MRI-based Synthetic CT Images of the Head and Neck

Sponsor

Amsterdam UMC, location VUmc (Other)

Overall Status

Enrolling by invitation

CT.gov ID

NCT06016335

Collaborator

MRIguidance B.V. (Industry)

Enrollment

Location

Arms

14.3

Anticipated Duration (Months)

5.6

Patients Per Site Per Month

Study Details

Study Description

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.

Condition or Disease	Intervention/Treatment	Phase
Imaging of Bony Structures of the Head (Various Conditions) Hearing Loss Cholesteatoma Sinusitis Head and Neck Tumor	Diagnostic Test: CT scan Diagnostic Test: MRI scan Other: Synthetic CT scan	N/A

Study Design

Study Type:

Interventional

Anticipated Enrollment :

80 participants

Allocation:

Non-Randomized

Intervention Model:

Parallel Assignment

Intervention Model Description:

For all participants the same research activities will be performed (namely CT and MRI). The resulting paired MRI and CT scans will then be divided into a training set and a test set.For all participants the same research activities will be performed (namely CT and MRI). The resulting paired MRI and CT scans will then be divided into a training set and a test set.

Masking:

None (Open Label)

Primary Purpose:

Diagnostic

Official Title:

Artificial Intelligence Driven Synthetic CT to Substitute CT Scans of the Head and Neck Region

Actual Study Start Date :

Sep 22, 2022

Anticipated Primary Completion Date :

Dec 1, 2023

Anticipated Study Completion Date :

Dec 1, 2023

Arms and Interventions

Arm	Intervention/Treatment
Other: Training Data from 25-35 participants will be used to train an algorithm to generate synthetic CT images from MRI scans.	Diagnostic Test: CT scan Participants receive a CT scan of the head as part of their regular care. A larger part of the head will be scanned than for standard care. Diagnostic Test: MRI scan Participants receive an MRI scan, specifically for the purpose of the study.
Other: Testing 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.	Diagnostic Test: CT scan Participants receive a CT scan of the head as part of their regular care. A larger part of the head will be scanned than for standard care. Diagnostic Test: MRI scan Participants receive an MRI scan, specifically for the purpose of the study. Other: Synthetic CT scan Synthetic CT scans will be generated from MRI scans, using the trained machine learning algorithm.

Arm

Intervention/Treatment

Other: Training

Data from 25-35 participants will be used to train an algorithm to generate synthetic CT images from MRI scans.

Diagnostic Test: CT scan

Participants receive a CT scan of the head as part of their regular care. A larger part of the head will be scanned than for standard care.

Diagnostic Test: MRI scan

Participants receive an MRI scan, specifically for the purpose of the study.

Other: Testing

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.

Diagnostic Test: CT scan

Participants receive a CT scan of the head as part of their regular care. A larger part of the head will be scanned than for standard care.

Diagnostic Test: MRI scan

Participants receive an MRI scan, specifically for the purpose of the study.

Other: Synthetic CT scan

Synthetic CT scans will be generated from MRI scans, using the trained machine learning algorithm.

Outcome Measures

Primary Outcome Measures

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

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".

Eligibility Criteria

Criteria

Ages Eligible for Study:

18 Years and Older

Sexes Eligible for Study:

All

Accepts Healthy Volunteers:

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.