Evidence suggests that inertial cavitation plays an important role in the renal injury incurred during shock-wave lithotripsy. However, it is unclear how tissue damage is initiated, and significant injury typically occurs only after a sufficient dose of shock waves. Although it has been suggested that shock-induced shearing might initiate injury, estimates indicate that individual shocks do not produce sufficient shear to do so. In this paper, we hypothesize that the cumulative shear of the many shocks is damaging. This mechanism depends on whether there is sufficient time between shocks for tissue to relax to its unstrained state. We investigate the mechanism with a physics-based simulation model, wherein the basement membranes that define the tubules and vessels in the inner medulla are represented as elastic shells surrounded by viscous fluid. Material properties are estimated from in-vitro tests of renal basement membranes and documented mechanical properties of cells and extracellular gels. Estimates for the net shear deformation from a typical lithotripter shock (approximately 0.1%) are found from a separate dynamic shock simulation. The results suggest that the larger interstitial volume (approximately 40%) near the papilla tip gives the tissue there a relaxation time comparable to clinical shock delivery rates (approximately 1 Hz), thus allowing shear to accumulate. Away from the papilla tip, where the interstitial volume is smaller (approximately 20%), the model tissue relaxes completely before the next shock would be delivered. Implications of the model are that slower delivery rates and broader focal zones should both decrease injury, consistent with some recent observations.
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http://dx.doi.org/10.1016/j.ultrasmedbio.2007.03.001 | DOI Listing |
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Department of Radiology, Radio-Oncology and Nuclear Medicine, Université de Montréal, Montreal, QC, Canada.
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Soft Matter
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Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
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January 2025
College of Civil and Transportation Engineering, Hohai University, No. 1 Xikang Road, Nanjing City, 210098, Jiangsu Province, People's Republic of China.
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