Wide-field spectral imaging of human ovary autofluorescence and oncologic diagnosis via previously collected probe data

Emerging clinical applications in oncology for non-invasive multi- and hyperspectral imaging of cell and tissue autofluorescence

Hyperspectral and multispectral imaging of cell and tissue autofluorescence is an emerging technology in which fluorescence imaging is applied to biological materials across multiple spectral channels. This produces a stack of images where each matched pixel contains information about the sample's spectral properties at that location. This allows precise collection of molecularly specific data from a broad range of native fluorophores. Importantly, complex information, directly reflective of biological status, is collected without staining and tissues can be characterised in situ, without biopsy. For oncology, this can spare the collection of biopsies from sensitive regions and enable accurate tumour mapping. For in vivo tumour analysis, the greatest focus has been on oral cancer, whereas for ex vivo assessment head-and-neck cancers along with colon cancer have been the most studied, followed by oral and eye cancer. This review details the scope and progress of research undertaken towards clinical translation in oncology.

Compact and ultracompact spectral imagers: technology and applications in biomedical imaging

Significance

Spectral imaging, which includes hyperspectral and multispectral imaging, can provide images in numerous wavelength bands within and beyond the visible light spectrum. Emerging technologies that enable compact, portable spectral imaging cameras can facilitate new applications in biomedical imaging.

Aim

With this review paper, researchers will (1) understand the technological trends of upcoming spectral cameras, (2) understand new specific applications that portable spectral imaging unlocked, and (3) evaluate proper spectral imaging systems for their specific applications.

Approach

We performed a comprehensive literature review in three databases (Scopus, PubMed, and Web of Science). We included only fully realized systems with definable dimensions. To best accommodate many different definitions of "compact," we included a table of dimensions and weights for systems that met our definition.

Results

There is a wide variety of contributions from industry, academic, and hobbyist spaces. A variety of new engineering approaches, such as Fabry-Perot interferometers, spectrally resolved detector array (mosaic array), microelectro-mechanical systems, 3D printing, light-emitting diodes, and smartphones, were used in the construction of compact spectral imaging cameras. In bioimaging applications, these compact devices were used for in vivo and ex vivo diagnosis and surgical settings.

Conclusions

Compact and ultracompact spectral imagers are the future of spectral imaging systems. Researchers in the bioimaging fields are building systems that are low-cost, fast in acquisition time, and mobile enough to be handheld.

An ultra-small nine-color spectrometer with a two-layer biparted ten-dichroic-mirror array and an image sensor

An ultra-small (54 × 58 × 8.5 mm) and large aperture (1 × 7 mm) nine-color spectrometer-using an array of ten dichroic mirrors "biparted" as two layers-was developed and used for snapshot spectral imaging. Incident-light flux with a cross section smaller than the aperture size is split into nine color fluxes with 20-nm-width contiguous wavelength bands and central wavelengths of 530, 550, 570, 590, 610, 630, 650, 670, and 690 nm. Images of the nine color fluxes are simultaneously and efficiently measured by an image sensor. Unlike a conventional dichroic-mirror array, the developed dichroic-mirror array has a unique biparted configuration that not only increases the number of colors that can be measured simultaneously but also improves the image resolution of each color flux. The developed nine-color spectrometer was used for four-capillary-array electrophoresis. Eight dyes concurrently migrating in each capillary were simultaneously quantified by nine-color laser-induced fluorescence detection. Since the nine-color spectrometer is not only ultra-small and inexpensive but also has high light throughput and sufficient spectral resolution for most spectral-imaging applications, it has the potential to be widely used in various fields.

Label-free hyperspectral imaging and deep-learning prediction of retinal amyloid β-protein and phosphorylated tau

Alzheimer's disease (AD) is a major risk for the aging population. The pathological hallmarks of AD-an abnormal deposition of amyloid β-protein (Aβ) and phosphorylated tau (pTau)-have been demonstrated in the retinas of AD patients, including in prodromal patients with mild cognitive impairment (MCI). Aβ pathology, especially the accumulation of the amyloidogenic 42-residue long alloform (Aβ42), is considered an early and specific sign of AD, and together with tauopathy, confirms AD diagnosis. To visualize retinal Aβ and pTau, state-of-the-art methods use fluorescence. However, administering contrast agents complicates the imaging procedure. To address this problem from fundamentals, ex-vivo studies were performed to develop a label-free hyperspectral imaging method to detect the spectral signatures of Aβ42 and pS396-Tau, and predicted their abundance in retinal cross-sections. For the first time, we reported the spectral signature of pTau and demonstrated an accurate prediction of Aβ and pTau distribution powered by deep learning. We expect our finding will lay the groundwork for label-free detection of AD.

Microscopy is better in color: development of a streamlined spectral light path for real-time multiplex fluorescence microscopy

Spectroscopic image data has provided molecular discrimination for numerous fields including: remote sensing, food safety and biomedical imaging. Despite the various technologies for acquiring spectral data, there remains a trade-off when acquiring data. Typically, spectral imaging either requires long acquisition times to collect an image stack with high spectral specificity or acquisition times are shortened at the expense of fewer spectral bands or reduced spatial sampling. Hence, new spectral imaging microscope platforms are needed to help mitigate these limitations. Fluorescence excitation-scanning spectral imaging is one such new technology, which allows more of the emitted signal to be detected than comparable emission-scanning spectral imaging systems. Here, we have developed a new optical geometry that provides spectral illumination for use in excitation-scanning spectral imaging microscope systems. This was accomplished using a wavelength-specific LED array to acquire spectral image data. Feasibility of the LED-based spectral illuminator was evaluated through simulation and benchtop testing and assessment of imaging performance when integrated with a widefield fluorescence microscope. Ray tracing simulations (TracePro) were used to determine optimal optical component selection and geometry. Spectral imaging feasibility was evaluated using a series of 6-label fluorescent slides. The LED-based system response was compared to a previously tested thin-film tunable filter (TFTF)-based system. Spectral unmixing successfully discriminated all fluorescent components in spectral image data acquired from both the LED and TFTF systems. Therefore, the LED-based spectral illuminator provided spectral image data sets with comparable information content so as to allow identification of each fluorescent component. These results provide proof-of-principle demonstration of the ability to combine output from many discrete wavelength LED sources using a double-mirror (Cassegrain style) optical configuration that can be further modified to allow for high speed, video-rate spectral image acquisition. Real-time spectral fluorescence microscopy would allow monitoring of rapid cell signaling processes (i.e., Ca²⁺ and other second messenger signaling) and has potential to be translated to clinical imaging platforms.

Nerve autofluorescence in near-ultraviolet light markedly enhances nerve visualization in vivo

BACKGROUND

During surgery, surgeons must accurately localize nerves to avoid injuring them. Recently, we have discovered that nerves fluoresce in near-ultraviolet light (NUV) light. The aims of the current study were to determine the extent to which nerves fluoresce more brightly than background and vascular structures in NUV light, and identify the NUV intensity at which nerves are most distinguishable from other tissues.

METHODS

We exposed sciatic nerves within the posterior thigh in five 250-300 gm Wistar rats, then observed them at four different NUV intensity levels: 20%, 35%, 50%, and 100%. Brightness of fluorescence was measured by fluorescence spectroscopy, quantified as a fluorescence score using Image-J software, and statistically compared between nerves, background, and both an artery and vein by unpaired Student's t tests with Bonferroni adjustment to accommodate multiple comparisons. Sensitivity, specificity, and accuracy were calculated for each NUV intensity.

RESULTS

At 20, 35, 50, and 100% NUV intensity, fluorescence scores for nerves versus background tissues were 117.4 versus 40.0, 225.8 versus 88.0, 250.6 versus 121.4, and 252.8 versus 169.4, respectively (all p < 0.001). Fluorescence scores plateaued at 50% NUV intensity for nerves, but continued to rise for background. At 35%, 50%, and 100% NUV intensity, a fluorescence score of 200 was 100% sensitive, specific, and accurate identifying nerves. At 100 NUV intensity, artery and vein scores were 61.8 and 60.0, both dramatically lower than for nerves (p < 0.001).

CONCLUSIONS

At all NUV intensities ≥ 35%, a fluorescence score of 200 is 100% accurate distinguishing nerves from other anatomical structures in vivo.

Multimodal imaging of laser speckle contrast imaging combined with mosaic filter-based hyperspectral imaging for precise surgical guidance

OBJECTIVE

To enable a real-time surgical guidance system that simultaneously monitors blood vessel perfusion, oxygen saturation, thrombosis, and tissue recovery by combining multiple optical imaging techniques into a single system: visible imaging, mosaic filter-based snapshot hyperspectral imaging (HSI), and laser speckle contrast imaging (LSCI).

METHODS

The multimodal optical imaging system was demonstrated by clamping blood vessels in the small intestines of rats to create areas of restricted blood flow. Subsequent tissue damage and regeneration were monitored during procedures. Using LSCI, vessel perfusion was measured, revealing the biological activity and survival of organ tissues. Blood oxygen saturation was monitored using HSI in the near-infrared region. Principal component analysis was used over the spectral dimension to identify an HSI wavelength combination optimized for hemodynamic biomarker visualization. HSI and LSCI were complimentary, identifying thrombus generation and tissue recovery, which was not possible in either modality alone.

RESULTS AND CONCLUSION

By analyzing multimodal tissue information from visible imaging, LSCI perfusion imaging, and HSI, a recovery prognosis could be determined based on the blood supply to the organ. The unique combination of the complementary imaging techniques into a single surgical microscope holds promise for improving the real-time determination of blood supply and tissue prognosis during surgery.

SIGNIFICANCE

Precise real-time monitoring for vascular anomalies promises to reduce the risk of organ damage in precise surgical operations such as tissue resection and transplantation. In addition, the convergence of label-free imaging technologies removes delays associated with the injection and diffusion of vascular monitoring dyes.

Nerve autofluorescence in near-ultraviolet light markedly enhances nerve visualization in vivo

BACKGROUND

During surgery, surgeons must accurately localize nerves to avoid injuring them. Recently, we have discovered that nerves fluoresce in near-ultraviolet light (NUV) light. The aims of the current study were to determine the extent to which nerves fluoresce more brightly than background and vascular structures in NUV light, and identify the NUV intensity at which nerves are most distinguishable from other tissues.

METHODS

We exposed sciatic nerves within the posterior thigh in five 250-300 gm Wistar rats, then observed them at four different NUV intensity levels: 20%, 35%, 50%, and 100%. Brightness of fluorescence was measured by fluorescence spectroscopy, quantified as a fluorescence score using Image-J software, and statistically compared between nerves, background, and both an artery and vein by unpaired Student's t tests with Bonferroni adjustment to accommodate multiple comparisons. Sensitivity, specificity, and accuracy were calculated for each NUV intensity.

RESULTS

At 20, 35, 50, and 100% NUV intensity, fluorescence scores for nerves versus background tissues were 117.4 versus 40.0, 225.8 versus 88.0, 250.6 versus 121.4, and 252.8 versus 169.4, respectively (all p < 0.001). Fluorescence scores plateaued at 50% NUV intensity for nerves, but continued to rise for background. At 35%, 50%, and 100% NUV intensity, a fluorescence score of 200 was 100% sensitive, specific, and accurate identifying nerves. At 100 NUV intensity, artery and vein scores were 61.8 and 60.0, both dramatically lower than for nerves (p < 0.001).

CONCLUSIONS

At all NUV intensities ≥ 35%, a fluorescence score of 200 is 100% accurate distinguishing nerves from other anatomical structures in vivo.

A review of the medical hyperspectral imaging systems and unmixing algorithms' in biological tissues

Hyperspectral fluorescence imaging (HFI) is a well-known technique in the medical research field and is considered a non-invasive tool for tissue diagnosis. This review article gives a brief introduction to acquisition methods, including the image preprocessing methods, feature selection and extraction methods, data classification techniques and medical image analysis along with recent relevant references. The process of fusion of unsupervised unmixing techniques with other classification methods, like the combination of support vector machine with an artificial neural network, the latest snapshot Hyperspectral imaging (HSI) and vortex analysis techniques are also outlined. Finally, the recent applications of hyperspectral images in cellular differentiation of various types of cancer are discussed.

Dark-field hyperspectral imaging for label free detection of nano-bio-materials

Nanomaterials are playing an increasingly important role in cancer diagnosis and treatment. Nanoparticle (NP)-based technologies have been utilized for targeted drug delivery during chemotherapies, photodynamic therapy, and immunotherapy. Another active area of research is the toxicity studies of these nanomaterials to understand the cellular uptake and transport of these materials in cells, tissues, and environment. Traditional techniques such as transmission electron microscopy, and mass spectrometry to analyze NP-based cellular transport or toxicity effect are expensive, require extensive sample preparation, and are low-throughput. Dark-field hyperspectral imaging (DF-HSI), an integration of spectroscopy and microscopy/imaging, provides the ability to investigate cellular transport of these NPs and to quantify the distribution of them within bio-materials. DF-HSI also offers versatility in non-invasively monitoring microorganisms, single cell, and proteins. DF-HSI is a low-cost, label-free technique that is minimally invasive and is a viable choice for obtaining high-throughput quantitative molecular analyses. Multimodal imaging modalities such as Fourier transform infrared and Raman spectroscopy are also being integrated with HSI systems to enable chemical imaging of the samples. HSI technology is being applied in surgeries to obtain molecular information about the tissues in real-time. This article provides brief overview of fundamental principles of DF-HSI and its application for nanomaterials, protein-detection, single-cell analysis, microbiology, surgical procedures along with technical challenges and future integrative approach with other imaging and measurement modalities. This article is categorized under: Diagnostic Tools > in vitro Nanoparticle-Based Sensing Diagnostic Tools > in vivo Nanodiagnostics and Imaging Implantable Materials and Surgical Technologies > Nanoscale Tools and Techniques in Surgery.

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.

Fast quantitative fluorescence authentication of milk powder and vanillin by a line-scan hyperspectral system

We present a fast hyperspectral line-scan fluorescence imaging system to verify the feasibility of quantitative fluorescence authentication of powders. Vanillin, which is restricted for use in milk powder, especially in milk powder for infants, is mixed with milk powder in different mass concentrations (5%, 10%, 30%, 50%, 70%, and 90%). Mixed powders are located on a motorized linear stage. A 405 nm line laser is utilized to excite the fluorescence of the sample. Based on galvo scanning, we can generate a laser line with high spatial resolution and high-intensity density on the samples. An imaging spectrometer with a complementary metal-oxide semiconductor (CMOS) camera as detector is built. The spectral range of the spectrometer is 365-810 nm, with about 1 nm spectral resolution. One snapshot of the CMOS can acquire the fluorescent spatial and spectral information of a line region in 100 ms. By scanning the motorized linear stage, we obtain the fluorescence hypercube of the sample. A 100×1926×1216 hypercube, which covers an area of 15  mm×5  mm, is obtained in 50 s. The imaging speed can be enhanced further by increasing the intensity of the excitation laser and the sensitivity of the area camera. Fully constrained least squares, a linear spectral mixture analysis, is utilized to analyze the hypercube obtained by our homemade imaging spectrometer, thus obtaining the pixel concentration of vanillin in each mixed powder. Linear regression analysis is used for the pixel concentration and mass concentration of vanillin. A linear relationship with coefficient of determination R² equal to one is observed, which demonstrates the capability of fluorescence hyperspectral quantitative analysis in powders.

Single-Cell Analysis Using Hyperspectral Imaging Modalities

Almost a decade ago, hyperspectral imaging (HSI) was employed by the NASA in satellite imaging applications such as remote sensing technology. This technology has since been extensively used in the exploration of minerals, agricultural purposes, water resources, and urban development needs. Due to recent advancements in optical re-construction and imaging, HSI can now be applied down to micro- and nanometer scales possibly allowing for exquisite control and analysis of single cell to complex biological systems. This short review provides a description of the working principle of the HSI technology and how HSI can be used to assist, substitute, and validate traditional imaging technologies. This is followed by a description of the use of HSI for biological analysis and medical diagnostics with emphasis on single-cell analysis using HSI.

Morphologic three-dimensional scanning of fallopian tubes to assist ovarian cancer diagnosis

The majority of high-grade serous ovarian cancers is now believed to originate in the fallopian tubes. Therefore, current practices include the pathological examination of excised fallopian tubes. Detection of tumors in the fallopian tubes using current clinical approaches remains difficult but is of critical importance to achieve accurate staging and diagnosis. Here, we present an intraoperative imaging system for the detection of human fallopian tube lesions. The system is based on optical coherence tomography (OCT) to access subepithelial tissue architecture. To demonstrate that OCT could identify lesions, we analyzed 180 OCT volumes taken from five different ovarian lesions and from healthy fallopian tubes, and compared them to standard pathological review. We demonstrated that qualitative features could be matched to pathological conditions. We then determined the feasibility of intraluminal imaging of intact human fallopian tubes by building a dedicated endoscopic single-fiber OCT probe to access the mucosal layer inside freshly excised specimens from five patients undergoing prophylactic surgeries. The probe insertion into the lumen acquired images over the entire length of the tubes without damaging the mucosa, providing the first OCT images of intact human fallopian tubes.

Ultraminiature optical design for multispectral fluorescence imaging endoscopes

A miniature wide-field multispectral endoscopic imaging system was developed enabling reflectance and fluorescence imaging over a broad wavelength range. At 0.8-mm diameter, the endoscope can be utilized for natural orifice imaging in small lumens such as the fallopian tubes. Five lasers from 250 to 642 nm are coupled into a 125 - ? m diameter multimode fiber and transmitted to the endoscope distal tip for illumination. Ultraviolet and blue wavelengths excite endogenous fluorophores, which can provide differential fluorescence emission images for health and disease. Visible wavelengths provide reflectance images that can be combined for pseudo-white-light imaging and navigation. Imaging is performed by a 300 - ? m diameter three-element lens system connected to a 3000-element fiber. The lens system was designed for a 70-deg full field of view, working distance from 3 mm to infinity, and 40% contrast at the Nyquist cutoff of the fiber bundle. Measured performance characteristics are near design goals. The endoscope was utilized to obtain example monochromatic, pseudo-white-light, and composite fluorescence images of phantoms and porcine reproductive tract. This work shows the feasibility of packaging a highly capable multispectral fluorescence imaging system into a miniature endoscopic system that may have applications in early detection of cancer.

Multispectral fluorescence imaging of human ovarian and fallopian tube tissue for early-stage cancer detection

With early detection, 5-year survival rates for ovarian cancer exceed 90%, yet no effective early screening method exists. Emerging consensus suggests over 50% of the most lethal form of the disease originates in the fallopian tube. Twenty-eight women undergoing oophorectomy or debulking surgery provided informed consent for the use of surgical discard tissue samples for multispectral fluorescence imaging. Using multiple ultraviolet and visible excitation wavelengths and emissions bands, 12 fluorescence and 6 reflectance images of 47 ovarian and 31 fallopian tube tissue samples were recorded. After imaging, each sample was fixed, sectioned, and stained for pathological evaluation. Univariate logistic regression showed cancerous tissue samples had significantly lower intensity than noncancerous tissue for 17 image types. The predictive power of multiple image types was evaluated using multivariate logistic regression (MLR) and quadratic discriminant analysis (QDA). Two MLR models each using two image types had receiver operating characteristic curves with area under the curve exceeding 0.9. QDA determined 56 image type combinations with perfect resubstituting using as few as five image types. Adaption of the system for future in vivo fallopian tube and ovary endoscopic imaging is possible, which may enable sensitive detection of ovarian cancer with no exogenous contrast agents.

Medical hyperspectral imaging: a review

Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. HSI acquires a three-dimensional dataset called hypercube, with two spatial dimensions and one spectral dimension. Spatially resolved spectral imaging obtained by HSI provides diagnostic information about the tissue physiology, morphology, and composition. This review paper presents an overview of the literature on medical hyperspectral imaging technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application.

Medical hyperspectral imaging: a review

Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. HSI acquires a three-dimensional dataset called hypercube, with two spatial dimensions and one spectral dimension. Spatially resolved spectral imaging obtained by HSI provides diagnostic information about the tissue physiology, morphology, and composition. This review paper presents an overview of the literature on medical hyperspectral imaging technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application.