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

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.

scholarly journals Patient specific biomodel of the whole aorta - the importance of calcified plaque removal

VASA ◽  
2011 ◽  
Vol 40 (6) ◽  
pp. 453-459 ◽  
Author(s):  
Håkansson ◽  
Rantatalo ◽  
Hansen ◽  
Wanhainen
Keyword(s):  
Computer Aided Design ◽  
Three Dimensional ◽  
Patient Specific ◽  
Imaging Data ◽  
Surgical Interventions ◽  
Plaque Removal ◽  
Calcified Plaque ◽  
And Performance ◽  
Plaster Model ◽  
Silicone Model

Background: The use of anatomical models produced by 3D printing technique (rapid prototyping, RP) is gaining increased acceptance as a complementary tool for planning complex surgical interventions. This paper describes a method for creating a patient specific replica of the whole aorta. Methods: Computed tomography angiography (CTA) DICOM-data was converted to a three-dimensional computer aided design-model (CAD) of the inner wall of the aorta representing the lumen where the calcified plaque contribution was removed in a multi-step editing-manoeuvre. The edited CAD-model was used for creating a physical plaster model of the true lumen in a 3D-printer. Elastic and transparent silicon was applied onto the plaster model, which was then removed leaving a silicon replica of the aorta. Results: The median (interquartile range) difference between diameters obtained from CTA- and RP plaster-model at 19 predefined locations was 0.5 mm (1 mm) which corresponds to a relative median difference of 4.6% (7.0%). The average wall thickness of the silicone model was 3.5 mm. The elasticity property and performance during intervention was good with an acceptable transparency. Conclusions: The integration of RP-techniques with CAD based reconstruction of 3D-medical imaging data provides the needed tools for making a truly patient specific replica of the whole aorta with high accuracy. Plaque removal postprocessing is necessary to obtain a true inner wall configuration.

Customised design of a patient specific 3D printed whole mandible implant

2017 ◽  
Vol 2 (2) ◽  
pp. 104 ◽  
Author(s):  
Mazher I. Mohammed ◽  
Angus P. Fitzpatrick ◽  
Ian Gibson
Keyword(s):  
Treatment Option ◽  
Skeletal Structure ◽  
Patient Specific ◽  
Imaging Data ◽  
Final Design ◽  
Representative Model ◽  
3D Printed ◽  
Scan Data ◽  
The Right

<p>In this study we investigate the design methodology for the creation of a patient specific, whole mandible implant based on a patient’s medical imaging data. We tailor the implant as a treatment option for a patient who will undergo a mandibulectomy due to cancer infiltration of the jaw. We create a 3D representative model of the patient’s skeletal structure from CT scan data, and us this to generate the implant from the patient’s corrupt mandible. In this particular case study the cancer is restricted to the right region of the mandible, and so the left side is used in a symmetry matching approach to create the final model for manufacturing. The final design was 3D printed in medical grade titanium and finished using a mechanical polishing technique, the yield a near mirror finish. We found the final implant to be highly robust, and an excellent fit to a representative model of the patient’s skeletal anatomy. We believe this approach to hold considerable potential for implementation as a treatment option for mandibular complications. </p>

scholarly journals 3D modelling for realistic training and learning

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Ayse Hilal Bati
Keyword(s):  
3D Printing ◽  
3D Reconstruction ◽  
Three Dimensional ◽  
3D Models ◽  
3D Modelling ◽  
Patient Specific ◽  
Physical Interaction ◽  
Imaging Data ◽  
Data Set ◽  
Modelling Techniques

AbstractObjectivesThree-dimensional (3D) reconstruction and modelling techniques based on computer vision have shown significant progress in recent years. Patient-specific models, which are derived from the imaging data set and are anatomically consistent with each other, are important for the development of knowledge and skills. The purpose of this article is to share information about three-dimensional (3D) reconstruction and modelling techniques and its importance in medical education.MethodsAs 3D printing technology develops and costs are lower, adaptation to the original model will increase, thus making models suitable for the anatomical structure and texture. 3D printing has emerged as an innovative way to help surgeons implement more complex procedures.ResultsRecent studies have shown that 3D modelling is a powerful tool for pre-operative planning, proofing, and decision-making. 3D models have excellent potential for alternative interventions and surgical training on both normal and pathological anatomy. 3D printing is an attractive, powerful and versatile technology.ConclusionsPatient-specific models can improve performance and improve learning faster, while improving the knowledge, management and confidence of trainees, whatever their area of expertise. Physical interaction with models has proven to be the key to gaining the necessary motor skills for surgical intervention.

scholarly journals Minimally Invasive Mini-orbitozygomatic Approach for Clipping an Anterior Communicating Artery Aneurysm: Virtual Reality Surgical Planning

2020 ◽  
Author(s):  
Nicolás González Romo ◽  
Franco Ravera Zunino
Keyword(s):  
Virtual Reality ◽  
Minimally Invasive ◽  
Surgical Planning ◽  
Artery Aneurysm ◽  
Patient Specific ◽  
Anterior Communicating Artery ◽  
Imaging Data ◽  
Advantages And Disadvantages ◽  
Orbitozygomatic Approach ◽  
Skull Base Anatomy

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.

scholarly journals Fully Data-Driven Pseudohealthy Synthesis for Planning Valve-Sparing Aortic Root Reconstruction using Conditional Variational Autoencoders

2020 ◽  
Vol 6 (3) ◽  
pp. 284-287
Author(s):  
Jannis Hagenah ◽  
Mohamad Mehdi ◽  
Floris Ernst
Keyword(s):  
Aortic Root ◽  
Similarity Index ◽  
Ground Truth ◽  
Representation Learning ◽  
Patient Specific ◽  
Ultrasound Images ◽  
Specific Geometry ◽  
The Individual ◽  
Native Root ◽  
Original Information

AbstractAortic root aneurysm is treated by replacing the dilated root by a grafted prosthesis which mimics the native root morphology of the individual patient. The challenge in predicting the optimal prosthesis size rises from the highly patient-specific geometry as well as the absence of the original information on the healthy root. Therefore, the estimation is only possible based on the available pathological data. In this paper, we show that representation learning with Conditional Variational Autoencoders is capable of turning the distorted geometry of the aortic root into smoother shapes while the information on the individual anatomy is preserved. We evaluated this method using ultrasound images of the porcine aortic root alongside their labels. The observed results show highly realistic resemblance in shape and size to the ground truth images. Furthermore, the similarity index has noticeably improved compared to the pathological images. This provides a promising technique in planning individual aortic root replacement.

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

2019 ◽  
Vol 66 (7) ◽  
pp. 1872-1883 ◽  
Author(s):  
Alberto Gomez ◽  
Marija Marcan ◽  
Christopher J. Arthurs ◽  
Robert Wright ◽  
Pouya Youssefi ◽  
...  
Keyword(s):  
Velocity Profiles ◽  
Patient Specific ◽  
Flow Imaging ◽  
Imaging Data ◽  
B Spline ◽  
Computational Hemodynamics

scholarly journals Enhancing Patient Experience With Internet Protocol Addressable Digital LED Lighting in Imaging Environments: A Phase I Study (Preprint)

2018 ◽  
Author(s):  
Melanie U Knopp ◽  
Katherine Binzel ◽  
Chadwick L Wright ◽  
Jun Zhang ◽  
Michael V Knopp
Keyword(s):  
Image Quality ◽  
Patient Experience ◽  
Patient Comfort ◽  
Patient Specific ◽  
Diagnostic Image Quality ◽  
Imaging Studies ◽  
Diagnostic Image ◽  
Clinical Imaging ◽  
Ambient Lighting ◽  
Led Lights

BACKGROUND Conventional approaches to improve the quality of clinical patient imaging studies focus predominantly on updating or replacing imaging equipment; however, it is often not considered that patients can also highly influence the diagnostic quality of clinical imaging studies. Patient-specific artifacts can limit the diagnostic image quality, especially when patients are uncomfortable, anxious, or agitated. Imaging facility or environmental conditions can also influence the patient’s comfort and willingness to participate in diagnostic imaging studies, especially when performed in visually unesthetic, anxiety-inducing, and technology-intensive imaging centers. When given the opportunity to change a single aspect of the environmental or imaging facility experience, patients feel much more in control of the otherwise unfamiliar and uncomfortable setting. Incorporating commercial, easily adaptable, ambient lighting products within clinical imaging environments allows patients to individually customize their environment for a more personalized and comfortable experience. OBJECTIVE The aim of this pilot study was to use a customizable colored light-emitting diode (LED) lighting system within a clinical imaging environment and demonstrate the feasibility and initial findings of enabling healthy subjects to customize the ambient lighting and color. Improving the patient experience within clinical imaging environments with patient-preferred ambient lighting and color may improve overall patient comfort, compliance, and participation in the imaging study and indirectly contribute to improving diagnostic image quality. METHODS We installed consumer-based internet protocol addressable LED lights using the ZigBee standard in different PET/CT scan rooms within a clinical imaging environment. We recruited healthy volunteers (n=35) to generate pilot data in order to develop a subsequent clinical trial. The visual perception assessment procedure utilized questionnaires with preprogrammed light/color settings and further assessed how subjects preferred ambient light and color within a clinical imaging setting. RESULTS Technical implementation using programmable LED lights was performed without any hardware or electrical modifications to the existing clinical imaging environment. Subject testing revealed substantial variabilities in color perception; however, clear trends in subject color preference were noted. In terms of the color hue of the imaging environment, 43% (15/35) found blue and 31% (11/35) found yellow to be the most relaxing. Conversely, 69% (24/35) found red, 17% (6/35) found yellow, and 11% (4/35) found green to be the least relaxing. CONCLUSIONS With the majority of subjects indicating that colored lighting within a clinical imaging environment would contribute to an improved patient experience, we predict that enabling patients to customize environmental factors like lighting and color to individual preferences will improve patient comfort and patient satisfaction. Improved patient comfort in clinical imaging environments may also help to minimize patient-specific imaging artifacts that can otherwise limit diagnostic image quality. CLINICALTRIAL ClinicalTrials.gov NCT03456895; https://clinicaltrials.gov/ct2/show/NCT03456895

scholarly journals A Protocol for Automated a-posteriori Adaptive Meshing with SimVascular

2019 ◽  
Author(s):  
Akash Gupta ◽  
Ethan O. Kung
Keyword(s):  
Mesh Size ◽  
Patient Specific ◽  
A Posteriori ◽  
Adaptive Meshing ◽  
Considerable Effort ◽  
Error Metrics ◽  
Scenario Modelling ◽  
Order Of Magnitude ◽  
Novice Users ◽  
Specific Geometry

Abstract Objective: Operational details regarding the use of the adaptive meshing (AM) algorithm available in the SimVascular package are scarce despite its application in several studies. Lacking these details, novice users of the AM algorithm may experience undesirable outcomes post-adaptation such as increases in mesh error metrics, unpredictable increases in mesh size, and losses in geometric fidelity. Here we propose an iterative protocol that will help prevent these undesirable outcomes and enhance the utility of the AM algorithm. We present three trials (conservative, aggressive and moderate settings) of our proposed protocol applied to a scenario modelling a Fontan junction with a patient-specific geometry and physiologically realistic boundary conditions. Results: In all three trials, an overall reduction in mesh error metrics is observed (range 47%-86%). The increase in the number of elements through each adaptation never exceeded the mesh size of the pre-adaptation mesh by one order of magnitude. In all three trials, the protocol resulted in consistent, repeatable improvements in mesh error metrics, no losses of geometric fidelity and steady increments in the number of elements in the mesh. Our proposed protocol prevented the aforementioned undesirable outcomes and can potentially save new users considerable effort and computing resources.

Sign in / Sign up

Export Citation Format

Share Document