PURPOSE: The purpose of this simulation study was to establish a reference percentage value that can be used to effectively reduce the size and polygons of the 3D mesh without drastically affecting the dimensions of the prosthesis itself.
MATERIAL AND METHODS: Fifteen different maxillary palatal defects were simulated on a dental cast and scanned to create 3D casts. Digital bulbs were fabricated from the casts. Conventional bulbs for the defects were fabricated, scanned, and compared with the digital bulb to serve as a control. The polygon parameters of digital bulbs were then reduced by different percentages (75%, 50%, 25%, 10%, 5%, and 1% of the original mesh) which created a total of 105 meshes across 7 mesh groups. The reduced mesh files were compared individually with the original design in an open-source point cloud comparison software program. The parameters of comparison used in this study were Hausdorff distance (HD), Dice similarity coefficient (DSC), and volume.
RESULTS: The reduction in file size was directly proportional to the amount of mesh reduction. There were minute yet insignificant differences in volume (P>.05) across all mesh groups, with significant differences (P
MATERIALS AND METHODS: An auricular prosthesis, a complete denture, and anterior and posterior crowns were constructed using conventional methods and laser scanned to create computerized 3D meshes. The meshes were optimized independently by four computer-aided design software (Meshmixer, Meshlab, Blender, and SculptGL) to 100%, 90%, 75%, 50%, and 25% levels of original file size. Upon optimization, the following parameters were virtually evaluated and compared; mesh vertices, file size, mesh surface area (SA), mesh volume (V), interpoint discrepancies (geometric similarity based on virtual point overlapping), and spatial similarity (volumetric similarity based on shape overlapping). The influence of software and optimization on surface area and volume of each prosthesis was evaluated independently using multiple linear regression.
RESULTS: There were clear observable differences in vertices, file size, surface area, and volume. The choice of software significantly influenced the overall virtual parameters of auricular prosthesis [SA: F(4,15) = 12.93, R2 = 0.67, p < 0.001. V: F(4,15) = 9.33, R2 = 0.64, p < 0.001] and complete denture [SA: F(4,15) = 10.81, R2 = 0.67, p < 0.001. V: F(4,15) = 3.50, R2 = 0.34, p = 0.030] across optimization levels. Interpoint discrepancies were however limited to <0.1mm and volumetric similarity was >97%.
CONCLUSION: Open-source mesh optimization of smaller dental prostheses in this study produced minimal loss of geometric and volumetric details. SculptGL models were most influenced by the amount of optimization performed.
Method: Scopus, PubMed, and Web of Science (all databases) were searched by 2 reviewers until 29th October 2020. Articles were screened and narratively synthesized according to PRISMA-DTA guidelines based on predefined eligibility criteria. Articles that made direct reference test comparisons to human clinicians were evaluated using the MI-CLAIM checklist. The risk of bias was assessed by JBI-DTA critical appraisal, and certainty of the evidence was evaluated using the GRADE approach. Information regarding the quantification method of dental pain and disease, the conditional characteristics of both training and test data cohort in the machine learning, diagnostic outcomes, and diagnostic test comparisons with clinicians, where applicable, were extracted.
Results: 34 eligible articles were found for data synthesis, of which 8 articles made direct reference comparisons to human clinicians. 7 papers scored over 13 (out of the evaluated 15 points) in the MI-CLAIM approach with all papers scoring 5+ (out of 7) in JBI-DTA appraisals. GRADE approach revealed serious risks of bias and inconsistencies with most studies containing more positive cases than their true prevalence in order to facilitate machine learning. Patient-perceived symptoms and clinical history were generally found to be less reliable than radiographs or histology for training accurate machine learning models. A low agreement level between clinicians training the models was suggested to have a negative impact on the prediction accuracy. Reference comparisons found nonspecialized clinicians with less than 3 years of experience to be disadvantaged against trained models.
Conclusion: Machine learning in dental and orofacial healthcare has shown respectable results in diagnosing diseases with symptomatic pain and with improved future iterations and can be used as a diagnostic aid in the clinics. The current review did not internally analyze the machine learning models and their respective algorithms, nor consider the confounding variables and factors responsible for shaping the orofacial disorders responsible for eliciting pain.
PURPOSE: The purpose of this virtual analysis study was to compare the accuracy and precision of 3-dimensional (3D) ear models generated by scanning gypsum casts with a smartphone camera and a desktop laser scanner.
MATERIAL AND METHODS: Six ear casts were fabricated from green dental gypsum and scanned with a laser scanner. The resultant 3D models were exported as standard tessellation language (STL) files. A stereophotogrammetry system was fabricated by using a motorized turntable and an automated microcontroller photograph capturing interface. A total of 48 images were captured from 2 angles on the arc (20 degrees and 40 degrees from the base of the turntable) with an image overlap of 15 degrees, controlled by a stepper motor. Ear 1 was placed on the turntable and captured 5 times with smartphone 1 and tested for precision. Then, ears 1 to 6 were scanned once with a laser scanner and with smartphones 1 and 2. The images were converted into 3D casts and compared for accuracy against their laser scanned counterparts for surface area, volume, interpoint mismatches, and spatial overlap. Acceptability thresholds were set at <0.5 mm for interpoint mismatches and >0.70 for spatial overlap.
RESULTS: The test for smartphone precision in comparison with that of the laser scanner showed a difference in surface area of 774.22 ±295.27 mm2 (6.9% less area) and in volume of 4228.60 ±2276.89 mm3 (13.4% more volume). Both acceptability thresholds were also met. The test for accuracy among smartphones 1, 2, and the laser scanner showed no statistically significant differences (P>.05) in all 4 parameters among the groups while also meeting both acceptability thresholds.
CONCLUSIONS: Smartphone cameras used to capture 48 overlapping gypsum cast ear images in a controlled environment generated 3D models parametrically similar to those produced by standard laser scanners.
METHODS: A prospective study was conducted to evaluate the outcome of a new reconstruction technique that produces patient-specific hybrid polymethyl methacrylate-autologous cranial implant. Computer-assisted 3D modeling and printing was utilized to produce patient-specific molds, which allowed real-time reconstruction of bone flap with partial defect intra-operatively.
RESULTS: Outcome assessment for 11 patients at 6 weeks and 3 months post-operatively revealed satisfactory implant alignment with favorable cosmesis. The mean visual analog scale for cosmesis was 91. Mean implant size was 50cm, and the mean duration of intra-operative reconstruction was 30 minutes. All of them revealed improvement in quality of life following surgery as measured by the SF-36 score. Cost analysis revealed that this technique is more cost-effective compared to customized cranial prosthesis.
CONCLUSION: This new technique and approach produce hybrid autologous-alloplastic bone flap that resulted in satisfactory implant alignment and favorable cosmetic outcome with relatively low costs.
METHODS: The pre- and post-operative CT images of 55 patients undergoing DC surgery were analyzed. The ICV was measured by segmenting every slice of the CT images, and compared with estimated ICV calculated using the 1-in-10 sampling strategy and processed using the SBI method. An independent t test was conducted to compare the ICV measurements between the two different methods. The calculation using this method was repeated three times for reliability analysis using the intraclass correlations coefficient (ICC). The Bland-Altman plot was used to measure agreement between the methods for both pre- and post-operative ICV measurements.
RESULTS: The mean ICV (±SD) were 1341.1±122.1ml (manual) and 1344.11±122.6ml (SBI) for the preoperative CT data. The mean ICV (±SD) were 1396.4±132.4ml (manual) and 1400.53±132.1ml (SBI) for the post-operative CT data. No significant difference was found in ICV measurements using the manual and the SBI methods (p=.983 for pre-op, and p=.960 for post-op). The intrarater ICC showed a significant correlation; ICC=1.00. The Bland-Altman plot showed good agreement between the manual and the SBI method.
CONCLUSION: The shape-based interpolation method with 1-in-10 sampling strategy gave comparable results in estimating ICV compared to manual segmentation. Thus, this method could be used in clinical settings for rapid, reliable and repeatable ICV estimations.
METHOD: Medical image data for five types of defects were selected, segmented, converted and decimated to 3D polygon models on a personal computer. The models were transferred to a computer aided design (CAD) software which aided in designing the prosthesis according to the virtual models. Two templates were designed for each defect, one by an OS (free) system and one by CS. The parameters for analyses were the virtual volume, Dice similarity coefficient (DSC) and Hausdorff's distance (HD) and were executed by the OS point cloud comparison tool.
RESULT: There was no significant difference (p > 0.05) between CS and OS when comparing the volume of the template outputs. While HD was within 0.05-4.33 mm, evaluation of the percentage similarity and spatial overlap following the DSC showed an average similarity of 67.7% between the two groups. The highest similarity was with orbito-facial prostheses (88.5%) and the lowest with facial plate prosthetics (28.7%).
CONCLUSION: Although CS and OS pipelines are capable of producing templates which are aesthetically and volumetrically similar, there are slight comparative discrepancies in the landmark position and spatial overlap. This is dependent on the software, associated commands and experienced decision-making. CAD-based templates can be planned on current personal computers following appropriate decimation.
Results: 87 articles were screened to get an update on the desired information. 74 were excluded based on a complete screening, and finally, 13 articles were recruited for complete reviewing. Discussion. The MFP is subjected to stress, which is reflected in the form of compressive and tensile strengths. The stress is mainly concentrated the resection line and around the apices of roots of teeth next to the defect. Diversity of designs and techniques were introduced to optimize the stress distribution, such as modification of the clasp design, using materials with different mechanical properties for dentures base and retainer, use of dental (DI) and/or zygomatic implants (ZI), and free flap reconstruction before prosthetic rehabilitation.
Conclusion: Using ZI in the defective side of the dentulous maxillary defect and defective and nondefective side of the edentulous maxillary defect was found more advantageous, in terms of compression and tensile stress and retention, when compared with DI and free flap reconstruction.
Objectives: Brain volume reduction occurs with age, especially in Parkinson plus syndrome or psychiatric disorders. We searched to define the degree of volume discrepancy in advanced IPD patients and correlate the anatomical volumetric changes to motor symptoms and cognitive function.
Methods: We determined the magnetic resonance imaging (MRI)-based volumetry of deep brain nuclei and brain structures of DBS-IPD group and matched controls.
Results: DBS-IPD group had significant deep nuclei atrophy and volume discrepancy, yet none had cognitive or psychobehavioural disturbances. Globus pallidus volume showed positive correlation to higher mental function.
Conclusion: The morphometric changes and clinical severity discrepancy in IPD may imply a more complex degenerative mechanism involving multiple neural pathways. Such alteration could be early changes before clinical manifestation.