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Markus J. Bookland, Edward S. Ahn, Petronella Stoltz, and Jonathan E. Martin

OBJECTIVE

The authors sought to evaluate the accuracy of a novel telehealth-compatible diagnostic software system for identifying craniosynostosis within a newborn (< 1 year old) population. Agreement with gold standard craniometric diagnostics was also assessed.

METHODS

Cranial shape classification software accuracy was compared to that of blinded craniofacial specialists using a data set of open-source (n = 40) and retrospectively collected newborn orthogonal top-down cranial images, with or without additional facial views (n = 339), culled between April 1, 2008, and February 29, 2020. Based on image quality, midface visibility, and visibility of the cranial equator, 351 image sets were deemed acceptable. Accuracy, sensitivity, and specificity were calculated for the software versus specialist classification. Software agreement with optical craniometrics was assessed with intraclass correlation coefficients.

RESULTS

The cranial shape classification software had an accuracy of 93.3% (95% CI 86.8–98.8; p < 0.001), with a sensitivity of 92.0% and specificity of 94.3%. Intraclass correlation coefficients for measurements of the cephalic index and cranial vault asymmetry index compared to optical measurements were 0.95 (95% CI 0.84–0.98; p < 0.001) and 0.67 (95% CI 0.24–0.88; p = 0.003), respectively.

CONCLUSIONS

These results support the use of image processing–based neonatal cranial deformity classification software for remote screening of nonsyndromic craniosynostosis in a newborn population and as a substitute for optical scanner– or CT-based craniometrics. This work has implications that suggest the potential for the development of software for a mobile platform that would allow for screening by telemedicine or in a primary care setting.

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Nathan K. Leclair, William A. Lambert, Joshua Knopf, Petronella Stoltz, David S. Hersh, Jonathan E. Martin, and Markus J. Bookland

OBJECTIVE

Craniosynostosis is a congenital disorder resulting from the premature fusion of cranial sutures in the infant skull. This condition results in significant cosmetic deformity and can impede neurodevelopment, if left untreated. Currently, rates of craniometric change following minimally invasive surgery have only been examined for sagittal craniosynostosis. A better understanding of postoperative skull adaptations in other craniosynostosis subtypes is needed to objectively categorize surgical outcomes and guide length of cranial orthosis therapy.

METHODS

Eleven patients with sagittal and 8 with metopic craniosynostosis treated using endoscopic strip craniectomy and postoperative helmet orthoses were retrospectively reviewed. Using semiautomated image analysis of top-down orthogonal 2D photographs, the following craniometrics were recorded before surgery and at postoperative visits: cephalic index (CI), cranial vault asymmetry index (CVAI), anterior arc angle (AAA), posterior arc angle (PAA), anterior-middle width ratio (AMWR), anterior-posterior width ratio (APWR), left-right height ratio (LRHR), sagittal Hu moment (Sag-Hu), and brachycephaly Hu moment (Brachy-Hu). These craniometrics were then normalized to photograph-based measurements of normocephalic patients and the rates of change between metopic and sagittal craniosynostoses were compared.

RESULTS

Patients with sagittal craniosynostosis exhibited significantly lower CI, lower PAA, higher AMWR, higher APWR, lower Sag-Hu, and higher Brachy-Hu preoperatively compared to patients with normocephalic craniosynostosis. Patients with metopic craniosynostosis exhibited lower AAA and AMWR preoperatively compared to normocephalic subjects. Sagittal and metopic patients had a rapid initial change in normalized CI or AAA, respectively. Craniometric rates of change that significantly differed between metopic and sagittal patients were found in AAA (p < 0.001), AMWR (p < 0.001), and APWR (p < 0.0001). Metopic patients had a prolonged AAA change with a significantly different rate of change up to 6 months postoperatively (median at 3 months = 0.027 normalized units/day, median at 6 months = 0.017 normalized units/day, and median at > 6 months = 0.007 normalized units/day), while sagittal CI rate of change at these time points was not significantly different.

CONCLUSIONS

Patients with metopic craniosynostosis have a prolonged rate of change compared to patients with sagittal craniosynostosis and may benefit from longer helmet use and extended postoperative follow-up. Categorizing craniometric changes for other craniosynostosis subtypes will be important for evaluating current treatment guidelines.