Application of Three-Dimensional Printed Customized Surgical Plates for Mandibular Reconstruction: Report of Consecutive Cases and Long-Term Postoperative Evaluation

Ma, Hongyang; Dessel, Jeroen Van; Bila, Michel; Sun, Yi; Politis, Constantinus; Jacobs, Reinhilde

doi:10.1097/scs.0000000000007835

Cited by 5 publications

(2 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This type of combined segmentation is not possible with the available semi-automatic segmentation software programs, where each structure has a different threshold requiring manual adjustment separately by the operator [ 17 ]. Clinically, this integrated segmentation could be a valuable tool in clinical orthodontics and maxillofacial surgical procedures, such as implant planning, bone grafting, and orthognathic and reconstructive surgery [ 18 – 21 ], where visualization of MVP and its relationship with surrounding structures is a necessity for reaching an accurate diagnosis and patient-specific treatment planning.…”

Section: Discussionmentioning

confidence: 99%

Three-dimensional maxillary virtual patient creation by convolutional neural network-based segmentation on cone-beam computed tomography images

Reis

Morgan

Nomidis³

et al. 2022

Clin Oral Invest

Self Cite

View full text Add to dashboard Cite

Objective To qualitatively and quantitatively assess integrated segmentation of three convolutional neural network (CNN) models for the creation of a maxillary virtual patient (MVP) from cone-beam computed tomography (CBCT) images. Materials and methods A dataset of 40 CBCT scans acquired with different scanning parameters was selected. Three previously validated individual CNN models were integrated to achieve a combined segmentation of maxillary complex, maxillary sinuses, and upper dentition. Two experts performed a qualitative assessment, scoring-integrated segmentations from 0 to 10 based on the number of required refinements. Furthermore, experts executed refinements, allowing performance comparison between integrated automated segmentation (AS) and refined segmentation (RS) models. Inter-observer consistency of the refinements and the time needed to create a full-resolution automatic segmentation were calculated. Results From the dataset, 85% scored 7–10, and 15% were within 3–6. The average time required for automated segmentation was 1.7 min. Performance metrics indicated an excellent overlap between automatic and refined segmentation with a dice similarity coefficient (DSC) of 99.3%. High inter-observer consistency of refinements was observed, with a 95% Hausdorff distance (HD) of 0.045 mm. Conclusion The integrated CNN models proved to be fast, accurate, and consistent along with a strong interobserver consistency in creating the MVP. Clinical relevance The automated segmentation of these structures simultaneously could act as a valuable tool in clinical orthodontics, implant rehabilitation, and any oral or maxillofacial surgical procedures, where visualization of MVP and its relationship with surrounding structures is a necessity for reaching an accurate diagnosis and patient-specific treatment planning.

show abstract

Section: Discussionmentioning

confidence: 99%

Three-dimensional maxillary virtual patient creation by convolutional neural network-based segmentation on cone-beam computed tomography images

Reis

Morgan

Nomidis³

et al. 2022

Clin Oral Invest

Self Cite

View full text Add to dashboard Cite

show abstract

“…The approach enables surgeons to reduce the number and size of incisions and to increase the accuracy of the procedures in a shorter operative time, thus improving the delivery of the clinical outcomes and, most importantly, the functional and aesthetic outcomes that patients value so highly. The present case report is a steppingstone for further detailed analyses of the cost-effectiveness of this approach in the management of patients with moderate and high complexity dentofacial deformities (10)…”

Section: Discussionmentioning

confidence: 99%

Surgery first orthognathic correction of dentofacial deformity secondary to condylar hyperplasia with a hybrid 3D approach for planning and printing of patient-specific implants: A case report

Jaramillo,

Zapata,

Chacón

et al. 2023

Preprint

View full text Add to dashboard Cite

Background: Orthognathic surgery (OS) is used to correct facial asymmetry, dentofacial deformity, skeletal malocclusion, and in complementary procedures to improve mastication and aesthetics. Herewith we report the case of a patient with progressive facial asymmetry who underwent OS with virtual surgical planning, patient-specific guides and custom implants at the Colsanitas Clinic, Bogota, Colombia. Case presentation: Twenty-four-year-old female with a dentofacial deformity secondary to condylar hyperplasia of 9 years evolution. A hybrid technique combined surgical planning and 3D printing of the customized guides and miniplates following a “surgery first” approach. Conclusion: Orthognathic surgery with a hybrid technique resulted in a precise translation of the treatment plan with optimal functional and aesthetic outcomes and patient satisfaction.

show abstract

Deep convolutional neural network-based automated segmentation of the maxillofacial complex from cone-beam computed tomography:A validation study

Preda

Morgan

Gerven³

et al. 2022

Journal of Dentistry

View full text Add to dashboard Cite

Application of Three-Dimensional Printed Customized Surgical Plates for Mandibular Reconstruction: Report of Consecutive Cases and Long-Term Postoperative Evaluation

Abstract: collaboration with other departments are essential for proper diagnosis and treatment. Also, the authors emphasize that ''simple marsupialization'' is not enough to cure SEM and must be as large as possible to avoid postoperative recurrence.

Cited by 5 publications

References 23 publications

Three-dimensional maxillary virtual patient creation by convolutional neural network-based segmentation on cone-beam computed tomography images

Three-dimensional maxillary virtual patient creation by convolutional neural network-based segmentation on cone-beam computed tomography images

Surgery first orthognathic correction of dentofacial deformity secondary to condylar hyperplasia with a hybrid 3D approach for planning and printing of patient-specific implants: A case report

Deep convolutional neural network-based automated segmentation of the maxillofacial complex from cone-beam computed tomography:A validation study

Contact Info

Product

Resources

About