Computer methods for automating preoperative dental implant planning: Implant positioning and size assignment
Introduction
In recent years, computer-aided methods have been introduced as supportive tools for diagnosis, operation planning and treatment in implant dentistry. Based on computed tomography (CT), their aim is to support preoperative planning towards a safer and more predictable treatment outcome.
Transfer of the dental implant planning on the computer screen offers significant advantages such as enhanced visualization capabilities of the anatomical case, accurate measurements, data processing for optimum implant allocation and size selection and, as well as, an inclusive documentation of the patient treatment. Increased user interaction and responsibility for the evaluation of the results are still, nevertheless, present in these systems.
This paper presents a computer-aided methodology that aims to a systematic dental implant planning approach based on appropriately processed CT-data. Patient anatomy, as it is represented by voxels of specific coordinates and intensity in CT images, is analyzed and the obtained results are evaluated towards an objective implant planning control. The rational allocation of a dental implant within a subject-specific anatomical site is addressed. Through a limited user input, an implantation axis with best possible position and orientation complying with established medical criteria is at a first stage suggested. Implants of various possible sizes are then automatically positioned and aligned to this axis and the thus produced alternative problem solutions are evaluated and classified. The produced implant planning schemes, for the dentist to make the final decision, are classified in terms of the derived bone volume and quality indexes at the implant site.
A case study demonstrates concept and method and allows for its discussion.
Section snippets
Background
The limitations of conventional pre-implant treatment planning, which is based among other data on 2D radiographs, have been over-passed, to a certain extent, by computer software systems and tools. Main contribution of the latter towards an optimum end result is the interactive visualization of multi-planar two-dimensional sections of the relevant anatomy including axial, cross-sectional and user-defined panoramic images, extended by 3D rendered representations of CT data [1], [2], [3]. Within
Method design considerations
Prosthetic dental treatment planning associated with implants is a complicated process, where many parameters have to be carefully assessed in order that the patient is properly treated. In addition to clinical issues, main factors that need to be accounted for, involve the geometry of the anatomic structures in contact or adjacent to the implant and the quality of the recipient bone mass [20], [21]. The placement of the prosthetic superstructure requires also particular consideration for a
Method implementation
Present method development stage provides for the assessment of mandible cases where every single tooth site is treated separately. Free splinted completed crowns are considered for restoration. CT images that contain patient-specific jaw anatomy and the provisional prosthesis morphology constitute the initial data. Matlab (MathWorks, Natick, MA) computing language is used for the method implementation and Mimics (Materialise, Leuven, Belgium) for the 3D visualization. An overview of the method
Case study and discussion
The studied instances for three posterior teeth in the patient mandible, at position nos. 36, 35 and 34 are presented and discussed. The patient wore a radio-opaque template of the pursued aesthetical and functional restorative result and was CT scanned. DICOM images were acquired with a resolution of 512 × 512, slice thickness 0.5 mm and pixel size 0.32 mm.
For each instance the axial range of prosthesis and mandibular bone images was at first selected. An axial plane inside the bone was in
Conclusions
The paper has presented a semi-automatic computer-aided methodology for the planning of dental implant therapy in single tooth cases of posterior mandible. For a given region of interest with regard to the pursued prosthetic outcome, an optimum orientation, position and size of a cylindrical implant are derived. The quality of the patient anatomic CT-data, such as the absence of serious artefacts, the geometrical consistence of the scanned radio-opaque template with that of the pursued
Acknowledgement
This research is supported by the General Secretariat for Research and Technology of Greece (GSRT, www.gsrt.gr) within the frame of the RTD program PENED.
References (29)
Presurgical planning with CT-derived fabrication of surgical guides
J. Oral Maxillofac. Surg.
(2005)An immediately loaded CAD/CAM-guided definitive prosthesis: a clinical report
J. Prosthetic Dent.
(2005)- et al.
Oral implant treatment planning in a virtual reality environment
Comp. Methods Prog. Biomed.
(1998) - et al.
Computer-based extraction of the inferior alveolar nerve canal in 3-D space
Comp. Methods Prog. Biomed.
(2004) - et al.
An image analysis approach for automatically re-orienteering CT images for dental implants
Comput. Med. Imaging Graphics
(2004) - et al.
Implant screw mechanics
Dental Clin. North Am.
(1998) - et al.
Bone grafting and its essential role in implant dentistry
Dental Clin. North Am.
(1998) - et al.
A review of selected dental literature on evidence-based treatment planning for dental implants: report of the Committee on Research in Fixed Prosthodontics of the Academy of Fixed Prosthodontics
J. Prosthetic Dent.
(2004) - et al.
Application of finite element analysis in implant dentistry: a review of the literature
J. Prosthetic Dent.
(2001) - et al.
Influence of cortical bone thickness and implant length on implant stability at the time of surgery-clinical, prospective, biomechanical, and imaging study
Bone
(2005)
Computer-assisted planning of oral implant surgery: a three-dimensional approach
Int. J. Oral Maxillofac. Implants
An image-guided planning system for endosseous oral implants
IEEE Trans. Med. Imaging
CT-based 3D-planning for dental implantology
Stud. Health Technol. Informatics
Computer-assisted implant placement. A case report: treatment of the mandible
Int. J. Oral Maxillofac. Implants
Cited by (39)
TAD-Net: tooth axis detection network based on rotation transformation encoding
2022, Graphical ModelsCitation Excerpt :In the workflow of digital orthodontics, dental features including tooth feature axis, points and arch curve defined on 3D tooth models [5], are necessary conditions, as they are usually used as important references in the treatments. In this paper, we focus on the tooth axis detection, which is essential for downstream tasks, such as classification of dental abnormalities [2], tooth redundancy analysis, and tooth arrangement [6]. Specifically, the inclination of a tooth is usually described by the angle between tooth axes as shown in Fig. 1 (a), and the rotation of a tooth is usually described by the movement around the tooth axis.
Development of an expert system for the simulation model for casting metal substructure of a metal-ceramic crown design
2017, Computer Methods and Programs in BiomedicineCitation Excerpt :Matin et al. [16] presented some aspects of the prototype integrated system and supporting procedure for the manufacture of metal substructure of metal-ceramic crowns. Galanis et al. [17] developed a semi-automatic computer-aided system for planning the dental implant therapy. Authors presented the developed methodology for planning a dental implant as a supportive tool for a dentist, helping to propose initial solutions based on the established clinical and biomechanical criteria by processing CT data with the increased accuracy.
Bone augmented with allograft onlays for implant placement could be comparable with native bone
2015, Journal of Oral and Maxillofacial SurgeryJaw tissues segmentation in dental 3D CT images using fuzzy-connectedness and morphological processing
2012, Computer Methods and Programs in BiomedicineCitation Excerpt :All this gives rise to the need for accurate segmentation that provides precise information to assure the success of the dental surgery for a great number of medical applications such as dental implant planning systems, and plastic reconstructive surgery. Many dental applications carry out the process of 3D reconstruction from CT data de-emphasizing tissue segmentation as in [1], and many others delegate this task to dentists or surgeons, providing tools for this purpose [2]. Fütterling et al. [3] carry out a segmentation of hard tissues by thresholding, while inner tissues are segmented by assigning different material properties to the tetrahedral finite elements, depending on the density values in the CT data-set.
Success Factors of Additive Manufactured Root Analogue Implants
2022, ACS Biomaterials Science and EngineeringMethod to Support Dental Implant Process Based on Image Processing
2022, Personalized Orthopedics: Contributions and Applications of Biomedical Engineering