Python tooth-inspired fixation device for enhanced rotator cuff repair

If you need an accessible version of this item, please email your request to digschol@iu.edu so that they may create one and provide it to you.
Date
2024
Language
American English
Embargo Lift Date
Committee Members
Degree
Degree Year
Department
Grantor
Journal Title
Journal ISSN
Volume Title
Found At
American Association for the Advancement of Science
Abstract

Rotator cuff repair surgeries fail frequently, with 20 to 94% of the 600,000 repairs performed annually in the United States resulting in retearing of the rotator cuff. The most common cause of failure is sutures tearing through tendons at grasping points. To address this issue, we drew inspiration from the specialized teeth of snakes of the Pythonoidea superfamily, which grasp soft tissues without tearing. To apply this nondamaging gripping approach to the surgical repair of tendon, we developed and optimized a python tooth-inspired device as an adjunct to current rotator cuff suture repair and found that it nearly doubled repair strength. Integrated simulations, 3D printing, and ex vivo experiments revealed a relationship between tooth shape and grasping mechanics, enabling optimization of the clinically relevant device that substantially enhances rotator cuff repair by distributing stresses over the attachment footprint. This approach suggests an alternative to traditional suturing paradigms and may reduce the risk of tendon retearing after rotator cuff repair.

Description
item.page.description.tableofcontents
item.page.relation.haspart
Cite As
Kurtaliaj I, Hoppe ED, Huang Y, et al. Python tooth-inspired fixation device for enhanced rotator cuff repair. Sci Adv. 2024;10(26):eadl5270. doi:10.1126/sciadv.adl5270
ISSN
Publisher
Series/Report
Sponsorship
Major
Extent
Identifier
Relation
Journal
Science Advances
Source
PMC
Alternative Title
Type
Article
Number
Volume
Conference Dates
Conference Host
Conference Location
Conference Name
Conference Panel
Conference Secretariat Location
Version
Final published version
Full Text Available at
This item is under embargo {{howLong}}