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Fidvi S, Holder J, Li H, Parnes GJ, Shamir SB, Wake N. Advanced 3D Visualization and 3D Printing in Radiology. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2023; 1406:103-138. [PMID: 37016113 DOI: 10.1007/978-3-031-26462-7_6] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/06/2023]
Abstract
Since the discovery of X-rays in 1895, medical imaging systems have played a crucial role in medicine by permitting the visualization of internal structures and understanding the function of organ systems. Traditional imaging modalities including Computed Tomography (CT), Magnetic Resonance Imaging (MRI) and Ultrasound (US) present fixed two-dimensional (2D) images which are difficult to conceptualize complex anatomy. Advanced volumetric medical imaging allows for three-dimensional (3D) image post-processing and image segmentation to be performed, enabling the creation of 3D volume renderings and enhanced visualization of pertinent anatomic structures in 3D. Furthermore, 3D imaging is used to generate 3D printed models and extended reality (augmented reality and virtual reality) models. A 3D image translates medical imaging information into a visual story rendering complex data and abstract ideas into an easily understood and tangible concept. Clinicians use 3D models to comprehend complex anatomical structures and to plan and guide surgical interventions more precisely. This chapter will review the volumetric radiological techniques that are commonly utilized for advanced 3D visualization. It will also provide examples of 3D printing and extended reality technology applications in radiology and describe the positive impact of advanced radiological image visualization on patient care.
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Affiliation(s)
- Shabnam Fidvi
- Department of Radiology, Montefiore Medical Center, Bronx, NY, USA.
| | - Justin Holder
- Department of Radiology, Montefiore Medical Center, Bronx, NY, USA
| | - Hong Li
- Department of Radiology, Jacobi Medical Center, Bronx, NY, USA
| | | | | | - Nicole Wake
- GE Healthcare, Aurora, OH, USA
- Center for Advanced Imaging Innovation and Research, NYU Langone Health, New York, NY, USA
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Sommer KN, Bhurwani MMS, Iyer V, Ionita CN. Comparison of fluid dynamics changes due to physical activity in 3D printed patient specific coronary phantoms with the Windkessel equivalent model of coronary flow. 3D Print Med 2022; 8:10. [PMID: 35389117 PMCID: PMC8988414 DOI: 10.1186/s41205-022-00138-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 03/29/2022] [Indexed: 11/11/2022] Open
Abstract
Background 3D printing (3DP) used to replicate the geometry of normal and abnormal vascular pathologies has been demonstrated in many publications; however, reproduction of hemodynamic changes due to physical activities, such as rest versus moderate exercise, need to be investigated. We developed a new design for patient specific coronary phantoms, which allow adjustable physiological variables such as coronary distal resistance and coronary compliance in patients with coronary artery disease. The new design was tested in precise benchtop experiments and compared with a theoretical Windkessel electrical circuit equivalent, that models coronary flow and pressure using arterial resistance and compliance. Methods Five phantoms from patients who underwent clinically indicated elective invasive coronary angiography were built from CCTA scans using multi-material 3D printing. Each phantom was used in a controlled flow system where patient specific flow conditions were simulated by a programmable cardiac pump. To simulate the arteriole and capillary beds flow resistance and the compliance for various physical activities, we designed a three-chamber outlet system which controls the outflow dynamics of each coronary tree. Benchtop pressure measurements were recorded using sensors embedded in each of the main coronary arteries. Using the Windkessel model, patient specific flow equivalent electrical circuit models were designed for each coronary tree branch, and flow in each artery was determined for known inflow conditions. Local flow resistances were calculated through Poiseuille’s Law derived from the radii and lengths of the coronary arteries using CT angiography based multi-planar reconstructions. The coronary stenosis flow rates from the benchtop and the electrical models were compared to the localized flow rates calculated from invasive pressure measurements recorded in the angio-suites. Results The average Pearson correlations of the localized flow rates at the location of the stenosis between each of the models (Benchtop/Electrical, Benchtop/Angio, Electrical/Angio) are 0.970, 0.981, and 0.958 respectively. Conclusions 3D printed coronary phantoms can be used to replicate the human arterial anatomy as well as blood flow conditions. It displays high levels of correlation when compared to hemodynamics calculated in electrically-equivalent coronary Windkessel models as well as invasive angio-suite pressure measurements.
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Affiliation(s)
- Kelsey N Sommer
- Department of Biomedical Engineering, University at Buffalo, Buffalo, NY, USA. .,Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY, USA. .,QAS.AI Incorporated, Buffalo, NY, 14203, USA.
| | - Mohammad Mahdi Shiraz Bhurwani
- Department of Biomedical Engineering, University at Buffalo, Buffalo, NY, USA.,Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY, USA
| | - Vijay Iyer
- University at Buffalo Cardiology, University at Buffalo Jacobs School of Medicine, Buffalo, NY, USA
| | - Ciprian N Ionita
- Department of Biomedical Engineering, University at Buffalo, Buffalo, NY, USA.,Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY, USA.,QAS.AI Incorporated, Buffalo, NY, 14203, USA
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Laughlin ME, Stephens SE, Hestekin JA, Jensen MO. Development of Custom Wall-Less Cardiovascular Flow Phantoms with Tissue-Mimicking Gel. Cardiovasc Eng Technol 2022; 13:1-13. [PMID: 34080171 PMCID: PMC8888498 DOI: 10.1007/s13239-021-00546-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 05/12/2021] [Indexed: 10/26/2022]
Abstract
PURPOSE Flow phantoms are used in experimental settings to aid in the simulation of blood flow. Custom geometries are available, but current phantom materials present issues with degradability and/or mimicking the mechanical properties of human tissue. In this study, a method of fabricating custom wall-less flow phantoms from a tissue-mimicking gel using 3D printed inserts is developed. METHODS A 3D blood vessel geometry example of a bifurcated artery model was 3D printed in polyvinyl alcohol, embedded in tissue-mimicking gel, and subsequently dissolved to create a phantom. Uniaxial compression testing was performed to determine the Young's moduli of the five gel types. Angle-independent, ultrasound-based imaging modalities, Vector Flow Imaging (VFI) and Blood Speckle Imaging (BSI), were utilized for flow visualization of a straight channel phantom. RESULTS A wall-less phantom of the bifurcated artery was fabricated with minimal bubbles and continuous flow demonstrated. Additionally, flow was visualized through a straight channel phantom by VFI and BSI. The available gel types are suitable for mimicking a variety of tissue types, including cardiac tissue and blood vessels. CONCLUSION Custom, tissue-mimicking flow phantoms can be fabricated using the developed methodology and have potential for use in a variety of applications, including ultrasound-based imaging methods. This is the first reported use of BSI with an in vitro flow phantom.
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Affiliation(s)
- Megan E Laughlin
- Department of Biomedical Engineering, University of Arkansas, John A. White Jr. Engineering Hall, 790 W. Dickson St. #120, Fayetteville, AR, 72701, USA
| | - Sam E Stephens
- Department of Biomedical Engineering, University of Arkansas, John A. White Jr. Engineering Hall, 790 W. Dickson St. #120, Fayetteville, AR, 72701, USA
| | - Jamie A Hestekin
- Department of Chemical Engineering, University of Arkansas, 3202 Bell Engineering Center, Fayetteville, AR, 72701, USA
| | - Morten O Jensen
- Department of Biomedical Engineering, University of Arkansas, John A. White Jr. Engineering Hall, 790 W. Dickson St. #120, Fayetteville, AR, 72701, USA.
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Williams KA, Shields A, Nagesh SVS, Bednarek DR, Rudin S, Ionita CN. 2D vessel contrast dilution gradient (CDG) analysis using 1000 fps high speed angiography (HSA) for velocity distribution estimation. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2022; 12031:1203107. [PMID: 35982769 PMCID: PMC9385177 DOI: 10.1117/12.2611790] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
PURPOSE Contrast dilution gradient (CDG) analysis is a technique used to extract velocimetric 2D information from digitally subtracted angiographic (DSA) acquisitions. This information may then be used by clinicians to quantitatively assess the effects of endovascular treatment on flow conditions surrounding pathologies of interest. The method assumes negligible diffusion conditions, making 1000 fps high speed angiography (HSA), in which diffusion between 1 ms frames may be neglected, a strong candidate for velocimetric analysis using CDG. Previous studies have demonstrated the success of CDG analysis in obtaining velocimetric one-dimensional data at the arterial centerline of simple vasculature. This study seeks to resolve velocity distributions across the entire vessel using 2D-CDG analysis with HSA acquisitions. MATERIALS AND METHODS HSA acquisitions for this study were obtained in vitro with a benchtop flow loop at 1000 fps using the XC-Actaeon (Direct Conversion Inc.) photon counting detector. 2D-CDG analyses were compared with computational fluid dynamics (CFD) via automatic co-registration of the results from each velocimetry method. This comparison was performed using mean absolute error between pixel values in each method (after temporal averaging). RESULTS CDG velocity magnitudes were slightly under approximated relative to CFD results (mean velocity: 27 cm/s, mean absolute error: 4.3 cm/s) as a result of incomplete contrast filling. Relative 2D spatial velocity distributions in CDG analysis agreed well with CFD distributions qualitatively. CONCLUSIONS CDG may be used to obtain velocity distributions in and surrounding vascular pathologies provided diffusion is negligible relative to convection in the flow, given a continuous gradient of contrast.
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Affiliation(s)
- Kyle A Williams
- Department of Biomedical Engineering, University at Buffalo, Buffalo, NY 14228
- Canon Stroke and Vascular Research Center, Buffalo, NY 14208
| | - Allison Shields
- Canon Stroke and Vascular Research Center, Buffalo, NY 14208
- Department of Medical Physics, University at Buffalo, Buffalo, NY 14228
- University at Buffalo Neurosurgery, University at Buffalo Jacobs School of Medicine, Buffalo, NY 14228
| | - S V Setlur Nagesh
- Canon Stroke and Vascular Research Center, Buffalo, NY 14208
- University at Buffalo Neurosurgery, University at Buffalo Jacobs School of Medicine, Buffalo, NY 14228
| | - Daniel R Bednarek
- Canon Stroke and Vascular Research Center, Buffalo, NY 14208
- Department of Medical Physics, University at Buffalo, Buffalo, NY 14228
- University at Buffalo Neurosurgery, University at Buffalo Jacobs School of Medicine, Buffalo, NY 14228
| | - Stephen Rudin
- Department of Biomedical Engineering, University at Buffalo, Buffalo, NY 14228
- Canon Stroke and Vascular Research Center, Buffalo, NY 14208
- Department of Medical Physics, University at Buffalo, Buffalo, NY 14228
- University at Buffalo Neurosurgery, University at Buffalo Jacobs School of Medicine, Buffalo, NY 14228
| | - Ciprian N Ionita
- Department of Biomedical Engineering, University at Buffalo, Buffalo, NY 14228
- Canon Stroke and Vascular Research Center, Buffalo, NY 14208
- Department of Medical Physics, University at Buffalo, Buffalo, NY 14228
- University at Buffalo Neurosurgery, University at Buffalo Jacobs School of Medicine, Buffalo, NY 14228
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Sommer KN, Bhurwani MMS, Tutino V, Siddiqui A, Davies J, Snyder K, Levy E, Mokin M, Ionita CN. Use of patient specific 3D printed neurovascular phantoms to simulate mechanical thrombectomy. 3D Print Med 2021; 7:32. [PMID: 34568987 PMCID: PMC8474770 DOI: 10.1186/s41205-021-00122-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 09/11/2021] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND The ability of the patient specific 3D printed neurovascular phantoms to accurately replicate the anatomy and hemodynamics of the chronic neurovascular diseases has been demonstrated by many studies. Acute occurrences, however, may still require further development and investigation and therefore we studied acute ischemic stroke (AIS). The efficacy of endovascular procedures such as mechanical thrombectomy (MT) for the treatment of large vessel occlusion (LVO), can be improved by testing the performance of thrombectomy devices and techniques using patient specific 3D printed neurovascular models. METHODS 3D printed phantoms were connected to a flow loop with physiologically relevant flow conditions, including input flow rate and fluid temperature. A simulated blood clot was introduced into the model and placed in the proximal Middle Cerebral Artery (MCA) region. Clot location, composition, length, and arterial angulation were varied and MTs were simulated using stent retrievers. Device placement relative to the clot and the outcome of the thrombectomy were recorded for each situation. Digital subtraction angiograms (DSA) were captured before and after LVO simulation. Recanalization outcome was evaluated using DSA as either 'no recanalization' or 'recanalization'. Forty-two 3DP neurovascular phantom benchtop experiments were performed. RESULTS Clot angulation within the MCA region had the most significant impact on the MT outcome, with a p-value of 0.016. Other factors such as clot location, clot composition, and clot length correlated weakly with the MT outcome. CONCLUSIONS This project allowed us to gain knowledge of how such characteristics influence thrombectomy success and can be used in making clinical decisions when planning the procedure and selecting specific thrombectomy tools and approaches.
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Affiliation(s)
- Kelsey N. Sommer
- grid.273335.30000 0004 1936 9887Department of Biomedical Engineering, University at Buffalo, Buffalo, NY 14228 USA ,grid.273335.30000 0004 1936 9887Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY 14208 USA
| | - Mohammad Mahdi Shiraz Bhurwani
- grid.273335.30000 0004 1936 9887Department of Biomedical Engineering, University at Buffalo, Buffalo, NY 14228 USA ,grid.273335.30000 0004 1936 9887Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY 14208 USA
| | - Vincent Tutino
- grid.273335.30000 0004 1936 9887Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY 14208 USA ,grid.273335.30000 0004 1936 9887Department of Neurosurgery, University at Buffalo, Buffalo, NY 14208 USA ,grid.273335.30000 0004 1936 9887Department of Pathology and Anatomical Sciences, University at Buffalo, Buffalo, 14208 USA
| | - Adnan Siddiqui
- grid.273335.30000 0004 1936 9887Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY 14208 USA ,grid.273335.30000 0004 1936 9887Department of Neurosurgery, University at Buffalo, Buffalo, NY 14208 USA
| | - Jason Davies
- grid.273335.30000 0004 1936 9887Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY 14208 USA ,grid.273335.30000 0004 1936 9887Department of Neurosurgery, University at Buffalo, Buffalo, NY 14208 USA ,grid.273335.30000 0004 1936 9887Department of Biomedical Informatics, University at Buffalo, Buffalo, 14208 USA
| | - Kenneth Snyder
- grid.273335.30000 0004 1936 9887Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY 14208 USA ,grid.273335.30000 0004 1936 9887Department of Neurosurgery, University at Buffalo, Buffalo, NY 14208 USA
| | - Elad Levy
- grid.273335.30000 0004 1936 9887Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY 14208 USA ,grid.273335.30000 0004 1936 9887Department of Neurosurgery, University at Buffalo, Buffalo, NY 14208 USA
| | - Maxim Mokin
- grid.170693.a0000 0001 2353 285XDepartment of Neurosurgery and Brain Repair, University of South Florida, Tampa, FL 33620 USA
| | - Ciprian N. Ionita
- grid.273335.30000 0004 1936 9887Department of Biomedical Engineering, University at Buffalo, Buffalo, NY 14228 USA ,grid.273335.30000 0004 1936 9887Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY 14208 USA ,grid.273335.30000 0004 1936 9887Department of Neurosurgery, University at Buffalo, Buffalo, NY 14208 USA
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Gharleghi R, Dessalles CA, Lal R, McCraith S, Sarathy K, Jepson N, Otton J, Barakat AI, Beier S. 3D Printing for Cardiovascular Applications: From End-to-End Processes to Emerging Developments. Ann Biomed Eng 2021; 49:1598-1618. [PMID: 34002286 PMCID: PMC8648709 DOI: 10.1007/s10439-021-02784-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2020] [Accepted: 04/24/2021] [Indexed: 12/16/2022]
Abstract
3D printing as a means of fabrication has seen increasing applications in medicine in the last decade, becoming invaluable for cardiovascular applications. This rapidly developing technology has had a significant impact on cardiovascular research, its clinical translation and education. It has expanded our understanding of the cardiovascular system resulting in better devices, tools and consequently improved patient outcomes. This review discusses the latest developments and future directions of generating medical replicas ('phantoms') for use in the cardiovascular field, detailing the end-to-end process from medical imaging to capture structures of interest, to production and use of 3D printed models. We provide comparisons of available imaging modalities and overview of segmentation and post-processing techniques to process images for printing, detailed exploration of latest 3D printing methods and materials, and a comprehensive, up-to-date review of milestone applications and their impact within the cardiovascular domain across research, clinical use and education. We then provide an in-depth exploration of future technologies and innovations around these methods, capturing opportunities and emerging directions across increasingly realistic representations, bioprinting and tissue engineering, and complementary virtual and mixed reality solutions. The next generation of 3D printing techniques allow patient-specific models that are increasingly realistic, replicating properties, anatomy and function.
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Affiliation(s)
- Ramtin Gharleghi
- Faculty of Engineering, School of Mechanical and Manufacturing, UNSW, Sydney, Australia
| | | | - Ronil Lal
- Faculty of Engineering, School of Mechanical and Manufacturing, UNSW, Sydney, Australia
| | - Sinead McCraith
- Faculty of Engineering, School of Mechanical and Manufacturing, UNSW, Sydney, Australia
| | | | - Nigel Jepson
- Prince of Wales Hospital, Sydney, Australia
- Prince of Wales Clinical School of Medicine, UNSW, Sydney, Australia
| | - James Otton
- Department of Cardiology, Liverpool Hospital, Sydney, Australia
| | | | - Susann Beier
- Faculty of Engineering, School of Mechanical and Manufacturing, UNSW, Sydney, Australia.
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Paccione E, Ionita CN. Challenges in hemodynamics assessment in complex neurovascular geometries using computational fluid dynamics and benchtop flow simulation in 3D printed patient specific phantoms. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2021; 11600. [PMID: 33814673 DOI: 10.1117/12.2582169] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Purpose Complex hemodynamics assessments, as those related to carotid stenosis, are not always easily straightforward due to multifaceted challenges presented by the collateral flow in the Circle of Willis (CoW) and brain flow autoregulation. Advanced computational and benchtop methods to investigate hemodynamics aspects related to such complex flows are often used, however both have limitations and could lead to results which may diverge. In this study we investigated these aspects by performing correlated computational fluid dynamics (CFD) simulations and benchtop experiments in patient specific 3D printed phantoms. Materials and Methods To investigate the flow in patients with carotid stenosis, we built two patient specific phantoms which contained the arterial lesion of interest, all main arteries leading to the brain, the CoW and main arteries branching from it. Each phantom was connected to a generic aortic arch. A programmable pump was connected and flow parameters were measured proximal and distal to the lesion and the contralateral arteries. The patient 3D geometry was used to perform a set of CFD simulations where inflow boundary conditions matched the experimental ones. Flow conditions were recorded at the same locations as the experimental setup. Further exploration into the translation from experimental to CFD was also performed by customizing vascular segmentation and physically manipulating arterial compliance properties. Results We initially observed significant differences between the CFD recordings and the experimental setup. Most of the differences were due to changes in phantom geometry when subjected to physiological pressures and simplistic outflow boundary conditions in the CFD simulations which do not account for pulsatility and nonlinear phenomena. Further work confirms the need for dynamic mesh behavior within CFD simulations attempting to computationally mimic 3D-printed benchtop experiments. Additionally, CFD simulation may benefit from considering geometry specific to a 3D-printed vascular phantom.
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Affiliation(s)
- Eric Paccione
- University Dept. of Biomedical Engineering, University at Buffalo, Buffalo, NY
| | - Ciprian N Ionita
- University Dept. of Biomedical Engineering, University at Buffalo, Buffalo, NY.,Canon Stroke and Vascular Research Center, Buffalo, NY
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Sommer KN, Bhurwani MMS, Mokin M, Ionita CN. Evaluation of challenges and limitations of mechanical thrombectomy using 3D printed neurovascular phantoms. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2021; 11601:116010B. [PMID: 34334874 PMCID: PMC8323489 DOI: 10.1117/12.2580962] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
The mechanical thrombectomy (MT) efficacy, for large vessel occlusion (LVO) treatment in patients with stroke, could be improved if better teaching and practicing surgical tools were available. We propose a novel approach that uses 3D printing (3DP) to generate patient anatomical vascular variants for simulation of diverse clinical scenarios of LVO treated with MT. 3DP phantoms were connected to a flow loop with physiologically relevant flow conditions, including input flow rate and fluid temperature. A simulated blood clot was introduced into the model and placed in the Middle Cerebral Artery region. Clot location, composition (hard or soft clot), length, and arterial angulation were varied and MTs were simulated using stent retrievers. Device placement relative to the clot and the outcome of the thrombectomy were recorded for each situation. Angiograms were captured before and after LVO simulation and after the MT. Recanalization outcome was evaluated using the Thrombolysis in Cerebral Infarction (TICI) scale. Forty-two 3DP neurovascular phantom benchtop experiments were performed. Clot mechanical properties, hard versus soft, had the highest impact on the MT outcome, with 18/42 proving to be successful with full or partial clot retrieval. Other factors such as device manufacturer and the tortuosity of the 3DP model correlated weakly with the MT outcome. We demonstrated that 3DP can become a comprehensive tool for teaching and practicing various surgical procedures for MT in LVO patients. This platform can help vascular surgeons understand the endovascular devices limitations and patient vascular geometry challenges, to allow surgical approach optimization.
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Affiliation(s)
- Kelsey N Sommer
- Department of Biomedical Engineering, University at Buffalo NY 14228,Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo NY 14208
| | - Mohammad Mahdi Shiraz Bhurwani
- Department of Biomedical Engineering, University at Buffalo NY 14228,Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo NY 14208
| | - Maxim Mokin
- Department of Neurosurgery, University of South Florida, Tampa, Florida 33620
| | - Ciprian N Ionita
- Department of Biomedical Engineering, University at Buffalo NY 14228,Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo NY 14208
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Ali A, Ballard DH, Althobaity W, Christensen A, Geritano M, Ho M, Liacouras P, Matsumoto J, Morris J, Ryan J, Shorti R, Wake N, Rybicki FJ, Sheikh A. Clinical situations for which 3D printing is considered an appropriate representation or extension of data contained in a medical imaging examination: adult cardiac conditions. 3D Print Med 2020; 6:24. [PMID: 32965536 PMCID: PMC7510265 DOI: 10.1186/s41205-020-00078-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Accepted: 09/04/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Medical 3D printing as a component of care for adults with cardiovascular diseases has expanded dramatically. A writing group composed of the Radiological Society of North America (RSNA) Special Interest Group on 3D Printing (SIG) provides appropriateness criteria for adult cardiac 3D printing indications. METHODS A structured literature search was conducted to identify all relevant articles using 3D printing technology associated with a number of adult cardiac indications, physiologic, and pathologic processes. Each study was vetted by the authors and graded according to published guidelines. RESULTS Evidence-based appropriateness guidelines are provided for the following areas in adult cardiac care; cardiac fundamentals, perioperative and intraoperative care, coronary disease and ischemic heart disease, complications of myocardial infarction, valve disease, cardiac arrhythmias, cardiac neoplasm, cardiac transplant and mechanical circulatory support, heart failure, preventative cardiology, cardiac and pericardial disease and cardiac trauma. CONCLUSIONS Adoption of common clinical standards regarding appropriate use, information and material management, and quality control are needed to ensure the greatest possible clinical benefit from 3D printing. This consensus guideline document, created by the members of the RSNA 3D printing Special Interest Group, will provide a reference for clinical standards of 3D printing for adult cardiac indications.
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Affiliation(s)
- Arafat Ali
- Department of Radiology, University of Cincinnati Medical Center, Cincinnati, OH, USA.
| | - David H Ballard
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Waleed Althobaity
- King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
| | - Andy Christensen
- Department of Radiology and The Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON, Canada
| | | | - Michelle Ho
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - Peter Liacouras
- 3D Medical Applications Center, Walter Reed National Military Medical Center, Washington, DC, USA
| | - Jane Matsumoto
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | - Justin Ryan
- Rady Children's Hospital, San Diego, CA, USA
| | - Rami Shorti
- Intermountain Healthcare, South Jordan, UT, USA
| | - Nicole Wake
- Department of Radiology, Montefiore Medical Center, Bronx, NY, USA
| | - Frank J Rybicki
- Department of Radiology, University of Cincinnati Medical Center, Cincinnati, OH, USA
| | - Adnan Sheikh
- Department of Radiology and The Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON, Canada
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Sommer KN, Iyer V, Kumamaru KK, Rava RA, Ionita CN. Method to simulate distal flow resistance in coronary arteries in 3D printed patient specific coronary models. 3D Print Med 2020; 6:19. [PMID: 32761497 PMCID: PMC7410153 DOI: 10.1186/s41205-020-00072-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Accepted: 07/24/2020] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Three-dimensional printing (3DP) offers a unique opportunity to build flexible vascular patient-specific coronary models for device testing, treatment planning, and physiological simulations. By optimizing the 3DP design to replicate the geometrical and mechanical properties of healthy and diseased arteries, we may improve the relevance of using such models to simulate the hemodynamics of coronary disease. We developed a method to build 3DP patient specific coronary phantoms, which maintain a significant part of the coronary tree, while preserving geometrical accuracy of the atherosclerotic plaques and allows for an adjustable hydraulic resistance. METHODS Coronary computed tomography angiography (CCTA) data was used within Vitrea (Vital Images, Minnetonka, MN) cardiac analysis application for automatic segmentation of the aortic root, Left Anterior Descending (LAD), Left Circumflex (LCX), Right Coronary Artery (RCA), and calcifications. Stereolithographic (STL) files of the vasculature and calcium were imported into Autodesk Meshmixer for 3D model optimization. A base with three chambers was built and interfaced with the phantom to allow fluid collection and independent distal resistance adjustment of the RCA, LAD and LCX and branching arteries. For the 3DP we used Agilus for the arterial wall, VeroClear for the base and a Vero blend for the calcifications, respectively. Each chamber outlet allowed interface with catheters of varying lengths and diameters for simulation of hydraulic resistance of both normal and hyperemic coronary flow conditions. To demonstrate the manufacturing approach appropriateness, models were tested in flow experiments. RESULTS Models were used successfully in flow experiments to simulate normal and hyperemic flow conditions. The inherent mean resistance of the chamber for the LAD, LCX, and RCA, were 1671, 1820, and 591 (dynes ∙ sec/ cm5), respectively. This was negligible when compared with estimates in humans, with the chamber resistance equating to 0.65-5.86%, 1.23-6.86%, and 0.05-1.67% of the coronary resistance for the LAD, LCX, and RCA, respectively at varying flow rates and activity states. Therefore, the chamber served as a means to simulate the compliance of the distal coronary trees and to allow facile coupling with a set of known resistance catheters to simulate various physical activity levels. CONCLUSIONS We have developed a method to create complex 3D printed patient specific coronary models derived from CCTA, which allow adjustable distal capillary bed resistances. This manufacturing approach permits comprehensive coronary model development which may be used for physiologically relevant flow simulations.
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Affiliation(s)
- Kelsey N Sommer
- Department of Biomedical Engineering, University at Buffalo, Buffalo, NY, USA
- Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY, USA
| | - Vijay Iyer
- University at Buffalo Cardiology, University at Buffalo Jacobs School of Medicine, Buffalo, NY, USA
| | | | - Ryan A Rava
- Department of Biomedical Engineering, University at Buffalo, Buffalo, NY, USA
- Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY, USA
| | - Ciprian N Ionita
- Department of Biomedical Engineering, University at Buffalo, Buffalo, NY, USA.
- Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY, USA.
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Podgorsak AR, Sommer KN, Reddy A, Iyer V, Wilson MF, Rybicki FJ, Mitsouras D, Sharma U, Fujimoto S, Kumamaru KK, Angel E, Ionita CN. Initial evaluation of a convolutional neural network used for noninvasive assessment of coronary artery disease severity from coronary computed tomography angiography data. Med Phys 2020; 47:3996-4004. [DOI: 10.1002/mp.14339] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 06/09/2020] [Accepted: 06/10/2020] [Indexed: 12/13/2022] Open
Affiliation(s)
- Alexander R. Podgorsak
- From the Canon Stroke and Vascular Research Center 875 Ellicott Street Buffalo NY 14222USA
| | - Kelsey N. Sommer
- From the Canon Stroke and Vascular Research Center 875 Ellicott Street Buffalo NY 14222USA
| | - Abhinay Reddy
- From the Canon Stroke and Vascular Research Center 875 Ellicott Street Buffalo NY 14222USA
| | - Vijay Iyer
- From the Canon Stroke and Vascular Research Center 875 Ellicott Street Buffalo NY 14222USA
| | - Michael F. Wilson
- From the Canon Stroke and Vascular Research Center 875 Ellicott Street Buffalo NY 14222USA
| | - Frank J. Rybicki
- Department of Radiology University of Cincinnati 234 Goodman Street Cincinnati OH USA
| | - Dimitrios Mitsouras
- San Francisco Department of Radiology and Biomedical Imaging University of California 505 Parnassus Avenue San Francisco CA 94143USA
| | - Umesh Sharma
- From the Canon Stroke and Vascular Research Center 875 Ellicott Street Buffalo NY 14222USA
| | - Shinchiro Fujimoto
- Department of Cardiovascular Medicine Juntendo University 3‐1‐3 Hongo, Bunkyo‐ku Tokyo Japan
| | - Kanako K. Kumamaru
- Department of Radiology Juntendo University 3‐1‐3 Hongo, Bunkyo‐ku Tokyo Japan
| | - Erin Angel
- Canon Medical Systems USA, Inc. 2441 Michelle Drive Tustin CA 92780USA
| | - Ciprian N. Ionita
- From the Canon Stroke and Vascular Research Center 875 Ellicott Street Buffalo NY 14222USA
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12
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Sommer KN, Shepard LM, Mitsouras D, Iyer V, Angel E, Wilson MF, Rybicki FJ, Kumamaru KK, Sharma UC, Reddy A, Fujimoto S, Ionita CN. Patient-specific 3D-printed coronary models based on coronary computed tomography angiography volumes to investigate flow conditions in coronary artery disease. Biomed Phys Eng Express 2020; 6:045007. [PMID: 33444268 DOI: 10.1088/2057-1976/ab8f6e] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
BACKGROUND 3D printed patient-specific coronary models have the ability to enable repeatable benchtop experiments under controlled blood flow conditions. This approach can be applied to CT-derived patient geometries to emulate coronary flow and related parameters such as Fractional Flow Reserve (FFR). METHODS This study uses 3D printing to compare such benchtop FFR results with a non-invasive CT-FFR research software algorithm and catheter based invasive FFR (I-FFR) measurements. Fifty-two patients with a clinical indication for I-FFR underwent a research Coronary CT Angiography (CCTA) prior to catheterization. CT images were used to measure CT-FFR and to generate patient-specific 3D printed models of the aortic root and three main coronary arteries. Each patient-specific model was connected to a programmable pulsatile pump and benchtop FFR (B-FFR) was derived from pressures measured proximal and distal to coronary stenosis using pressure transducers. B-FFR was measured for two coronary outflow rates ('normal', 250 ml min-1; and 'hyperemic', 500 ml min-1) by adjusting the model's distal coronary resistance. RESULTS Pearson correlations and ROC AUC were calculated using invasive I-FFR as reference. The Pearson correlation factor of CT-FFR and B-FFR-500 was 0.75 and 0.71, respectively. Areas under the ROCs for CT-FFR and B-FFR-500 were 0.80 (95%CI: 0.70-0.87) and 0.81 (95%CI: 0.64-0.91) respectively. CONCLUSION Benchtop flow simulations with 3D printed models provide the capability to measure pressure changes at any location in the model, for ultimately emulating the FFR at several simulated physiological blood flow conditions. CLINICAL TRIAL REGISTRATION https://clinicaltrials.gov/show/NCT03149042.
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Affiliation(s)
- Kelsey N Sommer
- Department of Biomedical Engineering, University at Buffalo, Buffalo, NY 14228, United States of America. Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY, United States of America
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13
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Thaker R, Araujo-Gutierrez R, Marcos-Abdala HG, Agrawal T, Fida N, Kassi M. Innovative Modeling Techniques and 3D Printing in Patients with Left Ventricular Assist Devices: A Bridge from Bench to Clinical Practice. J Clin Med 2019; 8:E635. [PMID: 31075841 PMCID: PMC6572374 DOI: 10.3390/jcm8050635] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Revised: 04/24/2019] [Accepted: 05/01/2019] [Indexed: 02/07/2023] Open
Abstract
Left ventricular assist devices (LVAD) cause altered flow dynamics that may result in complications such as stroke, pump thrombosis, bleeding, or aortic regurgitation. Understanding altered flow dynamics is important in order to develop more efficient and durable pump configurations. In patients with LVAD, hemodynamic assessment is limited to imaging techniques such as echocardiography which precludes detailed assessment of fluid dynamics. In this review article, we present some innovative modeling techniques that are often used in device development or for research purposes, but have not been utilized clinically. Computational fluid dynamic (CFD) modeling is based on computer simulations and particle image velocimetry (PIV) employs ex vivo models that helps study fluid characteristics such as pressure, shear stress, and velocity. Both techniques may help elaborate our understanding of complications that occur with LVAD and could be potentially used in the future to troubleshoot LVAD-related alarms. These techniques coupled with 3D printing may also allow for patient-specific device implants, lowering the risk of complications increasing device durability.
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Affiliation(s)
- Rishi Thaker
- Touro College of Osteopathic Medicine, Middletown, New York, NY 10940, USA.
| | - Raquel Araujo-Gutierrez
- Houston Methodist DeBakey Heart & Vascular Center, Houston Methodist Hospital, Houston, TX 77030, USA.
| | - Hernan G Marcos-Abdala
- Houston Methodist DeBakey Heart & Vascular Center, Houston Methodist Hospital, Houston, TX 77030, USA.
| | - Tanushree Agrawal
- Department of Internal Medicine, Houston Methodist Hospital, Houston, TX 77030, USA.
| | - Nadia Fida
- Houston Methodist DeBakey Heart & Vascular Center, Houston Methodist Hospital, Houston, TX 77030, USA.
| | - Mahwash Kassi
- Houston Methodist DeBakey Heart & Vascular Center, Houston Methodist Hospital, Houston, TX 77030, USA.
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14
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Shepard LM, Sommer KN, Angel E, Iyer V, Wilson MF, Rybicki FJ, Mitsouras D, Molloi S, Ionita CN. Initial evaluation of three-dimensionally printed patient-specific coronary phantoms for CT-FFR software validation. J Med Imaging (Bellingham) 2019; 6:021603. [PMID: 30891468 DOI: 10.1117/1.jmi.6.2.021603] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2018] [Accepted: 02/19/2019] [Indexed: 12/17/2022] Open
Abstract
We developed three-dimensionally (3D) printed patient-specific coronary phantoms that are capable of sustaining physiological flow and pressure conditions. We assessed the accuracy of these phantoms from coronary CT acquisition, benchtop experimentation, and CT-FFR software. Five patients with coronary artery disease underwent 320-detector row coronary CT angiography (CCTA) (Aquilion ONE, Canon Medical Systems) and a catheter lab procedure to measure fractional flow reserve (FFR). The aortic root and three main coronary arteries were segmented (Vitrea, Vital Images) and 3D printed (Eden 260V, Stratasys). Phantoms were connected into a pulsatile flow loop, which replicated physiological flow and pressure gradients. Contrast was introduced and the phantoms were scanned using the same CT scanner model and CCTA protocol as used for the patients. Image data from the phantoms were input to a CT-FFR research software (Canon Medical Systems) and compared to those derived from the clinical data, along with comparisons between image measurements and benchtop FFR results. Phantom diameter measurements were within 1 mm on average compared to patient measurements. Patient and phantom CT-FFR results had an absolute mean difference of 4.34% and Pearson correlation of 0.95. We have demonstrated the capabilities of 3D printed patient-specific phantoms in a diagnostic software.
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Affiliation(s)
- Lauren M Shepard
- University at Buffalo, University Department of Biomedical Engineering, Buffalo, New York, United States.,Canon Stroke and Vascular Research Center, Buffalo, New York, United States
| | - Kelsey N Sommer
- University at Buffalo, University Department of Biomedical Engineering, Buffalo, New York, United States.,Canon Stroke and Vascular Research Center, Buffalo, New York, United States
| | - Erin Angel
- Canon Medical Systems USA, Tustin, California, United States
| | - Vijay Iyer
- University at Buffalo Medicine, Interventional Cardiology, UBMD, Buffalo, New York, United States
| | - Michael F Wilson
- University at Buffalo Medicine, Interventional Cardiology, UBMD, Buffalo, New York, United States
| | - Frank J Rybicki
- University of Ottawa, Ottawa Hospital Research Institute and the Department of Radiology, Ottawa, Canada
| | - Dimitrios Mitsouras
- University of Ottawa, Ottawa Hospital Research Institute and the Department of Radiology, Ottawa, Canada
| | - Sabee Molloi
- University of California Irvine, University Department of Radiological Sciences, Irvine, California, United States
| | - Ciprian N Ionita
- University at Buffalo, University Department of Biomedical Engineering, Buffalo, New York, United States.,Canon Stroke and Vascular Research Center, Buffalo, New York, United States.,University at Buffalo, University Department of Neurosurgery, Buffalo, New York, United States
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