Bayesian calibration of a computational model of tissue expansion based on a porcine animal model.
Bayesian calibration of a computational model of tissue expansion based on a porcine animal model.
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DOI：
10.1016/j.actbio.2021.10.007
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发表时间：
2022-01-01
影响因子：
9.7
通讯作者：
Tepole AB
中科院分区：
文献类型：
--
作者：
Han T;Lee T;Ledwon J;Vaca E;Turin S;Kearney A;Gosain AK;Tepole AB
组织扩张术是临床上用于原位生长皮肤以矫正大的缺损的技术。尽管其具有巨大的潜力，但缺乏皮肤适应机械线索的基础知识，以及缺乏预测性计算模型，限制了组织扩张的更广泛采用和功效。在我们以前的工作中，我们介绍了一种组织扩张的有限元模型，该模型预测了应变和生长的关键模式，然后由我们的猪动物模型证实。在这里，我们使用一组新的实验数据来校准贝叶斯框架内的计算模型。在4只12周龄小型猪的背部皮肤上纹身4个10 × 10 cm 2贴片，共6个贴片成功植入组织扩张器并扩张至60 cc，扩张时间为1小时至7天。6个未植入扩张器的贴片作为分析的对照。我们发现，增长可以解释的基础上的弹性变形。预测的面积增长率为k ∈ [0.02，0.08] [hr−1]。生长是各向异性的，反映了猪背部皮肤的各向异性力学行为。喙尾轴比横轴显示出更大的变形，喙尾方向的生长时间尺度由速率参数k1 ∈ [0.04，0.1] [hr−1]给出，而横向的速率参数k2 ∈ [0.01，0.05] [hr−1]给出。此外，校准结果强调了生物系统的高度可变性，以及创建概率计算模型以预测现实环境中的组织适应的需要。
Tissue expansion is a technique used clinically to grow skin in situ to correct large defects. Despite its enormous potential, lack of fundamental knowledge of skin adaptation to mechanical cues, and lack of predictive computational models limit the broader adoption and efficacy of tissue expansion. In our previous work, we introduced a finite element model of tissue expansion that predicted key patterns of strain and growth which were then confirmed by our porcine animal model. Here we use the data from a new set of experiments to calibrate the computational model within a Bayesian framework. Four 10 × 10cm2 patches were tattooed in the dorsal skin of four 12 weeks-old minipigs and a total of six patches underwent successful tissue expander placement and inflation to 60cc for expansion times ranging from 1 hour to 7 days. Six patches that did not have expanders implanted served as controls for the analysis. We find that growth can be explained based on the elastic deformation. The predicted area growth rate is k ∈ [0.02, 0.08] [hr−1]. Growth is anisotropic and reflects the anisotropic mechanical behavior of porcine dorsal skin. The rostral-caudal axis shows greater deformation than the transverse axis, and the time scale of growth in the rostral-caudal direction is given by rate parameters k1 ∈ [0.04, 0.1] [hr−1] compared to k2 ∈ [0.01, 0.05] [hr−1] in the transverse direction. Moreover, the calibration results underscore the high variability in biological systems, and the need to create probabilistic computational models to predict tissue adaptation in realistic settings.
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