue processing requirements. Lasers Surg. Med. © 2020 Wiley Periodicals, Inc.

Stimulation of collagen and elastin production in-vivo using 1,540 nm Er:Glass laser: assessment of safety and efficacy

Introduction: Induction of collagen and elastin remodeling in the human skin can be achieved by non-ablative fractional laser (NAFXL) and ablative fractional laser (AFXL). Our objective was to compare the safety, efficacy, tolerability, and ability to induce collagen and elastin remodeling of NAFXL versus AFXL in a series of treatments over time.Materials and Methods: In this prospective, proof of principle, single-case study, the safety, tolerability and efficacy of the laser systems were assessed via histopathology and clinical evaluations including photographs. Optical biopsies by means of multiphoton tomography (MPT) were used to evaluate the induction of collagen and elastin remodeling.Results: Treatments by both NAFXL and AFXL were well tolerated. The NAFXL system was found to be less painful and resulted in a shorter down- and healing times. MPT findings showed the superior capability of the AFXL procedure to induce collagen; on the other hand, elastin induction was more pronounced after NAFXL treatments.Conclusions: While NAFXL is as effective and safe as the traditional AFXL, it is better tolerated and has a shorter downtime. Serial optical biopsies over time over time can be a useful tool to assess the induction of collagen and elastin remodeling in the human skin.

A Miniature Fibre-Optic Raman Probe Fabricated by Ultrafast Laser-Assisted Etching

Optical biopsy describes a range of medical procedures in which light is used to investigate disease in the body, often in hard-to-reach regions via optical fibres. Optical biopsies can reveal a multitude of diagnostic information to aid therapeutic diagnosis and treatment with higher specificity and shorter delay than traditional surgical techniques. One specific type of optical biopsy relies on Raman spectroscopy to differentiate tissue types at the molecular level and has been used successfully to stage cancer. However, complex micro-optical systems are usually needed at the distal end to optimise the signal-to-noise properties of the Raman signal collected. Manufacturing these devices, particularly in a way suitable for large scale adoption, remains a critical challenge. In this paper, we describe a novel fibre-fed micro-optic system designed for efficient signal delivery and collection during a Raman spectroscopy-based optical biopsy. Crucially, we fabricate the device using a direct-laser-writing technique known as ultrafast laser-assisted etching which is scalable and allows components to be aligned passively. The Raman probe has a sub-millimetre diameter and offers confocal signal collection with 71.3% ± 1.5% collection efficiency over a 0.8 numerical aperture. Proof of concept spectral measurements were performed on mouse intestinal tissue and compared with results obtained using a commercial Raman microscope.

Real-time colorectal cancer diagnosis using PR-OCT with deep learning

Prior reports have shown optical coherence tomography (OCT) can differentiate normal colonic mucosa from neoplasia, potentially offering an alternative technique to endoscopic biopsy - the current gold-standard colorectal cancer screening and surveillance modality. To help clinical translation limited by processing the large volume of generated data, we designed a deep learning-based pattern recognition (PR) OCT system that automates image processing and provides accurate diagnosis potentially in real-time. Method: OCT is an emerging imaging technique to obtain 3-dimensional (3D) "optical biopsies" of biological samples with high resolution. We designed a convolutional neural network to capture the structure patterns in human colon OCT images. The network is trained and tested using around 26,000 OCT images acquired from 20 tumor areas, 16 benign areas, and 6 other abnormal areas. Results: The trained network successfully detected patterns that identify normal and neoplastic colorectal tissue. Experimental diagnoses predicted by the PR-OCT system were compared to the known histologic findings and quantitatively evaluated. A sensitivity of 100% and specificity of 99.7% can be reached. Further, the area under the receiver operating characteristic (ROC) curves (AUC) of 0.998 is achieved. Conclusions: Our results demonstrate that PR-OCT can be used to give an accurate real-time computer-aided diagnosis of colonic neoplastic mucosa. Future development of this system as an "optical biopsy" tool to assist doctors in real-time for early mucosal neoplasms screening and treatment evaluation following initial oncologic therapy is planned.

Label-free spectroscopic tissue characterization using fluorescence excitation-scanning spectral imaging

Spectral imaging approaches provide new possibilities for measuring and discriminating fluorescent molecules in living cells and tissues. These approaches often employ tunable filters and robust image processing algorithms to identify many fluorescent labels in a single image set. Here, we present results from a novel spectral imaging technology that scans the fluorescence excitation spectrum, demonstrating that excitation-scanning hyperspectral image data can discriminate among tissue types and estimate the molecular composition of tissues. This approach allows fast, accurate quantification of many fluorescent species from multivariate image data without the need of exogenous labels or dyes. We evaluated the ability of the excitation-scanning approach to identify endogenous fluorescence signatures in multiple unlabeled tissue types. Signatures were screened using multi-pass principal component analysis. Endmember extraction techniques revealed conserved autofluorescent signatures across multiple tissue types. We further examined the ability to detect known molecular signatures by constructing spectral libraries of common endogenous fluorophores and applying multiple spectral analysis techniques on test images from lung, liver and kidney. Spectral deconvolution revealed structure-specific morphologic contrast generated from pure molecule signatures. These results demonstrate that excitation-scanning spectral imaging, coupled with spectral imaging processing techniques, provides an approach for discriminating among tissue types and assessing the molecular composition of tissues. Additionally, excitation scanning offers the ability to rapidly screen molecular markers across a range of tissues without using fluorescent labels. This approach lays the groundwork for translation of excitation-scanning technologies to clinical imaging platforms.

Structural validation of facial skin using optical coherence tomography: A descriptive study

BACKGROUND

In this immediate ex vivo study, we aimed to identify the structures of normal and pathological facial skin using optical coherence tomography (OCT) and compared them to the gold standard histopathology.

MATERIAL AND METHODS

A total of 53 patients, with 57 suspicious facial lesions, participated in this study. A set of variables have been highlighted by the pathologist to represent the minimum unique features that could be used to diagnose a skin pathology have been included in a checklist. One pathologist used this checklist while examining the histopathology slides and one clinician while examining the OCT images. The data from both checklists have been reviewed and compared.

RESULTS

Optical coherence tomography's overall accuracy in diagnosing AK was 83%. Best accuracy was achieved in diagnosing BCC and was 97%, while it was 85% for cutaneous SCC. OCT failed to diagnose LM with an accuracy of 33.3% based on the two parameters of the pathology checklist, while it was 81% for malignant melanoma.

CONCLUSION

This study proved the success of OCT in identifying structural changes in normal and pathological facial skin. Further studies to prove its usefulness in vivo are recommended.

Understanding optical reflectance contrast for real-time characterization of epithelial precursor lesions

Detecting early-stage epithelial cancers and their precursor lesions are challenging as lesions could be subtle and focally or heterogeneously distributed over large mucosal areas. Optical coherence tomography (OCT) that enables wide-field imaging of subsurface microstructures in vivo is a promising screening tool for epithelial diseases. However, its diagnostic capability has not been fully appreciated since the optical reflectance contrast is poorly understood. We investigated the back-scattered intensities from clustered or packed nanometer scale intracellular scatterers using finite-difference time-domain method and 1-μm resolution form of OCT, and uncovered that there existed correlations between the reflectance contrasts and the ultrastructural clustering or packing states of these scatterers, which allows us to interpret the physiological state of the cells. Specifically, both polarized goblet cells and foveolar cells exhibited asymmetric reflectance contrast, but they could be differentiated by the optical intensity of the mucin cup due to the different ultrastructural make-ups of the mucin granules; keratinocytes could demonstrate varied cytoplasmic intensity and their cytoplasmic contrast was closely correlated with the packing state of keratin filaments. Further preliminary study demonstrated that these new understandings of OCT image contrast enables the characterization of precancerous lesions, which could complement the current morphology-based criteria in realizing "virtual histology" and would have a profound impact for the screening and surveillance of epithelial cancers.

Analysis of oral mucosa erosive-ulcerative lesions by reflectance confocal microscopy

In vivo Reflectance Confocal Microscopy (RCM) allows to optically biopsy vital tissues, non-invasively and in real time. It results in horizontal virtual slices at a microscopic resolution and correlating with conventional histopathology. The aim of the present work is to describe RCM cellular and architectural findings in oral mucosae affected by erosive-ulcerative diseases, thus highlighting in vivo the wellknown histological peculiarities. A series of conventionally diagnosed Recurrent Aphthous stomatitis (RAS) and Pemphigus Vulgaris (PV) erosive and/or ulcerative oral lesions underwent RCM imaging to establish the application of RCM imaging to this kind of inflammatory non-tumoral lesions. A total of 12 RAS-related lesions and 8 PV-related lesions were considered. RCM imaging was capable to visualize their microscopic peculiarities, mainly inflammatory infiltrate, vessel dilation (RAS) and acantholytic cells, intraepithelial clefts and inflammatory cell carpets (PV). Despite RCM may result unnecessary to diagnose oral lesions referred to RAS and PV, its capability to highlight their main microscopic features could be advantageously used to monitor the healing or worsening of the clinical situation as well as the responsiveness/refractoriness to therapy.

Analysis of lip pigmentations by reflectance confocal microscopy: report of two cases

Oral mucosa pigmentations belong to a heterogeneous variety of lesions, which are usually divided into two groups: exogenous or endogenous pigmentations. The pigmented lesions most frequently found in the oral mucosa are the amalgam tattoo, the melanotic macula and the nevus. All these lesions may affect every part of the oral mucosa, and they may represent a hard diagnostic challenge for the clinician; the clinical objective examination is not sufficient to make a correct diagnosis. Reflectance Confocal Microscopy provides a real-time microscopic evaluation of tissue layers, and is widely considered a useful auxiliary tool in monitoring skin and mucosa lesions. In this context, Reflectance Confocal Microscopy imaging is a valid aid in the management of oral mucosa pigmented lesions, to corroborate and support the diagnostic process.

Portable spectroscopic system for in vivo skin neoplasms diagnostics by Raman and autofluorescence analysis

The present paper studies the applicability of a portable cost-effective spectroscopic system for the optical screening of skin tumors. in vivo studies of Raman scattering and autofluorescence (AF) of skin tumors with the 785 nm excitation laser in the near-infrared region included malignant melanoma, basal cell carcinoma and various types of benign neoplasms. The efficiency of the portable system was evaluated by comparison with a highly sensitive spectroscopic system and with the diagnosis accuracy of a human oncologist. Partial least square analysis of Raman and AF spectra was performed; specificity and sensitivity of various skin oncological pathologies detection varied from 78.9% to 100%. Hundred percent accuracy of benign and malignant skin tumors differentiation is possible only with a combined analysis of Raman and AF signals.

Optical biopsy of head and neck cancer using hyperspectral imaging and convolutional neural networks

For patients undergoing surgical cancer resection of squamous cell carcinoma (SCCa), cancer-free surgical margins are essential for good prognosis. We developed a method to use hyperspectral imaging (HSI), a noncontact optical imaging modality, and convolutional neural networks (CNNs) to perform an optical biopsy of ex-vivo, surgical gross-tissue specimens, collected from 21 patients undergoing surgical cancer resection. Using a cross-validation paradigm with data from different patients, the CNN can distinguish SCCa from normal aerodigestive tract tissues with an area under the receiver operator curve (AUC) of 0.82. Additionally, normal tissue from the upper aerodigestive tract can be subclassified into squamous epithelium, muscle, and gland with an average AUC of 0.94. After separately training on thyroid tissue, the CNN can differentiate between thyroid carcinoma and normal thyroid with an AUC of 0.95, 92% accuracy, 92% sensitivity, and 92% specificity. Moreover, the CNN can discriminate medullary thyroid carcinoma from benign multinodular goiter (MNG) with an AUC of 0.93. Classical-type papillary thyroid carcinoma is differentiated from MNG with an AUC of 0.91. Our preliminary results demonstrate that an HSI-based optical biopsy method using CNNs can provide multicategory diagnostic information for normal and cancerous head-and-neck tissue, and more patient data are needed to fully investigate the potential and reliability of the proposed technique.

Cancer Detection Using Hyperspectral Imaging and Evaluation of the Superficial Tumor Margin Variance with Depth

Head and neck squamous cell carcinoma (SCCa) is primarily managed by surgical resection. Recurrence rates after surgery can be as high as 55% if residual cancer is present. In this study, hyperspectral imaging (HSI) is evaluated for detection of SCCa in ex-vivo surgical specimens. Several methods are investigated, including convolutional neural networks (CNNs) and a spectral-spatial variant of support vector machines. Quantitative results demonstrate that additional processing and unsupervised filtering can improve CNN results to achieve optimal performance. Classifying regions that include specular glare, the average AUC is increased from 0.73 [0.71, 0.75 (95% confidence interval)] to 0.81 [0.80, 0.83] through an unsupervised filtering and majority voting method described. The wavelengths of light used in HSI can penetrate different depths into biological tissue, while the cancer margin may change with depth and create uncertainty in the ground-truth. Through serial histological sectioning, the variance in cancer-margin with depth is also investigated and paired with qualitative classification heat maps using the methods proposed for the testing group SCC patients.