Automated three-dimensional quantification of external root resorption following combined orthodontic-orthognathic surgical treatment. A validation study

Alqahtani, Khalid; Jacobs, Reinhilde; Shujaat, Sohaib; Politis, Constantinus; Shaheen, Eman

doi:10.1016/j.jormas.2022.09.010

Cited by 6 publications

(5 citation statements)

References 56 publications

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“…These methods can also aid in quantifying the magnitude and distribution of root remodeling in different dimensions, facilitating a more precise and objective assessment 25,26 . In the present study, a previously validated 3D fully automated protocol for assessing root changes was applied for patients who underwent orthognathic surgery 28 .…”

Section: Discussionmentioning

confidence: 99%

“…A previously validated 3D assessment protocol was applied including 3 main steps: segmentation, registration and 3D analysis 28 . Segmentation refers to the process of separating the teeth from the CBCT images, which was performed using a convolutional neural network-based online cloud platform (RELU BV, Leuven, Belgium) called "Virtual Patient Creator" that was previously validated for this purpose 29,30 .…”

Section: Root Changes Assessment Protocolmentioning

confidence: 99%

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Recommendations to minimize tooth root remodeling in patients undergoing maxillary osteotomies

Alqahtani,

Jacobs,

Da Costa Senior

et al. 2024

Sci Rep

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The purpose of this study was to report root remodeling/resorption percentages of maxillary teeth following the different maxillary osteotomies; i.e. one-piece, two-pieces, three-pieces Le Fort I, surgically assisted rapid palatal expansion (SARPE). The possibility of relationships between root remodeling and various patient- and/or treatment-related factors were further investigated. A total of 110 patients (1075 teeth) who underwent combined orthodontic and orthognathic surgery were studied retrospectively. The sample size was divided into: 30 patients in one-piece Le Fort I group, 30 patients in multi-pieces Le Fort I group, 20 patients in SARPE group and 30 patients in orthodontic group. Preoperative and 1 year postoperative cone beam computed tomography (CBCT) scans were obtained. A validated and automated method for evaluating root remodeling and resorption in three dimensions (3D) was applied. SARPE group showed the highest percentage of root remodeling. Spearman correlation coefficient revealed a positive relationship between maxillary advancement and root remodeling, with more advancement contributing to more root remodeling. On the other hand, the orthodontic group showed a negative correlation with age indicating increased root remodeling in younger patients. Based on the reported results of linear, volumetric and morphological changes of the root after 1 year, clinical recommendations were provided in the form of decision tree flowchart and tables. These recommendations can serve as a valuable resource for surgeons in estimating and managing root remodeling and resorption associated with different maxillary surgical techniques.

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Section: Discussionmentioning

confidence: 99%

Section: Root Changes Assessment Protocolmentioning

confidence: 99%

Recommendations to minimize tooth root remodeling in patients undergoing maxillary osteotomies

Alqahtani,

Jacobs,

Da Costa Senior

et al. 2024

Sci Rep

Self Cite

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“…28 resolution accuracy of 0.1 mm. Many dental studies have utilized VGi evo (NewTom, Verona, Italy) CBCT in areas such as endodontics [29][30][31] and orthognathic surgery, 32 demonstrating the acceptable reliability and validity of this instrument.…”

Section: Discussionmentioning

confidence: 99%

“…CBCT in this study was determined to have adequate accuracy in detecting changes in alveolar bone width based on the resolution accuracy of 0.1 mm. Many dental studies have utilized VGi evo (NewTom, Verona, Italy) CBCT in areas such as endodontics 29–31 and orthognathic surgery, 32 demonstrating the acceptable reliability and validity of this instrument.…”

Section: Discussionmentioning

confidence: 99%

Changes in alveolar bone width around maxillary implants, as determined through cone beam computed tomography based on bony landmarks: A preliminary study

Lin

et al. 2023

Clin Implant Dent Rel Res

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PurposeThis study aimed to investigate changes in alveolar bone width around dental implants and identify the anterior nasal spine (ANS), posterior nasal spine (PNS), and floor of the nasal cavity that can be used as reference landmarks for standardizing the orientation of different cone‐beam computed tomography (CBCT) scans.Materials and methodsWe enrolled two groups that comprised 30 implants. Two CBCT scans from the same patient after implant surgery in the first group were obtained to determine differences in the relative distance and angle between the ANS and apex of the dental implant. Then we compared the second group of patients’ presurgical and postsurgical CBCT images to evaluate changes in alveolar bone width after dental implant surgery by the aforementioned bony landmarks.ResultsIn the first group, no statistically significant differences were detected in the mean distance between the ANS, PNS and implant tip in different directions. In the second group, bone width increased at 1 mm (p = 0.020) and decreased at 4 mm (p < 0.001) and 7 mm (p < 0.001) below the alveolar bone crest after implant surgery.ConclusionsWithin the limitations of the present study, the ANS, PNS, and floor of the nasal cavity can be useful in standardizing the orientation of CBCT scans and alveolar bone remodeling after implant surgery varied depending on the height and direction from the alveolar bone crest based on the three landmarks.

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“…In dentistry, machine learning (ML), a sub eld of arti cial intelligence (AI) based tools, have been developed to automate the identi cation of oral and maxillofacial pathologies such as ERR [12]. Random Forest (RF) and Support Vector Machine (SVM) classi ers were the high-performing ML algorithms commonly utilized for image classi cation tasks in dentistry [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Application of Deep Learning and Feature Selection Technique on External Root Resorption Identification on CBCT Images

Reduwan,

Aziz,

Razi

et al. 2023

Preprint

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Background: Artificial intelligence have been proven to improve the identification of various maxillofacial lesions. The aim of the current study is two-fold, to assess the performance of four deep learning models (DLM) in external root resorption (ERR) identification, and to assess the effect of combining feature selection technique (FST) with DLM on their ability in ERR identification. Methods: External root resorption was simulated on 88 extracted premolar teeth using tungsten bur according to different depths (0.5mm, 1mm and 2mm). All teeth were scanned using a Cone beam CT (Carestream Dental-CHECK). A training (70%), validation (10%), and test (20%) dataset were established. The performance of four DLMs (i. Random Forest (RF)+Visual Geometry Group 16 (VGG), ii. RF+EfficienNetB4 (EFNET), iii. Support Vector Machine (SVM)+VGG and iv. SVM+EFNET) and four hybrid models (DLM+FST: i. FS+RF+VGG, ii. FS+RF+EFNET, iii. FS+SVM+VGG and iv. FS+SVM+EFNET) was compared. Five performance parameters were assessed namely classification accuracy, F1-score, precision, specificity, error rate. FST algorithms (Boruta and Recursive Feature Selection) were combined with the DLMs to assess their performance. Result: RF+VGG exhibited the highest performance in identifying ERR followed by the other tested models. Similarly, FST combined with RF+VGG outperformed other models with classification accuracy, F1-score, precision, and specificity of 81.9%, weighted accuracy of 83%, and AUC of 96%. Conclusion: In general, all DLMs have similar performance on ERR identification. However, the performance can be improved by combining FST with DLMs.

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Automated three-dimensional quantification of external root resorption following combined orthodontic-orthognathic surgical treatment. A validation study

Cited by 6 publications

References 56 publications

Recommendations to minimize tooth root remodeling in patients undergoing maxillary osteotomies

Recommendations to minimize tooth root remodeling in patients undergoing maxillary osteotomies

Changes in alveolar bone width around maxillary implants, as determined through cone beam computed tomography based on bony landmarks: A preliminary study

Application of Deep Learning and Feature Selection Technique on External Root Resorption Identification on CBCT Images

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