Architectural Changes Associated with Ageing of the Normal Oral Buccal Mucosa

Rasha Abu Eid, Faleh Sawair, Gabriel Landini, Takashi Saku

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

3 Citations (Scopus)


Background and Objective:
With the advances in medicine and the extended average human life expectancy, there is a tendency for the number of
geriatric individuals to increase. It is therefore important to understand the aging process of human tissues to aid in the care of that portion of the population.
The lining of the oral cavity provides protection from the forces of mastication and other potentially noxious effects.
The aging of the oral mucosa has so far been characterised mostly in relation to changes in the oral epithelium such as less prominent rete-ridges, decreased mean thickness (Shklar 1966, Scott et al 1983, Williams and Cruchley 1994), decreased cell density (Hill 1988), decreased mitotic activity and consequently a slow down in tissue regeneration and
healing rates (Barakat et al 1969, Karring and Loe 1973, Hill et al 1994).
Unfortunately, few studies have concentrated on quantitative morphological changes associated with the aging of the oral mucosa. Therefore, the aim of this work is to quantitatively study the architecture and morphology of histological sections representing normal oral mucosa (from biopsies with no mucosal pathology) from different age
groups, to elucidate any associated age changes. Studying the architectural changes associated with aging may help to understand the mechanisms leading to these tissue alterations and help in their monitoring and prevention.

Forty two digital images of normal oral mucosa samples representing different age groups (each group represented a
decade in life ranging from the first to the ninth decade) were captured at x40 magnification (resolution 1.61μm) and 26 images representing the same age groups were captured at x20 magnification (resolution 0.32μm).
The images were analyzed at two levels:
A) The tissue level: The x40 images were analyzed for the irregularity of the epithelial connective tissue interface (ECTI) to estimate changes in rete-pegs prominence using the box counting method to estimate the global fractal dimension.
B) The cellular level : morphometric properties of the epithelial cells were quantitatively assessed and compared across different age groups in the x20 images.
The epithelial cell borders were determined automatically by localization of nuclei based on the optical density of the haematoxylin stain after applying a colour deconvolution algorithm (Ruifrok and Johnston 2001). The nuclei are used as
nuclear “seeds” using greyscale reconstruction (Landini and Othman 2003) and a watershed transform (Vincent and Soille 1991) is then applied to the result of the reconstruction to divide the epithelial compartment into areas of influence unique to each nuclear seed. An example of such analysis is shown in Figure 1.
Cellular morphologic properties were extracted from the segmented images, these included: cell perimeter, area, radius of the inscribed circle centered at the centre of the mass, radius of the enclosing circle centered at the centre of the mass, largest axis length (feret), breadth, convex hull, area of the convex hull polygon, radius of the minimal bounding circle,
aspect ratio, roundness, area equivilent diameter, perimeter equivalent diameter, equivalent ellipse area, compactness, solidity, concavity, convexity, shape, Rfactor, modification ratio, sphericity, feret length, breadth and rectangularity.

The mean box fractal dimension for each age group is shown in (Table 1). No significant trends in the ECTI complexity values with age group were found (One Way ANOVA p>0.05).
Figure 1: A) x20 H&E image of the epithelium B) Haematoxylin component of A C) Segmented epithelial compartment after applying the watershed transform. D) Segmented epithelial compartment after performing the logical AND operation between A and C.
Table 1. Mean Box fractal dimension and the number of cases for different age groups.
Age Range (years) Mean Box Fractal Dimension Number of cases
0-10 1.1069 + 0.03267 2
11-20 1.1117 + 0.08987 2
21-30 1.1414 + 0.07095 4
31-40 1.1290 + 0.03822 4
41-50 1.0933 + 0.05661 5
51-60 1.1373 + 0.05657 8
61-70 1.0992 + 0.04456 9
71-80 1.1260 + 0.04751 5
81-90 1.0903 + 0.01675 3
A total of 52507 “cells” from a selection of cases were analyzed for various morphological parameters. Despite some of the parameters analyzed (case-wise) not showing statistically significant differences across the different age groups (One Way ANOVA p>0.05), cluster analysis showed that two main clusters exist with different average ages.
Cell-wise analysis of the different morphological parameters showed statistically significant differences between the cells of different age ranges (One Way ANOVA p<0.001). The homogenous subsets in the data (post hoc Tukey’s honestly significant difference test) based on different parameters clearly suggested that morphological differences were
present between 3 main age ranges; the first included cases from the first 2 decades of life (0-20 years), the second included cases between 21-50 years of age and the third included cases over 50 years of age.

Various age-related changes have been described in the literature, but preliminary quantitative results obtained in this study indicate that ageing of the oral mucosa does not seem to affect significantly the irregularity of the epithelial connective tissue interface in the range of scales investigated. Mean (case-wise) morphological cellular features
extracted from theoretical cell constructs, also showed no tendency to change with the ageing process when consideredalone, but when submitted to a clustering algorithm, natural groups with different average ages emerged.
When morphological features were compared cell-wise, statistically significant differences were found to exist between
3 main age ranges; 0-20 year, 21-50 year and 51-90 years.
Further studies are needed to look into association of these variables and further morphological features of epithelia in different age groups preferably using large sample sizes. Animal models might also provide further insights into the problem.

1. Abu Eid, R. and G. Landini, Quantification of the global and local complexity of the epithelial-connective tissue interface of normal,
dysplastic, and neoplastic oral mucosae using digital imaging, Pathology Research and Practice. 199: 7 (2003) 475-82.
2. Abu Eid, R. and G. Landini, Morphometry of pseudoepitheliomatous hyperplasia: objective comparison to normal and dysplastic oral mucosae, Analytical and Quantitative Cytology and Histology. 27:4 (2005) 232-40.
3. Abu Eid, R. and G. Landini, Morphometrical differences between pseudo-epitheliomatous hyperplasia in granular cell tumours and squamous cell carcinomas, Histopathology. 48:4 (2006) 407-416.
4. Anderson, D., Cause and prevention of lip canccer, Journal of the Canadian Dental Association. 4 (1971) 138-142.
5. Barakat, N., P. Toto ans N Choukas, Aging and cell renewal of oral epithelium, Journal of Periodontology. 40:10 (1969) 599-602.
6. Cawson, R., Oral ulceration-Clinical aspects, Oral Surgery, Oral Medicine and Oral Pathology. 33:6 (1972) 912-21.
7. Hill, M., Influence of age on the morphology and transit time of murine stratified squamous epithelia, Archives of Oral Biology. 33:4 (1988) 221-9 .
8. Hill, M., J. Karthigasan, J. Berg and C. Squier, Influence of age on the response of oral; mucosa to injury. In: Squier, C. and M. Hill (Eds)
The effect of aging in oral mucosa and skin. (1994) 129-142. CRC Press, Boca Raton.
9. Johnson, N., Orofacial neoplasms: global epidemiology, risk factors and recommendations for research, International Dental Journal. 41 (1991) 365-375.
10. Karring, T. ans H. Loe, The effect of age on mitotic activity in rat oral epithelium, Journal of Periodontal Research. 8:3 (1973) 164-70.
11. Krolls, S. and S. Hoffman, Squamous cell carcinoma of the oral tissues: a statistical analysis of 14,253 cases by age, sex and race of patients, Journal of the American Dental Association. 92 (1967) 571-574.
12. Landini, G. and I. E. Othman, Estimation of tissue layer level by sequential morphological reconstruction, Journal of Microscopy. 209: Pt 2 (2003) 118-25.
13. Ruifrok, A. and D. Johnston, Quantification of histochemical staining by colour deconvolution, Analytical and Quantitative Cytology and Histology. 23: (2001) 291-299.
14. Scott, J., J. Valentine, C. St. Hill and B. Balasooriya, A quantitative histological analysis of the effects of age and sex on human lingual epithelium, Journal de Biologie Buccale. 11:4 (1983) 303-15.
15. Shklar, G. The effects of aging upon oral mucosa, The Journal of Investigative Dermatology. 47:2 (1966) 115-20.
16. Vincent, L. and P. Soille, Watersheds in digital spaces: an efficient algorithm based on immersion simulations, IEEE Transactions on Pattern Analysis and Machine Intelligence. 13 (1991) 583–598.
17. Williams, D. and A. Cruchley, Structural aspects of aging in the oral mucosa. In: Squier, C. and M. Hill (Eds) The effect of aging in oral mucosa and skin. (1994) 65-74. CRC Press, Boca Raton.
Original languageEnglish
Title of host publicationRivista Di Biologia-Biology Forum 2008
Place of PublicationItaly
PublisherFabrizio Serra Editore
Number of pages28
Publication statusPublished - 2008
Externally publishedYes
Event5th International Symposium on Fractals in Biology and Medicine - Locarno, Switzerland
Duration: 12 Mar 200815 Mar 2008

Publication series

NameRivista di Biologia
PublisherFabrizio Serra Editore
ISSN (Print)0035-6050
ISSN (Electronic)0035-6050


Conference5th International Symposium on Fractals in Biology and Medicine
Internet address


Dive into the research topics of 'Architectural Changes Associated with Ageing of the Normal Oral Buccal Mucosa'. Together they form a unique fingerprint.

Cite this