Abstract:
Multiple different samples are obtained from a bulk material and are separately stained. The differently stained materials look different with the different stains but also have similar characteristics. A computer is used to reorient the images so that the samples are oriented with one another. The thus oriented samples can have their like parts either reoriented. Once the stained areas are analyzed, the identified area in the unstained sample can be removed by laser capture microdissection.

Description:
BACKGROUND 
       [0001]    Different techniques can be used to characterize pathology samples such as tumors. One of such techniques investigates homogenized samples and determines information from the homogenized sample, e.g., within a test tube, and the other collects spatially orientated information. 
         [0002]    Homogenized tissue sample tests can test for different characteristics. However, the whole contents of the test tube is averaged for the test. Tests of these types include polymerase chain reaction or PCR, Western blotting that can be used to quantify concentrations of types of proteins in a sample, DNA arrays, that can be used to quantify the amount of DNA in sequences, RNA arrays that can be used to quantify messenger RNA and thus determine the expression level of many different genes, and others. These kinds of tests can be very specific—for example, quantitative PCR can be used to determine the level of PCR differing by only a single mutation. However, the specificity is reduced since the test is specific to the entire sample. 
         [0003]    Staining techniques can also be used. In slide based tests the sample is sectioned into thin sections (typically 5 microns) and placed on a microscope slide for observation with a microscope, photo microscopy or image analysis. Stains are used on the tissue to make certain features visible. One stain is the classic H&amp;E stain. This stain allows pathologists to view the overall morphology of a tissue and identify areas of tumor based on morphological features that show up under the stain. Other stain techniques produce other results. For example, IHC (Immunohistochemistry) creates and links custom antibodies to proteins or other chemical species on a stain. IHC can be used to visualize contents of a slide to determine that a target molecule is present. IHC can also be used to specify which cells or even sub cellular structures in which the target molecule is present. By using several stains linked to different antibodies, it is possible to characterize the extent of co-localization of several targets or determine that they are found in different cells or organelles. 
         [0004]    FISH (Fluorescent in-situ hybridization) can locate the position on a chromosome of a given genetic sequence by using several probes linked to different colored dyes. Fish makes it possible to see the spatial relationship of different loci. For instance FISH can be used to detect chromosome translocation that cause leukemia by marking two loci known to be brought together by a translocation that causes leukemia with red and green fluorochromes. If the translocation has occurred, these 2 probes will be brought next to each other and will appear to be a single yellow dot. Thus FISH can produce detailed spatial data on the location of gene sequences. 
         [0005]    In general, the operation on homogenized tissue make many measurements but are in effect averaging over the entire block that was homogenized. This has limited their utility in practical diagnosis because the tissue sample delivered to a pathologist is rarely entirely cancerous. In cancer surgery, the goal is to remove tissue until the margins are clear (that is free of cancer). In biopsy samples, there is often no way to assure that only tumor is sampled. Further, it is known that many cancers are themselves genetically and metabolically heterogeneous. This means that the numbers produced by all of the homogenization methods may be averages of tumor and non tumor tissue or different regions of the tumor. 
         [0006]    Slide based methods overcome the localization limitations but suffer from restrictions on the number of chemical species that can be detected at once. While DNA arrays can test for thousands of sequences at once, FISH is restricted to 4 or 5 probes at a time. Similarly IHC is limited by the number of stains that can be attached and visualized, e.g., 3 or 4. 
         [0007]    These limitations mean that in practice it is possible to know the amount of various types of DNA, RNA and protein in a tissue in detail but not the precise location of those species or it is possible to know the location of a few species with high spatial accurately. 
         [0008]    Other techniques collect spatially oriented information from slides. Laser capture microdissection, for example, uses a laser to release a chosen section of the tissue, e.g. while observing the tissue on a slide under a microscope (with no cover slip). The released sample is captured in a vial, and the localized sample is tested using one of the methods mentioned above. This allows obtaining test information for a known location. While this is difficult at the sub cellular level, it is possible to select one or a few cells that are known to be part of a tumor. 
         [0009]    Laser capture microdissection has not been widely used because of its disadvantages. One is the cost and complexity of the equipment involved. Also, since the sample is collected after it has been fixed and possibly stained these processes may disrupt the target molecules and prevent some chemical methods from operating correctly. Also, since the size of the area sampled is inherently limited by the collection technique, it may be too small relative to the tumor that is to be characterized. 
       SUMMARY 
       [0010]    The present application describes using image analysis in conjunction with laser microdissection to automatically determine areas within the sample. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0011]    In the drawings: 
           [0012]      FIG. 1A-1E  show multiple slides sections; and 
           [0013]      FIG. 2  shows a composite slide section. 
       
    
    
     DETAILED DESCRIPTION 
       [0014]    When carrying out laser capture microdissection, one is faced with a tradeoff. One typically processes the unstained slides, to avoid effects from the staining and fixing of the slide portions. However, it is often difficult to determine items of interest (e.g. tumors) from the unstained slides within those sections. Therefore, it is very time consuming and labor intensive. Many laser microdissection users attempt to identify the areas of interest within the untreated slide. This adds to the difficulty of determining the area. 
         [0015]    The inventors recognize that usually when slides are taken, they are serial cut sections, cut from a block, about 4 microns apart, into a water bath. The sections are then pulled from the water bath, and may be in random locations on the slide. However, the serial sections have similar information. 
         [0016]    Multiple serial sections are obtained. One section, or more preferably plural sections, are stained using different staining techniques. Another section/slide is unstained. 
         [0017]    An interesting area is identified on one or multiple stained sections. For example,  FIG. 1A  illustrates a stained section  111 . Other techniques may be used, including manual drawing or automated image analysis to mark the interesting region. 
         [0018]    Shape analysis of the shapes, e.g.  106 , within slide  101  is then used to project one slide image  106  on top of another image  108 . These multiple serial sections are rotated and superimposed onto one another. The multiple stained sections can be rotated and superimposed on to an unstained section. The staining can be used to determine which regions are interesting. The determination can be automated, or it can be done remotely, for example by drawing on the screen. This avoids certain labor-intensive parts of the laser microdissection. The sections which are shown to be interesting by the stain are then translated into the unstained image. This can be used to form rules for guiding the laser by studying the stained sections, and then to use them on the unstained sections. 
         [0019]    The area determination and orientation can identify an area, and once identified, the outline or whole image is correlated with another area. A similarity measure can be carried out by cross correlation, which rotates and translates across every possible rotation and translation value, and finds similarity values at each relative orientation (e.g., using least mean squares measures). The closest match is used as a final match. This allows each tissue level feature to be accurately matched from a region on one slide to another slide. 
         [0020]      FIG. 1A-1E  illustrate an embodiment. A number of different sections are shown in  FIGS. 1A ,  1 B,  1 C,  1 D and  1 E. Each of these sections are serial sections from the same area. The section from  FIG. 1A  has a stained area  111  which is stained with a first stain, here H&amp;E.  FIG. 1C  shows another serial section  103  stained with a second stain, showing a second stained area  112 . Section slide  104  shows a third stain and a third stained area  113 . Slide  105  shows a fourth stain, and a fourth stained area  114 . 
         [0021]    Slide  102  is unstained. All of the stained areas are transposed and superimposed on the non-stained area  107 .  FIG. 2  illustrates a closeup view of the unstained slide  102 , in which all of the stained areas  111 ,  112 ,  113  and  114  are shown. Laser capture microdissection can be used for any of these areas. Each area has been projected onto the unstained slide. Area  115  is a projection of  112  onto area  107  taking into account translation and rotation between  108  and  107 . In a similar way,  116  is a projection of  111 ;  117  is a projection of  113 , and  118  is the intersection of the different stained regions. This allows a number of different stains to each be individually used on different slides. The system determines the translation and rotation between the areas, and uses that same translation and rotation to translate and rotate the slide. The intersection area may be used to identify, for example, areas of interest that are viewable only when stained with multiple stains. 
         [0022]    In the embodiment, the unstained slide is the one that is actually laser microdissected. In the embodiment, the unstained slide is between multiple stained slides. In this way, the slide that is microdissected is serially between stained slides, preferably in the middle of the sections. In this way, the dissected slide is between the other slides and forms a median of the other slides. 
         [0023]    The general structure and techniques, and more specific embodiments which can be used to effect different ways of carrying out the more general goals are described herein. 
         [0024]    Although only a few embodiments have been disclosed in detail above, other embodiments are possible and the inventors intend these to be encompassed within this specification. The specification describes specific examples to accomplish a more general goal that may be accomplished in another way. This disclosure is intended to be exemplary, and the claims are intended to cover any modification or alternative which might be predictable to a person having ordinary skill in the art. For example, other data formats, other kinds of slides, etc, may be used. 
         [0025]    The term serial means that the different sections are formed in series, but includes a situation where there are unused slides between the serially obtained sections. Also, the inventors intend that only those claims which use the words “means for” are intended to be interpreted under 35 USC 112, sixth paragraph. Moreover, no limitations from the specification are intended to be read into any claims, unless those limitations are expressly included in the claims. The computers that carry out the processing described herein may be any kind of computer, either general purpose, or some specific purpose computer such as a workstation. The computer may be an Intel (e.g., Pentium or Core 2 duo) or AMD based computer, running Windows XP or Linux, or may be a Macintosh computer. The computer may also be a handheld computer, such as a PDA, cellphone, or laptop. 
         [0026]    The programs may be written in C or Python, or Java, Brew or any other programming language. The programs may be resident on a storage medium, e.g., magnetic or optical, e.g. the computer hard drive, a removable disk or media such as a memory stick or SD media, wired or wireless network based or Bluetooth based Network Attached Storage (NAS), or other removable medium or other removable medium. The programs may also be run over a network, for example, with a server or other machine sending signals to the local machine, which allows the local machine to carry out the operations described herein. 
         [0027]    Where a specific numerical value is mentioned herein, it should be considered that the value may be increased or decreased by 20%, while still staying within the teachings of the present application, unless some different range is specifically mentioned. Where a specified logical sense is used, the opposite logical sense is also intended to be encompassed.