The automatic localization of the vena contracta using Intracardiac Echocardiography (ICE): a feasibility study

Djalal Fakim; Hareem Nisar; John T. Moore; Terry M. Peters; Elvis C. S. Chen

doi:10.1117/12.2610813

4 April 2022 The automatic localization of the vena contracta using Intracardiac Echocardiography (ICE): a feasibility study

Djalal Fakim, Hareem Nisar, John T. Moore, Terry M. Peters, Elvis C. S. Chen

Author Affiliations +

Proceedings Volume 12034, Medical Imaging 2022: Image-Guided Procedures, Robotic Interventions, and Modeling; 1203421 (2022) https://doi.org/10.1117/12.2610813
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

Conference Poster

Abstract

Recent recognition of the poor prognosis of significant tricuspid regurgitation (TR) has resulted in increased indication for tricuspid valve interventions. TR can affect 65% to 85% of the population worldwide and has a 1-year mortality rate greater than 25% in patients with severe regurgitation. A key procedure for patient selection and intraoperative assessment of intervention involves determining the location of the vena contracta width and regurgitant jet area. Manual visualization of the vena contracta (VC) can be time consuming depending on its location. Decreasing the required time for VC visualization would potentially result in decreased time for patient assessment, device deployment and intraprocedural intervention evaluation thus reducing hospital costs. There is currently no commercially available automatic VC detection system. We present a method to automatically localize the VC using 3D intracardiac echocardiography (ICE) on a simplified anthropomorphic phantom as a proof of concept. A beating heart phantom was outfitted with a silicone flange containing a mechanical valve and an orifice to cause a regurgitant jet. We propose an image processing pipeline to segment the regurgitant jet from Doppler ultrasound, as acquired by ICE, to determine the location of the VC automatically. The VC locations output by the algorithm were validated both qualitatively and quantitatively by comparison to manually annotated VC locations. On average, the location of VC detected by the algorithm was within 1.52±35mm to the location of the ground truth VC. We envision that this study will play a major role towards the development of an automated system for VC localization during TV interventions.

Citation Download Citation

Djalal Fakim, Hareem Nisar, John T. Moore, Terry M. Peters, and Elvis C. S. Chen "The automatic localization of the vena contracta using Intracardiac Echocardiography (ICE): a feasibility study", Proc. SPIE 12034, Medical Imaging 2022: Image-Guided Procedures, Robotic Interventions, and Modeling, 1203421 (4 April 2022); https://doi.org/10.1117/12.2610813

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