Using Computer-Aided Design/Computer-Aided Manufacturing for Autogenous, Split Calvarial Bone Graft-based Cranioplasty: Optimizing Reconstruction of Large, Complex Skull Defects.
Journal
The Journal of craniofacial surgery
ISSN: 1536-3732
Titre abrégé: J Craniofac Surg
Pays: United States
ID NLM: 9010410
Informations de publication
Date de publication:
Historique:
pubmed:
7
12
2018
medline:
16
8
2019
entrez:
4
12
2018
Statut:
ppublish
Résumé
While autologous split calvarial bone is an ideal graft material in cranioplasty, selection of a donor site can be challenging and limited in the reconstruction of complicated cranial defects. Computer-aided design and manufacturing (CAD/CAM) may improve donor-site harvest and contouring and mitigate operative complications in split calvarial bone graft-based cranioplasty for complex patients, but has not previously been studied in this unique setting. In this study, a retrospective review of patients who presented to the institution and underwent split-calvarial bone graft-based cranioplasty using CAD/CAM to optimize reconstruction of full-thickness cranial defects ≥30 cm was performed. Patient demographics, complications from past operations, intraoperative variables, and immediate and long-term postoperative outcomes were recorded. The CAD/CAM predicted and actual postoperative graft measurements were compared. Five patients were identified who fulfilled inclusion criteria. Mean age at operation was 43 years and mean size of cranial defect was 69 cm. Mean operative time was 443 minutes and mean estimated blood loss was 450 mL. There were no dural tears, sagittal sinus bleeds, or other intraoperative complications. There were no immediate postoperative complications requiring extended hospital stay or reoperation. The postoperative graft surface areas were on average within 2.1% of the planned graft and this difference was not statistically significant (P = 0.28). All patients expressed satisfaction with cranial contour postoperatively. Based on the early experience, the use of CAD/CAM enhances calvarial graft selection and improves contour accuracy in the reconstruction of complex skull defects with minimal complications.
Sections du résumé
BACKGROUND
BACKGROUND
While autologous split calvarial bone is an ideal graft material in cranioplasty, selection of a donor site can be challenging and limited in the reconstruction of complicated cranial defects. Computer-aided design and manufacturing (CAD/CAM) may improve donor-site harvest and contouring and mitigate operative complications in split calvarial bone graft-based cranioplasty for complex patients, but has not previously been studied in this unique setting.
METHODS
METHODS
In this study, a retrospective review of patients who presented to the institution and underwent split-calvarial bone graft-based cranioplasty using CAD/CAM to optimize reconstruction of full-thickness cranial defects ≥30 cm was performed. Patient demographics, complications from past operations, intraoperative variables, and immediate and long-term postoperative outcomes were recorded. The CAD/CAM predicted and actual postoperative graft measurements were compared.
RESULTS
RESULTS
Five patients were identified who fulfilled inclusion criteria. Mean age at operation was 43 years and mean size of cranial defect was 69 cm. Mean operative time was 443 minutes and mean estimated blood loss was 450 mL. There were no dural tears, sagittal sinus bleeds, or other intraoperative complications. There were no immediate postoperative complications requiring extended hospital stay or reoperation. The postoperative graft surface areas were on average within 2.1% of the planned graft and this difference was not statistically significant (P = 0.28). All patients expressed satisfaction with cranial contour postoperatively.
CONCLUSION
CONCLUSIONS
Based on the early experience, the use of CAD/CAM enhances calvarial graft selection and improves contour accuracy in the reconstruction of complex skull defects with minimal complications.
Identifiants
pubmed: 30507889
doi: 10.1097/SCS.0000000000005010
doi:
Types de publication
Case Reports
Journal Article
Langues
eng