Robotic median arcuate ligament release: management algorithm and clinical outcomes from a large minimally invasive series.

Abstract

Median arcuate ligament syndrome (MALS) is a rare and debilitating condition that remains difficult to diagnose. Proper patient selection remains key to achieving favorable outcomes for those undergoing MALR. The robotic technique facilitates a minimally invasive MALR approach given the fine precision of the instrumentation and stability of visualization. Here we describe our management algorithm and clinical outcomes for a large series of robotic MALR patients. This retrospective cohort study analyzed adult patients who underwent robotic MALR performed by a single surgeon at a tertiary academic hospital from 2014 to 2021. The diagnosis of MALS was made using objective criteria from celiac artery duplex ultrasound with a peak systolic velocity of > 350cm/s combined with a right upper quadrant abdominal ultrasound, esophagogastroduodenoscopy, and computer tomography or magnetic resonance angiography to exclude other diagnoses. Information on patient demographics, perioperative factors, and patient reported symptoms up to 1-year post-operatively were collected. A total of 74 patients underwent robotic MALR during the study period. The mean age was 27.3 ± 7.9years and the majority of patients were female (n = 60/74, 81.1%). The most common presenting symptom was post-prandial abdominal pain (n = 65/74, 87.7%). The mean operative time was 52.6 ± 18.1min. There were no conversions to open surgery and minimal blood loss (mean = 13.9 ± 8.4mL). At 3-months, 12% (n = 9/74) of patients had persistent abdominal pain and underwent additional imaging. 5 of these 9 patients had persistently elevated DUS expiratory PSV and were referred for angioplasty. 3 of these 5 referred patients had resolution of abdominal pain after angioplasty. At 1-year follow up, 90.3% (n = 56/62) continued to have no abdominal pain. Through this series, the largest set of minimally invasive (laparoscopic or robotic) MALR procedures published to date, we show that with strict adherence to a management algorithm, the robotic approach to MALR is safe and feasible, with good patient outcomes.