Potential Value of Fusion Imaging and Automated Three-Dimensional Heart Segmentation During Transcatheter Aortic Valve Replacement

Biaggi, Patric; Sager, Dominik F.; Külling, Jeremy; Küest, Silke M.; Wyss, Christophe; Hürlimann, David; Reho, Ivano; Bühler, Ines; Noll, Georg; Huber, Maurus; Gämperli, Oliver; Wenaweser, Peter; Corti, Roberto

doi:10.1016/j.echo.2019.12.012

Cited by 7 publications

(4 citation statements)

References 6 publications

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“…Transcatheter Aortic Valve Replacement Biaggi, P. et al [26] developed fusion software (FS) with 3D TEE and perspective images of 138 patients with severe AS who received TAVR treatment. This study is the first to investigate the efficacy of the novel FS in the perioperative period of TAVR.…”

Section: Intraoperative Navigationmentioning

confidence: 99%

“…Echo Navigator (EN) can effectively solve these problems by virtue of its multi-directional imaging. Biaggi, P. et al [26] applied EN in TAVR surgery. They superimposed 3D TEE and perspective images in real time, automatically generating heart models with key anatomical markers, and realizing accurate locating of the optimal flap ring plane and pacemaker lead position.…”

Section: Intraoperative Navigationmentioning

confidence: 99%

See 1 more Smart Citation

Artificial Intelligence-assisted Medical Imaging in Interventional Management of Valvular Heart Disease

Wenwen,

Yuji,

Zisang

et al. 2023

Advanced Ultrasound in Diagnosis and Therapy

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The integration of medical imaging and artificial intelligence (AI) has revolutionized interventional therapy of valvular heart diseases (VHD), owing to rapid development in multimodality imaging and healthcare big data. Medical imaging techniques, such as echocardiography, cardiovascular magnetic resonance (CMR) and computed tomography (CT), play an irreplaceable role in the whole process of pre-, intra-and post-procedural intervention of VHD. Different imaging techniques have unique advantages in different stages of interventional therapy. Therefore, single imaging technique can't fully meet the requirements of complicated clinical scenarios. More importantly, a single intraoperative image provides only limited vision of the surgical field, which could be a potential source for unsatisfactory prognosis. Besides, the non-negligible inter-and intraobserver variability limits the precise quantification of heart valve structure and function in daily clinical practice. With the help of analysis clustered and regressed by big data and exponential growth in computing power, AI broken grounds in the interventional therapy of VHD, including preoperative planning, intraoperative navigation, and postoperative follow-up. This article reviews the state-of-the-art progress and directions in the application of AI for medical imaging in the interventional therapy of VHD.

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Section: Intraoperative Navigationmentioning

confidence: 99%

Section: Intraoperative Navigationmentioning

confidence: 99%

Artificial Intelligence-assisted Medical Imaging in Interventional Management of Valvular Heart Disease

Wenwen,

Yuji,

Zisang

et al. 2023

Advanced Ultrasound in Diagnosis and Therapy

View full text Add to dashboard Cite

show abstract

“…Periprocedural imaging is essential when performing LAAC due to the considerable differences in size, shape, and relationship to neighboring structures such as the left pulmonary artery, left upper pulmonary vein, and circumflex artery [ 4 ]. Moreover, percutaneous interventions involve challenges such as navigation of the catheter and implantation of the device on a beating heart as well as the learning curve of the interventionalists [ 5 ]. Recent studies demonstrated that by improving aspects such as the design of the devices, periprocedural imaging, and the experience of cardiologists, the complication rate of peri-interventional life-threatening events such as pericardial effusion with cardiac tamponade, ischemic stroke, arrhythmias, bleeding, and increased 30-day mortality was significantly reduced [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Echocardiographic-Fluoroscopic Fusion Imaging Improves Interventionalists’ Learning Curve for Percutaneous Left Atrial Appendage Closure—Initial, Single-Center, Retrospective Observations

Kanschik,

Heidari,

Klein

et al. 2024

JCDD

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Due to the complex and variable anatomy of the left atrial appendage, percutaneous left atrial appendage closure (LAAC) can be challenging. In this study, we investigated the impact of fusion imaging (FI) on the LAAC learning curve of two interventionalists. The first interventionalist (IC 1) was initially trained without FI and continued his training with FI. The second interventionalist (IC 2) performed all procedures with FI. We compared the first 36 procedures without FI of IC 1 (group 1) with his next 36 interventions with FI (group 2). Furthermore, group 1 was compared to 36 procedures of IC 2 who directly started his training with FI (group 3). Group 1 demonstrated that the learning curve without FI has a flat course with weak correlations for fluoroscopy time, contrast volume, and procedure time, but not for dose area product. Group 2 with FI showed improvement with a steep course and strong correlations for all four parameters. In group 3, we also saw a steep progression with strong correlations. Furthermore, the mean measurements of the parameters in the groups with FI decreased significantly as an indicator of procedural efficacy. We demonstrated that FI may improve the learning curve of experienced and non-experienced ICs.

show abstract

“…Periprocedural imaging is essential when performing LAAC due to the considerable differences in size, shape, and relationship to neighboring structures such as left pulmonary artery, left upper pulmonary vein, and circumflex artery [4]. Besides, percutaneous interventions involve challenges such as navigation of the catheter and implantation of the device on a beating heart as well as the learning curve of the interventionalists [5]. Recent studies demonstrated that by improving the aspects such as design of the devices, periprocedural imaging, and the experience of cardiologists, the complication rate of periinterventional life-threatening events such as pericardial effusion with cardiac tamponade, ischemic stroke, arrhythmias, bleeding, and increased 30-day mortality was significantly reduced [6].…”

Section: Introductionmentioning

confidence: 99%

Echocardiographic-Fluoroscopic Fusion Imaging Improves Interventionalists´ Learning Curve for Percutaneous Left Atrial Appendage Closure

Kanschik,

Heidari,

Klein

et al. 2023

Preprint

View full text Add to dashboard Cite

Due to the complex and variable anatomy of the left atrial appendage, percutaneous left atrial appendage closure (LAAC) can be challenging. In this study, we investigated the impact of fusion imaging (FI) on the LAAC learning curve of 2 interventionalists. The first interventionalist (IC 1) was initially trained without FI and continued his training with FI. The second interventionalist (IC 2) performed all procedures with FI. We compared the first 36 procedures without FI of IC 1 (group 1) with his next 36 interventions with FI (group 2). Furthermore, group 1 was compared to 36 procedures of IC 2 who directly started his training with FI (group 3). Group 1 demonstrated that the learning curve without FI has a flat course with weak correlations for fluoroscopy time, contrast volume, and procedure time, but not for dose area product. Group 2 with FI showed improvement with a steep course and strong correlations for all 4 parameters. In group 3 we also saw a steep progression with strong correlations. Furthermore, the mean measurements of the procedural parameters in the groups with FI decreased significantly as indicator for procedural efficacy. We demonstrated that FI may improve the learning curve of experienced and non-experienced ICs.

show abstract

Potential Value of Fusion Imaging and Automated Three-Dimensional Heart Segmentation During Transcatheter Aortic Valve Replacement

Cited by 7 publications

References 6 publications

Artificial Intelligence-assisted Medical Imaging in Interventional Management of Valvular Heart Disease

Artificial Intelligence-assisted Medical Imaging in Interventional Management of Valvular Heart Disease

Echocardiographic-Fluoroscopic Fusion Imaging Improves Interventionalists’ Learning Curve for Percutaneous Left Atrial Appendage Closure—Initial, Single-Center, Retrospective Observations

Echocardiographic-Fluoroscopic Fusion Imaging Improves Interventionalists´ Learning Curve for Percutaneous Left Atrial Appendage Closure

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