MRI-based Synthetic CT Images of the Head and Neck

Not Applicable

Completed

• Conditions: Sinusitis; Head and Neck Tumor; Imaging of Bony Structures of the Head (Various Conditions); Hearing Loss; Cholesteatoma
• Interventions: Diagnostic Test: CT scan; Diagnostic Test: MRI scan; Other: Synthetic CT scan

• Registration Number: NCT06016335
• Lead Sponsor: Amsterdam UMC, location VUmc

Brief Summary

In case of surgical procedures in the head and neck region, MRI in combination with CT of the bone is often the standard modality to visualise bony landmarks for planning, navigation and risk assessment. An important downside of a CT scan is the associated radiation exposure, especially in children. An additional downside is the sedation or general anaesthesia needed for both the MRI and CT scan session in very young children. These downsides could be removed if the CT scan can be substituted by an MRI sequence that can provide the same information as CT. This project aims to determine the feasibility of recreating CT like images of the craniofacial bones from MRI images using machine learning techniques.

Detailed Description

Not available

Study Timeline

• Study Start: 2022-09-22
• Study First Submitted: 2023-08-07
• Study First Submitted QC: 2023-08-25
• Study First Posted: 2023-08-29
• Primary Completion: 2023-09-12
• Study Completion: 2023-09-12
• Status Verified: 2023-12
• Last Update Submitted: 2023-12-18
• Last Update Posted: 2023-12-19

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 80

Inclusion Criteria

• Patients from the outpatient ENT (Ear, Nose, Throat)-clinic.
• Aged 18 years or older.
• Referred for CT scan of the mastoid, sinonasal complex or face.

Exclusion Criteria

• Pregnancy.
• Contra-indications for MRI or CT.
• Unwillingness to be informed about possibly clinically relevant, incidental findings from the MRI examination.

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: PARALLEL

Arm && Interventions

Group	Intervention	Description
Training	CT scan	Data from 25-35 participants will be used to train an algorithm to generate synthetic CT images from MRI scans.
Training	MRI scan	Data from 25-35 participants will be used to train an algorithm to generate synthetic CT images from MRI scans.
Testing	CT scan	Data from remaining participants will be used to test the synthetic CT algorithm, by comparing true CT scans to synthetic CT scans made from MRI.
Testing	MRI scan	Data from remaining participants will be used to test the synthetic CT algorithm, by comparing true CT scans to synthetic CT scans made from MRI.
Testing	Synthetic CT scan	Data from remaining participants will be used to test the synthetic CT algorithm, by comparing true CT scans to synthetic CT scans made from MRI.

Primary Outcome Measures

Name	Time	Method
Geometrical accuracy.	Within one year after scans have been obtained.	Geometrical accuracy of the bone morphology by determining the mean surface distance in mm between the cortical edges on synthetic CT and on true CT.
Radiodensity accuracy.	Within one year after scans have been obtained.	Accuracy of the voxelwise radiodensity in Hounsfield Units and accuracy of the radiodensity contrast.
Visibility of landmarks.	Within one year after scans have been obtained.	Accuracy of the visibility of clinically relevant anatomical landmarks on the synthetic CT images compared to the corresponding true CT images in the adult population, rated by experienced physicians on a 4-point Likert scale (1 = not visible, 4 = very well visible).

Secondary Outcome Measures

Name	Time	Method
Usefulness.	Within one year after scans have been obtained.	Evaluation of potential usefulness of the synthetic CT images for surgical planning, surgical navigation and diagnostic purposes, as evaluated by experienced physicians and dichotomised into "useful" or "not useful".

Trial Locations

Locations (1)

Amsterdam University Medical Center; 🇳🇱 Amsterdam, Netherlands