Dataset Information

3D-Printing in Congenital Cardiology: From Flatland to Spaceland.

ABSTRACT: Medical imaging has changed to a great extent over the past few decades. It has been revolutionized by three-dimensional (3D) imaging techniques. Despite much of modern medicine relying on 3D imaging, which can be obtained accurately, we keep on being limited by visualization of the 3D content on two-dimensional flat screens. 3D-printing of graspable models could become a feasible technique to overcome this gap. Therefore, we printed pre- and postoperative 3D-models of a complex congenital heart defect. With this example, we intend to illustrate that these models hold value in preoperative planning, postoperative evaluation of a complex procedure, communication with the patient, and education of trainees. At this moment, 3D printing only leaves a small footprint, but makes already a big impression in the domain of cardiology and cardiovascular surgery. Further studies including more patients and more validated applications are needed to streamline 3D printing in the clinical setting of daily practice.

SUBMITTER: Deferm S

PROVIDER: S-EPMC4860452 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

3D-Printing in Congenital Cardiology: From Flatland to Spaceland.

Deferm Sébastien S Meyns Bart B Vlasselaers Dirk D Budts Werner W

Journal of clinical imaging science 20160330

Medical imaging has changed to a great extent over the past few decades. It has been revolutionized by three-dimensional (3D) imaging techniques. Despite much of modern medicine relying on 3D imaging, which can be obtained accurately, we keep on being limited by visualization of the 3D content on two-dimensional flat screens. 3D-printing of graspable models could become a feasible technique to overcome this gap. Therefore, we printed pre- and postoperative 3D-models of a complex congenital heart ...[more]

PMID: 27195174

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Project description:Inertial microfluidics has been broadly investigated, resulting in the development of various applications, mainly for particle or cell separation. Lateral migrations of these particles within a microchannel strictly depend on the channel design and its cross-section. Nonetheless, the fabrication of these microchannels is a continuous challenging issue for the microfluidic community, where the most studied channel cross-sections are limited to only rectangular and more recently trapezoidal microchannels. As a result, a huge amount of potential remains intact for other geometries with cross-sections difficult to fabricate with standard microfabrication techniques. In this study, by leveraging on benefits of additive manufacturing, we have proposed a new method for the fabrication of inertial microfluidic devices. In our proposed workflow, parts are first printed via a high-resolution DLP/SLA 3D printer and then bonded to a transparent PMMA sheet using a double-coated pressure-sensitive adhesive tape. Using this method, we have fabricated and tested a plethora of existing inertial microfluidic devices, whether in a single or multiplexed manner, such as straight, spiral, serpentine, curvilinear, and contraction-expansion arrays. Our characterizations using both particles and cells revealed that the produced chips could withstand a pressure up to 150?psi with minimum interference of the tape to the total functionality of the device and viability of cells. As a showcase of the versatility of our method, we have proposed a new spiral microchannel with right-angled triangular cross-section which is technically impossible to fabricate using the standard lithography. We are of the opinion that the method proposed in this study will open the door for more complex geometries with the bespoke passive internal flow. Furthermore, the proposed fabrication workflow can be adopted at the production level, enabling large-scale manufacturing of inertial microfluidic devices.

Dataset Information

3D-Printing in Congenital Cardiology: From Flatland to Spaceland.

Publications

3D-Printing in Congenital Cardiology: From Flatland to Spaceland.

Similar Datasets

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