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MRI-based Synthetic CT Images of the Head and Neck

NCT ID: NCT06016335

Last Updated: 2023-12-19

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

80 participants

Study Classification

INTERVENTIONAL

Study Start Date

2022-09-22

Study Completion Date

2023-09-12

Brief Summary

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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

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Conditions

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Imaging of Bony Structures of the Head (Various Conditions) Hearing Loss Cholesteatoma Sinusitis Head and Neck Tumor

Keywords

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MRI Synthetic CT Artificial Intelligence Craniofacial

Study Design

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Allocation Method

NON_RANDOMIZED

Intervention Model

PARALLEL

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.
Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

NONE

Study Groups

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Training

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

Group Type OTHER

CT scan

Intervention Type DIAGNOSTIC_TEST

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.

MRI scan

Intervention Type DIAGNOSTIC_TEST

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

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.

Group Type OTHER

CT scan

Intervention Type DIAGNOSTIC_TEST

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.

MRI scan

Intervention Type DIAGNOSTIC_TEST

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

Synthetic CT scan

Intervention Type OTHER

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

Interventions

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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.

Intervention Type DIAGNOSTIC_TEST

MRI scan

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

Intervention Type DIAGNOSTIC_TEST

Synthetic CT scan

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

Intervention Type OTHER

Eligibility Criteria

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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.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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MRIguidance B.V.

INDUSTRY

Sponsor Role collaborator

Amsterdam UMC, location VUmc

OTHER

Sponsor Role lead

Responsible Party

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Paul Merkus

Prof. Dr.

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Paul Merkus, MD PhD

Role: PRINCIPAL_INVESTIGATOR

Amsterdam UMC, location VUmc

Locations

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Amsterdam University Medical Center

Amsterdam, , Netherlands

Site Status

Countries

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Netherlands

Other Identifiers

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NL80426.029.22

Identifier Type: REGISTRY

Identifier Source: secondary_id

2022.0234

Identifier Type: -

Identifier Source: org_study_id