Implementing Models for Mechanical Circulatory Support Presurgical Assessment in Congenital Heart Disease Treatment

Congenital heart disease (CHD) remains the most common type of major congenital malformation and the leading cause of mortality from birth defects [1-4]. Advances in effective treatment for these lesions have significantly extended the lifespan of affected patients, especially for the most complex subtypes of disease. However, these patients are at higher risk of heart failure (HF) secondary to longer life expectancy. This includes patients with a systemic right ventricle and a single ventricle circulation palliated by a Fontan procedure [5, 6]. HF has been documented in up to 30% of patients with a systemic right ventricle and 40% of patients who have had a Fontan procedure [7].

Ventricular assist devices (VAD) are implanted in patients with HF to improve cardiac output and prolong life. VAD remains underutilized in patients with CHD and HF in part due to the highly variable anatomy in this population. This is true despite outcomes having been shown to be the same for VAD placement in patients with and without CHD [8-10]. In the absence of VAD placement, however, wait list mortality for patients with CHD is higher than for those patients without CHD [11, 12].

Advances in imaging techniques have allowed early diagnosis of CHD as well as anatomic assessment prior to surgical procedures. Given the significant yet often subtle anatomic differences between CHD patients, it is a substantial challenge to thoroughly depict all of the components of a complex patient's cardiac anatomy in a two-dimensional imaging dataset. An innovative technology that is being used with more enthusiasm in the medical field, is three-dimensional (3D) printing. The investigator and the research team have previously reported on the best technique that should be used to create 3D printed cardiac models from MRI and the subtypes of complex CHD's for which 3D printing should be utilized [13-16]. 3D printing allows creation of patient specific physical anatomic models from a patient's own imaging data. These models provide a physical guide to patient-specific anatomic features that often make VAD and cannula placement challenging in patients with CHD [17]. Factors such as complex cardiac anatomic malformations, heavy trabeculations or a severely dilated ventricle can distort the usual anatomic landmarks used to identify the best position for cannula placement. The primary goal is to establish the utility of this advanced imaging technique, which provides a much more comprehensive understanding of complex congenital cardiac anatomy. The investigator hypothesizes that 3D printed models will allow more informed preoperative planning with a clearer understanding of the best site for inflow and outflow cannula and VAD placement leading to better surgical preparedness, less operating room time and improved patient outcomes.

AIM 1: To assess if a 3D printed cardiac model improves perceived visualization of VAD and cannula placement sites in CHD-HF patients as compared to 2D imaging. The study will prospectively enroll CHD-HF patients at multiple centers and randomize to Group A (3D printed models will be used for pre-VAD planning) or Group B (no model-controls). For both Groups, all of the cardiothoracic surgeons at the participating center will complete a questionnaire after reviewing 2D imaging data. For Group A, a survey will also be administered after reviewing a patient specific 3D model. The primary outcome measure will be better perceived visualization of cannula and VAD sites. The investigator hypothesizes that the 3D model will more clearly demonstrate sites of cannula and VAD placement as compared to 2D imaging.

AIM 2: To determine if perioperative factors and outcomes improve in CHD-HF patients with use of a 3D printed model versus traditional imaging in VAD placement planning. Clinical characteristics will be collected at time of enrollment including primary diagnosis and indication for VAD. After VAD placement, information regarding the intraoperative and postoperative course will be collected including surgical cardiopulmonary bypass time (CPB) and need for cannula repositioning. Longer CPB increases morbidity and mortality and is associated with intensive care readmission in patients after LVAD placement [18-20]. The primary measures of improvement will be CPB. The investigator hypothesizes that the improved preoperative planning using 3D models will lead to a decrease in CPB time.