SPATIAL MULTIPLEXING OF HISTOLOGICAL STAINS

Abstract

The following concerns a method for co-localization of microscopy or histology stains by the assembly of a virtual image from one or more imaging operations. In particular, the method decreases the time required to obtain multiple labeled antigen or protein histology images of a biological sample. The method includes imaging the tissue as it is sliced by a microtome with a knife edge scanning microscope and spatially aligning the samples by the generated images. The spatial alignment of samples enabled by the method allows a panel of different antigen or protein secondary or functional stains to be compared across different sample slices, thereby allowing concurrent secondary stains of tissues and cells.

Description

CROSS-REFERENCE

This application claims benefit as a Continuation of U.S. application Ser. No. 15/205,288, filed Jul. 8, 2016, which claims benefit of U.S. Provisional Application No. 62/190,931, filed Jul. 10, 2015, the entire contents of the aforementioned is hereby incorporated by reference as if fully set forth herein, under 35 U.S.C. § 120. The applicant(s) hereby rescind any disclaimer of claim scope in the parent application(s) or the prosecution history thereof and advise the USPTO that the claims in this application may be broader than any claim in the parent application(s).

BACKGROUND

The present disclosure generally relates to a method of slicing, imaging, and staining tissue for diagnostic or research purposes. In particular, the present disclosure relates to Serial Section Microscopy, the sectioning of biological tissue and other material samples using a microtome, and more specifically, a method of imaging tissue samples stained with immunohistochemical antigens.

Immunohistochemistry is a process in which a set of antigens are applied to a section of biological tissue. Immunohistochemical staining is commonly used to identify abnormal cells, employing antibodies to test for certain antigens in a sample of tissue. The antibody is usually linked to a radioactive substance or a dye that causes the antigens in the tissue to become visible under a microscope, and this process is generally done in a panel or series of different stains to detect various cancer cell strains.

The present disclosure converges and optimizes of several different workflows that are traditionally used in immunohistochemistry by using the novel methods and processes made possible with the KESM technology. By presenting the following three studies of traditional workflows that represent the current state of the art, the novel and useful method as described herein can be better understood.

SUMMARY

The present disclosure generally relates to systems and methods for an imaging an object with a microtome and applying immunohistochemical stains, in order to detect certain biological markers for medical diagnosis or research. In particular, the present disclosure relates to using Serial Section Microscopy for these diagnostics, by sectioning biological tissue and other material samples using a Knife Edge Scanning Microscope and applying stains to individual sections, and using a spatial multiplexing method enabled by the Knife Edge Scanning technology to compare various stains and reactions across a sample.

The following concerns techniques for rapid pathological and/or histological examination of a tissue sample using multiple contrasting agents. By performing an additional imaging step before tissue handling made possible by the Knife Edge Scanning Microscope, the fundamental shape of the imaged object can be captured before physical or chemical deformations are made. Thus, the deformed slice may be registered back into the original coordinate system of the sample. This can also present a unique ability to better co-locate biological markers across many serial sections of a single sample, and can create a more accurate representation of the tissue as a whole by using the intermediate imaging step to re-map individual sections to each other, after chemical or mechanical treatment. This can provide unique advantages by allowing multiple contrast agents to be compared quickly across a sample more quickly than the traditional workflow, with less distortions.

Other goals and advantages of the disclosure will be further appreciated and understood when considered in conjunction with the following description and accompanying drawings. While the following description may contain specific details describing particular embodiments of the disclosure, they should not be construed as limitations to the scope of the disclosure but rather as an exemplification of preferable embodiments. For each aspect of the disclosure, many variations are possible as suggested herein that are known to those of ordinary skill in the art. A variety of changes and modifications can be made within the scope of the disclosure without departing from the spirit thereof.

INCORPORATION BY REFERENCE

All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference.

BRIEF DESCRIPTION OF THE DRAWINGS

The novel features of the invention are set forth with particularity in the appended claims. A better understanding of the features and advantages of the present invention will be obtained by reference to the following detailed description that sets forth illustrative embodiments, in which the principles of the invention are utilized, and the accompanying drawings of which:

FIG. 1A is a schematic illustrating the typical anatomist's workflow using the current state of the art.

FIG. 1B is a schematic illustrating the typical histologist or pathologist's workflow using the current state of the art.

FIG. 1C is a schematic illustrating the typical biologist's workflow using the current state of the art.

FIG. 1D1 is a is a schematic illustrating how image distortions occur in traditional workflow using the current state of the art.

FIG. 1D2 is a schematic illustrating how spatially mulitplexing using the technology described herein improves the process of aligning image stacks by aligning to a non-distorted image.

FIG. 2A is a schematic illustrating the steps for imaging a sample using the spatial multiplexing method described herein.

FIG. 2B is a schematic illustrating the co-registration of Primary and Secondary Images by side-by-side presentation.

FIG. 2C is a schematic illustrating the co-registration of several Z images with different stains applied by mathematical combination to create a composite image of coincident stain reactions.

DETAILED DESCRIPTION

Improved systems and methods are disclosed herein by comparison to the three traditional processes of slicing, staining and imaging tissue samples as described above. The present disclosure includes improvements upon the three aforementioned workflows by introducing an additional imaging step(s) at or before the time of sectioning, enabled by the KESM technology.

Definitions

“Immunohistochemistry” may refer to the application of antigens or proteins in tissue sections by the use of labeled antibodies as specific reagents that cause antigen-antibody interactions, which can be visualized by a marker such as fluorescent dye or stain.

“Serial Section Microscopy” may refer to the practice of taking serial sections with a microtome and imaging them, traditionally by mounting the slices to glass and staining.

“Knife Edge Scanning Microscope” or “KESM” may refer to a microscope that performs Serial Section Microscopy in an automated fashion. See U.S. Pat. No. 6,744,572.

“Section” or “slice” may refer to a single strip of contiguous material that was removed from the block face by means of a relative motion between the sample and the knife.

“Microtome” may refer to a device in which a block of material is precisely cut such that a very thin layer of material is removed, or sectioned, from the surface of the block. Similarly, the term “microtomy” may apply to the operation of microtomes.

“Imagery” may include any technique designed to measure an “image”, a spatial map of an optical or electronic response. This can include optical or electron microscopy techniques.

“Imaging” may generally refer to data collection in order to generate a visualization of a given area.

“Registration” or “co-registration” may refer to a computational step in which images are aligned, stretched, and deformed to match one another. In reference to Serial Sectioning Microscopy, this step can correct for tissue deformation from slicing, mounting, and chemical treatments.

“Multiplex” or “multiplexing” may refer to a method of selecting one location within a matrix by having two selective addressing systems on both sides of the matrix, thus needing only 2N selectors to address NA2 locations.

“Stain” may refer to a chemical treatment, which aims to change the photonic response of all or parts of a medium, by methods including but not limited to attaching a pigment, a genetically expressed flourophore, or chemistry designed to modify the target structure to be imaged. This may include but is not limited to traditional light microscopy stains, contrast agents used in immunohistochemistry (IHC) and in situ hybridization (ISH) labeling techniques.

“Molecular Diagnostic” may refer to a form of chemical test or assay, which takes a sample of tissue and identifies biological markers to make a diagnostic.

“Transformation” may refer to the re-mapping of a single point in an image from the unstained image to another stained image.

“Interpolation” may encompass methods for selective spatial sampling of a numerical value derived from another numerical field. Methods commonly used may include “nearest-neighbor” interpolation, linear, polynomial, or b-spline based techniques. These are generally used to compute discreet “interpolant” values of a transformed image, or approximate the value of a function at a given spatial coordinate.

Distortions

The process of capturing and mounting sections from a microtome to a glass slide may physically distort the tissue. The distortion can be a warping of the thin and delicate tissue, a folding of the sections, or even tearing. The warping can prevent simple alignment of serial sections, as the microscopic features may not line up properly from section to section. Typically, the distortions must be corrected using a combination of manual editing and software, where registration marks are chosen on the adjacent images and software aligns the registration marks. This process is often slow and difficult, and can prevent the more widespread adoption of serial sectioning.

Staining and Slice Thickness

Controlling slice thickness can be important for several reasons:

• • 1. Maintaining the structural/architectural integrity of the section for subsequent handling, staining, mounting, and processing.
  • 2. Ensuring that the section is an appropriate thickness to the structures being resolved. The slice should be thick enough so that unique features fit within the slice. In cell characterization, the slice is typically a thickness, which allows 1-2 layers of cells in plane. If it is too thick, many layers of cells can obscure the ability to obscure cell level detail. Similarly, if the slice it too thin relevant features within a singular cell layer may be truncated.
  • 3. Ensuring that the slice is thin enough of the chemical kinetics of staining to adequately label the associated features. Many contrast agents employ large molecules, which may be limited in the amount of tissue through which they are able to diffuse and correspondingly label.

Similarly contrast agents, which can depend on chemical-kinetics of the base material, may behave differently for thick or thin sections.

It is common practice in histology or pathology labs to cut slices of different thickness for different staining/contrasting techniques. This is especially true when rapid results are needed (thin slices typically can be stained more quickly), or complex chemistries are employed in the staining as in IHC or ISH methods.

The Anatomist Workflow

There are many reasons that a biologist might want to measure a tissue property across a three dimensional volume of space. To do this using the current state of the art, several slices would be cut, stained, and co-registered against one and other. FIG. 1A is a diagram that illustrates the typical anatomist's workflow 100A employing the current state of the art. In a step 111, a sample 101 may be sliced into one or more thick sections such as a first thick section 121A, a second thick section 121B, and a third thick section 121B. The thick sections 121A, 121B, 121C may be stained in a step 131 and the stained thick sections 121A, 121B, 121C may then be imaged and co-registered with one another in a step 141.

The Histologist/Pathologist Workflow

Similarly, when a histologist or pathologist is attempting to make a diagnosis of diseased tissue, several thick sections 121A, 121B, 121C may be cut. Then, one would be stained, imaged and examined in a step 151. Based on the imagery input from a medical professional, this process could be repeated several times before finally a diagnosis is made in a step 161, and the diagnosis of one of the thick sections may be used to inform the staining, imaging, and examination of further thick sections. The diagnosis of the stained thick sections may indicate an appropriate treatment for the patient in a step 171. FIG. 1B is a diagram that illustrates the typical histologist or pathologist's workflow 100B employing the current state of the art.

The Biologist Workflow

Biological researchers typically employ an immunohistochemical staining technique where a particular piece of tissue is stained, imaged, then stripped clear of the stain from the section of tissue. The staining and stripping process can be repeated in order to image the immune or antigen reactions of a full panel of stains on the sample piece of tissue. FIG. 1C is a diagram that illustrates the typical biologist's workflow 100C employing the current state of the art. The sample 101 can be sliced and placed in a slide in a step 181. In a step 191, the slice/slide may be stained. In a step 1011, the stained slide/slice may be imaged. In a step 1031, the image may be stored. In a step 1021, the stain may be removed and the slide/slice may be stained once more in a step 191.

This process of putting down a stain, imaging, stripping the stain, re-staining, re-imaging the stain, then re-imaging again is known as serial multiplexing. This approach, which is commonly used by biologists in immunohistochemistry, is time consuming, often taking a week or longer to complete a full panel of antigen stains.

Another approach is differential staining of the next section, based on examination from a pathologist. This can lead to fairly long turnaround times, as well as needing increased interaction from the physician.

All of these approaches have fundamental drawbacks which the scope of this disclosure seeks to address:

• • The slide-mounting, staining, and imaging each introduce unique deformations, distortions, and artifacts in the slices which can make the final process of co-registration difficult, error prone, and time consuming.
  • There are often a large number of serial steps, each of which can involve significant human labor and attention to detail if high-quality reliable results are to be produced.
  • Given the 3D nature of a sample, the features can be changing across even adjacent slices, and automated feature extraction and warp correction has been difficult in larger samples.

The present disclosure describes systems and methods to decreases the human effort required to process multiple stains on a sample and increase the accuracy of the reconstructed products by introducing an additional imaging step enabled by the KESM technology as applied herein.

Post-Processing Distortions

In typical serial section microscopy, the slices are aligned using human annotation or algorithms, where the warping during mounting is corrected prior to reconstructions. The process typically involves the selection of registration marks, which are points that occur across adjacent sections. The registration points may be used to calculate a transformation function, which is applied to both images to bring the pixels in the images into alignment. Choosing registration marks across a series of images can be difficult, because each of the images in the stack is different from the next. Features also rarely cross exactly perpendicular to the cutting plane, so if the same features are chosen for registration marks, the features may drift spatially across the sections and thus for example an object at an incline may be misconstrued as being vertical.

As disclosed herein, the post-processing of images may be improved because the post-processing of distortions may be performed on two images of the exact same section, one without distortions and one or more without. Since the images are of the same slice, the same exact registration marks will occur on all images, making the selection process easier and more consistent. The same phenomenon can also reduce spatial drift that would otherwise occur for cylindrical features traveling at an incline relative to the cutting plane. FIG. 1D1 and FIG. 1D2 illustrate how distortions occur employing the current state of the art (FIG. 1D1) in comparison to how image post-processing may be improved with regard to these distortions as disclosed herein (FIG. 1D2).

As shown in FIG. 1D1, an object 103 may be in present in the sample 101 which may be sliced into two slices 105A and 105B. Images 107A, 107B may be generated for each slice 105A, 105B, respectively, showing the object 103 at different depths.

As shown in FIG. 1D2, an object 103 may be present in the sample 101 which may be sliced into two slices 105A and 105B. Primary and secondary images may be generated for each of the slices 105A, 105B (such as primary image 109A1 and secondary image 109A2 for primary slice 105A, and primary image 109B1 and secondary image 109B2 for secondary slice 105B.)

Primary Imaging

As described herein, the first step in this method comprises a Primary Imaging (PI) step, which may capture a view of the section before processing or post-processing distortions. This may be accomplished by imaging the sample before slicing or by imaging during slicing. The primary imaging may be performed with a KESM, which may capture an un-warped image on the block face during the slicing operation. These images may be referred to as X_N. By incorporating this PI step, the Secondary Imaging (SI) step can have a direct anchor to the actual original shape and location of the slice, which may enable better registration and analysis of stain reactions of a sample. FIG. 2A is a diagram that illustrates the imaging steps for the spatial multiplexing method 200. The sample 101 may be imaged in a primary imaging step 211A before a thin section 221A is sliced from the sample 101. Further primary imaging steps 211B to 211N may be performed before further slicing the sample to further thin sections 221B to 221N. The primary images may be collected and registered with one another to generate a virtual thick slice 223.

As described herein, after the PI steps (221A, 221B, . . . 221N), the slice(s) may be mounted on a glass slide and antigen or protein stains may then be applied in a step 231 to the sample slices for further analysis.

Secondary Imaging

Another aspect of the disclosure includes a Secondary Imaging (SI) step(s) 241A, 241B, . . . 241N. In the SI steps, the KESM may be used to image the stained slices of the sample 101 after a stain or a full panel of stains 231 has been applied. These step(s) may be repeated as many times as is desired, re-imaging the slices each time a new stain is applied to the sample. These images will be referred to as Y_n.

Reconstruction

Another aspect of the disclosure describes a reconstruction step. In the reconstruction step, various computations may be employed to create a reconstructed image across different stained images. As shown in FIG. 2A, the secondary images may be collected and registered with one another to generate a stack of co-registered stains 243. The primary virtual thick slice 223 and the co-registered stack of stained slices 242 may be analyzed in a data-gathering or diagnosis step 251.

As described herein, a computational transformation of the Y_n images may be performed to reconstruct and spatially align the various sample slices to each other. The panel of stained Y_n images may be mapped back to the biomarker coordinates established by the X_n images by employing computational transformations. These remapped images will be referred to as Z_n. These computational transformations may include, but are not limited to:

• • a. “Procrustean” transformations, which may include stretch, shear, translation, rotation, and more general affine transformations to map visible variables or biomarkers across images.
  • b. “Elastic sheet” type transformations employing basis splines, or other non-linear interpolation schemes to map biomarkers by matching the curvature of the object, incorporating both affine and nonaffine transformations.
  • c. Optical-based corrections to account for the differences between the optics of the primary and secondary imaging. This can include perspective, barrel, pincushion, and chromatic corrections.

Co-Registration

Another aspect of the disclosure describes a co-registration step, wherein the images from the PI and SI steps captured by the KESM are compared and aligned to each other based on the mapped biomarkers established in the reconstruction step.

As described herein, the stack of Z_n images may be superimposed to co-register the different stains. This step may be repeated to complete a full panel of stains and compare the results based on the co-registered images. Methods for completing the co-registration step may include:

• • a. Side-by-side presentation, rendering, or image overlay of the Z_n images. FIG. 2B illustrates how the Primary images 261 and Secondary images 262 are co-registered using a side-by-side presentation method, and may be shown as a composite image 263.
  • b. Mathematical combination of several Z images to create a composite image or virtual “slice” capable of showing where different stains are present, and/or coincident. FIG. 2C illustrates how several images 271, 272, 273 may be combined to create a composite image 274 by mathematic combination.

Further Embodiments

An additional embodiment of a workflow may be similar to the work flow 200 above, with an additional imaging step between the mounting and staining steps.

The above description(s) describes the treatment of a single slice in FIG. 2A. Using the primary imaging information, multiple slices may be aligned across the Z plane to the slices above and below within the sample. Using this anchoring, the workflows 100A, 100B, 100C described above may be replaced in the following ways:

• • The Anatomist Workflow 100A: All of the stains in the “stain-panel” can be made the same. Each stained slice may be linked back to its primary imaging, and the primary images to each other. This can both improve the quality of reconstruction, as well as minimize the fraction of human involvement.
  • The Histologist/Pathologist Workflow 100B: A large number of requested stains could be run independently within the panel. Each of these stained images may be again linked back to the primary imaging, and many layers/contrast agents may be linked back to the overall sample. This may minimize the number of iterations in which the medical professional would be involved, and lead to a quicker diagnosis, and faster turnaround on lab analyses.
  • The Biologist Workflow 100C: Several different stains could be repeated on interleaved layers. In this way stains could be multiplexed over the sample volume, and example including 3 stains labeled a, b, c might look like:
    • a|b|c|a|b|c|a|b|c|a|b|c|a|b|c|a|b|c

This multiplexing approach gives a larger 3D distribution of the labels across the volume while tethering each slice back to the overall block. Additionally, the stained information could be interpolated across adjacent sections.

These embodiments could also be augmented in any one of at least the following ways:

• • 1. Several channel images can be combined into one, creating a virtual multi-channel panel image
  • 2. The optimal sectioning thickness and number of stains can be determined by the features observed in the primary imaging, i.e. some features may be large, and thick sections may be appropriate, where other features are smaller and may necessitate thin sections.
  • 3. The entire panel does not have to be determined at once. The output of a first round of imaging could be used to determine the second round.
  • 4. Section thickness could be adjusted with respect to the stain chemistry, i.e. thinner or thicker sections can be cut for a multiplexed stain optimized for each particular contrast agent's properties.
  • 5. Every n'th slice might be treated differently, based on the primary imaging. This might include:
  • 6. Being sliced at a thickness optimal for the stain in question.
  • 7. Being diverted to a molecular diagnostic or other chemical assay.
  • 8. Be discarded based on an imaging or slicing defect or lack of sample in the slice.
  • 9. Be archived to comply with regulations.
  • 10. As above, but instead making the slice treatment decision based on the Primary Imaging step.

While preferred embodiments of the present disclosure have been shown and described herein, it will be obvious to those skilled in the art that such embodiments are provided by way of example only. Numerous variations, changes, and substitutions will now occur to those skilled in the art without departing from the scope of the present disclosure. It should be understood that various alternatives to the embodiments of the present disclosure described herein may be employed in practicing the inventions of the present disclosure. It is intended that the following claims define the scope of the invention and that methods and structures within the scope of these claims and their equivalents be covered thereby.

Claims

1. A method of analyzing a sample, the method comprising:

slicing the sample into a plurality of sections;

for each section in the plurality of sections: generating a primary image of the section; associating the primary image with the section; based on information from the primary image of the section, determining whether to stain the section; based on a determination that the section is to be stained: determining a staining agent to be used to stain the section using the information from the primary image of the section; staining the section using the staining agent; generating a secondary image of the section by imaging the stained section; and associating the secondary image with the section.

2. The method of claim 1, wherein the sample comprises a tissue sample.

3. The method of claim 1, further comprising:

for each section in the plurality of sections having an associated primary image and an associated secondary image: co-registering the associated primary image with the associated secondary image by post-processing the associated primary image having no distortions with the associated secondary image having distortions that occurred during the staining, thereby improving post-processing of images; and wherein the post-processing includes processing distortions in the associated secondary image based on the associated primary image; and

co-registering the secondary images associated with the plurality of sections with one another.

4. The method of claim 1, further comprising:

generating a virtual model of the sample based on primary images associated with each section of the plurality of sections.

5. The method of claim 1, further comprising:

for each section in the plurality of sections having an associated primary image and an associated secondary image: co-registering the associated primary image with the associated secondary image by post-processing the associated primary image having no distortions with the associated secondary image having distortions that occurred during the staining, thereby improving post-processing of images; and wherein the post-processing includes processing distortions in the associated secondary image based on the associated primary image;

co-registering the secondary images associated with the plurality of sections with one another; and

co-registering the co-registered plurality of secondary images of the sample to the virtual model.

6. The method of claim 5, further comprising:

generating a diagnosis in response to the co-registration of the co-registered plurality of secondary images of the sample and the virtual model.

7. The method of claim 1, wherein slicing the sample into a plurality of sections comprises slicing a block face of the sample.

8. The method of claim 1, further comprising:

mounting the plurality of sections onto a plurality of slides.

9. The method of claim 1, wherein the staining agent is one of: an antigen or protein stain.

10. One or more non-transitory computer-readable storage media, storing one or more sequences of instructions, which when executed by one or more processors cause performance of:

slicing the sample into a plurality of sections;

for each section in the plurality of sections: generating a primary image of the section; associating the primary image with the section; based on information from the primary image of the section, determining whether to stain the section; based on a determination that the section is to be stained: determining a staining agent to be used to stain the section using the information from the primary image of the section; staining the section using the staining agent; generating a secondary image of the section by imaging the stained section; and associating the secondary image with the section.

11. The one or more non-transitory computer-readable storage media of claim 10, wherein the sample comprises a tissue sample.

12. The one or more non-transitory computer-readable storage media of claim 10, further comprising:

for each section in the plurality of sections having an associated primary image and an associated secondary image: co-registering the associated primary image with the associated secondary image by post-processing the associated primary image having no distortions with the associated secondary image having distortions that occurred during the staining, thereby improving post-processing of images; and wherein the post-processing includes processing distortions in the associated secondary image based on the associated primary image; and

co-registering the secondary images associated with the plurality of sections with one another.

13. The one or more non-transitory computer-readable storage media of claim 10, further comprising:

generating a virtual model of the sample based on primary images associated with each section of the plurality of sections.

14. The one or more non-transitory computer-readable storage media of claim 10, further comprising:

for each section in the plurality of sections having an associated primary image and an associated secondary image: co-registering the associated primary image with the associated secondary image by post-processing the associated primary image having no distortions with the associated secondary image having distortions that occurred during the staining, thereby improving post-processing of images; and wherein the post-processing includes processing distortions in the associated secondary image based on the associated primary image;

co-registering the secondary images associated with the plurality of sections with one another; and

co-registering the co-registered plurality of secondary images of the sample to the virtual model.

15. The one or more non-transitory computer-readable storage media of claim 14, further comprising generating a diagnosis in response to the co-registration of the co-registered plurality of secondary images of the sample and the virtual model.

16. The one or more non-transitory computer-readable storage media of claim 10, wherein slicing the sample into a plurality of sections comprises slicing a block face of the sample.

17. The one or more non-transitory computer-readable storage media of claim 10, further comprising:

mounting the plurality of sections onto a plurality of slides.

18. The one or more non-transitory computer-readable storage media of claim 10, wherein the staining agent is one of: an antigen or protein stain.

19. A method of analyzing a sample, the method comprising:

slicing the sample into a plurality of sections;

for each section in the plurality of sections: generating a primary image of the section; associating the primary image with the section; and based on information from the primary image of the section, diverting the section to a molecular diagnostic.