A Novel Computational Biomechanics Framework to Model Vascular Mechanopropagation in Deep Bone Marrow

• Published in: Advanced healthcare materials Vol. 12; no. 8; pp. e2201830 - n/a
• Main Authors: Zhao, Yunduo Charles, Zhang, Yingqi, Jiang, Fengtao, Wu, Chi, Wan, Boyang, Syeda, Ruhma, Li, Qing, Shen, Bo, Ju, Lining Arnold
• Format: Journal Article
• Language: English
• Published: Germany Wiley Subscription Services, Inc 01.03.2023; John Wiley and Sons Inc
• Subjects: Arteries; arteriole; Arterioles; Biomechanical engineering; Biomechanical Phenomena; Biomechanics; Blood pressure; Blood vessels; Bone and Bones; Bone biomechanics; Bone imaging; Bone marrow; Bone Marrow - blood supply; Computer applications; Cortical bone; Finite element method; finite elements analysis; Humans; Image reconstruction; Lymphopoiesis; Mechanical stimuli; mechanobiology; Medical imaging; Osteogenesis; Sine waves; sinusoid; stem cell niche; Stem cells; Stiffness; Tomography, X-Ray Computed; mechanobiology; finite elements analysis; stem cell niche; sinusoid; arteriole; osteogenesis; bone marrow
• ISSN: 2192-2640; 2192-2659; 2192-2659
• DOI: 10.1002/adhm.202201830

The mechanical stimuli generated by body exercise can be transmitted from cortical bone into the deep bone marrow (mechanopropagation). Excitingly, a mechanosensitive perivascular stem cell niche is recently identified within the bone marrow for osteogenesis and lymphopoiesis. Although it is long known that they are maintained by exercise‐induced mechanical stimulation, the mechanopropagation from compact bone to deep bone marrow vasculature remains elusive of this fundamental mechanobiology field. No experimental system is available yet to directly understand such exercise‐induced mechanopropagation at the bone‐vessel interface. To this end, taking advantage of the revolutionary in vivo 3D deep bone imaging, an integrated computational biomechanics framework to quantitatively evaluate the mechanopropagation capabilities for bone marrow arterioles, arteries, and sinusoids is devised. As a highlight, the 3D geometries of blood vessels are smoothly reconstructed in the presence of vessel wall thickness and intravascular pulse pressure. By implementing the 5‐parameter Mooney–Rivlin model that simulates the hyperelastic vessel properties, finite element analysis to thoroughly investigate the mechanical effects of exercise‐induced intravascular vibratory stretching on bone marrow vasculature is performed. In addition, the blood pressure and cortical bone bending effects on vascular mechanoproperties are examined. For the first time, movement‐induced mechanopropagation from the hard cortical bone to the soft vasculature in the bone marrow is numerically simulated. It is concluded that arterioles and arteries are much more efficient in propagating mechanical force than sinusoids due to their stiffness. In the future, this in‐silico approach can be combined with other clinical imaging modalities for subject/patient‐specific vascular reconstruction and biomechanical analysis, providing large‐scale phenotypic data for personalized mechanobiology discovery. The mechanical stimuli generated by body exercise can be transmitted from cortical bone into the deep bone marrow. We devise a computational framework that reconstructs in‐vivo 3D deep bone marrow vessels to quantify the mechanopropagation capabilities for arterioles, arteries, and sinusoids. In the future, this framework can combine with other clinical imaging modalities for personalized vascular reconstruction and mechanobiology analyses.