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Abstract

Objectives

The present study was performed in a sample of 33 cats and aimed (1) to characterise the mandible height (Mh), mandibular canal height (MCh) and the distance between the interdental alveolar margin and the mandibular canal (dIAM-MC); and (2) to develop a mathematical model for dimension prediction of MCh using the patient’s age, weight (Wg) and canine tooth width at the free gingival margin level (wCGM) that was easily accessible during the oral examination.

Methods

Age, sex, breed, weight, skull type and the wCGM were the recorded variables for each patient. Right and left lateral view skull radiographs were made followed by measurements of the mandible anatomical structures, taken between the third premolar distal root and the fourth premolar proximal root. Results were considered statistically significant for P values <0.05, and statistical analysis was performed using SPSS software.

Results

We observed a strong correlation only between wCGM and MCh, and a prediction mathematical model was developed to calculate the MCh, with a standard error of only 0.4 mm.

Conclusions and relevance

Our study allows a surgeon to establish relationships between a physical parameter, such as wCGM, evaluated in an oral examination, and the mandibular canal, which is a very important anatomical structure to consider in surgical procedures. Ideally, surgeons should always plan their mandible work only after obtaining a final diagnosis achieved through the use of complementary imaging exams, such as intra- and extra-oral radiographs. Thus, this mathematical equation offers an additional tool, providing more information on the relationships between oral anatomical structures, reducing the risk of iatrogenic lesions and promoting patient safety.

Introduction

Owing to the high prevalence of pathologies of the oral cavity and associated structures in cats, veterinary dentistry is a medical speciality of great importance in feline medical and surgical practice.^1,2 Based on the different anatomical morphologies of their teeth, cats are classified as heterodonts,^3–5 and as diphyodonts, presenting two types of dentition: deciduous and definitive dentition.³ Age, nutrition and oral hygiene care provided by the patient’s owners contribute significantly to the incidence and severity of oral diseases, such as periodontitis that, depending on these and other factors, can manifest itself at different ages,⁶ and affects 70% of all cats at 2 years of age.⁷ Dental fractures, oral masses, oropharyngeal inflammatory complexes and dental crown lesions, such as resorptive lesions, are other commonly diagnosed clinical entities.⁸

Access to medical imaging techniques is of high importance for establishing a correct diagnosis and planning a course of action in veterinary dentistry, especially when oral surgery is considered. In oral surgery, owing to its resolution of multiple pathological processes, exodontia (tooth extraction) is the most commonly performed procedure. To perform this procedure, a good knowledge of oral anatomy and good surgical skills are required to reduce the risk of iatrogenic lesions, such as crown or root fractures of the tooth, to the extracted or adjacent teeth, bleeding or regional nerve lesions.^4,5 After performing a complete clinical examination, a radiographic examination is necessary to evaluate regional anatomical structures, allowing the diagnosis and characterisation of existing lesions,⁵ and providing the surgeon with the necessary information for planning the least invasive procedure possible.

The present study was performed in a sample of 33 cats and aimed (1) to characterise the mandible height (Mh), mandibular canal height (MCh) and the distance between the interdental alveolar margin and the mandibular canal (dIAM-MC); and (2) to develop a mathematical model for the prediction of MCh using the patient’s age, weight (Wg) and the canine tooth width at the free gingival margin level (wCGM) that is easily accessible during the oral examination.

Materials and methods

The study used a sample of 33 cats, of both sexes, and of European common breeds, with a mean age of 4.5 years and weight of 3.7 kg, at the Anjos of Assis Veterinary Medicine Centre, Barreiro, Portugal, and Canham Veterinary Clinic, Almancil, Portugal, presented for elective spaying surgery. For this study, signed consent forms were obtained from the owners, allowing us to obtain radiographs from both sides of the skull in a lateral view in order to evaluate the following mandible structures: Mh, MCh and dIAM-MC. Patients <6 months of age, without complete eruption of the permanent dentition and with gingival hyperplasia, bone recession and major dental problems, were not included in the study.

For each patient, data were recorded for age, sex, breed, weight, skull type and the wCGM. Easily accessible during the patients’ oral examination, the wCGM measurement was achieved by using a digital calliper (SXG-model 110; Dongguan Hust Tony Instruments) (Figure 1), and, in order to achieve a mean value for Mh, MCh and dIAM-MC characterisation, all other mandible anatomical structure measurements were made on the digital radiographic image. The mandible region located between the third premolar distal root and the fourth premolar proximal root was used to perform all measurements because it is where the MCh is easily seen (Figure 2).⁹ SPSS software (IBM) was used for statistical analysis, and correlation analysis was performed using the Pearson correlation coefficient. Simple and multiple linear regressions were performed in order to investigate which variable should be used for the construction of predictive mathematical models. All results were considered statistically significant for P values <0.05.

Figure 1

Measuring the canine tooth width at the level of the free gingival margin – an easily accessible procedure during the patient’s oral examination

Figure 2

Lateral view of a cat’s third premolar distal root and fourth premolar mesial root region, for measurement of the mandible height (Mh), mandibular canal height (MCh), and distance between the interdental alveolar margin and mandibular canal (dIAM-MC)

Results

The results obtained for sample and mandible anatomical structure characterisation are given in Table 1. The Pearson correlation coefficient allowed us to evaluate the correlation between age, Wg and wCGM, and the Mh, MCh and dIAM-CM (Table 2). A strong correlation between Wg and wCGM was observed, along with their correlations to Mh, MCh and dIAM-CM (Figure 3). The following mathematical model was developed to calculate the MCh (y) using the variable wCGM (x), with R² = 0.60 and a standard error of 0.45 mm: $y = 1.137 + 0.492 x$ (Tables 3 and 4).

Table 1

Mean and dispersion measures linked to the physiological parameters of the patients: age, sex and weight, and to mandible anatomical structures

Parameter	n	$\bar{X}$	SD	% Mh
Sex	33
Male	13
Female	20
Age	33	4.56	± 3.54	−
Wg (kg)	33	3.71	± 1.13	−
Mh	33	9.57	± 1.92	100.00
MCh	33	3.02	± 0.71	31.56
dMAI-CM	33	5.27	± 0.99	55.07
vMC	33	−	−	13.37

Data mean ( $\bar{X}$ ) and dispersion (SD) measures obtained in a 95% confidence interval

% Mh = parameter as a proportion of the mandible height (Mh); Wg = weight; MCh = mandibular canal height; dMAI-CM = distance between the interdental alveolar margin and mandibular canal; vMC = ventral mandibular context

Table 2

Pearson correlation between variables recorded during the physical examination, and their correlation with important mandible structures for oral surgery

Parameter	n	Statistical test	Parameter
Parameter	n	Statistical test	Age	Wg	wCGM
Age	33	Pearson correlation	1	0.290	0.172
Age	33	Sig (two extremities)	−	0.102	0.338
Wg	33	Pearson correlation	0.290	1.000	0.629*
Wg	33	Sig (two extremities)	0.102	−	0.000
wCGM	33	Pearson correlation	0.172	0.629*	1
wCGM	33	Sig (two extremities)	0.338	0.000	−
Mh	33	Pearson correlation	0.019	0.131	−0.052
Mh	33	Sig (two extremities)	0.917	0.468	0.773
dIAM-MC	33	Pearson correlation	0.314	0.106	−0.170
dIAM-MC	33	Sig (two extremities)	0.075	0.557	0.343
MCh	33	Pearson correlation	0.204	0.523*	0.782*
MCh	33	Sig (two extremities)	0.254	0.002	0.000

High degree Pearson correlation coefficient value between the two variables. This value is associated with statistically significant Sig value (P <0.05).

Wg = weight; wCGM = canine tooth width at the free gingival margin level; Mh = mandibular height; dIAM-MC = distance between the interdental alveolar margin and mandibular canal; MCh = mandibular canal height; Sig = significant

Figure 3

The matrix confirms the presence of a strong correlation with a determination coefficient (R²) between the free gingival margin level (wCMG) and mandibular canal height (MCh) of cat 0611. Owing to this correlation, testing a model using a simple linear regression in which we could achieve the MCh value by using the wCMG was justified. Mh = mandible height; dIAM-MC = distance between the interdental alveolar margin and mandibular canal

Table 3

Prediction mathematical models developed to calculate the mandibular canal height, using the variable canine tooth width at the free gingival margin level

Coefficients^{* †}
Model	Résumé of the mathematical model				Standardised coefficients		Standardised coefficients	P value
Model	R	R²	AjR²	SD	Beta	SD	Beta	P value
Constant	0.782^*	0.611	0.599	0.452	1.137	0.281	−	<0.001
wCGM (mm)	−	−	−	−	0.492	0.070	0.782	<0.001

Predictor (constant): canine tooth width at the free gingival margin level (wCGM)

†

Dependent variable: mandibular canal height (MCh)

AjR² = adjusted R²

Table 4

Linear regression between variables registered during the study, and their respective R² value, considering a 95% confidence interval

Variables used in linear regression		R²
Age (years)	Weight (kg)	0.084
Age (years)	wCGM (mm)	0.029
Age (years)	dIAM-MC (mm)	0.098
Age (years)	Mh (mm)	<0.001
Age (years)	MCh (mm)	0.042
Weight (kg)	wCGM (mm)	0.396
Weight (kg)	Mh (mm)	0.017
Weight (kg)	dIAM-MC (mm)	0.011
Weight (kg)	MCh (mm)	0.274
wCGM (mm)	Mh (mm)	0.003
wCGM (mm)	dIAM-MC (mm)	0.029
wCGM (mm)	MCh (mm)	0.611
Mh (mm)	dIAM-MC (mm)	0.124
Mh (mm)	MCh (mm)	<0.001
dIAM-MC (mm)	MCh (mm)	0.029

wCGM = canine tooth width at the free gingival margin level; Mh = mandible height; dIAM-MC = distance between the interdental alveolar margin and mandibular canal

Discussion

Oral diseases are very common in feline medicine and surgery, and tooth extraction is the most common oral surgical procedure performed.⁴ With the patient under sedation or anaesthesia, combined with a good oral examination, access to complementary examinations like dental radiographs, and adequate dentistry training, the surgeon may achieve a final diagnosis of the patient’s clinical condition,^10,11 and develop an appropriate treatment plan; consideration always being given to individual anatomical structure variations in order to reduce the risk of iatrogenic injuries and promote patient safety.^1,12,13 During dental extractions and other oral surgical procedures, iatrogenic lesions, such as bleeding and fractures of maxilla, mandible or teeth, nerve injuries and ocular trauma may occur. By accessing information about each patient’s regional anatomy, regarding location, size and relationships of the mandible anatomical structures considered important for surgical planning, such as the Mh, MCh and dIAM-MC, the surgeon may improve the outcome of procedures.^1,14,15 In the present study, the mean values of Mh, MCh, dIAM-MC and wCGM were established, as were the proportions MCh and dMAI- CM relative to Mh; the latter corresponded to 31.56% and 55.07%, respectively, thus both structures represented 86.63% of the total Mh. No references in the literature were found to MCh variations in felines. A strong correlation was established between the wCGM (obtained during the cat’s physical examination) and the radiographic measurements of the Mh, MCh and dIAM-MC, which allowed us to develop a mathematical model to calculate the MCh value with a sufficiently high predictive capability and a very low standard error, thus providing a very reliable indicator of the evaluated structures’ real dimensions. It is anticipated that the model should be of great utility for planning regional surgical procedures when no access exists to essential imaging methods to obtain more precise information about a patient’s mandible anatomy. Residue analyses were performed to confirm the compliance of the developed model.

Conclusions

To our knowledge, this is the first study where a relationship between a physical parameter registered during a patient’s clinical examination, wCGM, and an anatomical mandible structure considered very important in oral surgery, Mh, is established. The correlation between wCGM and MCh was strong enough for the development and application of a mathematical predictive model of MCh value based on wCGM, with a standard error of only 0.4 mm. Ideally, all mandible surgical procedures should be planned using the information achieved with complementary imaging exams, such as intra- and extra-oral radiographs. Thus, the results of the study provide a mathematical equation that should be considered as an additional tool for the surgeon, allowing insight into the mandible structures’ anatomical relationships, and thereby reducing the risk of iatrogenic lesions during intra-oral surgical procedures and improving patient safety.

Footnotes

Acknowledgements

We thank the Interdisciplinary Centre of Research in Animal Health (CIISA), Faculty of Veterinary Medicine, University of Lisbon, Lisbon, Portugal; Prof Dr Isabel Neto from Faculty of Veterinary Medicine, University of Lisbon; Dr Ana Reis and Dr Tiago Carrapiço, Canham Veterinary Clinic, Alamancil, Portugal; and Dr Alexandra Costa, Dr Eva Mendes and Dr Pedro Azevedo, Anjos of Assis Veterinary Medicine Centre, Barreiro, Portugal.

Conflict of interest

The authors do not have any potential conflicts of interest to declare.

Funding

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

Accepted: 16 April 2015

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Mathematical equation for prediction of cat mandibular canal height dimension based on canine tooth width measurement

Abstract

Objectives

Methods

Results

Conclusions and relevance

Introduction

Materials and methods

Results

Discussion

Conclusions

Footnotes

Acknowledgements

Conflict of interest

Funding

References