Development of Three-dimensional Deep Learning for Automatic Design of Skull Implants

Recruiting

• Conditions: Skull Defect
• Interventions: Device: 3D deep learning neural network system

• Registration Number: NCT05603949
• Lead Sponsor: Chang Gung Memorial Hospital

Brief Summary

This project aims to develop an effective deep learning system to generate numerical implant geometry based on 3D defective skull models from CT scans. This technique is beneficial for the design of implants to repair skull defects above the Frankfort horizontal plane.

Detailed Description

Designing a personalized implant to restore the protective and aesthetic functions of the patient's skull is challenging. The skull defects may be caused by trauma, congenital malformation, infection, and iatrogenic treatments such as decompressive craniectomy, plastic surgery, and tumor resection. The project aims to develop a deep learning system with 3D shape reconstruction capabilities. The system will meet the requirement of designing high-resolution 3D implant numerical models efficiently.

A collection of skull images were used for training the deep learning system. Defective models in the datasets were created by numerically masking areas of intact 3D skull models. The final implant design should be verified by neurosurgeons using 3D printed models.

Study Timeline

• Study First Submitted: 2022-09-07
• Study First Submitted QC: 2022-11-01
• Study First Posted: 2022-11-03
• Status Verified: 2023-02
• Study Start: 2023-02-03
• Last Update Submitted: 2023-02-10
• Last Update Posted: 2023-02-13
• Primary Completion: 2023-07-15
• Study Completion: 2023-07-15

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 6

Inclusion Criteria

1. Scheduled for cranioplasty
2. Informed consent

Exclusion Criteria

(1)No informed consent

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
experimental group	3D deep learning neural network system	-

Primary Outcome Measures

Name	Time	Method
Number of patients where there is no need to augment/fill clefts between the Patient Specific Implant (PSI) and patient´s bone	6 weeks after surgery by standardised questionnaire	Number of patients where there is no need to augment/fill clefts between the Patient Specific Implant (PSI) and patient´s bone
Number of patients where there is no need to adapt the Patient Specific Implant (PSI) edges	6 weeks after surgery by standardised questionnaire	Number of patients where there is no need to adapt the Patient Specific Implant (PSI) edges

Trial Locations

Locations (1)

Linkou Chang Gung Memorial Hospital; 🇨🇳 Taoyuan City, Taiwan