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

Last updated: July 3, 2024
Sponsor: Columbia University
Overall Status: Active - Recruiting

Phase

N/A

Condition

Heart Disease

Congenital Heart Disease

Pentalogy Of Cantrell

Treatment

3D model of heart

Clinical Study ID

NCT03891160
AAAR7877
1K23HL165083-01
  • All Genders

Study Summary

The purpose of this research study is to look at the advantages of using a 3D printed heart model for surgical planning in children who have been diagnosed with Congenital Heart Disease (CHD) and clinical heart failure and will undergo a ventricular assist device (VAD) placement. The investigators want to study the correlation of having a 3D printed model with improvement in patient outcomes and compare those with patients who have had a VAD placement without a 3D model.

Eligibility Criteria

Inclusion

Inclusion Criteria:

  • Patients who weigh over 3 kilograms with CHD HF who are candidates for MCS will beprospectively identified at the participating centers.

Exclusion

Exclusion Criteria:

  • Any CHD-HF patient unable to tolerate a CMR or cardiac CT will be excluded.

Study Design

Total Participants: 36
Treatment Group(s): 1
Primary Treatment: 3D model of heart
Phase:
Study Start date:
January 22, 2020
Estimated Completion Date:
July 31, 2027

Study Description

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.

The skill with which patient specific CHD anatomy for pre-procedural planning is assessed must be improved, especially for the most complex patients. To confirm the clinical benefit of 3D printed models in pre-surgical planning and justify their use in routine care, multicenter clinical trials must be conducted. As an expert in the field of 3D imaging in cardiac disease, the investigator is well poised to lead this body of research. The goal is to become well versed in conducting high quality multicenter studies and to become facile in survey tool design through this K23 proposal. The investigator will then design a prospective multicenter study for an independent R01 proposal focused on assessing the utility of 3D models in pre-procedural planning for all complex congenital heart diseases. Investigating and reporting on these findings will result in a paradigm shift in what one considers "standard of care" for advanced imaging offered to our most complex CHD patients.

Connect with a study center

  • Montreal Heart Institute

    Montreal, QC H1T 1C8
    Canada

    Site Not Available

  • LaCardio

    Bogotá,
    Colombia

    Site Not Available

  • Instituto Nacional Cardiologia (Heart Institute)

    Mexico City, 14000
    Mexico

    Site Not Available

  • Children's National Hospital

    Washington, District of Columbia 20010
    United States

    Active - Recruiting

  • University of Florida

    Gainesville, Florida 32610
    United States

    Active - Recruiting

  • Children's Healthcare of Atlanta

    Atlanta, Georgia 30322
    United States

    Active - Recruiting

  • Lurie Children's Hospital

    Chicago, Illinois 60611
    United States

    Active - Recruiting

  • University of Iowa

    Iowa City, Iowa 52242
    United States

    Active - Recruiting

  • Johns Hopkins

    Baltimore, Maryland 21287
    United States

    Site Not Available

  • Harvard

    Boston, Massachusetts 02115
    United States

    Site Not Available

  • University of Michigan

    Ann Arbor, Michigan 48109
    United States

    Site Not Available

  • Mayo Clinic

    Rochester, Minnesota 55905
    United States

    Site Not Available

  • Washington University

    Saint Louis, Missouri 63110
    United States

    Active - Recruiting

  • Montefiore Medical Center

    Bronx, New York 10467
    United States

    Site Not Available

  • Columbia University

    New York, New York 10032
    United States

    Active - Recruiting

  • Weill Cornell

    New York, New York 10065
    United States

    Site Not Available

  • Duke University

    Durham, North Carolina 27710
    United States

    Site Not Available

  • Cleveland Clinic

    Cleveland, Ohio 44195
    United States

    Active - Recruiting

  • Nationwide Children's

    Columbus, Ohio 43205
    United States

    Site Not Available

  • UT Southwestern

    Dallas, Texas 75390
    United States

    Site Not Available

  • University of Virginia

    Charlottesville, Virginia 22903
    United States

    Site Not Available

  • Seattle childrens

    Seattle, Washington 98105
    United States

    Site Not Available

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