New Technologies in Oral Medicine: From Molecular Pathology to Clinical Practice

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Pathology and Molecular Diagnostics".

Deadline for manuscript submissions: 31 May 2025 | Viewed by 4442

Special Issue Editors


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Guest Editor
Department of Surgical, Medical and Molecular Pathology and Critical Care Medicine, University of Pisa, 56123 Pisa, Italy
Interests: oral medicine
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Unit of Dentistry and Oral Surgery, Department of Surgical, Medical and Molecular Pathology and Critical Care Medicine, University of Pisa, 56124 Pisa, Italy
Interests: oral medicine; oral surgery; clinical dentistry; MRONJ; diagnostic imaging
Special Issues, Collections and Topics in MDPI journals

E-Mail
Guest Editor
1. Department of Surgical, Medical and Molecular Pathology and Critical Care Medicine, University of Pisa, 56124 Pisa, Italy
2. Sub-Unit of Periodontology, Halitosis and Periodontal Medicine, University Hospital of Pisa, 56124 Pisa, Italy
Interests: clinical dentistry; oral surgery; periodontics; dental implantology; photobiomodulation; photodynamic therapy; dental biomaterials; laser therapy; light emitting diodes; temporary anchorage devices (TADs)
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, the field of oral medicine has undergone a transformative journey propelled by novel technologies. Cutting-edge advancements now enable a comprehensive understanding of oral diseases at the molecular level, revolutionizing diagnostics and treatment strategies. 

Molecular pathology has become a cornerstone, unraveling intricate genetic and molecular mechanisms underlying oral conditions. High-throughput sequencing techniques have unveiled a myriad of biomarkers, offering insights into disease progression, prognosis, and personalized therapeutic approaches. This molecular precision has paved the way for targeted therapies, optimizing outcomes and minimizing adverse effects.

In clinical practice, imaging technologies have evolved to provide detailed three-dimensional views, aiding in early detection and precise treatment planning. Cone-beam computed tomography (CBCT) and magnetic resonance imaging (MRI) have become invaluable tools, enhancing diagnostics for conditions ranging from temporomandibular joint disorders to oral cancers. In addition, the increasing application of high-resolution techniques, including ultrasonography, is paving the way towards an improvement in diagnostic accuracy.

Finally, artificial intelligence (AI) applications are making significant strides in oral medicine, streamlining data analysis and decision-making processes. AI algorithms can analyze vast datasets, identifying patterns that may elude human perception, thus expediting diagnosis and improving treatment outcomes.

As oral medicine embraces these technologies, the deeper understanding of oral pathologies at the molecular level could also be translated into tangible improvements in clinical practice, propelling the field towards a future of personalized, efficient, and patient-centered care.

The objective of this Special Issue is to spotlight innovative diagnostic approaches utilized in oral medicine, offering a glimpse into a focused and effective approach to oral healthcare.

Dr. Rossana Izzetti
Dr. Marco Nisi
Dr. Stefano Gennai
Guest Editors

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Keywords

  • oral medicine
  • molecular pathology
  • clinical dentistry
  • periodontics
  • orthodontics

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Published Papers (4 papers)

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Research

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10 pages, 545 KiB  
Article
Single-Nucleotide Polymorphisms in WNT Genes in Patients with Non-Syndromic Orofacial Clefts in a Polish Population
by Alicja Zawiślak, Krzysztof Woźniak, Gianluca Tartaglia, Xabier Agirre, Satish Gupta, Beata Kawala, Anna Znamirowska-Bajowska, Katarzyna Grocholewicz, Felipe Prosper, Jan Lubiński and Anna Jakubowska
Diagnostics 2024, 14(14), 1537; https://doi.org/10.3390/diagnostics14141537 - 17 Jul 2024
Cited by 1 | Viewed by 1243
Abstract
Non-syndromic orofacial cleft (OFC) is the most common facial developmental defect in the global population. The etiology of these birth defects is complex and multifactorial, involving both genetic and environmental factors. This study aimed to determine if SNPs in the WNT gene family [...] Read more.
Non-syndromic orofacial cleft (OFC) is the most common facial developmental defect in the global population. The etiology of these birth defects is complex and multifactorial, involving both genetic and environmental factors. This study aimed to determine if SNPs in the WNT gene family (rs1533767, rs708111, rs3809857, rs7207916, rs12452064) are associated with OFCs in a Polish population. The study included 627 individuals: 209 children with OFCs and 418 healthy controls. DNA was extracted from saliva for the study group and from umbilical cord blood for the control group. Polymorphism genotyping was conducted using quantitative PCR. No statistically significant association was found between four variants and clefts, with odds ratios for rs708111 being 1.13 (CC genotype) and 0.99 (CT genotype), for rs3809857 being 1.05 (GT genotype) and 0.95 (TT genotype), for rs7207916 being 0.86 (AA genotype) and 1.29 (AG genotype) and for rs12452064 being 0.97 (AA genotype) and 1.24 (AG genotype). However, the rs1533767 polymorphism in WNT showed a statistically significant increase in OFC risk for the GG genotype (OR = 1.76, p < 0.001). This research shows that the rs1533767 polymorphism in the WNT gene is an important risk marker for OFC in the Polish population. Full article
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12 pages, 391 KiB  
Article
Classification-Predictive Model Based on Artificial Neural Network Validated by Histopathology and Direct Immunofluorescence for the Diagnosis of Oral Lichen Planus
by Katarzyna Osipowicz, Piotr Turkowski and Izabela Zdolińska-Malinowska
Diagnostics 2024, 14(14), 1525; https://doi.org/10.3390/diagnostics14141525 - 15 Jul 2024
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Abstract
The diagnosis of oral lichen planus (OLP) poses many challenges due to its nonspecific clinical symptoms and histopathological features. Therefore, the diagnostic process should include a thorough clinical history, immunological tests, and histopathology. Our study aimed to enhance the diagnostic accuracy of OLP [...] Read more.
The diagnosis of oral lichen planus (OLP) poses many challenges due to its nonspecific clinical symptoms and histopathological features. Therefore, the diagnostic process should include a thorough clinical history, immunological tests, and histopathology. Our study aimed to enhance the diagnostic accuracy of OLP by integrating direct immunofluorescence (DIF) results with clinical data to develop a multivariate predictive model based on the Artificial Neural Network. Eighty patients were assessed using DIF for various markers (immunoglobulins of classes G, A, and M; complement 3; fibrinogen type 1 and 2) and clinical characteristics such as age, gender, and lesion location. Statistical analysis was performed using machine learning techniques in Statistica 13. The following variables were assessed: gender, age on the day of lesion onset, results of direct immunofluorescence, location of white patches, locations of erosions, treatment history, medications and dietary supplement intake, dental status, smoking status, flossing, and using mouthwash. Four statistically significant variables were selected for machine learning after the initial assessment. The final predictive model, based on neural networks, achieved 85% in the testing sample and 71% accuracy in the validation sample. Significant predictors included stress at onset, white patches under the tongue, and erosions on the mandibular gingiva. In conclusion, while the model shows promise, larger datasets and more comprehensive variables are needed to improve diagnostic accuracy for OLP, highlighting the need for further research and collaborative data collection efforts. Full article
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9 pages, 568 KiB  
Article
Demirjian’s and Cameriere’s Methods for the Assessment of Dental Age Estimation in Children from a Southern Brazilian City
by Julia Carelli, Gabriela Sabrina da Silva, Mariana Vegini Gomes, Thais Vilalba, Flares Baratto-Filho, João Armando Brancher, Svenja Beisel-Memmert, Christian Kirschneck, Celia Maria Condeixa de França Lopes, Alexandre Moro and Erika Calvano Küchler
Diagnostics 2024, 14(14), 1513; https://doi.org/10.3390/diagnostics14141513 - 13 Jul 2024
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Abstract
The chronological age estimation of living individuals is a crucial part of forensic practice and clinical practice, such as in orthodontic treatment. It is well-known that methods for age estimation in living children should be tested on different populations. Ethnic affiliations in Brazil [...] Read more.
The chronological age estimation of living individuals is a crucial part of forensic practice and clinical practice, such as in orthodontic treatment. It is well-known that methods for age estimation in living children should be tested on different populations. Ethnic affiliations in Brazil are divided into several major groups depending on the region, with the south of Brazil being known for its German immigration. (1) Background: This study aimed to evaluate the correlation between chronological age and dental age using Demirjian’s method and Cameriere’s method in a group of children from Joinville, South Brazil to investigate if both methods can be used to estimate dental age in this population. (2) Methods: The sample consisted of 229 panoramic radiographs (119 were males and were 110 females) from Brazilian children (ages ranging from 6 to 12 years). The chronological age at the time of the panoramic radiographic exam was calculated for each child. The dental age was estimated according to Demirjian’s method and Cameriere’s method. All continuous data were tested for normality by using the Shapiro–Wilk test. The Pearson correlation coefficient test was applied. An alpha of 5% (p < 0.05) was used for all analyses. (3) Results: The mean chronological age was 8.75 years. According to Demirjian’s method, the mean dental age was 9.3 years, while according to Cameriere’s method, the mean dental age was 8.66 years. A strong correlation between chronological age and dental age according to Demirjian (r = 0.776 and p < 0.0001) and Cameriere (r = 0.735 and p < 0.0001) was observed for both genders. (4) Conclusions: Both methods presented a good correlation with chronological age in the studied population and could be used to assess dental age in this population. Full article
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30 pages, 2672 KiB  
Systematic Review
The Diagnostic Potential of Non-Invasive Tools for Oral Cancer and Precancer: A Systematic Review
by Tania Vanessa Pierfelice, Emira D’Amico, Chiara Cinquini, Giovanna Iezzi, Camillo D’Arcangelo, Simonetta D’Ercole and Morena Petrini
Diagnostics 2024, 14(18), 2033; https://doi.org/10.3390/diagnostics14182033 - 13 Sep 2024
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Abstract
Objectives: This systematic review aimed to analyse the published evidence for the use of non-invasive methods for the early detection of oral squamous cell carcinoma (OSCC) and oral potentially malignant disorders (OPMDs). Methods: The literature was systematically searched through several databases: PubMed, Cochrane [...] Read more.
Objectives: This systematic review aimed to analyse the published evidence for the use of non-invasive methods for the early detection of oral squamous cell carcinoma (OSCC) and oral potentially malignant disorders (OPMDs). Methods: The literature was systematically searched through several databases: PubMed, Cochrane Library, and Web of Science. Additional exploration was performed through cross-checks on the bibliographies of selected reviews. The inclusion criteria involved studies assessing the application of non-invasive tests on humans in the screening, diagnosis, or surveillance of OSCC or OPMDs and reporting sensitivity (SE) and specificity (SP). The Newcastle–Ottawa scale (NOS) was applied to assess the quality of the studies included. Results: The search strategy resulted in 8012 preliminary records. After a duplicate check, 116 titles remained. After abstract analysis, 70 papers remained. After full text analysis, only 54 of the 70 papers fit the inclusion criteria (28 were original articles and 26 were reviews). Those 26 reviews were used to manually search for further original articles. From this last search, 33 original articles were found. Thus, a total of 61 original studies were included and investigated. Findings from this systematic review indicate useful information, such as a description of the mechanisms, ease of use, limitations, and SE and SP values, to drive the choice of the optimal minimally invasive method to be utilized as an adjunctive tool to examine the suspicious lesions. Conclusions: Each of the analysed tools can be improved or implemented, considering their high SE and low SP. Despite advancements, incisional biopsy continues to be the gold standard for the definitive diagnosis of oral cancer and precancerous lesions. Further research and development are essential to improving the sensitivity, specificity, and reliability of non-invasive tools for widespread clinical application. Full article
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