title: Blood Pool Segmentation Results in Superior Virtual Cardiac Models than Myocardial Segmentation for 3D Printing.
abstract: The method of cardiac magnetic resonance (CMR) three-dimensional (3D) image acquisition and post-processing which should be used to create optimal virtual models for 3D printing has not been studied systematically. Patients (n = 19) who had undergone CMR including both 3D balanced steady-state free precession (bSSFP) imaging and contrast-enhanced magnetic resonance angiography (MRA) were retrospectively identified. Post-processing for the creation of virtual 3D models involved using both myocardial (MS) and blood pool (BP) segmentation, resulting in four groups: Group 1-bSSFP/MS, Group 2-bSSFP/BP, Group 3-MRA/MS and Group 4-MRA/BP. The models created were assessed by two raters for overall quality (1-poor; 2-good; 3-excellent) and ability to identify predefined vessels (1-5: superior vena cava, inferior vena cava, main pulmonary artery, ascending aorta and at least one pulmonary vein). A total of 76 virtual models were created from 19 patient CMR datasets. The mean overall quality scores for Raters 1/2 were 1.63 ± 0.50/1.26 ± 0.45 for Group 1, 2.12 ± 0.50/2.26 ± 0.73 for Group 2, 1.74 ± 0.56/1.53 ± 0.61 for Group 3 and 2.26 ± 0.65/2.68 ± 0.48 for Group 4. The numbers of identified vessels for Raters 1/2 were 4.11 ± 1.32/4.05 ± 1.31 for Group 1, 4.90 ± 0.46/4.95 ± 0.23 for Group 2, 4.32 ± 1.00/4.47 ± 0.84 for Group 3 and 4.74 ± 0.56/4.63 ± 0.49 for Group 4. Models created using BP segmentation (Groups 2 and 4) received significantly higher ratings than those created using MS for both overall quality and number of vessels visualized (p < 0.05), regardless of the acquisition technique. There were no significant differences between Groups 1 and 3. The ratings for Raters 1 and 2 had good correlation for overall quality (ICC = 0.63) and excellent correlation for the total number of vessels visualized (ICC = 0.77). The intra-rater reliability was good for Rater A (ICC = 0.65). Three models were successfully printed on desktop 3D printers with good quality and accurate representation of the virtual 3D models. We recommend using BP segmentation with either MRA or bSSFP source datasets to create virtual 3D models for 3D printing. Desktop 3D printers can offer good quality printed models with accurate representation of anatomic detail.
authors.affiliation: Division of Pediatric Cardiology, Rutgers-New Jersey Medical School, 185 South Orange Avenue- MSB-F512, Newark, NJ, 07103, USA. Kanwal.farooqi@rutgers.edu.|Division of Pediatric Cardiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA. Kanwal.farooqi@rutgers.edu.|Zena and Michael A. Wiener Cardiovascular Institute and Marie-Josee and Henry R. Kravis Center for Cardiovascular Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA. Kanwal.farooqi@rutgers.edu.
authors.forename: Kanwal M
authors.initials: KM
authors.lastname: Farooqi
authors.affiliation: Zena and Michael A. Wiener Cardiovascular Institute and Marie-Josee and Henry R. Kravis Center for Cardiovascular Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
authors.forename: Carlos Gonzalez
authors.initials: CG
authors.lastname: Lengua
authors.affiliation: Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
authors.forename: Alan D
authors.initials: AD
authors.lastname: Weinberg
authors.affiliation: Division of Pediatric Cardiology, Rutgers-New Jersey Medical School, 185 South Orange Avenue- MSB-F512, Newark, NJ, 07103, USA.|Division of Pediatric Cardiology, Stony Brook University Medical Center, Stony Brook, NY, USA.
authors.forename: James C
authors.initials: JC
authors.lastname: Nielsen
authors.affiliation: Zena and Michael A. Wiener Cardiovascular Institute and Marie-Josee and Henry R. Kravis Center for Cardiovascular Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
authors.forename: Javier
authors.initials: J
authors.lastname: Sanz
mesh_terms: D006321:Heart; D006801:Humans; D021621:Imaging, Three-Dimensional; D018810:Magnetic Resonance Angiography; D066330:Printing, Three-Dimensional; D015203:Reproducibility of Results
keywords: 3D printing; Cardiac imaging; Cardiac models; Segmentation