Overview

This study aims to test the safety and effectiveness of Force Feedback instruments used during robotic-assisted mitral valve repair with the da Vinci Surgical System, Model IS5000 (dV5).

Eligibility

Inclusion Criteria:

1. Age ≥22 years.
2. Subjects with mitral regurgitation (MR) resulting from primary (degenerative) etiology with normal ventricular function (left ventricular function \> 40%) provided that annuloplasty or ventricular repair is feasible robotically.
3. Subjects with moderate-severe (Grade 3) or severe (Grade 4) mitral regurgitation (MR) confirmed by transthoracic echocardiography (TTE) or transesophageal echocardiography (TEE) within 60 days of surgery or evaluation for surgery.
4. Subjects with low-moderate operative risk (Society of Thoracic Surgeons Predicted Risk of Mortality (STS-PROM) score of \<4%).
5. Subjects that are able to provide written informed consent using the study informed consent form prior to the study.
6. Subjects that are willing to comply with protocol-specified follow-up visits.
7. Subjects must be candidates for minimally invasive surgery (no contraindications to robotic approach). Based on the study Investigator's clinical judgement, the Subject is deemed suitable to undergo multiport robotic-assisted surgery for mitral valve repair.

Exclusion Criteria:

PREOPERATIVE EXCLUSION CRITERIA:

1. Subjects with symptomatic mitral regurgitation determined to be at prohibitive risk for mitral valve surgery.
2. Subjects with previous mitral valve surgery, transcatheter repair, or annuloplasty.
3. Subjects with prior cardiac surgery (endoscopic, open, or robotic) or ipsilateral thoracic surgery (open, endoscopic, or robotic).
4. Subjects with planned emergent procedure (e.g., cardiogenic shock, acute decompensation requiring immediate surgery).
5. Subjects requiring surgery with multiple stages (i.e., mitral repair cannot be completed in a single procedure).
6. Subject with planned major concomitant surgery for a different medical condition (e.g., coronary artery bypass, cancer resection unrelated to mitral regurgitation).
7. Subjects with non-reparable anatomy.
8. Subjects with severe pulmonary hypertension (systolic Pulmonary Artery Pressure \>70 mmHg).
9. Subjects with severe renal insufficiency (estimated Glomerular Filtration Rate \<30 mL/min/1.73m²) or liver failure (Child-Pugh C).
10. Subjects with active infection.
11. Subjects with contraindication to anesthesia/surgery (e.g., severe frailty, uncorrectable coagulopathy).
12. Subjects with any past or ongoing condition, or personal circumstance, that in the Investigator's judgment places the Subject at high surgical risk, deems them unsuitable for mitral valve repair, or might interfere with study participation or data collection (e.g., severe chronic obstructive pulmonary disease, uncontrolled diabetes, immunocompromised state, non-compliance).
13. Subjects with severe aortic/tricuspid valve disease requiring concurrent open surgery.
14. Subjects who are pregnant, suspected pregnancy, or breastfeeding.
15. Subjects currently participating in another investigational drug/device study or participation in a significant-risk investigational device study within the past 6 months.
16. Subject with inability to complete follow-up (e.g., geographic inaccessibility, dementia).
17. Subjects who belong to a vulnerable population (e.g., prisoners, cognitively impaired individuals unable to consent).

INTRAOPERATIVE EXCLUSION CRITERIA:

1. Subject with hemodynamic or respiratory instability that precludes the Investigator from performing the Robotic Assisted Surgery (RAS).
2. Subject in whom inadequate visualization makes a minimally invasive approach not feasible, as determined by the Investigator assessment prior to docking the robot.
3. Subject with adhesions, scarring, and disease status in the body which, in the opinion of the investigator, limits the ability to perform the minimally invasive procedure.
4. Subject has any other condition that, in the judgment of the Investigator, might interfere with the collection of complete quality data.