About this Research Topic
Transcatheter valve treatment techniques (TAVR) have advanced rapidly in recent years. An increasing number of low-risk aortic stenosis patients have received TAVR, resulting in excellent clinical outcomes. Clinic research data showed a safe and fast recovery compared with traditional open heart valve surgery. In addition to aortic stenosis disease, aortic regurgitation has also attracted much attention. Several unique TAVR valves with graspers, such as the Yena Valve, J Valve, and so on, have been tested in clinical settings with satisfactory results. What is more, the valve-in-valve techniques used in cases of tissue valve dysfunction have also been expanded globally. The meta-analysis of these valve-in-valve techniques shows better results compared to redo open heart surgery.
However, the specific surgical risks and individual anatomic and clinical characteristics in the patients pose great challenges, highlighting the significance of precision medicine in the context of TAVR. The novel development of these techniques, particularly the use of AI, shows great promise in improving patient selection and risk management of interventional cardiovascular procedures.
This Research Topic aims to explore the latest developments in TAVR, focusing on personalized treatment strategies, enhancing safety and efficacy, and improving the management of patient-specific risks and benefits. The objective is to gather insights that will ultimately lead to better patient outcomes and elevate the overall quality of care in interventional cardiovascular procedures. Key questions include how new valve designs can be optimized for individual patients, the role of AI in guiding TAVR procedures, and the potential for expanding transcatheter techniques to other heart valves. We welcome articles addressing, but not limited to, the following themes:
1. New TAVR valve design and trial
2. AI-based machine learning to guide TAVR
3. Transcatheter mitral and tricuspid valve repair with clip techniques
4. Patient indication and right heart failure evaluation
5. Pulmonary valve treatment new techniques
However, the specific surgical risks and individual anatomic and clinical characteristics in the patients pose great challenges, highlighting the significance of precision medicine in the context of TAVR. The novel development of these techniques, particularly the use of AI, shows great promise in improving patient selection and risk management of interventional cardiovascular procedures.
This Research Topic aims to explore the latest developments in TAVR, focusing on personalized treatment strategies, enhancing safety and efficacy, and improving the management of patient-specific risks and benefits. The objective is to gather insights that will ultimately lead to better patient outcomes and elevate the overall quality of care in interventional cardiovascular procedures. Key questions include how new valve designs can be optimized for individual patients, the role of AI in guiding TAVR procedures, and the potential for expanding transcatheter techniques to other heart valves. We welcome articles addressing, but not limited to, the following themes:
1. New TAVR valve design and trial
2. AI-based machine learning to guide TAVR
3. Transcatheter mitral and tricuspid valve repair with clip techniques
4. Patient indication and right heart failure evaluation
5. Pulmonary valve treatment new techniques
Keywords: transcatheter aortic valve replacement, artificial intellengence, valve disease, personalized and precision medicine
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
