Acquisition of 3D Facial Geometry of Patients' Scheduled for Radiotherapy Treatment

• Conditions: Head and Neck Cancer

• Registration Number: NCT02930915
• Lead Sponsor: University of East Anglia

Brief Summary

This study investigates the feasibility of using 3D-Printing to manufacture masks used to immobilize patients undergoing radiotherapy treatment for tumors affecting the head and neck.

Detailed Description

The current types of masks that are used in radiotherapy treatment sessions for those patients who have head-and-neck cancer are 'made to measure' and the methods currently employed to make them are invasive and in some cases patients' have found this to be particularly unpleasant. Their experience motivates research into less invasive and potentially more accurate techniques for their manufacture.

To effectively develop an automatic manufacturing pipeline, and to assess the accuracy of the approach we need access to CT data from a cohort of patients for which we also have an accurate (ground truth) 3D facial model. Such a model can be acquired in a few minutes using a hand-held laser scanner.

Study Timeline

• Study Start: 2016-06
• Status Verified: 2016-10
• Study First Submitted: 2016-10-10
• Study First Submitted QC: 2016-10-10
• Last Update Submitted: 2016-10-10
• Study First Posted: 2016-10-12
• Last Update Posted: 2016-10-12
• Primary Completion: 2017-06
• Study Completion: 2017-09

Recruitment & Eligibility

• Status: UNKNOWN
• Sex: All
• Target Recruitment: 12

Inclusion Criteria

• Have a Head-and-neck cancer
• Receiving radiotherapy treatments (CT images)

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Exclusion Criteria

• Children (age less than 18)

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Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
3D facial geometry of patient's head	15 minutes	The resultant 3D facial geometry of patient's head will be used to construct a 3D digital model which will be used to evaluate the accuracy of the model generated by CT images. In other words, the outcome will be used as a ground-truth for the CT-derived model.

Trial Locations

Locations (2)

Norfolk and Norwich Univeristy Hospital NHS foundation Trust; 🇬🇧 Norwich, Norfolk, United Kingdom

School of Computing Sciences, University of East Anglia; 🇬🇧 Norwich, Norfolk, United Kingdom