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. 2025 Apr 28;55(2):114–125. doi: 10.5624/isd.20240243

Radiographic relationship of third molars with the mandibular canal as a predictor of inferior alveolar nerve sensory disturbance: A systematic review and meta-analysis

Abbas Shokri 1, Ashkan Sadeghi Farnia 2, Ali Heidari 3, Forough Abbasiyan 1,✉, Behnaz Alafchi 4
PMCID: PMC12210119  PMID: 40607074

Abstract

Purpose

This study was performed to assess the relationship of the third molars with the mandibular canal as a predictor of inferior alveolar nerve (IAN) sensory disturbances using panoramic radiography (PR) and cone-beam computed tomography (CBCT).

Materials and Methods

A systematic search was conducted of 4 databases—PubMed, Scopus, Web of Science, and Google Scholar—for the period from 1985 to 2024. In the retrieved articles, the outcome of interest was the relationship of the mandibular canal with the third molars on PR and CBCT scans. The risk of bias was assessed using the Newcastle-Ottawa Scale, and quantitative meta-analysis was performed using STATA. A random-effects restricted maximum likelihood model was employed for the meta-analysis, and the I2 statistic was used to assess heterogeneity.

Results

A total of 1,635 articles were initially retrieved. After a rigorous selection process, 20 studies were included in the qualitative synthesis, and 8 were selected for the meta-analysis. The findings indicated that CBCT yielded higher prevalence rates for root darkening, root deflection, interruption of the white line, diversion of the mandibular canal, and narrowing of the mandibular canal (theta values: 49.962, 4.76, 8.09, 2.229, and 4.708, respectively) compared with PR (theta values: 1.363, 1.605, 6.322, 0.655, and 1.449, respectively).

Conclusion

CBCT was more accurate than PR in investigating predictors of IAN paresthesia in mandibular third molar surgery. Considering the higher prevalence of paresthesia in the presence of root darkening, CBCT may be highly efficient in detecting this parameter and thus aiding in the prevention of paresthesia.

Keywords: Mandibular Nerve; Molar, Third; Paresthesia; Cone-Beam Computed Tomography; Radiography, Panoramic

Introduction

Inferior alveolar nerve (IAN) injury is a significant complication of mandibular third molar extraction, occurring in 0.35% to 8.4% of cases.1 It can potentially result in serious outcomes such as paresthesia and spontaneous uncomfortable sensations in the lower third of the face.2 This injury may occur indirectly (through infection, hematoma, or nerve edema) or directly (via nerve damage) and is associated with risk factors including patient age, surgeon inexperience, tooth impaction depth, and mandibular canal position.3,4 Although most cases are transient and recover spontaneously, severe injuries may lead to permanent paresthesia.5

Proper preoperative planning and integration of surgical techniques with fundamental principles are essential in third molar extraction to minimize intraoperative and postoperative complications.6 Various imaging modalities, including panoramic radiography (PR) and cone-beam computed tomography (CBCT), are used for preoperative assessment of the mandibular canal anatomy to foresee and prevent potential complications.7,8

PR is commonly utilized as a standard imaging modality for the preoperative assessment of impacted mandibular third molars and their relationship with anatomical structures.9 It is often requested as the first radiographic examination, either alone or in combination with other radiographic modalities.10 Seven radiographic signs are recommended to determine the relationship between the mandibular third molar and the inferior alveolar canal. Four of these relate to the tooth, including root darkening, root deflection, root narrowing, and bifid root apex. The remaining 3 signs are associated with the canal, namely interruption of the white line, diversion of the mandibular canal, and narrowing of the mandibular canal.4 These radiographic signs represent standard indicators for assessing the risk of IAN damage during mandibular third molar extraction.7,11

As a 2-dimensional radiographic modality, PR can aid in identifying high-risk patients; however, it cannot be used to evaluate the spatial relationship between the mandibular canal and impacted mandibular third molars.7,12,13 Instead, 3-dimensional (3D) visualization of the anatomical structures of interest is often necessary.13 Specifically, distortion and overlapping of structures reduce the reliability indicators on PR and may lead to misinterpretations or misdiagnosis.14

CBCT is a 3D imaging modality that has recently gained attention for overcoming the drawbacks of PR. CBCT plays a role in surgical planning as well as in reducing operation time and patient complications.15,16 This modality administers a significantly lower radiation dose than regular computed tomography scans.12 On 3D imaging, 3 reliable radiographic predictors are available for IAN injury: the shape and position of the mandibular canal and the absence of cortex between the canal and the mandibular third molar.7,17 However, the widespread use of CBCT as a replacement for PR is limited due to its comparatively large radiation dose, high cost, and reduced accessibility.18,19 Considering the growing popularity of CBCT in dentistry, its efficacy compared to 2D modalities represents a key area of research.10

Previous studies have reported conflicting results regarding the accuracy of CBCT and PR in predicting IAN injury. In 2020, Kubota et al.16 demonstrated that CBCT had a higher predictive value in determining the location of the IAN compared to PR. Similarly, Yabroudi (2012)20 reported that CBCT provided greater accuracy in determining the location of the nerve. However, Gomes et al. (2008)21 found that radiographic findings had limited sensitivity (66%) and specificity (39%) in predicting nerve damage. Additionally, George et al. (2020)22 concluded that both methods had limited efficacy and accuracy in predicting nerve bundle exposure during surgery.

Knowledge of the exact position of the IAN is crucial for the safety of surgical procedures and tooth extraction. Considering the conflicting results of previous studies and the importance of minimizing radiation dose to patients, the present study was conducted to assess the relationship of the third molars with the mandibular canal as a predictor of IAN sensory disturbances using PR and CBCT.

Materials and Methods

Eligibility criteria

This systematic review followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines.23 The eligibility criteria were established in accordance with the Population, Intervention, Comparison, and Outcome (PICO) framework (Table 1).

Table 1. Inclusion and exclusion criteria based on PICO model.

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PICO: Population, Intervention, Comparison, and Outcome, PR: panoramic radiography, CBCT: cone-beam computed tomography, IAN: inferior alveolar nerve.

Data source

A search for relevant articles was conducted in 3 primary databases (MEDLINE/PubMed, Scopus, and Web of Science), along with a supplementary search of Google Scholar. These databases were selected for their capacity to perform precise searches, offer comprehensive coverage of the medical literature, and index numerous articles from peer-reviewed studies and high-impact journals. Google Scholar was specifically included to identify gray literature and informal sources. The reference lists of the selected articles were manually searched, and a limited search was also conducted on the websites of relevant conferences to uncover potential unpublished articles.

The search was limited to English-language publications and targeted articles published between 1985 and 2024. The year 1985 was chosen as the starting point because PR emerged as a standard method in the 1980s,24 while CBCT technology, following the introduction of the FDK algorithm in 1984,25 was initially researched in the 1990s and saw clinical adoption in the early 2000s.26 Selecting 1985 allowed this research to include studies that reflect advancements in both modalities and provide a comprehensive evaluation of their diagnostic applications.

Search strategy

The keywords “inferior alveolar nerve,” “mandibular third molar,” “sensory disturbances,” “tooth apex,” “paresthesia,” “cone-beam computed tomography” and “panoramic radiography” were used in the database queries. These keywords were selected based on the research objectives. Key concepts were first identified; next, relevant terms were systematically extracted through a comprehensive search of related article titles and abstracts, expert consultations, and the use of controlled vocabularies such as Medical Subject Headings (MeSH terms). In PubMed, the search was conducted using MeSH terms. The search strategy, including the incorporated keywords and Boolean operators (“AND” and “OR”) used for each database, is detailed in Table 2.

Table 2. Search strategy for each database.

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Selection process

All steps of article selection and data extraction were independently performed by 2 reviewers. In cases of disagreement, consensus was reached through discussion. Initially, records from each database were imported into End-Note X8 (Clarivate Analytics, Philadelphia, PA, USA). Duplicate articles were then removed using a built-in EndNote function and manual review of the titles. Next, irrelevant articles were excluded based on abstract review. The final selection, based on the inclusion and exclusion criteria, was made by reading the full texts of the remaining articles after the titles and abstracts were screened.

Data collection and extraction

Two reviewers independently examined the included studies and collected the initial data. As detailed in Table 3, the extracted data included the first author's name, publication year, study design, radiographic modality, sex distribution, sample size, age range, number of teeth, type of teeth, nature of the mandibular canal connection with the mandibular third molars, and statistical tests employed. If any of this information was missing, the corresponding author of the article was contacted by email, and the article was excluded if no response was received. The results were entered into Microsoft Excel 2016 (Microsoft Corp., Redmond, WA, USA) and analyzed.

Table 3. Data extracted from the included studies.

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ANOVA: analysis of variance, PR: panoramic radiography, CBCT: cone-beam computed tomography

The correlation coefficient was used as an effect measure, along with the 95% confidence interval. The inverse variance weighting method with a random-effects approach was employed to combine results from different studies, and the I2 statistic was used to determine heterogeneity. Additionally, Comprehensive Meta-Analysis software (Biostat, Inc., Englewood, NJ, USA) was used.

Risk of bias assessment

The risk of bias of the included studies was assessed using the Newcastle-Ottawa Scale (NOS),27 as shown in Table 4. The NOS was chosen because the included studies were primarily observational and because it offers thorough quality evaluation covering 3 domains: selection, comparability, and outcome assessment. It is a simple and widely accepted tool in medical and dental systematic reviews. Alternative tools, such as the Cochrane Risk of Bias 2 (RoB 2)28 tool for randomized controlled trials and the Risk Of Bias In Non-Randomized Studies - of Interventions (ROBINS-I) instrument29 for non-randomized intervention studies, were less appropriate for our study design. The NOS is used to evaluate the quality of systematic reviews and meta-analyses, assessing the potential for bias in the design, conduct, and study analysis. The quality was categorized as follows: 9–10, very good; 7–8, good; 5–6, satisfactory; and 0–4, unsatisfactory. Discrepancies in this evaluation were resolved through discussion.

Table 4. Assessment of risk of bias in the included studies using the Newcastle-Ottawa Scale.

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Results

The electronic search initially yielded 1,635 articles. After eliminating duplicates and irrelevant articles and adding 6 articles from other sources, 710 articles underwent title and abstract review. A total of 680 articles were excluded because they did not meet the inclusion criteria or were irrelevant. The remaining 30 studies were assessed for eligibility. In the final selection process, 20 articles were included in the qualitative synthesis, and 8 articles7,17,22,30,31,32,33,34 were chosen for quantitative analysis. The PRISMA flowchart for the present study is shown in Figure 1.

Fig. 1. PRISMA flowchart for systematic review. PRISMA: Preferred Reporting Items for Systematic reviews and Meta-Analyses.

Fig. 1

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Table 3 presents the data extracted from the included studies. The selected articles were published between 2011 and 2021. Regarding the diverse parameters predicting IAN paresthesia in mandibular third molar extraction surgery, 2 studies exclusively focused on PR, while 6 studies used both PR and CBCT. The number of teeth evaluated in the studies ranged considerably, from 20 to 350.

Based on the risk of bias assessment (Table 4), 5 studies were classified as very good, while the remaining 3 were considered good. Overall, the studies included in the meta-analysis were generally of good quality. Table 5 summarizes the information extracted from the articles used in this meta-analysis. Due to the variability among studies with regard to country as well as uncontrolled variables, a random-effects restricted maximum likelihood model was employed for the meta-analysis. The I2 statistic was used to assess heterogeneity. Additionally, a regression-based Egger test for small-study effects was conducted, with the “Prob” value indicating the absence of a statistically significant risk of bias in the meta-analysis. The variable theta (θ) represents the prevalence of each parameter; a greater θ value indicates higher sensitivity of the modality. For evaluation of the interruption of the white line, θ was 8.090 for CBCT and 6.322 for PR, suggesting higher sensitivity of CBCT in detecting this parameter (Figs. 2 and 3).

Table 5. Meta-analysis data checklist for sensory disturbances.

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PR: panoramic radiography, CBCT: cone-beam computed tomography

Fig. 2. Prevalence rate of interruption of the white line on panoramic images (β1=−8.62, θ=6.322, z=−1.36, Prob>z=0.1726). CI, confidence interval.

Fig. 2

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Fig. 3. Prevalence rate of interruption of the white line on conebeam computed tomography scans (β1=−15.63, θ=8.090, z=−1.93, Prob>z=0.0533). CI, confidence interval.

Fig. 3

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Regarding narrowing of the mandibular canal, θ was 4.708 for CBCT and 1.449 for PR, again suggesting higher sensitivity for CBCT (Figs. 4 and 5). Root deflection exhibited θ values of 4.76 for CBCT and 1.605 for PR, indicating greater sensitivity of CBCT (Figs. 6 and 7). For root darkening, θ was 49.962 for CBCT and 1.363 for PR (Figs. 8 and 9). This significant difference in prevalence indicates especially precise detection of root darkening with CBCT relative to PR. In assessing the diversion of the mandibular canal, the θ values were 2.2 for CBCT and 0.655 for PR, suggesting higher sensitivity of CBCT (Figs. 10 and 11). For root narrowing and bifid root apex, these values were 1.721 for CBCT and 1.38 for PR, similarly indicating inferior detection of these parameters by PR (Figs. 12 and 13).

Fig. 4. Prevalence rate of narrowing of the mandibular canal on panoramic images (β1=3.80, θ=1.449, z=2.62, Prob> z=0.0087). CI, confidence interval.

Fig. 4

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Fig. 5. Prevalence rate of narrowing of the mandibular canal on cone-beam computed tomography scans (β1=0.45, θ=4.708, z=0.09, Prob>z=0.9243). CI, confidence interval.

Fig. 5

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Fig. 6. Prevalence rate of root deflection on panoramic images (β1=7.74, θ=1.605, z=4.82, Prob>z=0.0000). CI, confidence interval.

Fig. 6

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Fig. 7. Prevalence rate of root deflection on cone-beam computed tomography scans (θ=4.76, Prob>z=0.0000, test of homogeneity: Q=chi2(1)=0.88). CI, confidence interval.

Fig. 7

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Fig. 8. Prevalence rate of root darkening on panoramic images (β1=4.12, θ=1.363, z=3.02, Prob>z=0.0025). CI, confidence interval.

Fig. 8

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Fig. 9. Prevalence rate of root darkening on cone-beam computed tomography scans (β1=13.47, θ=42.962, z=0.31, Prob> z=0.7540). CI, confidence interval.

Fig. 9

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Fig. 10. Prevalence rate of diversion of the mandibular canal on panoramic images (β1=1.00, θ=0.655, z=1.53, Prob>z=0.1266). CI, confidence interval.

Fig. 10

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Fig. 11. Prevalence rate of diversion of the mandibular canal on cone-beam computed tomography scans (β1=4.94, theta=2.229, z=2.22, Prob>z=0.0267). CI, confidence interval.

Fig. 11

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Fig. 12. Prevalence rate of root narrowing on panoramic images (β1=2.98, θ=1.721, z=1.73, Prob>z=0.0833). CI, confidence interval.

Fig. 12

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Fig. 13. Prevalence rate of bifid root apex on panoramic images (θ=1.38, Prob>z=0.1674, test of homogeneity: Q=chi2(1)= 18.29). CI, confidence interval.

Fig. 13

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The θ values for IAN injury were 3.034 for interruption of the white line (Fig. 14), 2.024 for root darkening (Fig. 15), 1.115 for root narrowing (Fig. 16), 0.908 for mandibular canal deviation (Fig. 17), and 1.76 for root deflection (Fig. 18). The highest prevalence rates of IAN injury were associated with interruption of the white line and root darkening. Considering the significantly higher detection rate of root darkening using CBCT compared with PR, CBCT can be highly beneficial for detecting this parameter and preventing IAN injury.

Fig. 14. Prevalence rate of sensory disturbances in the presence of interruption of the white line (β1=11.68, θ=3.034, z=3.85, Prob>z=0.0001). CI, confidence interval.

Fig. 14

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Fig. 15. Prevalence rate of sensory disturbances in the presence of root darkening (β1=9.07, θ=2.024, z=4.48, Prob>z=0.0000). CI, confidence interval.

Fig. 15

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Fig. 16. Prevalence rate of sensory disturbances in the presence of root narrowing (β1=3.86, θ=1.115, z=3.46, Prob>z=0.0005). CI, confidence interval.

Fig. 16

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Fig. 17. Prevalence rate of sensory disturbances in the presence of mandibular canal diversion (β1=4.52, θ=0.908, z=4.97, Prob>z=0.0000). CI, confidence interval.

Fig. 17

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Fig. 18. Prevalence rate of sensory disturbances in the presence of root deflection (θ=1.76, Prob>z=0.0783, test of homogeneity: Q=Chi2(1) =5.11). CI, confidence interval.

Fig. 18

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Discussion

Surgical extraction of impacted mandibular third molars may damage the IAN. A precise understanding of the mandibular canal's position is crucial for safe surgery. When an impacted mandibular third molar contacts the distal surface of the second molar, the risk of caries on that surface increases. In addition, the retromolar canal—a bifurcated branch of the mandibular canal—may contain accessory vasculature for mandibular molars or be associated with malpositioned branches of the buccal nerve, giving it particular importance in mandibular surgical procedures.

In the present study, CBCT demonstrated superior detection of root darkening, root deflection, interruption of the white line, diversion of the mandibular canal, and narrowing of the mandibular canal (θ: 49.962, 4.76, 8.09, 2.229, and 4.708, respectively) compared with PR (θ: 1.363, 1.605, 6.322, 0.655, and 1.449, respectively). In other words, CBCT enabled a more accurate assessment of these parameters for mandibular third molar extraction surgery. This marked discrepancy in prevalence rates indicates the superior diagnostic efficacy of CBCT compared to the limited utility of PR in detecting these parameters.

The θ values for IAN injury were 3.034 in the presence of interruption of the white line, 2.024 with root darkening, 1.76 with root deflection, 1.115 with root narrowing, and 0.908 with diversion of the mandibular canal. The highest prevalence rates of IAN damage were associated with interruption of the white line and root darkening. Given that CBCT detected root darkening more frequently than PR, the former modality may be particularly useful for identifying and preventing IAN damage. Overall, considering the similarity of θ values for various parameters—apart from root darkening, which displayed a substantially higher prevalence on CBCT—both imaging techniques offer limited diagnostic efficacy and predictive value for most parameters. Nonetheless, when all parameters are considered collectively, CBCT exhibited a higher overall prevalence and, consequently, greater accuracy compared to PR.

Kubota et al.16 evaluated CBCT- and PR-based predictive models for estimating IAN injury after mandibular third molar extraction, all of which tended to overestimate the risk. However, models incorporating CBCT, particularly a newly developed model, demonstrated significantly better predictive value than those based on panoramic images. In a retrospective study by Issrani et al.,7 examining the radiographic anatomical relationship between mandibular third molar roots and the mandibular canal, CBCT was highly recommended if deviation of the mandibular canal was observed on panoramic views or an interradicular canal was present. Moreover, in a study by George et al.,22 CBCT displayed limited efficacy in predicting nerve bundle exposure before the surgical extraction of impacted mandibular third molars. The accuracy of conventional PR in predicting neurovascular exposure is also limited. Patel et al.34 emphasized the necessity of obtaining CBCT imaging before the surgical extraction of horizontally impacted and distoangular third molars, as well as in other suspicious cases indicated by panoramic images, to minimize postoperative nerve complications. According to Yabroudi et al.,20 CBCT was more accurate than PR in determining nerve location, and the observed differences in mandibular canal position may stem from racial variations. Gomes et al.21 reported a sensitivity of 66% and a specificity of 39% for radiographic findings in predicting nerve damage associated with third molar surgery. In a study by Ng et al.,35 visualization of the alveolar crest was significantly easier than that of the mandibular canal on cross-sectional CBCT images. The use of multiple CBCT sections aided in the more accurate determination of the mandibular canal's position, with cross-sectional CBCT images considered the gold standard. Statistical analysis revealed significant differences among the 3 views in determining horizontal and vertical distances on cross-sectional PR images (P<0.05). Therefore, employing various CBCT views may contribute to more accurate identification of the mandibular canal position.

The results of the present study indicate a significant correlation between the CBCT/PR images of mandibular third molars and the prediction of IAN sensory disturbances. However, CBCT provided a significantly more accurate evaluation of various predictive parameters for IAN sensory disturbances during mandibular third molar extraction surgery than PR.

In summary, both CBCT and PR offer limited diagnostic and predictive values for most parameters, apart from root darkening, which exhibited a higher prevalence on CBCT. However, CBCT demonstrated a higher overall prevalence, and thus a greater accuracy, when all parameters were considered. Given the positive association between root darkening and IAN sensory disturbances, CBCT may be particularly beneficial in detecting this parameter and preventing such disturbances.

Footnotes

Conflicts of Interest: None

References

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