A Novel Computational Biomechanics Framework to Model Vascular Mechanopropagation in Deep Bone Marrow. Issue 8 (8th January 2023)

• Record Type: Journal Article
• Authors: Zhao, Yunduo Charles; Zhang, Yingqi; Jiang, Fengtao; Wu, Chi; Wan, Boyang; Syeda, Ruhma; Li, Qing; Shen, Bo; Ju, Lining Arnold
• Is Part Of: Advanced healthcare materials. Volume 12:Issue 8(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2023-01-08
• Subjects: mechanobiology -- stem cell niche -- finite elements analysis -- bone marrow -- osteogenesis -- arteriole -- sinusoid; Biomedical materials -- Periodicals; 610.28
• DOI: 10.1002/adhm.202201830
• Languages: English
• ISSNs: 2192-2640

Abstract

Abstract: 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. Abstract : 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.