Skull Thickness Calculation Using Thermal Analysis and Finite Elements
Abstract
:1. Introduction
2. Materials and Methods
2.1. Generating Solid 3D Models
2.2. Mesh Generation Using the Finite Element Method
2.3. Thermal Analysis of 3D Solid Models
2.4. Firat University Neurosurgery Dataset (FUND)
3. Proposed Skull Thickness Analysis Method
- 1-
- Raw skull CT images are taken in DICOM format.
- 2-
- DICOM data are transformed into computer-based design models for analysis. In this transformation, the data are recorded in STL file format.
- 3-
- Some undesired bone particle regions obtained from CT should be removed. The STL files are cleared of errors caused by CT scanning in the SpaceClaim software, and these images are thereby made ready for analysis. Thus, the skull image is prepared for the mesh production process. Mesh production is performed using the appropriate number of nodes and elements. Thus, the meshed skull image is suitable for thermal analysis.
- 4-
- In this step, steady-state thermal analysis is carried out. Certain temperature values are applied to the inner and outer surfaces of the skull. In this paper, the internal temperature value is denoted as 0 °C. When the inner surface temperature value is set at 0 °C, the inner–outer temperature difference will automatically be equal to the outer surface temperature value. The temperature values on the outer surface of the skull images are taken along two perpendicular curves.
- 5-
- When obtaining bone thickness using temperature information, the distance between any skull point along the perpendicular curves and the closest inner surface point to this point is used. By using the Euclidean distance between these two points, the bone thickness information of the relevant point can be obtained.
4. Experimental Results
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
CT | Computed tomography |
FEM | Finite element method |
3D | Three-dimensional |
DICOM | Digital imaging and communications in medicine |
STL | Stereolithography |
FUND | Firat University neurosurgery dataset |
References
- Kung, W.-M.; Tzeng, I.-S.; Lin, M.-S. Three-Dimensional CAD in Skull Reconstruction: A Narrative Review with Focus on Cranioplasty and Its Potential Relevance to Brain Sciences. Appl. Sci. 2020, 10, 1847. [Google Scholar] [CrossRef] [Green Version]
- Flores-Justa, A.; Baldoncini, M.; Pérez Cruz, J.C.; Sánchez Gonzalez, F.; Martínez, O.A.; González-López, P.; Campero, Á. White Matter Topographic Anatomy Applied to Temporal Lobe Surgery. World Neurosurg. 2019, 132, e670–e679. [Google Scholar] [CrossRef] [PubMed]
- Wang, S.-H.; Ko, Y.-C.; Tsai, M.-T.; Fuh, L.-J.; Huang, H.-L.; Shen, Y.-W.; Hsu, J.-T. Can Male Patient’s Age Affect the Cortical Bone Thickness of Jawbone for Dental Implant Placement? A Cohort Study. Int. J. Environ. Res. Public Health 2021, 18, 4284. [Google Scholar] [CrossRef]
- Frank, K.; Gotkin, R.H.; Pavicic, T.; Morozov, S.P.; Gombolevskiy, V.A.; Petraikin, A.V.; Movsisyan, T.V.; Koban, K.C.; Hladik, C.; Cotofana, S. Age and Gender Differences of the Frontal Bone: A Computed Tomographic (CT)-Based Study. Aesthet. Surg. J. 2019, 39, 699–710. [Google Scholar] [CrossRef] [PubMed]
- Tornberg, A.; Jacobsson, L. Care and consequences of traumatic brain injury in Neolithic Sweden: A case study of ante mortem skull trauma and brain injury addressed through the bioarchaeology of care. Int. J. Osteoarchaeol. 2018, 28, 188–198. [Google Scholar] [CrossRef]
- Yellinek, S.; Cohen, A.; Merkin, V.; Shelef, I.; Benifla, M. Clinical significance of skull base fracture in patients after traumatic brain injury. J. Clin. Neurosci. 2016, 25, 111–115. [Google Scholar] [CrossRef]
- Modi, Y.K.; Sanadhya, S. Design and additive manufacturing of patient-specific cranial and pelvic bone implants from computed tomography data. J. Braz. Soc. Mech. Sci. Eng. 2018, 40, 503. [Google Scholar] [CrossRef]
- Lillie, E.M.; Urban, J.E.; Lynch, S.K.; Weaver, A.A.; Stitzel, J.D. Evaluation of Skull Cortical Thickness Changes with Age and Sex from Computed Tomography Scans. J. Bone Miner. Res. 2016, 31, 299–307. [Google Scholar] [CrossRef] [Green Version]
- Kidder, J.H.; Durband, A.C. A re-evaluation of the metric diversity within Homo erectus. J. Hum. Evol. 2004, 46, 297–313. [Google Scholar] [CrossRef]
- Yang, S.; Zhao, Y.; Liao, M.; Zhang, F. An Unsupervised Learning-Based Multi-Organ Registration Method for 3D Abdominal CT Images. Sensors 2021, 21, 6254. [Google Scholar] [CrossRef]
- Ebraheim, N.A.; Liu, J.; Patil, V.; Sanford, C.G.; Crotty, M.J.; Haman, S.P.; Yeasting, R.A. Evaluation of skull thickness and insertion torque at the halo pin insertion areas in the elderly: A cadaveric study. Spine J. 2007, 7, 689–693. [Google Scholar] [CrossRef] [PubMed]
- Imagawa, N.; Inoue, K.; Matsumoto, K.; Omori, M.; Yamamoto, K.; Nakajima, Y.; Kato-Kogoe, N.; Nakano, H.; Le, P.T.M.; Yamaguchi, S.; et al. Histological Evaluation of Porous Additive-Manufacturing Titanium Artificial Bone in Rat Calvarial Bone Defects. Materials 2021, 14, 5360. [Google Scholar] [CrossRef] [PubMed]
- Sommer, H.J.; Eckhardt, R.B.; Shiang, T.Y. Superquadric modeling of cranial and cerebral shape and asymmetry. Am. J. Phys. Anthropol. 2006, 129, 189–195. [Google Scholar] [CrossRef] [PubMed]
- Alexandratou, I.; Patrikelis, P.; Messinis, L.; Alexoudi, A.; Verentzioti, A.; Stefanatou, M.; Nasios, G.; Panagiotopoulos, V.; Gatzonis, S. Long-Term Neuropsychological Outcomes Following Temporal Lobe Epilepsy Surgery: An Update of the Literature. Healthcare 2021, 9, 1156. [Google Scholar] [CrossRef] [PubMed]
- Antonakakis, M.; Schrader, S.; Aydin, Ü.; Khan, A.; Gross, J.; Zervakis, M.; Rampp, S.; Wolters, C.H. Inter-Subject Variability of Skull Conductivity and Thickness in Calibrated Realistic Head Models. Neuroimage 2020, 223, 117353. [Google Scholar] [CrossRef] [PubMed]
- Harvey, L.A.; Close, J.C.T. Traumatic brain injury in older adults: Characteristics, causes and consequences. Injury 2012, 43, 1821–1826. [Google Scholar] [CrossRef]
- Hollensteiner, M.; Fürst, D.; Augat, P.; Schrödl, F.; Esterer, B.; Gabauer, S.; Hunger, S.; Malek, M.; Stephan, D.; Schrempf, A. Characterization of an artificial skull cap for cranio-maxillofacial surgery training. J. Mater. Sci. Mater. Med. 2018, 29, 135. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Smith, K.; Politte, D.; Reiker, G.; Nolan, T.S.; Hildebolt, C.; Mattson, C.; Tucker, D.; Prior, F.; Turovets, S.; Larson-Prior, L.J. Automated measurement of pediatric cranial bone thickness and density from clinical computed tomography. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, San Diego, CA, USA, 28 August–1 September 2012; Volume 2012, pp. 4462–4465. [Google Scholar]
- Calderbank, T.; Morgan, B.; Rutty, G.N.; Brough, A. An investigation of juvenile cranial thickness-analysis of skull morphometrics across the complete developmental age range. J. Forensic Radiol. Imaging 2016, 4, 70–75. [Google Scholar] [CrossRef] [Green Version]
- Delye, H.; Clijmans, T.; Mommaerts, M.Y.; Sloten, J.V.; Goffin, J. Creating a normative database of age-specific 3D geometrical data, bone density, and bone thickness of the developing skull: A pilot study. J. Neurosurg. Pediatr. 2015, 16, 687–702. [Google Scholar] [CrossRef] [Green Version]
- Hildebrand, T.; Rüegsegger, P. A new method for the model-independent assessment of thickness in three-dimensional images. J. Microsc. 1997, 185, 67–75. [Google Scholar] [CrossRef]
- Deffieux, T.; Konofagou, E.E. Numerical study of a simple transcranial focused ultrasound system applied to blood-brain barrier opening. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 2010, 57, 2637–2653. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lynnerup, N. Cranial thickness in relation to age, sex and general body build in a Danish forensic sample. Forensic Sci. Int. 2001, 117, 45–51. [Google Scholar] [CrossRef]
- Shahzad Masood, M.; Ahmad, A.; Alim Mufti, R. Unconventional Modeling and Stress Analysis of Femur Bone under Different Boundary Condition. Int. J. Sci. Eng. Res. 2013, 4, 293–296. [Google Scholar]
- Coats, B.; Margulies, S.S. Material properties of human infant skull and suture at high rates. J. Neurotrauma 2006, 23, 1222–1232. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Baumer, T.G.; Passalacqua, N.V.; Powell, B.J.; Newberry, W.N.; Fenton, T.W.; Haut, R.C. Age-dependent fracture characteristics of rigid and compliant surface impacts on the infant skull—A porcine model. J. Forensic Sci. 2010, 55, 993–997. [Google Scholar] [CrossRef]
- Gzik, M.; Wolański, W.; Tejszerska, D.; Gzik-Zroska, B.; Koźlak, M.; Larysz, D.; Mandera, M. Application of 3D modeling and modern visualization technique to neurosurgical trigonocephaly correction in children. IFMBE Proc. 2009, 25, 68–71. [Google Scholar] [CrossRef]
- Ramadan, A.N.; Jing, P.; Zhang, J.; Zohny, H.N.E.-D. Numerical Analysis of Additional Stresses in Railway Track Elements Due to Subgrade Settlement Using FEM Simulation. Appl. Sci. 2021, 11, 8501. [Google Scholar] [CrossRef]
- Giuliano, G.; Polini, W. Strain State in Metal Sheet Axisymmetric Stretching with Variable Initial Thickness: Numerical and Experimental Results. Appl. Sci. 2021, 11, 8265. [Google Scholar] [CrossRef]
- Li, W.; Chen, X.; Wang, H.; Chan, A.H.C.; Cheng, Y. Evaluating the Seismic Capacity of Dry-Joint Masonry Arch Structures via the Combined Finite-Discrete Element Method. Appl. Sci. 2021, 11, 8725. [Google Scholar] [CrossRef]
- Ahmed, M.; Singh, D.; AlQadhi, S.; Alrefae, M.A. Improvement of the Zienkiewicz–Zhu Error Recovery Technique Using a Patch Configuration. Appl. Sci. 2021, 11, 8120. [Google Scholar] [CrossRef]
- Chen, Y.; Pani, M.; Taddei, F.; Mazzà, C.; Li, X.; Viceconti, M. Large-scale finite element analysis of human cancellous bone tissue micro computer tomography data: A convergence study. J. Biomech. Eng. 2014, 136, 101013. [Google Scholar] [CrossRef]
- Tiede, U.; Bomans, M.; Höhne, K.H.; Pommert, A.; Riemer, M.; Schiemann, T.; Schubert, R.; Lierse, W. A computerized three-dimensional atlas of the human skull and brain. AJNR. Am. J. Neuroradiol. 1993, 14, 551–561. [Google Scholar] [CrossRef]
- Semeniuk, B.P.; Göransson, P.; Dazel, O. Dynamic equations of a transversely isotropic, highly porous, fibrous material including oscillatory heat transfer effects. J. Acoust. Soc. Am. 2019, 146, 2540. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Beckman, W.A. Solar Engineering of Thermal Processes; John Wiley & Sons: Hoboken, NJ, USA, 2013; ISBN 9780470873663. [Google Scholar]
- Webster, J.G. Mechanical Variables Measurement: Solid, Fluid, and Thermal; CRC Press: Boca Raton, FL, USA, 2000. [Google Scholar]
- Sagar, M.V.; Suresh, N. Thermal Analysis of Engine Cylinder with Fins by using ANSYS Workbench. Int. J. Eng. Res. 2017, 6, 502–514. [Google Scholar] [CrossRef]
- Wang, H.Y.; Yang, M.; Stufken, J. Information-Based Optimal Subdata Selection for Big Data Linear Regression. J. Am. Stat. Assoc. 2019, 114, 393–405. [Google Scholar] [CrossRef]
- Shafiq-Ul-Hassan, M.; Zhang, G.G.; Latifi, K.; Ullah, G.; Hunt, D.C.; Balagurunathan, Y.; Abdalah, M.A.; Schabath, M.B.; Goldgof, D.G.; Mackin, D.; et al. Intrinsic dependencies of CT radiomic features on voxel size and number of gray levels. Med. Phys. 2017, 44, 1050–1062. [Google Scholar] [CrossRef]
- Ansys 2020 R1. Available online: https://www.ansys.com/products/release-highlights (accessed on 28 October 2021).
- Grothe, T.; Brockhagen, B.; Storck, J.L. Three-dimensional printing resin on different textile substrates using stereolithography: A proof of concept. J. Eng. Fiber. Fabr. 2020, 15, 1–7. [Google Scholar] [CrossRef]
- RadiAnt DICOM Viewer. Available online: https://www.radiantviewer.com/ (accessed on 28 October 2021).
- Ekşi, M.Ş.; Güdük, M.; Usseli, M.I. Frontal Bone is Thicker in Women and Frontal Sinus is Larger in Men. J. Craniofac. Surg. 2021, 32, 1683–1684. [Google Scholar] [CrossRef] [PubMed]
- Möller, T.; Trumbore, B. Fast, minimum storage ray/triangle intersection. In Proceedings of the ACM SIGGRAPH 2005 Courses SIGGRAPH 2005, Los Angeles, CA, USA, 31 July–4 August 2005. [Google Scholar] [CrossRef]
- Jaroslaw Tuszynski Triangle/Ray Intersection—File Exchange—MATLAB Central. Available online: https://www.mathworks.com/matlabcentral/fileexchange/33073-triangle-ray-intersection (accessed on 22 August 2021).
Authors | Young’s Modulus (MPa) | Poisson Ratio | References |
---|---|---|---|
Coats and Margulies (2006) | 300 | 0.19 | [25] |
Baumer et al. (2009) | 238 | 0.20 | [26] |
Gzik et al. (2009) | 380 | 0.22 | [27] |
Model No. | Mesh Size (mm) | Node | Elements | Study Time |
---|---|---|---|---|
1 | 1 | 7635 | 1395 | 3 min, 8 s |
2 | 2 | 1435 | 213 | 1 min, 17 s |
3 | 3 | 637 | 80 | 0 min, 29 s |
Id | Gender | Age | Frames | PixelSpaceX | PixelSpaceY | PixelSpaceZ | Slice Thickness |
---|---|---|---|---|---|---|---|
1 | M | 16.00 | 742 | 0.546 | 0.546 | 0.5 | 0.5 |
2 | M | 16.00 | 305 | 0.488281 | 0.488281 | 0.625 | 0.625 |
3 | F | 12.00 | 292 | 0.582031 | 0.582031 | 0.625 | 0.625 |
4 | M | 14.00 | 766 | 0.546 | 0.546 | 0.5 | 0.625 |
5 | F | 15.00 | 769 | 0.546 | 0.546 | 0.5 | 0.5 |
6 | F | 16.00 | 303 | 0.492188 | 0.492188 | 0.625 | 0.625 |
7 | M | 14.00 | 296 | 0.488281 | 0.488281 | 0.625 | 0.625 |
8 | M | 13.00 | 650 | 0.546 | 0.546 | 0.5 | 0.5 |
9 | M | 15.00 | 423 | 0.466797 | 0.466797 | 0.5 | 0.625 |
10 | F | 11.00 | 288 | 0.488281 | 0.488281 | 0.625 | 0.625 |
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Calisan, M.; Talu, M.F.; Pimenov, D.Y.; Giasin, K. Skull Thickness Calculation Using Thermal Analysis and Finite Elements. Appl. Sci. 2021, 11, 10483. https://doi.org/10.3390/app112110483
Calisan M, Talu MF, Pimenov DY, Giasin K. Skull Thickness Calculation Using Thermal Analysis and Finite Elements. Applied Sciences. 2021; 11(21):10483. https://doi.org/10.3390/app112110483
Chicago/Turabian StyleCalisan, Mucahit, Muhammed Fatih Talu, Danil Yurievich Pimenov, and Khaled Giasin. 2021. "Skull Thickness Calculation Using Thermal Analysis and Finite Elements" Applied Sciences 11, no. 21: 10483. https://doi.org/10.3390/app112110483
APA StyleCalisan, M., Talu, M. F., Pimenov, D. Y., & Giasin, K. (2021). Skull Thickness Calculation Using Thermal Analysis and Finite Elements. Applied Sciences, 11(21), 10483. https://doi.org/10.3390/app112110483