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İmplantolojinin Çene Kemiğinde Neden Olduğu Termal ve Mekanik Gerilmelerin Sonlu Elemanlar Analizi için Yapay Sinir Ağı Tasarımı

Yıl 2022, Cilt: 38 Sayı: 2, 218 - 232, 23.08.2022

Öz

Primer iyileşme için implant yuvasının hazırlanması ve sağlıklı kemik gerekli olduğundan, kemikte oluşan mekanik ve ısıl hasarın önlenmesi kritik önem taşır. Bu nedenle cerrahi rehberler kullanılarak implant yuvası hazırlanırken klinik koşullarda ısı oluşumu kontrol altında tutulması gerekmektedir. Bu çalışmada, implant kaviteleri hazırlanırken oluşan termal ve mekanik gerilmelerin bilgisayar yazılımı ile tahmin edilmesi amaçlanmıştır. Klasik yöntemle dört farklı plot delici uç kullanılarak implant yuvası açılması esnasında çene kemiği çevresinde oluşan termal ve mekanik stres analizi Sonlu Elemanlar Metodu (FEM) kullanılarak yapılmıştır. Sayısal analizden elde edilen veriler kullanılarak gerçek zamanlı tahmin yapılmıştır. Tahmin analizi, sağlam ve uyarlanabilir bir yapıya sahip olan Uyarlamalı Ağ Tabanlı Bulanık Çıkarım Sistemleri (ANFIS) yaklaşımı ile yapılmıştır. ANFIS simülasyonundan elde edilen sonuçlar, Sonlu Elemanlar Metodu ile elde edilen sonuçlarla aynı davranışı gösterebilme yeteneği, sinirsel tahmincinin sistemin termal ve Von-Miss gerilim parametrelerini tahmin etmek için kullanılabileceğini göstermektedir. Bu çalışma, implant cerrahisi esnasındaki mekanik ve termal gerilme değişimlerinin yapay sinir ağları ile tahminini göstermektedir.

Kaynakça

  • Branemark, P.I.; Hansson, BO;Adell, R.; et al.Osseointegrated implants in the treatment of the edentulous jaw. Experience from a 10-year period. Scand J Plast Reconstr Surg Suppl 1977,16: 1-132.
  • Albrektsson, T.; Eriksson, A. Thermally induced bone necrosis in rabbits: relation to implant failure in humans. Clinical Orthopaedics and Related Research 1985, 195, 311-312.
  • Lundskog, J. Heat and Bone Tissue. An Experimental Investigation of the Thermal Properties of Bone and Threshold Levels for Thermal Injury. Journal of Plastic and Reconstructive Surgery 1972; 9, 1-80.
  • Eriksson, R.A.; Adell, R. Temperatures during for the placement of implants using the osseointegration technique. Journal of Oral & Maxillofacial Surgery 1986; 44(1), 4-7.
  • Eriksson, R.A.; Albrektsson, T. Temperature threshold levels for heat- induced bone tissue injury: a vital-microscopic study in the rabbit. The Journal of Prosthetic Dentistry 1983; Goteborg, 50(1), 101-107.
  • Bachus, K.N.; Rondina, M.T; Hutchinson, D.T. The effects of drilling force on cortical temperatures and their duration: an in vitro study. Medical Engineering & Physics 2000; 22: 685-69. https://doi.org/10.1016/S1350-4533(01)00016-9.
  • Sharawy, M.; Misch, C.E.; Weller, N.; et al. Heat generation during implant drilling: the significance of motor speed. Journal of Oral & Maxillofacial Surgery 2002; 60(10), 1160-1169. https://doi.org/10.1053/joms.2002.34992.
  • Şener, B.C.; Dergin, G.; Gürsoy, B.; et al. effects of irrigation temperature on heat control in vitro at different drilling depths. Clinical Oral Implants Research 2009; 20, 294-298. https://doi.org/10.1111/j.1600-0501.2008.01643.x.
  • Nieri, M.; Crescini, A.; Rotundo, R.; et al. Factors affecting the clinical approach to impacted maxillary canines: a bayesian network analysis. Am Orthod Dentofac Orthop 2010; 137:755‑62. https://doi.org/10.1016/j.ajodo.2008.08.028.
  • Miladinović, M.; Mihailović, B.; Janković, A.; et al.. Reasons for extraction obtained by artificial intelligence. Acta Fac Med Naissensis 2010;27:143‑58.
  • Sukegawa, S.; Kazumasa, Y.; Takeshi, H.; et al. Deep Neural Networks for Dental Implant System Classification. Biomolecules 2020; 10(7):984. doi: 10.3390/biom10070984.
  • Turgut, B. Examination of mechanical and thermal changes caused by implant application in the jawbone, Msc, Erciyes University, 2016.
  • Turgut, B.; Erdemir, D.; Altuntop, N. Examınatıon of mechanıcal and thermal varıatıons caused by the ımplantology ın the jawbone. International Conference on Advances in Mechanical Engineering 2016; 788-795.
  • Eskitaşcıoğlu G. Investigation of functional stress in different centric contact types in natural and prosthetic restorated teeth with structural analysis program, Phd, Ankara University, 1991.
  • İmiroğlu, H.İ.; Tosun, Z.; Kaymaz, İ.; et al. A New TMJ Implant Design. Süleyman Demirel University Journal of Engineering Sciences and Design 2014; 2(3), 199-210.
  • Huiskes, J. Some Fundamental Aspects Of Human Joint Replacement. Acta Orthopaedica 1980, 185, 44-108.
  • Alam, K.; Mitrofanov, A.V.; Silberschmidt, V.V. Thermal analysis of orthogonal cutting of cortical bone using finite element simulations. International Journal of Experimental and Computational Biomechanics 2010; 1(3).https://doi.org/10.1504/IJECB.2010.035259 .
  • Davidson, S.R.H.; James, D.F. Measurement of thermal conductivity of bovine cortical bone. Medical Engineering and Physics 2000; 22, 741-747. https://doi.org/10.1016/S1350-4533(01)00003-0.
  • Clattenburg, R.; Cohen, J. Thermal properties of cancellous bone, Journal of Biomedical Materials Research 1975; 9, 169-182.
  • http://silver.neep.wisc.edu/~lakes/BoneTrab.html .(Accessed on 20 June 2021).
  • Kopperdah, D.L.; Keaveny, T.M. Yield strain behavior of trabecular bone. Journal of Biomechanics 1998; 31: 601-608. https://doi.org/10.1016/S0021-9290(98)00057-8.
  • Tüfekçi, K.; Kayacan, R.; Kurbanoğlu, C. Investigation of the mechanical behavior of cortical bone sterilized by gamma radiation under dynamic load. Süleyman Demirel University Journal of Engineering Sciences and Design 2014; 2(3), 299-302.
  • Bevill, G.; Easley, S.K.; Keaveny, T.M. Side-artifact errors in yield strength and elastic modulus for human trabecular bone and their dependence on bone volume fraction and anatomic site. Journal of Biomechanics 2007; 40(15). https://doi.org/10.1016/j.jbiomech.2007.05.008.
  • http://www.asm.matweb.com. (Accessed on 20 June 2021).
  • http://www.matweb.com. (Accessed on 20 June 2021).
  • http://www.tasarimveimalat.com.( Accessed on 20 June 2021).
  • Bachir, O.; Zoubir, A.F. Adaptive neuro-fuzzy inference system based control of puma 600 robot manipulator. Int J Electr Comput Eng 2012; 2, 90–97.

Design of Neural Network Predictor for A Finite Element Analysis of Thermal and Mechanical Stresses Caused in the Jawbone of Implantology

Yıl 2022, Cilt: 38 Sayı: 2, 218 - 232, 23.08.2022

Öz

As implant cavity preparation and healthy bone are essential for primary healing, prevention of mechanical and thermal damage, which occurs at bone, is critical importance. So heat generation under clinical conditions must be kept under control while preparing implant cavity by using surgical guides. In this study, thermal and mechanical stresses were aimed to predict with computer software while drilling implant cavities. Thermal and mechanical stress analysis that occurs around the jawbone while drilling implant cavities by using plot drills of four different drills with a classical method was conducted by using Finite Elements Method (FEM). The real time estimation was made using data obtained from numerical analysis. The estimation analysis was performed with Adaptive-Network Based Fuzzy Inference Systems (ANFIS) approach that have a robust and adaptive structure. The results from the ANFIS simulation, the ability to demonstrate the same behavior as the results obtained with the Finite Element Method shows that neural predictor can be used to estimate the system's thermal and Von- Misses stresses parameters. This presentation shows the estimation of thermal and mechanical stresses changes during implant surgery with artificial intelligence.

Kaynakça

  • Branemark, P.I.; Hansson, BO;Adell, R.; et al.Osseointegrated implants in the treatment of the edentulous jaw. Experience from a 10-year period. Scand J Plast Reconstr Surg Suppl 1977,16: 1-132.
  • Albrektsson, T.; Eriksson, A. Thermally induced bone necrosis in rabbits: relation to implant failure in humans. Clinical Orthopaedics and Related Research 1985, 195, 311-312.
  • Lundskog, J. Heat and Bone Tissue. An Experimental Investigation of the Thermal Properties of Bone and Threshold Levels for Thermal Injury. Journal of Plastic and Reconstructive Surgery 1972; 9, 1-80.
  • Eriksson, R.A.; Adell, R. Temperatures during for the placement of implants using the osseointegration technique. Journal of Oral & Maxillofacial Surgery 1986; 44(1), 4-7.
  • Eriksson, R.A.; Albrektsson, T. Temperature threshold levels for heat- induced bone tissue injury: a vital-microscopic study in the rabbit. The Journal of Prosthetic Dentistry 1983; Goteborg, 50(1), 101-107.
  • Bachus, K.N.; Rondina, M.T; Hutchinson, D.T. The effects of drilling force on cortical temperatures and their duration: an in vitro study. Medical Engineering & Physics 2000; 22: 685-69. https://doi.org/10.1016/S1350-4533(01)00016-9.
  • Sharawy, M.; Misch, C.E.; Weller, N.; et al. Heat generation during implant drilling: the significance of motor speed. Journal of Oral & Maxillofacial Surgery 2002; 60(10), 1160-1169. https://doi.org/10.1053/joms.2002.34992.
  • Şener, B.C.; Dergin, G.; Gürsoy, B.; et al. effects of irrigation temperature on heat control in vitro at different drilling depths. Clinical Oral Implants Research 2009; 20, 294-298. https://doi.org/10.1111/j.1600-0501.2008.01643.x.
  • Nieri, M.; Crescini, A.; Rotundo, R.; et al. Factors affecting the clinical approach to impacted maxillary canines: a bayesian network analysis. Am Orthod Dentofac Orthop 2010; 137:755‑62. https://doi.org/10.1016/j.ajodo.2008.08.028.
  • Miladinović, M.; Mihailović, B.; Janković, A.; et al.. Reasons for extraction obtained by artificial intelligence. Acta Fac Med Naissensis 2010;27:143‑58.
  • Sukegawa, S.; Kazumasa, Y.; Takeshi, H.; et al. Deep Neural Networks for Dental Implant System Classification. Biomolecules 2020; 10(7):984. doi: 10.3390/biom10070984.
  • Turgut, B. Examination of mechanical and thermal changes caused by implant application in the jawbone, Msc, Erciyes University, 2016.
  • Turgut, B.; Erdemir, D.; Altuntop, N. Examınatıon of mechanıcal and thermal varıatıons caused by the ımplantology ın the jawbone. International Conference on Advances in Mechanical Engineering 2016; 788-795.
  • Eskitaşcıoğlu G. Investigation of functional stress in different centric contact types in natural and prosthetic restorated teeth with structural analysis program, Phd, Ankara University, 1991.
  • İmiroğlu, H.İ.; Tosun, Z.; Kaymaz, İ.; et al. A New TMJ Implant Design. Süleyman Demirel University Journal of Engineering Sciences and Design 2014; 2(3), 199-210.
  • Huiskes, J. Some Fundamental Aspects Of Human Joint Replacement. Acta Orthopaedica 1980, 185, 44-108.
  • Alam, K.; Mitrofanov, A.V.; Silberschmidt, V.V. Thermal analysis of orthogonal cutting of cortical bone using finite element simulations. International Journal of Experimental and Computational Biomechanics 2010; 1(3).https://doi.org/10.1504/IJECB.2010.035259 .
  • Davidson, S.R.H.; James, D.F. Measurement of thermal conductivity of bovine cortical bone. Medical Engineering and Physics 2000; 22, 741-747. https://doi.org/10.1016/S1350-4533(01)00003-0.
  • Clattenburg, R.; Cohen, J. Thermal properties of cancellous bone, Journal of Biomedical Materials Research 1975; 9, 169-182.
  • http://silver.neep.wisc.edu/~lakes/BoneTrab.html .(Accessed on 20 June 2021).
  • Kopperdah, D.L.; Keaveny, T.M. Yield strain behavior of trabecular bone. Journal of Biomechanics 1998; 31: 601-608. https://doi.org/10.1016/S0021-9290(98)00057-8.
  • Tüfekçi, K.; Kayacan, R.; Kurbanoğlu, C. Investigation of the mechanical behavior of cortical bone sterilized by gamma radiation under dynamic load. Süleyman Demirel University Journal of Engineering Sciences and Design 2014; 2(3), 299-302.
  • Bevill, G.; Easley, S.K.; Keaveny, T.M. Side-artifact errors in yield strength and elastic modulus for human trabecular bone and their dependence on bone volume fraction and anatomic site. Journal of Biomechanics 2007; 40(15). https://doi.org/10.1016/j.jbiomech.2007.05.008.
  • http://www.asm.matweb.com. (Accessed on 20 June 2021).
  • http://www.matweb.com. (Accessed on 20 June 2021).
  • http://www.tasarimveimalat.com.( Accessed on 20 June 2021).
  • Bachir, O.; Zoubir, A.F. Adaptive neuro-fuzzy inference system based control of puma 600 robot manipulator. Int J Electr Comput Eng 2012; 2, 90–97.
Toplam 27 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Buket Turgut 0000-0002-4953-4244

Aslı Durmuşoğlu 0000-0002-2797-1304

Çağlar Sevim 0000-0001-6456-5949

Necdet Altuntop 0000-0001-6708-1982

Erken Görünüm Tarihi 23 Ağustos 2022
Yayımlanma Tarihi 23 Ağustos 2022
Yayımlandığı Sayı Yıl 2022 Cilt: 38 Sayı: 2

Kaynak Göster

APA Turgut, B., Durmuşoğlu, A., Sevim, Ç., Altuntop, N. (2022). Design of Neural Network Predictor for A Finite Element Analysis of Thermal and Mechanical Stresses Caused in the Jawbone of Implantology. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi, 38(2), 218-232.
AMA Turgut B, Durmuşoğlu A, Sevim Ç, Altuntop N. Design of Neural Network Predictor for A Finite Element Analysis of Thermal and Mechanical Stresses Caused in the Jawbone of Implantology. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi. Ağustos 2022;38(2):218-232.
Chicago Turgut, Buket, Aslı Durmuşoğlu, Çağlar Sevim, ve Necdet Altuntop. “Design of Neural Network Predictor for A Finite Element Analysis of Thermal and Mechanical Stresses Caused in the Jawbone of Implantology”. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi 38, sy. 2 (Ağustos 2022): 218-32.
EndNote Turgut B, Durmuşoğlu A, Sevim Ç, Altuntop N (01 Ağustos 2022) Design of Neural Network Predictor for A Finite Element Analysis of Thermal and Mechanical Stresses Caused in the Jawbone of Implantology. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi 38 2 218–232.
IEEE B. Turgut, A. Durmuşoğlu, Ç. Sevim, ve N. Altuntop, “Design of Neural Network Predictor for A Finite Element Analysis of Thermal and Mechanical Stresses Caused in the Jawbone of Implantology”, Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi, c. 38, sy. 2, ss. 218–232, 2022.
ISNAD Turgut, Buket vd. “Design of Neural Network Predictor for A Finite Element Analysis of Thermal and Mechanical Stresses Caused in the Jawbone of Implantology”. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi 38/2 (Ağustos 2022), 218-232.
JAMA Turgut B, Durmuşoğlu A, Sevim Ç, Altuntop N. Design of Neural Network Predictor for A Finite Element Analysis of Thermal and Mechanical Stresses Caused in the Jawbone of Implantology. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi. 2022;38:218–232.
MLA Turgut, Buket vd. “Design of Neural Network Predictor for A Finite Element Analysis of Thermal and Mechanical Stresses Caused in the Jawbone of Implantology”. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi, c. 38, sy. 2, 2022, ss. 218-32.
Vancouver Turgut B, Durmuşoğlu A, Sevim Ç, Altuntop N. Design of Neural Network Predictor for A Finite Element Analysis of Thermal and Mechanical Stresses Caused in the Jawbone of Implantology. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi. 2022;38(2):218-32.

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