Development of patient-specific 3D models from histopathological samples for applications in radiation therapy

2021 ◽  
Vol 81 ◽  
pp. 162-169
Author(s):  
Joseph M. DeCunha ◽  
Christopher M. Poole ◽  
Martin Vallières ◽  
Jose Torres ◽  
Sophie Camilleri-Broët ◽  
...  
Keyword(s):  
Radiation Therapy ◽  
3D Models ◽  
Patient Specific

scholarly journals Quality Control in 3D Printing: Accuracy Analysis of 3D-Printed Models of Patient-Specific Anatomy

Materials ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1021
Author(s):  
Bernhard Dorweiler ◽  
Pia Elisabeth Baqué ◽  
Rayan Chaban ◽  
Ahmed Ghazy ◽  
Oroa Salem
Keyword(s):  
Wall Thickness ◽  
Large Scale ◽  
Fused Deposition Modeling ◽  
Vascular Anatomy ◽  
3D Models ◽  
Patient Specific ◽  
Stl File ◽  
Fused Deposition ◽  
3D Printed ◽  
The Mean

As comparative data on the precision of 3D-printed anatomical models are sparse, the aim of this study was to evaluate the accuracy of 3D-printed models of vascular anatomy generated by two commonly used printing technologies. Thirty-five 3D models of large (aortic, wall thickness of 2 mm, n = 30) and small (coronary, wall thickness of 1.25 mm, n = 5) vessels printed with fused deposition modeling (FDM) (rigid, n = 20) and PolyJet (flexible, n = 15) technology were subjected to high-resolution CT scans. From the resulting DICOM (Digital Imaging and Communications in Medicine) dataset, an STL file was generated and wall thickness as well as surface congruency were compared with the original STL file using dedicated 3D engineering software. The mean wall thickness for the large-scale aortic models was 2.11 µm (+5%), and 1.26 µm (+0.8%) for the coronary models, resulting in an overall mean wall thickness of +5% for all 35 3D models when compared to the original STL file. The mean surface deviation was found to be +120 µm for all models, with +100 µm for the aortic and +180 µm for the coronary 3D models, respectively. Both printing technologies were found to conform with the currently set standards of accuracy (<1 mm), demonstrating that accurate 3D models of large and small vessel anatomy can be generated by both FDM and PolyJet printing technology using rigid and flexible polymers.

scholarly journals Complex wall modeling for hemodynamic simulations of intracranial aneurysms based on histologic images

2021 ◽  
Vol 16 (4) ◽  
pp. 597-607
Author(s):  
Annika Niemann ◽  
Samuel Voß ◽  
Riikka Tulamo ◽  
Simon Weigand ◽  
Bernhard Preim ◽  
...  
Keyword(s):  
Wall Thickness ◽  
Vessel Wall ◽  
Intracranial Aneurysms ◽  
Geometric Model ◽  
Image Data ◽  
Outer Wall ◽  
3D Models ◽  
Patient Specific ◽  
Intracranial Vessel ◽  
Hemodynamic Simulations

Abstract Purpose For the evaluation and rupture risk assessment of intracranial aneurysms, clinical, morphological and hemodynamic parameters are analyzed. The reliability of intracranial hemodynamic simulations strongly depends on the underlying models. Due to the missing information about the intracranial vessel wall, the patient-specific wall thickness is often neglected as well as the specific physiological and pathological properties of the vessel wall. Methods In this work, we present a model for structural simulations with patient-specific wall thickness including different tissue types based on postmortem histologic image data. Images of histologic 2D slices from intracranial aneurysms were manually segmented in nine tissue classes. After virtual inflation, they were combined into 3D models. This approach yields multiple 3D models of the inner and outer wall and different tissue parts as a prerequisite for subsequent simulations. Result We presented a pipeline to generate 3D models of aneurysms with respect to the different tissue textures occurring in the wall. First experiments show that including the variance of the tissue in the structural simulation affect the simulation result. Especially at the interfaces between neighboring tissue classes, the larger influence of stiffer components on the stability equilibrium became obvious. Conclusion The presented approach enables the creation of a geometric model with differentiated wall tissue. This information can be used for different applications, like hemodynamic simulations, to increase the modeling accuracy.

The applicability of patient-Specific 3D models in the planning of nerve-sparing robot-assisted radical prostatectomy

2021 ◽  
Vol 79 ◽  
pp. S1556-S1557
Author(s):  
H. Veerman ◽  
T.N. Boellaard ◽  
C. Hoeks ◽  
J.A. Van Eick ◽  
J. Sluijter ◽  
...  
Keyword(s):  
Radical Prostatectomy ◽  
3D Models ◽  
Patient Specific ◽  
Nerve Sparing ◽  
Robot Assisted

scholarly journals Multiclass CBCT Image Segmentation for Orthodontics with Deep Learning

2021 ◽  
pp. 002203452110053
Author(s):  
H. Wang ◽  
J. Minnema ◽  
K.J. Batenburg ◽  
T. Forouzanfar ◽  
F.J. Hu ◽  
...  
Keyword(s):  
Gold Standard ◽  
Orthodontic Treatment ◽  
3D Models ◽  
Similarity Coefficient ◽  
Patient Specific ◽  
Dice Similarity Coefficient ◽  
Surface Deviations ◽  
Surface Deviation ◽  
Binary Segmentation ◽  
Time Required

Accurate segmentation of the jaw (i.e., mandible and maxilla) and the teeth in cone beam computed tomography (CBCT) scans is essential for orthodontic diagnosis and treatment planning. Although various (semi)automated methods have been proposed to segment the jaw or the teeth, there is still a lack of fully automated segmentation methods that can simultaneously segment both anatomic structures in CBCT scans (i.e., multiclass segmentation). In this study, we aimed to train and validate a mixed-scale dense (MS-D) convolutional neural network for multiclass segmentation of the jaw, the teeth, and the background in CBCT scans. Thirty CBCT scans were obtained from patients who had undergone orthodontic treatment. Gold standard segmentation labels were manually created by 4 dentists. As a benchmark, we also evaluated MS-D networks that segmented the jaw or the teeth (i.e., binary segmentation). All segmented CBCT scans were converted to virtual 3-dimensional (3D) models. The segmentation performance of all trained MS-D networks was assessed by the Dice similarity coefficient and surface deviation. The CBCT scans segmented by the MS-D network demonstrated a large overlap with the gold standard segmentations (Dice similarity coefficient: 0.934 ± 0.019, jaw; 0.945 ± 0.021, teeth). The MS-D network–based 3D models of the jaw and the teeth showed minor surface deviations when compared with the corresponding gold standard 3D models (0.390 ± 0.093 mm, jaw; 0.204 ± 0.061 mm, teeth). The MS-D network took approximately 25 s to segment 1 CBCT scan, whereas manual segmentation took about 5 h. This study showed that multiclass segmentation of jaw and teeth was accurate and its performance was comparable to binary segmentation. The MS-D network trained for multiclass segmentation would therefore make patient-specific orthodontic treatment more feasible by strongly reducing the time required to segment multiple anatomic structures in CBCT scans.

Combining patient-specific, digital 3D models with tele-education for adolescents with CHD

2021 ◽  
pp. 1-6
Author(s):  
David Liddle ◽  
Sheri Balsara ◽  
Karin Hamann ◽  
Adam Christopher ◽  
Laura Olivieri ◽  
...  
Keyword(s):  
Medical Condition ◽  
Three Dimensional ◽  
Medical Knowledge ◽  
3D Models ◽  
Patient Specific ◽  
Coarctation Of Aorta ◽  
Education Session ◽  
Post Intervention ◽  
Cardiac Defects ◽  
Transposition Of Great Arteries

Abstract Introduction: Adolescents with CHD require transition to specialised adult-centred care. Previous studies have shown that adolescents’ knowledge of their medical condition is correlated with transition readiness. Three-dimensional printed models of CHD have been used to educate medical trainees and patients, although no studies have focused on adolescents with CHD. This study investigates the feasibility of combining patient-specific, digital 3D heart models with tele-education interventions to improve the medical knowledge of adolescents with CHD. Methods: Adolescent patients with CHD, aged between 13 and 18 years old, were enrolled and scheduled for a tele-education session. Patient-specific digital 3D heart models were created using images from clinically indicated cardiac magnetic resonance studies. The tele-education session was performed using commercially available, web-conferencing software (Zoom, Zoom Video Communications Inc.) and a customised software (Cardiac Review 3D, Indicated Inc.) incorporating an interactive display of the digital 3D heart model. Medical knowledge was assessed using pre- and post-session questionnaires that were scored by independent reviewers. Results: Twenty-two adolescents completed the study. The average age of patients was 16 years old (standard deviation 1.5 years) and 56% of patients identified as female. Patients had a variety of cardiac defects, including tetralogy of Fallot, transposition of great arteries, and coarctation of aorta. Post-intervention, adolescents’ medical knowledge of their cardiac defects and cardiac surgeries improved compared to pre-intervention (p < 0.01). Conclusions: Combining patient-specific, digital 3D heart models with tele-education sessions can improve adolescents’ medical knowledge and may assist with transition to adult-centred care.

scholarly journals A Three-Dimensional-Printed Patient-Specific Phantom for External Beam Radiation Therapy of Prostate Cancer

2018 ◽  
Vol 1 (4) ◽  
Author(s):  
Christopher L. Lee ◽  
Max C. Dietrich ◽  
Uma G. Desai ◽  
Ankur Das ◽  
Suhong Yu ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Radiation Therapy ◽  
Treatment Plan ◽  
Ejaculatory Duct ◽  
Three Dimensional ◽  
External Beam Radiation Therapy ◽  
External Beam Radiation ◽  
Patient Specific ◽  
External Beam ◽  
Beam Radiation

This paper presents the design evolution, fabrication, and testing of a novel patient and organ-specific, three-dimensional (3D)-printed phantom for external beam radiation therapy (EBRT) of prostate cancer. In contrast to those found in current practice, this phantom can be used to plan and validate treatment tailored to an individual patient. It contains a model of the prostate gland with a dominant intraprostatic lesion (DIL), seminal vesicles, urethra, ejaculatory duct, neurovascular bundles, rectal wall, and penile bulb generated from a series of combined T2-weighted/dynamic contrast-enhanced magnetic resonance (MR) images. The iterative process for designing the phantom based on user interaction and evaluation is described. Using the CyberKnife System at Boston Medical Center, a treatment plan was successfully created and delivered. Dosage delivery results were validated through gamma index calculations based on radiochromic film measurements which yielded a 99.8% passing rate. This phantom is a demonstration of a methodology for incorporating high-contrast MR imaging into computed-tomography-based radiotherapy treatment planning; moreover, it can be used to perform quality assurance (QA).

scholarly journals Accessing 3D Printed Vascular Phantoms for Procedural Simulation

2021 ◽  
Vol 7 ◽  
Author(s):  
Jasamine Coles-Black ◽  
Damien Bolton ◽  
Jason Chuen
Keyword(s):  
3D Printing ◽  
Endovascular Procedures ◽  
Low Cost ◽  
3D Models ◽  
Routine Care ◽  
Aortic Aneurysms ◽  
Patient Specific ◽  
Ct Angiogram ◽  
Abdominal Aortic ◽  
3D Printed

Introduction: 3D printed patient-specific vascular phantoms provide superior anatomical insights for simulating complex endovascular procedures. Currently, lack of exposure to the technology poses a barrier for adoption. We offer an accessible, low-cost guide to producing vascular anatomical models using routine CT angiography, open source software packages and a variety of 3D printing technologies.Methods: Although applicable to all vascular territories, we illustrate our methodology using Abdominal Aortic Aneurysms (AAAs) due to the strong interest in this area. CT aortograms acquired as part of routine care were converted to representative patient-specific 3D models, and then printed using a variety of 3D printing technologies to assess their material suitability as aortic phantoms. Depending on the technology, phantoms cost $20–$1,000 and were produced in 12–48 h. This technique was used to generate hollow 3D printed thoracoabdominal aortas visible under fluoroscopy.Results: 3D printed AAA phantoms were a valuable addition to standard CT angiogram reconstructions in the simulation of complex cases, such as short or very angulated necks, or for positioning fenestrations in juxtarenal aneurysms. Hollow flexible models were particularly useful for device selection and in planning of fenestrated EVAR. In addition, these models have demonstrated utility other settings, such as patient education and engagement, and trainee and anatomical education. Further study is required to establish a material with optimal cost, haptic and fluoroscopic fidelity.Conclusion: We share our experiences and methodology for developing inexpensive 3D printed vascular phantoms which despite material limitations, successfully mimic the procedural challenges encountered during live endovascular surgery. As the technology continues to improve, 3D printed vascular phantoms have the potential to disrupt how endovascular procedures are planned and taught.

Evaluation of Spherical Parameterization Methods for Three-Dimensional Reconstruction of Medical Images

2013 ◽  
Vol 365-366 ◽  
pp. 1342-1349
Author(s):  
Xing Hui Wu ◽  
Zhi Xiu Hao
Keyword(s):  
Medical Images ◽  
Three Dimensional ◽  
3D Models ◽  
Mapping Method ◽  
Geometric Error ◽  
Patient Specific ◽  
Shape Modelling ◽  
Dimensional Reconstruction ◽  
Statistical Shape ◽  
Spherical Parameterization

The spherical parameterization is important for the correspondence problem that is a major part of statistical shape modelling for the reconstruction of patient-specific 3D models from medical images. In this paper, we present comparative studies of five common spherical mapping methods applied to the femur and tibia models: the Issenburg et al. method, the Alexa method, the Saba et al. method, the Praun et al. method and the Shen et al. method. These methods are evaluated using three sets of measures: distortion property, geometric error and distance to standard landmarks. Results show that the Praun et al. method performs better than other methods while the Shen et al. method can be regarded as the most reliable one for providing an acceptable correspondence result. We suggest that the area preserving property can be used as a sufficient condition while the angle preserving property is not important when choosing a spherical mapping method for correspondence application.

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