Craniosynostosis is a condition where infants are born with or subsequently develop an abnormally shaped skull. The skull develops from plates of bone separated from each other by growth lines (sutures). Craniosynostosis refers to early fusion of one or more of these sutures. Whilst in many cases the abnormal head shape provides doctors with the underlying diagnosis, it is necessary to confirm this using imaging. A CT scan involves using multiple x-rays to build a picture of the part of the body being examined. X-rays are associated with potential long term harm, particularly in young children who have longer to incur those risks. MRI uses magnets and radiowaves to create images of the body, and therefore a radiation-free method of imaging. The investigators have previously shown in a pilot group that a specific MRI technique ("Black Bone") can distinguish between normal and prematurely fused cranial sutures, and that the images can be reconstructed in 3D in the same way as CT. The investigators now need to confirm the findings in a larger patient group, and develop automated methods of creating 3D images of the bone. Children in whom there is clinical suspicion of craniosynostosis will be recruited for MRI examination. In children who are already undergoing MRI examination of the head (for any indication), the investigators will add on bone specific sequences. There are no known long term risks associated with MRI, and no contrast medium is required. Anonymised MRI data will be used to further develop our 3D techniques.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
80
MRI examination with Black Bone, and ultrashort/zero echo time MRI techniques
University of Cambridge
Cambridge, United Kingdom
RECRUITINGDiagnosis of craniosynostosis
Accuracy of diagnosis on MRI of craniosynostosis
Time frame: Average one week for diagnosis of individual participants. End of study (2 years) for cohort analysis.
3D reconstruction of craniofacial MRI
Automated segmentation of craniofacial MRI
Time frame: Preliminary 3D outputs within 2 weeks of participation per patient, and by end of study for automated segmentation algorithms(2 years)
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