Research Article: 3D printing for congenital heart disease: a single site’s initial three-yearexperience

Date Published: November 8, 2018

Publisher: Springer International Publishing

Author(s): Justin Ryan, Jonathan Plasencia, Randy Richardson, Daniel Velez, John J. Nigro, Stephen Pophal, David Frakes.

http://doi.org/10.1186/s41205-018-0033-8

Abstract

3D printing is an ideal manufacturing process for creating patient-matched models (anatomical models) for surgical and interventional planning. Cardiac anatomical models have been described in numerous case studies and journal publications. However, few studies attempt to describe wider impact of the novel planning augmentation tool. The work here presents the evolution of an institution’s first 3 full years of 3D prints following consistent integration of the technology into clinical workflow (2012–2014) – a center which produced 79 models for surgical planning (within that time frame). Patient outcomes and technology acceptance following implementation of 3D printing were reviewed.

A retrospective analysis was designed to investigate the anatomical model’s impact on time-based surgical metrics. A contemporaneous cohort of standard-of-care pre-procedural planning (no anatomical models) was identified for comparative analysis. A post-surgery technology acceptance assessment was also employed in a smaller subset to measure perceived efficacy of the anatomical models. The data was examined.

Within the timeframe of the study, 928 primary-case cardiothoracic surgeries (encompassing both CHD and non-CHD surgeries) took place at the practicing pediatric hospital. One hundred sixty four anatomical models had been generated for various purposes. An inclusion criterion based on lesion type limited those with anatomic models to 33; there were 113 cases matching the same criterion that received no anatomical model. Time-based metrics such as case length-of-time showed a mean reduction in overall time for anatomical models. These reductions were not statistically significant. The technology acceptance survey did demonstrate strong perceived efficacy. Anecdotal vignettes further support the technology acceptance.

The anatomical models demonstrate trends for reduced operating room and case length of time when compared with similar surgeries in the same time-period; in turn, these reductions could have significant impact on patient outcomes and operating room economics. While analysis did not yield robust statistical powering, strong Cohen’s d values suggest poor powering may be more related to sample size than non-ideal outcomes. The utility of planning with an anatomical model is further supported by the technology acceptance study which demonstrated that surgeons perceive the anatomical models to be an effective tool in surgical planning for a complex CHD repair. A prospective multi-center trial is currently in progress to further validate or reject these findings.

Partial Text

Congenital heart disease (CHD) is a significant morphological deviation of cardiac anatomy present at birth, resulting in hemodynamic and functional anomalies, often necessitating early interventional and/or surgical palliation or repair. Patients with CHD lesions represent a significant part of the medical population as the lesions are present in approximately 8 out of 1000 births in the United States [1–3] and represent the leading cause of mortality from congenital defects [4].

Phoenix Children’s Hospital’s Institutional Review Board approved the following retrospective study for patients between September 1, 2012 and December 31, 2014.

Within the timeframe of the study, 928 primary-case cardiothoracic surgeries (encompassing both CHD and non-CHD surgeries) took place at the practicing pediatric hospital. In that time-frame, 164 anatomical models had been generated for various purposes: education, family consultation, catheter-based intervention, and surgical planning; 79 models were specifically used for surgical planning of CHD patients. As these 79 spanned many different disease lesions with drastically different inherent complexities, a further-restricting inclusion criteria was established keeping patients with the following lesions: 1) pulmonary atresia (ventricular septal defect variant), 2) Tetralogy of Fallot (pulmonary atresia and absent pulmonary valve variants), 3) double outlet right ventricle (transposition of the great arteries variant), 4) truncus arteriosus, 5) vascular rings, and 6) single ventricle. The inclusion criteria limited those with anatomic models to 33; standard-of-care (no anatomical models) cases for the same time frame and inclusion criteria amounted to 113 (Tables 1, 2 and 3).Table 1ANOVA table illustrating the effect of anatomical model-based planning on case length of time. Green cells illustrate the lower, preferred mean time for surgeries planned with an anatomical model. Anatomical models are abbreviated as 3DP. Abbreviations: D.F. is degrees of freedom, Adj. S.S. is adjusted sum of squares, Adj. M.S. is adjusted mean squares, St.Dev is standard deviation, and C.I. is confidence intervalCase length of time (anatomical model vs Traditional Planning): all included patientsSourceD.F.Adj. S.S.Adj. M.S.F-ValueP-Value 3DP1191619160.180.674 Error1441,557,29210,815 Total1451,559,208PlanningNMean (minutes)St.Dev95 C.I. SoC113229.33101.81(209.99, 248.66) 3DP33220.7111.3(184.9, 256.4)Case length of time’s Cohen’s d effect size was small (0.081) suggesting no practical difference between SoC and 3DP case length of time for all patient casesTable 2Contingency tables illustrating the effect of anatomical model-based planning on 30-day readmission and 30-day mortality. Fisher’s exact test was used to determine probability for the rejection of the stated null hypothesis30-day Readmission (anatomical model vs Traditional Planning): all included patientsCount Total%No 30-day Readm.30-day Readm.TotalFisher’s Exact TestSoC3122.30%7856.12%10978.42%Null Hypothesis:• Probability of readmission is greater for surgeries planned with an anatomical model• P-value = 0.16093DP128.63%1812.95%3021.58%Total4330.94%9669.06%139100.0%Table 3Contingency tables illustrating the effect of anatomical model-based planning on 30-day readmission and 30-day mortality. Fisher’s exact test was used to determine probability for the rejection of the stated null hypothesis30 day Mortality (anatomical model vs Traditional Planning): all included patientsCount Total%No 30-day Mort.30-day Mort.TotalFisher’s Exact TestSoC11176.03%21.37%11377.40%Null Hypothesis:• Probability of 30-day mortality is greater for surgeries planned with an anatomical model• P-value = 0.59783DP3322.60%00.00%3322.60%Total14496.63%21.37%146100.0%

The advent of commercially-available 3D printing technology has enabled systematic development of anatomical models for surgical planning. The retrospective study illustrates not only the systemic integration of 3D technology into the medical environment, but it also proposes potential areas of impact within the care system. However, the work herein is not unique to the medical domain. As mentioned, there are numerous publications from case studies to case series and even a few larger studies already in print [5, 7–37]. The novelty of this study is in its earnest attempt to statistically describe the anatomical models’ impact with the intent of informing the design of a subsequent studies/trials.

Despite these study biases and modeling limitations, the surgical anatomical model study demonstrates trends for reduced operating room and case length of time. The added benefit may be attributed to better surgeon preparedness. This preparedness may yield better patient outcomes with lower chances for morbidity and mortality. The utility of planning with an anatomical model is supported by the TAM study which demonstrated that anatomical models for surgical planning may increase surgeon familiarity of patient-specific morphology and help surgeon plan for a complex CHD repair. A multi-center clinical trial, currently in progress, could show the measured effect of the anatomical model on critical surgical factors such as 30-day outcome, case length of time, or cardiopulmonary bypass time. Illustrating reductions in morbidity and mortality in patients with CHDs would aid in the acceptance, by the greater medical community, regarding the efficacy of anatomical model as a surgical planning tool. Acceptance of the technology is already high at the participating hospital where over 500 hearts have been printed for clinical planning to date.

 

Source:

http://doi.org/10.1186/s41205-018-0033-8

 

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