Developing patient-specific carotid artery ultrasound imaging phantoms for clinical training using 3D printing

2019 ◽  
Vol 74 ◽  
pp. e9-e10
Author(s):  
Inshal Imtiaz ◽  
Nazia Malik ◽  
Wenfeng Xia ◽  
Efthymios Maneas ◽  
Adrien Desjardins
Keyword(s):  
3D Printing ◽  
Carotid Artery ◽  
Ultrasound Imaging ◽  
Clinical Training ◽  
Patient Specific ◽  
Imaging Phantoms

scholarly journals Characterization of 3-Dimensional Printing and Casting Materials for use in Magnetic Resonance Imaging Phantoms at 3 T

2020 ◽  
Vol 125 ◽  
Author(s):  
B. E. Yunker ◽  
K. F. Stupic ◽  
J. L. Wagner ◽  
S. Huddle ◽  
R. Shandas ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Tensile Strength ◽  
Magnetic Resonance ◽  
3D Printing ◽  
Spin Echo ◽  
Relaxation Times ◽  
Patient Specific ◽  
Resonance Imaging ◽  
Fused Deposition ◽  
Imaging Phantoms

Imaging phantoms are used to calibrate and validate the performance of magnetic resonance imaging (MRI) systems. Many new materials have been developed for additive manufacturing (three-dimensional [3D] printing) processes that may be useful in the direct printing or casting of dimensionally accurate, anatomically accurate, patient-specific, and/or biomimetic MRI phantoms. The T1, T2, and T2* spin relaxation times of polymer samples were tested to discover materials for use as tissue mimics and structures in MRI phantoms. This study included a cohort of polymer compounds that was tested in cured form. The cohort consisted of 101 standardized polymer samples fabricated from: two-part silicones and polyurethanes used in commercial casting processes; one-part optically cured polyurethanes used in 3D printing; and fused deposition thermoplastics used in 3D printing. The testing was performed at 3 T using inversion recovery, spin echo, and gradient echo sequences for T1, T2, and T2*, respectively. T1, T2, and T2* values were plotted with error bars to allow the reader to assess how well a polymer matches a tissue for a specific application. A correlation was performed between T1, T2 , T2* values and material density, elongation, tensile strength, and hardness. Two silicones, SI_XP-643 and SI_P-45, may be usable mimics for reported liver values; one silicone, SI_XP-643, may be a useful mimic for muscle; one silicone, SI_XP-738, may be a useful mimic for white matter; and four silicones, SI_P-15, SI_GI-1000, SI_GI-1040, and SI_GI-1110, may be usable mimics for spinal cord. Elongation correlated to T2 (p = 0.0007), tensile strength correlated to T1 (p = 0.002), T2 (p = 0.0003), and T2* (p = 0.003). The 80 samples not providing measurable signal with T1, T2, T2* relaxation values too short to measure with the standard sequences, may be useful for MRI-invisible fixturing and medical devices at 3 T.

scholarly journals Point-of-Care 3D Printing: a Low-Cost Approach to Teaching Carotid Artery Stenting

2021 ◽  
Author(s):  
Pieter De Backer ◽  
Charlotte Allaeys ◽  
Charlotte Debbaut ◽  
Roel Beelen
Keyword(s):  
3D Printing ◽  
Carotid Artery ◽  
Carotid Artery Stenting ◽  
3D Model ◽  
Point Of Care ◽  
Low Cost ◽  
Patient Specific ◽  
Stent Deployment ◽  
Invasive Approach ◽  
Minimal Invasive Approach

Abstract Background Carotid Artery Stenting (CAS) is increasingly being used in selected patients as a minimal invasive approach to carotid endarterectomy. Despite the abundance of performed endovascular treatments, the concept of stent-placement is still unclear to many patients. Furthermore, visual feedback on stent-deployment is difficult to obtain as it is always performed under radiographic feedback. Three-Dimensional (3D) printing might tackle both challenges. A particular use case of Point-of-Care 3D Printing is the pretreatment printing of vascular anatomy in support of endovascular procedures. Purpose This study reports the first use of a low-cost patient-specific 3D printed model for CAS education to both experienced surgeons and patients. Methodology An angio computed tomography (CT) scan was segmented and converted to STL format using Mimics inPrint™ software. The carotid arteries were bilaterally truncated to fit the whole model on a Formlabs 2 printer without omitting the internal vessel diameter. Next, this model was offset using a 1 mm margin. A ridge was modelled on the original vessel anatomy which was subsequently subtracted from the offset model in order to obtain a deroofed 3D model. All vessels were truncated as to facilitate flow on the inside. Results Date-expired carotid artery stents were successfully deployed inside the vessel. The deroofing allows for clear visualization of the bottlenecks and characteristics of CAS deployment and positioning, including foreshortening and tapering of the stent. This low-cost 3D model provides insights in stent deployment and positioning, and allows for patient-specific procedure planning. Conclusion Printing patient-specific 3D models preoperatively could assist in accurate patient selection, a better preoperative planning and case-specific training. Furthermore, this 3D model also allows for better patient education and informed consent. However, more research is warranted to evaluate the added value of these models.

scholarly journals Point-of-care 3D printing: a low-cost approach to teaching carotid artery stenting

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Pieter De Backer ◽  
Charlotte Allaeys ◽  
Charlotte Debbaut ◽  
Roel Beelen
Keyword(s):  
Patient Education ◽  
3D Printing ◽  
Carotid Artery ◽  
Carotid Artery Stenting ◽  
3D Model ◽  
Low Cost ◽  
Patient Specific ◽  
Stent Deployment ◽  
Invasive Approach ◽  
3D Printed

Abstract Background Carotid Artery Stenting (CAS) is increasingly being used in selected patients as a minimal invasive approach to carotid endarterectomy. Despite the long standing tradition of endovascular treatments, visual feedback during stent-deployment is impossible to obtain as deployment is performed under fluoroscopic imaging. Furthermore, the concept of stent-placement is often still unclear to patients. 3D Printing allows to replicate patient-specific anatomies and deploy stents inside them to simulate procedures. As such these models are being used for endovascular training as well as patient education. Purpose To our knowledge, this study reports the first use of a low-cost patient-specific 3D printed model for teaching CAS deployment under direct visualization, without fluoroscopy. Methodology A CT-angiogram was segmented and converted to STL format using Mimics inPrint™ software. The carotid arteries were bilaterally truncated to fit the whole model on a Formlabs 2 printer without omitting the internal vessel diameter. Next, this model was offset using a 1 mm margin. A ridge was modelled on the original vessel anatomy which was subsequently subtracted from the offset model in order to obtain a deroofed 3D model. All vessels were truncated to facilitate post-processing, flow and guide wire placement. Results Carotid artery stents were successfully deployed inside the vessel. The deroofing allows for clear visualization of the bottlenecks and characteristics of CAS deployment and positioning, including stent foreshortening, tapering and recoil. This low-cost 3D model provides visual insights in stent deployment and positioning, and can allow for patient-specific procedure planning. Conclusions The presented approach demonstrates the use of low-cost 3D Printed CAS models in teaching complex stent behavior as observed during deployment. Two main findings are illustrated. On one hand, the feasibility of low-cost in-hospital model production is shown. On the other hand, the teaching of CAS deployment bottlenecks at the carotid level without the need for fluoroscopic guidance, is illustrated. The observed stent characteristics as shown during deployment are difficult to assess in radiologic models. Furthermore, printing patient-specific 3D models preoperatively could possibly assist in accurate patient selection, preoperative planning, case-specific training and patient education.

3D Printing & Pharmaceutical Manufacturing: Opportunities and Challenges

2016 ◽  
Vol 5 (01) ◽  
pp. 4723 ◽  
Author(s):  
Bhusnure O. G.* ◽  
Gholve V. S. ◽  
Sugave B. K. ◽  
Dongre R. C. ◽  
Gore S. A. ◽  
...  
Keyword(s):  
Drug Delivery ◽  
Tissue Engineering ◽  
3D Printing ◽  
Computer Aided Design ◽  
Patient Specific ◽  
Computer Design ◽  
3D Scaffolds ◽  
Engineering Research ◽  
Advantages And Disadvantages ◽  
Computer Aided

Many researchers have attempted to use computer-aided design (C.A.D) and computer-aided manufacturing (CAM) to realize a scaffold that provides a three-dimensional (3D) environment for regeneration of tissues and organs. As a result, several 3D printing technologies, including stereolithography, deposition modeling, inkjet-based printing and selective laser sintering have been developed. Because these 3D printing technologies use computers for design and fabrication, and they can fabricate 3D scaffolds as designed; as a consequence, they can be standardized. Growth of target tissues and organs requires the presence of appropriate growth factors, so fabrication of 3Dscaffold systems that release these biomolecules has been explored. A drug delivery system (D.D.S) that administrates a pharmaceutical compound to achieve a therapeutic effect in cells, animals and humans is a key technology that delivers biomolecules without side effects caused by excessive doses. 3D printing technologies and D. D. Ss have been assembled successfully, so new possibilities for improved tissue regeneration have been suggested. If the interaction between cells and scaffold system with biomolecules can be understood and controlled, and if an optimal 3D tissue regenerating environment is realized, 3D printing technologies will become an important aspect of tissue engineering research in the near future. 3D Printing promises to produce complex biomedical devices according to computer design using patient-specific anatomical data. Since its initial use as pre-surgical visualization models and tooling molds, 3D Printing has slowly evolved to create one-of-a-kind devices, implants, scaffolds for tissue engineering, diagnostic platforms, and drug delivery systems. Fuelled by the recent explosion in public interest and access to affordable printers, there is renewed interest to combine stem cells with custom 3D scaffolds for personalized regenerative medicine. Before 3D Printing can be used routinely for the regeneration of complex tissues (e.g. bone, cartilage, muscles, vessels, nerves in the craniomaxillofacial complex), and complex organs with intricate 3D microarchitecture (e.g. liver, lymphoid organs), several technological limitations must be addressed. Until recently, tablet designs had been restricted to the relatively small number of shapes that are easily achievable using traditional manufacturing methods. As 3D printing capabilities develop further, safety and regulatory concerns are addressed and the cost of the technology falls, contract manufacturers and pharmaceutical companies that experiment with these 3D printing innovations are likely to gain a competitive edge. This review compose the basics, types & techniques used, advantages and disadvantages of 3D printing

Patient-specific treatment allocation for carotid artery disease

2009 ◽  
Vol 1 (1) ◽  
pp. 41-49
Author(s):  
Marc Bosiers ◽  
Koen Deloose ◽  
Jurgen Verbist ◽  
Patrick Peeters
Keyword(s):  
Carotid Artery ◽  
Carotid Artery Disease ◽  
Specific Treatment ◽  
Patient Specific ◽  
Treatment Allocation ◽  
Artery Disease

scholarly journals Determinants of Cerebrovascular Reserve in Patients with Significant Carotid Stenosis

2020 ◽  
Author(s):  
Joseph P Archie
Keyword(s):  
Blood Flow ◽  
Cerebral Blood Flow ◽  
Carotid Artery ◽  
Carotid Stenosis ◽  
Vascular Resistance ◽  
Cerebral Perfusion ◽  
Perfusion Pressure ◽  
Systemic Arterial Pressure ◽  
Patient Specific ◽  
Flow Reserve

AbstractIntroductionIn patients with 70% to 99% diameter carotid artery stenosis cerebral blood flow reserve may be protective of future ischemic cerebral events. Reserve cerebral blood flow is created by brain auto-regulation. Both cerebral blood flow reserve and cerebrovascular reactivity can be measured non-invasively. However, the factors and variables that determine the availability and magnitude and of reserve blood flow remain poorly understood. The availability of reserve cerebral blood flow is a predictor of stroke risk. The aim of this study is to employ a hemodynamic model to predict the variables and functional relationships that determine cerebral blood flow reserve in patients with significant carotid stenosis.MethodsA basic one-dimensional, three-unit (carotid, collateral and brain) energy conservation fluid mechanics blood flow model is employed. It has two distinct but adjacent blood flow components with normal cerebral blood flow at the interface. In the brain auto-regulated blood flow component cerebral blood flow is maintained normal by reserve flow. In the brain pressure dependent blood flow component cerebral blood flow is below normal because cerebral perfusion pressure is below the lower threshold value for auto-regulation. Patient specific values of collateral vascular resistance are determined from a model solution using clinically measured systemic and carotid arterial stump pressures. Collateral vascular resistance curves illustrate the model solutions for reserve and actual cerebral blood flow as a function of percent diameter carotid artery stenosis and mean systemic arterial pressure. The threshold cerebral perfusion pressure value for auto-regulation is assumed to be 50 mmHg. Normal auto-regulated regional cerebral blood flow is assumed to be 50 ml/min/100g. Cerebral blood flow and reserve blood flow solutions are given for systemic arterial pressures of 80, 90, 100, 110 and 120 mmHg and for three patient specific collateral vascular resistance values, Rw = 1.0 (mean patient value), Rw = 0.5 (lower 1 SD) and Rd = 3.0 (upper 1 SD).ResultsReserve cerebral blood flow is only available when a patients cerebral perfusion pressure is in the normal auto-regulatory range. Both actual and reserve cerebral blood flows are primarily from the carotid circulation when carotid stenosis is less than 60% diameter. Between 60% and 75% stenosis the remaining carotid blood flow reserve is utilized and at higher degrees of stenosis all reserve flow is from the collateral circulation. The primary independent variables that determine actual and reserve cerebral blood flow are mean systemic arterial pressure, degree of carotid stenosis and patient specific collateral vascular resistance. Approximate 16% of patients have collateral vascular resistance greater than 5.0 and are predicted to be at high risk of cerebral ischemia or infarction with progression to severe carotid stenosis or occlusion. The approximate 50% of patients with a collateral vascular resistance less than 1.0 are predicted to have adequate cerebral blood flow with progression to carotid occlusion, and most maintain some reserve. Clinically measured values of cerebral blood flow reserve or cerebrovascular reactivity are predicted to be unreliable without consideration of systemic arterial pressure and degree of carotid stenosis. Reserve cerebral blood flow values measured in patients with only moderate 60% to 70% carotid stenosis are in general too high and variable to be of clinical value, but are most reliable when measured near 80% diameter stenosis and considered as percent of the maximum reserve blood flow. Patient specific measured reserve blood flow values can be inserted into the model to calculate the collateral vascular resistance.ConclusionsPredicting cerebral blood flow reserve in patients with significant carotid stenosis is complex and multifactorial. A simple cerebrovascular model predicts that patient specific collateral vascular resistance is an excellent predictor of reserve cerebral blood flow in patients with significant carotid stenosis. Cerebral blood flow reserve measurements are of limited value without accounting for systemic pressure and actual percent carotid stenosis. Asymptomatic patients with severe carotid artery stenosis and a collateral vascular resistance greater than 1.0 are at increased risk of cerebral ischemia and may benefit from carotid endarterectomy.

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