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

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.

Novel Movable Typing for Personalized Vein‐Chips in Large Scale: Recapitulate Patient‐Specific Virchow's Triad and its Contribution to Cerebral Venous Sinus Thrombosis

“…In the second step, with our customized surface smoothing algorithm [ 32 ] (see Experimental Section; Figure 2b), we numerically reconstructed the 3D anatomy of this U‐shape sigmoid sinus with a stenotic region. To translate this vein geometry to a microfluidic device as a Vein‐Chip, we scaled down the luminal diameter by a factor of 0.15 to a minimum diameter, D min = 400 µm, suitable for standard stereolithography (SLA) 3D printing (Figure 2c).…”

Microvasculature‐on‐a‐Post Chip That Recapitulates Prothrombotic Vascular Geometries and 3D Flow Disturbance

“…To correlate the hemodynamics with thrombosis, we numerically reconstructed the geometries and surface topography from the 3D confocal images of the microvasculature‐on‐a‐post chip. [ 16 ] Then we conducted computational fluid dynamic (CFD) simulation to map the disturbed blood flow profile (see the Experimental Section and Figure 5E,F). The blood flow transverses the post and produces a polynomial distribution along the post surface, with maxima of shear rates at the apical edges of both the small (Figure 5E, γ max = 1746 s −1 ) and large (Figure 5F, γ max = 1926 s −1 ) post, resulting in the activation and exacerbation of thrombotic process in those regions.…”

Movable typing of full‐lumen personalized Vein‐Chips to model cerebral venous sinus thrombosis

“…[ 23 ] Thus, we used our established algorithm to extract the anatomy of the left sigmoid sinus from an MRV image of a 70‐year‐old female patient. [ 16,24 ] The sigmoid sinus had a longitudinal length of 80 mm and a luminal diameter of 4 mm. We scaled down this luminal diameter to a minimum of 400 μm, a size suitable for stereolithography 3D printing.…”

“…(B) The procedures of deriving a full‐lumen Vein‐Chip microfluidic device from patient‐specific MRV images using an established algorithm for 3D reconstruction. [ 24 ] (C) The schematics of the advanced movable typing process used for creating a personalized full‐lumen Vein‐Chip. This includes the step‐by‐step procedure from printing two halves of the vessel as negative molds, fabricating a positive mold using high‐throughput movable typing, to the final step of injecting PDMS between the mold and a glass slide.…”