1.Office-based 2-stage Posterior Maxillary Segmental Osteotomy for Mandibular Implant Placement: Clinical Study
Bong-Jin JEONG ; Yeonjin OH ; Hyunmi JO ; Junho JUNG ; Byung-Joon CHOI ; Joo-Young OHE
Journal of Korean Dental Science 2020;13(2):67-72
Purpose:
This clinical study presented the effectiveness of 2-stage posterior maxillary segmental osteotomy (PMSO) under local anesthesia in gaining interarch space to restore the posterior mandibular segment with dental implants.
Materials and Methods:
Nine patients who received two-stage PMSO for mandibular implant placement from 2003 to 2011 were included in the study. Of the 9 patients, 7 were female and 2 were male. Ages ranged form 28 to 72 (mean 46.6). Potential complications were investigated such as sinus infection, survival of bone segment, inflammatory root resorption of adjacent teeth, relapse of bone segment and timing of implant placement, delivery of implant prosthesis and stability of bone segment.Result: None of the patients showed relapse or complication. Bone segments were stabilized by opposed implant prosthesis.
Conclusion
Office-based 2-stage PMSO under local anesthesia can be considered a stable and predictable procedure. Also pedicle damage can be avoided by allowing favor of blood supply to the bone segments. From these advantages, it can be concluded that this surgical procedure can decrease post-operative complications.
2.Enhancing recurrent laryngeal nerve localization during transoral endoscopic thyroid surgery using augmented reality: a proof-of-concept study
Moon Young OH ; Yeonjin CHOI ; Taesoo JANG ; Eun Kyung CHOE ; Hyoun-Joong KONG ; Young Jun CHAI
Annals of Surgical Treatment and Research 2025;108(3):135-142
Purpose:
During transoral endoscopic thyroidectomy, preserving the recurrent laryngeal nerve (RLN) is a major challenge because visualization of this nerve is often obstructed by the thyroid itself, increasing the risk of serious complications.This study explores the application of an augmented reality (AR) system to facilitate easier identification of the RLN during transoral endoscopic thyroidectomy.
Methods:
Three patients scheduled for transoral endoscopic thyroidectomy were enrolled in this proof-of-concept study. Preoperative computed tomography scans were used to create an AR model that included the thyroid, trachea, veins, arteries, and RLN. The model was overlaid onto real-time endoscopic camera images during live surgeries.Manual registration of the AR model was performed using a customized controller. The model was aligned with surgical landmarks such as the trachea and common carotid artery. Manual registration accuracy was assessed using the Dice similarity coefficient (DSC) to evaluate the alignment between the real RLN and the RLN of the AR model.
Results:
The 3 patients included were female (mean age, 33.3 ± 15.7 years), and the mean tumor size was 1.0 ± 0.3 cm. All patients underwent transoral endoscopic thyroidectomy of the right lobe. Final histopathological diagnoses comprised 2 papillary thyroid carcinomas and one follicular adenoma. The manual registration accuracy was 0.60, 0.70, and 0.57 for patients 1, 2, and 3, respectively, with a mean value of 0.6 ± 0.1.
Conclusion
The application of an AR system during transoral endoscopic thyroidectomy proved feasible and demonstrated potential for improving the localization of anatomical structures, particularly the RLN, as indicated by a moderate DSC.
3.Enhancing recurrent laryngeal nerve localization during transoral endoscopic thyroid surgery using augmented reality: a proof-of-concept study
Moon Young OH ; Yeonjin CHOI ; Taesoo JANG ; Eun Kyung CHOE ; Hyoun-Joong KONG ; Young Jun CHAI
Annals of Surgical Treatment and Research 2025;108(3):135-142
Purpose:
During transoral endoscopic thyroidectomy, preserving the recurrent laryngeal nerve (RLN) is a major challenge because visualization of this nerve is often obstructed by the thyroid itself, increasing the risk of serious complications.This study explores the application of an augmented reality (AR) system to facilitate easier identification of the RLN during transoral endoscopic thyroidectomy.
Methods:
Three patients scheduled for transoral endoscopic thyroidectomy were enrolled in this proof-of-concept study. Preoperative computed tomography scans were used to create an AR model that included the thyroid, trachea, veins, arteries, and RLN. The model was overlaid onto real-time endoscopic camera images during live surgeries.Manual registration of the AR model was performed using a customized controller. The model was aligned with surgical landmarks such as the trachea and common carotid artery. Manual registration accuracy was assessed using the Dice similarity coefficient (DSC) to evaluate the alignment between the real RLN and the RLN of the AR model.
Results:
The 3 patients included were female (mean age, 33.3 ± 15.7 years), and the mean tumor size was 1.0 ± 0.3 cm. All patients underwent transoral endoscopic thyroidectomy of the right lobe. Final histopathological diagnoses comprised 2 papillary thyroid carcinomas and one follicular adenoma. The manual registration accuracy was 0.60, 0.70, and 0.57 for patients 1, 2, and 3, respectively, with a mean value of 0.6 ± 0.1.
Conclusion
The application of an AR system during transoral endoscopic thyroidectomy proved feasible and demonstrated potential for improving the localization of anatomical structures, particularly the RLN, as indicated by a moderate DSC.
4.Enhancing recurrent laryngeal nerve localization during transoral endoscopic thyroid surgery using augmented reality: a proof-of-concept study
Moon Young OH ; Yeonjin CHOI ; Taesoo JANG ; Eun Kyung CHOE ; Hyoun-Joong KONG ; Young Jun CHAI
Annals of Surgical Treatment and Research 2025;108(3):135-142
Purpose:
During transoral endoscopic thyroidectomy, preserving the recurrent laryngeal nerve (RLN) is a major challenge because visualization of this nerve is often obstructed by the thyroid itself, increasing the risk of serious complications.This study explores the application of an augmented reality (AR) system to facilitate easier identification of the RLN during transoral endoscopic thyroidectomy.
Methods:
Three patients scheduled for transoral endoscopic thyroidectomy were enrolled in this proof-of-concept study. Preoperative computed tomography scans were used to create an AR model that included the thyroid, trachea, veins, arteries, and RLN. The model was overlaid onto real-time endoscopic camera images during live surgeries.Manual registration of the AR model was performed using a customized controller. The model was aligned with surgical landmarks such as the trachea and common carotid artery. Manual registration accuracy was assessed using the Dice similarity coefficient (DSC) to evaluate the alignment between the real RLN and the RLN of the AR model.
Results:
The 3 patients included were female (mean age, 33.3 ± 15.7 years), and the mean tumor size was 1.0 ± 0.3 cm. All patients underwent transoral endoscopic thyroidectomy of the right lobe. Final histopathological diagnoses comprised 2 papillary thyroid carcinomas and one follicular adenoma. The manual registration accuracy was 0.60, 0.70, and 0.57 for patients 1, 2, and 3, respectively, with a mean value of 0.6 ± 0.1.
Conclusion
The application of an AR system during transoral endoscopic thyroidectomy proved feasible and demonstrated potential for improving the localization of anatomical structures, particularly the RLN, as indicated by a moderate DSC.