Dataset Information

Dental characteristics of patients with four different types of skeletal dysplasias.

ABSTRACT:

Objective

Skeletal dysplasia (SD) comprises more than 450 separate disorders. We hypothesized that their dental features would be distinctive and investigated the tooth characteristics of four patients with different SDs.

Material and methods

Four SD patients with molecularly confirmed diagnoses, Pt-1 acromicric dysplasia, Pt-2 hypophosphatasia and hypochondroplasia, Pt-3 cleidocranial dysplasia, and Pt-4 achondroplasia, were recruited. A tooth from each patient was evaluated for mineral density (micro-computerized tomography), surface roughness (surface profilometer), microhardness, mineral contents (energy-dispersive X-ray), and ultrastructure (scanning electron microscopy and histology), and compared with three tooth-type matched controls.

Results

Pt-1 and Pt-3 had several unerupted teeth. Pt-2 had an intact-root-exfoliated tooth at 2 years old. The lingual surfaces of the patients' teeth were significantly smoother, while their buccal surfaces were rougher, than controls, except for Pt-1's buccal surface. The patients' teeth exhibited deep grooves around the enamel prisms and rough intertubular dentin. Pt-3 demonstrated a flat dentinoenamel junction and Pt-2 had an enlarged pulp, barely detectable cementum layer, and ill-defined cemento-dentinal junction. Reduced microhardnesses in enamel, dentin, and both layers were observed in Pt-3, Pt-4, and Pt-1, respectively. Pt-1 showed reduced Ca/P ratio in dentin, while both enamel and dentin of Pt-2 and Pt-3 showed reduced Ca/P ratio.

Conclusion

Each SD has distinctive dental characteristics with changes in surface roughness, ultrastructure, and mineral composition of dental hard tissues.

Clinical relevance

In this era of precision dentistry, identifying the specific potential dental problems for each patient with SD would help personalize dental management guidelines.

SUBMITTER: Tantibhaedhyangkul W

PROVIDER: S-EPMC10560164 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

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Publications

Dental characteristics of patients with four different types of skeletal dysplasias.

Tantibhaedhyangkul Worasap W Tantrapornpong Jenjira J Yutchawit Nuttanun N Theerapanon Thanakorn T Intarak Narin N Thaweesapphithak Sermporn S Porntaveetus Thantrira T Shotelersuk Vorasuk V

Clinical oral investigations 20230807 10

<h4>Objective</h4>Skeletal dysplasia (SD) comprises more than 450 separate disorders. We hypothesized that their dental features would be distinctive and investigated the tooth characteristics of four patients with different SDs.<h4>Material and methods</h4>Four SD patients with molecularly confirmed diagnoses, Pt-1 acromicric dysplasia, Pt-2 hypophosphatasia and hypochondroplasia, Pt-3 cleidocranial dysplasia, and Pt-4 achondroplasia, were recruited. A tooth from each patient was evaluated for ...[more]

PMID: 37548766

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Project description:BackgroundSkeletal dysplasias collectively affect a large number of patients worldwide. Most of these disorders cause growth anomalies. Hence, evaluating skeletal maturity via the determination of bone age (BA) is a useful tool. Moreover, consecutive BA measurements are crucial for monitoring the growth of patients with such disorders, especially for timing hormonal treatment or orthopedic interventions. However, manual BA assessment is time-consuming and suffers from high intra- and inter-rater variability. This is further exacerbated by genetic disorders causing severe skeletal malformations. While numerous approaches to automate BA assessment have been proposed, few are validated for BA assessment on children with skeletal dysplasias.ObjectiveWe present Deeplasia, an open-source prior-free deep-learning approach designed for BA assessment specifically validated on patients with skeletal dysplasias.Materials and methodsWe trained multiple convolutional neural network models under various conditions and selected three to build a precise model ensemble. We utilized the public BA dataset from the Radiological Society of North America (RSNA) consisting of training, validation, and test subsets containing 12,611, 1,425, and 200 hand and wrist radiographs, respectively. For testing the performance of our model ensemble on dysplastic hands, we retrospectively collected 568 radiographs from 189 patients with molecularly confirmed diagnoses of seven different genetic bone disorders including achondroplasia and hypochondroplasia. A subset of the dysplastic cohort (149 images) was used to estimate the test-retest precision of our model ensemble on longitudinal data.ResultsThe mean absolute difference of Deeplasia for the RSNA test set (based on the average of six different reference ratings) and dysplastic set (based on the average of two different reference ratings) were 3.87 and 5.84 months, respectively. The test-retest precision of Deeplasia on longitudinal data (2.74 months) is estimated to be similar to a human expert.ConclusionWe demonstrated that Deeplasia is competent in assessing the age and monitoring the development of both normal and dysplastic bones.

Dataset Information

Dental characteristics of patients with four different types of skeletal dysplasias.

Objective

Material and methods

Results

Conclusion

Clinical relevance

Publications

Dental characteristics of patients with four different types of skeletal dysplasias.

Similar Datasets

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