Optimal B-Spline Mapping of Flow Imaging Data for Imposing Patient-Specific Velocity Profiles in Computational Hemodynamics

AbstractVirtual reality (VR) has increasingly been implemented in neurosurgical practice. A patient with an unruptured anterior communicating artery (AcoA) aneurysm was referred to our institution. Imaging data from computed tomography angiography (CTA) was used to create a patient specific 3D model of vascular and skull base anatomy, and then processed to a VR compatible environment. Minimally invasive approaches (mini-pterional, supraorbital and mini-orbitozygomatic) were simulated and assessed for adequate vascular exposure in VR. Using an eyebrow approach, a mini-orbitozygomatic approach was performed, with clip exclusion of the aneurysm from the circulation. The step-by-step process of VR planning is outlined, and the advantages and disadvantages for the neurosurgeon of this technology are reviewed.

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Main Clinical Use of Additive Manufacturing (Three-Dimensional Printing) in Finland Restricted to the Head and Neck Area in 2016–2017

Scandinavian Journal of Surgery ◽

10.1177/1457496919840958 ◽

2019 ◽

Vol 109 (2) ◽

pp. 166-173 ◽

Cited By ~ 3

Author(s):

A.B.V. Pettersson ◽

M. Salmi ◽

P. Vallittu ◽

W. Serlo ◽

J. Tuomi ◽

...

Keyword(s):

Additive Manufacturing ◽

Computer Aided Design ◽

Three Dimensional ◽

Patient Specific ◽

Future Research ◽

Imaging Data ◽

University Hospitals ◽

Three Dimensional Printing ◽

Dimensional Printing ◽

Head Area

Background and Aims: Additive manufacturing or three-dimensional printing is a novel production methodology for producing patient-specific models, medical aids, tools, and implants. However, the clinical impact of this technology is unknown. In this study, we sought to characterize the clinical adoption of medical additive manufacturing in Finland in 2016–2017. We focused on non-dental usage at university hospitals. Materials and Methods: A questionnaire containing five questions was sent by email to all operative, radiologic, and oncologic departments of all university hospitals in Finland. Respondents who reported extensive use of medical additive manufacturing were contacted with additional, personalized questions. Results: Of the 115 questionnaires sent, 58 received answers. Of the responders, 41% identified as non-users, including all general/gastrointestinal (GI) and vascular surgeons, urologists, and gynecologists; 23% identified as experimenters or previous users; and 36% identified as heavy users. Usage was concentrated around the head area by various specialties (neurosurgical, craniomaxillofacial, ear, nose and throat diseases (ENT), plastic surgery). Applications included repair of cranial vault defects and malformations, surgical oncology, trauma, and cleft palate reconstruction. Some routine usage was also reported in orthopedics. In addition to these patient-specific uses, we identified several off-the-shelf medical components that were produced by additive manufacturing, while some important patient-specific components were produced by traditional methodologies such as milling. Conclusion: During 2016–2017, medical additive manufacturing in Finland was routinely used at university hospitals for several applications in the head area. Outside of this area, usage was much less common. Future research should include all patient-specific products created by a computer-aided design/manufacture workflow from imaging data, instead of concentrating on the production methodology.

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Clinical Applications of Patient-Specific 3D Printed Models in Cardiovascular Disease: Current Status and Future Directions

Biomolecules ◽

10.3390/biom10111577 ◽

2020 ◽

Vol 10 (11) ◽

pp. 1577

Author(s):

Zhonghua Sun

Keyword(s):

Cardiovascular Disease ◽

3D Printing ◽

Current Status ◽

Patient Specific ◽

Future Research ◽

Junior Doctors ◽

Imaging Data ◽

Training Tool ◽

Complex Anatomy ◽

3D Printed

Three-dimensional (3D) printing has been increasingly used in medicine with applications in many different fields ranging from orthopaedics and tumours to cardiovascular disease. Realistic 3D models can be printed with different materials to replicate anatomical structures and pathologies with high accuracy. 3D printed models generated from medical imaging data acquired with computed tomography, magnetic resonance imaging or ultrasound augment the understanding of complex anatomy and pathology, assist preoperative planning and simulate surgical or interventional procedures to achieve precision medicine for improvement of treatment outcomes, train young or junior doctors to gain their confidence in patient management and provide medical education to medical students or healthcare professionals as an effective training tool. This article provides an overview of patient-specific 3D printed models with a focus on the applications in cardiovascular disease including: 3D printed models in congenital heart disease, coronary artery disease, pulmonary embolism, aortic aneurysm and aortic dissection, and aortic valvular disease. Clinical value of the patient-specific 3D printed models in these areas is presented based on the current literature, while limitations and future research in 3D printing including bioprinting of cardiovascular disease are highlighted.

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Integration of Patient Specific MRI Imaging Data Into a Stochastic Low-Grade Glioma Model

Biomedical Engineering / Biomedizinische Technik ◽

10.1515/bmt-2013-4342 ◽

2013 ◽

Cited By ~ 1

Author(s):

Thaís Roque ◽

Maria Concepcion Garcia Otaduy ◽

Waldemar Zylka

Keyword(s):

Low Grade Glioma ◽

Patient Specific ◽

Low Grade ◽

Imaging Data ◽

Mri Imaging ◽

Glioma Model

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Real-Time Haptic and Visual Simulation of Bone Dissection

Presence Teleoperators & Virtual Environments ◽

10.1162/105474603763835378 ◽

2003 ◽

Vol 12 (1) ◽

pp. 110-122 ◽

Cited By ~ 35

Author(s):

Marco Agus ◽

Andrea Giachetti ◽

Enrico Gobbetti ◽

Gianluigi Zanetti ◽

Antonio Zorcolo

Keyword(s):

Real Time ◽

Bone Erosion ◽

Training System ◽

Visual Simulation ◽

Patient Specific ◽

Imaging Data ◽

Erosion Process ◽

Bone Surgery ◽

Temporal Bone Surgery ◽

Current Implementation

Bone dissection is an important component of many surgical procedures. In this paper, we discuss a haptic and visual simulation of a bone-cutting burr that is being developed as a component of a training system for temporal bone surgery. We use a physically motivated model to describe the burr-bone interaction, which includes haptic forces evaluation, the bone erosion process, and the resulting debris. The current implementation, directly operating on a voxel discretization of patient-specific 3D CT and MR imaging data, is efficient enough to provide real-time feedback on a low-end multiprocessing PC platform.

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Custom Patient-Specific Three-Dimensional Printed Mitral Valve Models for Pre-Operative Patient Education Enhance Patient Satisfaction and Understanding

Journal of Medical Devices ◽

10.1115/1.4043737 ◽

2019 ◽

Vol 13 (3) ◽

Author(s):

Kay S. Hung ◽

Michael J. Paulsen ◽

Hanjay Wang ◽

Camille Hironaka ◽

Y. Joseph Woo

Keyword(s):

Patient Education ◽

Mitral Valve ◽

Three Dimensional ◽

3D Models ◽

Patient Specific ◽

Imaging Data ◽

Anatomical Models ◽

Mitral Valves ◽

Flexible Polymer ◽

3D Printed

In recent years, advances in medical imaging and three-dimensional (3D) additive manufacturing techniques have increased the use of 3D-printed anatomical models for surgical planning, device design and testing, customization of prostheses, and medical education. Using 3D-printing technology, we generated patient-specific models of mitral valves from their pre-operative cardiac imaging data and utilized these custom models to educate patients about their anatomy, disease, and treatment. Clinical 3D transthoracic and transesophageal echocardiography images were acquired from patients referred for mitral valve repair surgery and segmented using 3D modeling software. Patient-specific mitral valves were 3D-printed using a flexible polymer material to mimic the precise geometry and tissue texture of the relevant anatomy. 3D models were presented to patients at their pre-operative clinic visit and patient education was performed using either the 3D model or the standard anatomic illustrations. Afterward, patients completed questionnaires assessing knowledge and satisfaction. Responses were calculated based on a 1–5 Likert scale and analyzed using a nonparametric Mann–Whitney test. Twelve patients were presented with a patient-specific 3D-printed mitral valve model in addition to standard education materials and twelve patients were presented with only standard educational materials. The mean survey scores were 64.2 (±1.7) and 60.1 (±5.9), respectively (p = 0.008). The use of patient-specific anatomical models positively impacts patient education and satisfaction, and is a feasible method to open new opportunities in precision medicine.

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Personalized Three-Dimensional Printed Models in Congenital Heart Disease

Journal of Clinical Medicine ◽

10.3390/jcm8040522 ◽

2019 ◽

Vol 8 (4) ◽

pp. 522 ◽

Cited By ~ 13

Author(s):

Sun ◽

Lau ◽

Wong ◽

Yeong

Keyword(s):

Congenital Heart Disease ◽

Heart Disease ◽

Congenital Heart ◽

Three Dimensional ◽

Patient Specific ◽

Future Research ◽

Imaging Data ◽

Doctor Patient Communication ◽

Medical Education And Training ◽

3D Printed

Patient-specific three-dimensional (3D) printed models have been increasingly used in cardiology and cardiac surgery, in particular, showing great value in the domain of congenital heart disease (CHD). CHD is characterized by complex cardiac anomalies with disease variations between individuals; thus, it is difficult to obtain comprehensive spatial conceptualization of the cardiac structures based on the current imaging visualizations. 3D printed models derived from patient’s cardiac imaging data overcome this limitation by creating personalized 3D heart models, which not only improve spatial visualization, but also assist preoperative planning and simulation of cardiac procedures, serve as a useful tool in medical education and training, and improve doctor–patient communication. This review article provides an overall view of the clinical applications and usefulness of 3D printed models in CHD. Current limitations and future research directions of 3D printed heart models are highlighted.

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Complementing sparse vascular imaging data by physiological adaptation rules

Journal of Applied Physiology ◽

10.1152/japplphysiol.00250.2019 ◽

2020 ◽

Author(s):

Maarten H.G. Heusinkveld ◽

Robert J. Holtackers ◽

Bouke P. Adriaans ◽

Jos Op't Roodt ◽

Theo Arts ◽

...

Keyword(s):

Clinical Decision Making ◽

Mechanical Load ◽

Wall Stress ◽

Clinical Decision ◽

Physiological Adaptation ◽

Patient Specific ◽

Data Sets ◽

Imaging Data ◽

Artery Segment ◽

Flow Waveforms

Introduction:Mathematical modeling of pressure and flow waveforms in blood vessels using pulse wave propagation (PWP)-models has tremendous potential to support clinical decision-making. For a personalized model outcome, measurements of all modeled vessel radii and wall thicknesses are required. In clinical practice, however, data sets are often incomplete. To overcome this problem, we hypothesized that the adaptive capacity of vessels in response to mechanical load could be utilized to fill in the gaps of incomplete patient-specific data sets. Methods:We implemented homeostatic feedback loops in a validated PWP model to allow adaptation of vessel geometry to maintain physiological values of wall stress and wall shear stress. To evaluate our approach, we gathered vascular MRI and ultrasound data sets of wall thicknesses and radii of central and arm arterial segments of ten healthy subjects. Reference models (i.e. termed RefModel, n=10) were simulated using complete data, whereas adapted models (AdaptModel, n=10) used data of one carotid artery segment only while the remaining geometries in this model were estimated using adaptation. We evaluated agreement between RefModel and AdaptModel geometries, as well as between pressure and flow waveforms of both models. Results:Limits of agreement (bias±2SD of difference) between AdaptModel and RefModel radii and wall thicknesses were 0.2±2.6 mm and -140±557 μm, respectively. Pressure and flow waveform characteristics of the AdaptModel better resembled those of the RefModels as compared to the model in which the vessels were not adapted.Conclusions:Our adaptation-based PWP-model enables personalization of vascular geometries even when not all required data is available.

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Orthotic Design through 3D Reconstruction: A Passive-Assistance Ankle–Foot Orthotic

Applied Bionics and Biomechanics ◽

10.1155/2006/497687 ◽

2006 ◽

Vol 3 (2) ◽

pp. 93-99

Author(s):

A. L. Darling ◽

W. Sun

Keyword(s):

3D Reconstruction ◽

Major Axis ◽

Patient Comfort ◽

Skeletal Structure ◽

Patient Specific ◽

Imaging Data ◽

Skin Contact ◽

Specific Geometry ◽

Plaster Model ◽

Foot Orthotic

Current methods of designing and manufacturing custom orthotics include manual techniques such as casting a limb in plaster, making a plaster duplicate of the limb to be treated and forming a polymer orthotic directly onto the plaster model. Such techniques are usually accompanied with numerous postmanufacture alterations to adapt the orthotic for patient comfort. External modeling techniques rely heavily on the skill of the clinician, as the axes of rotation of any joint are partially specified by the skeletal structure and are not completely inferable from the skin, especially in cases where edema is present. Clinicians could benefit from a simultaneous view of external and skeletal patient-specific geometry. In addition to providing more information to clinicians, quantification of patient-specific data would allow rapid production of advanced orthotics, requiring machining rather than casting. This paper presents a supplemental method of orthotic design and fitting, through 3D reconstruction of medical imaging data to parameterise an orthotic design based on a major axis of rotation, shape of rigid components and placement of skin contact surfaces. An example of this design approach is shown in the design of an ankle–foot orthotic designed around the computed tomography data from the Visible Human Project.

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Does the DSA reconstruction kernel affect hemodynamic predictions in intracranial aneurysms? An analysis of geometry and blood flow variations

Journal of NeuroInterventional Surgery ◽

10.1136/neurintsurg-2017-012996 ◽

2017 ◽

Vol 10 (3) ◽

pp. 290-296 ◽

Cited By ~ 19

Author(s):

P Berg ◽

S Saalfeld ◽

S Voß ◽

T Redel ◽

B Preim ◽

...

Keyword(s):

Blood Flow ◽

Intracranial Aneurysms ◽

Three Dimensional ◽

Patient Specific ◽

Parent Artery ◽

Imaging Data ◽

Specific Flow ◽

Aneurysm Neck ◽

Velocity Magnitude ◽

Reconstruction Kernel

BackgroundComputational fluid dynamics (CFD) blood flow predictions in intracranial aneurysms promise great potential to reveal patient-specific flow structures. Since the workflow from image acquisition to the final result includes various processing steps, quantifications of the individual introduced potential error sources are required.MethodsThree-dimensional (3D) reconstruction of the acquired imaging data as input to 3D model generation was evaluated. Six different reconstruction modes for 3D digital subtraction angiography (DSA) acquisitions were applied to eight patient-specific aneurysms. Segmentations were extracted to compare the 3D luminal surfaces. Time-dependent CFD simulations were carried out in all 48 configurations to assess the velocity and wall shear stress (WSS) variability due to the choice of reconstruction kernel.ResultsAll kernels yielded good segmentation agreement in the parent artery; deviations of the luminal surface were present at the aneurysm neck (up to 34.18%) and in distal or perforating arteries. Observations included pseudostenoses as well as noisy surfaces, depending on the selected reconstruction kernel. Consequently, the hemodynamic predictions show a mean SD of 11.09% for the aneurysm neck inflow rate, 5.07% for the centerline-based velocity magnitude, and 17.83%/9.53% for the mean/max aneurysmal WSS, respectively. In particular, vessel sections distal to the aneurysms yielded stronger variations of the CFD values.ConclusionsThe choice of reconstruction kernel for DSA data influences the segmentation result, especially for small arteries. Therefore, if precise morphology measurements or blood flow descriptions are desired, a specific reconstruction setting is required. Furthermore, research groups should be encouraged to denominate the kernel types used in future hemodynamic studies.

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