Strain-adaptive in silico modeling of bone adaptation — A computer simulation validated by in vivo micro-computed tomography data

• Published in: Bone (New York, N.Y.) Vol. 52; no. 1; pp. 485 - 492
• Main Authors: Schulte, Friederike A., Zwahlen, Alexander, Lambers, Floor M., Kuhn, Gisela, Ruffoni, Davide, Betts, Duncan, Webster, Duncan J., Müller, Ralph
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Inc 01.01.2013; Elsevier; Elsevier Science Inc
• Subjects: Adaptation, Physiological; Adaptations; Algorithms; Animal models; Animals; Biological and medical sciences; Bone loss; Computed tomography; Computer Simulation; Data processing; Endocrinologie, métabolisme & nutrition; Endocrinology, metabolism & nutrition; Female; Fundamental and applied biological sciences. Psychology; Human health sciences; In silico simulation; In vivo micro-computed tomography; Loading; Mathematical models; Mechanical loading; Medical sciences; Mice; Mice, Inbred C57BL; Orthopedics; Osteogenesis; Ovariectomy; Sciences de la santé humaine; Spatial distribution; Surgery (general aspects). Transplantations, organ and tissue grafts. Graft diseases; Surgery of the genital tract and mammary gland; Tomography, X-Ray Computed - methods; Trabecular bone; Validation; Vertebrates: anatomy and physiology, studies on body, several organs or systems; In silico simulation; Validation; Trabecular bone; Ovariectomy; Mechanical loading; In vivo micro-computed tomography; Radiodiagnosis; Computer simulation; Modeling; In vivo; Treatment; Surgery; Morphology; Medical imagery; Computerized axial tomography; Spongious bone; Adaptation
• ISSN: 8756-3282; 1873-2763; 1873-2763
• DOI: 10.1016/j.bone.2012.09.008

Computational models are an invaluable tool to test different mechanobiological theories and, if validated properly, for predicting changes in individuals over time. Concise validation of in silico models, however, has been a bottleneck in the past due to a lack of appropriate reference data. Here, we present a strain-adaptive in silico algorithm which is validated by means of experimental in vivo loading data as well as by an in vivo ovariectomy experiment in the mouse. The maximum prediction error following four weeks of loading resulted in 2.4% in bone volume fraction (BV/TV) and 8.4% in other bone structural parameters. Bone formation and resorption rate did not differ significantly between experiment and simulation. The spatial distribution of formation and resorption sites matched in 55.4% of the surface voxels. Bone loss was simulated with a maximum prediction error of 12.1% in BV/TV and other bone morphometric indices, including a saturation level after a few weeks. Dynamic rates were more difficult to be accurately predicted, showing evidence for significant differences between simulation and experiment (p<0.05). The spatial agreement still amounted to 47.6%. In conclusion, we propose a computational model which was validated by means of experimental in vivo data. The predictive value of an in silico model may become of major importance if the computational model should be applied in clinical settings to predict bone changes due to disease and test the efficacy of potential pharmacological interventions. ► We developed a microstructural load-dependent remodeling algorithm for trabecular bone adaptation. ► The in silico algorithm is validated by experimental in vivo loading and ovariectomy data of the mouse. ► Both mechanical loading and osteoporotic bone loss are predicted with a maximum error of 12.1% in bone morphometric indices. ► Bone formation and resorption rates do not differ significantly in the loading but in the ovariectomy experiment.