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  • 1.
    Faghihian, Hessamoddin
    et al.
    Dental Research Center, School of Dentistry, Isfahan University of Medical Sciences, Isfahan, Iran.
    Faghihian, Reyhaneh
    Department of Pediatric Dentistry, School of Dentistry, Isfahan University of Medical Sciences, Isfahan, Iran.
    Khademi, Abbasali
    Department of Endodontics, Dental Research Center, School of Dentistry, Isfahan University of Medical Sciences, Isfahan, Iran.
    Aggarwal, Vivek
    Department of Conservative Dentistry and Endodontics, Faculty of Dentistry, Jamia Millia Islamia, New Delhi, India.
    Anesthetic efficacy of lidocaine/ketorolac in inferior alveolar nerve block in patients with irreversible pulpitis: a randomized clinical trial2020In: European Endodontic Journal, E-ISSN 2548-0839, Vol. 5, no 3, p. 186-190Article in journal (Refereed)
    Abstract [en]

    Objective: The purpose of this randomized, double-blind study was to evaluate the anesthetic efficacy of lidocaine-ketorolac administration by Inferior Alveolar Nerve Block (IANB) in patients with irreversible pulpitis.

    Methods: Eighty-eight adult patients received a combination of either one cartridge of “2% lidocaine with 1: 80.000 epinephrine” (Li) plus one cartridge of a mixture of 0.8 mL of the same solution and 1mL ketorolac tromethamine (KT)(30 mg/mL), or one cartridge of Li solution plus one cartridge of a mixture of the same solution and saline. Endodontic access was prepared after fifteen minutes. Anesthetic success was defined as no or mild pain [less than 54 mm on the Heft-Parker visual analog scale (HP-VAS)] during access cavity preparation and initial file insertion. Chi-square test was used for data analysis, and the level of significance was set at 0.05 (P=0.05).

    Results: Results showed that the success rates were 34.1% and 27.3% for Li-KT and Li-Saline groups, respectively, with no significant difference between the two groups (P=0.48). However, significant decrease of baseline mean VAS pain score of the participants in both groups was found during access cavity preparation or initial file insertion (P<0.05).Conclusion: Mixed Li-KT solution did not increase the success rate of IANB injection significantly. (EEJ-2019-09-097)

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  • 2.
    Lahoud, P.
    et al.
    OMFS-IMPATH Research Group, Department of Imaging and Pathology, Faculty of Medicine, Leuven, Belgium;Department of Oral and Maxillofacial Surgery, University Hospitals Leuven, Leuven, Belgium; Division of Periodontology and Oral Microbiology, Department of Oral Health Sciences, KU Leuven, Leuven, Belgium.
    Faghihian, Hessamoddin
    Umeå University, Faculty of Medicine, Department of Odontology.
    Richert, R.
    Hospices Civils de Lyon, PAM Odontologie, Lyon, France; Laboratoire de Mécanique Des Contacts Et Structures LaMCoS, UMR 5259 INSA Lyon, CNRS, Villeurbanne 69621, France.
    Jacobs, R.
    OMFS-IMPATH Research Group, Department of Imaging and Pathology, Faculty of Medicine, Leuven, Belgium; Department of Oral and Maxillofacial Surgery, University Hospitals Leuven, Leuven, Belgium; Department of Dental Medicine, Karolinska Institute, Stockholm, Sweden.
    EzEldeen, M.
    OMFS-IMPATH Research Group, Department of Imaging and Pathology, Faculty of Medicine, Leuven, Belgium; Department of Oral and Maxillofacial Surgery, University Hospitals Leuven, Leuven, Belgium; Department of Oral Health Sciences, KU Leuven and Paediatric Dentistry and Special Dental Care, University Hospitals Leuven, KU Leuven, Leuven, Belgium.
    Finite element models: a road to in-silico modeling in the age of personalized dentistry2024In: Journal of Dentistry, ISSN 0300-5712, E-ISSN 1879-176X, Vol. 150, article id 105348Article in journal (Refereed)
    Abstract [en]

    Objective: This article reviews the applications of Finite Element Models (FEMs) in personalized dentistry, focusing on treatment planning, material selection, and CAD-CAM processes. It also discusses the challenges and future directions of using finite element analysis (FEA) in dental care.

    Data: This study synthesizes current literature and case studies on FEMs in personalized dentistry, analyzing research articles, clinical reports, and technical papers on the application of FEA in dental biomechanics.

    Sources: Sources for this review include peer-reviewed journals, academic publications, clinical case studies, and technical papers on dental biomechanics and finite element analysis. Key databases such as PubMed, Scopus, Embase, and ArXiv were used to identify relevant studies.

    Study selection: Studies were selected based on their relevance to the application of FEMs in personalized dentistry. Inclusion criteria were studies that discussed the use of FEA in treatment planning, material selection, and CAD-CAM processes in dentistry. Exclusion criteria included studies that did not focus on personalized dental treatments or did not utilize FEMs as a primary tool.

    Conclusions: FEMs are essential for personalized dentistry, offering a versatile platform for in-silico dental biomechanics modeling. They can help predict biomechanical behavior, optimize treatment outcomes, and minimize clinical complications. Despite needing further advancements, FEMs could help significantly enhance treatment precision and efficacy in personalized dental care.

    Clinical significance: FEMs in personalized dentistry hold the potential to significantly improve treatment precision and efficacy, optimizing outcomes and reducing complications. Their integration underscores the need for interdisciplinary collaboration and advancements in computational techniques to enhance personalized dental care.

     

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