Nicolette S Birbara1, James M Otton2, Nalini Pather3. 1. School of Medical Sciences, Medicine, University of New South Wales, Sydney, NSW, Australia. 2. School of Medical Sciences, Medicine, University of New South Wales, Sydney, NSW, Australia; Victor Chang Cardiac Research Institute, Sydney, NSW, Australia; Liverpool Hospital, Sydney, NSW, Australia. 3. School of Medical Sciences, Medicine, University of New South Wales, Sydney, NSW, Australia. Electronic address: n.pather@unsw.edu.au.
Abstract
BACKGROUND: A comprehensive knowledge of mitral valve (MV) anatomy is crucial in the assessment of MV disease. While the use of three-dimensional (3D) modelling and printing in MV assessment has undergone early clinical evaluation, the precision and usefulness of this technology requires further investigation. This study aimed to assess and validate 3D modelling and printing technology to produce patient-specific 3D MV models. METHODS: A prototype method for MV 3D modelling and printing was developed from computed tomography (CT) scans of a plastinated human heart. Mitral valve models were printed using four 3D printing methods and validated to assess precision. Cardiac CT and 3D echocardiography imaging data of four MV disease patients was used to produce patient-specific 3D printed models, and 40 cardiac health professionals (CHPs) were surveyed on the perceived value and potential uses of 3D models in a clinical setting. RESULTS: The prototype method demonstrated submillimetre precision for all four 3D printing methods used, and statistical analysis showed a significant difference (p<0.05) in precision between these methods. Patient-specific 3D printed models, particularly using multiple print materials, were considered useful by CHPs for preoperative planning, as well as other applications such as teaching and training. CONCLUSIONS: This study suggests that, with further advances in 3D modelling and printing technology, patient-specific 3D MV models could serve as a useful clinical tool. The findings also highlight the potential of this technology to be applied in a variety of medical areas within both clinical and educational settings.
BACKGROUND: A comprehensive knowledge of mitral valve (MV) anatomy is crucial in the assessment of MV disease. While the use of three-dimensional (3D) modelling and printing in MV assessment has undergone early clinical evaluation, the precision and usefulness of this technology requires further investigation. This study aimed to assess and validate 3D modelling and printing technology to produce patient-specific 3D MV models. METHODS: A prototype method for MV 3D modelling and printing was developed from computed tomography (CT) scans of a plastinated human heart. Mitral valve models were printed using four 3D printing methods and validated to assess precision. Cardiac CT and 3D echocardiography imaging data of four MV diseasepatients was used to produce patient-specific 3D printed models, and 40 cardiac health professionals (CHPs) were surveyed on the perceived value and potential uses of 3D models in a clinical setting. RESULTS: The prototype method demonstrated submillimetre precision for all four 3D printing methods used, and statistical analysis showed a significant difference (p<0.05) in precision between these methods. Patient-specific 3D printed models, particularly using multiple print materials, were considered useful by CHPs for preoperative planning, as well as other applications such as teaching and training. CONCLUSIONS: This study suggests that, with further advances in 3D modelling and printing technology, patient-specific 3D MV models could serve as a useful clinical tool. The findings also highlight the potential of this technology to be applied in a variety of medical areas within both clinical and educational settings.
Authors: David A Salazar; Justin Cramer; Nicholas W Markin; Nathaniel H Hunt; Gabe Linke; Justin Siebler; Jorge Zuniga Journal: Ann Transl Med Date: 2022-04
Authors: Ramtin Gharleghi; Claire A Dessalles; Ronil Lal; Sinead McCraith; Kiran Sarathy; Nigel Jepson; James Otton; Abdul I Barakat; Susann Beier Journal: Ann Biomed Eng Date: 2021-05-17 Impact factor: 3.934
Authors: Nalini Pather; Phil Blyth; Jamie A Chapman; Manisha R Dayal; Natasha A M S Flack; Quentin A Fogg; Rodney A Green; Anneliese K Hulme; Ian P Johnson; Amanda J Meyer; John W Morley; Peter J Shortland; Goran Štrkalj; Mirjana Štrkalj; Krisztina Valter; Alexandra L Webb; Stephanie J Woodley; Michelle D Lazarus Journal: Anat Sci Educ Date: 2020-05-10 Impact factor: 5.958