Computed Tomography in Patients With Craniosynostosis: A Survey to Ascertain Practice Patterns Among Craniofacial Surgeons

CranioRate: An Image-Based, Deep-Phenotyping Analysis Toolset and Online Clinician Interface for Metopic Craniosynostosis

BACKGROUND

The diagnosis and management of metopic craniosynostosis involve subjective decision-making at the point of care. The purpose of this work was to describe a quantitative severity metric and point-of-care user interface to aid clinicians in the management of metopic craniosynostosis and to provide a platform for future research through deep phenotyping.

METHODS

Two machine-learning algorithms were developed that quantify the severity of craniosynostosis-a supervised model specific to metopic craniosynostosis [Metopic Severity Score (MSS)] and an unsupervised model used for cranial morphology in general [Cranial Morphology Deviation (CMD)]. Computed tomographic (CT) images from multiple institutions were compiled to establish the spectrum of severity, and a point-of-care tool was developed and validated.

RESULTS

Over the study period (2019 to 2021), 254 patients with metopic craniosynostosis and 92 control patients who underwent CT scanning between the ages of 6 and 18 months were included. CT scans were processed using an unsupervised machine-learning based dysmorphology quantification tool, CranioRate. The average MSS was 0.0 ± 1.0 for normal controls and 4.9 ± 2.3 ( P < 0.001) for those with metopic synostosis. The average CMD was 85.2 ± 19.2 for normal controls and 189.9 ± 43.4 ( P < 0.001) for those with metopic synostosis. A point-of-care user interface (craniorate.org) has processed 46 CT images from 10 institutions.

CONCLUSIONS

The resulting quantification of severity using MSS and CMD has shown an improved capacity, relative to conventional measures, to automatically classify normal controls versus patients with metopic synostosis. The authors have mathematically described, in an objective and quantifiable manner, the distribution of phenotypes in metopic craniosynostosis.

Postoperative computed tomography imaging of pediatric patients with craniosynostosis: radiation dose and image quality comparison between multi-slice computed tomography and O-arm cone-beam computed tomography

BACKGROUND

When postoperative multi-slice computed tomography (MSCT) imaging of patients with craniosynostosis is used, it is usually performed a few days after surgery in a radiology department. This requires additional anesthesia for the patient. Recently, intraoperative mobile cone-beam CT (CBCT) devices have gained popularity for orthopedic and neurosurgical procedures, which allows postoperative CT imaging in the operating room.

OBJECTIVE

This single-center retrospective study compared radiation dose and image quality of postoperative imaging performed using conventional MSCT scanners and O-arm CBCT.

MATERIALS AND METHODS

A total of 104 pediatric syndromic and non-syndromic patients who were operated on because of single- or multiple-suture craniosynostosis were included in this study. The mean volumetric CT dose index (CTDIvol) and dose-length product (DLP) values of optimized craniosynostosis CT examinations (58 MSCT and 46 CBCT) were compared. Two surgeons evaluated the subjective image quality.

RESULTS

CBCT resulted in significantly lower CTDIvol (up to 14%) and DLP (up to 33%) compared to MSCT. Multi-slice CT image quality was considered superior to CBCT scans. However, all scans were considered to be of sufficient quality for diagnosis.

CONCLUSION

The O-arm device allowed for an immediate postoperative CBCT examination in the operating theater using the same anesthesia induction. Radiation exposure was lower in CBCT compared to MSCT scans, thus further encouraging the use of O-arms. Cone-beam CT imaging with an O-arm is a feasible method for postoperative craniosynostosis imaging, yielding less anesthesia to patients, lower health costs and the possibility to immediately evaluate results of the surgical operation.