The use of virtual and physical 3D modeling for assessing head shape has become more common place in the last decade.25–29 A significant drawback in methods presented by previous studies has been the reliance on CT scans for data acquisition, subjecting the patients to ionizing radiation and a general anesthetic. Wong et al.30 demonstrated that a photogrammetric method using the 3dMD system could be effective in capturing cranial measurements. Photogrammetric methods to analyze craniosynostosis have also been validated in other studies31,32 and in nonsynostotic craniofacial deformities.33
There is a concern with that craniosynostosis could limit brain growth and neurological development by limiting in the cranial vault size.34–36 Hence, measurements of intracranial volume (ICV) have been used to quantify the outcomes of surgery.9,35,37–40 Comparisons of the ICVs of normal and sagittal synostosis patients have found limited evidence of decreased ICV with sagittal synostosis.9,38,40 Our results showed no significant difference in cranial volume between normal and sagittal synostosis patients (0–15 months; Fig. 4). This supports conclusions of Fischer et al.,38 Heller et al.,9 and Posnick et al.40 that sagittal synostosis volumes are equal to, or larger than, normal volumes.
CI has been widely used to assess the outcome of surgery for craniofacial deformities2,5–9,12–16 as the CI is generally able to distinguish between normal and scaphocephalic head shapes.2,5,6,40 Although the present study found significant differences between the preoperative sagittal synostosis group and the normal group, this difference is not “clear cut” with considerable overlap between the 2 groups (see Fig. 5). The CI improved from an average of 71–77 from the preoperative group compared with the P1 but was not significant at the P = 0.05 level. P2 and P3 both reported slightly decreased CI relative to P1, but these differences were not significant. This trend is supported by studies by Windh et al.6 and van Veelan et al.5 who also report a trend toward a scaphocephalic head shape following surgery using the CI at 1- and 3-year postoperative time points.
Although the CI fails to characterize the location of change following surgery, the 6-compartment volume analysis introduced here has shown promise in defining postoperative changes. David et al.4 using a frontal volume to characterize improvements following Spring Mediated Crianioplasty (SMC) and Wikberg et al.41 using a ratio of the frontal volume to total volume to assess postoperative changes for metopic synostosis. A comprehensive study of volume analysis by Wilbrand et al.32 divided the head into 4 compartments and used the ratio of the compartment volumes to quantify the outcome of surgery for a variety of single-suture cases. Although the use of 4 compartments allows for improved quantification and localization of the areas affected by surgery, it is limited in its use for isolating the affected area of change. For example, it cannot differentiate between an increase in the frontal volume and a decrease in the posterior volume based on ratios alone.
The present study also applied the 6-compartment volume distribution method to sagittal synostosis patients following spring-mediated cranioplasty to quantify the effects of the surgery on the volume distribution in the head. Since a volume distribution is used, the method is size invariant, which was shown by the lack of a relationship between volume distribution and age. The method aimed to use the minimum number of compartments that could (1) account for asymmetry and (2) be sensitive (precise) enough to identify differences in the main anatomical regions of the crania that are affected by synostosis. The 3 sagittal split lines are based on anatomical regions of (normal) crania (see Figs. 2, 3).
The PCA of the 6-compartment volume distributions showed that the anterior and middle compartments were more useful in differentiating between normal, preoperative, and postoperative patients. The PCA and ANOVAs showed an increase in the volume distribution in the anterior compartment, a similar (unchanged) volume distribution in the posterior compartments and a decrease in the volume distribution in the middle compartments of sagittal synostosis patients compared with normal (see Fig. 8). Although the anterior and middle compartment results were expected, we also expected an increase in the posterior compartments as this would fit the classic scaphocephalic description of an elongation and narrowing of the head42; however, this was not what the present study found. The ANOVA of the PC1 results demonstrated significant differences between normals, the preoperative group, and postoperative groups, showing that 6-compartment volume distribution method is effective for differentiating between these head shapes in these groups.
When examining the trends for the anterior and middle compartments, it is notable that all the postoperative groups were between the normal and preoperative groups and significantly different from the preoperative group. This means that while the spring-mediated cranioplasty did not fully restore the head shape of patients to the normal group shape, it significantly improved their head shape compared with their preoperative state. Unlike the CI, the 6-compartment volume analysis was able to identify significant differences between the preoperative group and P1, which potentially indicates greater sensitivity in the 6-compartment volume distribution analysis method than the CI measurement.
P1 was situated closest to the normal group in 3 of 4 compartments with the most significant differences (anterior and middle compartments). This suggests that the biggest impact on head shape is in the first year following spring-mediated cranioplasty, after which there may be a shift back toward the preoperative shape. The small sample sizes in P2 and P3 are a clear limitation of this study (n = 9 and n = 5, respectively), and future studies with an increased number of postoperative follow-ups would allow for statistically significant long-term postoperative trends to be determined.
The authors thank Rachel Fitzpatrick and Darryl Heaney for their help in collecting CT scans and Paul de Sensi for his help in collecting 3dMD photogrammetry data.
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