Age at Death Evaluation by Tooth Cementum Annulation

Figure 3. Tooth embedded in a epoxide resin bloc (Biodur E12) and fixed in a microtome saw (Leica 1600). The tooth crown of the sample was cut off.

Figure 4. (A) LocalizaFon of slices. Tooth-‐scheme (lateral view). 8-‐10 sec<on were taken (B) Thin secFons on a slide.

Age at death evaluaFon by tooth cementum annulaFon (TCA) – a soLware for an automated line counFng (Auto-‐TCA) Andrea Czermak1, Adrian Czermak2, Gisela Grupe3, Hartmut Ernst2 1 Ins<tut für Archäologische WissenschaMen, Frühgeschichtliche Archäologie und Archäologie des MiPelalters, Albert-‐Ludwigs-‐Universität Freiburg, Germany; 2 LMU Biozentrum, Ludwig Maximilians Universität München, Germany; 3 Faculty of Computer Sciences, University of Applied Science Rosenheim, Germany;

This research work was supported by the Hanns-‐Seidl-‐S<Mung, Munich, Germany (PhD grant to Andrea Czermak)

Acknowledgement

Conclusions

Figure 13. Example for Auto-‐TCA counFng results of the incremental lines of individuals in different age groups (morphologically determined). The soMware was tested on samples of individuals with unknown age-‐at-‐death from historical excava<ons. The coun<ng results of one slice show a Gaussian distribu<on curve and several coun<ng on different spots at one slice largely coincide. The younger an individual, the slender the Gaussian curve and the definite the result (A). Proceeding (morphologically determined) age leads to a flat curve and more scaPering results (B). In higher age groups differences between slices near the tooth crown and slices from the middle of the root become clearly visible (C). The older one individual, the longer can the distance from the curves of different slices become (D) (Czermak 2006, 2012).

A valid age at death estimation is required in historical and forensic anthropology. Tooth cementum annulation (TCA) provides a technique for age-at-death estimation of adult individuals. The approach uses light microscopic images acquired from tooth root cross sections. Age is estimated by counting the number of visible tooth cementum incremental lines and adding the result to the assumed age of tooth eruption. Manual line counting, however, is time consuming, potentially subjective and the number of individual counts is insufficient for quantitative evaluations. Here a custom-made software (AutoTCA) is presented that allows automated evaluation of TCA images. It involves Fourier filtering, ‘‘line-by-line’’ scanning and the counting of grey scale intensity peaks within a selected region of interest (ROI). Each scanning process of a particular ROI yields up to 400 counts, thus minimizing the potential error induced by manual line counting. This simple and time saving program can substitute manual counting and provides reproducibly consistent and user independent unbiased results. Reliability of the results, however, still depends largely on the state of preservation of the analysed material, the preparation, the choice of the thin section and image quality, underlining the need to standardize these factors.

Principle of tooth cementum annulaFon (TCA)

References

Figure 11. Power spectrum of the rotated ROI. (A) Ver<cally orientated incremental lines are grouped near the central horizontal line of the power spectrum. In contrast, non linear structures or linear structures orientated in different angles to the incremental lines in the original image (e.g. saw blade marks) are represented by pixels that are more distant from the horizontal line. (B) To completely eliminate interfering ar<facts a point symmetric masked was applied an angular filter (20°) was used. (C) Masked power spectrum of rotated ROI.

Figure 9. ScaWerplot aLer 11x11 Gauss low-‐pass filter and DFFT. The ROI was segmented into equal rectangles (128 pixels x length of ROI). Each segment was rotated to a horizontal posi<on, using the outer dark line as a reference. Applica<on of Gauss low-‐pass filter and Fourier transforma<on (DFFT: discrete fast Fourier transforma<on). (A) The scaPer plot shows a preferred direc<on, which is extracted by fidng a straight line. (B) This line determines the ideal rota<on angle

Single counts Applied data

1 tooth ≈ 8000 each tooth mean value of all images

≈ 5 images ≈ 1600 each image mean value of all ROIs

≈ 4 ROI each image ≈ 400 each ROI mean value of the mode of the single counts of a ROI

≈ 400 Single-counts each ROI Mode of each ROI

Figure 6. Slice-‐secFon in a bright field microscope. Cementum-‐layer with incremental lines (right side), den<ne-‐layer (leM ) (magnifica<on of 20x diameters). Picture taken with the incremental lines in ver<cal direc<on for a bePer program-‐run.

Sample preparaFon, microscopy and imaging

Figure 5. SecFon cut and microscopic image. Sec<on cuts taken in an 90°-‐angle to the root orienta<on show coincide ring structures. In the bright field microscope image there is a higher contrast between bright and dark lines (medium box). Sec<on cuts along the axis of the tooth root are not ver<cal to the growing line of the cementum and they show rings which are shiMed and not completely overlapping (lower box) (Maat 2006). Sec<ons in the upper and medium part of the root show the most dis<nctly and visibly lines. (Figure modified aMer Maat 2006)

Figure 1. Tooth scheme (longitudinal cut). The root area is surrounded by the tooth-‐cementum. The cementum is added in layers on the bone-‐side of the tooth, comparable with tree-‐rings. The cementum is “nerved” by collagen fibers (“sharpey fibers”), which are fixing the tooth in the alveolar bone. (Figure modified aMer Schroeder 2001).

Figure 2. CorrelaFon of bands, fiber orientaFon, crystal structure and season. Dark and bright lines, visible in transmiPed light microscope are supposable correla<ng with variable orienta<on and different mineraliza<on of the collagen fibers. Bright bands seem to be developed in winter, dark lines in the summer season (Liebermann 1994; Stutz 2002). The changeover of the bands happens in March/April and September/October (Wedel 2007). (A) The varying orienta<on of collagen fibers (Liebermann 1993, 1994; assumed orienta<on of the sharpey fibers in the course of one year aMer Wedel 2007) and (B) the (presumably) consequen<al orienta<on and/or size of the crystals (Cool 2002) seem to create the phenotype of the rings. (Figures: Czermak).

Figure 10. ROI aLer rotaFon. Incremental lines are now accurately orientated in verFcal direcFon. The lines are oMen disrupted by refrac<on or diffrac<on ar<facts (Fig. 6), by par<al decomposi<on of the tooth or by linear kerf marks caused by saw blade (arrows). These kerf marks are similar to incremental lines and in case of a parallel course they can influence the coun<ng result

Program run QuanFtaFve evaluaFon using Auto-‐TCA-‐soLware

Figure 8. Region of interest (ROI). Several points have to be marked to span a polygon around the region to be evaluated. The boundary should follow the bright “erup<on line” on one side and the dark border to the embedding resin on the other side.

Figure 7. DiffracFon arFfacts. Ar<fact lines (arrows) are oMen visible on the interface of prepara<on and embedding material (magnifica<on 20x). They could be mistaken for incremental lines, mainly on images with lower magnifica<on than 40x diameters (Czermak 2006, 2012).

(1) Using the Auto-‐TCA-‐soMware is much more <me saving than manual coun<ng. (2) The soMware provides user independent, consistent and reproducible results. (3) Sta<s<cal error is minimized by larger number of single counts compared to manual coun<ng.

Abstract Aims of this project (1)  CreaFon of an unbiased method

to subsFtute manual line counFng

(2)  OpFmize sample preparaFon and imaging

(3)  QuanFtaFve evaluaFon using Auto-‐TCA-‐soLware

Digital image processing DetecFon of the ROI VerFcally orientaFon of the “naturally grown” incremental lines

B

A A

B

C

Figure 12. (A) ROI aLer image analysis. AMer Fourier back-‐transforma<on of the masked spectrum all interfering structures are eliminated from the image. (B) Example for a line scan. AMer image processing the applied algorithm creates a line-‐by-‐line scan of pixel-‐by-‐pixel gray scale values of the processes ROI. Local maxima and local minima and local minima. Local maxima correspond to the number of incremental lines in this row. They are detected and counted by a programmed peak-‐finder algorithm.

EliminaFon of interfering structures

VerFcally orientaFon of the “naturally grown” incremental lines

Table 1. Number of single-‐counts each counFng level and applied data for further examinaFon . Each coun<ng process generates depending on ROI size 300-‐500 single counts. The Auto-‐TCA soMware shows the results in of one coun<ng-‐process in a window, sorted by the most counted line-‐number, in downward order. The “most counted value”, the mode, of a ROI was taken for further examina<on.

grayscale level

width of ROI

EvaluaFon of the counFng results

[1] Czermak A, Czermak AM, Ernst H, Grupe G (2006): A New Method for the Automated Age-‐at-‐Death Evalua<on by Tooth-‐Cementum Annula<on (TCA). Anthopologischer Anzeiger 64 (1): 25-‐40.

[2] Czermak A (2012): Social Stra<fica<on in the Early Middle Ages -‐ Evidence by Demography, Physical Stress and Nutri<on. (Soziale Stra<fizierung im frühen MiPelalter – Aussage und Nachweismöglichkeiten anhand von biologischen Indikatoren). Disserta<on, München.

[3] Cool SM, Forwood MR, Campbell P, Bennet MB (2002): Comparison between bone and cementum composi<ons and the possible basis for their layered appearances. Bone 30 (2): 386-‐392.

[7] Schroeder H (2001). Orale Strukturbiologie. StuPgart, Thieme. [8] Stutz A (2002). Polarizing Microscopy Iden<fica<on of Chemical Diagenesis in Archaeological Cementum. Journal of Archaeological Science

29: 1327-‐1347. [9] Wedel VL (2007). Determina<on of Season at Death Using Dental Cementum Increment Analysis. Journal of Forensic Science 52 (6):

1334-‐1337.

[4] Liebermann D E (1993): Life History Variables Preserved in Dental Cementum Microstructure. Science 261: 1162-‐1164. [5] Liebermann DE (1994): The Biological Basis for Seasonal Increments in Dental Cementum and their Applica<on to Archaeological

Research. Journal of Archaeological Science 21: 525-‐539. [6] Maat G, Gerretsen R, et al. (2006). Improving the visibility of tooth cementum annula<ons by adjustment of the cudng angle of

microscopic sec<ons. Forensic Science Interna<onal 159(S): 95-‐S99.

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Occurrence

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slice3/count1 slice4/count1 slice5/count1






slice3/count1 slice4/count1 slice7/count1 slice8/count1






early adult (aged 20-‐24) middle adult (aged 25-‐31)

late adult (aged 32-‐38) middle mature (aged 46-‐52)

TCA: aged 27

TCA: aged 41

TCA (1): aged 37 TCA (2):

aged 40

TCA (1): aged 45

TCA (2): aged 52

[email protected] Corresponding address

Auto-‐TCA-‐soLware

Image quality is crucial for valid line counFng.

The soLware provides reliable counFng results, but does not validate the TCA-‐method.

B A

C D

TCA-‐method (1) Using the Auto-‐TCA-‐soMware is much more <me saving than manual coun<ng. (2) The soMware provides user independent, consistent and r

Age at Death Evaluation by Tooth Cementum Annulation

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