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  1. Dudley J, Richards L, Mahmud M
    BMC Psychol, 2020 Mar 14;8(1):24.
    PMID: 32171332 DOI: 10.1186/s40359-020-0391-z
    BACKGROUND: The use of psychological testing to indicate the potential for dissatisfaction with dental treatment has many potential patient and clinician benefits but has been rarely investigated. The study aimed to explore the use of the Symptom Checklist-90-Revised (SCL-90-R) psychological testing instrument in describing the relationship between pre-treatment psychological traits and aesthetic restorative treatment satisfaction.

    METHODS: Thirty patients requiring aesthetic restorative dental treatment completed three questionnaires, namely 1) a pre-treatment expectation assessment, 2) an SCL-90-R analysis pre-treatment and 3) an outcome assessment post-treatment to assess patient's expectations and satisfaction of the proposed dental treatment relating to function, aesthetics, comfort and tissue preservation. Logistic regression models were used to assess the impact of psychological variables on patient satisfaction after adjusting for baseline expectations (P 

  2. Farook TH, Rashid F, Alam MK, Dudley J
    Clin Oral Investig, 2022 Dec 29.
    PMID: 36577849 DOI: 10.1007/s00784-022-04835-w
    BACKGROUND: To explore the digitisation of jaw movement trajectories through devices and discuss the physiological factors and device-dependent variables with their subsequent effects on the jaw movement analyses.

    METHODS: Based on predefined eligibility criteria, the search was conducted following PRISMA-P 2015 guidelines on MEDLINE, EBSCO Host, Scopus, PubMed, and Web of Science databases in 2022 by 2 reviewers. Articles then underwent Cochrane GRADE approach and JBI critical appraisal for certainty of evidence and bias evaluation.

    RESULTS: Thirty articles were included following eligibility screening. Both in vitro experiments (20%) and in vivo (80%) devices ranging from electronic axiography, electromyography, optoelectronic and ultrasonic, oral or extra-oral tracking, photogrammetry, sirognathography, digital pressure sensors, electrognathography, and computerised medical-image tracing were documented. 53.53% of the studies were rated below "moderate" certainty of evidence. Critical appraisal showed 80% case-control investigations failed to address confounding variables while 90% of the included non-randomised experimental studies failed to establish control reference.

    CONCLUSION: Mandibular and condylar growth, kinematic dysfunction of the neuromuscular system, shortened dental arches, previous orthodontic treatment, variations in habitual head posture, temporomandibular joint disorders, fricative phonetics, and to a limited extent parafunctional habits and unbalanced occlusal contact were identified confounding variables that shaped jaw movement trajectories but were not highly dependent on age, gender, or diet. Realistic variations in device accuracy were found between 50 and 330 µm across the digital systems with very low interrater reliability for motion tracing from photographs. Forensic and in vitro simulation devices could not accurately recreate variations in jaw motion and muscle contractions.

  3. 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.

  4. 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.
  5. 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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