Abstract
3D imaging datasets from cardiac computed tomography (CT), magnetic resonance imaging (CMR), or echocardiography can be used to create 3D virtual models for 3D printing. Although CT imaging is not considered first line to diagnose congenital heart disease, it has significant advantages when a 3D printed cardiac model is needed. Advantages over ultrasound include ability to depict vascular and non-vascular extracardiac structures and coronary anatomy with high tissue contrast between lumen and myocardium/vessel wall. CTA also offers superior spatial resolution to MRI, is more widely available, and can be acquired in shorter imaging times. Compared to cardiac CT, CMR offers the advantages of lack of radiation exposure, better temporal resolution, and good blood to myocardium differentiation without the necessary use of intravenous contrast. Echocardiography on the other hand allows real-time image acquisition often without the need for sedation, provides detailed images of valve anatomy, and is a readily available technology which does not routinely require much advanced notice for use of an ultrasound machine. This chapter covers the details of each technology including descriptions of imaging protocols and settings that may be applied to optimize images to be used for 3D printed model creation.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Shiraishi I, Yamagishi M, Hamaoka K, Fukuzawa M, Yagihara T. Simulative operation on congenital heart disease using rubber-like urethane stereolithographic biomodels based on 3D datasets of multislice computed tomography. Eur J Cardiothorac Surg. 2010;37(2):302.
Greil GF, Wolf I, Kuettner A, et al. Stereolithographic reproduction of complex cardiac morphology based on high spatial resolution imaging. Clin Res Cardiol. 2007;96(3):176.
Maragiannis D, Jackson MS, Igo SR, et al. Replicating patient-specific severe aortic valve stenosis with functional 3D modeling. Circ Cardiovasc Imaging. 2015;8(10):e003626.
Han BK, Rigsby CK, Hlavacek A, et al. Computed tomography imaging in patients with congenital heart disease part I: rationale and utility. An expert consensus document of the society of Cardiovascular Computed Tomography (SCCT): endorsed by the Society of Pediatric Radiology (SPR) and the north American Society of Cardiac Imaging (NASCI). J Cardiovasc Comput Tomogr. 2015;9(6):475.
American College of Cardiology Foundation Task Force on Expert Consensus D, Hundley WG, Bluemke DA et al. ACCF/ACR/AHA/NASCI/SCMR 2010 expert consensus document on cardiovascular magnetic resonance: a report of the American College of Cardiology Foundation task force on expert consensus documents. J Am Coll Cardiol. 2010;55(23):2614.
Han BK, Rigsby CK, Leipsic J, et al. Computed tomography imaging in patients with congenital heart disease, part 2: technical recommendations. An expert consensus document of the society of Cardiovascular Computed Tomography (SCCT): Endorsed by the Society of Pediatric Radiology (SPR) and the North American Society of Cardiac Imaging (NASCI). J Cardiovasc Comput Tomogr. 2015;9(6):493.
Han BK, Lindberg J, Overman D, et al. Safety and accuracy of dual-source coronary computed tomography angiography in the pediatric population. J Cardiovasc Comput Tomogr. 2012;6(4):252.
Rigsby CK, Gasber E, Seshadri R, et al. Safety and efficacy of pressure-limited power injection of iodinated contrast medium through central lines in children. AJR Am J Roentgenol. 2007;188(3):726.
Shuman WP, Leipsic JA, Busey JM, et al. Prospectively ECG gated CT pulmonary angiography versus helical ungated CT pulmonary angiography: impact on cardiac related motion artifacts and patient radiation dose. Eur J Radiol. 2012;81(9):2444.
Halliburton S, Arbab-Zadeh A, Dey D, et al. State-of-the-art in CT hardware and scan modes for cardiovascular CT. J Cardiovasc Comput Tomogr. 2012;6(3):154.
Halliburton SS, Abbara S, Chen MY, et al. SCCT guidelines on radiation dose and dose-optimization strategies in cardiovascular CT. J Cardiovasc Comput Tomogr. 2011;5(4):198.
Siegel MJ, Hildebolt C, Bradley D. Effects of automated kilovoltage selection technology on contrast-enhanced pediatric CT and CT angiography. Radiology. 2013;268(2):538.
Jadhav SP, Golriz F, Atweh LA, Zhang W, Krishnamurthy R. CT angiography of neonates and infants: comparison of radiation dose and image quality of target mode prospectively ECG-gated 320-MDCT and ungated helical 64-MDCT. AJR Am J Roentgenol. 2015;204(2):W184.
Huang MP, Liang CH, Zhao ZJ, et al. Evaluation of image quality and radiation dose at prospective ECG-triggered axial 256-slice multi-detector CT in infants with congenital heart disease. Pediatr Radiol. 2011;41(7):858.
Son SS, Choo KS, Jeon UB, et al. Image quality of CT angiography with model-based iterative reconstruction in young children with congenital heart disease: comparison with filtered back projection and adaptive statistical iterative reconstruction. Int J Cardiovasc Imaging. 2015;31(Suppl 1):31.
Mottl-Link S, Hübler M, Kühne T, Rietdorf U, Krueger JJ, Schnackenburg B, et al. Physical models aiding in complex congenital heart surgery. Ann Thorac Surg. 2008;86(1):273–7.
Vranicar M, Gregory W, Douglas WI, Di Sessa P, Di Sessa TG. The use of stereolithographic hand held models for evaluation of congenital anomalies of the great arteries. Stud Health Technol Inform. 2008;132:538–43.
Farooqi KM, Nielsen JC, Uppu SC, Srivastava S, Parness I, Sanz J, Nguyen K. Use of 3D printing to demonstrate complex intra-cardiac relationships in double outlet right ventricle for surgical planning. Circ Cardiovasc Imaging. 2015;8(5):e003043.
Farooqi KM, Gonzalez-Lengua C, Weinberg AD, Nielsen JC, Sanz J. Blood pool segmentation results in superior virtual cardiac models than myocardial segmentation for 3D printing. Pediatr Cardiol. 2016.
Groves EM, Bireley W, Dill K, Carroll TJ, Carr JC. Quantitative analysis of ECG-gated high-resolution contrast-enhanced MR angiography of the thoracic aorta. AJR Am J Roentgenol. 2007;188(2):522–8.
Foo TK, Ho VB, Marcos HB, Hood MN, Choyke PL. MR angiography using steady-state free precession. Magn Reson Med. 2002;48(4):699–706.
Lang RM, Badano LP, Tsang W, Adams DH, Agricola E, Buck T, et al. EAE/ASE recommendations for image acquisition and display using three-dimensional echocardiography. Eur Heart J Cardiovasc Imaging. 2012;13(1):1–46.
Roberson DA, Cui W, Patel D, Tsang W, Sugeng L, Weinert L, et al. Three-dimensional transesophageal echocardiography of atrial septal defect: a qualitative and quantitative anatomic study. J Am Soc Echocardiogr. 2011;24(6):600–10.
Pushparajah K, Miller OI, Simpson JM. 3D echocardiography of the atrial septum: anatomical features and landmarks for the echocardiographer. JACC Cardiovasc Imaging. 2010;3(9):981–4.
Simpson JM, Miller O. Three-dimensional echocardiography in congenital heart disease. Arch Cardiovasc Dis. 2011;104(1):45–56.
Lang RM, Badano LP, Tsang W, Adams DH, Agricola E, Buck T, et al. EAE/ASE recommendations for image acquisition and display using three-dimensional echocardiography. J Am Soc Echocardiogr. 2012;25(1):3–46.
Olivieri LJ, Krieger A, Loke YH, Nath DS, Kim PC, Sable CA. Three-dimensional printing of intracardiac defects from three-dimensional echocardiographic images: feasibility and relative accuracy. J Am Soc Echocardiogr. 2015;28(4):392–7.
Witschey WR, Pouch AM, McGarvey JR, Ikeuchi K, Contijoch F, Levack MM, et al. Three-dimensional ultrasound-derived physical mitral valve modeling. Ann Thorac Surg. 2014;98(2):691–4.
Pouch AM, Yushkevich PA, Jackson BM, Jassar AS, Vergnat M, Gorman JH, et al. Development of a semi-automated method for mitral valve modeling with medial axis representation using 3D ultrasound. Med Phys. 2012;39(2):933–50.
Pouch AM, Wang H, Takabe M, Jackson BM, Gorman JH 3rd, Gorman RC, et al. Fully automatic segmentation of the mitral leaflets in 3D transesophageal echocardiographic images using multi-atlas joint label fusion and deformable medial modeling. Med Image Anal. 2014;18(1):118–29.
Pouch AM, Xu C, Yushkevich PA, Jassar AS, Vergnat M, Gorman JH 3rd, et al. Semi-automated mitral valve morphometry and computational stress analysis using 3D ultrasound. J Biomech. 2012;45(5):903–7.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this chapter
Cite this chapter
Sanz, J., Farooqi, K.M., Nielsen, J.C., Srivastava, S. (2017). Image Acquisition for Creation of a 3D Model: CT, CMR, and Echocardiography. In: Farooqi, K. (eds) Rapid Prototyping in Cardiac Disease. Springer, Cham. https://doi.org/10.1007/978-3-319-53523-4_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-53523-4_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-53522-7
Online ISBN: 978-3-319-53523-4
eBook Packages: MedicineMedicine (R0)