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Counting Cells in Sectioned Material: A Suite of Techniques, Tools, and Tips

Robert W. Williams1,  Christopher S.von Bartheld2,  Glenn D. Rosen3

1University of Tennessee Health Science Center, Memphis, Tennessee
2University of Nevada School of Medicine, Reno, Nevada
3Beth Israel Deaconess Medical Center, Boston, Massachusetts



Publication Name: 
Current Protocols in Neuroscience
Unit Number: 
UNIT 1.11
DOI: 
10.1002/0471142301.ns0111s24
Online Posting Date: 
November, 2003
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Glenn Rosen

Abstract

This unit presents protocols to obtain accurate estimates of cell density and cell number in sectioned material by using a light microscope. The “optical disector” or “3-D counting method” is described, followed by Abercrombie's less commonly used two-section comparison (TSC) method. These basic protocols are accompanied by four support protocols: one for celloidin embedding, which renders superb morphology, one for point counting, which is important for volume measurements and is almost always used in conjunction with the disector or 3-D counting, one for handling the potential problem of z-axis distortion and the consequences that this error can have on density estimates and sampling tactics when using the disector, and finally, one that provides a guide for calibrating and verifying estimates obtained by counting methods.

Keywords: stereology; optical disector; cell counting; counting box; bias; two-section comparison method; histology; celloidin; Nissl stain; Cavalieri's rule; volume estimation; z-axis compression; tissue section; differential shrinkage; systematic bias calibration; serial sections

     
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Table of Contents

  • Unit Introduction
  • Basic Protocol 1: 3-D Counting and the Optical Disector
  • Basic Protocol 2: Two-Section Comparison Method
  • Support Protocol 1: Celloidin Embedding and Cresyl Violet Staining
  • Support Protocol 2: Estimation of Regional Volume from Serial Sections Using Point Counting and Cavalieri's Rule
  • Support Protocol 3: Measurement of Differential Shrinkage or Compression in the Z-Axis of Tissue Sections
  • Support Protocol 4: Calibration of Counting Methods by a Limited and Simple 3-D Reconstruction of Serial Sections
  • Commentary
  • Literature Cited
  • Figures
  • Tables
     
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Materials

Basic Protocol 1: 3-D Counting and the Optical Disector

 Materials
  • Specimen: Sectioned material with a thickness preferably between 15- and 50-µm after processing (see Support Protocol 1; see Critical Parameters)
  • Immersion oil
  • Light microscope with oil immersion objective, preferably 63× or 100×, fitted for differential interference contrast (DIC) imaging (see Critical Parameters)
  • Equipment to accurately track movements of microscope stage (and tissue) in the z-axis: digital micrometer or rotary encoder (microcator) for direct readings from the fine-focus dial (Fig. 1.11.2; also see Critical Parameters)
  • Video system for microscope (recommended, although not essential for simple tasks where a camera lucida or drawing tube can be used; see Critical Parameters)
  • Video overlay hardware or software (see Critical Parameters)
  • Calibration slide (stage micrometer slides, 2 µm/division, or image analysis micrometer, Edmund Scientific; http://edmundoptics.com)

Basic Protocol 2: Two-Section Comparison Method

 Materials
  • Brain specimens
  • Microtome (see unit 1.1)
  • Microscope
  • Video overlay hardware or software (optional; see Critical Parameters)

Support Protocol 1: Celloidin Embedding and Cresyl Violet Staining

 Materials
  • Celloidin (Parlodion) strips (SPI Supplies; also available from Fisher)
  • 80% ethanol, 95%, and 100% (v/v) ethanol
  • Ethyl ether
  • Rodent brain specimens, fixed (unit 1.1; may be post-fixed in 10% formalin ³2 weeks to improve uniformity of processing)
  • 1:1 (v/v) absolute ethanol/ethyl ether
  • 0.5% cresyl violet: dissolve 1 g cresylecht violet (use only CellPoint Scientific, cat. no. IA396) in 200 ml distilled water; filter before initial use; can be reused up to 1 month
  • Rosin stock solution: Dissolve 35 g gum rosin (Sigma cat. no. R3755) in 100 ml of 100% ethanol
  • -terpineol (Fisher)
  • Xylenes
  • Permount mounting medium (e.g., Fisher)
  • Glass jar with tight-fitting screw-on lid (e.g., with hinged-glass lids used for canning fruit; make sure seals resist ether/alcohol)
  • Glass jars (or scintillation vials) for brain embedding
  • Plastic embedding boats (Thermo Shandon)
  • Wheaton dish (or any square glass container with lid)
  • Scalpel blades
  • Glass rod
  • Mounting blocks (25 × 25 × 21 mm; Thermo Shandon)
  • Sliding microtome (unit 1.1)
  • Glass petri dishes (110 × 15 mm)
  • Circular staining nets (Brain Research Laboratories; clear plastic cylinder divided into 6 or 8 compartments with fine plastic mesh bottom and open top; for details, see http://mbl.org/procedures/tissue_proc.html)
  • Glass microscope slides and coverslips
  • Additional reagents and equipment for cutting sections with a sliding microtome (unit 1.1)

Support Protocol 2: Estimation of Regional Volume from Serial Sections Using Point Counting and Cavalieri's Rule

 Materials
  • Serial sections (see Support Protocol 1; frozen or paraffin-embedded sections are also acceptable; see unit 1.1) mounted at intervals such that there are at least 5 to 7 sections containing the region of interest.
  • Light microscope with appropriate objectives
  • z-axis micrometer (see Fig. 1.11.2; also see Critical Parameters for discussion on equipment for tracking movement of microscope stage)
  • Video camera or photographic attachment for microscope (light stand with a macro lens attachment can sometimes be used)
  • Image-processing software: NIH Image, Adobe PhotoShop, Point Grid Macro, or a transparency

Support Protocol 3: Measurement of Differential Shrinkage or Compression in the Z-Axis of Tissue Sections

 Materials
  • 5 to 10 tissue sections on glass slides (prepared as for for optical disector analysis, 20 to 40 µm thick; see Basic Protocol 1, Support Protocol 1, and Critical Parameters)
  • Microscope with counting box (reticle grid in eyepiece or a video system) and a z-axis position encoder (microcator) for z-axis measurements (preferably with a digital read-out accurate for movements of less than 0.4 µm; see Critical Parameters)
  • Calculator or computer with spreadsheet program

Support Protocol 4: Calibration of Counting Methods by a Limited and Simple 3-D Reconstruction of Serial Sections

 Materials
  • 5 to 10 serial stained tissue sections on glass slides (prepared as for for disector or profile counting, 20 to 30 µm thick; see Basic Protocol 1, Support Protocol 1, and Critical Parameters)
  • Transmitted light microscope equipped with a camera lucida (drawing tube) or a video-imaging system and a high-quality monitor
  • Transparencies
  • Color markers (ultrafine “Sharpies”; e.g., red, black, and blue)
Looking for materials?  Suppliers Guide
     
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Figures

  • Figure 1.11.1
    (A) The unbiased method for counting cells in a 2-D plane using Gundersen's (1977) counting rules. Cells that cross into four shaded neighbors are not counted (cells 1, 8, 9, and 10). (B) The counting box as seen in perspective, as if from the lower right corner of panel A. The central counting box is surrounded by 26 similar boxes, although only 9 of these are illustrated. Cells that intrude into half of these 26 neighbors (e.g., cells 1, 8, 9, and 10; solid black transects) are excluded. The other four cells—3, 5, 7, and 13—only intrude into permitted neighbors and are counted. Surfaces that separate forbidden and permitted compartments are shaded. These forbidden surfaces extend outward without change in orientation as indicated by the arrows. Cells in Figure 1.11.1A that are entirely inside the box (e.g., 2, 11, 12, and 14), which are always counted, are not shown in Figure 1.11.1B. “C” is indicated as a common reference point.

    View Image
  • Figure 1.11.2
    A typical setup for 3-D counting. On the left side of the figure, a microscope is shown equipped with a shaft encoder (e.g., Hewlett-Packard HEDS-6000B-06) on the fine-focus control, or a digital length gauge (e.g., Heidenhain Metro-25 digital length gauge) is shown positioned over the stage. Only one of these devices is required. The z-axis control unit decodes and displays the vertical position of the stage with a resolution of 0.1 µm and generates high and low tones when the stage moves above or below the top and bottom sides of the counting box. The video mixing equipment includes a video camera, a video processor, a video mixer, and a television monitor. The last three items are now commonly integrated into one computer system.

    View Image
  • Figure 1.11.3
    Schematic view of a thick (25 µm) section from the side to show the z-axis (arrow). Cell nuclei and their centers (or nucleoli) are indicated and numbered consecutively as they would appear in focus when moving the focal plane from the top to the bottom surface of the tissue section. The resulting measurements and calculated data points can be tabulated as shown in Table 1.11.1.

    View Image
  • Figure 1.11.4
    Histograms showing the distribution of “centers” of neuronal nuclei through the extent of tissue sections. The number of neuronal nuclei with their percentiles from 0 to 100 is indicated as the percentage of total number. A uniform distribution throughout the tissue section would show 10% of the centers of nuclei in each of the 10 percentile groups (dashed line). When several groups of 100 or more objects are scored separately, error bars (such as standard error of the mean, SEM) can be calculated. (A) In this case a bimodal distribution is apparent, and the optical disector would render biased estimates if guard spaces were used. (B) In this case the distribution is largely uniform, and the use of guard spaces would not bias the estimates significantly.

    View Image
  • Figure 1.11.5
    The top of the figure shows three sections with particles as they would appear when collapsed in the z-axis of adjacent sections (1 to 3). Each particle that has its center within the section is numbered from 1 to 11 in the sequence, as they would appear when focusing from the top of section 1 to the bottom of section 3. As explained in the text, for each section, three transparencies should be prepared on the camera lucida so that all particles intersecting the top surface will be drawn in red, particles not intersecting either surface in black, and particles intersecting the bottom surface in blue. The bottom of the figure shows the microscope view of section number 1, with focus on the bottom surface (to be drawn in blue), and section number 2, with focus on the top surface (to be drawn in red). Landmarks (such as blood vessels or other prominent structures) should be used to unambiguously identify fragments of cells or cell nuclei in adjacent surfaces. The data collection for the three sections is shown in Table 1.11.3.

    View Image

Literature Cited

Literature Cited
    Abercrombie, M. 1946. Estimation of nuclear populations from microtome sections. Anat. Rec. 94:239-247.
    Airey, D.C., Lu, L., and Williams, R.W. 2001. Genetic control of the mouse cerebellum: Identification of quantitative trait loci modulating size and architecture. J. Neurosci. 21:5099-5109.
    Benes, F.M. and Lange, N. 2001. Two-dimensional versus three-dimensional cell counting: A practical perspective. Trends Neurosci. 24:11-17.
    Boddeke, F.R., van Vliet, L.J., and Young, I.T. 1997. Calibration of the automated z-axis of a microscope using focus functions. J. Microsc. 186:270-274.
    Clarke, P.G.H. and Oppenheim, R.W. 1995. Neuron death in vertebrate development: In vivo methods. Methods Cell Biol. 46:277-321.
    Coggeshall, R.E. 1992. A consideration of neural counting methods. Trends Neurosci. 15:9-13.
    Coggeshall, R.E., La Forte, R., and Klein, C.M. 1990. Calibration of methods for determining numbers of dorsal root ganglion cells. J. Neurosci. Methods 35:187-194.
    Coggeshall, R.E. and Lekan, H.A. 1996. Methods for determining numbers of cells and synapses: A case for more uniform standards of review. J. Comp. Neurol. 364:6-15.
    Cruz-Orive, L.M. 1994. Towards a more objective biology. Neurobiol. Aging 15:377-378.
    Dorph-Petersen, K.A., Nyengaard, J.R., and Gundersen, H.J.G. 2001. Tissue shrinkage and unbiased stereological estimation of particle number and size. J. Microsc. 204:232-246.
    Galaburda, A.M. and Pandya, D.N. 1983. The intrinsic architectonic and connectional organization of the superior temporal region of the rhesus monkey. J. Comp. Neurol. 221:169-184.
    Gardella, D., Hatton, W.J., Rind, H.B., Rosen, G.D., and von Bartheld, C.S. 2003. Differential tissue shrinkage and compression in the z-axis: Implications for optical disector counting in vibratome-, plastic- and cryosections. J Neurosci. Methods 124:45-59.
    Geuna, S. 2000. Appreciating the difference between design-based and model-based sampling strategies in quantitative morphology of the nervous system. J. Comp. Neurol. 427:333-339.
    Gould, S.J. 1996. "The mismeasure of man". W.W. Norton & Co. New York.
    Guillery, R.W. 2002. On counting and counting errors. J. Comp. Neurol. 447:1-7.
    Guillery, R.W. and Herrup, K. 1997. Quantification without pontification: Choosing a method for counting objects in sectioned tissues. J. Comp. Neurol. 386:2-7.
    Gundersen, H.J.G. 1977. Notes on the estimation of the numerical density of arbitrary profiles: The edge effect. J. Micros. 111:21-23.
    Gundersen, H.J.G. and Jensen. E.B. 1987. The efficiency of systematic sampling in stereology and its prediction. J. Micros. 147:229-263.
    Gundersen, H.J.G., Bagger, P., Bendtsen, T.F., Evans, S.M., Korbo, L., Marcussen, N., Ller, A., Nielsen, K., Nyengaard, J.R., Pakkenberrg, P., Rensen, F.B., Vesterby, A., and West, M.J. 1988. The new stereological tools: Disector, fractionator, nucleator, and point sampled intercepts and their use in pathological research and diagnosis. Acta Path Microbiol. Immunol. Scand. 96:857-881.
    Hatton, W.J. and von Bartheld C.S. 1999. Analysis of cell death in the trochlear nucleus of chick embryos: Calibration of the optical disector counting technique reveals systematic bias. J. Comp. Neurol. 409:169-186.
    Hedreen, J.C. 1998a. Lost caps in histological counting methods. Anat. Rec. 250:366-372.
    Hedreen, J.C. 1998b. What was wrong with the Abercrombie and empirical cell counting methods A review. Anat. Rec. 250:373-380.
    Howard, C.V. and Reed, M.G. 1998. "Unbiased stereology. Three-Dimensional Measurement in Microscopy". Springer, New York.
    Kevles, D.J. 1985. "In the Name of Eugenics: Genetics and the Uses of Human Heredity", 1st Edition. Alfred A. Knopf, New York.
    Lia, B., Williams, R.W., and Chalupa, L.M. 1987. Formation of retinal ganglion cell topography during prenatal development. Science 236:848–851.
    Mayhew, T.M. and Gundersen, H.J. 1996. “If you assume, you can make an ass out of u and me”: A decade of the disector for stereological counting of particles in 3D space. J. Anat. 188:1-15.
    Mosteller, F. and Tukey, J.W. 1977. "Data Analysis and Regression: A Second Course in Statistics". Addison-Wesley, Reading Mass.
    Popken, G.J. and Farel, P.B. 1996. Reliability and validity of the physical disector method for estimating neuron number. J. Neurobiol. 31:166-174.
    Popken, G.J. and Farel, P.B. 1997. Sensory neuron number in neonatal and adult rats estimated by means of stereologic and profile-based methods. J. Comp. Neurol. 386:8-15.
    Pover, C.M. and Coggeshall, R.E. 1991. Verification of the disector method for counting neurons, with comments on the empirical method. Anat. Rec. 231:573-578.
    Rosen, G.D. and Harry, J.D. 1990. Brain volume estimation from serial section measurements: A comparison of methodologies. J. Neurosci. Methods 35:115-124.
    Rosen, G.D. and Williams, R.W. 2001. Complex trait analysis of the mouse striatum: Independent QTLs modulate volume and neuron number. Biomed. Central Neurosci. 2:5.
    Rosen, G.D., Sherman, G.F., Emsbo, K., Mehler, C., and Galaburda, A.M. 1990. The midsagittal area of the corpus callosum and total neocortical volume differ in three inbred strains of mice. Exp. Neurol. 107:271-276.
    Saper, C.B. 1999. Unbiased stereology: Three-dimensional measurement in microscopy. Book review. Trends Neurosci. 22:94-95.
    Schmitz, C., Korr, H., and Heinsen, H. 1999. Design-based counting techniques: The real problems. Trends Neurosci. 22:345-346.
    Sterio, D.C. 1984. The unbiased estimation of number and sizes of arbitrary particles using the disector. J. Microsc. 134:127-136.
    von Bartheld, C.S. 1999. Systematic bias in an “unbiased” neuronal counting technique. Anat Rec. 257:119-120.
    von Bartheld, C.S. 2001. Comparison of 2-D and 3-D counting: The need for calibration and common sense. Trends Neurosci. 24:504-506.
    von Bartheld, C.S. 2002. Counting particles in tissue sections: Choices of methods and importance of calibration to minimize biases. Histol. Histopathol. 17:639-648.
    West, M.J. 1999. Stereological methods for estimating the total number of neurons and synapses: Issues of precision and bias. Trends Neurosci. 22:51-61.
    Williams, R.W. and Rakic, P. 1988. Three-dimensional counting: An accurate and direct method to estimate numbers of cells in sectioned material. J. Comp. Neurol. 278:344-353.
    Williams, R.W., Strom, R.C., Rice, D.S., and Goldowitz, D. 1996. Genetic and environmental control of retinal ganglion cell number in mice. J. Neurosci. 16:719-7205.
    Yakovlev, P.I. 1970. Whole-brain serial sections. In Neuropathology: Methods, Diagnosis (C.G. Tedeschi, ed.), pp 371-378. Little, Brown, and Co., Boston.
 Key References
 Differential shrinkage or compression in the z-axis
    Howard, C.V. and Reed, M.G. 1998. "Unbiased Stereology: Three-Dimensional Measurement in Microscopy", p. 246. Springer, New York.

Provides a useful review of the history, introduction, concept and protocols of the optical disector.

 Calibration by 3-D reconstruction
    Coggeshall et al. 1990. See above.

Provides an example of how to calibrate counting methods by a detailed 3-dimensional reconstruction of serial sections.

    Hatton and von Bartheld, 1999. See above.

Provides evidence for potential bias in the optical disector due to differential tissue compression or shrinkage. The authors used basically the same method provided in this unit to evaluate z-axis distortion of sections.

    von Bartheld, 2002. See above.

This review provides an update of recent arguments for calibration of counting methods and practical recommendations, including advantages and disadvantages of current counting methods.

 Internet Resources
 The optical disector and two-section comparison methods
    Many of these and other web resources can be quickly found using a search engine and search phrases: stereology, disector, and 3-D counting
    http://nervenet.org/papers/AberFP.html

A link to the original text of Abercrombie (1946) with annotation by R. W. Williams. Covers both the TSC method and the more well known method that involves the application of the Abercrombie correction factor.

    http://nervenet.org/main/papers.html#Papers2

The authors of this unit have provided Web access to an updated version of the 1988 paper by Williams and Rakic on the http://nervenet site. This Web edition incorporates corrections and additions suggested by Drs. Rakic, Gundersen, Howard, and von Bartheld.

    http://www.biomed2.man.ac.uk/ns/id/lecnte/Disector.html

Notes on the use of the disector with a CNS perspective.

    http://nervenet.org/mbl/mbl_main/mbl_movies.html

A short video clip as examples of the sorts of images that are used for generating cell counts.

    http://nervenet.org/mbl/iscope/aboutiscope.html

The second Internet resource is a Web-interfaced research-grade microscope fit with differential interference contrast optics that can be used interactively to generate one's own cell counts. The Internet microscope interface runs in a standard Web browser on one's local computer and controls the microscope in in the authors' laboratory, providing an updated series of video images.

    http://nervenet.org/netpapers/Rosen/Cav90/Caval.html

A link to a paper by Rosen and Harry (1990) on estimating the volume of parts of the brain from sectioned material.

    http://disector.com

A link to Peter Mouton's useful and informative Stereology Resource Center site. You can join the stereology LISTSERV and find out about upcoming courses in stereology.

    http://micro.magnet.fsu.edu/primer/

A superb microscopy site with a fine primer in optical microscopy at Florida State University. See the chapter on DIC optics.

    http://www.stereologysociety.org/

Web site of the International Society for Stereology.

    http://2spi.com/catalog/richardson/richardson1.html

One of several sources for calibration slides.

 Celloidin embedding and cresyl violet staining
    http://brainmuseum.org/

A superb collection of over 100 species of mammals that have been processed in celloidin. Images of selected sections can be downloaded.

    http://www.mbl.org

A collection of over 1500 celloidin-embedded mouse brains from over 120 strains. The site includes a number of mouse brain atlases, an Internet microscope system, and a variety of resources of interest to neurogeneticists. A detailed protocol of the specific steps used to create this resource can be found at http://www.mbl.org/tutorials/MBLTrainingManual/index.html

 Point counting and Cavalieri's rule
    http://mbl.org/procedures/pointcounting.html

A point counting macro for NIH Image written by John Capra.

    http://simon.bio.uva.nl/object-image.html

Object Image: a modified version of NIH Image that includes point counting.

    http://rsb.info.nih.gov/ij/

Web site of ImageJ: Wayne Rasbands's Java-based incarnation of NIH Image.

    http://nervenet.org/videoscribbler/vscrib.html

Videoscribbler: a live video overlay with built-in points (but manual counting) written by John Capra.

     
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