Abstract #5176

Protocol for in vivo acquisition and fully-automated segmentation of the anterior cruciate ligament

Laura Bernadette Lane¹, Gabriel della Maggiora^1,2, Nicolás Schlotterbeck¹, Cristián Montalba¹, Pablo Besa³, Sebastián Irarrazaval³, Alvaro Burdiles⁴, and Pablo Irarrazaval^1,2,5

¹Biomedical Imaging Center, Pontificia Universidad Católica de Chile, Santiago, Chile, ²Department of Electrical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile, ³Department of Orthopedics and Traumatology, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile, ⁴Department of Radiology, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile, ⁵Institute for Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile

In this preclinical study we propose a protocol for rapid 3D imaging and fully automated segmentation to create a standardized healthy ACL image database. The segmentation problem of the ACL is particularly challenging due to its poor contrast. Our protocol demonstrated promising fully-automated segmentation of the ACL. Thus, allowing us to have a 3D computational model of the ACL. Ongoing experimentation explores dynamic imaging of the ACL in motions of flexion-extension. Such work will improve understanding of in vivo knee mechanics with potential to inform treatment of different injuries related to the ACL.

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