Spectral unmixing of imaged fluorophores

Abstract

Systems and methods for calibrating an imager for unmixing of images with multiple fluorophores is described. One example method performed by a computing device includes receiving one or more single-color control images, a foreground channel, and a background channel. The single-color control images are images of the sample with a single fluorophore applied to the sample, and the foreground channel and the background channel are associated with the fluorophore. The method includes determining a difference between the foreground channel and the background channel, acquiring a foreground pixel mask from the difference, averaging a set of foreground pixels in the foreground pixel mask to generate a first spectrum, and subtracting an unstained spectrum from the first spectrum to generate a second spectrum. The second spectrum defines a spectral profile of the sample. A calibration slide and a method of preparing a calibration slide are also described.

Description

SPECTRAL UNMIXING OF IMAGED FLUOROPHORESFIELD

[0001] This disclosure relates to fluorescence imaging. More specifically, the present disclosure relates to spectral unmixing of images with multiple fluorophores that may be overlapping in their spectra that are acquired using fluorescence microscopy.BACKGROUND

[0002] Microscopy of sectioned tissue samples stained with fluorescent dyes and / or immuno staining (e.g., direct or indirect staining with primary or secondary antibodies conjugated to fluorophores) provides valuable histological, cellular and biomarker information. When multiple fluorescent reagents are used simultaneously for the same tissue sample spectral bleed- through, i.e., detection of fluorescence from neighboring fluorescent channels in the channel of interest can hamper identification of actual targets. One workaround would be to limit the number of targets by staining samples with a few spectrally separate fluorophores. However, multiplexing the detection is often required since the availability of tissue samples can be limited, and the tissue and the detection reagents can be expensive. Fluorescence imaging is based on photochemistry of dyes. To detect a fluorescence image with a camera the chemical reactions initiated by light absorption, where molecules absorb photons, become excited, and then emit light (fluorescence) as they return to their ground state need to be studied. The fluorescence absorption spectrum and the fluorescence emission spectrum of a set of dyes needs to be known in to define dyes candidates for spectral unmixing at given plex. Based on that knowledge spectral characteristics of light source and filters are optimized. Precise knowledge of the signatures of dye fluorescence absorption (fluorescence excitation spectrum), and the dye emission (fluorescence emission spectrum) is needed to achieve successful unmixing at high plex.

[0003] Accordingly, there is a need for unmixing spectra of multiple fluorescent reagents to produce individual images.SUMMARY

[0004] Systems and methods described herein generally relate to capturing spectra using fluorescence microscopy. When acquiring data from biological samples with multiple overlapping fluorophores, it is desirable to separate the fluorophores into individual fluorophore channels. Accordingly, systems and methods described herein provide for calibrating a fluorescence microscope to separate fluorophores within captured images. Calibration includes capturing an unstained image of a sample and a plurality of images of samples stained with a single fluorophore (referred to herein as single-color control samples). The unstained image and the plurality of single-color control sample images are used to generate an unmixing matrix for desired fluorescence channels. The unmixing matrix is then used to extract individual fluorophore channels from multi-channel images of samples.

[0005] One example provides a method for automatically extracting spectral profiles of imaged samples. The method includes receiving, by a computing device, one or more single color control images, a foreground channel, and a background channel. As used in this disclosure, a foreground channel refers to a specific channel which includes the area or signal of interest. A background channel represents a surrounding area with minimal to no fluorescence from a dye which is used to estimate and subtract background noise which may include autofluorescence from the foreground signal. As used herein, autofluorescence is the natural fluorescent emission from biological structures or other substances in the presence of excitation light. The method includes determining, by the computing device, a difference between the foreground channel and the background channel, acquiring, by the computing device, a foreground pixel mask from the difference, averaging, by the computing device, a set of foreground pixels in the foreground pixel mask to generate a first spectrum, and subtracting, by the computing device, an unstained spectrum from the first spectrum to generate a second spectrum, wherein the second spectrum defines a spectral profile of the sample. As used in this specification, a pixel mask may be defined as the pixels from the foreground channel used in averaging the intensity in all the channels.

[0006] Another example provides a method of calibrating an imaging device. The method includes obtaining a first image of an unstained version of a sample, acquiring an unstained spectral profile of the sample using the first image, obtaining, for each of a plurality of stainedversions of the sample, a second image, and extracting a plurality of spectral profiles associated with the plurality of stained images, each spectral profile associated a fluorophorc of the plurality of fluorophores. In each of the stained images, a portion of the sample is stained with a different fluorophore of a plurality of fluorophores. The method includes generating an unmixing matrix based on the unstained spectral profile and the plurality of spectral profiles.

[0007] Another example provides an imaging system comprising a calibrated imaging device and a controller including an electronic processor and a non-transitory, computer readable medium. The controller is configured to receive a selection of one or more fluorescent channels for imaging a sample, where the sample is stained with a plurality of fluorophores, and capture, with the imaging device, a raw image of the sample. The controller is configured to apply an unmixing matrix to the raw image to generate an unmixed image. The unmixing matrix is generated by repeating a single color control (SCC) operation, where a single operation includes subtracting the background channel from the foreground channel; defining a pixel masks; and applying the pixel mask to all of the channels, on a plurality of calibration samples, each calibration sample in the plurality of calibration samples stained with a different fluorophore included in the plurality of fluorophores.

[0008] In another aspect described herein, a calibration slide for use in the calibration of an imaging device is disclosed. The calibration slide comprises a microscope slide, and a plurality of detectable calibration beads disposed in a mountant within a defined area on the surface of the microscope slide. The mountant has a refractive index that at least matches the refractive index of the microscope slide. The calibration slide contains between 1,300,000 to about 2,600,000 beads within a 10 mm2area on the slide surface. The beads have an average diameter ranging from about 0.1 pm to about 6.0 pm, with a preferred average diameter of about 4 pm to about 5 pm. The coefficient of variation (CV) of the bead diameter ranges from about 2% to 5%, with an optimal CV of around 2%.

[0009] The mountant used can be polymeric and may include a non-ionic detergent, glycerol, or a combination thereof, with a refractive index between 1.47 and 1.52. Each calibration bead comprises one or more detectable labels, such as fluorophores. The beads can contain two or more populations of fluorophores, which emit detectable light with different emission maxima between about 385 nm and 860 nm, when irradiated with light with excitation wavelengths between 100 nm and 800 nm. The calibration beads may include 2-10 populations offluorophores, each detectable in different imaging system channels, with a signal intensity that is visible with less than 100 msec exposure time. Fluorophores may include cyanine-based dyes, hemi-cyanine -based dyes, rhodamine-based dyes, coumarin-based dyes, pyrene-based dyes, indacene-based dyes, or indole-based dyes. These beads encapsulate the fluorophores, and the slide maintains a shelf life of 1 year or more when stored at 2°C to 30°C, protected from light.

[0010] In another aspect, a method for preparing the calibration slide is disclosed. The method involves dispersing fluorescent beads in a dispersal solution, spreading the solution onto a microscope slide, drying the beads, and then mounting them using a mounting solution. The beads are typically polystyrene based, with a diameter of about 4.7 pm, and the dispersal solution contains about 0.2% w / v beads, including a non-ionic detergent. The bead solution is spread onto the slide at a thickness of about 10 pm to about 15 pm, resulting in a bead density of about 4000 to about 8000 beads per 20x field of view. The mounting solution, which is preferably glycerol-based, has a refractive index that matches that of the microscope slide. Additionally, the method includes staining the beads with a plurality of fluorescent dyes, which emit light across different wavelengths (385 nm - 860 nm), optimizing the stain concentration for visibility with less than 100 msec exposure time.

[0011] In another aspect a calibration slide useful for optical alignment, illumination correction, and spectral unmixing calibration of imaging systems is disclosed.

[0012] In another aspect, an imaging system is disclosed. The imaging system includes the calibration slide and an imaging device calibrated with the calibration slide.

[0013] This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an indication of the scope of the claimed subject matter.

[0014] Additional features and advantages of the disclosure will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the disclosure. The features and advantages of the disclosure may be realized and obtained by means of the instruments and combinations disclosed herein. These and other features of the present disclosure will become more fully apparent from the following description and appended claims or may be learned by the practice of the disclosure as set forth hereinafter.BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Features and advantages of the present technology will become more apparent from the following detailed description of example embodiments thereof taken in conjunction with the accompanying drawings in which:

[0016] FIGS. 1A-1B show an example of spatial transcriptomics.

[0017] FIG. 2 illustrates a process diagram of linear unmixing of a 9-plex sample.

[0018] FIG. 3A represents a block diagram of an example fluorescence microscope.

[0019] FIG. 3B represents a block diagram of an example controller of the fluorescence microscope of FIG. 3A.

[0020] FIG. 4 is a block diagram of a method for performing spectral unmixing of an image including multiple overlapping fluorophores.

[0021] FIG. 5 is a block diagram of a method for identifying unstained spectrums for raw sample images.

[0022] FIG. 6 is a block diagram of a method for identifying foreground and background fluorescent channels for selected dyes.

[0023] FIG. 7 is a block diagram of a method for generating an unmixing matrix.

[0024] FIG. 8 shows a block diagram of a method for obtaining a single-color control sample spectrum.

[0025] FIGS. 9A-9B represent block diagrams of a method for a spectral extraction operation.

[0026] FIG. 10 illustrates examples metrics regarding the calibration of a fluorescence microscope.

[0027] FIG. 11 illustrates a block diagram of a method to recalculate unmixing evaluation metrics.

[0028] FIG. 12 illustrates examples of the captured fluorophores.

[0029] FIG. 13 shows an illustration of a calibration slide.

[0030] FIG. 14 illustrates a method of preparing a microscope slide for an unmixing experiment.

[0031] While the present technology is susceptible to various modifications and alternative forms, specific embodiments have been shown by way of example in the drawings and will be described in detail herein. It should be understood, however, that the invention is not intended tobe limited to the particular forms disclosed. Rather, the invention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention as defined by the appended claims.DETAILED DESCRIPTION

[0032] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. For example, any nomenclatures used in connection with, and techniques of microscopy, biochemistry, molecular biology, immunology, microbiology, genetics, cell and tissue culture, and protein and nucleic acid chemistry described herein are well known and commonly used in the art. In case of conflict, the present disclosure, including definitions, will control. Exemplary methods and materials are described below, although methods and materials similar or equivalent to those described herein can be used in practice or testing of the embodiments and aspects described herein.

[0033] As used herein, the terms “amino acid,” “nucleotide,” “polynucleotide,” “vector,” “polypeptide,” and “protein” have their common meanings as would be understood by a biochemist of ordinary skill in the art. Standard single letter nucleotides (A, C, G, T, U) and standard single letter amino acids (A, C, D, E, F, G, H, I, K, L, M, N, P, Q, R, S, T, V, W, or Y) are used herein.

[0034] As used herein, terms such as “include,” “including,” “contain,” “containing,” “having,” and the like mean “comprising.” The present disclosure also contemplates other embodiments “comprising,” “consisting essentially of,” and “consisting of’ the embodiments or elements presented herein, whether explicitly set forth or not. As used herein, “comprising,” is an “open-ended” term that does not exclude additional, unrecited elements or method steps. As used herein, “consisting essentially of’ limits the scope of a claim to the specified materials or steps and those that do not materially affect the basic and novel characteristics of the claimed invention. As used herein, “consisting of” excludes any element, step, or ingredient not specified in the claim.

[0035] As used herein, the term “a,” “an,” “the” and similar terms used in the context of the disclosure (especially in the context of the claims) are to be construed to cover both the singular and plural unless otherwise indicated herein or clearly contradicted by the context. In addition,“a,” “an,” or “the” means “one or more” unless otherwise specified. As used herein, the term “or” can be conjunctive or disjunctive. As used herein, the term “and / or” refers to both the conjunctive and disjunctive. As used herein, the term “substantially” means to a great or significant extent, but not completely.

[0036] As used herein, the term “about” or “approximately” as applied to one or more values of interest, refers to a value that is similar to a stated reference value, or within an acceptable error range for the particular value as determined by one of ordinary skill in the art, which will depend in part on how the value is measured or determined, such as the limitations of the measurement system. In one aspect, the term “about” refers to any values, including both integers and fractional components that are within a variation of up to ± 10% of the value modified by the term “about.” Alternatively, “about” can mean within 3 or more standard deviations, per the practice in the art. Alternatively, such as with respect to biological systems or processes, the term “about” can mean within an order of magnitude, in some embodiments within 5-fold, and in some embodiments within 2-fold, of a value. As used herein, the symbol means “about” or “approximately.”

[0037] All ranges disclosed herein include both end points as discrete values as well as all integers and fractions specified within the range. For example, a range of 0.1-2.0 includes 0.1, 0.2, 0.3, 0.4 . . . 2.0. If the end points are modified by the term “about,” the range specified is expanded by a variation of up to ±10% of any value within the range or within 3 or more standard deviations, including the end points, or as described above in the definition of “about.”

[0038] As used herein, the terms “active ingredient” or “active pharmaceutical ingredient” refer to a pharmaceutical agent, active ingredient, compound, or substance, compositions, or mixtures thereof, that provide a pharmacological, often beneficial, effect.

[0039] As used herein, the terms “control,” or “reference” are used herein interchangeably. A “reference” or “control” level may be a predetermined value or range, which is employed as a baseline or benchmark against which to assess a measured result. “Control” also refers to control experiments or control cells.

[0040] “Antibody” as used herein means an immunoglobulin or a fragment thereof and encompasses any polypeptide comprising an antigen-binding site regardless of the source, method of production, and other characteristics.

[0041] An “analyte” or “antigen” as used herein refers to any substance recognized by an antibody, or another means of detection.

[0042] A “detectable label” as used herein refers to any molecule which may be detected directly or indirectly to reveal the presence of a target in the sample. A direct detectable label may be used. Direct detectable labels may be detected without the need for additional molecules. Examples include fluorescent dyes, radioactive substances, and metal particles. Indirect detectable labels may be used, which require the employment of one or more additional molecules. Examples include enzymes that affect a color change in a suitable substrate, as well as any molecule that may be specifically recognized by another substance carrying a label or react with a substance carrying a label. Other examples of indirect detectable labels thus include antibodies, antigens, nucleic acids and nucleic acid analogs, ligands, substrates, and haptens. Examples of detectable labels that can be used herein include, but are not limited to, fluorophores, chromophores, chemiluminescent compounds (e.g., luminol, isoluminol, acridinium esters, 1,2-dioxetanes, and pyridopyridazines), electrochemiluminescent labels (e.g., ruthenium derivatives), bioluminescent labels, and enzymes that catalyze a color change in a substrate. For some detectable labels, the target is detected by the presence of a color, or a change in color in the sample. More than one type of color may be used, for instance, by attaching distinguishable labels to a single detection unit or by using more than one detection unit, each carrying a different and distinguishable label. Other examples of detectable labels that can be used in spatial biology workflows, either alone or in combination with the methods described herein include gold or other metal particles, heavy atoms, spin labels, radioisotopes, and quantum dots. Detectable labels can be attached (e.g., conjugated) to a variety of different substances, including, without limitation, haptens, antigens, nucleic acids or nucleic acid analogues, proteins, such as receptors, peptide ligands, enzymes, enzyme substrates, or antibodies (including antibody fragments). Other examples of detectable labels and substances that can be conjugated to detectable labels include polymers, polymer particles, bead or other solid surfaces and substrates.

[0043] “Fluorophore” as used herein is a molecule that emits detectable electro-magnetic radiation upon excitation with electro-magnetic radiation at one or more wavelengths. A large variety of fluorophores are known in the ail and arc developed by chemists for use as detectablemolecular labels and can be conjugated to affinity molecules described herein. The term “fluorophorc” and “fluorescent dye” may be used interchangeably herein.

[0044] “Chromogen” as used herein refers to a chemical compound that can, by chemical or other means, be converted into a chromophore. Exemplary chromogens include, but are not limited to, naphthols, aryl diazonium salts, and 1,3-diketones. The term “chromophore,” as used herein, refers to an aromatic compound including a chemical grouping that gives color to the compound by causing displacement of, or appearance of, absorbent bands in the visible spectrum. Exemplary chromophores include, but are not limited to, R-N=N- (e.g., azo dyes).

[0045] As used herein, the terms “inhibit,” “inhibition,” or “inhibiting” refer to the reduction or suppression of a given biological process, condition, symptom, disorder, or disease, or a significant decrease in the baseline activity of a biological activity or process.

[0046] The terms “recognize,” “recognition,” or “recognizing,” etc., as used herein, mean an event in which one substance, such as an affinity molecule, directly or indirectly interacts with a target in any way such that the interaction with the target may be detected by an affinity molecule. In some nonlimiting examples, a probe may react with a target, or directly bind to a target, or indirectly react with or bind to a target by directly binding to another substance that in turn directly binds to or reacts with a target.

[0047] As used herein, the term “subject” refers to an animal. Typically, the subject is a mammal. A subject also refers to primates (e.g., humans, male or female; infant, adolescent, or adult), non-human primates, rats, mice, guinea pigs, rabbits, pigs, cows, sheep, goats, horses, dogs, cats, fish, birds, reptiles, amphibians, insects, plants, fungi, bacteria, or archaea, among other life forms. In one embodiment, the subject is a primate. In one embodiment, the subject is a human.

[0048] “Target,” also used interchangeably with “analyte,” as used herein refers to any substance present in a sample that is capable of being detected.

[0049] The term “multiplex” or “multiplexing” refers to the ability to analyze and visualize two or more molecular markers or data types. Within the context of the spatial biology field, multiplex detection refers typically refers to detection of more than five molecular markers or data types within the same biological sample (e.g., tissue section or cell), while preserving spatial information. “Multiplexing” also refers to techniques for measuring the expression or presenceof multiple genes, proteins, or other molecules in the same tissue sample, while maintaining their spatial location.

[0050] The present disclosure is described with reference to the drawings, where like reference numerals are used to refer to like elements throughout. In the following description, for purposes of explanation, numbers of specific details are set forth to provide an improved understanding of the present disclosure. It may be evident, however, that the systems and methods of the present disclosure may be practiced without one or more of these specific details. In other instances, well-known structures and devices are shown in block diagram form to facilitate describing the systems and methods of the present disclosure. There is no specific requirement that a system, method, or technique relating to microscope image analysis include all of the details characterized herein to obtain some benefit according to the present disclosure. Thus, the specific examples characterized herein are meant to be example applications of the techniques described and alternatives are possible.

[0051] Calibration Involving Unmixing of Spectra.

[0052] Fluorescence microscopy is commonly used to capture images of tissue stained with fluorophores (e.g., staining targets, dyes). Each fluorophore has a unique spectral emission profile spread over a plurality of fluorescence channels (e.g., wavelengths of light). For example, FIGS. 1A-1B show an example of fluorescence microscopy in use in the field of spatial transcriptomics. In particular, FIG. 1A shows the spectral emission profiles of 9 fluorophores illustrating the spectral overlap of different dyes (DAPI, eFluor 506, Alexa Fluor™ 488, Alexa Fluor™ 514, Alexa Fluor™ 555, eFluor 615, Alexa Fluor™ 647, Alexa Fluor™ 700, Alexa Fluor™ ' 750). As shown in FIG. 1A, the spectral profile of DAPI ranges from approximately 375 nm to approximately 650 nm. For example, DAPI has a peak intensity at approximately 450 nm. Each fluorophore has a unique spectral range and peak intensity. However, when capturing particular fluorescence channels (for example, 500 nm), the spectral emission profile of multiple fluorophores may overlap. Accordingly, a spectral image acquisition operation may be performed to acquire both mixed and unmixed images of the sample. FIG. IB shows example spectrally mixed (left) and unmixed (right) composite images of human tonsil tissue sample stained with 9 fluorophores. While the mixed image includes all fluorescent channels, the unmixed image includes only the desired fluorescent channels.

[0053] FIG. 2 illustrates a process diagram of linear unmixing of a 9-plex sample. At step 202, a multiplex (c.g., 9-plcx) tissue sample is received. At step 204, ten control samples arc obtained, where the multiplex tissue sample is imaged as an unstained sample and for nine fluorescent dyes. At step 206, ten single color control slides are prepared (e.g., ten images are captured, one for each control sample). At step 208, the spectral profiles 208 of each fluorophore and tissue autofluorescence are obtained to produce an unmixing matrix. At step 210, a mixed 9-plex image of the sample stained with each of the nine fluorescent dyes is captured. At step 212, the unmixing matrix 212 is employed to calculate the relative contribution from each fluorophore for every pixel of the mixed 9-plex image 210. At step 214, an unmixed image is obtained that includes only the desired fluorescent channels. One of ordinary skill in the art would understand that a 9-plex is a representative example of a multiplex tissue sample and that unmixing other multiplex tissue samples such as but not limited to 12-plex and 15-plex are possible.

[0054] FIG. 3A shows a block diagram of an example fluorescence microscope 300. The fluorescence microscope 300 includes a controller component 302, a light source 304 (e.g., a laser light source), and fluorescence detectors 306. The light source may include, for example, one or more light emitting diodes (LEDs), one or more laser diodes, one or more photomultiplier tubes (PMTs), a single-photon avalanche diode (SPAD) array, dichroic filters, emission filters, and combinations thereof. When the fluorescence microscope 300 initiates an analytical inteiTogation of the sample, the light source 304 projects light, such as laser light, onto the sample. While not illustrated, the fluorescence microscope 300 may also include one or more light manipulating devices (for example, one or more filters, reflectors, lenses, or a combination thereof) to direct light from the light source 304 onto a sample. Light contacting the sample may cause fluorophores within the sample to fluoresce. The fluorescent light from the fluorophores is captured by the fluorescence detectors 306 as a response to the interrogation of the sample.

[0055] Referring now to FIG. 3B, the controller component 302 may include an electronic processor 310, data storage device(s) 312, and an input / output (TO) interface 314. The controller component 302 is suitable for the application and setting, and can include, for example, multiple electronic processors, multiple I / O interfaces, multiple data storage devices, or combinations thereof. In some implementations, some or all of the components included in the controller component 302 may be attached to one or more mother boards and enclosed in a housing (e.g., including plastic, metal and / or other materials). In some implementations, some of thesecomponents may be fabricated onto a single system-on-a-chip or SoC (e.g., an SoC may include one or more processing devices and one or more storage devices). Additionally, one or more of these components may be situated in a separate housing. For example, the electronic processor 310 may be situated in a first housing, while the data storage device(s) 312 are situated in a second housing communicatively coupled to the first housing.

[0056] As used herein, “processors” or “electronic processor” refers to any device(s) or portion(s) of a device that process electronic data from registers and / or memory to transform that electronic data that may be stored in registers and / or memory. The electronic processor 310 may include one or more digital signal processors (DSPs), application-specific integrated circuits (ASICs), central processing units (CPUs), graphics processing units (GPUs), cryptoprocessors (specialized processors that execute cryptographic algorithms within hardware), server processors, or any other suitable processing devices.

[0057] The data storage device 312 may include one or more local or remote memory devices such as random-access memory (RAM) devices (e.g., static RAM (SRAM) devices, magnetic RAM (MRAM) devices, dynamic RAM (DRAM) devices, resistive RAM (RRAM) devices, or conductive-bridging RAM (CBRAM) devices), hard drive-based memory devices, solid-state memory devices, networked drives, cloud drives, or any combination of memory devices. In some implementations, the data storage device 312 may include memory that shares a die with a processor. In such an implementation, the memory may be used as a cache memory and may include embedded dynamic random-access memory (eDRAM) or spin transfer torque magnetic random-access memory (STT-MRAM), for example. In some implementations, the data storage device 312 may include non-transitory computer readable media having instructions thereon that, when executed by one or more processors (e.g., the electronic processor 310), causes the controller component 302 to store various applications and data for performing one or more of the methods described herein or portions described herein. It should be understood that each method described herein may be implemented via one application or multiple applications and, in some examples, the data storage device 312 stores additional data in various configurations.

[0058] The I / O interface 314 of controller component 302 may include one or more communication chips, connectors, and / or other hardware and software to govern communications between the controller component 302 and other components. For example, the I / O interface 314 may include circuitry for managing wireless communications for the transfer ofdata to and from the controller component 302. In some implementations, the I / O interface 314 may include one or more antennas (c.g., one or more antenna arrays) for receipt and / or transmission of wire communications. In some instances, the fluorescence microscope 300 includes one or more output devices, such as a display screen, which are connected to the electronic processor 310 via the I / O interface 314.

[0059] Traditionally, when generating an unmixed image of a 9-plex sample, each control slide must also be captured, resulting in preparing eleven different samples for capture (e.g., capturing the ten control slides and the mixed image). This utilizes a large amount of tissue sample that may be limited in supply. Accordingly, there is a need to minimize the amount of prepared tissue sample. Example systems and methods described herein provide for calibrating a fluorescence microscope for capturing multiple sample images without requiring the need for repeated control samples.

[0060] Additionally, the fluorescence microscope 300 may acquire data from biological samples labeled with multiple overlapping fluorophores. The images of tissue samples are then separated into individual fluorophore channels. For example, unmixing of these spectra is performed to produce individual images. Methods and operations described herein provide an unmixing algorithm performed by the fluorescence microscope 300 that provides maximal interpretability of the results and provides a guided calibration for a user of the fluorescence microscope 300 to extract spectra from calibration slides.

[0061] FIG. 4 illustrates a block diagram of an example method 400 for performing spectral unmixing of an image including multiple overlapping fluorophores. The method 400 is described herein as being performed by the fluorescence microscope 300. However, it should be understood that the method 400 (or portions thereof) may be performed by one or more electronic controllers located within the fluorescence microscope 300 (such as the controller component 302), separate or remote from the fluorescence microscope 300, or a combination thereof. Additionally, in various instances, various blocks illustrated in the example method 400 may be removed, added, combined, or modified without departing from the spirit of the present disclosure. It further should be understood that, while steps are illustrated as occurring in series, certain steps could be performed simultaneously in parallel.

[0062] At step 402, the fluorescence microscope 300 receives a sample. For example, a tissue sample is provided in a module received by the fluorescence microscope 300 for imaging. In an exemplary aspect, the sample is a 9-plex sample that includes nine fluorescent dyes.

[0063] At step 404, the controller component 302 performs an overview scan operation. The overview scan operation may have the controller component 302 acquires a low-resolution image of the entire slide on which the sample is situated. A user of the fluorescence microscope 300 may then provide an input to the controller component 302 to select the specific area on the slide at which the sample is situated.

[0064] At step 406, the controller component 302 receives selected channels and settings for imaging the sample. For example, a user of the fluorescence microscope 300 may select fluorescent channels of interest (e.g., via the I / O interface 314) to unmix (e.g., separate) from an image of the sample. The user may also set a field of view (FOV) of which to capture an image of the sample. As used in this disclosure, the field of view (FOV) is the range of what is the maximum area visible of a region of interest. In some implementations, multiple FOVs are selected by the user. The FOV may indicate one or more regions of interest of the sample that the user desires to image.

[0065] At step 408, the controller component 302 captures a raw image (e.g., a mixed image) of the sample. For example, the controller component 302 controls the light source 304 to inteiTogate the sample, causing the sample to fluoresce. The fluorescence from the sample is captured as an image by the fluorescence detectors 306. The raw image includes all fluorescent light emitted by the sample.

[0066] At step 410, the controller component 302 applies linear unmixing to the raw image to generate an unmixed image. For example, an unmixing matrix is applied to the raw image to separate each fluorophore for every pixel of the raw image, thereby producing unmixed images. In some implementations, the unmixing matrix may be re-scaled according to the selected channels at step 406. For example, the unmixing matrix may be altered by the controller component 302 such that the unmixed image only includes the selected channels at step 406.

[0067] At step 412, the controller component 302 provides the unmixed image. The unmixed image may be output via an output device of the fluorescence microscope 300 (e.g., a device connected to the I / O interface 314). In another instance, the unmixed image may be stored in the data storage device(s) 312.

[0068] The fluorescence microscope 300 may be calibrated by capturing multi-channel images of single-color control samples (SCCs) to extract the spectral signatures of the fluorophorcs applied to samples, including an unstained sample. The multi-channel images of slides stained with multiple markers are then captured, and the calibrated spectral signatures are used to identify the contribution of individual fluorophores at each pixel in the image. FIG. 5 illustrates a block diagram of an example method 500 for identifying unstained spectrums for raw sample images. The method 500 is described herein as being performed by the fluorescence microscope 300. However, it should be understood that the method 500 (or portions thereof) may be performed by one or more electronic controllers located within the fluorescence microscope 300 (such as the controller component 302), separate or remote from the fluorescence microscope 300, or a combination thereof. Additionally, in various instances, various blocks illustrated in the example method 500 may be removed, added, combined, or modified without departing from the spirit of the present disclosure. It further should be understood that, while steps are illustrated as occurring in series, certain steps could be performed simultaneously in parallel.

[0069] At step 502, the controller component 302 receives a raw unstained image. For example, an unstained sample is provided for imaging by the fluorescence microscope 300. The controller component 302 controls the light source 304 to interrogate the sample, causing the sample to fluoresce. The fluorescence detectors 306 capture the fluorescent light from the sample, and the controller component 302 processes signals provided by the fluorescence detectors 306 to generate the raw unstained image.

[0070] At step 504, the controller component 302 receives a selected region of interest of the sample. For example, a user of the fluorescence microscope 300 may select a region of interest (or field of view) within the SCC image by interfacing with the I / O interface 314. In some instances, the controller component 302 clips the SCC image to the region of interest such that only the region of interest is shown to the user.

[0071] At step 506, the controller component 302 averages all pixels within the selected region of interest in the SCC image to obtain an unstained spectrum. The unstained spectrum represents the values of all pixels within the selected region of interest for the SCC. The unstained spectrum represents the natural spectrum of the sample with no dyes applied to the sample.

[0072] At step 508, the controller component 302 provides the unstained spectrum. As one example, the unstained spectrum may be output via an output device of the fluorescence microscope 300 (e.g., a device, such as the display, connected to the I / O interface 314). In another instance, the unstained spectrum may be stored in the data storage device(s) 312.

[0073] Additionally, foreground and background florescent channels may be identified for each dye to assist with the unmixing operation. The foreground channel may be the channel with the highest available fluorescence signal for a given fluorophore. The background channel may be the closest available channel (relative to the foreground channel) with no fluorescence for a given fluorophore. When determining the background channel, the fluorophore may be expected to have autofluorescence. FIG. 6 illustrates a block diagram of an example method 600 for identifying foreground and background fluorescent channels for selected dyes (e.g., selected fluorophores). The method 600 is described herein as being performed by the fluorescence microscope 300. However, it should be understood that the method 600 (or portions thereof) may be performed by one or more electronic controllers located within the fluorescence microscope 300 (such as the controller component 302), separate or remote from the fluorescence microscope 300, or a combination thereof. Additionally, in various instances, various blocks illustrated in the example method 600 may be removed, added, combined, or modified without departing from the spirit of the present disclosure. It further should be understood that, while steps are illustrated as occurring in series, certain steps could be performed simultaneously in parallel.

[0074] At step 602, the controller component 302 receives a selected dye. For example, a dye may be selected by a user of the fluorescence microscope 300 for calibration of the fluorescence microscope 300. The dye may be a fluorescent dye as described with respect to FIGS. 1A-1B.

[0075] At step 604, the controller component 302 loads a reference spectrum for the selected dye. For example, in some implementations, the data storage device(s) 312 stores a plurality of reference spectrums, each reference spectrum associated with a dye that may be selected by the user. The electronic processor 312 may retrieve the reference spectrum from the data storage device(s) 312. The reference spectrum may be an SCC spectrum obtained by the controller component 302 for a particular dye (for example, as described with respect to method 800 of FIG. 8).

[0076] At step 606, the controller component 302 identifies a maximum intensity channel of the reference spectrum. For example, the controller component 302 determines a fluorescence channel within the reference spectrum that has the greatest average intensity, such as an intensity peak of the reference spectrum.

[0077] At step 608, the controller component 302 identifies a foreground channel based on the maximum intensity channel. For example, the controller component 302 may select the fluorescence channel with the greatest average intensity to be the foreground channel.

[0078] At step 610, the controller component 302 sorts the selected florescence channels by LEDs and filters. For example, the fluorescence channels are sorted according to their wavelength proximity to the identified foreground channel for the given fluorophore. The fluorescence channels may be sorted first according to excitation wavelength (e.g., the LEDs), and then according to emission wavelength (e.g., the filters) as a heuristic for channel similarity.

[0079] At step 612, the controller component 302 identifies the closest non-fluorescent channel relative to the foreground channel based on the unstained spectrum. For example, the closest non-fluorescent channel to the foreground channel is determined according to emission and excitation wavelengths. A heuristic may be defined by which the difference in emission wavelengths is weighted as a less important factor than the distance in excitation wavelengths. The “closest” non-fluorescent channel minimizes the distance between the excitation wavelengths.

[0080] At step 614, the controller component 302 identifies the background channel based on the non-fluorescent channel. For example, the non-fluorescent channel identified at step 612 is selected as the background channel.

[0081] To perform unmixing of fluorescent channels, an unmixing matrix is determined by the controller component 302. FIG. 7 illustrates a block diagram of an example method 700 for generating an unmixing matrix. The method 700 is described herein as being performed by the fluorescence microscope 300. However, it should be understood that the method 700 (or portions thereof) may be performed by one or more electronic controllers located within the fluorescence microscope 300 (such as the controller component 302), separate or remote from the fluorescence microscope 300, or a combination thereof. Additionally, in various instances, various blocks illustrated in the example method 700 may be removed, added, combined, or modified without departing from the spirit of the present disclosure. It further should beunderstood that, while steps are illustrated as occurring in series, certain steps could be performed simultaneously in parallel.

[0082] At step 702, the controller component 302 receives a plurality of selected dyes. For example, multiple dyes may be selected by a user of the fluorescence microscope 300. The selected dyes are dyes that are applied to a sampled to be imaged.

[0083] At step 704, the controller component 302 selects multiple channels for capturing a fluorescent image of a sample stained with the dyes. In some instances, the controller component 302 determines which fluorescent channels will best fluoresce from the sample based on the plurality of selected dyes. For example, the controller component 302 calculates available fluorescent channels based on a spectrum associated with the selected dyes. In another example, the controller component 302 compares the selected dyes to a lookup table to identify fluorescent channels associated with the selected dyes. In other instances, a user selects desired channels to be unmixed from a captured mixed image of the stained sample.

[0084] At step 706, the controller component 302 adjusts channel settings of the fluorescent microscope 300 based on the selected channels and selected field of view. For example, exposure time of the sample may be adjusted based on the selected channels.

[0085] At step 708, the controller component 302 performs a SCC operation to generate a matrix of the spectra. An example of the SCC operation is described below with respect to method 800 (shown in FIG. 8). The SCC operation is repeated for each dye of the plurality of selected dyes.

[0086] At step 710, the controller component 302 calculates an unmixing matrix based on the matrix of the spectra. For example, the controller component 302 computes the unmixing matrix by performing a pseudoinverse operation on the matrix of the spectra.

[0087] At step 712, the controller component 302 provides the unmixing matrix. As one example, the unmixing matrix may be output via an output device of the fluorescence microscope 300 (e.g., a device, such as the display, connected to the VO interface 314). In another instance, the unmixing matrix may be stored in the data storage device(s) 312.

[0088] FIG. 8 illustrates a block diagram of an example method 800 for obtaining a SCC spectrum. The method 800 is described herein as being performed by the fluorescence microscope 300. However, it should be understood that the method 800 (or portions thereof) may be performed by one or more electronic controllers located within the fluorescence microscope300 (such as the controller component 302), separate or remote from the fluorescence microscope 300, or a combination thereof. Additionally, in various instances, various blocks illustrated in the example method 800 may be removed, added, combined, or modified without departing from the spirit of the present disclosure. It further should be understood that, while steps are illustrated as occurring in series, certain steps could be performed simultaneously in parallel.

[0089] At step 802, the fluorescence microscope 300 receives a sample. The sample may be, for example, stained with a single lluorophore.

[0090] At step 804, the controller component 302 acquires selected channels for imaging of the sample. For example, the controller component 302 determines which fluorescent channels will best fluoresce from the sample based on the selected fluorophore. In some instances, a user of the fluorescence microscope 300 selects channels for imaging of the sample.

[0091] At step 806, the controller component 302 captures a raw SCC image of the sample. For example, the controller component 302 controls the light source 304 to interrogate the sample, causing the sample to fluoresce. The fluorescence detectors 306 capture the fluorescent light from the sample, and the controller component 302 processes signals provided by the fluorescence detectors 306 to generate the raw SCC image.

[0092] At step 808, the controller component 302 performs a spectral extraction operation on the raw SCC image to obtain a SCC spectrum. An example of the spectral extraction operation is described below with respect to method 900 (shown in FIG. 9). The controller component 302 may be configured to select a particular combination of LEDs in the light source 304, dichroic filters, and emission filters that are associated with the selected channels for imaging the sample.

[0093] At step 810, the controller component 302 normalizes the SCC spectrum. The SCC spectrum may be normalized to account for an exposure time of the sample to the laser from the light source 304. For example, each SCC spectrum may be divided by the exposure time of the sample to acquire a normalized SCC spectrum.

[0094] At step 812, the controller component 302 provides the normalized SCC spectrum. As one example, the normalized SCC spectrum may be output via an output device of the fluorescence microscope 300 (e.g., a device, such as the display, connected to the I / O interface 314). In another instance, the normalized SCC spectrum may be stored in the data storage device(s) 312.

[0095] In some instances, the controller component 302 repeats the method 800 to capture all SCC images, and therefore SCC spectrums, which arc associated with a particular combination of fluorophores.

[0096] FIGS. 9A-9B illustrate a block diagram of an example method 900 for a spectral extraction operation. The method 900 is described herein as being performed by the fluorescence microscope 300. However, it should be understood that the method 900 (or portions thereof) may be performed by one or more electronic controllers located within the fluorescence microscope 300 (such as the controller component 302), separate or remote from the fluorescence microscope 300, or a combination thereof. Additionally, in various instances, various blocks illustrated in the example method 900 may be removed, added, combined, or modified without departing from the spirit of the present disclosure. It further should be understood that, while steps are illustrated as occurring in series, certain steps could be performed simultaneously in parallel.

[0097] At step 902, the controller component 302 selects foreground channel and background channel images. For example, a user may indicate that a sample being analyzed is stained with a particular dye. The controller component 302 retrieves the foreground channel and the background channel associated with the dye from the data storage device(s) 312 (as identified in method 600).

[0098] At step 904, the controller component 302 conditions the foreground channel and the background channel for processing. For example, the controller component 302 may apply intensity normalization to the foreground channel and / or the background channel. In some instances, the controller component 302 may apply a scaling function to the foreground channel and / or the background channel.

[0099] At step 906, the controller component 302 determines a difference between the foreground channel and the background channel. For example, the controller component 302 may subtract the background channel from the foreground channel or may subtract the foreground channel from the background channel, thereby generating a difference image.

[0100] At step 908, the controller component 302 clips bottom intensity values of the difference image. For example, any negative values of the difference image may be clipped to a value of zero.

[0101] At step 910, the controller component 302 applies a thresholding operation to the clipped difference image to generate a signal mask image (c.g., a pixel mask). For example, an Otsu’s method is performed on the clipped difference image to perform automatic image thresholding.

[0102] At step 912, the controller component 302 clips foreground and background channel intensities to pre-defined thresholds to generate a clipped image.

[0103] At step 914, the controller component 302 calculates a correlation coefficient between the signal mask image and the clipped image.

[0104] At step 916, the controller component 302 applies a threshold operation on the correlation coefficient to threshold the correlation coefficient by a maximum value, thereby generating a correlation threshold filter.

[0105] At step 918, the controller component 302 averages non-zero foreground pixels in the signal mask image to obtain a first spectrum.

[0106] At step 920, the controller component 302 subtracts the unstained spectrum from the first spectrum to generate a second spectrum.

[0107] At step 922, the controller component 302 applies the correlation threshold filter to the second spectrum to generate an SCC spectrum associated with the indicated dye.

[0108] Accordingly, the unstained image, the SCC images, the foreground channel information, and the background channel information are used to extract a mask of the foreground pixels, in which the tissue in the sample is labeled with a fluorescent marker. This is achieved by subtracting the foreground and background channels, followed by an Otsu threshold operation. This operation returns a single intensity threshold that separates pixels into foreground pixels and background pixels. The signal in the resulting pixels is averaged across images and the unstained spectrum is subtracted to obtain a best estimate of the signal in each channel. In some instances, additional processing is performed to filter the extracted signal. Optionally, the correlation of the pixel mask and the clipped image is calculated, and the extracted spectrum values a e set to zero for any channels where this correlation metric is below a pre-determined factor.

[0109] In some implementations, after following the spectral extraction algorithm across the images, the fluorescence microscope 300 provides recommendations to a user for the best channels to be retained during unmixing. This enables users to achieve maximum acquisitionspeed by imaging only the most critical channels. For example, for each spectrum extracted across the full channel set, the core channel is always retained. Next, the least impactful channel (measured by the unmixing sensitivity) is removed. This provides a list of channels that may be dropped in the order of their importance to the unmixing output. In the example, the controller component 302 loads spectral profiles associated with all selected dyes and associated with the unstained image. An unmixing matrix is generated for the spectral profiles, and a sum of squares operation is performed across the fluorescence channels included in the unmixing matrix. This value is calculated for each unmixing matrix with one channel dropped, and the channel with maximum of the sum of squares after removal is removed such that only recommended channels remain. The procedure is repeated the first time to find core channels by reducing the subset of channels to the number of dyes, then repeated again to find recommended channels.

[0110] In some implementations, users may be provided with several metrics for evaluating the unmixing and spectral extraction following calibration of the fluorescence microscope 300. FIG. 10 illustrates a method 1000 for determining metrics for evaluation of a panel for microscope 300. Examples of these metrics include, but are not limited to, fraction bleedthough, an estimated dynamic range, signal to unmixed unstained ratio for each channel. These values are calculated for a set of calibration samples to be evaluated. At step 1005 a set of calibration images is acquired, scaled to a common exposure time, and unmixed with the extracted calibration matrix. At step 1010, all unmixed calibration images and extracted signal masks from the calibration procedure are used to estimate the 95thpercentile of the signal in each target and off-target channel, a robust estimate of fluorophore intensity. This yields a matrix of values for each fluorophore and fluorophore crosstalk intensities. To calculate fraction bleedthrough, at step 1015, each off target channel is normalized by the value of intensity in the core channel intensity for a particular fluorophore. To calculate effective dynamic range (EDR), at step 1020, the sum of cross talk intensities for each channel are subtracted from each core channel intensity. At step 1025, fraction bleedthrough are displayed to the user in a matrix and automatically flagged to the user if they are higher than a target value. An automated recommendation can be made to change the panel when values are high. EDR values are displayed to the user as one value per fluorophore, and the user is automatically advised to increase signal intensities in their panel when EDR values are below a threshold.

[0111] In some iterations, evaluation metrics may also be recalculated to provide information about a user-imaged multiplex sample. FIG 11 shows method 1100 to recalculate unmixing and spectral extraction metrics. At step 1105, the matrix of signal intensities per channel and fluorophores is calculated from the unmixed calibration samples. At step 1110, each adjusted core channel intensity is estimated for each fluorophore in the raw or unmixed multiplex sample. At step 1115, a signal mask for each unmixed multiplex channel is calculated by a thresholding algorithm such as an otsu threshold. At step 1120, the 95thpercentile signal intensity in the selected pixels may be calculated from the calculated signal mask in the raw channels of the multiplex samples. At step 1125, a scaling factor for each fluorophore is calculated as the ratio of the multiplex channel intensity to calibration sample intensity for that fluorophore. At step 1130, each row of the signal matrix is scaled by the scaling factor. At step 1135, fraction bleedthrough and EDR are calculated as before from the scaled signal matrix.

[0112] Additionally, prior to signal extraction, a user may inspect a cosine similarity matrix, unmixing sensitivity, and a complexity index for the selected dye panel to evaluate the collinearity and identify dye pairs that are difficult to unmix.

[0113] During extraction, users may also inspect the signal mask identified from each of the SCCs to validate that the signal selected is correctly extracted. Additionally, a similarity angle maps may provide a visualization for users to inspect the similarity of their extracted spectrum to each pixel in the image. Finally, post-unmixing the SCCs, the projected dynamic range, dye bleedthrough, signal to unstained intensity, and IOU relative to max channels may be displayed to users.

[0114] EXAMPLE 1: Unmixing of Fluorophores Following Calibration

[0115] Table 1, provided below, shows an example dataset including a nine-fluorophore panel. The table indicates each applied fluorophore, an associated antibody, and a dilution value of the fluorophore within the sample.Table 1. Nine-Fluorophore Panel 1Fluorophore Antibody DilutionDAPI - 1:1000 eF506 Ki67 DOL 6.45 1:20AF488 CD20 DOL 3.1 1:100AF514 CD68 DOL 10.67 1:20AF555+ PCNA DOL 1.78 1:20AF594 CD 1 lb DOL 1.78 1:10AF647+ FOXP3 DOL 5.83 1:10AF700 PanCK DOL2 1:100AF750+ CD45RO DOL 3.82 1:10

[0116] Following unmixing, images of each fluorophore are obtained in individual channels. Examples of the captured fluorophores are provided in FIG. 12. The figure shows that the methods described for fluorescent microscope calibration significantly enhance the unmixing of individual channels for each fluorophore. By ensuring precise alignment and accurate calibration of the microscope, these techniques minimize spectral overlap and improve the distinction between different fluorescent signals. This results in clearer, more accurate imaging, allowing for better identification and analysis of the various fluorophores present in the sample.Consequently, the overall quality and reliability of fluorescence microscopy data are greatly improved.

[0117] The methods described herein may be used in an immunohistochemistry assay, an immunocytochemistry assay, an in-situ hybridization (ISH) assay, enzyme immuno-assays (EIA), enzyme linked immuno-assays (ELISA), blotting methods (e.g., Western, Southern, and Northern), labeling inside electrophoresis systems or on surfaces or arrays, or other general detection assays known in the art.

[0118] For example, immunohistochemical (IHC) staining provides a method of detecting targets in a sample or tissue specimen in situ. See e.g., Mokry, Acta Medica 39(4): 129-140 (1996). The overall cellular integrity of the sample is maintained in IHC, thus allowing detection of both the presence and location of the targets of interest. Typically, a sample is fixed with formalin, embedded in paraffin, and cut into sections for staining and subsequent inspection by light microscopy. Current methods of IHC use either direct labeling or secondary antibody-based or hapten-based labeling. Examples of known IHC systems include, but are not limited to, EnVision™ (DakoCytomation), Powervision® (Immunovision, Springdale, Ariz.), the NBA™kit (Zymed Laboratories Inc., South San Francisco, Calif.), HistoFine® (Nichirei Corp, Tokyo, Japan). The apparatus and methods disclosed herein may allow for enhancement of signal, increased flexibility in IHC detection platforms, or a combination thereof.

[0119] Many types of samples are compatible with the apparatus and methods disclosed herein. Samples may comprise a solid, for example, containing targets in a tissue slice from an organ. Samples may be derived from living matter taken from any living organism, such as an animal, such as mammals (e.g., humans), plants, fungi, archaea, or bacteria. Thus, samples may comprise eukaryotic cells, archaeal cells, or prokaryotic cells. The tissue sample may be from a subject selected from humans, non-human primates, rats, mice, guinea pigs, rabbits, pigs, cows, sheep, goats, horses, dogs, cats, fish, birds, reptiles, amphibians, insects, plants, fungi, bacteria, or combinations thereof.

[0120] Samples may comprise a cell sample, such as a cell smear or colony, or a tissue specimen derived from a living organism, such as a tissue sample from an organ. Samples may also comprise other naturally obtained samples such as plant tissue samples, and synthetically derived samples such as chemical or industrial products and food products.

[0121] Tissue or cell samples may be prepared by a variety of methods known to those of ordinary skill in the art, depending on the type of sample and the assay format. For instance, tissue or cell samples may be fresh or preserved, and may be, for example, flash-frozen, smeared, dried, embedded, or fixed on slides or other supports. Samples may be prepared and stained using a free-floating technique. For example, a tissue section may be brought into contact with different reagents and wash buffers in suspension or freely floating in appropriate containers, for example microcentrifuge tubes, before being mounted on slides for further treatment and examination by the methods described herein.

[0122] A tissue section may be mounted on a slide or other substrate after an incubation with immuno-specific reagents. The remains of the staining process may then be conducted after mounting. For example, for microscopic inspection in IHC and ISH, samples may be comprised in a tissue section mounted on a suitable solid substrate. For photomicrographs, sections comprising samples may be mounted on a glass slide or other planar substrate, to highlight by selective staining certain morphological indicators of disease states or detection of detectable targets. The substrate may be a glass or plastic microscope slide (e.g., 26 x 75 x 1 mm or 1 x 3 x 0.04 in).

[0123] EXAMPLE 2: Calibration Slides and Preparation Methods for the Slides for Use in Spectral Imaging Systems.

[0124] Calibration slides are described herein for calibrating illumination profiles across multiple emission channels of a spectral imaging system. The calibration slides include fluorescent materials that span the range of fluorescent excitation and emission channels currently in use for spectral imaging platforms. The described calibration slides can be used to calibrate the X, Y, and Z focal planes of a spectral imager. The calibration slides disclosed herein provide a significant advancement over existing approaches for calibrating fluorescent microscopes that fail to provide a particle density that is high enough for calibration of illumination profiles across all channels.

[0125] Although slide-mounted, multispectral fluorescence microspheres (e.g., TetraSpeck™ Fluorescent Microspheres Size Kit (mounted on slide) from Thermo Fisher Scientific are useful for calibration of standard fluorescence microscopes, the spectral range and performance characteristics of these calibration slides are not adequate for producing high-quality multiplex images under the rigorous demands of spectral imaging systems equipped with many excitation and emission channels. For example, each microsphere in the TetraSpeck™ Kit is stained with four different fluorescent dyes (365 / 430 nm (blue), 505 / 515 nm (green), 560 / 580 nm (orange), and 660 / 680 nm (dark red)), whereas the instant slides utilize fluorescent microspheres that are stained with a combination of 7 dyes, 347 / 440nm (UV-blue), 425 / 550 nm (Cyan), 504 / 520 nm (Green), 570 / 575 nm (Orange-red), 644 / 668 nm (Deep red), 736 / 780 nm (NIR) and 760 / 820 nm (NIR).

[0126] Thus, as shown in FIG 13 provided herein are improved calibration slides 1300 (not shown to scale) that include multispectral fluorescence beads 1305 disposed on the surface of microscope slide 1310 in a polymer matrix. An expanded view (1315) shows the beads for illustration purposes as circular dots. The bead density can range from about 4000-8000 beads per 20x field of view. The beads are covered with cover slip 1320. The beads may include fluorescent compounds that may emit light across all channels of a spectral imaging system upon appropriate irradiation. Beads with uniform size (e.g., about 0.1 pm to about 6 pm) may be distributed substantially as a monolayer across the slide surface within a polymer matrix formulated to minimize optical refraction and spherical aberration in the optical path.

[0127] Beads 1305 may include polystyrene-based beads (e.g., microspheres), each stained with multiple different fluorescent dyes that may display well-separated excitation and emission peaks over the visible and / or near-IR spectral range. In a non-limiting example, a single bead can include multiple different fluorescent dyes, each with well- separated excitation / emission peaks, to provide an emission range (385 nm - 860 nm), significantly expanding detection into the far- red and near-IR channels of the spectral imaging system. In another non-limiting example, a calibration slide can include multiple sets of beads, wherein the beads within each set of beads may have approximately the same nominal size. Each bead set may be stained with fluorescent dyes that may emit in the desired spectral range upon excitation at an appropriate wavelength.

[0128] To calibrate a spectral imaging instrument that includes multiple detection channels, a calibration slide can include multiple sets of beads 1305. Each bead set containing beads 1305 may emit a detectable fluorescence signal within a specific channel of the spectral imaging system. For example, for a spectral imaging system that may include channels at 430, 488, 514, 555, 594, 647, 700, and 750 nm, a calibration slide may include eight different bead sets that emit within each of these channels. For instance, a bead set that emits in the 430 channel can include fluorophores that emit in the range between about 460 nm and 490 nm. The type and amount of fluorescent dyes in each bead set are tailored for use in the spectral unmixing methods described above. Each dye concentration may be optimized to provide visible signal with < 100 msec exposure time, and approximately equivalent intensities across the entire spectrum. The calibration slides may be utilized in an on-board calibration method using calibration software of the spectral imaging system to evaluate and adjust both illumination profiles of all of the excitation sources, as well as parfocality of all emission channels in the x, y, and z directions.

[0129] FIG. 14 discloses an exemplary method 1400 describing the steps of preparing a calibration slide for a spectral imaging application. In step 1405, polystyrene-based beads having a nominal diameter of about 4.7 pm are formulated at a concentration of 0.2% w / v. These beads are suspended in a solution containing 1 % of a non-ionic detergent, such as a Pluronic™ surfactant (BASF) to help with dispersal of the beads. In step 1410, the solution (e.g., about 10- 15 pL) can be cast evenly onto a microscope slide. In step 1415, the beads are allowed to dry at elevated temperatures. The bead density can range from about 4000-8000 beads per 20x field of view. One advantage of these high-density beads is that they facilitate alignment of the excitation channels by assessing the illumination profile of each excitation source.

[0130] Once dry, at step 1420, slides are mounted with a coverslip, using a mounting solution. Any suitable mounting medium that has the requisite optical properties can be used to mount the beads onto the surface of the slide. For spectral imaging applications, it can be advantageous to use a mounting media that exhibits a refractive index (RI) of at least that matches that of the microscope slide. Ideally, the RI is equivalent to the refractive index of the microscope slide (e.g., about 1.50 to about 1.52) and should be chemically and optically stable, such that the calibration slides can be stored over time without degradation. A representative example of a mounting media that can be used to prepare a slide for spectral imaging calibration is a glycerolbased mounting media such as ProLong™ Glass Antifade mountant from Thermo Fisher Scientific. Another example of a glycerol-based, aqueous mounting media for embedding fluorescently labeled beads that provides an appropriate RI for spectral imaging applications includes a methacrylamide-based polymer, includes -20% of a methacrylamide-based polymer, such as poly(N-methyl methacrylamide), and about -10% glycerol, buffered to -pH 8.4 using Tris buffer.

[0131] For IHC, a sample may be taken from an individual, fixed, and exposed to, for example, antibodies which specifically bind to the detectable target of interest. Sample processing steps may include, for example, antigen retrieval, exposure to a primary antibody, washing, exposure to a secondary antibody (optionally coupled to a suitable detectable label), washing, and exposure to a tertiary antibody linked to a detectable label. Washing steps may be performed with any suitable buffer or solvent, e.g., phosphate-buffered saline (PBS), Trisbuffered saline (TBS), or distilled water. The wash buffer may optionally contain a detergent, e.g., polyoxyethylene sorbitan monolaurate (TWEEN®20) or octylphenoxypolyethoxyethanol (Nonidet P-40).

[0132] IHC samples may include, for instance: preparations comprising un-fixed fresh tissues and / or cells or solution samples; fixed and embedded tissue specimens, such as archived material; and frozen tissues or cells. An IHC staining procedure may comprise steps such as: cutting and trimming tissue, fixation, dehydration, paraffin infiltration, cutting in thin sections, mounting onto glass slides, baking, deparaffination, rehydration, antigen retrieval, blocking steps, applying primary antibody, washing, applying secondary antibody-enzyme conjugate, washing, applying a tertiary antibody conjugated to a polymer and linked with an enzyme, applying a chromogen substrate, washing, counter staining, applying a cover slip, andmicroscopic examination using a fluorescence microscope and processed using imaging and unmixing software.

[0133] ISH samples, for instance, may be taken from an individual and fixed before being exposed to a nucleic acid or nucleic acid analog probe on a recognition unit. The nucleic acid in the sample may first be denatured to expose the target binding sites. Various counterstains or paints may further be used to locate nucleic acid molecules or chromosomes within an ISH sample.

[0134] Tissue or cell samples may be fixed or embedded. Fixatives may be needed, for example, to preserve cells and tissues in a reproducible and life-like manner. Fixatives may also stabilize cells and tissues, thereby protecting them from the rigors of processing and staining techniques. For example, samples comprising tissue blocks, sections, or smears may be immersed in a fixative fluid, or in the case of smears, dried.

[0135] Many methods of fixing and embedding tissue specimens are known, for example, alcohol fixation and formalin-fixation and subsequent paraffin embedding (FFPE). Any suitable fixing agent may be used. Examples include ethanol, acetic acid, picric acid, 2-propanol, 3,3'- diaminobenzidine tetrahydrochloride dihydrate, acetoin (mixture of monomer) and dimer, acrolein, crotonaldehyde (cis + trans), formaldehyde, glutaraldehyde, glyoxal, potassium dichromate, potassium permanganate, osmium tetroxide, paraformaldehyde, mercuric chloride, tolylene-2,4-diisocyanate, trichloroacetic acid, and tungstic acid. Other examples include formalin (aqueous formaldehyde), neutral buffered formalin, glutaraldehyde, carbodiimide, imidates, benzoquinone, osmic acid, and osmium tetraoxide. Fresh biopsy specimens, cytological preparations (including touch preparations and blood smears), frozen sections, and tissues for IHC analysis may be fixed in organic solvents, including ethanol, acetic acid, methanol and / or acetone.

[0136] It may be useful to pre-treat the samples to increase the reactivity or accessibility of a detectable target and to reduce nonspecific interactions. If the target is an antigen, for example, a process called “antigen retrieval” may be used (and which is also known in the ail as target retrieval, epitope retrieval, target unmasking, or antigen unmasking). See, e.g., Shi et al., J. Histochem. Cytochem. 45(3): 327-343 (1997). Antigen retrieval encompasses a variety of methods including enzymatic digestion with proteolytic enzymes, such as proteinase, pronase, pepsin, papain, trypsin, or neuraminidase. Heat may be used, such as heat-induced epitoperetrieval or HIER. Heating may involve microwave irradiation, a water bath, a steamer, a regular oven, an autoclave, or a pressure cooker in an appropriately pH stabilized buffer, usually containing EDTA, EGTA, Tris-HCl, citrate, urea, glycin-HCl, or boric acid. Detergents may be added to the HIER buffer to increase the epitope retrieval, or to the dilution media and / or rinsing buffers to lower non-specific binding. Combinations of different antigen retrieval methods may be used. The antigen retrieval buffer may be aqueous, but may also contain other solvents, including solvents with a boiling point above that of water such as glycerol. This allows for treatment of the tissue at greater than 100 °C at standard pressure.

[0137] Signal-to-noise ratio may be increased by different physical methods, including application of vacuum, ultrasound, or freezing and thawing tissue samples before or during incubation of the reagents.

[0138] Treatments may be performed to reduce nonspecific binding. For example, carrier proteins, carrier nucleic acid molecules, salts, or detergents may reduce or prevent non-specific binding. Non-specific binding sites may be blocked in some embodiments with inert proteins like, HSA, BSA, ovalbumin, with fetal calf serum or other sera, or with detergents like polyoxyethylene sorbitan monolaurate (TWEEN®20), octylphenoxypolyethoxyethanol (Nonidet P-40), / -octylphenoxypolyethoxyethanol (TRITON™ X-100), triterpene glycosides (Saponin), nonionic polyoxyethylene surfactants (BRIJ®-35), or nonionic triblock copolymers (PLURONICS®). Alternatively, non-specific binding sites may be blocked with unlabeled competitors for the recognition event between the target and the affinity molecule. For example, in the case of a nucleic acid interaction, non-specific binding may be reduced by adding unlabeled competitor nucleic acids or nucleic acid analogs such as digested, total human DNA, or unlabeled versions of the affinity molecule. In addition, repetitive sequences may be blocked, for example, using nucleic acids or nucleic acid analogs that specifically recognize those sequences, or sequences derived from a total DNA preparation. Salt, buffer, and temperature conditions may also be modified to reduce non-specific binding.

[0139] Cross reactivity of different components of the detection methods may be avoided, for example, by using antibodies derived from different species. Furthermore, combinations of, for example, secondary antibodies against primary antibodies and haptens may also be used to avoid unwanted cross reactivity. Endogenous biotin binding sites or endogenous enzyme activity (for example phosphatase, catalase, or peroxidase) may be removed as a step in the stainingprocedure. Endogenous biotin and peroxidase activity may be removed by treatment with peroxides, while endogenous phosphatase activity may be removed by treatment with levamisole. Heating may destroy endogenous phosphatase and esterase activity.

[0140] Representative examples of suitable fluorophores for imaging application include, without limitation fluorescein or its derivatives, such as fluorescein-5 -isothiocyanate (FITC), 5- (and 6)-carboxyfluorescein, 5- or 6-earboxyfluorescein, 6-(fluorescein)-5-(and 6)-carboxamido hexanoic acid, fluorescein isothiocyanate, xanthene and its derivatives; rhodamine and its derivatives, such as tetramethylrhodamine and tetramethylrhodamine-5-(and-6)-isothiocyanate (TRITC); cyanine and its derivatives,; coumarin and its derivatives, such as (diethyl- amino)coumarin or 7-amino-4-methylcoumarin-3-acetic acid, succinimidyl ester (AMCA), as well as BODIPY dyes, pyrene-based dyes, anthracene-based dyes , as well as derivatives thereof, and non-standard dye scaffolds such as charge transfer dyes that exhibit long-Stokes shift behaviors.

[0141] Fluorophores for use in imaging application can include reactive functional groups (e.g., amine, carboxylic acid, azide, alkyne, succinimidyl ester, sulfonyl chloride, maleimide, and the like) that are capable of reaction with reactive group in or on a substance to provide a fluorescently-labeled substance. Representative examples of reactive fluorophores include, but are not limited to: sulforhodamine 101 sulfonyl chloride (TexasRed™ or TexasRed™ sulfonyl chloride; 5-(and-6)-carboxyrhodamine 101, succinimidyl ester, also known as 5-(and-6)- carboxy-X-rhodamine, succinimidyl ester (CXR); lissamine or lissamine derivatives such as lissamine rhodamine B sulfonyl chloride (EisR); 5-(and-6)-carboxyfluorescein, succinimidyl ester (CFI); fluorescein-5 -isothiocyanate (FITC); 7 -diethylaminocoumarin-3 -carboxylic acid, succinimidyl ester (DECCA); 5-(and-6)-carboxytetramethylrhodamine, succinimidyl ester (CTMR); 7-hydroxycoumarin-3-carboxylic acid, succinimidyl ester (HCCA); 6-fluorescein-5- (and-6)-carboxamidolhexanoic acid (FCHA); A^-(4,4-difluoro-5,7-dimethyl-4-bora-3a,4a-diaza- 3-indacenepropionic acid, succinimidyl ester; also known as 5,7-dimethyl BODIPY™ propionic acid, succinimidyl ester (DMBP); “activated fluorescein derivative” (FAP), available from Thermo Fisher Scientific; eosin-5-isothiocyanate (EITC); erythrosin-5-isothiocyanate (ErlTC); and Cascade™ Blue acetylazide (CBAA) (the O-acetylazide derivative of 1 -hydroxy-3, 6, 8- pyrenetrisulfonic acid). Yet other potential fluorophores useful herein include, but are not limited to, fluorescent proteins such as green fluorescent protein (GFP) and its analogues or derivatives,fluorescent amino acids such as tyrosine and tryptophan and their analogues, and fluorescent nucleosides.

[0142] Fluorescent molecules for use as detectable labels include commercially available compounds or their reactive counterparts, such as, for example, cyanine dyes such as Cy2, Cy3, Cy 3.5, Cy5, Cy5.5, Cy 7 from Cytiva (Marlborough, MA); cyanine and rhodamine-based DY dyes from Dyomics GmbH (Germany); and dyes that are commercially available from Sigma- Aldrich Co. (St. Louis, MO) and Thermo Fisher Scientific (Waltham, MA), including, e.g., eFluor™ dyes, Alexa Fluor™ dyes (e.g., Alexa Fluor™ 350, 488, 555, 568, 594, 647, 680 and 750), Alexa Fluor™ Plus dyes, NovaFluor™ dyes, Oregon Green 488, Pacific Blue (3-carboxy- 6, 8-difluoro-7-hydroxy coumarin), and Rhodamine Green. Additional commercial suppliers of fhiorophores and reactive versions thereof suitable for spatial imaging techniques, as disclosed herein, include the iFluor and mFluor reagents, as well as PE-Cy5 and APC-Cy7 tandem fluorescent probes from AAT Bioquest and ATTO fluorescent labels from Atto-Tec GmbH (Siegen, Germany).

[0143] Yet other examples of detectable labels that can be used in imaging methods described herein include phycoerythrin and inorganic fluorescent labels such as particles based on semiconductor material (e.g., Qdot™ semiconductor nanocrystals from Thermo Fisher Scientific).

[0144] A target or analyte may comprise a protein, such as a glycoprotein or lipoprotein, phosphoprotein, methylated protein, or a protein fragment, a peptide, or a polypeptide. A target or analyte may comprise a nucleic acid segment or a nucleic acid analog segment.

[0145] A target or analyte may comprise one or more of lipids; glyco-lipids; carbohydrates; polysaccharides; salts; ions; or a variety of other organic and inorganic substances. A target or analyte may be expressed on the surface of the sample, such as on a membrane or interface. Alternatively, a target or analyte may be contained in the interior of the sample. In the case of a cell sample, for instance, an interior target or analyte may comprise a target or analyte located within the cell membrane, periplasmic space, cytoplasm, or nucleus, or within an intracellular compartment or organelle.

[0146] A target or analyte may also include viral particles, or portions thereof, such as nucleic acids or proteins. The viral particle may be a free viral particle, i.e., not associated with any othermolecule, or it may be associated with any sample described above. A target or analyte may be an antigen or an antibody.

[0147] One embodiment described herein is a method for calibrating an imaging device and analyzing a sample for a plurality of analytes comprising incubating a solution comprising one or more affinity molecules that labels one or more analytes in the sample and detecting a signal from each affinity molecule that is bound to the plurality of analytes, thereby detecting the presence or amount of each analyte in the plurality of analyte. In one aspect, the affinity molecule is conjugated to a fluorophore, conjugated to an enzyme, bound by another affinity molecule that is conjugated to a fluorophore, or bound by another affinity molecule that is conjugated to an enzyme. In another aspect, the detecting is performed using an imaging device selected from a light or fluorescence microscope, a charge coupled device (CCD) camera or imager, a phosphorimager, or a combination thereof. The method further comprises calibrating an imaging device by obtaining a first image of an unstained version of a sample; acquiring an unstained spectral profile of the sample using the first image; obtaining, for each of a plurality of stained versions of the sample, a second image, wherein, in each of the stained images, a portion of the sample is stained with a different fluorophore of a plurality of fluorophores; acquiring a plurality of spectral profiles associated with the plurality of stained images, each spectral profile associated a fluorophore of the plurality of fluorophores; generating an unmixing matrix based on the unstained spectral profile and the plurality of spectral profiles; obtaining a mixed image of a second sample, wherein, in the mixed image, the second sample is stained with each fluorophore of the plurality of fluorophores; and obtaining an unmixed image of the second sample by applying the unmixing matrix to the mixed image.

[0148] Various operations may be described as multiple discrete actions or operations in turn, in a manner that is most helpful in understanding the subject matter disclosed herein. However, the order of description should be construed as to imply that these operations are necessarily order dependent. In particular, these operations may not be performed in the order of presentation. Operations described may be performed in a different order from the described implementation. Various additional operations may be performed, and / or described operations may be omitted in additional implementations.

Claims

CLAIMS1. A method for automatically extracting spectral profiles of a calibration sample, the method comprising: receiving, by a computing device, one or more single-color control images, a foreground channel, and a background channel; determining, by the computing device, a difference between the foreground channel and the background channel; acquiring, by the computing device, a foreground pixel mask from the difference; averaging, by the computing device, a set of foreground pixels in the foreground pixel mask to generate a first spectrum; and subtracting, by the computing device, an unstained spectrum from the first spectrum to generate a second spectrum, wherein the second spectrum defines a spectral profile of the sample.

2. The method of claim 1, further comprising: receiving the unstained spectrum of the sample; receiving a reference spectrum associated with each of the one or more fluorophores applied to the sample; and determining, based on the unstained spectrum and the reference spectrum, the foreground channel and the background channel.

3. The method of claim 1 or claim 2, further comprising: applying, before determining the difference, an intensity normalization value to the foreground channel and the background channel; and scaling, before determining the difference, the background channel.

4. The method of any of claims 1 - 3, wherein determining the difference between the foreground channel and the background channel includes subtracting the background channel from the foreground channel.

5. The method of any of claims 1 - 4, further comprising: determining a correlation threshold for the foreground pixel mask; applying the correlation threshold to the second spectrum to generate a third spectrum; and outputting the third spectrum.

6. The method of any of claims 1 - 5, wherein acquiring the first pixel mask includes applying a first threshold to the difference.

7. The method of claim 6, wherein applying the first threshold to the difference including performing an Otsu’s method thresholding operation on the difference.

8. The method of any of claims 1- 7, further comprising: capturing an unstained image of the sample prior to the one or more fluorophores being applied to the sample; and extracting the unstained spectrum from the unstained image.

9. The method of any of claims 1 - 8, wherein the set of foreground pixels includes non-zero foreground pixels in the foreground pixel mask.

10. A method of calibrating an imaging device, the method comprising: obtaining a first image of an unstained version of a sample; acquiring an unstained spectral profile of the sample using the first image; obtaining, for each of a plurality of stained versions of the sample, a second image, wherein, in each of the stained images, a portion of the sample is stained with a different fluorophore of a plurality of fluorophores; extracting a plurality of spectral profiles associated with the plurality of stained images, each spectral profile associated a fluorophore of the plurality of fluorophores; and generating an unmixing matrix based on the unstained spectral profile and the plurality of spectral profiles.

11. The method of claim 10, further comprising: receiving a selection of one or more fluorescent channels to capture in the unmixed image, wherein applying the unmixing matrix to the mixed image removes fluorescent channels from the mixed image that are not included in the selection of one or more fluorescent channels.

12. The method of any of claims 10 - 11, wherein acquiring the unstained spectral profile of the first sample includes averaging all pixels in the unstained image.

13. The method of claims 10 - 12, wherein acquiring the plurality of spectral profiles associated with the plurality of stained images includes: receiving, for each of the plurality of stained images, one or more single-color control images, a foreground channel, and a background channel, wherein the singlecolor control images are images of the sample with the fluorophore applied to a portion of the sample, and wherein the foreground channel and the background channel are associated with the fluorophore; determining a difference between the foreground channel and the background channel; and acquiring a foreground pixel mask from the difference.

14. The method of claim 13, wherein acquiring the plurality of spectral profiles associated with the plurality of stained images includes: averaging a set of foreground pixels in the foreground pixel mask to generate a first spectrum; and subtracting an unstained spectrum from the first spectrum to generate a second spectrum.

15. A method of image acquisition of a tissue sample, the method comprising: calibrating an imaging device as in any of claims 10 - 14;obtaining a mixed image of a tissue sample, wherein, in the mixed image, the tissue sample is stained with each fluorophorc of the plurality of fluorophorcs; and obtaining an unmixed image of the second sample by applying an unmixing matrix to the mixed image.

16. An imaging system, comprising: a calibrated imaging device, and a controller including an electronic processor and a non-transitory, computer readable medium, wherein the controller is configured to: receive a selection of one or more fluorescent channels for imaging a sample, wherein the sample is stained with a plurality of fluorophores; capture, with the imaging device, a raw image of the sample; apply an unmixing matrix to the raw image to generate an unmixed image, wherein the unmixing matrix is generated by repeating a single color control (SCC) operation on a plurality of calibration samples, wherein each calibration sample in the plurality of calibration samples is stained with a different fluorophorc included in the plurality of fluorophores; and generate an unmixed image.

17. The imaging system of claim 16, wherein the SCC operation includes: capturing a raw SCC image of a first calibration sample; performing spectral extraction on the raw SCC image to obtain an SCC spectrum; and normalizing the SCC spectrum.

18. The imaging system of claim 17, wherein the unmixing matrix is generated using the normalized SCC spectrum.

19. The imaging system of claims 16 - 18, wherein applying the unmixing matrix to the mixed image removes fluorescent channels from the raw image that are not included in the selection of one or more fluorescent channels.

20. The imaging system of any of claims 16 - 19, wherein applying the unmixing matrix to the mixed image calculates the relative contribution from each fluorophorc of the plurality of fluorophores for every pixel of the mixed image.

21. A calibration slide, comprising: a microscope slide; and a plurality of detectable calibration beads disposed in a mountant within a defined area on the surface of the microscope slide, wherein the mountant has a refractive index that at least matches the refractive index of the microscope slide.

22. The calibration slide of claim 21, comprising a 1,300,000 to about 2,600,000 beads within a 10 mm2area on the surface of the slide.

23. The calibration slide of any of claims 21 or 22, wherein the plurality of beads has an average bead diameter ranging from about 0.1 pm to about 6.0 pm.

24. The calibration slide of any of claims 21-23, wherein the plurality of beads has an average bead diameter of about 4 pm to about 5 pm.

25. The calibration slide of any of claims 21-24, wherein the plurality of beads has an average bead diameter with a coefficient of variation (CV) of between about 2% and 5%.

26. The calibration slide of any of claims 21-25, wherein the wherein the plurality of beads has an average bead diameter with a coefficient of variation (CV) is around 2%27. The calibration slide of any of claims 21-26, wherein the mountant is a polymeric.

28. The calibration slide of any of claims 21-27, wherein the mountant further comprises a non-ionic detergent, glycerol, or a combination thereof.

29. The calibration slide of any of claims 21-28, wherein the mountant has a refractive index of 1.47 to 1.52.

30. The calibration slide of any of claims 21-29, wherein the calibration beads each comprise a polymeric bead, wherein each bead comprises one or more detectable labels.

31. The calibration slide of claim 30, wherein the one or more detectable labels is a fluorophore.

32. The calibration slide of any of claims 21-31, wherein the plurality of calibration beads comprises two or more populations of fluorophores, wherein the two or more populations of fluorophores emit detectable light with a different emission maximum between about 385 nm and 860 nm, when irradiated with light with excitation wavelength corresponding to between 100 and 800 nm.

33. The calibration slide of any of claims 21-32, wherein the plurality of calibration beads comprises 2-10 populations of fluorophores.

34. The calibration slide of claim 33, wherein the fluorescence emission maximum of each fluorophore population is detectable in a different channel of an imaging system.

35. The calibration slide of claim 33, wherein the fluorescence emission maximum of each fluorophore population has a fluorescence signal intensity that is detectable in a different channel of an imaging system.

36. The calibration slide of claim 33, wherein each fluorophore populations emits light with less than 100 msec exposure time.

37. The calibration slide of claim 33, wherein the fluorophore comprises cyanine-based dyes, hemi-cyanine -based dyes, rhodamine-based dyes, coumarin-based dyes, pyrene-based dyes, indacene-based dyes, or indole-based dyes.

38. The calibration slide of claim 33, wherein each calibration bead encapsulates the one or more fluorophores.

39. The calibration slide of any of claims 21-38, wherein the slide exhibits a shelf life of 1 year or greater when stored at a temperature ranging from about 2 degrees C to about 30 degrees C, when protected from light.

40. A method of preparing a calibration slide, the method comprising: providing fluorescent beads dispersed a dispersal solution; spreading the dispersal solution onto a microscope slide; drying the beads in the bead solution; and mounting the beads using a mounting solution.

41. The method of claim 40, wherein the beads are polysterene-based beads.

42. The method of claims 40 or 41, wherein the beads have a diameter ranging from about0.1 pm to about 6.0 pm.

43. The method of any of claims 40-42, wherein the diameter of the bead is about 4.7 pm.

44. The method of any of claims 40-43, wherein the dispersal solution has a concentration of beads of about 0.2% w / v.

45. The method of claim 44, wherein the dispersal solution comprises a non-ionic detergent.

46. The method of any of claims 40-45, wherein a bead solution is spread onto the microscope slide ranges from about 10 pm to about 15 pm.

47. The method of any of claims 40-46, wherein the bead density of the beads mounted on the calibration slide ranges from about 4000 to about 8000 beads per 20x field of view.

48. The method of any of claims 40-47, wherein the mounting solution has a refractive index that at least matches the refractive index of the microscope slide.

49. The method of any of claims 40-48, wherein the mounting solution is glycerol-based.

50. The method of any of claims 40-49 further comprising: staining one or more beads with a plurality of fluorescent dyes, wherein each dye in the plurality of dyes emits at different wavelengths; and generating a bead set51. The method of claim 50, wherein the plurality of fluorescent dyes emits light in the range between 385 nm - 860 nm.

52. The method of any of claims 40-51, wherein the concentration of stain for staining the beads is optimized to provide visible signal with less than 100 msec exposure time.

53. The method of any of claims 40-52, wherein the bead set comprises beads stained with dyes that emit at different wavelengths when excited at a particular wavelength.

54. Use of the calibration slide of any one of the preceding claims for optical alignment, illumination correction, and spectral unmixing calibration of a fluorescent or brightfield imaging system.

55. An imaging system, the system comprising: the calibration slide of claims 21-39; and an imaging device, wherein the calibration slide is used to calibrate the imaging device.

Images