Cone Beam Computed Tomography and Impacted Maxillary Canines : Dose, Optimisation, and Justification

Retinerte hjørnetenner i overkjeven som er sperret av andre tenner for å vokse ut, er den vanligste grunnen til bruk av Cone Beam Computed Tomography (CBCT) hos barn og unge. Hvis diagnostisering av de retinerte hjørnetenner mangler eller kommer sent, kan rotresorpsjon forekomme på de permanente nabo tennene. Resorpsjonene kan senere føre til behov for kjeveortopedisk behandling, kirurgiske ekstraksjoner og i noen tilfeller implantat eller andre proteseløsninger. Retinerte hjørnetenner oppdages vanligvis hos barn ved klinisk undersøkelse i kombinasjon med intraorale og panorama røntgenbilder. Når mer informasjon er nødvendig for diagnostikk og planlegging, er CBCT-undersøkelse berettiget. På grunn av råd om strålevern er det enighet om at CBCT ikke bør brukes ved førstehånds undersøkelse, men det er fortsatt ingen konsensus om hvorvidt CBCT påvirker terapiplanlegging blant klinikere. Den ideelle radiografiske modaliteten og eksponering varierer, avhengig av den klinisk situasjonen. Når ioniserende stråling benyttes for å undersøke pasienter, må man være oppmerksom på balansen mellom fordelene for pasienten og klinikeren og risikoen ved stråling. Denne doktorgradsavhandlingen hadde som mål å vurdere belastningen ved strålingsdose for barn der retinerte hjørnetenner ble undersøkt. Avhandlingen ser også på metoder for å begrense doseeksponering ved å bruke protokoller for å optimaliserte en lav dose og begrense CBCT-undersøkelsene. Første artikkel i avhandlingen hadde som mål å se effektiv dose ved å sammenligne todimensjonale (2D) undersøkelser (panorama og periapikale røntgenbilder) og tredimensjonale (3D) CBCT. Dosen fra 2D-undersøkelse og CBC fra to enheter (Promax3D og NewTom 5G) ble sammenlignet etter måling av doser på et antropomorft barnefantom. Dosen fra CBCT-undersøkelsen var fra 15 til 140 ganger høyere enn for de konvensjonelle 2D-undersøkelsene, avhengig av CBCT-enhet og type 2D-undersøkelse. Andre artikkel evaluerte bildekvalitet og synlighet av anatomiske strukturer på lavdose CBCT-skanning og effekten av et støyreduksjonsfilter for vurdering av overkjevens front. Flere CBCT-protokoller (Promax3D), blant annet fire lavdoseprotokoller, ble testet på skallefantomer for å sammenligne bildekvalitet og synlighet av anatomiske strukturer som er relevante for vurdering av retinerte hjørnetenner. Tre av lavdoseprotokollene gav akseptabel diagnostisk bildekvalitet, selv om dosen ble redusert med 61 % – 77 %. I tredje artikkel ble det undersøkt hvordan CBCT påvirker behandlingsplanen til pasienter med retinerte hjørnetenner, samt mulige kliniske og 2D-bilde markører for planlagt CBCT-bruk. For å avgjøre om CBCT var berettiget for planlegging av behandling, evaluerte og planlagt en tverrfaglig gruppe 89 kasus med retinerte hjørnetenner. Mer enn halvparten av CBCT-undersøkelsene ble vurdert som uberettiget. Planlagt behandling ble endret i 9,8 % av tilfellene. Variable målt før CBCT som predikerte behovet for ytterligere CBCT, var horisontalt plasserte hjørnetenner, strategi for ekstraksjon på permanente tenner, og bukkalt posisjonerte hjørnetenner. Denne avhandlingen viser at, CBCT medfør høyere effektiv dose for pasienter sammenlignet med konvensjonell 2D røntgenbilder. Dosene pasienter får ved undersøkelse av retinerte hjørnetenner kan minimeres ved å 1) optimalisere protokoller for lavdose CBCT og 2) begrense bruk av CBCT til tilfeller der ytterligere 3D-informasjon er viktig for videre terapeutisk behandling.Impacted maxillary canines are the most common reason for Cone Beam Computed Tomography (CBCT) examinations of the anterior maxilla in children and adolescents today. If impacted canines are missed or diagnosed late, root resorptions may occur on permanent adjacent incisors. In turn, these resorptions may lead to the need for further orthodontic treatment, surgical extractions, and even implants or other prosthetic solutions. Impacted canines are usually discovered in children via clinical examinations in combination with intraoral periapical radiographs and panoramic images. When more diagnostic information is needed, the next step is a CBCT examination. While regulating authorities in radiation protection agree that CBCT should not be used first-hand, there is still no consensus over whether CBCT alters therapy planning amongst clinicians. The ideal radiographic modality and exposure parameters vary, depending on each individual clinical task. When using ionizing radiation to examine patients, attention must be paid to the balance between the benefit to the patient and clinician contra the radiation risk. This thesis aimed to assess the radiation dose burden to children examined for impacted canines and explore methods of limiting dose exposure by applying optimised low-dose protocols and by limiting CBCT examinations through a justification process performed at the therapeutic thinking level. The first paper aimed to measure the effective dose using two-dimensional (2D) examinations (panoramic and periapical radiographs) and three-dimensional (3D) CBCT devices. 2D examination doses and CBCT doses from two devices (Promax3D and NewTom 5G) were compared after measuring organ doses on an anthropomorphic child phantom. The dose from CBCT examinations ranged from 15 to 140 times higher than conventional 2D examinations, depending on the CBCT unit and the type of 2D examination. The second paper evaluated overall image quality and visibility of anatomic structures on low-dose CBCT scans and the effect of a noise reduction filter for assessment of the anterior maxilla. Multiple CBCT protocols (Promax3D), including four low-dose protocols, were tested on dry skull phantoms to compare overall image quality and visibility of anatomic structures pertinent to impacted canine assessment. Of the low-dose protocols, three provided acceptable diagnostic image quality while reducing the dose by 61% – 77%. The third paper investigated how CBCT affects the treatment plan of patients with impacted canines, as well as identified possible clinical and 2D imaging markers for the justified CBCT examination at the therapeutic thinking level. To decide whether CBCT was justified for therapy planning, an interdisciplinary therapy-planning group evaluated impacted canine cases and decided treatment alternatives, first without and later in addition to diagnostic information from CBCT examinations. More than half of the CBCT examinations were considered unjustified, and the therapy plan changed in 9.8% of the cases. Variables measured prior to CBCT that predict the need for further CBCT examinations were horizontally positioned canines (OR= 10.9, p = 0.013 when compared to vertically positioned canines), when extraction strategy was involved (OR = 6.7, p = 0.006), and buccally positioned canines when compared to palatal (OR = 5.3, p = 0.047), central (OR = 25.0, p = 0.001), and distal or uncertain positions (OR =7.7, p = 0.005). Even when optimised, CBCT examinations come at the cost of a higher radiation dose than conventional 2D images. Based on the papers comprising this thesis, patient dose burdens can be minimized when assessing impacted maxillary canines in radiosensitive paediatric patient populations by 1) optimising low-dose CBCT protocols and 2) limiting CBCT exposures to cases where additional 3D information is important for therapeutic thinking and planning.Doktorgradsavhandlin

A Deep Learning Approach to Teeth Segmentation and Orientation from Panoramic X-rays

Accurate teeth segmentation and orientation are fundamental in modern oral healthcare, enabling precise diagnosis, treatment planning, and dental implant design. In this study, we present a comprehensive approach to teeth segmentation and orientation from panoramic X-ray images, leveraging deep learning techniques. We build our model based on FUSegNet, a popular model originally developed for wound segmentation, and introduce modifications by incorporating grid-based attention gates into the skip connections. We introduce oriented bounding box (OBB) generation through principal component analysis (PCA) for precise tooth orientation estimation. Evaluating our approach on the publicly available DNS dataset, comprising 543 panoramic X-ray images, we achieve the highest Intersection-over-Union (IoU) score of 82.43% and Dice Similarity Coefficient (DSC) score of 90.37% among compared models in teeth instance segmentation. In OBB analysis, we obtain the Rotated IoU (RIoU) score of 82.82%. We also conduct detailed analyses of individual tooth labels and categorical performance, shedding light on strengths and weaknesses. The proposed model's accuracy and versatility offer promising prospects for improving dental diagnoses, treatment planning, and personalized healthcare in the oral domain. Our generated OBB coordinates and codes are available at https://github.com/mrinal054/Instance_teeth_segmentation

Cone-Beam Computed Tomography and Radiographs in Dentistry: Aspects Related to Radiation Dose

Introduction. The aim of this study was to discuss the radiation doses associated with plain radiographs, cone-beam computed tomography (CBCT), and conventional computed tomography (CT) in dentistry, with a special focus on orthodontics. Methods. A systematic search for articles was realized by MEDLINE from 1997–March 2011. Results. Twenty-seven articles met the established criteria. The data of these papers were grouped in a table and discussed. Conclusions. Increases in kV, mA, exposure time, and field of view (FOV) increase the radiation dose. The dose for CT is greater than other modalities. When the full-mouth series (FMX) is performed with round collimation, the orthodontic radiographs transmit higher dose than most of the large FOV CBCT, but it can be reduced if used rectangular collimation, showing lower effective dose than large FOV CBCT. Despite the image quality, the CBCT does not replace the FMX. In addition to the radiation dose, image quality and diagnostic needs should be strongly taken into account

Cone beam computed tomography indications for interdisciplinary therapy planning of impacted canines

Objective: To investigate how cone beam computed tomography (CBCT) affects the therapeutic planning of impacted maxillary canines. Study Design: A total of 132 impacted canines from 89 pediatric patients were collected from 3 specialist clinics in Stockholm, Sweden. An interdisciplinary therapy planning team consisting of 5 dental specialists evaluated each case and chose their preferred treatment alternative, initially without and later with CBCT images, to decide whether CBCT was justified for therapy planning. Predefined variables measurable using only 2-dimensional (2D) assessments were analyzed using stepwise logistic regression analyses. Results: The CBCT was considered indicated in 47% of the cases. Additional information from CBCT led to a treatment decision change in 9.8%. Significant 2D predictors for CBCT justification were horizontal canine angulation compared with vertical angulation (odds ratio [OR] = 10.9), extraction strategy involvement (OR = 6.7), and buccally positioned canines compared with palatal (OR = 5.3), central (OR = 25.0), and distal or uncertain positions (OR = 7.7). Conclusions: The benefit-risk assessment of CBCT for impacted canines may be reinforced by performing and applying justification decisions for CBCT acquisition at the therapeutic thinking level. If preliminary treatment planning motivates further in-depth investigation of either root status or tooth location, a CBCT is indicated.publishedVersio

Deep Recurrent Neural Network-Based Assessment of Human Dental Age and Gender from Dental Radiographs

The First Chapter's introduction discussed the ability to determine a person's gender and dental age with great accuracy and efficiency is made possible by this technology. It has also done a study that aims to leverage the groundbreaking advantages of deep learning in the dental age and gender evaluation by providing an accurate and automated approach that goes beyond the constraints of traditional methods. The Second Chapter's Literature Review explained Deep Learning Applications in Dental Radiography and Traditional Methods for Dental Age and Gender Assessment and Datasets and Annotations for Dental Radiographs. It has also done Temporal Dependencies in Dental Radiographs. The Third Chapter Methodology discussed that dental radiography data contains rich environmental information that necessitates a nuanced comprehension; this study employs an interpretivist research philosophy. It has also been done to examine pre-existing ideas and models in the context of tooth age and gender evaluation, a deductive approach is used in this study

Künstliche Intelligenz in der Zahnheilkunde: Scoping-Review und Schließung beobachteter Wissenslücken durch eine methodische und eine klinische Studie

Objectives: The aims of this dissertation were to (1) conduct a scoping review of stud-ies on machine learning (ML) in dentistry and appraise their robustness, (2) perform a benchmarking study to systematically compare various ML algorithms for a specific dental task, and (3) evaluate the influence of a ML-based caries detection software on diagnostic accuracy and decision-making in a randomized controlled trial. Methods: The scoping review included studies using ML in dentistry published between 1st January 2015 and 31st May 2021 on MEDLINE, IEEE Xplore, and arXiv. The risk of bias and reporting quality were assessed with the QUADAS‐2 and TRIPOD checklists, respectively. In the benchmarking study, 216 ML models were built using permutations of six ML model architectures (U-Net, U-Net++, Feature Pyramid Networks, LinkNet, Pyramid Scene Parsing Network, and Mask Attention Network), 12 model backbones of varying complexities (ResNet18, ResNet34, ResNet50, ResNet101, ResNet152, VGG13, VGG16, VGG19, DenseNet121, DenseNet161, DenseNet169, and Dense-Net201), and three initialization strategies (random, ImageNet, and CheXpert weights). 1,625 dental bitewing radiographs were used for training and testing. Five-fold cross-validation was carried out and model performance assessed using F1-score. In the clin-ical trial, each one of 22 dentists examined 20 randomly selected bitewing images for proximal caries; 10 images were evaluated with ML and 10 images without ML. Accura-cy in lesion detection and the suggested treatment were evaluated. Results: The scoping review included 168 studies, describing different ML tasks, mod-els, input data, methods to generate reference tests, and performance metrics, imped-ing comparison across studies. The studies showed considerable risk of bias and mod-erate adherence to reporting standards. In the benchmarking study, more complex models only minimally outperformed their simpler counterparts, if at all. Models initial-ized by ImageNet or CheXpert weights outperformed those using random weights (p<0.05). The clinical trial demonstrated that dentists using ML showed increased accu-racy (area under the receiver operating characteristic [mean (95% confidence interval): 0.89 (0.87–0.90)]) compared with those not using ML [0.85 (0.83–0.86); p<0.05], pri-marily due to their higher sensitivity [0.81 (0.74–0.87) compared to 0.72 (0.64–0.79); p<0.05]. Notably, dentists using ML also showed a higher frequency of invasive treat-ment decisions than those not using it (p<0.05). Conclusion: To facilitate comparisons across ML studies in dentistry, a minimum (core) set of outcomes and metrics should be developed, and researchers should strive to improve robustness and reporting quality of their studies. ML model choice should be performed on an informed basis, and simpler models may often be similarly capable as more complex ones. ML can increase dentists’ diagnostic accuracy but also lead to more invasive treatment.Ziele: Die Ziele dieser Dissertation waren, (1) ein Scoping-Review von Studien über maschinelles Lernen (ML) in der Zahnmedizin, (2) eine Benchmarking-Studie zum systematischen Vergleich verschiedener ML-Algorithmen für eine bestimmte zahnmedizinische Aufgabe, und (3) eine randomisierte kontrollierte Studie zur Bewertung einer ML-basierten Karies-Erkennungssoftware bezüglich diagnostischer Genauigkeit und Einfluss auf den Entscheidungsprozess durchzuführen. Methoden: Das Scoping-Review umfasste Studien über ML in der Zahnmedizin, veröffentlicht vom 1. Januar 2015 bis 31. Mai 2021 auf MEDLINE, IEEE Xplore und arXiv. Bias-Risiko und Berichtsqualität wurden mit den Checklisten QUADAS-2 beziehungsweise TRIPOD bewertet. In der Benchmarking-Studie wurden 216 ML-Modelle durch Permutationen von sechs Architekturen (U-Net, U-Net++, Feature Pyramid Networks, LinkNet, Pyramid Scene Parsing Network und Mask Attention Network), 12 Backbones (Res-Net18, ResNet34, ResNet50, ResNet101, ResNet152, VGG13, VGG16, VGG19, DenseNet121, DenseNet161, DenseNet169 und DenseNet201) und drei Initialisierungsstrategien (zufällige-, ImageNet- und CheXpert-Gewichtungen) erstellt. Zum Training und Testen wurden 1.625 Bissflügel-Röntgenaufnahmen genutzt. Es wurde eine fünffache Kreuzvalidierung durchgeführt und die Modellleistung anhand des F1-Scores bewertet. In der klinischen Studie untersuchten 22 Zahnärzte jeweils 20 zufällig ausgewählte Bissflügelbilder auf Approximalkaries; 10 Bilder wurden mit und 10 Bilder ohne ML ausgewertet. Die Genauigkeit in der Erkennung von Läsionen sowie die abgeleitete Therapieempfehlung wurden bewertet. Ergebnisse: Das Scoping-Review schloss 168 Studien ein, in denen verschiedene ML-Aufgaben, Modelle, Eingabedaten, Methoden zur Generierung von Referenztests und Leistungsmetriken beschrieben wurden. Die Studien zeigten ein erhebliches Bias-Risiko und eine mäßige Einhaltung der Berichtsstandards. In der Benchmarking-Studie hatten komplexere Modelle gegenüber einfachen Modellen allenfalls geringe Vorteile. Mit ImageNet- oder CheXpert-Gewichtungen initialisierte Modelle übertrafen solche mit Zufallsgewichtungen (p<0,05). In der klinischen Studie erreichten Zahnärzte mit ML eine höhere Genauigkeit bei der Kariesdetektion (Receiver-Operating-Charakteristik [Mittelwert (95 % Konfidenzintervall) 0,89 (0,87–0,90)]) als ohne ML [0,85 (0,83–0,86); p<0,05], hauptsächlich aufgrund höherer Sensitivität [0,81 (0,74–0,87) verglichen mit 0,72 (0,64–0,79); p<0,05]. Zahnärzte mit ML wählten auffallend häufiger invasive Behandlungen als ohne ML (p<0,05). Schlussfolgerung: Zur besseren Vergleichbarkeit von ML-Studien in der Zahnmedizin, sollten Core Outcomes und Metriken definiert sowie Robustheit und Berichtsqualität verbessert werden. Die Entwicklung von ML-Modellen sollte auf informierter Basis erfolgen, bei oft ähnlicher Leistung von einfacheren und komplexeren Modellen. ML kann die diagnostische Genauigkeit erhöhen, aber auch zu mehr invasiven Behandlungen führen

Root Length Changes in Orthodontically Displaced Teeth Treated with the Corticotomy Approach

The aim of the study: Corticotomy-facilitated orthodontics is a modern approach to resolve complicated orthodontic cases that may increase the pace of tooth movement. The study's goal was to assess the changes that occurred at the root level following orthodontic treatment when corticotomy was used. Material and methods: Based on Cone Beam Computer Tomography, measurements of the root length at T0 (before corticotomy) and T1 (after corticotomy) were taken after splitting the individuals into two groups (maxillary and mandibular corticotomy) (6 months after surgery). For statistical analysis of the data, many tests were utilized. Results: The root length values obtained at T1 showed minimal changes in length, with statistically insignificant values (for the maxillary arch, the values obtained were 13.36 ± 2.41 mm for women and 14.26 ± 2.06 mm for men; for the lower arch, the measured values were 12.38 ± 2.09 mm for women and 11.56 ± 2.29 mm for men). The canine on the left hemiarcade had the most significant change in root length following treatment, with a value assessed at T1 of 16.72 ± 1.78 mm, which was statistically significant, p 0.05. Conclusion: According to the data obtained in this study, when orthodontic therapy is associated with corticotomy, there is a decrease in root resorption that may occur in the case of conventional orthodontic treatments