Submitted:
19 December 2025
Posted:
22 December 2025
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Abstract
Keywords:
1. Introduction
2. Materials and Methods
2.1. Specimen Selection
2.2. Measurements
2.3. Statistics
2.4. Meta-Analysis
3. Results
3.1. Prevalence, Size and Location of Accessory Mandibular Foramina
3.2. Clustering Accessory Mandibular Foramina Reveals Two Distinct Groups
3.3. Meta-Analysis of Prevalence of Accessory Mandibular Foramina
3.4. Critical Appraisal of the Present Meta-Analysis
4. Discussion
4.1. Additive Value of the Present Study in Relation to the Established Knowledge
4.2. Strengths and Limitations of the Present Study
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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| Study | Origin | Material | Sample (No of mandibles) | Mandibles without AMaF | Mandibles with unilateral AMaF | Mandibles with bilateral AMaF | Mandibles with multiple AMaFs | Total number of AMaFs |
| Sutton 1974 [21] | Australia | DM | 300 | 131 | ||||
| Suazo 2009 [22] | Brazil | DM | 256 | 147 | 60 | 49 | 0 | 158 |
| Murlimanju 2011 [23] | India | DM | 67 | 56 | 6 | 5 | 2 | 13 |
| Freire 2012 [24] | Brazil | DM | 222 | 126 | 56 | 40 | 27 | 173 |
| Samanta 2013 [25] | India | DM | 60 | 50 | 10 | 0 | 4 | 14 |
| Padmavathi 2014 [26] | India | DM | 65 | 38 | 19 | 8 | 0 | 27 222 12 18 |
| Patra 2015 [27] | India | DM | 160 | 42 | 51 | 67 | 36 | |
| Raghavendra 2015 [28] | India | DM | 100 | 91 | 9 | 0 | 3 | |
| Gopalakrishna 2016 [29] | India | DM | 100 | 82 | 18 | 0 | 0 | |
| Hoque 2016 [30] | Bangladesh | DM | 185 | 173 | 9 | 3 | 0 | 15 |
| Lima 2016 [31] | Brazil | DM | 30 | 15 | 8 | 7 | 0 | 22 |
| Shalini 2016 [32] | India | DM | 204 | 138 | 28 | 18 | 20 | 110 |
| Sultana 2016 [33] | India | DM | 100 | 38 | 47 | 13 | 0 | 73 |
| Goyal 2017 [34] | India | DM | 100 | 61 | 26 | 12 | 1 | 53 |
| Rajkumari 2017 [35] | India | DM | 50 | 36 | 5 | 9 | 0 | 23 |
| Asdullah 2018 [36] | India | DM | 50 | 43 | 0 | 7 | 0 | 14 |
| Mathur 2018 [37] | India | DM | 100 | 75 | 21 | 4 | 6 | 35 |
| Sarkar 2018 [38] | India | DM | 50 | 36 | 14 | 0 | 0 | 14 |
| Pal 2018 [39] | India | DM | 160 | 55 | 78 | 27 | 21 | 164 |
| Dave 2019 [40] | India | DM | 300 | 174 | 104 | 22 | 70 | 290 |
| Kuberappa 2019 [41] | India | DM | 100 | 67 | 27 | 6 | 0 | 39 |
| Mondal, 2019 [42] | India | DM | 30 | 3 | 6 | 20 | 1 | 48 |
| Nayak 2019 [43] | India | DM | 30 | 24 | 2 | 5 | 0 | 10 |
| Chandan 2020 [44] | India | DM | 56 | 25 | 20 | 11 | 0 | 42 |
| Iwanaga 2020 [6] | Japan | FFC | 11 | 4 | 5 | 2 | 0 | 9 |
| Singh 2020 [45] | India | DM | 28 | 17 | 5 | 6 | 3 | 19 |
| Thunyacharoen 2020 [46] | Thailand | DM | 220 | 152 | 55 | 41 | 10 | 96 |
| Mistry 2021 [47] | India | DM | 140 | 96 | 18 | 26 | 2 | 96 |
| Induja 2022 [48] | India | DM | 50 | 18 | 32 | 0 | 0 | 32 |
| Shwetha 2022 [49] | India | DM | 112 | 78 | 22 | 12 | 3 | 49 |
| Adalarasan 2024 [50] | India | DM | 77 | 124 | 20 | 10 | 0 | 40 |
| Bandlamudi 2024 [51] | India | DM | 51 | 21 | 16 | 14 | 0 | 44 |
| Sakalem 2024 [52] | Brazil | DM | 63 | 59 | 4 | 0 | 4 | 4 |
| Sujatha 2024 [53] | India | DM | 70 | 59 | 10 | 1 | 1 | 13 |
| Singh 2025 [54] | India | DM | 30 | 19 | 6 | 5 | 1 | 12 |
| Present study | Greece | DM | 96 | 88 | 3 | 5 | 4 | 25 |
| Study | Domain 1: Objectives and study characteristics | Domain 2: Study design | Domain 3: Methodology characterization | Domain 4: Descriptive anatomy | Domain 5: Reporting of results | Quality assessment |
| Sutton 1974 [21] | Unclear | Low | Low | Unclear | Low | Medium |
| Suazo 2009 [22] | Low | Low | Low | Low | Low | High |
| Murlimanju 2011 [23] | Low | Low | Low | Low | Low | High |
| Freire 2012 [24] | Unclear | Low | Low | Low | Low | High |
| Samanta 2013 [25] | Unclear | Low | Unclear | Low | Low | Medium |
| Padmavathi 2014 [26] | Unclear | Low | Low | Low | Low | High |
| Patra 2015 [27] | Unclear | Low | Unclear | Low | Low | Medium |
| Raghavendra 2015 [28] | Unclear | Low | Unclear | Low | Low | Medium |
| Gopalakrishna 2016 [29] | Unclear | Low | Unclear | Low | Low | Medium |
| Hoque 2016 [30] | Unclear | Low | Unclear | Low | Low | Medium |
| Lima 2016 [31] | Unclear | Low | Low | Low | Low | High |
| Shalini 2016 [32] | Unclear | Low | Low | Low | Low | High |
| Sultana 2016 [33] | Unclear | Low | Low | Low | Low | High |
| Goyal 2017 [34] | Unclear | Low | Unclear | Low | Low | Medium |
| Rajkumari 2017 [35] | Unclear | Low | Low | Low | Low | High |
| Asdullah 2018 [36] | Unclear | Low | Unclear | Low | Low | Medium |
| Mathur 2018 [37] | Unclear | Low | Unclear | Low | Low | Medium |
| Sarkar 2018 [38] | Unclear | Low | Low | Low | Low | High |
| Pal 2018 [39] | Unclear | Low | Unclear | Low | Low | Medium |
| Dave 2019 [40] | Unclear | Low | Unclear | Low | Low | Medium |
| Kuberappa 2019 [41] | Unclear | Low | Unclear | Low | Low | Medium |
| Mondal, 2019 [42] | Unclear | Low | Unclear | Low | Low | Medium |
| Nayak 2019 [43] | Low | Low | Unclear | Low | Low | High |
| Chandan 2020 [44] | Unclear | Low | Unclear | Low | Low | Medium |
| Iwanaga 2020 [6] | Low | Low | Low | Low | Low | High |
| Singh 2020 [45] | Unclear | Low | Unclear | Low | Low | Medium |
| Thunyacharoen 2020 [46] | Low | Low | Low | Low | Low | High |
| Mistry 2021 [47] | Unclear | Low | Unclear | Low | Low | Medium |
| Induja 2022 [48] | Unclear | Low | Low | Low | Unclear | Medium |
| Shwetha 2022 [49] | Unclear | Low | Low | Low | Low | High |
| Adalarasan 2024 [50] | Unclear | Low | Low | Low | Low | High |
| Bandlamudi 2024 [51] | Unclear | Low | Low | Low | Low | High |
| Sakalem 2024 [52] | Unclear | Low | Low | Low | Low | High |
| Sujatha 2024 [53] | Unclear | Low | Low | Low | Low | High |
| Singh 2025 [54] | Unclear | Low | Low | Low | Low | High |
| Present study | Unclear | Low | Low | Low | Low | High |
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