Assessment of Root Canal Morphology of Maxillary Premolars: A CBCT Study Exploring Age and Gender Variations

doi:10.21203/rs.3.rs-3449226/v1

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Assessment of Root Canal Morphology of Maxillary Premolars: A CBCT Study Exploring Age and Gender Variations

https://doi.org/10.21203/rs.3.rs-3449226/v1

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Background: In complex teeth like maxillary premolars, endodontic treatment success depends on a complete comprehension of root canal anatomy. While mandibular premolars have been extensively studied, there is little data on the root canal anatomy of maxillary premolars. This study aimed to explore the root canal morphology of maxillary premolars using cone-beam computed tomography (CBCT) imaging, considering age and gender variations.

Methods: From 500 patient CBCT scans, 1,230 maxillary premolar teeth were evaluated. The sample was divided by gender and age (10-20, 21-30, 31-40, 41-50, 51-60, and 61 years and older). Ahmed et al. classification system was used to record root canal morphology.

Results: The most frequent classifications for right maxillary 1st premolars were ²MPM¹ B¹ L¹(39.03%) and ¹MPM¹ (2.81%), while the most frequent classifications for right maxillary 2nd premolars were ²MPM¹ B¹ L¹ (39.08%) and ¹MPM¹ (17.85%). Most of the premolars typically had two roots (left maxillary first premolars: 81.5%, left maxillary second premolars: 82.7%, right maxillary first premolars: 74.4%, right maxillary second premolars: 75.7%). Left and right maxillary 1st premolars for classes ¹MPM¹ and ¹MPM^1-2-1 showed significant gender differences. For classifications ¹MPM¹ and ¹MPM^1-2-1, age-related changes were seen in the left and right maxillary first premolars.

Conclusion: The research findings offer significant new knowledge of the complex and diverse root canal anatomy of maxillary premolars. The results highlight the significance of CBCT imaging for accurate treatment planning and clinical decision-making. Understanding the differences in root canal anatomy attributed to age and gender may facilitate endodontic treatment outcomes.

CBCT

dental anatomy

dental diagnostic imaging

dental pulp

endodontics

morphology

root

root canal

Premolars

The morphology and variability of root canal systems play a crucial role in the success of endodontic treatment (1). Understanding the intricacies of root canal anatomy is essential for effective diagnosis, treatment planning, and applying appropriate techniques. While extensive research has been conducted on the root canal morphology of mandibular premolars (2, 3), limited information is available regarding the root canal morphology of maxillary premolars.

Maxillary premolars present unique challenges due to their anatomical complexity, including multiple canals, isthmuses, and accessory canals (4, 5). Accurately identifying and classifying root canal systems in maxillary premolars is crucial for diagnosis and achieving optimal treatment outcomes.

Despite the importance of understanding root canal morphology, there remains a gap in knowledge concerning maxillary premolars. This lack of comprehensive information on the root canal morphology of maxillary premolars hinders endodontic practitioners' ability to deliver precise and successful treatments. This study aims to fill this gap by conducting an investigation using cone-beam computed tomography (CBCT) imaging. CBCT, as a non-invasive and highly accurate imaging technique, offers the advantage of providing detailed three-dimensional representations of root canal systems, which were previously not easily achievable through conventional radiographs. The high-resolution images obtained through CBCT will provide valuable data to enhance the knowledge and clinical management of root canal anatomy in these teeth, leading to better-informed treatment decisions and reduced complications (3).

By analyzing a large sample size of CBCT images, we aim to comprehensively understand the root canal configuration in maxillary premolars, considering factors such as age and gender. The findings of this study will contribute to enhancing the knowledge and clinical management of root canal anatomy in maxillary premolars, improving treatment success rates and reducing complications.

By elucidating the variations and complexities of root canal morphology in maxillary premolars, this study will aid dental professionals in making informed decisions regarding treatment approaches, instrument selection, and the application of advanced endodontic techniques (6, 7). Furthermore, the results will provide valuable insights for dental educators, researchers, and students, facilitating the development of standardized protocols and guidelines for managing root canal systems in maxillary premolars.

Ethical Consideration:

Ethical approval

for this retrospective study was obtained from the Local Committee of Bioethics for Research at the Dentistry College, King Abdul-Aziz University, with Ethical Approval No. 025-02-22. Informed consent was obtained from the Committee of Bioethics for Research, College of Dentistry, King Abdul-Aziz University, Jeddah, Saudi Arabia, considering the study's retrospective nature. Before any investigation or treatment, the patients signed a general consent form, allowing the use of findings in future studies without revealing personal information.

Sample Size:

The sample size of 183 scanned samples was determined using G Power 3.1.9.4 software, based on a chi-square test for goodness-of-fit, statistical power analysis, and an a priori approach. The present study included a total of 1,230 maxillary premolars (645 first premolars and 585-second premolars) from 500 cone-beam computed tomography (CBCT) images of patients, including retrospective data.

Data Collection:

Access to patient records, including age and gender information, required prior approval from the academic and clinical affairs vice dean. The CBCT images, acquired for unrelated purposes, were provided by the radiology department of the College of Dentistry. Personally identifiable information of the patients, such as names and other personal details, was not recorded to ensure compliance with ethical obligations. The study team had access only to anonymized data. The study focused on CBCT images of healthy maxillary premolars with small carious or restorative crowns, fully formed root apex, and defect-free radiographic images. Exclusion criteria included root canal-treated teeth, fractured upper and lower posterior teeth, post and core restorations, calcification, resorption defects, and anomalies of crown and root.

Calibration:

An expert endodontist and an observer performed the calibration. The observer studied 50 CBCT images and identified root canal morphology by evaluating axial, sagittal, and coronal views. A single score was assigned to each tooth. Disagreements were resolved through deliberation and discussion, leading to a consensus decision.

Root and Canal Analysis:

An expert endodontist and an observer acquired and analyzed the images using the iCAT scanner system (Imaging Sciences International, Hatfield, PA, USA). 8 × 8 cm images were scanned at 120 KVp and 5–7 mA with a voxel size of 0.2 mm. Images were viewed and analyzed on a calibrated Dell 17-inch high-resolution monitor at 16-bit colour depth and 1024 × 768 pixels screen resolution. The obtained images were divided into age groups (10 to 20, 21 to 30, 31 to 40, 41 to 50, 51 to 60, and 61 years above) and categorized by gender (males and females). Root canal morphology was recorded and classified according to the classification system proposed by Ahmed et al. in 2017 (Figure. 1). Differences related to the age and gender of the subjects were noted.

Statistical Analysis:

Statistical analysis was performed using SPSS version 26 software (IBM SPSS Statistics, Armonk, NY, USA). Descriptive statistics, such as mean frequency and standard deviation, were calculated. The association between root canal morphology in maxillary premolars and the age and gender of the patients were analyzed using the chi-square test or Fisher exact test. The significance level was set at 5% (p ≤ 0.05).

The distribution of maxillary premolars according to Ahmed's classification was examined. Table 1 presents the distribution of premolars based on the classification categories. For right maxillary 1st premolars, the majority belonged to ²MPM¹ B¹ L¹ (39.03%) and ¹MPM¹ (2.81%) categories. Similarly, for right maxillary 2nd premolars, ²MPM¹ B¹ L¹ (39.08%) and ¹MPM¹ (17.85%) were the most prevalent categories.

Table 1

Distribution of maxillary premolars according to Ahmed's classification
Classification	Right Max 1st PM		Right Max 2nd PM		Left Max 1st PM		Left Max 2nd PM
Classification	n	%	n	%	n	%	n	%
¹ MPM ¹	11	2.81	70	17.85	8	2.03	74	18.8
² MPM ¹ B ¹ P ¹	153	39.03	45	11.48	154	39.08	45	11.42
³ MPM MB ¹ DB ¹ P ¹	1	0.25	3	0.77	2	0.5	2	0.5
¹ MPM ^{1–2−1–2−1–2}	1	0.25	1	0.25	0	0	0	0
¹ MPM ^{2−1−2−1}	0	0	1	0.25	1	0.25	0	0
¹ MPM ²⁻¹	4	1.02	2	0.51	6	1.52	2	0.5
¹ MPM ^1–2−1	22	5.61	52	13.26	26	6.6	52	13.2
¹ MPM ²⁻²	11	2.81	9	2.3	9	2.28	5	1.26
¹ MPM ^1–2	3	0.77	1	0.25	4	1.01	3	0.76
¹ MPM ^{1–2−1–2}	1	0.25	1	0.25	0	0	0	0
¹ MPM ²⁻¹⁻²	0	0	0	0	0	0	1	0.25
Total	207	52.8	185	47.2	210	53.3	184	46.7

Table 2 displays the distribution of maxillary premolars based on the number of roots. The majority of premolars had two roots (81.5% for left maxillary 1st premolars, 82.7% for left maxillary 2nd premolars, 74.4% for right maxillary 1st premolars, and 75.7% for right maxillary 2nd premolars) (Fig. 2–4).

Table 2

Distribution of maxillary premolars according to number of roots
Number of roots	Left Max 1st PM	Left Max 2nd PM	Right Max 1st PM	Right Max 2nd PM
One root	54	137	53	137
Two roots	154	45	153	45
Three roots	2	2	1	3
Total	210	184	207	185

Tables 3 and 4 present the distribution of left and right maxillary 1st and 2nd premolars, respectively, based on gender. In Table 3, significant gender differences were observed for the classification ¹MPM¹ (p = 0.515) and ¹MPM^1–2−1 (p = 0.010*) for both left maxillary 1st and 2nd premolars. The number of males and females for MPM¹ in left maxillary 1st premolars was 121 and 88, respectively, while for ¹MPM¹ in left maxillary 2nd premolars, it was 111 and 72, respectively. Similarly, for ¹MPM^1–2−1 in left maxillary 1st premolars, the number of males and females was 3 and 3, respectively, whereas for left maxillary 2nd premolars, it was 30 and 21, respectively.

Table 3

Distribution of left maxillary 1st and 2nd premolar with respect to gender
Classification	Left Mand 1st PM			Left Mand 2nd PM
Classification	Male	Female	p-value	Male	Female	p-value
¹MPM¹	6	2	0.515	36	38	0.010*
²MPM¹ B¹ P¹	93	61		37	8
³MPMMB¹DB¹P¹	1	1		1	1
¹MPM²⁻¹	0	1		2	0
¹MPM^1–2−1	3	3		30	21
¹MPM²⁻²	12	13		4	1
¹MPM^1–2	3	6		1	2
¹MPM²⁻¹⁻²	3	1		0	1
Total	121	88		111	72
*Significant value < 0.05; Chi-square test

Table 4

Distribution of right maxillary 1st and 2nd premolar with respect to gender
Classification	Right Mand 1st PM			Right Mand 2nd PM
Classification	Male	Female	p-value	Male	Female	p-value
¹MPM¹	5	6	0.032*	34	36	0.003*
²MPM¹ B¹ P¹	100	53		38	7
³MPMMB¹DB¹P¹	0	1		2	1
¹MPM^{1–2−1–2−1–2}	1	0		0	1
¹MPM ^{2−1−2−1}	0	0		0	1
¹MPM²⁻¹	1	3		2	0
¹MPM ^1–2−1	10	11		33	18
¹MPM²⁻²	2	9		5	4
¹MPM^1–2	2	1		1	0
¹MPM ^{1–2−1–2}	1	0		0	1
Total	122	84		115	69
*Significant value < 0.05; Chi-square test

Table 4 indicates significant gender differences for the classification MPM¹ (p = 0.032*) and ¹MPM^1–2−1 (p = 0.003*) in the right maxillary 1st premolars. The number of males and females for ¹MPM¹ in the right maxillary 1st premolars was 122 and 84, respectively, while for ¹MPM¹ in the right maxillary 2nd premolars, it was 115 and 69, respectively. Additionally, the number of males and females for ¹MPM^1–2−1 in right maxillary 1st premolars was 10 and 11, respectively, whereas, for right maxillary 2nd premolars, it was 33 and 18, respectively.

Tables 5 and 6 demonstrate the distribution of left and right maxillary 1st and 2nd premolars, respectively, based on age groups. In Table 5, significant differences were observed for the classification ¹MPM¹ (p = 0.053) and ¹MPM^1–2−1 (p = 0.002*) in left maxillary 1st premolars. The number of premolars in each age group for ¹MPM¹ in left maxillary 1st premolars ranged from 1 to 7, whereas for ¹MPM^1–2−1, it ranged from 0 to 3. For left maxillary 2nd premolars, significant differences were observed for the classification ¹MPM¹ (p = 0.002*) and ¹MPM^1–2−1 (p = 0.002*). The number of premolars in each age group for ¹MPM¹ in left maxillary 2nd premolars ranged from 6 to 38, whereas for ¹MPM^1–2−1, it ranged from 4 to 23.

Table 5

Distribution of left maxillary 1st and 2nd premolars with respect to age
Classification	Left Max 1st PM							Left Max 2nd PM
	AGE						p-value	AGE						p-value
	10–20	21–30	31–40	41–50	51–60	60+		10–20	21–30	31–40	41–50	51–60	60+
¹ MPM ¹	1	3	3	0	1	0	0.053	13	23	16	9	7	6	0.002*
² MPM ¹ B ¹ P ¹	17	41	47	20	14	15		5	16	14	4	3	3
³ MPM MB ¹ DB ¹ P ¹	0	2	0	0	0	0		0	1	1	0	0	0
¹ MPM ²⁻¹	0	1	0	0	0	0		0	0	1	1	0	0
¹ MPM ^1–2−1	0	1	2	0	2	1		2	13	13	11	9	4
¹ MPM ²⁻²	3	7	5	5	3	3		0	3	1	0	1	1
¹ MPM ^1–2	0	3	1	1	1	3		0	0	1	2	0	0
¹ MPM ²⁻¹⁻²	0	2	1	0	1	0		0	0	1	0	0	0
Total	21	60	59	26	22	22		20	56	48	27	20	14
*Significant value < 0.05; Chi-square test

Table 6

Distribution of right maxillary 1st and 2nd premolars with respect to age
Classification	Right Max 1st PM							Right Max 2nd PM
	AGE						p-value	AGE						p-value
	10–20	21–30	31–40	41–50	51–60	60+		10–20	21–30	31–40	41–50	51–60	60+
¹ MPM ¹	1	3	3	1	3	0	0.055	12	25	17	4	6	6	0.002*
² MPM ¹ B ¹ P ¹	17	39	45	22	12	18		7	13	14	5	3	3
³ MPMMB ¹ DB ¹ P ¹	0	1	0	0	0	0		0	2	1	0	0	0
¹ MPM ^{1–2−1–2−1–2}	0	0	1	0	0	0		0	0	0	1	0	0
¹ MPM ^{2−1−2−1}	0	0	0	0	0	0		0	1	0	0	0	0
¹ MPM ²⁻¹	0	1	1	0	2	0		0	0	1	1	0	0
¹ MPM ^1–2−1	3	7	8	1	0	3		1	15	12	7	7	10
¹ MPM ²⁻²	0	4	2	1	2	2		0	3	3	0	0	3
¹ MPM ^1–2	0	2	0	0	1	0		0	0	0	1	0	0
¹ MPM ^{1–2−1–2}	0	0	0	0	0	1		0	0	1	0	0	0
Total	21	57	60	25	20	24		20	59	49	19	16	22
*Significant value < 0.05; Chi-square test

In Table 6, significant differences were observed for the classification ¹MPM¹ (p = 0.055) and MPM¹ (p = 0.002*) in the right maxillary 1st and 2nd premolars, respectively. The number of premolars in each age group for ¹MPM¹ in the right maxillary 1st premolars ranged from 1 to 6, whereas for ¹MPM^1–2−1, it ranged from 0 to 15. For right maxillary 2nd premolars, significant differences were observed for the classification ¹MPM¹ (p = 0.002*) and ¹MPM^1–2−1 (p = 0.002*). The number of premolars in each age group for ¹MPM¹ in the right maxillary 2nd premolars ranged from 6 to 36, whereas for ¹MPM^1–2−1, it ranged from 3 to 15.

The present study aimed to investigate the root canal morphology of maxillary premolars using cone-beam computed tomography (CBCT) imaging. By analyzing a large sample size of CBCT images, we sought to provide a comprehensive understanding of the complex and variable root canal configuration in maxillary premolars, considering factors such as gender and age.

As mentioned in the literature (8, 9), our findings revealed a diverse range of root canal configurations in maxillary premolars. Multiple canals, isthmuses, and accessory canals in these teeth pose a challenge to endodontic treatment, as it necessitates thorough exploration, disinfection, and meticulous instrumentation (10). Recognizing such complex anatomy underscores the importance of employing advanced imaging techniques, such as CBCT, to accurately visualize and assess root canal morphology (11).

Our study observed age-related variations in root canal anatomy, corroborating previous research (12–14). These age-related changes can be attributed to factors such as dentin deposition and secondary dentin formation, which may alter the shape and complexity of the root canal system over time. Therefore, endodontists should consider these age-related variations when planning and performing root canal procedures, particularly in older patients (15).

Furthermore, our study identified gender-based differences in root canal morphology. This finding aligns with Ahmed et al. (8), who reported similar gender differences in maxillary premolars. Their study revealed a higher prevalence of multiple canals in males than females, which supports our observations of significant gender variations in root canal morphology. However, it is worth noting that Ahmed et al. did not mention the specific classification code ¹MPM^1–2−1 in their study, making a direct comparison somewhat limited.

Likewise, Cleghorn et al. (9) found that the prevalence of multiple canals in maxillary first premolars ranged from 30–73%, a range consistent with our findings. Shi et al., while studying the Chinese population (12), also noted significant differences in the number of roots and gender in both maxillary first and second premolars.

In a study conducted by Mashyakhy et al. (16) in a Saudi population, highly statistically significant differences in canal configurations were observed between genders in maxillary teeth. Similarly, Martins et al. (17) reported a gender difference in the root canal morphology of the Portuguese population. However, it is essential to mention that some contrasting results were found in specific subpopulations. For instance, no significant difference in root canal morphology was noted in the Malaysian subpopulation (18) and the German subpopulation (19).

In summary, our study adds to the existing body of literature by providing further evidence of gender-related variations in root canal morphology, and it is in line with previous research in this field.

This study's utilization of CBCT imaging provided valuable insights into the three-dimensional morphology of maxillary premolars. CBCT has emerged as a powerful diagnostic tool in endodontics, enabling the visualization of intricate root canal anatomy (20). Accurately assessing root canal morphology facilitates precise treatment planning, guiding clinicians in determining the appropriate access, instrumentation, and obturation techniques (21). The present study has several advantages, reinforcing its conclusions' reliability and veracity. First and foremost, a large sample size was used in the study, with 500 cone-beam computed tomography (CBCT) images in total, 1230 maxillary premolars included. This large sample size improves the study's statistical power and broadens the applicability of the results to the intended population.

The study employed qualified endodontists and observers calibrated to evaluate root canal morphology to achieve precise and reliable analysis. To determine the classification of root canal morphology, 50 CBCT images were examined as part of the calibration process. The research boosted the consistency and accuracy of the results by creating a smooth decision-making process that reduced the possibility of observer bias.

In the present study, a standardized classification scheme was used. This classification system offers a reliable and standardized method for classifying root canal morphology. The study's findings may be easily compared and integrated with those of other research utilizing the same approach because it used a recognized classification system. Understanding root canal morphology in maxillary premolars is ultimately enhanced by this, making it easier for future research and enabling meta-analyses.

Additionally, the study compared its findings to pertinent literature, enabling a thorough interpretation of the data in light of earlier research. The study offers important insights into the heterogeneity of root canal morphology in maxillary premolars by comparing the consistency or divergence of results across different populations and studies. The scientific knowledge base is expanded, and this topic is better-understood thanks to the comparative method.

Despite the valuable contributions of this study to understanding root canal morphology in maxillary premolars, several limitations should be acknowledged. The sample size was obtained from retrospective data, which may introduce selection bias and limit generalizability. Additionally, the study focused on a specific population, and variations in root canal anatomy among different ethnicities and populations should be considered.

Future research endeavours should explore the relationship between root canal morphology and treatment outcomes in maxillary premolars to enhance our knowledge further. Long-term follow-up studies can provide valuable insights into the success rates and potential complications associated with different root canal configurations. Furthermore, advancements in imaging modalities and treatment techniques, such as guided endodontics and regenerative approaches, hold promise for overcoming the challenges posed by complex root canal anatomy.

The present study highlighted the complex and variable root canal morphology of maxillary premolars. The findings underscore the importance of thorough exploration, disinfection, and personalized treatment approaches to ensure successful endodontic outcomes. CBCT imaging and consideration of age and gender-related variations in root canal anatomy are crucial in improving treatment planning and clinical decision-making in managing maxillary premolars.

Data Availability

All data supporting the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgements

Not applicable.

Funding Statement

The current paper did not receive any external funding.

Author contributions

Conception and design of the study: MIK, and TYN. Acquisition of data: AZ and SJ. Analysis and interpretation of data: RB and AHA. Drafting the article: MIK, RB, AHA and SJ. Revising it critically for important intellectual content: MIK, AZ, HAA, MAA and TYN. All authors approved the final submitted version.

Conflicts of Interest

All the authors declare that they have no known conflicts of interest in terms of competing financial interests or personal relationships that could have an influence or are relevant to the work reported in this paper.

Ethics approval

Ethical approval for this retrospective study was obtained from the Local Committee of Bioethics for Research at the Dentistry College, King Abdul-Aziz University, with Ethical Approval No. 025-02-22. Informed consent was obtained from the Committee of Bioethics for Research, College of Dentistry, King Abdul-Aziz University, Jeddah, Saudi Arabia, considering the study's retrospective nature. Before any investigation or treatment, the patients signed a general consent form, allowing the use of findings in future studies and publication without revealing personal information.

Consent for publication

The patients signed a general consent form, allowing the use of findings in future studies and for publication without revealing personal information.

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No competing interests reported.

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Assessment of Root Canal Morphology of Maxillary Premolars: A CBCT Study Exploring Age and Gender Variations

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Introduction

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Root and Canal Analysis:

Statistical Analysis:

Results

Discussion

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