Andrej Thurzo
@uniba.sk
Department of Orthodontics, Regenerative and Forensic Dentistry, Faculty of Medicine Comenius University in Bratislava, Slovakia
Comenius University in Bratislava, Slovakia
is an Associate Professor in the Department of Stomatology and Maxillofacial Surgery and in the Center of simulation and virtual medical education at the Faculty of Medicine, Comenius University in Bratislava, Slovakia. He is a Forensic expert in the field of dentistry.
Education background: 2000–2006 - Medical faculty Comenius University, graduation (MD) specialization dentistry 2006–2009 - 1st approbation from stomatology 2006–2011 - PhD (Implementation of digital systems in orthodontics) 2009–2012 - 2nd approbation from orthodontics 2010–2013 - Master of public Health (MPH) 2013–2014 - Master of Health Administration (MHA) 2022 - habilitation Comenius University - Associate Professor Education abroad: 2009: USA, Chapel Hill - University of North Carolina, with Prof. William R. Proffit, Former Chair of Orthodontics 2005 :Italy, Rome - Erasmus at Faculty of Medicine at Università Cattolica del Sacro Cuore, Gemelli University Hospital Work experience; Since 2006—Univer
EDUCATION
2000-2006 - (MD) Comenius University, Medical faculty (LFUK), specialization dentistry
2006-2009 - 1st approbation from stomatology - Slovak Medical University
2006-2011 - PhD (Implementation of digital systems in orthodontics) (LFUK)
2009-2012 - 2nd approbation from orthodontics – Slovak Medical University
2010-2013 - Master of public Health (MPH) - Slovak Medical University
2013-2014 - (MHA)Master of Health Administration - College of Health&Social Work
2022 – assistant professor (doc. habilitation) Comenius University, Medical faculty,
RESEARCH INTERESTS
3D medical printing, bioprinting, artificial intelligence, orthodontics, forensic dentistry, regenerative medicine
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Daniela Tichá, Juraj Tomášik, Ľubica Oravcová, and Andrej Thurzo
MDPI AG
Three-dimensional printing has transformed dentistry by enabling the production of customized dental restorations, aligners, surgical guides, and implants. A variety of polymers and composites are used, each with distinct properties. This review explores materials used in 3D printing for dental applications, focusing on trends identified through a literature search in PubMed, Scopus, and the Web of Science. The most studied areas include 3D-printed crowns, bridges, removable prostheses, surgical guides, and aligners. The development of new materials is still ongoing and also holds great promise in terms of environmentally friendly technologies. Modern manufacturing technologies have a promising future in all areas of dentistry: prosthetics, periodontology, dental and oral surgery, implantology, orthodontics, and regenerative dentistry. However, further studies are needed to safely introduce the latest materials, such as nanodiamond-reinforced PMMA, PLA reinforced with nanohydroxyapatite or magnesium, PLGA composites with tricalcium phosphate and magnesium, and PEEK reinforced with hydroxyapatite or titanium into clinical practice.
Peter Kováč, Peter Jackuliak, Alexandra Bražinová, Ivan Varga, Michal Aláč, Martin Smatana, Dušan Lovich, and Andrej Thurzo
MDPI AG
This narrative review explores the potential, complexities, and consequences of using artificial intelligence (AI) to screen large government-held facial image databases for the early detection of rare genetic diseases. Government-held facial image databases, combined with the power of artificial intelligence, offer the potential to revolutionize the early diagnosis of rare genetic diseases. AI-powered phenotyping, as exemplified by the Face2Gene app, enables highly accurate genetic assessments from simple photographs. This and similar breakthrough technologies raise significant privacy and ethical concerns about potential government overreach augmented with the power of AI. This paper explores the concept, methods, and legal complexities of AI-based phenotyping within the EU. It highlights the transformative potential of such tools for public health while emphasizing the critical need to balance innovation with the protection of individual privacy and ethical boundaries. This comprehensive overview underscores the urgent need to develop robust safeguards around individual rights while responsibly utilizing AI’s potential for improved healthcare outcomes, including within a forensic context. Furthermore, the intersection of AI and sensitive genetic data necessitates proactive cybersecurity measures. Current and future developments must focus on securing AI models against attacks, ensuring data integrity, and safeguarding the privacy of individuals within this technological landscape.
Juraj Tomášik, Márton Zsoldos, Kristína Majdáková, Alexander Fleischmann, Ľubica Oravcová, Dominika Sónak Ballová and Andrej Thurzo
Improving one’s appearance is one of the main reasons to undergo an orthodontic therapy. While occlusion is important, not just for long-term stability, aesthetics is often considered a key factor in patient’s satisfaction. Following recent advances in artificial intelligence (AI), this study set out to investigate whether AI can help guide orthodontists in diagnosis and treatment planning. In this study, 25 male and 25 female faces were generated and consequently enhanced using FaceApp (ver. 11.10, FaceApp Technology Limited, Limassol, Cyprus), one of the many pictures transforming applications on the market. Both original and FaceApp-modified pictures were then assessed by 441 respondents regarding their attractiveness, and the pictures were further compared using a software for picture analyses. Statistical analysis was performed using Chi-square goodness of fit test R Studio Studio (ver. 4.1.1, R Core Team, Vienna, Austria) software and the level of statistical significance was set to 0.05. The interrater reliability was tested using Fleiss’ Kappa for m Raters. The results showed that in 49 out of 50 cases, the FaceApp-enhanced pictures were considered to be more attractive. Selected pictures were further analyzed using the graphical software GIMP. The most prominent changes were observed in lip fullness, eye size, and lower face height. The results suggest that AI-powered face enhancement could be a part of the diagnosis and treatment planning stages in orthodontics. These enhanced pictures could steer clinicians towards soft-tissue-oriented and personalized treatment planning, respecting patients’ wishes for improved face appearance.
Ľuboš Bača, Tatiana Sivčáková, Zuzana Varchulová Nováková, Marián Matejdes, Martina Horváth Orlovská, Andrej Thurzo, Ľuboš Danišovič, and Marián Janek
Elsevier BV
Michal Gašparovič, Petra Jungová, Juraj Tomášik, Bela Mriňáková, Dušan Hirjak, Silvia Timková, Ľuboš Danišovič, Marián Janek, Ľuboš Bača, Peter Peciar,et al.
MDPI AG
Regenerative dentistry has experienced remarkable advancement in recent years. The interdisciplinary discoveries in stem cell applications and scaffold design and fabrication, including novel techniques and biomaterials, have demonstrated immense potential in the field of tissue engineering and regenerative therapy. Scaffolds play a pivotal role in regenerative dentistry by facilitating tissue regeneration and restoring damaged or missing dental structures. These biocompatible and biomimetic structures serve as a temporary framework for cells to adhere, proliferate, and differentiate into functional tissues. This review provides a concise overview of the evolution of scaffold strategies in regenerative dentistry, along with a novel analysis (Bard v2.0 based on the Gemini neural network architecture) of the most commonly employed materials used for scaffold fabrication during the last 10 years. Additionally, it delves into bioprinting, stem cell colonization techniques and procedures, and outlines the prospects of regenerating a whole tooth in the future. Moreover, it discusses the optimal conditions for maximizing mesenchymal stem cell utilization and optimizing scaffold design and personalization through precise 3D bioprinting. This review highlights the recent advancements in scaffold development, particularly with the advent of 3D bioprinting technologies, and is based on a comprehensive literature search of the most influential recent publications in this field.
Juraj Tomášik, Márton Zsoldos, Ľubica Oravcová, Michaela Lifková, Gabriela Pavleová, Martin Strunga, and Andrej Thurzo
MDPI AG
In the age of artificial intelligence (AI), technological progress is changing established workflows and enabling some basic routines to be updated. In dentistry, the patient’s face is a crucial part of treatment planning, although it has always been difficult to grasp in an analytical way. This review highlights the current digital advances that, thanks to AI tools, allow us to implement facial features beyond symmetry and proportionality and incorporate facial analysis into diagnosis and treatment planning in orthodontics. A Scopus literature search was conducted to identify the topics with the greatest research potential within digital orthodontics over the last five years. The most researched and cited topic was artificial intelligence and its applications in orthodontics. Apart from automated 2D or 3D cephalometric analysis, AI finds its application in facial analysis, decision-making algorithms as well as in the evaluation of treatment progress and retention. Together with AI, other digital advances are shaping the face of today’s orthodontics. Without any doubts, the era of “old” orthodontics is at its end, and modern, face-driven orthodontics is on the way to becoming a reality in modern orthodontic practices.
Andrej Thurzo, Petra Jungová, and Ľuboš Danišovič
IEEE
The era of 3D printing of biocompatible personalized scaffolds has arrived, and Cone Beam Computed Tomography (CBCT) is essential for 3D reproduction of individualized human anatomy. When designing the shape of the personalized scaffold, the starting point is typically the CBCT scan, which must first be segmented to define the complementary shape of the scaffold. In the past, this was usually a lengthy manual segmentation process that could take hours. Today, artificial intelligence-based software can perform automatic segmentation of the various structures in the maxillo-facial region directly from CBCT data in seconds. This study presents a novel workflow comparing manual segmentation in Invivo (Anatomage, San Jose, CA, USA) with AI-automated segmentation in Diagnocat (Miami, FL, USA). In 24 cases, the time required for segmentation were compared and evaluated with a paired t-test. This revealed a statistically significant difference in segmentation time between the two groups, with the AI-driven analysis being significantly faster. The difference in average segmentation time between manual (36.03 minutes) and AI-driven analysis (4.96 minutes) showed that AI-driven analysis was on average more than five time faster than manual segmentation. AI-driven analysis reduces segmentation time by 86.17% compared to manual segmentation of CBCT. This means that AI-driven analysis can save clinicians a lot of time. The presented feasibility of AI-automated workflow with STL (Standard Triangle Language) output models suitable for 3D modeling of scaffold shapes - complementary to individual anatomy in Meshmixer (Autodesk, San Rafael, CA, USA), were suitable for 3D printing with hydroxyapatite. This has significance for various workflows in regenerative dentistry.
Martin Strunga, Dominika Sόnak Ballová, Juraj Tomášik, Ľubica Oravcová, Ľuboš Danišovič, and Andrej Thurzo
IEEE
Cephalometric analysis has typically been used to evaluate lateral skull radiographs taken with a cephalostat to determine the skeletal pattern and assess treatment difficulties in orthodontics. Nowadays, Cone beam computed tomography (CBCT) data can be used for 3D cephalometrics. This study compares the performance of AI-automated cephalometric tracing with human-operated digital tracing using the Invivo 7.1.2 software on a sample of 120 scans evaluated by 5 observers (4 human and AI) for 14 cephalometric variables. Measurements were repeated for paired tests. ANOVA was used to minimize type I error. Normality of the data was tested using the Shapiro-Wilk test. The Wilcoxon test was used to compare measurement times between humans and AI. This study found that there were statistically significant differences between human observers and AI in 6 of 14 variables. The AI measurements were higher than the human measurements for these variables. The duration of measurements was also statistically significantly shorter for human observers than for AI. Now at the dawn of an era of AI-assisted diagnostics, we temporarily experience translational period of AI-automated algorithms being less accurate and slower than humans, albeit they will likely become the new normal in orthodontic treatment planning. This study also highlights the importance of rigorous scientific evaluation by independent researchers of incoming AI-automated cephalometric tracing solutions before they are considered clinically appropriate.
Veronika Kurilová, Dominika Bemberáková, Matúš Kocián, Daniel Šterbák, Tomáš Knapčok, Miriam Palkovič, Samuel Hančák, Jarmila Pavlovičová, Miloš Oravec, Andrej Thurzo,et al.
Walter de Gruyter GmbH
Abstract Reconstruction of a 3D eye model by photogrammetry from a smartphone video could be prospectively used in self-diagnosis, screening and telemedicine monitoring of diseases of the front part of the eye and its surroundings. The main use could be found in the treatment of diseases of the curvature and surface of the cornea and in follow-up after some refractive procedures. In our work, we create 3D image-based models of the eye after scanning the face with a smartphone. An unexpected phenomenon appeared during the reconstruction of the transparent cornea – a crater-like depression was formed at the place where nearby objects reflected on the cornea, which corresponds to the first Purkinje image, the so-called glint. We thus encountered complications that may arise when modelling transparent living structures from a video taken in a normal environment, which will need to be solved if we want to create such 3D models of the eye using this method for medical purposes. Another 3D reconstruction approach or additional algorithms must be considered as a future work.
Martin Čverha, Ivan Varga, Tereza Trenčanská, Barbora Šufliarsky, and Andrej Thurzo
MDPI AG
The Robin sequence is a congenital anomaly characterized by a triad of features: micrognathia, glossoptosis, and airway obstruction. This comprehensive historical review maps the evolution of approaches and appliances for its treatment from the past to the current modern possibilities of an interdisciplinary combination of modern engineering, medicine, materials, and computer science combined approach with emphasis on designing appliances inspired by nature and individual human anatomy. Current biomimetic designs are clinically applied, resulting in appliances that are more efficient, comfortable, sustainable, and safer than legacy traditional designs. This review maps the treatment modalities that have been used for patients with a Robin sequence over the years. Early management of the Robin sequence focused primarily on airway maintenance and feeding support, while current management strategies involve both nonsurgical and surgical interventions and biomimetic biocompatible personalized appliances. The goal of this paper was to provide a review of the evolution of management strategies for patients with the Robin sequence that led to the current interdisciplinary biomimetic approaches impacting the future of Robin Sequence treatment with biomimetics at the forefront.
Petra Švábová nee Uhrová, Radoslav Beňuš, Mária Chovancová nee Kondeková, Adriana Vojtušová, Miroslav Novotný, and Andrej Thurzo
Springer Science and Business Media LLC
Jana Surovková, Sára Haluzová, Martin Strunga, Renáta Urban, Michaela Lifková, and Andrej Thurzo
MDPI AG
This paper explores the impact of Artificial Intelligence (AI) on the role of dental assistants and nurses in orthodontic practices, as there is a gap in understanding the currently evolving impact on orthodontic treatment workflows. The introduction of AI-language models such as ChatGPT 4 is changing patient-office communication and transforming the role of orthodontic nurses. Teledentistry is now heavily reliant on AI implementation in orthodontics. This paper presents the proof of a novel concept: an AI-powered orthodontic workflow that provides new responsibilities for an orthodontic nurse. It also provides a report of an assessment of such a workflow in an orthodontic practice that uses an AI solution called Dental Monitoring over a period of three years. The paper evaluates the benefits and drawbacks of daily automated assessments of orthodontic treatment progress, the impact of AI on personalized care, and the new role of a dental assistant. The paper concludes that AI will improve dental practice through more precise and personalized treatment, bringing new roles and responsibilities for trained medical professionals but raising new ethical and legal issues for dental practices.
Renáta Urban, Sára Haluzová, Martin Strunga, Jana Surovková, Michaela Lifková, Juraj Tomášik, and Andrej Thurzo
MDPI AG
Within the next decade, artificial intelligence (AI) will fundamentally transform the workflow of modern dental practice. This paper reviews the innovations and new roles of dental assistants in CBCT data management with the support of AI. Its use in 3D data management brings new roles for dental assistants. Cone beam computed tomography (CBCT) technology is, together with intraoral 3D scans and 3D facial scans, commonly used 3D diagnostic in a modern digital dental practice. This paper provides an overview of the potential benefits of AI implementation for semiautomated segmentations in standard medical diagnostic workflows in dental practice. It discusses whether AI tools can enable healthcare professionals to increase their reliability, effectiveness, and usefulness, and addresses the potential limitations and errors that may occur. The paper concludes that current AI solutions can improve current digital workflows including CBCT data management. Automated CBCT segmentation is one of the current trends and innovations. It can assist professionals in obtaining an accurate 3D image in a reduced period of time, thus enhancing the efficiency of the whole process. The segmentation of CBCT serves as a helpful tool for treatment planning as well as communicating the problem to the patient in an understandable way. This paper highlights a high bias risk due to the inadequate sample size and incomplete reporting in many studies. It proposes enhancing dental workflow efficiency and accuracy through AI-supported cbct data management
Martin Strunga, Renáta Urban, Jana Surovková, and Andrej Thurzo
MDPI AG
This scoping review examines the contemporary applications of advanced artificial intelligence (AI) software in orthodontics, focusing on its potential to improve daily working protocols, but also highlighting its limitations. The aim of the review was to evaluate the accuracy and efficiency of current AI-based systems compared to conventional methods in diagnosing, assessing the progress of patients’ treatment and follow-up stability. The researchers used various online databases and identified diagnostic software and dental monitoring software as the most studied software in contemporary orthodontics. The former can accurately identify anatomical landmarks used for cephalometric analysis, while the latter enables orthodontists to thoroughly monitor each patient, determine specific desired outcomes, track progress, and warn of potential changes in pre-existing pathology. However, there is limited evidence to assess the stability of treatment outcomes and relapse detection. The study concludes that AI is an effective tool for managing orthodontic treatment from diagnosis to retention, benefiting both patients and clinicians. Patients find the software easy to use and feel better cared for, while clinicians can make diagnoses more easily and assess compliance and damage to braces or aligners more quickly and frequently.
Andrej Thurzo, Martin Strunga, Renáta Urban, Jana Surovková, and Kelvin I. Afrashtehfar
MDPI AG
In this intellectual work, the clinical and educational aspects of dentistry were confronted with practical applications of artificial intelligence (AI). The aim was to provide an up-to-date overview of the upcoming changes and a brief analysis of the influential advancements in the use of AI in dental education since 2020. In addition, this review provides a guide for a dental curriculum update for undergraduate and postgraduate education in the context of advances in AI applications and their impact on dentistry. Unsurprisingly, most dental educators have limited knowledge and skills to assess AI applications, as they were not trained to do so. Also, AI technology has evolved exponentially in recent years. Factual reliability and opportunities with OpenAI Inc.’s ChatGPT are considered critical inflection points in the era of generative AI. Updating curricula at dental institutions is inevitable as advanced deep-learning approaches take over the clinical areas of dentistry and reshape diagnostics, treatment planning, management, and telemedicine screening. With recent advances in AI language models, communication with patients will change, and the foundations of dental education, including essay, thesis, or scientific paper writing, will need to adapt. However, there is a growing concern about its ethical and legal implications, and further consensus is needed for the safe and responsible implementation of AI in dental education.
Andrej Thurzo, Paulína Gálfiová, Zuzana Varchulová Nováková, Štefan Polák, Ivan Varga, Martin Strunga, Renáta Urban, Jana Surovková, Ľuboš Leško, Zora Hajdúchová,et al.
MDPI AG
This paper presents a proof-of-concept study on the biocolonization of 3D-printed hydroxyapatite scaffolds with mesenchymal stem cells (MSCs). Three-dimensional (3D) printed biomimetic bone structure made of calcium deficient hydroxyapatite (CDHA) intended as a future bone graft was made from newly developed composite material for FDM printing. The biopolymer polyvinyl alcohol serves in this material as a thermoplastic binder for 3D molding of the printed object with a passive function and is completely removed during sintering. The study presents the material, the process of fused deposition modeling (FDM) of CDHA scaffolds, and its post-processing at three temperatures (1200, 1300, and 1400 °C), as well it evaluates the cytotoxicity and biocompatibility of scaffolds with MTT and LDH release assays after 14 days. The study also includes a morphological evaluation of cellular colonization with scanning electron microscopy (SEM) in two different filament orientations (rectilinear and gyroid). The results of the MTT assay showed that the tested material was not toxic, and cells were preserved in both orientations, with most cells present on the material fired at 1300 °C. Results of the LDH release assay showed a slight increase in LDH leakage from all samples. Visual evaluation of SEM confirmed the ideal post-processing temperature of the 3D-printed FDM framework for samples fired at 1300 °C and 1400 °C, with a porosity of 0.3 mm between filaments. In conclusion, the presented fabrication and colonization of CDHA scaffolds have great potential to be used in the tissue engineering of bones.
Andrej Thurzo, Martin Strunga, Romana Havlínová, Katarína Reháková, Renata Urban, Jana Surovková, and Veronika Kurilová
MDPI AG
The current paradigm shift in orthodontic treatment planning is based on facially driven diagnostics. This requires an affordable, convenient, and non-invasive solution for face scanning. Therefore, utilization of smartphones’ TrueDepth sensors is very tempting. TrueDepth refers to front-facing cameras with a dot projector in Apple devices that provide real-time depth data in addition to visual information. There are several applications that tout themselves as accurate solutions for 3D scanning of the face in dentistry. Their clinical accuracy has been uncertain. This study focuses on evaluating the accuracy of the Bellus3D Dental Pro app, which uses Apple’s TrueDepth sensor. The app reconstructs a virtual, high-resolution version of the face, which is available for download as a 3D object. In this paper, sixty TrueDepth scans of the face were compared to sixty corresponding facial surfaces segmented from CBCT. Difference maps were created for each pair and evaluated in specific facial regions. The results confirmed statistically significant differences in some facial regions with amplitudes greater than 3 mm, suggesting that current technology has limited applicability for clinical use. The clinical utilization of facial scanning for orthodontic evaluation, which does not require accuracy in the lip region below 3 mm, can be considered.
Andrej Thurzo, Barbora Šufliarsky, Wanda Urbanová, Martin Čverha, Martin Strunga, and Ivan Varga
MDPI AG
This paper introduces a complex novel concept and methodology for the creation of personalized biomedical appliances 3D-printed from certified biocompatible photopolymer resin Dental LT Clear (V2). The explained workflow includes intraoral and CT scanning, patient virtualization, digital appliance design, additive manufacturing, and clinical application with evaluation of the appliance intended for patients with cranio-facial syndromes. The presented concept defines virtual 3D fusion of intraoral optical scan and segmented CT as sufficient and accurate data defining the 3D surface of the face, intraoral and airway morphology necessary for the 3D design of complex personalized intraoral and extraoral parts of the orthopedic appliance. A central aspect of the concept is a feasible utilization of composite resin for biomedical prototyping of the sequence of marginally different appliances necessary to keep the pace with the patient rapid growth. Affordability, noninvasiveness, and practicality of the appliance update process shall be highlighted. The methodology is demonstrated on a particular case of two-year-old infant with Pierre Robin sequence. Materialization by additive manufacturing of this photopolymer provides a highly durable and resistant-to-fracture two-part appliance similar to a Tübingen palatal plate, for example. The paper concludes with the viability of the described method and material upon interdisciplinary clinical evaluation of experts from departments of orthodontics and cleft anomalies, pediatric pneumology and phthisiology, and pediatric otorhinolaryngology.
Georgia Fountoulaki and Andrej Thurzo
MDPI AG
This retrospective study evaluated changes in the pharyngeal portion of the upper airway in patients with constricted and normal airways treated with clear aligners (Invisalign, Align). Additionally, we assessed the change of tongue position in the oral cavity from a lateral view. Evaluation was performed with specialized software (Invivo 6.0, Anatomage) on pretreatment and post-treatment pairs of cone beam computed tomography imaging (CBCT) data. The level of airway constriction, volume, cross-section minimal area and tongue profile were evaluated. Patients with malocclusion, with pair or initial and finishing CBCT and without significant weight change between the scans, treated with Invisalign clear aligners were distributed into two groups. Group A consisted of fifty-five patients with orthodontic malocclusion and constricted upper airway. Control group B consisted of thirty-one patients with orthodontic malocclusions without any airway constriction. In the group with airway constriction there was a statistically significant increase in volume during therapy (p < 0.001). The surface of the most constricted cross-section of the airway did not change significantly after treatment in any of the groups. The final tongue position was different from the initial position in 62.2% of all clear aligner treatments. The position of the smallest clearance of the airway in the pharynx was similar for both groups localized at the level of 2nd cervical vertebra.
Andrej Thurzo, Wanda Urbanová, Bohuslav Novák, Ladislav Czako, Tomáš Siebert, Peter Stano, Simona Mareková, Georgia Fountoulaki, Helena Kosnáčová, and Ivan Varga
MDPI AG
This literature research had two main objectives. The first objective was to quantify how frequently artificial intelligence (AI) was utilized in dental literature from 2011 until 2021. The second objective was to distinguish the focus of such publications; in particular, dental field and topic. The main inclusion criterium was an original article or review in English focused on dental utilization of AI. All other types of publications or non-dental or non-AI-focused were excluded. The information sources were Web of Science, PubMed, Scopus, and Google Scholar, queried on 19 April 2022. The search string was “artificial intelligence” AND (dental OR dentistry OR tooth OR teeth OR dentofacial OR maxillofacial OR orofacial OR orthodontics OR endodontics OR periodontics OR prosthodontics). Following the removal of duplicates, all remaining publications were returned by searches and were screened by three independent operators to minimize the risk of bias. The analysis of 2011–2021 publications identified 4413 records, from which 1497 were finally selected and calculated according to the year of publication. The results confirmed a historically unprecedented boom in AI dental publications, with an average increase of 21.6% per year over the last decade and a 34.9% increase per year over the last 5 years. In the achievement of the second objective, qualitative assessment of dental AI publications since 2021 identified 1717 records, with 497 papers finally selected. The results of this assessment indicated the relative proportions of focal topics, as follows: radiology 26.36%, orthodontics 18.31%, general scope 17.10%, restorative 12.09%, surgery 11.87% and education 5.63%. The review confirms that the current use of artificial intelligence in dentistry is concentrated mainly around the evaluation of digital diagnostic methods, especially radiology; however, its implementation is expected to gradually penetrate all parts of the profession.
Andrej Thurzo, Viera Jančovičová, Miroslav Hain, Milan Thurzo, Bohuslav Novák, Helena Kosnáčová, Viera Lehotská, Ivan Varga, Peter Kováč, and Norbert Moravanský
MDPI AG
(1) Teeth, in humans, represent the most resilient tissues. However, exposure to concentrated acids might lead to their dissolving, thus making human identification difficult. Teeth often contain dental restorations from materials that are even more resilient to acid impact. This paper aims to introduce a novel method for the 3D reconstruction of dental patterns as a crucial step for the digital identification of dental records. (2) With a combination of modern methods, including micro-computed tomography, cone-beam computer tomography, and attenuated total reflection, in conjunction with Fourier transform infrared spectroscopy and artificial intelligence convolutional neural network algorithms, this paper presents a method for 3D-dental-pattern reconstruction, and human remains identification. Our research studies the morphology of teeth, bone, and dental materials (amalgam, composite, glass-ionomer cement) under different periods of exposure to 75% sulfuric acid. (3) Our results reveal a significant volume loss in bone, enamel, dentine, as well as glass-ionomer cement. The results also reveal a significant resistance by the composite and amalgam dental materials to the impact of sulfuric acid, thus serving as strong parts in the dental-pattern mosaic. This paper also probably introduces the first successful artificial intelligence application in automated-forensic-CBCT segmentation. (4) Interdisciplinary cooperation, utilizing the mentioned technologies, can solve the problem of human remains identification with a 3D reconstruction of dental patterns and their 2D projections over existing ante-mortem records.
Andrej Thurzo, Wanda Urbanová, Iveta Waczulíková, Veronika Kurilová, Bela Mriňáková, Helena Kosnáčová, Branislav Gális, Ivan Varga, Marek Matajs, and Bohuslav Novák
MDPI AG
With the arrival of the highly transmissible Omicron variants (BA.4 and BA.5), dentistry faces another seasonal challenge to preserve the biosafety of dental care and education. With the aim of protecting patients, students, teachers and healthcare professionals, this paper introduces a prospective sustainable biosafety setting for everyday dental care and education. The setting developed by dental clinicians, epidemiologists, and teachers of dentistry consists of a combination of modern technologies focused on the air-borne part of the viral pathway. The introduced biosafety setting has been clinically evaluated after 18 months of application in the real clinical environment. The protocol has three fundamental pillars: (1) UVC air disinfection; (2) air saturation with certified virucidal essences with nebulizing diffusers; (3) complementary solutions including telehealth and 3D printing. A pseudonymous online smart form was used as the evaluation method. The protocol operates on the premise that everybody is a hypothetical asymptomatic carrier. The results of a clinical evaluation of 115 patient feedbacks imply that no virus transmission from patient to patient or from doctor to nurse was observed or reported using this protocol, and vice versa, although nine patients retrospectively admitted that the clinic visit is likely to be infectious. Despite these promising results, a larger clinical sample and exposition to the current mutated strains are needed for reliable conclusions about protocol virucidal efficiency in current dental environments.
Andrej Thurzo, Wanda Urbanová, Iveta Neuschlová, Dimitrios Paouris, and Martin Čverha
Elsevier BV
Andrej Thurzo, Wanda Urbanová, Bohuslav Novák, Iveta Waczulíková, and Ivan Varga
MDPI AG
This paper introduces a novel method of 3D designing and 3D printing of a hybrid orthodontic tooth-borne personalized distalizer for treatment of unilateral Class II malocclusion. Research objectives were to clinically utilize 3D printed distalizers, appraise feasibility of this technique and compare two different biocompatible photopolymers (white and transparent). Frequency of distalizers’ debonding and patients’ aesthetical perception was evaluated on the set of 12 complete orthodontic treatments. The mean duration of treatment period with a bonded distalizer was 6.4 months. All cases were adults with unilateral Class II malocclusion managed with a hybrid approach as a part of Invisalign® comprehensive treatment. Results showed that such perspective practice is feasible for 3D design and in-office 3D printing of a personalized distalizer. Results also showed no clinically significant differences between both studied biopolymers. The paper discusses an evaluation of such personalized distalizer functionality with regard to the current state of the art and compares to conventional prefabricated alternatives like a Carriere® Distalizer™ appliance. Research showed a preference of patients towards transparent biocompatible photopolymer instead of the white A2 shade. The paper concludes that additive manufacturing from dental resins is a viable method in personalization and in-office 3D printing of orthodontic auxiliaries, particularly distalizers. New materials for orthodontic 3D printing endow enhanced individualization, thus more efficient treatment.
Andrej Thurzo, Veronika Kurilová, and Ivan Varga
MDPI AG
Background: Treatment of malocclusion with clear removable appliances like Invisalign® or Spark™, require considerable higher level of patient compliance when compared to conventional fixed braces. The clinical outcomes and treatment efficiency strongly depend on the patient’s discipline. Smart treatment coaching applications, like strojCHECK® are efficient for improving patient compliance. Purpose: To evaluate the impact of computerized personalized decision algorithms responding to observed and anticipated patient behavior implemented as an update of an existing clinical orthodontic application (app). Materials and Methods: Variables such as (1) patient app interaction, (2) patient app discipline and (3) clinical aligner tracking evaluated by artificial intelligence system (AI) system—Dental monitoring® were observed on the set of 86 patients. Two 60-day periods were evaluated; before and after the app was updated with decision tree processes. Results: All variables showed significant improvement after the update except for the manifestation of clinical non-tracking in men, evaluated by artificial intelligence from video scans. Conclusions: Implementation of application update including computerized decision processes can significantly enhance clinical performance of existing health care applications and improve patients’ compliance. Using the algorithm with decision tree architecture could create a baseline for further machine learning optimization.