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  1. Farook TH, Radford J, Alam MK, Jamayet NB
    Br Dent J, 2020 Oct 20.
    PMID: 33082524 DOI: 10.1038/s41415-020-2026-4
    Objective Following a survey of the literature, a systematic review was carried out with the aim of answering the following questions: 1) What is 'acceptable plagiarism'?; 2) Who carries out plagiarism?; 3) What factors could encourage plagiarism?; 4) How can plagiarism be managed?Data source and selection Following PRISMA guidelines, data were gathered by searching Scopus, PubMed and Web of Science. After removal of duplicates, 345 titles were identified. Then, having satisfied a priori eligibility criteria, 29 papers were interrogated. The quality of relevant papers (n = 23) was assessed using the Joanna Briggs Critical Appraisal Tool.Data extraction There was no clear threshold as to what is 'acceptable plagiarism'. Despite this lack of clarity, it is argued consistently that males, and those who wrote in a language that is not their mother tongue, were more likely to plagiarise.Conclusion Plagiarism is all but inescapable due to various reasons: 1) there is no agreed threshold as to what is 'acceptable plagiarism'; 2) the internet; 3) institutional; and 4) societal expectations. Plagiarism could be mitigated in the student domain by grammar support and, for example, non-written submissions such as presenting work by video. Academic fraud is fundamentally undermined by valuing original and creative scholarship and sound ethical principles.
  2. Farook TH, Abdullah JY, Jamayet NB, Alam MK
    J Prosthet Dent, 2021 Feb 15.
    PMID: 33602541 DOI: 10.1016/j.prosdent.2020.07.039
    STATEMENT OF PROBLEM: Computer-aided design (CAD) of maxillofacial prostheses is a hardware-intensive process. The greater the mesh detail is, the more processing power is required from the computer. A reduction in mesh quality has been shown to reduce workload on computers, yet no reference value of reduction is present for intraoral prostheses that can be applied during the design.

    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

  3. Farook TH, Barman A, Abdullah JY, Jamayet NB
    J Prosthodont, 2021 Jun;30(5):420-429.
    PMID: 33200429 DOI: 10.1111/jopr.13286
    PURPOSE: Mesh optimization reduces the texture quality of 3D models in order to reduce storage file size and computational load on a personal computer. This study aims to explore mesh optimization using open source (free) software in the context of prosthodontic application.

    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.

  4. Farook TH, Jamayet NB, Abdullah JY, Alam MK
    Pain Res Manag, 2021;2021:6659133.
    PMID: 33986900 DOI: 10.1155/2021/6659133
    Purpose: The study explored the clinical influence, effectiveness, limitations, and human comparison outcomes of machine learning in diagnosing (1) dental diseases, (2) periodontal diseases, (3) trauma and neuralgias, (4) cysts and tumors, (5) glandular disorders, and (6) bone and temporomandibular joint as possible causes of dental and orofacial pain.

    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.

  5. Beh YH, Farook TH, Jamayet NB, Dudley J, Rashid F, Barman A, et al.
    Cleft Palate Craniofac J, 2021 03;58(3):386-390.
    PMID: 32808548 DOI: 10.1177/1055665620950074
    OBJECTIVE: The virtual cone beam computed tomography-derived 3-dimensional model was compared with the scanned conventional model used in the fabrication of a palatal obturator for a patient with a large palatal defect.

    DESIGN: A digitally derived 3-dimensional maxillary model incorporating the palatal defect was generated from the patient's existing cone beam computerized tomography data and compared with the scanned cast from the conventional impression for linear dimensions, area, and volume. The digitally derived cast was 3-dimensionally printed and the obturator fabricated using traditional techniques. Similarly, an obturator was fabricated from the conventional cast and the fit of both final obturator bulbs were compared in vivo.

    RESULTS: The digitally derived model produced more accurate volumes and surface areas within the defect. The defect margins and peripheries were overestimated which was reflected clinically.

    CONCLUSION: The digitally derived model provided advantages in the fabrication of the palatal obturator; however, further clinical research is required to refine consistency.

  6. Farook TH, Jamayet NB, Abdullah JY, Rajion ZA, Alam MK
    J Stomatol Oral Maxillofac Surg, 2020 Jun;121(3):268-277.
    PMID: 31610244 DOI: 10.1016/j.jormas.2019.10.003
    A systematic review was conducted in early 2019 to evaluate the articles published that dealt with digital workflow, CAD, rapid prototyping and digital image processing in the rehabilitation by maxillofacial prosthetics. The objective of the review was to primarily identify the recorded cases of orofacial rehabilitation made by maxillofacial prosthetics using computer assisted 3D printing. Secondary objectives were to analyze the methods of data acquisition recorded with challenges and limitations documented with various software in the workflow. Articles were searched from Scopus, PubMed and Google Scholar based on the predetermined eligibility criteria. Thirty-nine selected papers from 1992 to 2019 were then read and categorized according to type of prosthesis described in the papers. For nasal prostheses, Common Methods of data acquisition mentioned were computed tomography, photogrammetry and laser scanners. After image processing, computer aided design (CAD) was used to design and merge the prosthesis to the peripheral healthy tissue. Designing and printing the mold was more preferred. Moisture and muscle movement affected the overall fit especially for prostheses directly designed and printed. For auricular prostheses, laser scanning was most preferred. For unilateral defects, CAD was used to mirror the healthy tissue over to the defect side. Authors emphasized on the need of digital library for prostheses selection, especially for bilateral defects. Printing the mold and conventionally creating the prosthesis was most preferred due to issues of proper fit and color matching. Orbital prostheses follow a similar workflow as auricular prosthesis. 3D photogrammetry and laser scans were more preferred and directly printing the prosthesis was favored in various instance. However, ocular prostheses fabrication was recorded to be a challenge due to difficulties in appropriate volume reconstruction and inability to mirror healthy globe. Only successful cases of digitally designed and printed iris were noted.
  7. Barman A, Rashid F, Farook TH, Jamayet NB, Dudley J, Yhaya MFB, et al.
    Polymers (Basel), 2020 Jul 12;12(7).
    PMID: 32664615 DOI: 10.3390/polym12071536
    Although numerous studies have demonstrated the benefits of incorporating filler particles into maxillofacial silicone elastomer (MFPSE), a review of the types, concentrations and effectiveness of the particles themselves was lacking. The purpose of this systematic review and meta-analysis was to review the effect of different types of filler particles on the mechanical properties of MFPSE. The properties in question were (1) tensile strength, (2) tear strength, (3) hardness, and (4) elongation at break. The findings of this study can assist operators, technicians and clinicians in making relevant decisions regarding which type of fillers to incorporate based on their needs. The systematic review was performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 26 original articles from 1970 to 2019 were selected from the databases, based on predefined eligibility criteria by two reviewers. The meta-analyses of nine papers were carried out by extracting data from the systematic review based on scoring criteria and processed using Cochrane Review Manager 5.3. Overall, there were significant differences favoring filler particles when incorporated into MFPSE. Nano fillers (69.23% of all studies) demonstrated superior comparative outcomes for tensile strength (P < 0.0001), tear strength (P < 0.00001), hardness (P < 0.00001) and elongation at break (P < 0.00001) when compared to micro fillers (30.76% of all studies). Micro fillers demonstrated inconsistent outcomes in mechanical properties, and meta-analysis of elongation at break argued against (P < 0.01) their use. Current findings suggest that 1.5% ZrSiO4, 3% SiO2, 1.5% Y2O3, 2-6% TiO2, 2-2.5% ZnO, 2-2.5% CeO2, 0.5% TiSiO4 and 1% Ag-Zn Zeolite can be used to reinforce MFPSE, and help the materials better withstand mechanical degradation.
  8. Farook TH, Jamayet NB, Abdullah JY, Asif JA, Rajion ZA, Alam MK
    Comput Biol Med, 2020 03;118:103646.
    PMID: 32174323 DOI: 10.1016/j.compbiomed.2020.103646
    OBJECTIVE: To design and compare the outcome of commercial (CS) and open source (OS) software-based 3D prosthetic templates for rehabilitation of maxillofacial defects using a low powered personal computer setup.

    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.

  9. Al-Oulabi A, Al Rawas M, Farook TH, Rashid F, Barman A, Jamayet NB, et al.
    Work, 2021 Jun 25.
    PMID: 34180457 DOI: 10.3233/WOR-213519
    BACKGROUND: Two patients received ocular injuries from rusted metallic projectiles at their industrial workplaces. Said injuries resulted in the loss of their eyes by evisceration surgeries to prevent fatal infections.

    CASE DESCRIPTION: The first case, a man in his twenties, received a stock conformer immediately after surgery and started prosthetic therapy within 2 months. The second case, a man in his forties, started prosthetic therapy after 10 years. Definitive custom ocular prostheses were fabricated and relined according to conventional protocol.

    RESULTS: On issue of the prosthesis, there was adequate retention, aesthetics and stability to extra-ocular movements and treatment was considered successful for both cases. However, follow-ups showed noticeable prosthetic eye movements for case 1 which, to some extent mimicked the physiologic movement of its fellow natural eye. Case 1 adjusted to his prosthesis better while case 2 was still adjusting with little to no physiologic movement.

    CONCLUSION: Prosthetic rehabilitation should be started as early as possible to obtain optimum rehabilitative results.

  10. Jamayet NB, Farook TH, Al-Oulabi A, Johari Y, Patil PG
    J Prosthet Dent, 2021 Oct 08.
    PMID: 34635339 DOI: 10.1016/j.prosdent.2021.08.021
    This clinical report describes how a hollow obturator prosthesis was designed and fabricated for an 82-year-old partially edentulous patient with a large palatal defect. Computer-aided design (CAD) was used to design, articulate, and align the mandibular denture with the obturator prosthesis. The prosthesis was printed, adjusted chairside, rescanned, and made hollow by using a CAD software program. The prosthesis was printed in resin with a dental 3D printer. Quantitative evaluations of clinical (prosthesis dimensions, rest, and occlusal vertical dimensions) and virtual (surface area, volume, weight, interpoint mismatches, spatial overlap) parameters found that the 3D-printed prosthesis required an additional 5% chairside modification. The greatest differences in volume (24.7% less) and weight (22.2% less) were observed when the modified obturator bulb was made hollow via CAD. Hollowing the bulb, therefore, reduced the spatial overlap in volume by 16.8%.
  11. Farook TH, Jamayet NB, Asif JA, Din AS, Mahyuddin MN, Alam MK
    Sci Rep, 2021 04 19;11(1):8469.
    PMID: 33875672 DOI: 10.1038/s41598-021-87240-9
    Palatal defects are rehabilitated by fabricating maxillofacial prostheses called obturators. The treatment incorporates taking deviously unpredictable impressions to facsimile the palatal defects into plaster casts for obturator fabrication in the dental laboratory. The casts are then digitally stored using expensive hardware to prevent physical damage or data loss and, when required, future obturators are digitally designed, and 3D printed. Our objective was to construct and validate an economic in-house smartphone-integrated stereophotogrammetry (SPINS) 3D scanner and to evaluate its accuracy in designing prosthetics using open source/free (OS/F) digital pipeline. Palatal defect models were scanned using SPINS and its accuracy was compared against the standard laser scanner for virtual area and volumetric parameters. SPINS derived 3D models were then used to design obturators by using (OS/F) software. The resultant obturators were virtually compared against standard medical software designs. There were no significant differences in any of the virtual parameters when evaluating the accuracy of both SPINS, as well as OS/F derived obturators. However, limitations in the design process resulted in minimal dissimilarities. With further improvements, SPINS based prosthetic rehabilitation could create a viable, low cost method for rural and developing health services to embrace maxillofacial record keeping and digitised prosthetic rehabilitation.
  12. Farook TH, Rashid F, Jamayet NB, Abdullah JY, Dudley J, Khursheed Alam M
    J Prosthet Dent, 2022 Oct;128(4):830-836.
    PMID: 33642077 DOI: 10.1016/j.prosdent.2020.12.041
    STATEMENT OF PROBLEM: The anatomic complexity of the ear challenges conventional maxillofacial prosthetic rehabilitation. The introduction of specialized scanning hardware integrated into computer-aided design and computer-aided manufacturing (CAD-CAM) workflows has mitigated these challenges. Currently, the scanning hardware required for digital data acquisition is expensive and not readily available for prosthodontists in developing regions.

    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.

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