Human Remains Identification Using Micro-CT, Chemometric and AI Methods in Forensic Experimental Reconstruction of Dental Patterns after Concentrated Sulphuric Acid Significant Impact
Abstract
:1. Introduction
- A human mandible with teeth (treated post-mortem) was degraded in 75% sulfuric acid, and the accompanying morphological and chemical changes were documented;
- CBCT and micro-CT technologies were used for the 3D reconstruction of dental patterns and descriptive morphological evaluation;
- ATR-FTIR spectroscopy was utilized to investigate the changes in dental restorations;
- The advanced AI–CNN algorithm was utilized for automated mandible segmentation;
- This research provides an unprecedented 3D morphological set of four stages of degradation of human mandibular bone and teeth presented in five different regions.
2. Materials and Methods
2.1. Materials
2.1.1. The Bone of Human Mandible with Teeth
2.1.2. Various Dental Materials
- Dental amalgam—Ana 2000 capsules non-gamma-two, extra-high copper (containing 43% silver, 26.1% copper, 30.8% tin);
- Glass ionomer—GC FUJI IX GP wear-resistant multipurpose (containing powder: 95% Fluro alumino silicate glass, 5% Polyacrylic acid powder; liquid: 40% Polyacrylic acid and tartaric acid, 50% distilled water, 10% Polybasic carboxylic acid);
- Dental composite—Neo Spectra ST (containing methacrylate-modified polysiloxane, dimethacrylate resins, fluorescent pigment, UV stabilizer, Camphorquinone, Ethyl-4 (dimethylamino)benzoate, Bis (4-methyl-phenyl) iodonium hexafluorophosphate, Barium–aluminium–borosilicate glass, Ytterbium fluoride, iron-oxide pigments and titanium-oxide pigments, according to shade). Prime and Bond Universal were used as an adhesive system in the dental filling/restorations with a composite.
2.2. Methods
- The 2D shape of each dental filling was extracted graphically from the panoramic X-ray 2D image;
- The outer contours and inner contours with shades of gray gradient were identified, thus creating a unique grayscale image pattern with contours;
- The 3D-CBCT dental fillings were segmented and extracted from the tooth;
- The semitranslucent 3D model from the CBCT of each dental filling was transposed over each 2D unique grayscale image pattern with contours in supposed positions;
- In the basic match, a viewer’s perspective was adapted to achieve an exact match.
2.3. Digital Optical Scanning
2.4. CBCT Scanning
- -
- A panoramic exposure with the following settings and values: 2D panoramic, standard, patient size M = medium-sized adult, 67 kV, 11 mA, 15 s;
- -
- The 3D exposure was performed with the following settings: CBCT volume Ø100 × 100 in a high-definition (HD) mode, voxel size 150 μm;
- -
- Two pairs of OPG and CBCT were created. The first scan was before the teeth preparative treatment, and the final scan was after the dental filling/restoration.
2.5. STL Segmentation
2.6. Micro-CT Scanning
2.7. Acid Exposure
2.8. FTIR Spectroscopy
3. Results
3.1. Descriptive Morphological Evaluation Based on Micro-CT Analysis
3.2. Digital Matching and AI Implementation in CBCT Segmentation
3.3. ATR-FTIR Spectroscopy
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
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Time (h) | 0 | 6 | 24 | 96 |
---|---|---|---|---|
Volume 0 h (mm3) | Volume 6 h (mm3) | Volume 24 h (mm3) | Volume 96 h (mm3) | |
sample 32 | ||||
dentine | 190.29 | 185.1 | 170.5 | 110.95 |
percentage loss | 0.0% | −2.7% | −10.4% | −41.7% |
enamel | 12.81 | 8.56 | 7.64 | 2.03 |
percentage loss | 0.0% | −33.2% | −40.4% | −84.2% |
tooth | 203.1 | 193.7 | 178.12 | 112.98 |
percentage loss | 0.0% | −4.6% | −12.3% | −44.4% |
bone | 668.1 | 601.85 | 399.56 | 61.77 |
percentage loss | 0.0% | −9.9% | −40.2% | −90.8% |
sample 33 | 324.45 | 299.16 | 290.64 | 270.57 |
0.0% | −7.8% | −10.4% | −16.6% | |
Composite | 16.46 | 16.43 | 16.45 | 16.46 |
0.0% | −0.2% | −0.1% | 0.0% | |
sample 43 | ||||
glass ionomer | 11.57 | 1 | 3.65 | 0 |
0.0% | 1 | −68.5% | −100.0% | |
sample 47 | ||||
amalgam | 33.42 | 33.43 | 33.37 | 33.4 |
0.0% | 0.0% | −0.1% | −0.1% |
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Thurzo, A.; Jančovičová, V.; Hain, M.; Thurzo, M.; Novák, B.; Kosnáčová, H.; Lehotská, V.; Varga, I.; Kováč, P.; Moravanský, N. Human Remains Identification Using Micro-CT, Chemometric and AI Methods in Forensic Experimental Reconstruction of Dental Patterns after Concentrated Sulphuric Acid Significant Impact. Molecules 2022, 27, 4035. https://doi.org/10.3390/molecules27134035
Thurzo A, Jančovičová V, Hain M, Thurzo M, Novák B, Kosnáčová H, Lehotská V, Varga I, Kováč P, Moravanský N. Human Remains Identification Using Micro-CT, Chemometric and AI Methods in Forensic Experimental Reconstruction of Dental Patterns after Concentrated Sulphuric Acid Significant Impact. Molecules. 2022; 27(13):4035. https://doi.org/10.3390/molecules27134035
Chicago/Turabian StyleThurzo, Andrej, Viera Jančovičová, Miroslav Hain, Milan Thurzo, Bohuslav Novák, Helena Kosnáčová, Viera Lehotská, Ivan Varga, Peter Kováč, and Norbert Moravanský. 2022. "Human Remains Identification Using Micro-CT, Chemometric and AI Methods in Forensic Experimental Reconstruction of Dental Patterns after Concentrated Sulphuric Acid Significant Impact" Molecules 27, no. 13: 4035. https://doi.org/10.3390/molecules27134035
APA StyleThurzo, A., Jančovičová, V., Hain, M., Thurzo, M., Novák, B., Kosnáčová, H., Lehotská, V., Varga, I., Kováč, P., & Moravanský, N. (2022). Human Remains Identification Using Micro-CT, Chemometric and AI Methods in Forensic Experimental Reconstruction of Dental Patterns after Concentrated Sulphuric Acid Significant Impact. Molecules, 27(13), 4035. https://doi.org/10.3390/molecules27134035