Automated transcatheter heart valve 4DCT-based deformation assessment throughout the cardiac cycle: Towards enhanced long-term durability.

Authors

Busto L,Veiga C,González-Nóvoa JA,Campanioni S,Martínez C,Juan-Salvadores P,Jiménez V,Suárez S,López-Campos JÁ,Segade A,Alba-Castro JL,Kütting M,Baz JA,Íñiguez A

Affiliations (8)

  • Cardiology Research Group, Galicia Sur Health Research Institute, Vigo, Spain; AI Platform for Biomedical Analysis, Galicia Sur Health Research Institute, Vigo, Spain.
  • Cardiology Research Group, Galicia Sur Health Research Institute, Vigo, Spain; AI Platform for Biomedical Analysis, Galicia Sur Health Research Institute, Vigo, Spain. Electronic address: [email protected].
  • AI Platform for Biomedical Analysis, Galicia Sur Health Research Institute, Vigo, Spain; Department of Electronic Technology, University of Vigo, Vigo, Spain.
  • Cardiology Research Group, Galicia Sur Health Research Institute, Vigo, Spain.
  • Cardiology Department, SERGAS, Álvaro Cunqueiro Hospital, Vigo, Spain.
  • CINTECX, Department of Mechanical Engineering, University of Vigo, Vigo, Spain.
  • atlanTTic Research Center for Telecommunication Technologies, University of Vigo, Vigo, Spain.
  • NVT/Biosensors, Hechingen, Germany.

Abstract

Transcatheter heart valve (THV) durability is a critical concern, and its deformation may influence long-term performance. Current assessments rely on CT-based single-phase measurements and require a tedious analysis process, potentially overlooking deformation dynamics throughout the cardiac cycle. A fully automated artificial intelligence-based method was developed to assess THV deformation in post-transcatheter aortic valve implantation (TAVI) 4DCT scans. The approach involves segmenting the THV, extracting orthogonal cross-sections along its axis, fitting ellipses to these cross-sections, and computing eccentricity to analyze deformation over the cardiac cycle. The method was evaluated in 21 TAVI patients with different self-expandable THV models, using one post-TAVI 4DCT series per patient. The THV inflow level exhibited the greatest eccentricity variations (0.35-0.69 among patients with the same THV model at end-diastole). Additionally, eccentricity varied throughout the cardiac cycle (0.23-0.57), highlighting the limitations of single-phase assessments in characterizing THV deformation. This method enables automated THV deformation assessment based on cross-sectional eccentricity. Significant differences were observed at the inflow level, and cyclic variations suggest that full cardiac cycle analysis provides a more comprehensive evaluation than single-phase measurements. This approach may aid in optimizing THV durability and function while preventing related complications.

Topics

Journal Article

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