A theoretical‐experimental methodology for assessing the sensitivity of biomedical spectral imaging platforms,assays, and analysis methods

Spectral imaging technologies have been used for many years by the remote sensing community. More recently, these approaches have been applied to biomedical problems, where they have shown great promise. However, biomedical spectral imaging has been complicated by the high variance of biological data and the reduced ability to construct test scenarios with fixed ground truths. Hence, it has been difficult to objectively assess and compare biomedical spectral imaging assays and technologies. Here, we present a standardized methodology that allows assessment of the performance of biomedical spectral imaging equipment, assays, and analysis algorithms. This methodology incorporates real experimental data and a theoretical sensitivity analysis, preserving the variability present in biomedical image data. We demonstrate that this approach can be applied in several ways: to compare the effectiveness of spectral analysis algorithms, to compare the response of different imaging platforms, and to assess the level of target signature required to achieve a desired performance. Results indicate that it is possible to compare even very different hardware platforms using this methodology. Future applications could include a range of optimization tasks, such as maximizing detection sensitivity or acquisition speed, providing high utility for investigators ranging from design engineers to biomedical scientists.

     

Front Cover: A theoretical‐experimental methodology for assessing the sensitivity of biomedical spectral imaging platforms,assays, and analysis methods (J. Biophotonics 1/2018)

A hyperspectral image data cube acquired from HEK‐293 cells labeled with cytoplasmic and nuclear stains: Calcein Green and NucBlu. The top view (XY plane) displays three spectrally unmixed channels for cellular autofluorescence (red), Calcein Green (green), and NucBlue (blue). The Z axis shows spectral information, from low to high wavelength. The article by Leavesley and colleagues describes an approach for calculating the sensitivity of spectral imaging assays for detecting a fluorescence signature within a mix of other signatures or autofluorescence. Further details can be found in the article by Silas J. Leavesley et al. ( e201600227 ).

     

Investigation on the potential of Mueller matrix imaging for digital staining

Digital staining based on Mueller matrix measurements and their derivatives was investigated. Mueller matrix imaging was performed at the microscopic level on gastric tissue sections. Full Mueller matrices (4 × 4) were reconstructed using recorded images, followed by the extraction of polarization parameters. The most effective parameters and their combinations were extracted from Mueller matrix elements, principal component scores and polarization parameters respectively to classify samples into three categories – i.e. cancer, dysplasia and intestinal metaplasia/normal glands for various regions of interest sizes. It was observed that two‐step classification yielded higher classification accuracy than the traditional one‐step classification and that pixel classification based on Mueller matrix elements yielded higher accuracy than that based on polarization parameters and derived principal components. Moreover, Mueller matrix images with a lower spatial resolution generated higher classification accuracy but those with a higher spatial resolution revealed more morphological details.ns.

The original stained image (top) and the digital staining image (bottom).     

龈下菌斑涂片两种染色分类方法的比较

目的:用革兰染色和刚果红负染两种不同的染色方法对同一龈下菌斑样本进行分类计数,比较两种分类方法的优缺点,提出应用中的问题以及解决方法.方法:随机抽样采集40例牙周病患者的80个位点龈下菌斑,同一标本进行生理盐水涂片革兰染色和刚果红负染.光学显微镜油镜(15×100)镜检共计数200个细菌,包括5种不同形状细菌.采用SPSS 10.01统计软件,对数据进行分析.结果:两种染色分类方法计数统计结果为螺旋体、弯曲菌、梭形菌3种菌数值P＞0.05无统计学意义,而球菌、杆菌2种菌数值经统计P＜0.01有高度统计学意义.结论:刚果红负染简便易行,但龈下菌斑球菌、杆菌进行百分计数时,不适宜用刚果红负染法,应根据实验目的选择恰当的方法.     

Synthetic data framework to estimate the minimum detectable concentration of contrast agents for multispectral optoacoustic imaging of small animals

The concentrations of contrast agents for optoacoustic imaging of small animals must usually be optimized through extensive pilot experiments on a case‐by‐case basis. The present work describes a streamlined approach for determining the minimum detectable concentration (MDC) of a contrast agent given experimental conditions and imaging system parameters. The developed Synthetic Data Framework (SDF) allows estimation of MDCs of various contrast agents under different tissue conditions without extensive animal experiments. The SDF combines simulated optoacoustic signals from exogenously administered contrast agents with in vivo experimental signals from background tissue to generate realistic synthetic multispectral optoacoustic images. In this paper, the SDF is validated with in vivo measurements and demonstrates close agreement between SDF synthetic data and experimental data in terms of both image intensity and MDCs. Use of the SDF to estimate MDCs for fluorescent dyes and nanoparticles at different tissue depths and for imaging lesions of different sizes is illustrated.     

4种染色方法对甜瓜白粉病菌染色效果的观察比较

考马斯亮蓝组织透明染色方法可以清楚观察到白粉病菌的5个发育阶段,即萌发的分生孢子、初生芽管、胞间菌丝、分生孢子梗和后期菌落。考马斯亮蓝几乎使寄主组织不着色,不产生背景色干扰,而菌体变深蓝色。苯胺蓝组织透明染色方法也可观察到病菌的不同发育阶段,但苯胺蓝易使寄主组织产生浅蓝色背景,而菌体呈现深蓝色,观察效果不理想。荧光素钠和苯胺蓝两种荧光染色方法均能使菌体在紫外或者蓝光下产生黄绿色荧光,而寄主组织呈现黑色背景,强烈的反差利于观察。荧光素钠可以观察到菌体整个发育阶段。苯胺蓝只适合于前期菌体入侵过程的观察。     

Fluorescent multiplexing of 3D spheroids: Analysis of biomarkers using automated immunohistochemistry staining platform and multispectral imaging

In preclinical cancer studies, three-dimensional (3D) cell spheroids and aggregates are preferred over monolayer cell cultures due to their architectural and functional similarity to solid tumors. We performed a proof-of-concept study to generate physiologically relevant and predictive preclinical models using non–small cell lung adenocarcinoma, and colon and colorectal adenocarcinoma cell line-derived 3D spheroids and aggregates. Distinct panels were designed to determine the expression profiles of frequently studied biomarkers of the two cancer subtypes. The lung adenocarcinoma panel included ALK, EGFR, TTF-1, and CK7 biomarkers, and the colon and colorectal adenocarcinoma panel included BRAF V600E, MSH2, MSH6, and CK20. Recent advances in immunofluorescence (IF) multiplexing and imaging technology enable simultaneous detection and quantification of multiple biomarkers on a single slide. In this study, we performed IF staining of multiple biomarkers per section on formalin-fixed paraffin-embedded 3D spheroids and aggregates. We optimized protocol parameters for automated IF and demonstrated staining concordance with automated chromogenic immunohistochemistry performed with validated protocols. Next, post-acquisition spectral unmixing of the captured fluorescent signals were utilized to delineate four differently stained biomarkers within a single multiplex IF image, followed by automated quantification of the expressed markers. This workflow has the potential to be adapted to preclinical high-throughput screening and drug efficacy studies utilizing 3D spheroids from cancer cell lines and patient-derived organoids. The process allows for cost, time, and resource savings through concurrent staining of several biomarkers on a single slide, the ability to study the interactions of multiple expressed proteins within a single region of interest, and enable quantitative assessment of biomarkers in cancer cells.     

Environment‐specific spectral modeling: A new tool for the analysis of biological specimens

The recent discovery of fluorescent dyes for improving pathologic tissues identification has highlighted the need of robust methods for performance validation especially in the field of fluorescence‐guided surgery. Optical imaging of excised tissue samples is the reference tool to validate the association between dyes localization and the underlying histology in a controlled environment. Spectral unmixing may improve the validation process discriminating dye from endogenous signal. Here, an innovative spectral modeling approach that weights the spectral shifts associated with changes in chemical environment is described. The method is robust against spectral shift variations and its application leads to unbiased spectral weights estimates as demonstrated by numerical simulations. Finally, spectral shifts values computed pixel‐wise from spectral images are used to display additional information with potential diagnostic value.      

Smartphone‐based spectral imaging otoscope: System development and preliminary study for evaluation of its potential as a mobile diagnostic tool

We develop a novel smartphone‐based spectral imaging otoscope for telemedicine and examine its capability for the mobile diagnosis of middle ear diseases. The device was applied to perform spectral imaging and analysis of an ear‐mimicking phantom and a normal and abnormal tympanic membrane for evaluation of its potential for the mobile diagnosis. Spectral classified images were obtained via online spectral analysis in a remote server. The phantom experimental results showed that it allowed us to distinguish four different fluids located behind a semitransparent membrane. Also, in the spectral classified images of normal ears (n = 3) and an ear with chronic otitis media (n = 1), the normal and abnormal regions in each ear could be quantitatively distinguished with high contrast. These preliminary results thus suggested that it might have the potentials for providing quantitative information for the mobile diagnosis of various middle ear diseases.     

In vivo monitoring blood‐brain barrier permeability using spectral imaging through optical clearing skull window

The blood‐brain barrier (BBB) plays a key role in the health of the central nervous system. Opening the BBB is very important for drug delivery to brain tissues to enhance the therapeutic effect on brain diseases. It is necessary to in vivo monitor the BBB permeability for assessing drug release with high resolution; however, an effective method is lacking. In this work, we developed a new method that combined spectral imaging with an optical clearing skull window to in vivo dynamically monitor BBB opening caused by 5‐aminolevulinic acid (5‐ALA)‐mediated photodynamic therapy (PDT), in which the Evans blue dye (EBd) acted as an indicator of the BBB permeability. Using this method, we effectively monitored the cerebrovascular EBd leakage process. Moreover, the analysis of changes in the vascular and extravascular EBd concentrations demonstrated that the PDT‐induced BBB opening exhibited spatiotemporal differences in the cortex. This spectral imaging method based on the optical clearing skull window provides a low‐cost and simply operated tool for in vivo monitoring BBB opening process. This has a high potential for the visualization of drug delivery to the central nervous system. Thus, it is of tremendous significance in brain disease therapy. Monitoring the changes in PDT‐induced BBB permeability by evaluating the EBd concentration using an optical clearing skull window. (A) Entire brains and coronal sections following treatment of PDT with/without an optical clearing skull window after injection of EBd. (B) Typical EBd distribution maps before and after laser irradiation captured by the spectral imaging method. (Colorbar represents the EBd concentration).      

Multiple functional linear model for association analysis of RNA-seq with imaging

Emerging integrative analysis of genomic and anatomical imaging data which has not been well developed, provides invaluable information for the holistic discovery of the genomic structure of disease and has the potential to open a new avenue for discovering novel disease susceptibility genes which cannot be identified if they are analyzed separately. A key issue to the success of imaging and genomic data analysis is how to reduce their dimensions. Most previous methods for imaging information extraction and RNA-seq data reduction do not explore imaging spatial information and often ignore gene expression variation at the genomic positional level. To overcome these limitations, we extend functional principle component analysis from one dimension to two dimensions (2DFPCA) for representing imaging data and develop a multiple functional linear model (MFLM) in which functional principal scores of images are taken as multiple quantitative traits and RNA-seq profile across a gene is taken as a function predictor for assessing the association of gene expression with images. The developed method has been applied to image and RNA-seq data of ovarian cancer and kidney renal clear cell carcinoma (KIRC) studies. We identified 24 and 84 genes whose expressions were associated with imaging variations in ovarian cancer and KIRC studies, respectively. Our results showed that many significantly associated genes with images were not differentially expressed, but revealed their morphological and metabolic functions. The results also demonstrated that the peaks of the estimated regression coefficient function in the MFLM often allowed the discovery of splicing sites and multiple isoforms of gene expressions.     

Detecting fluorescent protein expression and co-localisation on single secretory vesicles with linear spectral unmixing

Many questions in cell biology and biophysics involve the quantitation of co-localisation and the interaction of proteins tagged with different fluorophores. However, the incomplete separation of the different colour channels due to the presence of autofluorescence, along with cross-excitation and emission "bleed-through" of one colour channel into the other, all combine to render the interpretation of multi-band images ambiguous. Here we introduce a new live-cell epifluorescence spectral imaging and linear unmixing technique for classifying resolution-limited point objects containing multiple fluorophores. We demonstrate the performance of our technique by detecting, at the single-vesicle level, the co-expression of the vesicle-associated membrane protein, VAMP-2 (also called synaptobrevin-2), linked to either enhanced green fluorescent protein (EGFP) or citrine [a less pH-sensitive variant of enhanced yellow fluorescent protein (EYFP)], in mouse cortical astrocytes. In contrast, the co-expression of VAMP-2-citrine and the lysosomal transporter sialine fused to EGFP resulted in little overlap. Spectral imaging and linear unmixing permit us to fingerprint the expression of spectrally overlapping fluorescent proteins on single secretory organelles in the presence of a spectrally broad autofluorescence. Our technique provides a robust alternative to error-prone dual- or triple colour co-localisation studies.     

Methyl green-pyronin Y staining of nucleic acids: studies on the effects of staining time,dye composition and diffusion rates

Since the introduction of the methyl green-pyronin Y procedure as a differential histological stain more than 100 years ago, the method has become a histochemical procedure for differential demonstration of DNA and RNA. Numerous variants of the procedure have been suggested, and a number of hypotheses have been put forward concerning kinetics and binding mechanisms. Using both filter paper models containing DNA, RNA or heparin and histological sections, we have attempted to evaluate the kinetics of staining and the role of staining time for methyl green and pyronin Y by applying the dyes individually, simultaneously and sequentially. The results are presented as color charts approximating the observed staining patterns using a computerized palette. Our results indicate unequivocally that the differential staining is not time-dependent, but that it is dictated by the relative concentrations of methyl green and pyronin Y and by the pH of the staining solution.     

Methyl green-pyronin Y staining of nucleic acids: studies on the effects of staining time, dye composition and diffusion rates

Since the introduction of the methyl green-pyronin Y procedure as a differential histological stain more than 100 years ago, the method has become a histochemical procedure for differential demonstration of DNA and RNA. Numerous variants of the procedure have been suggested, and a number of hypotheses have been put forward concerning kinetics and binding mechanisms. Using both filter paper models containing DNA, RNA or heparin and histological sections, we have attempted to evaluate the kinetics of staining and the role of staining time for methyl green and pyronin Y by applying the dyes individually, simultaneously and sequentially. The results are presented as color charts approximating the observed staining patterns using a computerized palette. Our results indicate unequivocally that the differential staining is not time-dependent, but that it is dictated by the relative concentrations of methyl green and pyronin Y and by the pH of the staining solution.     

Basic Caenorhabditis elegans methods: synchronization and observation

Research into the molecular and developmental biology of the nematode Caenorhabditis elegans was begun in the early seventies by Sydney Brenner and it has since been used extensively as a model organism. C. elegans possesses key attributes such as simplicity, transparency and short life cycle that have made it a suitable experimental system for fundamental biological studies for many years. Discoveries in this nematode have broad implications because many cellular and molecular processes that control animal development are evolutionary conserved. C. elegans life cycle goes through an embryonic stage and four larval stages before animals reach adulthood. Development can take 2 to 4 days depending on the temperature. In each of the stages several characteristic traits can be observed. The knowledge of its complete cell lineage together with the deep annotation of its genome turn this nematode into a great model in fields as diverse as the neurobiology, aging, stem cell biology and germ line biology. An additional feature that makes C. elegans an attractive model to work with is the possibility of obtaining populations of worms synchronized at a specific stage through a relatively easy protocol. The ease of maintaining and propagating this nematode added to the possibility of synchronization provide a powerful tool to obtain large amounts of worms, which can be used for a wide variety of small or high-throughput experiments such as RNAi screens, microarrays, massive sequencing, immunoblot or in situ hybridization, among others. Because of its transparency, C. elegans structures can be distinguished under the microscope using Differential Interference Contrast microscopy, also known as Nomarski microscopy. The use of a fluorescent DNA binder, DAPI (4',6-diamidino-2-phenylindole), for instance, can lead to the specific identification and localization of individual cells, as well as subcellular structures/defects associated to them.     

Quantitative FRET measurement based on spectral unmixing of donor,acceptor and spontaneous excitation‐emission spectra

The spontaneous excitation‐emission (ExEm) spectrum is introduced to the quantitative mExEm‐spFRET methodology we recently developed as a spectral unmixing component for quantitative fluorescence resonance energy transfer measurement, named as SPEES‐FRET method. The spectral fingerprints of both donor and acceptor were measured in HepG2 cells with low autofluorescence separately expressing donor and acceptor, and the spontaneous spectral fingerprint of HEK293 cells with strong autofluoresence was measured from blank cells. SPEES‐FRET was performed on improved spectrometer‐microscope system to measure the FRET efficiency (E) and concentration ratio (R _C) of acceptor to donor vales of FRET tandem plasmids in HEK293 cells, and obtained stable and consistent results with the expected values. Moreover, SPEES‐FRET always obtained stable results for the bright and dim cells coexpressing Cerulean and Venus or Cyan Fluorescent Protein (CFP)‐Bax and Yellow fluorescent protein (YFP)‐Bax, and the E values between CFP‐Bax and YFP‐Bax were 0.02 for healthy cells and 0.14 for the staurosporine (STS)‐treated apoptotic cells. Collectively, SPEES‐FRET has very strong robustness against cellular autofluorescence, and thus is applicable to quantitative evaluation on the protein‐protein interaction in living cells with strong autofluoresence.      

Bismuth chemistry and the glutaraldehyde insensitive staining reaction

The free metal ion, Bi3+, is the only chemical species of bismuth that stains a strongly bismuth-reactive molecule, polyarginine, in vitro. The bismuth solution specifically requires tartrate as a chelating agent for the reaction to occur between pH 7.4 and 8.0. Since Bi3+ reacts strongly with polyarginine, creatine and ATP fixed to cellulose acetate strips and DEAE-cellulose and P-cellulose, the free metal ion (Bi3+) may bind to phosphate or guanidyl groups, or both, after glutaraldehyde fixation.     

CLASI-FISH: Principles of combinatorial labeling and spectral imaging

Although the number of phylotypes present in a microbial community may number in the hundreds or more, until recently, fluorescence in situ hybridization has been used to label, at most, only a handful of different phylotypes in a single sample. We recently developed a technique, CLASI-FISH for combinatorial labeling and spectral imaging – fluorescence in situ hybridization, to greatly expand the number of distinguishable taxa in a single FISH experiment. The CLASI technique involves labeling microbes of interest with combinations of probes coupled with spectral imaging to allow the use of fluorophores with highly overlapping excitation and emission spectra. Here, we present the basic principles and theory of CLASI-FISH along with some guidelines for performing CLASI-FISH experiments. We further include a protocol for creating fluorescence spectral reference standards, a vital component of successful CLASI-FISH.