Skip to content
2000
  1. Home
  2. A-Z Publications
  3. Current Medical Imaging
  4. Volume 20, Issue 1
  5. Article
Volume 20, Issue 1
  • ISSN: 1573-4056
  • E-ISSN: 1875-6603
file format pdf download PDF
side by side viewer icon HTML

Abstract

Background

Medical imaging plays a key role in neurosurgery; thereby, imaging and analysis of the soft and hard tissues during bone grinding is of paramount importance for neurosurgeons. Bone grinding, a minimally invasive operation in the field of neurosurgery amid osteotomy, has been used during brain cancer surgery.

Aims and Objectives

With increasing attention to neural tissue damage in machining operations, imaging of these neural tissues becomes vital and reducing temperature is imperative.

Methods

In the present study, a novel attempt has been made to perform the imaging of bone tissues during the bone grinding procedure and further investigate the relationship between rotational speed, feed rate, depth of cut with cutting forces, and temperature. The role of cutting forces and temperature has been addressed as per the requirements of neurosurgeons. Firstly, a three-factor, three-level design was constructed with a full factorial design. Regression models were employed to construct the models between input parameters and response characteristics. Medical imaging techniques were used to perform a thorough analysis of thermal necrosis and damage to the bone. Subsequently, the non-dominated sorting genetic algorithm (NSGA-III) was used to optimize the parameters for reduction in the cutting forces and temperature during bone grinding while reducing neural tissue damage.

Results

The results revealed that the maximum value of tangential force was 21.32 N, thrust force was 9.25 N, grinding force ratio was 0.453, torque was 4.55 N-mm, and temperature was 59.3°C. It has been observed that maximum temperature was generated at a rotational speed of 55000 rpm, feed rate of 60 mm/min, and depth of cut of 1.0 mm. Histopathological imaging analysis revealed the presence of viable lacunas, empty lacunas, haversian canals, and osteocytes in the bone samples. Furthermore, the elemental composition of the bone highlights the presence of carbon (c) 59.49%, oxygen (O) 35.82%, sodium (Na) 0.11%, phosphorous 1.50%, sulphur 0.33%, chlorine 0.98%, and calcium 1.77%.

Conclusion

The study revealed that compared to the initial scenario, NSGA-III can produce better results without compromising the trial results. According to a statistical study, the rise in temperature during bone grinding was significantly influenced by rotating speed. The density of osteocytes in the lacunas was higher at lower temperatures. Furthermore, the results of surface electron microscopy and energy dispersive spectroscopy revealed the presence of bone over the surface of the grinding burr, which resulted in the loading of the grinding burr. The results of the present investigation will be beneficial for researchers and clinical practitioners worldwide.

© 2024 The Author(s). Published by Bentham Science Publisher.
This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Loading

Article metrics loading...

/content/journals/cmir/10.2174/0115734056284074231222042746
2024-01-26
2025-01-28

  • From This Site

    /content/journals/cmir/10.2174/0115734056284074231222042746
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

/deliver/fulltext/cmir/20/1/CMIR-20-E15734056284074.html?itemId=/content/journals/cmir/10.2174/0115734056284074231222042746&mimeType=html&fmt=ahah

References

  1. GaoC. PengS. FengP. ShuaiC. Bone biomaterials and interactions with stem cells.Bone Res.2017511705910.1038/boneres.2017.5929285402
     [Google Scholar]
  2. FeldmannA. GanserP. NolteL. ZyssetP. Orthogonal cutting of cortical bone: Temperature elevation and fracture toughness.Int. J. Mach. Tools Manuf.2017118-11911110.1016/j.ijmachtools.2017.03.009
     [Google Scholar]
  3. LughmaniW.A. Bouazza-MaroufK. AshcroftI. RepositoryI. LughmaniW.A. Bouazza-MaroufK. Drilling in cortical bone: A finite element model and experimental investigations.J. Mech. Behav. Biomed. Mater.201542324210.1016/j.jmbbm.2014.10.01725460924
     [Google Scholar]
  4. BabbarA. JainV. GuptaD. In vivo evaluation of machining forces, torque, and bone quality during skull bone grinding.Proc. Inst. Mech. Eng. H2020234662663810.1177/095441192091149932181700
     [Google Scholar]
  5. ShihA.J. TaiB.L. ZhangL. SullivanS. MalkinS. Prediction of bone grinding temperature in skull base neurosurgery.CIRP Ann.201261130731010.1016/j.cirp.2012.03.078
     [Google Scholar]
  6. TaiB.L. ZhangL. WangA.C. SullivanS. WangG. ShihA.J. Temperature prediction in high speed bone grinding using motor PWM signal.Med. Eng. Phys.201335101545154910.1016/j.medengphy.2013.05.01123806419
     [Google Scholar]
  7. BabbarA. JainV. GuptaD. Thermo-mechanical aspects and temperature measurement techniques of bone grinding.Mater. Today Proc.2020331458146210.1016/j.matpr.2020.01.497
     [Google Scholar]
  8. BabbarA. JainV. GuptaD. PrakashC. AgrawalD. Potential Application of CEM43 °C and Arrhenius Model in Neurosurgical Bone Grinding.ChamSpringer202214515810.1007/978‑3‑031‑04301‑7_9
     [Google Scholar]
  9. ZhangL. TaiB.L. WangG. ZhangK. SullivanS. ShihA.J. Thermal model to investigate the temperature in bone grinding for skull base neurosurgery.Med. Eng. Phys.201335101391139810.1016/j.medengphy.2013.03.02323683875
     [Google Scholar]
  10. ZhangL. ZouL. WenD. WangX. KongF. PiaoZ. Investigation of the effect of process parameters on bone grinding performance based on on‐line measurement of temperature and force sensors.Sensors20202011332510.3390/s2011332532545229
     [Google Scholar]
  11. BabbarA. JainV. GuptaD. Thermogenesis mitigation using ultrasonic actuation during bone grinding: A hybrid approach using CEM43°C and Arrhenius model.J. Braz. Soc. Mech. Sci. Eng.2019411040110.1007/s40430‑019‑1913‑6
     [Google Scholar]
  12. BabbarA. JainV. GuptaD. Neurosurgical Bone Grinding. Biomanufacturing.ChamSpringer International Publishing201913715510.1007/978‑3‑030‑13951‑3_7
     [Google Scholar]
  13. BabbarA. JainV. GuptaD. AgrawalD. Finite element simulation and integration of CEM43 °C and arrhenius models for ultrasonic-assisted skull bone grinding: A thermal dose model.Med. Eng. Phys.20219092210.1016/j.medengphy.2021.01.00833781484
     [Google Scholar]
  14. HuY. HuX. FanZ. LiuZ. ZhangC. FuW. Cortical bone grinding mechanism modeling and experimental studyfor damage minimization in craniotomy.Proc. Inst. Mech. Eng. H2022236332032810.1177/0954411921106013534894878
     [Google Scholar]
  15. MarkovićA. ĆalasanD. ČolićS. Stojčev-StajčićL. JanjićB. MišićT. Implant stability in posterior maxilla: Bone-condensing versus bone-drilling: A clinical study.Oral Surg. Oral Med. Oral Pathol. Oral Radiol. Endod.2011112555756310.1016/j.tripleo.2010.11.01021330161
     [Google Scholar]
  16. SuiJ. SugitaN. IshiiK. HaradaK. MitsuishiM. Mechanistic modeling of bone-drilling process with experimental validation.J. Mater. Process. Technol.201421441018102610.1016/j.jmatprotec.2013.11.001
     [Google Scholar]
  17. EbrahimzadehA. AzimifarF. NosouhiR. Design and manufacturing of integrated drilling and cutting orthopedic bone-specific surgical guide.Mater. Manuf. Process.201631560861110.1080/10426914.2015.1025969
     [Google Scholar]
  18. AlamK. QamarS.Z. Ultrasonically assisted bone drilling—effect of process parameters on delamination.Mater. Manuf. Process.201833161894189810.1080/10426914.2018.1476768
     [Google Scholar]
  19. FernandesM.G. FonsecaE.M.M. JorgeR.N. VazM. DiasM.I. Thermal analysis in drilling of ex vivo bovine bones.J. Mech. Med. Biol.2017175175008210.1142/S0219519417500828
     [Google Scholar]
  20. GholampourS. DroesslerJ. FrimD. The role of operating variables in improving the performance of skull base grinding.Neurosurg. Rev.20224532431244010.1007/s10143‑022‑01736‑035258695
     [Google Scholar]
  21. YangM. LiC. LuoL. LiR. LongY. Predictive model of convective heat transfer coefficient in bone micro-grinding using nanofluid aerosol cooling.Int. Commun. Heat Mass Transf.202112510531710.1016/j.icheatmasstransfer.2021.105317
     [Google Scholar]
  22. MizutaniT. SatakeU. EnomotoT. A study on a cooling method for bone grinding using diamond bur for minimally invasive surgeries.Precis. Eng.20217015516310.1016/j.precisioneng.2021.01.010
     [Google Scholar]
  23. PandeyR.K. PandaS.S. Optimization of bone drilling parameters using grey-based fuzzy algorithm.Measurement20144738639210.1016/j.measurement.2013.09.007
     [Google Scholar]
  24. SinghG. JainV. GuptaD. GhaiA. Optimization of process parameters for drilled hole quality characteristics during cortical bone drilling using Taguchi method.J. Mech. Behav. Biomed. Mater.20166235536510.1016/j.jmbbm.2016.05.01527254280
     [Google Scholar]
  25. AkhbarM.F.A. YusoffA.R. Multi-objective optimization of surgical drill bit to minimize thermal damage in bone-drilling.Appl. Therm. Eng.201915711359410.1016/j.applthermaleng.2019.04.004
     [Google Scholar]
  26. TahmasbiV. GhoreishiM. ZolfaghariM. Investigation, sensitivity analysis, and multi-objective optimization of effective parameters on temperature and force in robotic drilling cortical bone.Proc. Inst. Mech. Eng. H2017231111012102410.1177/095441191772609828803514
     [Google Scholar]
  27. KanayaH. EnokidaM. UeharaK. UekiM. NagashimaH. Thermal damage of osteocytes during pig bone drilling: An in vivo comparative study of currently available and modified drills.Arch. Orthop. Trauma Surg.2019139111599160510.1007/s00402‑019‑03239‑y31289845
     [Google Scholar]
  28. GuptaV. PandeyP.M. Experimental investigation and statistical modeling of temperature rise in rotary ultrasonic bone drilling.Med. Eng. Phys.201638111330133810.1016/j.medengphy.2016.08.01227639655
     [Google Scholar]
  29. GuptaV. PandeyP.M. An in-vitro study of cutting force and torque during rotary ultrasonic bone drilling.Proc. Inst. Mech. Eng., B J. Eng. Manuf.201823291549156010.1177/0954405416673115
     [Google Scholar]
  30. GuptaV. PandeyP.M. In-situ tool wear monitoring and its effects on the performance of porcine cortical bone drilling: a comparative in-vitro investigation.Mech. Adv. Mater. Mod. Process.201731210.1186/s40759‑017‑0019‑z32355608
     [Google Scholar]
  31. SinghG. BabbarA. JainV. GuptaD. Comparative statement for diametric delamination in drilling of cortical bone with conventional and ultrasonic assisted drilling techniques.J. Orthop.202125535810.1016/j.jor.2021.03.01733927509
     [Google Scholar]
  32. EnomotoT. ShigetaH. SugiharaT. SatakeU. A new surgical grinding wheel for suppressing grinding heat generation in bone resection.CIRP Ann.201463130530810.1016/j.cirp.2014.03.026
     [Google Scholar]
  33. ZhangL. TaiB.L. WangA.C. ShihA.J. Mist cooling in neurosurgical bone grinding.CIRP Ann.201362136737010.1016/j.cirp.2013.03.125
     [Google Scholar]
  34. SharmaA. JainV. Experimental investigation of cutting temperature during drilling of float glass specimen.IOP Conf Ser Mater Sci Engvol. 715202010.1088/1757‑899X/715/1/012050
     [Google Scholar]
  35. SharmaA. JainV. GuptaD. Characterization of chipping and tool wear during drilling of float glass using rotary ultrasonic machining.Measurement201812825426310.1016/j.measurement.2018.06.040
     [Google Scholar]
  36. SharmaA. JainV. GuptaD. Comparative analysis of chipping mechanics of float glass during rotary ultrasonic drilling and conventional drilling: For multi-shaped tools.Mach. Sci. Technol.201923454756810.1080/10910344.2019.1575402
     [Google Scholar]
  37. SinghA.K. KumarS. SinghV.P. Effect of the addition of conductive powder in dielectric on the surface properties of superalloy Super Co 605 by EDM process.Int. J. Adv. Manuf. Technol.2015771-49910610.1007/s00170‑014‑6433‑z
     [Google Scholar]
  38. SinghA.K. KumarS. SinghV.P. Optimization of parameters using conductive powder in dielectric for EDM of super Co 605 with multiple quality characteristics.Mater. Manuf. Process.201429326727310.1080/10426914.2013.864397
     [Google Scholar]
  39. FeldmannA. ZyssetP. Experimental determination of the emissivity of bone.Med. Eng. Phys.201638101136113810.1016/j.medengphy.2016.06.01927387900
     [Google Scholar]
  40. DebK. JainH. An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, Part I: Solving problems with box constraints.IEEE Trans. Evol. Comput.201418457760110.1109/TEVC.2013.2281535
     [Google Scholar]
  41. LiuQ. HuangG. FangC. CuiC. XuX. Experimental investigations on grinding characteristics and removal mechanisms of 2D–Cf/C-SiC composites based on reinforced fiber orientations.Ceram. Int.20174317152661527410.1016/j.ceramint.2017.08.064
     [Google Scholar]
/content/journals/cmir/10.2174/0115734056284074231222042746
Loading
Medical Imaging and Analysis of Thermal Necrosis During Bone Grinding: Implementation of Non-dominated Sorting Genetic Algorithm (NSGA-III) in Healthcare
Curr. Med. Imaging 20, e15734056284074 (2024); https://doi.org/10.2174/0115734056284074231222042746
/content/journals/cmir/10.2174/0115734056284074231222042746
/content/journals/cmir/10.2174/0115734056284074231222042746
Loading

Data & Media loading...


  • Article Type:     Research Article
Keyword(s): Bone grinding; Energy dispersive spectroscopy; Histopathology; Imaging; NSGA-III; Optimization; Surface electron microscopy

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test