Back to Search Start Over

Assessment of Effectiveness of the Algorithm for Automated Quantitative Analysis of Metallic Strut Tissue Short-Term Coverage with Intravascular Optical Coherence Tomography.

Authors :
Fluder-Wlodarczyk, Joanna
Schneider, Zofia
Pawłowski, Tomasz
Wojakowski, Wojciech
Gasior, Pawel
Pociask, Elżbieta
Source :
Journal of Clinical Medicine. Aug2024, Vol. 13 Issue 15, p4336. 11p.
Publication Year :
2024

Abstract

Background: Due to its high resolution, optical coherence tomography (OCT) is the most suitable modality for neointimal coverage assessments. Evaluation of stent healing seems crucial to accurately define their safety profile since delayed healing is connected with stent thrombosis. This study aimed to present an algorithm for automated quantitative analysis of stent strut coverage at the early stages of vessel healing in intravascular OCT. Methods: A set of 592 OCT frames from 24 patients one month following drug-eluting stent implantation was used to assess the algorithm's effectiveness. Struts not covered on any side or covered but only on one side were categorized as uncovered. The algorithm consists of several key steps: preprocessing, vessel lumen segmentation, automatic strut detection, and measurement of neointimal thickness. Results: The proposed algorithm proved its efficiency in lumen and stent area estimation versus manual reference. It showed a high positive predictive value (PPV) (89.7%) and true positive rate (TPR) (91.4%) in detecting struts. A qualitative assessment for covered and uncovered struts was characterized by high TPR (99.1% and 80%, respectively, for uncovered and covered struts) and PPV (77.3% and 87%). Conclusions: The proposed algorithm demonstrated good agreement with manual measurements. Automating the stent coverage assessment might facilitate imaging analysis, which might be beneficial in experimental and clinical settings. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20770383
Volume :
13
Issue :
15
Database :
Academic Search Index
Journal :
Journal of Clinical Medicine
Publication Type :
Academic Journal
Accession number :
178947821
Full Text :
https://doi.org/10.3390/jcm13154336