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Modeling bladder mechanics with 4D reconstruction of murine ex vivo bladder filling.

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Title: Modeling bladder mechanics with 4D reconstruction of murine ex vivo bladder filling.
Authors: Broemer, Eli1 (AUTHOR), Saxena, Pragya2 (AUTHOR), Bartolone, Sarah3 (AUTHOR), Hennig, Grant4 (AUTHOR), Herrera, Gerald M.4 (AUTHOR), Zwaans, Bernadette3,5 (AUTHOR), Tykocki, Nathan R.2 (AUTHOR), Roccabianca, Sara1,6 (AUTHOR) sara.r@wustl.edu
Source: Biomechanics & Modeling in Mechanobiology. Feb2025, Vol. 24 Issue 1, p347-359. 13p.
Subjects: Biological systems, Gastrointestinal system, Uterine contraction, Strains & stresses (Mechanics), Artificial intelligence
Abstract: This study presents a novel methodology for high-resolution 3D bladder modeling during filling, developed by leveraging improved imaging and computational techniques. Using murine bladder filling data, the methodology generates accurate 3D geometries across time, enabling in-depth mechanical analysis. Comparison with a traditional spherical model revealed similar stress trends, but the 3D model permitted nuanced quantifications, such as localized surface curvature and stress analysis. This advanced 3D model captures complex tissue behavior crucially influenced by tissue-specific microstructural characteristics. This methodology can also be extended to other tissues such as lungs, uterus, and gastrointestinal tract tissues. Applying this analysis to different tissues can uncover mechanisms driven by localized mechanics, such as the sensation of fullness in the bladder due to microcontractions, uterine contractions during labor, and peristaltic contractions in the gastrointestinal tract. This broader applicability underscores our approach's potential to advance the understanding of tissue-specific mechanical behaviors across various biological systems. [ABSTRACT FROM AUTHOR]
Copyright of Biomechanics & Modeling in Mechanobiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="JN" term="%22Biomechanics+%26+Modeling+in+Mechanobiology%22">Biomechanics & Modeling in Mechanobiology</searchLink>. Feb2025, Vol. 24 Issue 1, p347-359. 13p.
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  Data: <searchLink fieldCode="DE" term="%22Biological+systems%22">Biological systems</searchLink><br /><searchLink fieldCode="DE" term="%22Gastrointestinal+system%22">Gastrointestinal system</searchLink><br /><searchLink fieldCode="DE" term="%22Uterine+contraction%22">Uterine contraction</searchLink><br /><searchLink fieldCode="DE" term="%22Strains+%26+stresses+%28Mechanics%29%22">Strains & stresses (Mechanics)</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink>
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  Data: This study presents a novel methodology for high-resolution 3D bladder modeling during filling, developed by leveraging improved imaging and computational techniques. Using murine bladder filling data, the methodology generates accurate 3D geometries across time, enabling in-depth mechanical analysis. Comparison with a traditional spherical model revealed similar stress trends, but the 3D model permitted nuanced quantifications, such as localized surface curvature and stress analysis. This advanced 3D model captures complex tissue behavior crucially influenced by tissue-specific microstructural characteristics. This methodology can also be extended to other tissues such as lungs, uterus, and gastrointestinal tract tissues. Applying this analysis to different tissues can uncover mechanisms driven by localized mechanics, such as the sensation of fullness in the bladder due to microcontractions, uterine contractions during labor, and peristaltic contractions in the gastrointestinal tract. This broader applicability underscores our approach's potential to advance the understanding of tissue-specific mechanical behaviors across various biological systems. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Biomechanics & Modeling in Mechanobiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Feb2025
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