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Digital Scans and Human Identification

July 9, 2021
by Botond Simon, DMD; Ajang Armin Farid, DMD, FO; George Freedman, BSc, DDS; Janos Vag, DMD, PhD


Background
The exponential growth of digital technology in dentistry is inherently accompanied by a significant expansion of 2D and 3D dental image records. Traditional stone models are impractical to keep long-term due to storage volume and fragility.

Comprehensive and accurate models offer an excellent record of the preoperative dentition for the complete restoration of a smile that matches the original1,2. The longer-term storage of dental models facilitates resolving legal cases, and might aid bite mark analysis in some criminal cases.3 Yet another application of dental models is for human identification. In addition to DNA and fingerprints, dental examination is a primary tool for disaster victim identification (DVI).4,5 Dental models that are discarded or lost may deprive biologically driven oral rehabilitation of historical tooth, bite, and bone reference points, and may hamper positive identification.

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Population-wide databases for fingerprints6,7 and DNA8,9 are limited and very fragmented. After the 2004 tsunami disaster in Thailand, 46% of the victims were identified by dental records, as compared to only 19% by DNA and 34% by fingerprints. The dental identification method is an analogous visual comparison of the ante- and post-mortem dental records.10,11 The basis of this concept is that dental treatments are always very specific and unique.12,13 To confuse matters somewhat, teeth are continually impacted by abrasion, disease, trauma, and dental treatment. Thus, the available ante-mortem data might not correlate well to the post-mortem data. Furthermore, treatment notation and information are not standardized, and it is exceedingly difficult to run an automatic search in a large, fragmented database.

Identifying the victim’s dentist, or, at the very least, the area where the victim was treated, is a mandatory prerequisite for a DVI search. Antemortem dental records can be very challenging if no other victim information is available. In fact, younger patients may have only orthodontic records. The search process can be accelerated dramatically by accessing the ever-increasing number of digital scans and cloud-based data storage systems.

Digital dental records must be retained, depending on national regulations, from years to decades.14,15 Thus, digital dental records open new pathways for DVI. The logical next step is to find oral cavity characteristics with universality, uniqueness, invariability (stable throughout the life), and ease of access.

Monozygotic (MZ) twins cannot be distinguished by DNA analysis16 and they look very similar (phenotypes). Hence, one way to prove the uniqueness of an identification method is its ability to reliably distinguish MZ twins. It has recently been revealed that palatal morphology (palatal vault and surface texture) can differentiate MZ twins through intraoral scans.17 Rugoscopy (also known as palatoscopy, calcorrugoscopy) is based on the difference in palatal rugae pattern, and can distinguish among ethnic and race groups, offering great assistance during DVI.18-25 The palate is more resistant to burn deformation injury when compared to the skin.26 It is stable over time and little varied after orthodontic treatment. 27-30

Objective
The aim of this pilot study was to compare teeth and palate uniqueness using the intraoral scans (IOS) of MZ twins.

Methods
Three MZ pairs, ages 17, 22, and 26 were enrolled in the study. The complete maxillary arch, including the palate, was scanned by the Emerald intraoral scanner (Planmeca, Helsinki, Finland, software version: Romexis 5.2.1). The palate was carefully isolated on each scan and was exported to a separate model. The left maxillary first molar was intact in five subjects and filled in one subject. The left maxillary second molar was intact in each subject. These two teeth were segmented, and the images were exported to respective new files.

Palatal digital models and tooth digital models were aligned between nonrelatives (Fig. 1) and between siblings. (Fig. 2) The superimpositions were made using the GOM Inspect software (GOM GmbH, Germany), utilizing the local best-fit algorithm. The mean absolute deviations were calculated for each superimposition with the surface comparison tool. The data were statistically analyzed by the generalized linear mixed method using SPSS (IBM SPSS Statistics for Windows, Version 27.0., United States).

Fig. 1

 The surface comparison maps of nonrelative subjects of the maxillary first molars, of the maxillary second molars, and of the palate. None of the teeth had restorations. Deep red and blue areas indicate distance deviation higher than the range of the color scale.

The surface comparison maps of nonrelative subjects of the maxillary first molars, of the maxillary second molars, and of the palate. None of the teeth had restorations. Deep red and blue areas indicate distance deviation higher than the range of the color scale.

Fig. 2

 The digital cast of the two siblings (green and blue) and the surface comparison (color map). The first row shows two maxillary first molars of the 22-year-old MZ pair (pair #3). The teeth have occlusal restorations resulting in increased deviation (red arrows). The second row shows two maxillary second molars of pair #3. These teeth have no restorations or abrasions. However, the occlusal surface morphology is quite different between siblings. The third row shows two maxillary first molars of 19-year-old MZ pairs (pair #1). There are no restorations, and the cusp shapes are very similar. However, a sign of abrasion can be seen in sibling A (blue), creating an increased deviation between scans (red arrows). The fourth row shows the palate of pair #3. Please note that the color range in the palatal is three times more than in the tooth map.

The digital cast of the two siblings (green and blue) and the surface comparison (color map). The first row shows two maxillary first molars of the 22-year-old MZ pair (pair #3). The teeth have occlusal restorations resulting in increased deviation (red arrows). The second row shows two maxillary second molars of pair #3. These teeth have no restorations or abrasions. However, the occlusal surface morphology is quite different between siblings. The third row shows two maxillary first molars of 19-year-old MZ pairs (pair #1). There are no restorations, and the cusp shapes are very similar. However, a sign of abrasion can be seen in sibling A (blue), creating an increased deviation between scans (red arrows). The fourth row shows the palate of pair #3. Please note that the color range in the palatal is three times more than in the tooth map.

Results and Discussion
The mean absolute deviations (± the standard deviation) of the first and second molars between non-relatives (Fig. 1) were not significantly different (0.259±0.039 mm, 0.277±0.037 mm, p=0.733), but the mean absolute deviation of the palates was significantly higher (1.061±0.314 mm, p<0.001). Previous studies found that a single tooth’s trueness is between 14-72µm.31,32,33 The trueness of the palate was reported between 80.5μm34 and 130.5μm.35 Accordingly, the intraoral scan can distinguish between non-relative people based on either tooth or palate imagery.

Molars in MZ siblings look very similar (Fig. 2 first three rows). The mean absolute first molar deviation between siblings was significantly lower than the second molar deviation (0.087±0.032 mm, 0.137±0.038 mm, p<0.05). Notwithstanding that one of the first molars of the MZ pairs had restorations, these values were significantly (p<0.001) lower than the deviations between non-relatives. Since these values are not much higher than the IOS trueness, they jeopardize the confidence in MZ twin identification. The palatal deviation between siblings was 3-4 times higher (0.393±0.079 mm, p<0.001) than the teeth deviation. Although, the deviation is significantly (p<0.001) lower than the values between non-relatives, it was ten times higher than the precision (i.e., reproducibility, 35µm) of a recent IOS.17 It was three times more than the trueness of the IOS regarding the palate.33,34

Along with the present findings, there is increasing evidence that the 3D digital palatal model could serve as a highly reliable tool for human identifications30,36 and for distinguishing between MZ twins.17,37 Recent and ongoing developments in IOS technology will further improve the reliability. Digital casts of twins can also be used to study genetic and environmental factors in odontogenesis38. It is of great importance that dentists should not discard digital models after completion of the dental work. These archived models are very useful for legal, forensic, and rehabilitation purposes, now and far into the future.

Oral Health welcomes this original article.

References

  1. Renne, W. G., Z. P. Evans, A. Mennito and M. Ludlow (2017). “A novel technique for reference point generation to aid in intraoral scan alignment.” J Esthet Restor Dent 29(6): 391-395.
  2. Revilla-Leon, M., L. Raney, W. Piedra-Cascon, J. Barrington, A. Zandinejad and M. Ozcan (2020). “Digital workflow for an esthetic rehabilitation using a facial and intraoral scanner and an additive manufactured silicone index: A dental technique.” J Prosthet Dent 123(4): 564-570.
  3. Khatri, M., M. J. Daniel and S. V. Srinivasan (2013). “A comparative study of overlay generation methods in bite mark analysis.” J Forensic Dent Sci 5(1): 16-21.
  4. Interpool. “Disaster victim identification “, from https://www.interpol.int/How-we-work/Forensics/Disaster-Victim-Identification-DVI.
  5. Tsokos, M., R. Lessig, C. Grundmann, S. Benthaus and O. Peschel (2006). “Experiences in tsunami victim identification.” Int J Legal Med 120(3): 185-187.
  6. Peralta, D., I. Triguero, S. García, F. Herrera and J. M. Benitez (2016). “DPD-DFF: A dual phase distributed scheme with double fingerprint fusion for fast and accurate identification in large databases.” Information Fusion 32: 40-51.
  7. Thalesgroup.com. (2021, 06 March 2021). “Biometrics: definition, trends, use cases, laws and latest news.” from https://www.thalesgroup.com/en/markets/digital-identity-and-security/government/inspired/biometrics.
  8. Smith, M. E. (2006). “Let’s Make the DNA Identification Database as Inclusive as Possible.” The Journal of Law, Medicine & Ethics 34(2): 385-389.
  9. Amankwaa, A. O. and C. McCartney (2018). “The UK National DNA Database: Implementation of the Protection of Freedoms Act 2012.” Forensic Sci Int 284: 117-128.
  10. Miki, Y., C. Muramatsu, T. Hayashi, X. Zhou, T. Hara, A. Katsumata and H. Fujita (2017). “Classification of teeth in cone-beam CT using deep convolutional neural network.” Comput Biol Med 80: 24-29.
  11. Alsalamah, S. and E. Nuzzolese (2020). “Promising Blockchain Technology Applications and Use Case Designs for the Identification of Multinational Victims of Mass Disasters.” Frontiers in Blockchain 3.
  12. Pretty, I. A. and D. Sweet (2001). “A look at forensic dentistry—Part 1: The role of teeth in the determination of human identity.” Br Dent J 190(7): 359-366.
  13. Ata-Ali, J. and F. Ata-Ali (2014). “Forensic dentistry in human identification: A review of the literature.” J Clin Exp Dent 6(2): e162-167.
  14. Charangowda, B. K. (2010). “Dental records: An overview.” J Forensic Dent Sci 2(1): 5-10.
  15. Devadiga, A. (2014). “What’s the deal with dental records for practicing dentists? Importance in general and forensic dentistry.” Journal of forensic dental sciences 6(1): 9-15.
  16. Bell, J. T. and T. D. Spector (2011). “A twin approach to unraveling epigenetics.” Trends Genet 27(3): 116-125.
  17. Simon, B., L. Liptak, K. Liptak, A. D. Tarnoki, D. L. Tarnoki, D. Melicher and J. Vag (2020). “Application of intraoral scanner to identify monozygotic twins.” BMC Oral Health 20(1): 268.
  18. Hermosilla Venegas, V., J. San Pedro Valenzuela, M. Cantín López and I. C. Suazo Galdames (2009). “Palatal Rugae: Systematic Analysis of its Shape and Dimensions for Use in Human Identification.” International Journal of Morphology 27: 819-825.
  19. Bajracharya, D., A. Vaidya, S. Thapa and S. Shrestha (2013). “Palatal rugae pattern in nepalese subjects.” Orthodontic Journal of Nepal 3(2): 36-39.
  20. Azab, S. M. S., R. Magdy and M. A. Sharaf El Deen (2016). “Patterns of palatal rugae in the adult Egyptian population.” Egyptian Journal of Forensic Sciences 6(2): 78-83.
  21. Suhartono, A. W., K. Syafitri, A. D. Puspita, N. Soedarsono, F. P. Gultom, P. T. Widodo, M. Luthfi and E. I. Auerkari (2016). “Palatal rugae patterning in a modern Indonesian population.” Int J Legal Med 130(3): 881-887.
  22. Kommalapati, R. K., D. Katuri, K. K. Kattappagari, L. P. C. Kantheti, R. B. Murakonda, C. S. Poosarla, R. T. Chitturi, S. R. Gontu and V. R. R. Baddam (2017). “Systematic Analysis of Palatal Rugae Pattern for Use in Human Identification between Two Different Populations.” Iran J Public Health 46(5): 602-607.
  23. Saadeh, M., J. G. Ghafari, R. V. Haddad and F. Ayoub (2017). “Palatal rugae morphology in an adult mediterranean population.” J Forensic Odontostomatol 35(1): 21-32.
  24. Barbo, B., F. Azeredo and L. Menezes (2018). “Assessment of Size, Shape, and Position of Palatal Rugae: A Preliminary Study.” Oral Health and Dental Studies 1.
  25. Basman, R., A. Puspita, R. Achmad, A. Suhartono and E. Auerkari (2018). Palatal rugae comparison between ethnic Javanese and non-Javanese. Journal of Physics: Conference Series, IOP Publishing.
  26. Muthusubramanian, M., K. S. Limson and R. Julian (2005). “Analysis of rugae in burn victims and cadavers to simulate rugae identification in cases of incineration and decomposition.”
    J Forensic Odontostomatol 23(1): 26-29.
  27. Bailey, L. T., A. Esmailnejad and M. A. Almeida (1996). “Stability of the palatal rugae as landmarks for analysis of dental casts in extraction and nonextraction cases.” Angle Orthod 66(1): 73-78.
  28. Abdel-Aziz, H. M. and N. E. Sabet (2001). “Palatal rugae area: a landmark for analysis of pre- and post-orthodontically treated adult Egyptian patients.” East Mediterr Health J 7(1-2): 60-66.
  29. Ali, B., A. Shaikh and M. Fida (2016). “Stability of Palatal Rugae as a Forensic Marker in Orthodontically Treated Cases.” J Forensic Sci 61(5): 1351-1355.
  30. Lanteri, V., G. Cossellu, M. Farronato, A. Ugolini, R. Leonardi, F. Rusconi, S. De Luca, R. Biagi and C. Maspero (2020). “Assessment of the Stability of the Palatal Rugae in a 3D-3D Superimposition Technique Following Slow Maxillary Expansion (SME).” Sci Rep 10(1): 2676.
  31. Lee, J. J., I. D. Jeong, J. Y. Park, J. H. Jeon, J. H. Kim and W. C. Kim (2017). “Accuracy of single-abutment digital cast obtained using intraoral and cast scanners.” J Prosthet Dent 117(2): 253-259.
  32. Uhm, S. H., J. H. Kim, H. B. Jiang, C. W. Woo, M. Chang, K. N. Kim, J. M. Bae and S. Oh (2017). “Evaluation of the accuracy and precision of four intraoral scanners with 70% reduced inlay and four-unit bridge models of international standard.” Dent Mater J 36(1): 27-34.
  33. Vag, J., Z. Nagy, B. Simon, A. Mikolicz, E. Kover, A. Mennito, Z. Evans and W. Renne (2019). “A novel method for complex three-dimensional evaluation of intraoral scanner accuracy.” Int J Comput Dent 22(3): 239-249.
  34. Zhongpeng, Y., X. Tianmin and J. Ruoping (2019). “Deviations in palatal region between indirect and direct digital models: an in vivo study.” BMC Oral Health 19(1): 66.
  35. Gan, N., Y. Xiong and T. Jiao (2016). “Accuracy of Intraoral Digital Impressions for Whole Upper Jaws, Including Full Dentitions and Palatal Soft Tissues.” PLoS ONE 11(7): e0158800.
  36. Gibelli, D., D. De Angelis, V. Pucciarelli, F. Riboli, V. F. Ferrario, C. Dolci, C. Sforza and C. Cattaneo (2018). “Application of 3D models of palatal rugae to personal identification: hints at identification from 3D-3D superimposition techniques.” Int J Legal Med 132(4): 1241-1245.
  37. Taneva, E., C. Evans and G. Viana (2017). “3D Evaluation of Palatal Rugae in Identical Twins.” Case Rep Dent 2017: 2648312.
  38. Smith, R. N., G. Townsend, K. Chen and A. Brook (2009). “Synetic superimposition of dental 3D data: application in twin studies.” Front Oral Biol 13: 142-147.

About the Author

Dr. Ajang Armin Farid is the chief forensic odontologist of Hungary’s Interpol DVI dental unit, and member of Interpol’s DVI Odontology sub-working group. He is a Fellow of the American Academy of Forensic Sciences and a Member of the American Society of Forensic Odontology. He lectures at Semmelweis Medical University and maintains a private practice.

 

Dr. Botond Simon is a PhD student at Semmelweis University. He is a specialist in Restorative Dentistry and Prosthodontists. He is co-founder of Scrunch Ltd., an early-stage start-up company for providing personalized online dental care for patients. Dr Simon maintains a private practice.

 

 

Dr. George Freedman is a founder and past president of the American Academy of Cosmetic Dentistry, cofounder of the Canadian Academy for Esthetic Dentistry, Diplomate of the American Board of Aesthetic Dentistry and Regent of the IADFE. His most recent textbook is "Contemporary Esthetic Dentistry" (Elsevier). Dr. Freedman sits on Oral Health's Editorial Board (Dental Materials and Technology), is a REALITY Team Member and lectures internationally on dental esthetics and technology. A McGill graduate, Dr. Freedman maintains a private practice limited to Esthetic Dentistry in Markham, ON, Canada.Dr. George Freedman a founder and past president, AACD, co-founder CAED, Regent and Fellow, International Academy for Dental Facial Esthetics, Diplomate and Chair, American Board of Aesthetic Dentistry, is Adjunct Professor of Dental Medicine, Western University, Pomona CA and Professor/Program Director, BPP University, London, UK, MClinDent Programme in Restorative and Cosmetic Dentistry.

 

János Vág is Associate Professor and Head, Department of Conservative Dentistry, Semmelweis University, Hungary. He is a Specialist in Restorative Dentistry, Endodontics, and Prosthodontists. He is co-founder of Scrunch Ltd., a start-up company for providing personalized online dental care for patients.