Liu Jiawei, Elkhill Connor, LeBeau Scott, French Brooke, Lepore Natasha, Linguraru Marius George, Porras Antonio R
Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colo.
Department of Pediatric Plastic and Reconstructive Surgery, Children's Hospital Colorado, Aurora, Colo.
Plast Reconstr Surg Glob Open. 2022 Aug 10;10(8):e4457. doi: 10.1097/GOX.0000000000004457. eCollection 2022 Aug.
Available normative references of cranial bone development and suture fusion are incomplete or based on simplified assumptions due to the lack of large datasets. We present a fully data-driven normative model that represents the age- and sex-specific variability of bone shape, thickness, and density between birth and 10 years of age at every location of the calvaria.
The model was built using a cross-sectional and multi-institutional pediatric computed tomography image dataset with 2068 subjects without cranial pathology (age 0-10 years). We combined principal component analysis and temporal regression to build a statistical model of cranial bone development at every location of the calvaria. We studied the influences of sex on cranial bone growth, and our bone density model allowed quantifying for the first time suture fusion as a continuous temporal process. We evaluated the predictive accuracy of our model using an independent longitudinal image dataset of 51 subjects.
Our model achieved temporal predictive errors of 2.98 ± 0.69 mm, 0.27 ± 0.29 mm, and 76.72 ± 91.50 HU in cranial bone shape, thickness, and mineral density changes, respectively. Significant sex differences were found in intracranial volume and bone surface areas ( < 0.01). No significant differences were found in cephalic index, bone thickness, mineral density, or suture fusion.
We presented the first pediatric age- and sex-specific statistical reference for local cranial bone shape, thickness, and mineral density changes. We showed its predictive accuracy using an independent longitudinal dataset, we studied developmental differences associated with sex, and we quantified suture fusion as a continuous process.
由于缺乏大型数据集,现有的颅骨发育和颅缝融合的标准参考资料不完整或基于简化假设。我们提出了一个完全由数据驱动的标准模型,该模型代表了颅骨各个部位在出生至10岁之间骨骼形状、厚度和密度的年龄和性别特异性变异性。
该模型使用了一个横断面、多机构的儿科计算机断层扫描图像数据集,其中有2068名无颅骨病变的受试者(年龄0至10岁)。我们结合主成分分析和时间回归,建立了颅骨各个部位发育的统计模型。我们研究了性别对颅骨生长的影响,并且我们的骨密度模型首次允许将颅缝融合量化为一个连续的时间过程。我们使用51名受试者的独立纵向图像数据集评估了模型的预测准确性。
我们的模型在颅骨形状、厚度和矿物质密度变化方面的时间预测误差分别为2.98±0.69毫米、0.27±0.29毫米和76.72±91.50亨氏单位。在颅内体积和骨表面积方面发现了显著的性别差异(<0.01)。在头指数、骨厚度、矿物质密度或颅缝融合方面未发现显著差异。
我们提出了首个针对局部颅骨形状、厚度和矿物质密度变化的儿科年龄和性别特异性统计参考。我们使用独立的纵向数据集展示了其预测准确性,研究了与性别相关的发育差异,并将颅缝融合量化为一个连续过程。