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© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Deep vein thrombosis (DVT) is a life-threatening condition that can lead to its sequelae pulmonary embolism (PE) or post-thrombotic syndrome (PTS). Murine models of DVT are frequently used in early-stage disease research and to assess potential therapies. This creates the need for the reliable and easy quantification of blood clots. In this paper, we present a novel high-frequency 3D ultrasound approach for the quantitative evaluation of the volume of DVT in an in vitro model and an in vivo murine model. The proposed method involves the use of a high-resolution ultrasound acquisition system and semiautomatic segmentation of the clot. The measured 3D volume of blood clots was validated to be correlated with in vitro blood clot weights with an R2 of 0.89. Additionally, the method was confirmed with an R2 of 0.91 in the in vivo mouse model with a cylindrical volume from macroscopic measurement. We anticipate that the proposed method will be useful in pharmacological or therapeutic studies in murine models of DVT.

Details

Title
A Quantitative Method for the Evaluation of Deep Vein Thrombosis in a Murine Model Using Three-Dimensional Ultrasound Imaging
Author
Xie, Yanjun 1 ; Huang, Yi 1 ; Stevenson, Hugo C S 1 ; Li, Yin 2 ; Zhang, Kaijie 2 ; Zain Husain Islam 2 ; Marcum, William Aaron 2 ; Johnston, Campbell 2 ; Hoyt, Nicholas 2 ; Kent, Eric William 2 ; Bowen, Wang 2   VIAFID ORCID Logo  ; Hossack, John A 1 

 Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA; [email protected] (Y.X.); [email protected] (Y.H.); 
 Department of Surgery, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA 
First page
200
Publication year
2024
Publication date
2024
Publisher
MDPI AG
e-ISSN
22279059
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2918592999
Copyright
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.