J Forensic Sci, 2012 doi: 10.1111/j.1556-4029.2012.02195.x Available online at: onlinelibrary.wiley.com
TECHNICAL NOTE ANTHROPOLOGY
Marissa C. Stewart,1 M.A.; Lara E. McCormick,1 M.A.; Jesse R. Goliath,1 M.A.; Paul W. Sciulli,1 Ph.D.; and Sam D. Stout,1 Ph.D.
A Comparison of Histomorphometric Data Collection Methods*
ABSTRACT: Although many variables that skeletal biologists examine have been standardized, the actual techniques used to collect these data from bone thin sections vary. This project compares different methods of obtaining data (relative cortical area values) for histomorphometric research. One visual and three digital methods of histomorphometric data collection are compared: (i) Merz microscopic eyepiece counting reticule, (ii) flatbed scanner, (iii) overlaying multiple images of a thin section, and (iv) digital SLR camera with macro settings. The discussion includes a comparison of usability factors such as cost, time, user-experience, and ease-of-use, which vary for each method. Values from the different methods are compared using ANOVA tests to evaluate inter-method, inter-observer, and intra-observer variability. Intra-observer error was greater for the microscopic method, although the error values are concomitant with experience. We found no statistically significant differences between the four methods examined, but certain caveats must be addressed when these methods are used. KEYWORDS: forensic science, forensic anthropology, skeletal biology, histomorphometry, histology, bone
Skeletal histomorphometry is the microscopic study of the properties, shapes, and measurements of bone tissue. In forensic anthropology, histomorphometry is most often used in the microscopic estimation of age of a decedent, although its wider focus includes examination of pathological conditions, activity levels, and overall health and nutrition (1–7). Although many of the variables skeletal biologists examine have been standardized (8), the actual methods used to collect data from thin sections of bone vary by researcher and institution. Standardization of some of the variables used (e.g., intact osteon, fragmentary osteon) is only now being addressed. This study evaluates the comparability, precision, and accuracy of four histomorphometric methods. In light of the 1993 Daubert and 1999 Kumho tire rulings, it has become increasingly important to validate methods that may be used in a forensic context (9,10). However, it is also important to examine the methods by which researchers collect data to ensure a measure of certainty if one is using a different histomorphometric technique than was originally proposed. This study examined relative cortical area, a variable within cortical bone. Cortical bone is more commonly used than trabecular bone in anthropological research because of its rigid and durable nature. Anthropologists use cortical bone to provide information on activity patterns, health and nutritional status, and age (1–7). Relative cortical area is cortical area (the amount of cortical bone that is present in the cross-section) divided by total area (the bone that is surrounded by the outer perimeter, including the marrow cavity) (5,7,11). Relative cortical area is a cross-sectional geometric variable used in anthropological research and methods such as histological age estimation (7). 1 Department of Anthropology, The Ohio State University, 4034 Smith Laboratory, 174 West 18th Avenue, Columbus, OH 43210. *Presented at the Annual Meeting of the American Association of Physical Anthropology, April 13-16, 2011, in Minneapolis, MN. Received 28 June 2011; and in revised form 30 Sept. 2011; accepted 9 Oct. 2011.
2012 American Academy of Forensic Sciences
The purpose of this study was to examine whether different procedures for obtaining and examining images in the microscopic analysis of bone produced comparable results. This study compared the results of four methods; three of which are commonly used by histomorphometric researchers, and one that has been recently developed. All methods had to be calibrated before the measurements were obtained. Calibration techniques are discussed later. The first method requires the use of a reticule imprinted with a grid fitted into the eyepiece of a microscope, hereafter referred to as the ‘‘point count method.’’ This method has been used in research contexts with varying types of grids (7,12– 15), and it was more commonly used prior to the availability of imaging software. Two of the methods requiring image software have been used previously: using a flatbed scanner (16,17) and taking overlapping images using imaging software and compiling them with Adobe Photoshop (Adobe Systems Incorporated, San Jose, CA) (18). The method involving the use of a digital SLR camera with extension tubes has been recently developed. Materials and Methods Ten histological slides of human rib sections were randomly selected from a cadaver population and examined to determine the relative cortical area. These rib samples are derived from remains interred in the Washington Park Cemetery in St. Louis, MO, and made available during relocation operations under the discretion of the Missouri Department of Natural Resources. These slides were prepared using standard histological preparation techniques (7,19,20). These samples were examined using the four methods to determine whether there were discernible differences among methods, researchers, and subsequent readings by each of the three researchers (the first three authors) resulting in a total of 240 measurements. 1
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The statistical analyses were performed using the SAS 9.2 program (SAS Institute Inc., Cary, NC). The relative cortical area values from the different methods and observers were compared using two-way fixed-factor analyses of variance (ANOVAs). Intraand inter-observer error values were determined by calculating the root mean squared error value from ANOVAs.
Bethesda, MD) (Fig. 2). The flatbed scanner used to capture the images was an EPSON Perfection 4870 Photo scanner (Seiko Epson Corporation, Long Beach, CA). The software was calibrated by determining the pixel count per millimeter for the scanner. Cortical area was calculated by subtracting the endosteal area from the total area. Relative cortical area was determined by dividing the cortical area value by the total area value.
Method 1: Point Count Method For this method, a Merz eyepiece counting reticule was inserted into the eyepiece of an Olympus CX41 microscope (Olympus Corporation, Tokyo, Japan). The slides were examined using 100· magnifications, (a 10· objective lens with a 10· eyepiece). The Merz counting reticule superimposes a grid onto the section of the slide being examined providing a way to calculate the area of a bone (Fig. 1) (21,22). The reticule is a grid of undulating lines with 36 hash-marks positioned in a 6 · 6 square. When the grid is imposed over a section of bone, a hash-mark that is positioned over the bone is considered a ‘‘hit.’’ Every field of the slide was read by the researchers with a visual landmark selected in each field to avoid overlap when the microscope field was moved. The counting reticule was calibrated with the use of a stage micrometer (Olympus Objective Micrometer) which defines the distance between two hash-marks as they appear superimposed over the section. The grid enables the researcher to obtain the total area of a section by determining the number of hash-marks falling on bone cortex and multiplying by the squared calibrated distance between hash-marks. Each of the researchers computed the number of hits that were present in the cortical area of each entire rib section as well as the total area (including the medullary cavity). Relative cortical area was then determined by dividing the cortical hits by the total area hits (7).
Method 3: Photo-Merging Method In this method, a Spot InsightTM QE Color 4.2.1 camera (SPOT Imaging Solutions, Sterling Heights, MI) attached to an Olympus BX51 microscope and interfaced with a computer was used to take overlapping micrographs of each slide. The micrographs were calibrated by determining the pixel count for a known distance. It was necessary to produce 15–30 images per slide to image the entire cross-section of the rib at 100· magnification. The margins of each field were widened to include details from the surrounding fields. Once sufficient images from each slide specimen were captured, the photos were then merged using Adobe Photoshop (Fig. 3). The Adobe Photoshop program is able to merge the photos based on identifying landmarks, color hue, and shape. The program then merges the images based on the overlapping portions on the edges of the fields. After the image was completely merged, relative cortical area was calculated using ImageJ software in the same manner as the flatbed scanner.
Method 2: Flatbed Scanner Method The use of the flatbed scanner involved scanning the microscopic slide and using the digital image to obtain measurements with ImageJ image analysis software (U.S. National Institutes of Health,
FIG. 2—A rib captured using the flatbed scanner method of image capture. The borders of the rib are clear, but the details of the cortical area are not visible.
FIG. 1—The Merz counting reticule on an image of a rib. This image shows the grid that was used in the collection of relative cortical area values for the point count method. The intersection points, or hits, are the dash marks that appear on the grid.
FIG. 3—A rib captured using the photo-merging method. The multiple overlapping individual images are visible in this figure.
STEWART ET AL. • COMPARISON OF HISTOMORPHOMETRIC METHODS
Method 4: Digital SLR Camera Method This method utilized a Nikon D5000 camera with a Nikon 18–55 mm lens, with a range of apertures from F3.5 to 5.6 (Nikon Corporation, Tokyo, Japan). Extension tubes were adopted for this study to increase the image magnification without adding additional glass. The length of the extension tubes and the lens focus was adjusted for each specimen to ensure the best quality image possible. A special photographic set-up was designed to provide a clear imaging surface for the specimen with adequate light and contrast to capture the images. A metric ruler was included in each image so that the images could be calibrated (Fig. 4). Once the images were digitally captured, relative cortical area values were then measured using ImageJ software. Results A two-way fixed-factor ANOVA was performed to compare the results of the four methods and the values for each slide specimen. The two-way ANOVA test examined the effects of the different observers and methods on the relative cortical area values; it also examined the interactive effect of these two factors (23). Relative cortical area results for three of the 10 rib samples demonstrated a significant interaction with the method used (Table 1). As the effects of the methods and the observers on the relative cortical area value readings cannot be isolated, the results for these three
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samples were discounted. When relative cortical areas were compared for the remaining seven rib samples, two slide specimens demonstrated a significant difference in the values generated using each of the four methods. These results suggest inter-method variability in the relative cortical area values measured. There was only a single slide specimen that demonstrated a significant effect of the researcher performing the data collection, suggesting that the researcher significantly affected the relative cortical area values for that slide specimen. Relative cortical areas for only one rib sample demonstrated a significant observer effect on relative cortical area values. Intra-observer error was determined for the three participants in the study. For all methods, one set of measurements was calculated by each observer with a 4-month period elapsing before the second reading was conducted. The length of time between the two readings was designed to ensure that the observers would not be influenced by their earlier measurements. Intra-observer measurement errors were determined using the root mean squared error values from an ANOVA procedure for each observer and for each method using the two sets of measurements taken by each observer (Table 2). The current study attempted to determine the most reliable and precise method for measuring histomorphometric variables, specifically relative cortical area. Once the interactions between methods and observers were examined, the complete relative cortical area values from each method were compared (Table 3). When examining the data, a number of discrepant readings were identified. It was proposed that these discrepant values may be skewing the mean values toward the more inconsistent methods. Fourteen of the 240 measurements were identified as not matching the rest of the values for the slide specimen by an outside and independent observer. These outliers were determined to be the result of researcher error (either data entry or calibration errors) and were removed from the subsequent analysis. Once more, the four methods were compared, and from the analysis, it was determined that there are no significant differences in the means and standard deviations produced by any of the methods (Table 4). Discussion Although no significant difference was observed among relative cortical areas determined using the four different methods, the point
FIG. 4—A rib captured using the digital SLR camera method. This is a single image that was captured using extension tubes and a special photographic set-up. The ticks of the ruler represent 1 mm. TABLE 1—Example of sample results from two-way fixed-factor ANOVA tests. Specimen
Source
DF
SSQ
MSQ
F-value
p>F
821706A
Cells (Model) Person Method Interaction Error Total
11
0.08702131
0.00791103
6.08
0.0021
2 3 6 12 23
0.01825421 0.03191393 0.03685317 0.01562669 0.10264801
0.00912711 0.01062798 0.00614220 0.00130222 –
7.01 8.17 4.72 – –
0.0096 0.0031 0.0109* – –
This represents an example of the data produced by the two-way fixedfactor ANOVA tests for the 10 slide specimens in the study. The data marked with the asterisk (*)indicates a slide specimen that demonstrated a significant interaction between the method used and the researcher performing the reading. As these interactions were significant, the slide specimen had to be discounted.
TABLE 2—Intra-observer error results for relative cortical area values. Observer
Scans
Photos
Photo-Merged
Point Count
Averages
1 2 3 Averages
0.012894 0.020996 0.030510 0.021467
0.008968 0.069933 0.013105 0.030669
0.010550 0.015592 0.008440 0.011527
0.014246 0.009949 0.126875 0.050357
0.011665 0.029118 0.044733 0.028505
TABLE 3—Means and standard deviations for relative cortical area values. Methods Scans Photos Photo-merged Point count All methods
N
Mean
Std Deviation
60 60 60 60 240
0.48526038 0.45551065 0.44917683 0.48868789 0.46965894 (xc )*
0.10952582 0.11368571 0.11691183 0.14808026 0.12347792
*The xc represents the mean of all relative cortical area values for all methods in the study.
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TABLE 4—Means and standard deviations for corrected relative cortical area values. Methods Scans Photos Photo-merged Point count All methods
N
Mean
Std Deviation
57 59 60 51 226
0.49301436 0.45267151 0.44917683 0.46333784 0.46222839 (xc )*
0.10653135 0.11249576 0.11691183 0.11930968 0.11328271
*The xc represents the mean of all corrected relative cortical area values for all methods in the study (once the identified outliers have been removed). This value is the approximated mean for the data.
count method produces values most similar to the determined xc (c. mean value, see Table 4). The mean values of the digital photo and photo-merged methods are slightly further from the xc than the point count method, but are relatively close when compared with the scanning method. The scanning method mean is the least similar to the xc , suggesting it to be the least accurate of the four methods. It is important to note that the accuracy of these methods is impossible to determine because the true relative cortical area value is not known; all observations are merely approximations of the true value. The results of this study are not definitive, but are a reasonable approximation of the accuracy of the methods. The precision of the different methods is determined by comparing the standard deviation values of the data as a measure of how they cluster around the mean value (Table 4). The scanning method appears to be the most precise method of collecting data. The other three methods (the point count, photo, and photo-merged method) are all comparable in terms of their precision. The amount of intra-observer error varies between the different methods and between the different observers; however, the error values are relatively small (Table 2). It is apparent that one of the observers produced variable results for the point count method. This discrepancy between the two subsequent point count readings likely represents a lack of previous histomorphometric experience. Therefore, for the point count method, experience and knowledge is a beneficial asset when examining slides and determining crosssectional properties. For the other three methods examined, there is no discernible pattern affecting the intra-observer error values. It was concluded that all four methods tested can produce relatively precise and comparable results; however, some methods are more dependent upon researcher knowledge and experience than others. Even though the point count method was determined to be the closest to the approximated mean, the measurement of variables using the microscope requires extensive time and experience to ensure the most accurate results. Other methods do not require the same amount of technical expertise. Once the images are captured using the scanning, photo-merging, and digital SLR camera methods, the collection of data is relatively straightforward. While an eyepiece counting reticule is a widely available and relatively inexpensive method, it does not allow for image retention after variable collection. In contrast, the other methods allow the researcher to retain images for presentation, comparison, and further study. The point count method offered the researcher enhanced magnification of the slides and clarity of the bone tissue. Enhanced visibility of the slide allows for better differentiation and identification of the cortical bone boundaries. The scanning method produced images of varying quality and resolution, not conducive to accurate histomorphometric analysis, despite the high precision. The photo-merged and digital SLR camera methods are both precise; however, the digital SLR camera method required less time to capture a high-quality image. It requires the use of a single image in the measurement process, whereas the photo-merging
method required the capturing of a number of different images before a usable image was completed. The sample ribs analyzed required 15–30 separate images before a completed photo-merged image could be formed. A larger bone, like the femur, would require many more images and would be time intensive. Additionally, the photo-merging method relies on the accuracy of the Adobe Photoshop software to compile the images correctly and the software appeared to have some difficulty identifying trabecular structure in the medullary cavity. The scanning method is the most time efficient and precise method; however, it was found to produce values furthest from the xc value. When investigating histomorphometric studies conducted at different laboratories and institutions, we observed varying methods for data collection. This study represents the first comparison of these various methods to determine their precision and comparability in the data they produce. It was determined that when collecting relative cortical area data, researchers can defend the use of any of the four methods examined. It is important to be able to explain the research methods used in regards to resources and equipment available. Each method demonstrated a selection of benefits and drawbacks varying from the expense of the equipment to the time required for preparation and data collection. Despite potential drawbacks of each method, in the hands of an experienced and well-trained researcher, each method can provide meaningful and justifiable results. Acknowledgments The authors would like to thank those individuals that read drafts of this paper, Dr. Jules Angel for assistance with digital photography, Amanda Agnew for assistance with photo-merging images, Brittney Blankenship for slide selection, and all other assistants in the project. References 1. Cho H, Stout SD, Madsen RW, Streeter MA. Population-specific histological age estimating method: a model for known African-American and European-American skeletal remains. J Forensic Sci 2002;47:12–18. 2. Larsen CS. Bioarchaeology: interpreting behavior from the human skeleton. Cambridge, UK: Cambridge University Press, 1997. 3. Ruff CB, Hayes WC. Cross-sectional geometry of Pecos Pueblos femora and tibiae—a biomechanical investigation: I. Method and general patterns of variation. Am J Phys Anthropol 1983;60:359–81. 4. Ruff CB, Hayes WC. Cross-sectional geometry of Pecos Pueblos femora and tibiae—a biomechanical investigation: II. Sex, age, and side differences. Am J Phys Anthropol 1983;60:383–400. 5. Ruff CB. Biomechanical analyses of archaeological human skeletons. In: Katzenberg M, Saunders SR, editors. Biological anthropology of the human skeleton, 2nd rev. edn. New York, NY: Wiley-Liss, 2008;183– 206. 6. Stout SD, Lueck R. Bone remodeling rates and skeletal maturation in three archaeological skeletal populations. Am J Phys Anthropol 1995;98:161–71. 7. Stout SD, Paine RR. Histological age estimation using rib and clavicle. Am J Phys Anthropol 1992;87:111–15. 8. Parfitt AM, Drezner MK, Glorieux FH, Kanis JA, Malluche H, Meunier PJ, et al. Bone histomorphometry: standardization of nomenclature, symbols and units: report of the ASBMR histomorphometry nomenclature committee. J Bone Miner Res 1987;2:595–610. 9. Daubert v. Merrell Dow Pharmaceuticals, Inc. (92-102), 509 U.S. 579 (1993). 10. Kumho Tire Company, Ltd. v. Carmichael, 526 U.S. 137 (1999). 11. Cho H, Stout SD, Bishop TA. Cortical bone remodeling rates in a sample of African American and European American descent groups from the American Midwest: comparisons of age and sex in ribs. Am J Phys Anthropol 2006;130:214–26. 12. Epker BN, Frost HM. The parabolic index: a proposed index of the degree of osteoporosis in ribs. J Gerontol 1964;19:469–73.
STEWART ET AL. • COMPARISON OF HISTOMORPHOMETRIC METHODS 13. Epker BN, Frost HM. A histological study of remodeling at the periosteal, haversian canal, cortical endosteal and trabecular endosteal surfaces in human rib. Anat Rec 1965;152:129–35. 14. Sedlin ED, Frost HM, Villanueva AR. Variations in cross-section area of rib cortex with age. J Gerontol 1963;18:9–13. 15. Stout SD. The use of bone histomorphometry in skeletal identification: the case of Francisco Pizarro. J Forensic Sci 1986;31:296–300. 16. Cho H, Stout SD, Bishop TA. Cortical bone remodeling rates in a sample of African American and European American descent groups from the American Midwest: comparisons of age and sex in ribs. Am J Phys Anthropol 2006;130:214–26. 17. Peck JJ, Stout SD. Intraskeletal variability in bone mass. Am J Phys Anthropol 2007;132:89–97. 18. Agnew AM, Stout SD. Brief communication: reevaluating osteoporosis in human ribs: the role of intracortical porosity. Am J Phys Anthropol 2012; e-pub ahead of print. DOI: 10.1002/ajpa.22048. 19. Frost HM. Preparation of thin undecalcified bone sections by rapid manual method. Stain Technol 1958;34:273–7. 20. Robling AG, Stout SD. Histomorphometry of human cortical bone: applications to age estimations. In: Katzenberg M, Saunders SR, editors.
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Biological anthropology of the human skeleton. New York, NY: WileyLiss, 2008;149–82. 21. Anderson C. Manual for the examination of bone. Boca Raton, FL: CRC Press, 1982. 22. Kimmel DB, Jee WSS. Measurements of area, perimeter and distance: details of data collection in bone histomorphometry. In: Recker RR, editor. Bone histomorphometry: techniques and interpretation. Boca Raton, FL: CRC Press, 1983;89–108. 23. Zar JH. Biostatistical analysis, 5th rev. edn. Upper Saddle River, NJ: Pearson Prentice Hall, 2010. Additional information and reprint requests: Marissa Stewart, M.A. Graduate Teaching Associate Department of Anthropology The Ohio State University 4034 Smith Laboratory 174 West 18th Avenue Columbus, OH 43210 E-mail:
[email protected]
