Advances in Diagnosis and Treatment in Pediatric Dentistry

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Clinical Diagnosis and Prognosis".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 816

Special Issue Editors


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Guest Editor
1. Institute of Dental Clinic, A. Gemelli University Policlinic IRCCS, Catholic University of Sacred Heart, 00168 Rome, Italy
2. Postgraduate School of Orthodontics, Catholic University of Sacred Heart, Largo A. Gemelli 8, 00168 Rome, Italy
Interests: pediatric dentistry; special needs; proteomics; OSA
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
1. Institute of Dental Clinic, A. Gemelli University Policlinic IRCCS, Catholic University of Sacred Heart, 00168 Rome, Italy
2. Postgraduate School of Orthodontics, Catholic University of Sacred Heart, Largo A. Gemelli 8, 00168 Rome, Italy
Interests: orthodontics; 3D imaging; oral diagnosis; cleft palate
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor Assistant
1. Institute of Dental Clinic, A. Gemelli University Policlinic IRCCS, Catholic University of Sacred Heart, 00168 Rome, Italy
2. Postgraduate School of Orthodontics, Catholic University of Sacred Heart, Largo A. Gemelli 8, 00168 Rome, Italy
Interests: pediatric dentistry; proteomics; special needs; OSA

Special Issue Information

Dear Colleagues,

We are pleased to invite you to contribute to this Special Issue focused on the diagnosis of obstructive sleep apnea (OSA), interceptive orthodontics, and the management of patients with special needs in pediatric dentistry. Pediatric OSA is often underdiagnosed, despite its significant impact on craniofacial development, growth, and overall quality of life. Pediatric dentists and orthodontists play a crucial role in early diagnosis by assessing airway structures, occlusion, and clinical signs such as snoring or postural alterations. Additionally, interceptive orthodontic treatments, including functional appliances and rapid maxillary expansion, have shown promising results in reducing airway resistance and improving upper airway function. The management of pediatric patients with special needs, including those with neurodevelopmental disorders and motor disabilities, presents unique challenges in both the diagnosis of OSA and the application of orthodontic and dental treatments. Addressing these issues through a multidisciplinary approach is essential in optimizing patient care and outcomes.

This Special Issue will showcase the latest scientific evidence, clinical experiences, and innovative therapeutic approaches in the diagnosis and management of OSA, interceptive orthodontics, and the treatment of pediatric patients with special needs. Given the increasing recognition of the role of pediatric dentists and orthodontists in the early detection and management of airway-related issues, this topic is highly relevant to the journal’s scope. This Special Issue will foster interdisciplinary collaboration by bringing together expertise from pediatric dentistry, orthodontics, sleep medicine, and related fields. Our ultimate goal is to enhance awareness and promote best practices for early diagnosis and timely intervention, ultimately improving the quality of pediatric dental care.

For this Special Issue, original research articles, case reports, and reviews are welcome. Research areas may include the following:

  • Diagnosis and screening protocols for pediatric OSA;
  • Interceptive orthodontic approaches to airway improvement;
  • Challenges and adaptations in dental and orthodontic care for children with special needs;
  • Proteomics as a diagnostic tool in pediatric dentistry;
  • 3D imaging in orthodontics.

We look forward to receiving your contributions.

Dr. Patrizia Gallenzi
Dr. Edoardo Staderini
Guest Editors

Dr. Federica Guglielmi
Guest Editor Assistant

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • OSA
  • special needs patients
  • interceptive orthodontics
  • proteomics
  • 3D imaging
  • parafunctional habits

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Published Papers (1 paper)

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Research

16 pages, 1340 KB  
Article
Artificial Intelligence-Aided Tooth Detection and Segmentation on Pediatric Panoramic Radiographs in Mixed Dentition Using a Transfer Learning Approach
by Serena Incerti Parenti, Giorgio Tsiotas, Alessandro Maglioni, Giulia Lamberti, Andrea Fiordelli, Davide Rossi, Luciano Bononi and Giulio Alessandri-Bonetti
Diagnostics 2025, 15(20), 2615; https://doi.org/10.3390/diagnostics15202615 - 16 Oct 2025
Viewed by 495
Abstract
Background/Objectives: Accurate identification of deciduous and permanent teeth on panoramic radiographs (PRs) during mixed dentition is fundamental for early detection of eruption disturbances, yet relies heavily on clinician experience due to developmental variability. This study aimed to develop a deep learning model [...] Read more.
Background/Objectives: Accurate identification of deciduous and permanent teeth on panoramic radiographs (PRs) during mixed dentition is fundamental for early detection of eruption disturbances, yet relies heavily on clinician experience due to developmental variability. This study aimed to develop a deep learning model for automated tooth detection and segmentation in pediatric PRs during mixed dentition. Methods: A retrospective dataset of 250 panoramic radiographs from patients aged 6–13 years was analyzed. A customized YOLOv11-based model was developed using a novel hybrid pre-annotation strategy leveraging transfer learning from 650 publicly available adult radiographs, followed by expert manual refinement. Performance evaluation utilized mean average precision (mAP), F1-score, precision, and recall metrics. Results: The model demonstrated robust performance with mAP0.5 = 0.963 [95%CI: 0.944–0.983] and macro-averaged F1-score = 0.953 [95%CI: 0.922–0.965] for detection. Segmentation achieved mAP0.5 = 0.890 [95%CI: 0.857–0.923]. Stratified analysis revealed excellent performance for permanent teeth (F1 = 0.977) and clinically acceptable accuracy for deciduous teeth (F1 = 0.884). Conclusions: The automated system achieved near-expert accuracy in detecting and segmenting teeth during mixed dentition using an innovative transfer learning approach. This framework establishes reliable infrastructure for AI-assisted diagnostic applications targeting eruption or developmental anomalies, potentially facilitating earlier detection while reducing clinician-dependent variability in mixed dentition evaluation. Full article
(This article belongs to the Special Issue Advances in Diagnosis and Treatment in Pediatric Dentistry)
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