TAVI-PREP: A Deep Learning-Based Tool for Automated Measurements Extraction in TAVI Planning.

ABSTRACT:

Background

Transcatheter aortic valve implantation (TAVI) is a less invasive alternative to open-heart surgery for treating severe aortic stenosis. Despite its benefits, the risk of procedural complications necessitates careful preoperative planning.

Methods

This study proposes a fully automated deep learning-based method, TAVI-PREP, for pre-TAVI planning, focusing on measurements extracted from computed tomography (CT) scans. The algorithm was trained on the public MM-WHS dataset and a small subset of private data. It uses MeshDeformNet for 3D surface mesh generation and a 3D Residual U-Net for landmark detection. TAVI-PREP is designed to extract 22 different measurements from the aortic valvular complex. A total of 200 CT-scans were analyzed, and automatic measurements wer

SUBMITTER: Santalo-Corcoy M 

PROVIDER: S-EPMC10606167 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature