What’s in a Name? Accurately Diagnosing Metopic Craniosynostosis Using a Computational Approach

Wood, Benjamin C.; Mendoza, Carlos S.; Oh, Albert K.; Myers, Emmarie; Safdar, Nabile M.; Linguraru, Marius George; Rogers, Gary F.

doi:10.1097/prs.0000000000001938

Cited by 41 publications

(60 citation statements)

References 23 publications

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“…Other research has focused on the narrowness of the forehead as a diagnostic tool and even created a surrogate based on CT scan measurements. 11,17,31 Indeed, in our analysis, the use of the IFDA was helpful in discerning between the subgroups of MCS, MR, and controls. But, the narrow forehead is not the only change associated with MCS.…”

Section: Discussionmentioning

confidence: 85%

“…The CT scan findings of an omega sign 3 and IFA 11,17 have been associated with the diagnosis of MCS. We elicited additional signs via a web-based survey of 6 experienced craniofacial physicians regarding the CT scan findings, which are most informative for their diagnosis of MCS.…”

Section: Methodsmentioning

confidence: 99%

“…Raters’ findings were entered into a RedCap database. Interfrontal angle and interfrontal divergence angle (IFDA) as described by Wood et al 17 were calculated for each subgroup (MCS, MR, and controls) using Dolphin imaging software (Dolphin Imaging and Management Solutions 9200 Oakdale Ave. Suite 500 Chatsworth, Calif.; Fig. 8).…”

Section: Methodsmentioning

confidence: 99%

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Practical Computed Tomography Scan Findings for Distinguishing Metopic Craniosynostosis from Metopic Ridging

Birgfeld

Heike

Al‐Mufarrej

et al. 2019

Plastic and Reconstructive Surgery - Global Open

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Background: Premature fusion of the metopic suture (ie, metopic craniosynostosis) can be difficult to discriminate from physiological closure of the metopic suture with ridging (MR). Yet, MCS is treated surgically, whereas MR is treated nonsurgically. Often, the diagnosis can be made by physical examination alone, but in difficult cases, a computed tomography (CT) scan can add additional diagnostic information. Methods: We de-identified, randomized, and analyzed the CT scans of patients with MCS (n = 52), MR (n = 20) and age-matched normative controls (n = 52) to identify specific findings helpful in distinguishing between MCS and MR. Four expert clinicians were blinded to the clinical diagnosis and assessed each CT for features of the orbits, frontal bones, and inner table of calvaria. Results: Although no single feature was diagnostic of MCS, we identified several signs that were correlated with MCS, MR, or controls. Features such as “posteriorly displaced frontal bone” and “frontal bone tangent to mid-orbit or medial” demonstrated higher correlation with MCS than MR and the addition of other features improves the accuracy of diagnosis as did inclusion of the interfrontal divergence angle. Conclusion: The presence of a closed metopic suture in addition to other CT scan findings may improve the accuracy of diagnosing MCS, MR, and normocephaly.

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Section: Discussionmentioning

confidence: 85%

Section: Methodsmentioning

confidence: 99%

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Practical Computed Tomography Scan Findings for Distinguishing Metopic Craniosynostosis from Metopic Ridging

Birgfeld

Heike

Al‐Mufarrej

et al. 2019

Plastic and Reconstructive Surgery - Global Open

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“…In many cases, this results in an abnormal growth pattern of the cranial bones and malformations. If untreated, craniosynostosis can cause increased intra-cranial pressure, impaired brain growth, visual problems and cognitive delay [2]. …”

Section: Introductionmentioning

confidence: 99%

Personalized Optimal Planning for the Surgical Correction of Metopic Craniosynostosis

Porras

Zukić

Equobahrie

et al. 2016

Clinical Image-Based Procedures. Translational Research in Medical Imaging

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We introduce a quantitative and automated method for personalized cranial shape remodeling via fronto-orbital advancement surgery. This paper builds on an objective method for automatic quantification of malformations caused by metopic craniosynostosis in children and presents a framework for personalized interventional planning. First, skull malformations are objectively quantified using a statistical atlas of normal cranial shapes. Then, we propose a method based on poly-rigid image registration that takes into account both the clinical protocol for fronto-orbital advancement and the physical constraints in the skull to plan the creation of the optimal post-surgical shape. Our automated surgical planning technique aims to minimize cranial malformations. The method was used to calculate the optimal shape for 11 infants with age 3.8±3.0 month old presenting metopic craniosynostosis and cranial malformations. The post-surgical cranial shape provided for each patient presented a significant average malformation reduction of 49% in the frontal cranial bones, and achieved shapes whose malformations were within healthy ranges. To our knowledge, this is the first work that presents an automatic framework for an objective and personalized surgical planning for craniosynostosis treatment.

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“…These malformations can result in severe conditions such as increased intra-cranial pressure and impaired brain growth [1]. In case of single suture-fusion, depending on which suture is affected, craniosynostosis can be classified as metopic, coronal, sagittal, or lambdoid.…”

Section: Introductionmentioning

confidence: 99%

Locally Affine Diffeomorphic Surface Registration for Planning of Metopic Craniosynostosis Surgery

Porras

Paniagua

Enquobahrie

et al. 2017

Lecture Notes in Computer Science

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The outcome of cranial vault reconstruction for the surgical treatment of craniosynostosis heavily depends on the surgeon’s expertise because of the lack of an objective target shape. We introduce a surface-based diffeomorphic registration framework to create the optimal post-surgical cranial shape during craniosynostosis treatment. Our framework estimates and labels where each bone piece needs to be cut using a reference template. Then, it calculates how much each bone piece needs to be translated and in which direction, using the closest normal shape from a multi-atlas as a reference. With our locally affine approach, the method also allows for bone bending, modeling independently the transformation of each bone piece while ensuring the consistency of the global transformation. We evaluated the optimal plan for 15 patients with metopic craniosynostosis. Our results showed that the automated surgical planning creates cranial shapes with a reduction in cranial malformations of 51.43% and curvature discrepancies of 35.09%, which are the two indices proposed in the literature to quantify cranial deformities objectively. In addition, the cranial shapes created were within healthy ranges.

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What’s in a Name? Accurately Diagnosing Metopic Craniosynostosis Using a Computational Approach

Abstract: Diagnostic, IV.

Cited by 41 publications

References 23 publications

Practical Computed Tomography Scan Findings for Distinguishing Metopic Craniosynostosis from Metopic Ridging

Practical Computed Tomography Scan Findings for Distinguishing Metopic Craniosynostosis from Metopic Ridging

Personalized Optimal Planning for the Surgical Correction of Metopic Craniosynostosis

Locally Affine Diffeomorphic Surface Registration for Planning of Metopic Craniosynostosis Surgery

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