Visual and haptic perceptibility of 3D printed skeletal models in orthognathic surgery

Quality and haptic feedback of three-dimensionally printed models for simulating dental implant surgery

STATEMENT OF PROBLEM

A model offering anatomic replication and haptic feedback similar to that of real bone is essential for hands-on surgical dental implant training. Patient-specific skeletal models can be produced with 3-dimensional (3D) printing, but whether these models can offer optimal haptic feedback for simulating implant surgery is unknown.

PURPOSE

The purpose of this trial was to compare the haptic feedback of different 3D printed models for simulating dental implant surgery.

MATERIAL AND METHODS

A cone beam computed tomography image of a 60-year-old man with a partially edentulous mandible was manipulated to segment the mandible and isolated from the rest of the scan. Three-dimensional models were printed with 6 different printers and materials: material jetting-based printer (MJ, acrylic-based resin); digital light processing-based printer (DLP, acrylic-based resin); fused filament fabrication-based printer (FFF1, polycarbonate filament; FFF2, polylactic acid filament); stereolithography-based printer (SLA, acrylic-based resin); and selective laser sintering-based printer (SLS, polyamide filament). Five experienced maxillofacial surgeons performed a simulated implant surgery on the models. A 5-point Likert scale questionnaire was established to assess the haptic feedback. The Friedman test and cumulative logit models were applied to evaluate differences among the models (α=.05).

RESULTS

The median score for drilling perception and implant insertion was highest for the MJ-based model and lowest for the SLS-based model. In relation to the drill chips, a median score of ≥3 was observed for all models. The score for corticotrabecular transition was highest for the MJ-based model and lowest for the FFF2-based model. Overall, the MJ-based model offered the highest score compared with the other models.

CONCLUSIONS

The 3D printed model with MJ technology and acrylic-based resin provided the best haptic feedback for performing implant surgery. However, none of the models were able to completely replicate the haptic perception of real bone.

Dimensional accuracy and precision and surgeon perception of additively manufactured bone models: effect of manufacturing technology and part orientation

BACKGROUND

Additively manufactured (AM) anatomical bone models are primarily utilized for training and preoperative planning purposes. As such, they must meet stringent requirements, with dimensional accuracy being of utmost importance. This study aimed to evaluate the precision and accuracy of anatomical bone models manufactured using three different AM technologies: digital light processing (DLP), fused deposition modeling (FDM), and PolyJetting (PJ), built in three different part orientations. Additionally, the study sought to assess surgeons' perceptions of how well these models mimic real bones in simulated osteosynthesis.

METHODS

Computer-aided design (CAD) models of six human radii were generated from computed tomography (CT) imaging data. Anatomical models were then manufactured using the three aforementioned technologies and in three different part orientations. The surfaces of all models were 3D-scanned and compared with the original CAD models. Furthermore, an anatomical model of a proximal femur including a metastatic lesion was manufactured using the three technologies, followed by (mock) osteosynthesis performed by six surgeons on each type of model. The surgeons' perceptions of the quality and haptic properties of each model were assessed using a questionnaire.

RESULTS

The mean dimensional deviations from the original CAD model ranged between 0.00 and 0.13 mm with maximal inaccuracies < 1 mm for all models. In surgical simulation, PJ models achieved the highest total score on a 5-point Likert scale ranging from 1 to 5 (with 1 and 5 representing the lowest and highest level of agreement, respectively), (3.74 ± 0.99) in the surgeons' perception assessment, followed by DLP (3.41 ± 0.99) and FDM (2.43 ± 1.02). Notably, FDM was perceived as unsuitable for surgical simulation, as the material melted during drilling and sawing.

CONCLUSIONS

In conclusion, the choice of technology and part orientation significantly influenced the accuracy and precision of additively manufactured bone models. However, all anatomical models showed satisfying accuracies and precisions, independent of the AM technology or part orientation. The anatomical and functional performance of FDM models was rated by surgeons as poor.

Nanomaterial-based drug delivery of immunomodulatory factors for bone and cartilage tissue engineering

As life expectancy continues to increase, so do disorders related to the musculoskeletal system. Orthopedics-related impairments remain a challenge, with nearly 325 thousand and 120 thousand deaths recorded in 2019. Musculoskeletal system, including bone and cartilage tissue, is a living system in which cells constantly interact with the immune system, which plays a key role in the tissue repair process. An alternative to bridge the gap between these two systems is exploiting nanomaterials, as they have proven to serve as delivery agents of an array of molecules, including immunomodulatory agents (anti-inflammatory drugs, cytokines), as well as having the ability to mimic tissue by their nanoscopic structure and promote tissue repair per se. Therefore, this review outlooks nanomaterials and immunomodulatory factors widely employed in the area of bone and cartilage tissue engineering. Emerging developments in nanomaterials for delivery of immunomodulatory agents for bone and cartilage tissue engineering applications have also been discussed. It can be concluded that latest progress in nanotechnology have enabled to design intricate systems with the ability to deliver biologically active agents, promoting tissue repair and regeneration; thus, nanomaterials studied herein have shown great potential to serve as immunomodulatory agents in the area of tissue engineering.

Changes in alveolar bone width around maxillary implants, as determined through cone beam computed tomography based on bony landmarks: A preliminary study

PURPOSE

This study aimed to investigate changes in alveolar bone width around dental implants and identify the anterior nasal spine (ANS), posterior nasal spine (PNS), and floor of the nasal cavity that can be used as reference landmarks for standardizing the orientation of different cone-beam computed tomography (CBCT) scans.

MATERIALS AND METHODS

We enrolled two groups that comprised 30 implants. Two CBCT scans from the same patient after implant surgery in the first group were obtained to determine differences in the relative distance and angle between the ANS and apex of the dental implant. Then we compared the second group of patients' presurgical and postsurgical CBCT images to evaluate changes in alveolar bone width after dental implant surgery by the aforementioned bony landmarks.

RESULTS

In the first group, no statistically significant differences were detected in the mean distance between the ANS, PNS and implant tip in different directions. In the second group, bone width increased at 1 mm (p = 0.020) and decreased at 4 mm (p < 0.001) and 7 mm (p < 0.001) below the alveolar bone crest after implant surgery.

CONCLUSIONS

Within the limitations of the present study, the ANS, PNS, and floor of the nasal cavity can be useful in standardizing the orientation of CBCT scans and alveolar bone remodeling after implant surgery varied depending on the height and direction from the alveolar bone crest based on the three landmarks.

The Use of Tactile Sensors in Oral and Maxillofacial Surgery: An Overview

BACKGROUND

This overview aimed to characterize the type, development, and use of haptic technologies for maxillofacial surgical purposes. The work aim is to summarize and evaluate current advantages, drawbacks, and design choices of presented technologies for each field of application in order to address and promote future research as well as to provide a global view of the issue.

METHODS

Relevant manuscripts were searched electronically through Scopus, MEDLINE/PubMed, and Cochrane Library databases until 1 November 2022.

RESULTS

After analyzing the available literature, 31 articles regarding tactile sensors and interfaces, sensorized tools, haptic technologies, and integrated platforms in oral and maxillofacial surgery have been included. Moreover, a quality rating is provided for each article following appropriate evaluation metrics.

DISCUSSION

Many efforts have been made to overcome the technological limits of computed assistant diagnosis, surgery, and teaching. Nonetheless, a research gap is evident between dental/maxillofacial surgery and other specialties such as endovascular, laparoscopic, and microsurgery; especially for what concerns electrical and optical-based sensors for instrumented tools and sensorized tools for contact forces detection. The application of existing technologies is mainly focused on digital simulation purposes, and the integration into Computer Assisted Surgery (CAS) is far from being widely actuated. Virtual reality, increasingly adopted in various fields of surgery (e.g., sino-nasal, traumatology, implantology) showed interesting results and has the potential to revolutionize teaching and learning. A major concern regarding the actual state of the art is the absence of randomized control trials and the prevalence of case reports, retrospective cohorts, and experimental studies. Nonetheless, as the research is fast growing, we can expect to see many developments be incorporated into maxillofacial surgery practice, after adequate evaluation by the scientific community.

Craniotomy Simulator with Force Myography and Machine Learning-Based Skills Assessment

Craniotomy is a fundamental component of neurosurgery that involves the removal of the skull bone flap. Simulation-based training of craniotomy is an efficient method to develop competent skills outside the operating room. Traditionally, an expert surgeon evaluates the surgical skills using rating scales, but this method is subjective, time-consuming, and tedious. Accordingly, the objective of the present study was to develop an anatomically accurate craniotomy simulator with realistic haptic feedback and objective evaluation of surgical skills. A CT scan segmentation-based craniotomy simulator with two bone flaps for drilling task was developed using 3D printed bone matrix material. Force myography (FMG) and machine learning were used to automatically evaluate the surgical skills. Twenty-two neurosurgeons participated in this study, including novices (n = 8), intermediates (n = 8), and experts (n = 6), and they performed the defined drilling experiments. They provided feedback on the effectiveness of the simulator using a Likert scale questionnaire on a scale ranging from 1 to 10. The data acquired from the FMG band was used to classify the surgical expertise into novice, intermediate and expert categories. The study employed naïve Bayes, linear discriminant (LDA), support vector machine (SVM), and decision tree (DT) classifiers with leave one out cross-validation. The neurosurgeons' feedback indicates that the developed simulator was found to be an effective tool to hone drilling skills. In addition, the bone matrix material provided good value in terms of haptic feedback (average score 7.1). For FMG-data-based skills evaluation, we achieved maximum accuracy using the naïve Bayes classifier (90.0 ± 14.8%). DT had a classification accuracy of 86.22 ± 20.8%, LDA had an accuracy of 81.9 ± 23.6%, and SVM had an accuracy of 76.7 ± 32.9%. The findings of this study indicate that materials with comparable biomechanical properties to those of real tissues are more effective for surgical simulation. In addition, force myography and machine learning provide objective and automated assessment of surgical drilling skills.