{Reference Type}: Journal Article
{Title}: Craniofacial morphological variability in orthodontic patients with non-syndromic orofacial clefts: an approach using geometric morphometrics.
{Author}: Schraad F;Schwahn C;Krey KF;Doberschütz PH;
{Journal}: Clin Oral Investig
{Volume}: 28
{Issue}: 7
{Year}: 2024 Jul 2
{Factor}: 3.606
{DOI}: 10.1007/s00784-024-05796-y
{Abstract}: <B>OBJECTIVE: </B>Orofacial clefts are complex congenital anomalies that call for comprehensive treatment based on a thorough assessment of the anatomy. This study aims to examine the effect of cleft type on craniofacial morphology using geometric morphometrics.<BR><B>METHODS: </B>We evaluated lateral cephalograms of 75 patients with bilateral cleft lip and palate, 63 patients with unilateral cleft lip and palate, and 76 patients with isolated cleft palate. Generalized Procrustes analysis was performed on 16 hard tissue landmark coordinates. Shape variability was studied with principal component analysis. In a risk model approach, the first nine principal components (PC) were used to examine the effect of cleft type.<BR><B>RESULTS: </B>We found statistically significant differences in the mean shape between cleft types. The difference is greatest between bilateral cleft lip and palate and isolated cleft palate (distance of means 0.026, P = 0.0011). Differences between cleft types are most pronounced for PC4 and PC5 (P = 0.0001), which together account for 10% of the total shape variation. PC4 and PC5 show shape differences in the ratio of the upper to the lower face, the posterior mandibular height, and the mandibular angle.<BR><B>CONCLUSIONS: </B>Cleft type has a statistically significant but weak effect on craniofacial morphological variability in patients with non-syndromic orofacial clefts, mainly in the vertical dimension.<BR><B>CONCLUSIONS: </B>Understanding the effects of clefts on craniofacial morphology is essential to providing patients with treatment tailored to their specific needs. This study contributes to the literature particularly due to our risk model approach in lieu of a prediction model.