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What's in a Name? Accurately Diagnosing Metopic Craniosynostosis Using a Computational Approach.
Plast Reconstr Surg. 2016 Jan; 137(1):205-213.PR

Abstract

BACKGROUND

The metopic suture is unlike other cranial sutures in that it normally closes in infancy. Consequently, the diagnosis of metopic synostosis depends primarily on a subjective assessment of cranial shape. The purpose of this study was to create a simple, reproducible radiographic method to quantify forehead shape and distinguish trigonocephaly from normal cranial shape variation.

METHODS

Computed tomography scans were acquired for 92 control patients (mean age, 4.2 ± 3.3 months) and 18 patients (mean age, 6.2 ± 3.3 months) with a diagnosis of metopic synostosis. A statistical model of the normal cranial shape was constructed, and deformation fields were calculated for patients with metopic synostosis. Optimal and divergence (simplified) interfrontal angles (IFA) were defined based on the three points of maximum average deformation on the frontal bones and metopic suture, respectively. Statistical analysis was performed to assess the accuracy and reliability of the diagnostic procedure.

RESULTS

The optimal interfrontal angle was found to be significantly different between the synostosis (116.5 ± 5.8 degrees; minimum, 106.8 degrees; maximum, 126.6 degrees) and control (136.7 ± 6.2 degrees; minimum, 123.8 degrees; maximum, 169.3 degrees) groups (p < 0.001). Divergence interfrontal angles were also significantly different between groups. Accuracy, in terms of available clinical diagnosis, for the optimal and divergent angles, was 0.981 and 0.954, respectively.

CONCLUSIONS

Cranial shape analysis provides an objective and extremely accurate measure by which to diagnose abnormal interfrontal narrowing, the hallmark of metopic synostosis. The simple planar angle measurement proposed is reproducible and accurate, and can eliminate diagnostic subjectivity in this disorder.

CLINICAL QUESTION/LEVEL OF EVIDENCE

Diagnostic, IV.

Authors+Show Affiliations

Washington, D.C. From the Division of Plastic and Reconstructive Surgery, Children's National Health System; the Division of Plastic Surgery, George Washington University School of Medicine and Health Sciences; Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Health System; and the Departments of Radiology and Pediatrics, School of Medicine and Health Sciences, George Washington University.No affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Comparative Study
Journal Article

Language

eng

PubMed ID

26710024

Citation

Wood, Benjamin C., et al. "What's in a Name? Accurately Diagnosing Metopic Craniosynostosis Using a Computational Approach." Plastic and Reconstructive Surgery, vol. 137, no. 1, 2016, pp. 205-213.
Wood BC, Mendoza CS, Oh AK, et al. What's in a Name? Accurately Diagnosing Metopic Craniosynostosis Using a Computational Approach. Plast Reconstr Surg. 2016;137(1):205-213.
Wood, B. C., Mendoza, C. S., Oh, A. K., Myers, E., Safdar, N., Linguraru, M. G., & Rogers, G. F. (2016). What's in a Name? Accurately Diagnosing Metopic Craniosynostosis Using a Computational Approach. Plastic and Reconstructive Surgery, 137(1), 205-213. https://doi.org/10.1097/PRS.0000000000001938
Wood BC, et al. What's in a Name? Accurately Diagnosing Metopic Craniosynostosis Using a Computational Approach. Plast Reconstr Surg. 2016;137(1):205-213. PubMed PMID: 26710024.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - What's in a Name? Accurately Diagnosing Metopic Craniosynostosis Using a Computational Approach. AU - Wood,Benjamin C, AU - Mendoza,Carlos S, AU - Oh,Albert K, AU - Myers,Emmarie, AU - Safdar,Nabile, AU - Linguraru,Marius G, AU - Rogers,Gary F, PY - 2015/12/29/entrez PY - 2015/12/29/pubmed PY - 2016/5/7/medline SP - 205 EP - 213 JF - Plastic and reconstructive surgery JO - Plast Reconstr Surg VL - 137 IS - 1 N2 - BACKGROUND: The metopic suture is unlike other cranial sutures in that it normally closes in infancy. Consequently, the diagnosis of metopic synostosis depends primarily on a subjective assessment of cranial shape. The purpose of this study was to create a simple, reproducible radiographic method to quantify forehead shape and distinguish trigonocephaly from normal cranial shape variation. METHODS: Computed tomography scans were acquired for 92 control patients (mean age, 4.2 ± 3.3 months) and 18 patients (mean age, 6.2 ± 3.3 months) with a diagnosis of metopic synostosis. A statistical model of the normal cranial shape was constructed, and deformation fields were calculated for patients with metopic synostosis. Optimal and divergence (simplified) interfrontal angles (IFA) were defined based on the three points of maximum average deformation on the frontal bones and metopic suture, respectively. Statistical analysis was performed to assess the accuracy and reliability of the diagnostic procedure. RESULTS: The optimal interfrontal angle was found to be significantly different between the synostosis (116.5 ± 5.8 degrees; minimum, 106.8 degrees; maximum, 126.6 degrees) and control (136.7 ± 6.2 degrees; minimum, 123.8 degrees; maximum, 169.3 degrees) groups (p < 0.001). Divergence interfrontal angles were also significantly different between groups. Accuracy, in terms of available clinical diagnosis, for the optimal and divergent angles, was 0.981 and 0.954, respectively. CONCLUSIONS: Cranial shape analysis provides an objective and extremely accurate measure by which to diagnose abnormal interfrontal narrowing, the hallmark of metopic synostosis. The simple planar angle measurement proposed is reproducible and accurate, and can eliminate diagnostic subjectivity in this disorder. CLINICAL QUESTION/LEVEL OF EVIDENCE: Diagnostic, IV. SN - 1529-4242 UR - https://www.unboundmedicine.com/medline/citation/26710024/What's_in_a_Name_Accurately_Diagnosing_Metopic_Craniosynostosis_Using_a_Computational_Approach_ L2 - https://Insights.ovid.com/pubmed?pmid=26710024 DB - PRIME DP - Unbound Medicine ER -