Integrated photoacoustic and hyperspectral dual‐modality microscopy for co‐imaging of melanoma and cutaneous squamous cell carcinoma in vivo

Skin carcinoma such as melanoma (MM) and cutaneous squamous cell carcinoma (cSCC) are considered as the highest mortality and the most aggressive skin cancers in dermatology. In view that early diagnosis and treatment can greatly improve the survival rate and life quality of the patients, developing noninvasive and effective evaluation methods is of great significance for the detection and identification of early stage cutaneous cancers. In this article, we propose a hybrid photoacoustic and hyperspectral dual‐modality microscopy to evaluate and differentiate skin carcinoma by structural and multiphysiological parameters. The proposed system's imaging abilities are verified by mimic phantoms and normal mice experiments. Furthermore, in vivo characterization and evaluation results of MM and cSCC mice are obtained successfully, which prove this novel method could be used as a reliable and useful method for skin cancer detection in early stages.     

Estimating quantitative physiological and morphological tissue parameters of murine tumor models using hyperspectral imaging and optical profilometry

Understanding tumors and their microenvironment are essential for successful and accurate disease diagnosis. Tissue physiology and morphology are altered in tumors compared to healthy tissues, and there is a need to monitor tumors and their surrounding tissues, including blood vessels, non-invasively. This preliminary study utilizes a multimodal optical imaging system combining hyperspectral imaging (HSI) and three-dimensional (3D) optical profilometry (OP) to capture hyperspectral images and surface shapes of subcutaneously grown murine tumor models. Hyperspectral images are corrected with 3D OP data and analyzed using the inverse-adding doubling (IAD) method to extract tissue properties such as melanin volume fraction and oxygenation. Blood vessels are segmented using the B-COSFIRE algorithm from oxygenation maps. From 3D OP data, tumor volumes are calculated and compared to manual measurements using a vernier caliper. Results show that tumors can be distinguished from healthy tissue based on most extracted tissue parameters (). Furthermore, blood oxygenation is 50% higher within the blood vessels than in the surrounding tissue, and tumor volumes calculated using 3D OP agree within 26% with manual measurements using a vernier caliper. Results suggest that combining HSI and OP could provide relevant quantitative information about tumors and improve the disease diagnosis.     

Automatic identification and quantitative morphometry of unstained spinal nerve using molecular hyperspectral imaging technology

Quantitative observation of nerve fiber sections is often complemented by morphological analysis in both research and clinical condition. However, existing manual or semi-automated methods are tedious and labour intensive, fully automated morphometry methods are complicated as the information of color or gray images captured by traditional microscopy is limited. Moreover, most of the methods are time-consuming as the nerve sections need to be stained with some reagents before observation. To overcome these shortcomings, a molecular hyperspectral imaging system is developed and used to observe the spinal nerve sections. The molecular hyperspectral images contain both the structural and biochemical information of spinal nerve sections which is very useful for automatic identification and quantitative morphological analysis of nerve fibers. This characteristic makes it possible for researchers to observe the unstained spinal nerve and live cells in their native environment. To evaluate the performance of the new method, the molecular hyperspectral images were captured and the improved spectral angle mapper algorithm was proposed and used to segment the myelin contours. Then the morphological parameters such as myelin thickness and myelin area were calculated and evaluated. With these morphological parameters, the three dimension surface view images were drawn to help the investigators observe spinal nerve at different angles. The experiment results show that the hyperspectral based method has the potential to identify the spinal nerve more accurate than the traditional method as the new method contains both the spectral and spatial information of nerve sections.     

Scattering based hyperspectral imaging of plasmonic nanoplate clusters towards biomedical applications

A new optical scattering contrast‐agent based on polymer‐nanoparticle encapsulated silver nanoplates (PESNs) is presented. Silver nanoplates were chosen due to the flexibility of tuning their plasmon frequencies. The polymer coating preserves their physical and optical properties and confers other advantages such as controlled contrast agent delivery. Finite difference time domain (FDTD) simulations model the interaction of light with the nanoplates in different orientations in the cluster. Hyperspectral dark field microscopy (HYDFM) observes the scattering spectra of the PESNs. An unsupervised sequential maximum angle convex cone (SMACC) image analysis resolves spectral endmembers corresponding to different stacking orientations of the nanoplates. The orientation‐dependent endmembers qualitatively agree with the FDTD results. For contrast enhancement, the uptake and spatial distribution of PESNs are demonstrated by an HYDFM study of single melanoma cells to result in an enhanced contrast of up to 400%. A supervised spatial mapping of the endmembers obtained by the unsupervised SMACC algorithm reveals spatial distributions of PESNs with various clustering orientations of encapsulated nanoplates. Our study demonstrates tunability in plasmonics properties in clustered metal nanoparticles and its utility for the development of scatter‐based imaging contrast agents for a broad range of applications, including studies of single cells and other biomedical systems.

     

Optical hyperspectral imaging in microscopy and spectroscopy – a review of data acquisition

Rather than simply acting as a photographic camera capturing two‐dimensional (x, y) intensity images or a spectrometer acquiring spectra (λ), a hyperspectral imager measures entire three‐dimensional (x, y, λ) datacubes for multivariate analysis, providing structural, molecular, and functional information about biological cells or tissue with unprecedented detail. Such data also gives clinical insights for disease diagnosis and treatment. We summarize the principles underpinning this technology, highlight its practical implementation, and discuss its recent applications at microscopic to macroscopic scales.

Datacube acquisition strategies in hyperspectral imaging x, y, spatial coordinates; λ, wavelength.     

Intraoperative multispectral and hyperspectral label‐free imaging: A systematic review of in vivo clinical studies

Multispectral and hyperspectral imaging (HSI) are emerging optical imaging techniques with the potential to transform the way surgery is performed but it is not clear whether current systems are capable of delivering real‐time tissue characterization and surgical guidance. We conducted a systematic review of surgical in vivo label‐free multispectral and HSI systems that have been assessed intraoperatively in adult patients, published over a 10‐year period to May 2018. We analysed 14 studies including 8 different HSI systems. Current in‐vivo HSI systems generate an intraoperative tissue oxygenation map or enable tumour detection. Intraoperative tissue oxygenation measurements may help to predict those patients at risk of postoperative complications and in‐vivo intraoperative tissue characterization may be performed with high specificity and sensitivity. All systems utilized a line‐scanning or wavelength‐scanning method but the spectral range and number of spectral bands employed varied significantly between studies and according to the system's clinical aim. The time to acquire a hyperspectral cube dataset ranged between 5 and 30 seconds. No safety concerns were reported in any studies. A small number of studies have demonstrated the capabilities of intraoperative in‐vivo label‐free HSI but further work is needed to fully integrate it into the current surgical workflow.      

Development of an image pre‐processor for operational hyperspectral laryngeal cancer detection

Hyperspectral imaging (HSI) is a technology with high potential in the field of non‐invasive detection of cancer. However, in complex imaging situations like HSI of the larynx with a rigid endoscope, various image interferences can disable a proper classification of cancerous tissue. We identified three main problems: i) misregistration of single images in a HS cube due to patient heartbeat ii) image noise and iii) specular reflections (SR). Consequently, an image pre‐processor is developed in the current paper to overcome these image interferences. It encompasses i) image registration ii) noise removal by minimum noise fraction (MNF) transformation and iii) a novel SR detection method. The results reveal that the pre‐processor improves classification performance, while the newly developed SR detection method outperforms global thresholding technique hitherto used by 46%. The novel pre‐processor will be used for future studies towards the development of an operational scheme for HS‐based larynx cancer detection.

RGB image of the larynx derived from the hyperspectral cube and corresponding specular reflections ( a ) manually segmented and ( b ) detected by a novel specular reflection detection method.     

Autofluorescence hyperspectral imaging of radiofrequency ablation lesions in porcine cardiac tissue

Radiofrequency ablation (RFA) is a widely used treatment for atrial fibrillation, the most common cardiac arrhythmia. Here, we explore autofluorescence hyperspectral imaging (aHSI) as a method to visualize RFA lesions and interlesional gaps in the highly collagenous left atrium. RFA lesions made on the endocardial surface of freshly excised porcine left atrial tissue were illuminated by UV light (365 nm), and hyperspectral datacubes were acquired over the visible range (420–720 nm). Linear unmixing was used to delineate RFA lesions from surrounding tissue, and lesion diameters derived from unmixed component images were quantitatively compared to gross pathology. RFA caused two consistent changes in the autofluorescence emission profile: a decrease at wavelengths below 490 nm (ascribed to a loss of endogenous NADH) and an increase at wavelengths above 490 nm (ascribed to increased scattering). These spectral changes enabled high resolution, in situ delineation of RFA lesion boundaries without the need for additional staining or exogenous markers. Our results confirm the feasibility of using aHSI to visualize RFA lesions at clinically relevant locations. If integrated into a percutaneous visualization catheter, aHSI would enable widefield optical surgical guidance during RFA procedures and could improve patient outcome by reducing atrial fibrillation recurrence.

     

Autofluorescence imaging for recurrence detection in skin cancer postoperative scars

This clinical study is a first attempt to use autofluorescence for recurrence diagnosis of skin cancer in postoperative scars. The proposed diagnostic parameter is based on a reduction in scar autofluorescence, evaluated in the green spectral channel. The validity of the method has been tested on 110 postoperative scars from 56 patients suspected of non‐melanoma skin cancer, with eight patients (13 scars) available for the repeated examination. The recurrence diagnosis within a scar has been made after two subsequent autofluorescence check‐ups, representing the temporal difference between the scar autofluorescence amplitudes as a vector. The recognition of recurrence has been discussed to represent the significant deviations from the value of vector angle θ. This new autofluorescence‐based method can be easily integrated into the postoperative monitoring of surgical scars and can help diagnose the recurrence of skin cancer from the early stage of scar development.     

Understanding tissue specific compositions of bioenergy feedstocks through hyperspectral Raman imaging

Hyperspectral Raman imaging was used to study the tissue/cell type specific distribution of lignin and cellulose polymers within the plant cell walls. Distinct differences in cell wall compositions were identified between two potential bioenergy feedstocks: corn stover and Eucalyptus globulus. Characteristic bands of 627, 1,175, 1,206, and 1,428 cm⁻¹ were only observed for corn stover and 1,381 cm⁻¹ was only present in E. globulus. One‐dimensional and two‐dimensional chemical maps of lignin and cellulose were generated for the stem of corn stover, ranging from the epidermis to the pith area and revealed that lignin and cellulose abundance varies significantly among different cell types in the following order: sclerenchyma cells and tracheids (∼5 times) > epidermal cells (∼3 times) > bundle sheath cells > parenchyma cells. The Raman mapping methods developed on corn stover were also validated on E. globulus and clearly highlighted their difference in lignin composition. Biotechnol. Bioeng. 2011;108: 286–295. © 2010 Wiley Periodicals, Inc.     

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

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

Imaging depth variations in hyperspectral imaging: Development of a method to detect tumor up to the required tumor‐free margin width

Hyperspectral imaging is a promising technique for resection margin assessment during cancer surgery. Thereby, only a specific amount of the tissue below the resection surface, the clinically defined margin width, should be assessed. Since the imaging depth of hyperspectral imaging varies with wavelength and tissue composition, this can have consequences for the clinical use of hyperspectral imaging as margin assessment technique. In this study, a method was developed that allows for hyperspectral analysis of resection margins in breast cancer. This method uses the spectral slope of the diffuse reflectance spectrum at wavelength regions where the imaging depth in tumor and healthy tissue is equal. Thereby, tumor can be discriminated from healthy breast tissue while imaging up to a similar depth as the required tumor‐free margin width of 2 mm. Applying this method to hyperspectral images acquired during surgery would allow for robust margin assessment of resected specimens. In this paper, we focused on breast cancer, but the same approach can be applied to develop a method for other types of cancer.     

Diagnosis of early gastric cancer based on fluorescence hyperspectral imaging technology combined with partial‐least‐square discriminant analysis and support vector machine

This study investigated the feasibility of using fluorescence hyperspectral imaging technology to diagnose of early‐stage gastric cancer. Fluorescence spectral images of 76 patients who were pathologically diagnosed as non‐atrophic gastritis, premalignant lesions and gastric cancer were collected. Fluorescence spectra at 100‐pixel points were randomly extracted after binarization. Diagnostic models of non‐atrophic gastritis, premalignant lesions and gastric cancer were constructed through partial‐least‐square discriminant analysis (PLS‐DA) and support vector machine (SVM) algorithms. The prediction effects of PLS‐DA and SVM models were compared. Results showed that the average spectra of normal, precancerous and gastric cancer tissues significantly differed at 496, 546, 640 and 670 nm, and regular changes in fluorescence intensity at 546 nm were in the following order: normal > precancerous lesions > gastric cancer. Additionally, the effect of the diagnostic model established by SVM is significantly better than PLS‐DA which accuracy, specificity and sensitivity are above 94%. Experimental results revealed that the fast diagnostic model of early gastric cancer by combining fluorescence hyperspectral imaging technology and improved SVM was effective and feasible, thereby providing an accurate and rapid method for diagnosing early‐stage gastric cancer.      

Enhanced spatial resolution for snapshot hyperspectral imaging of blood perfusion and melanin information within human tissue

We report a reconstruction method to achieve high spatial resolution for hyperspectral imaging of chromophore features in skin in vivo. The method utilizes an established structure‐adaptive normalized convolution algorithm to reconstruct high spatial resolution of hyperspectral images from snapshot low‐resolution hyperspectral image sequences captured by a snapshot spectral camera. The reconstructed images at chromophore‐sensitive wavebands are used to map the skin features of interest. We demonstrate the method experimentally by mapping the blood perfusion and melanin features (moles) on the facial skin. The method relaxes the constrains of the relatively low spatial resolution in the snapshot hyperspectral camera, making it more usable in imaging applications.     

A label-free photonic crystal biosensor imaging method for detection of cancer cell cytotoxicity and proliferation

A label-free method for detecting the attachment of human cancer cells to a biosensor surface for rapid screening for biological activity is described, in which attachment of a cell results in highly localized increase of the resonant reflected wavelength of a photonic crystal narrowband reflectance filter incorporated into a standard 96-well microplate. An imaging detection instrument is used to determine the spatial distribution of attached cells by mapping the shift in reflected resonant wavelength as a function of position. The method enables monitoring of cancer cell attachment, cell proliferation, and cell detachment that is induced by exposure of the cells to drug compounds. We demonstrate the efficacy of this method as an early screening technique for the rapid quantification of the rate of cancer cell proliferation on the sensor surface, and subsequently as a means for quantifying cell detachment resulting from apoptosis that is induced by exposure of the cells to cytotoxic chemicals.     

Body mass index,height and early-onset basal cell carcinoma in a case-control study

IntroductionBasal cell carcinoma (BCC) is the most common malignancy in the US. Body mass index (BMI) and height have been associated with a variety of cancer types, yet the evidence regarding BCC is limited. Therefore, we evaluated BMI and height in relation to early-onset BCC (under age 40) and explored the potential role of ultraviolet (UV) radiation exposure and estrogen-related exposures in the BMI-BCC relationship.MethodsBCC cases (n = 377) were identified through a central dermatopathology facility in Connecticut. Control subjects (n = 389) with benign skin conditions were randomly sampled from the same database and frequency matched to cases on age (median = 36, interquartile range 33–39), gender, and biopsy site. Participants reported weight (usual adult and at age 18), adult height, sociodemographic, phenotypic, and medical characteristics, and prior UV exposures. We calculated multivariate odds ratios (ORs) and 95% confidence intervals (CIs) using unconditional logistic regression models.ResultsAdult BMI was inversely associated with early-onset BCC (obese vs. normal OR = 0.43, 95% CI = 0.26–0.71). A similar inverse association was present for BMI at age 18 (OR = 0.54, 95% CI = 0.34–0.85). Excluding UV exposures from the BMI models and including estrogen-related exposures among women only did not alter the association between BMI and BCC, indicating limited mediation or confounding. We did not observe an association between adult height and BCC (OR per cm = 1.00, 95% CI = 0.98–1.02).ConclusionsWe found a significant inverse association between BMI and early-onset BCC, but no association between height and BCC. This association was not explained by UV exposures or estrogen-related exposures in women.     

Autofluorescence and white light imaging‐guided endoscopic Raman and diffuse reflectance spectroscopy for in vivo nasopharyngeal cancer detection

Nasopharyngeal cancer (NPC) is an endemic with high incidence in Southern China and Southeast Asia countries. Screening for NPC under conventional white light imaging (WLI) nasopharyngoscope examination remains a great clinical challenge due to its poor sensitivity. Here, we developed an integrated 4‐modality endoscopy system combining WLI, autofluorescence imaging (AFI), diffuse reflectance spectroscopy and Raman spectroscopy technologies for in vivo endoscopic cancer detection for the first time. A pilot clinical test of the system for NPC detection was conducted, in which 283 in vivo Raman and diffuse reflectance spectral data sets from 30 NPC patients and 30 healthy subjects were acquired under the guidance of AFI and WLI. Both high diagnostic sensitivity (98.6%) and high specificity (95.1%) for differentiating cancer from normal tissue sites were achieved using this system combined with principal component analysis‐linear discriminant analysis diagnostic algorithm, demonstrating great potential for improving real‐time, in vivo diagnosis of NPC at endoscopy.      

In vivo nonlinear optical imaging to monitor early microscopic changes in a murine cutaneous squamous cell carcinoma model

Early detection of cutaneous squamous cell carcinoma (cSCC) can enable timely therapeutic and preventive interventions for patients. In this study, in vivo nonlinear optical imaging (NLOI) based on two‐photon excitation fluorescence (TPEF) and second harmonic generation (SHG), was used to non‐invasively detect microscopic changes occurring in murine skin treated topically with 7,12‐dimethylbenz(a)anthracene (DMBA). The optical microscopic findings and the measured TPEF‐SHG index show that NLOI was able to clearly detect early cytostructural changes in DMBA treated skin that appeared clinically normal. This suggests that in vivo NLOI could be a non‐invasive tool to monitor early signs of cSCC.

In vivo axial NLOI scans of normal murine skin (upper left), murine skin with preclinical hyperplasia (upper right), early clinical murine skin lesion (lower left) and late or advanced murine skin lesion (lower right).     

Back Cover: Autofluorescence and white light imaging‐guided endoscopic Raman and diffuse reflectance spectroscopy for in vivo nasopharyngeal cancer detection (J. Biophotonics 4/2018)

An integrated 4‐modality endoscopy system combining white light imaging, autofluorescence imaging, diffuse reflectance spectroscopy and Raman spectroscopy technologies was developed for in vivo endoscopic nasopharyngeal cancer detection. Both high diagnostic sensitivity (98.6%) and high specificity (95.1%) for differentiating cancer from normal tissue sites were achieved using this system combined with multivariate diagnostic algorithm, demonstrating great potential for improving real‐time, in vivo diagnosis of cancer at endoscopy. Further details can be found in the article by Duo Lin et al. ( e201700251 )

     

Characterization of blood coagulation dynamics and oxygenation in ex‐vivo retinal vessels by fluorescence hyperspectral imaging

Blood coagulation mechanisms forming a blood clot and preventing hemorrhage have been extensively studied in the last decades. Knowing the mechanisms behind becomes very important particularly in the case of blood vessel diseases. Real‐time and accurate diagnostics accompanied by the therapy are particularly needed, for example, in diseases related to retinal vasculature. In our study, we employ for the first time fluorescence hyperspectral imaging (fHSI) combined with the spectral analysis algorithm concept to assess physical as well as functional information of blood coagulation in real‐time. By laser‐induced local disruption of retinal vessels to mimic blood leaking and subsequent coagulation and a proper fitting algorithm, we were able to reveal and quantify the extent of local blood coagulation through direct identification of the change of oxyhemoglobin concentration within few minutes. We confirmed and illuminated the spatio‐temporal evolution of the essential role of erythrocytes in the coagulation cascade as the suppliers of oxygenated hemoglobin. By additional optical tweezers force manipulation, we showed immediate aggregation of erythrocytes at the coagulation site. The presented fluorescence‐based imaging concept could become a valuable tool in various blood coagulation diagnostics as well as theranostic systems if coupled with the laser therapy.