scholarly journals A Personalized 3D-Printed Model for Obtaining Informed Consent Process for Thyroid Surgery: A Randomized Clinical Study Using a Deep Learning Approach with Mesh-Type 3D Modeling

2021 ◽  
Vol 11 (6) ◽  
pp. 574
Author(s):  
Jungirl Seok ◽  
Sungmin Yoon ◽  
Chang-Hwan Ryu ◽  
Seok-ki Kim ◽  
Junsun Ryu ◽  
...  
Keyword(s):  
Deep Learning ◽  
Informed Consent ◽  
3D Modeling ◽  
Thyroid Surgery ◽  
3D Model ◽  
Informed Consent Process ◽  
Modeling Technique ◽  
Thyroid Lesion ◽  
3D Printed ◽  
The Mean

The aim of this study was to evaluate the usefulness of a personalized 3D-printed thyroid model that characterizes a patient’s individual thyroid lesion. The randomized controlled prospective clinical trial (KCT0005069) was designed. Fifty-three of these patients undergoing thyroid surgery were randomly assigned to two groups: with or without a 3D-printed model of their thyroid lesion when obtaining informed consent. We used a U-Net-based deep learning architecture and a mesh-type 3D modeling technique to fabricate the personalized 3D model. The mean 3D printing time was 258.9 min, and the mean price for production was USD 4.23 for each patient. The size, location, and anatomical relationship of the tumor and thyroid gland could be effectively presented using the mesh-type 3D modeling technique. The group provided with personalized 3D-printed models showed significant improvement in all four categories (general knowledge, benefits and risks of surgery, and satisfaction; all p < 0.05). All patients received a personalized 3D model after surgery and found it helpful to understand the disease, operation, and possible complications and their overall satisfaction (all p < 0.05). In conclusion, the personalized 3D-printed thyroid model may be an effective tool for improving a patient’s understanding and satisfaction during the informed consent process.

scholarly journals Numerical simulation of welding distortions in large structures with a simplified engineering approach

Open Physics ◽  
2019 ◽  
Vol 17 (1) ◽  
pp. 719-730 ◽  
Author(s):  
Mato Perić ◽  
Karlo Seleš ◽  
Zdenko Tonković ◽  
Martina Lovrenić-Jugović
Keyword(s):  
3D Modeling ◽  
3D Model ◽  
Welding Process ◽  
Modeling Technique ◽  
Computational Time ◽  
Zone Size ◽  
Large Structures ◽  
Proposed Model ◽  
Large Panel ◽  
Inherent Strain

AbstractThis paper presents an efficient thermo-elastoplastic method for the prediction of welding-induced distortions in a large panel structure. It is based on a shell/3D modeling technique which was proposed and experimentally validated in the authors’ previous study. Two numerical examples are analyzed to evaluate the accuracy and efficiency of the present method. In the first example, the recommendations for the estimation of the minimum 3D zone size in the shell/3D model reported in the authors’ previous work are verified, in comparison with the full 3D model, on a T-joint model consisting of plates with different thicknesses. It is shown that the shell/3D modeling technique provides a significant reduction in the computational time needed for the simulation of the welding process and thus enables efficient thermo-elastoplastic analyses on large structures. In the second example, the proposed model is validated on a large panel structure by corresponding the experimental data and inherent strain solutions from the literature.

Informed Consent Process Scale--Chinese Version

2019 ◽  
Author(s):  
Shu Yu Chen ◽  
Shu-Chen Susan Chang ◽  
Chiu-Chu Lin ◽  
Qingqing Lou ◽  
Robert M. Anderson
Keyword(s):  
Informed Consent ◽  
Informed Consent Process ◽  
Chinese Version ◽  
Consent Process ◽  
Process Scale

Readability of Informed Consent Forms: Analysis and Recommendations for Development of Consent Forms for Use with Communities with Limited or Low Literacy

2016 ◽  
Author(s):  
Miraida Morales ◽  
Sarah Barriage
Keyword(s):  
Informed Consent ◽  
Pilot Study ◽  
Informed Consent Process ◽  
Consent Process ◽  
Measurement Tool ◽  
Low Literacy ◽  
Consent Forms ◽  
Early Readers ◽  
Research With Children ◽  
Consentement Éclairé

This poster presents a pilot study that analyzed a small corpus of informed consent forms used in research with children, adolescents, and adult early readers using Coh-Metrix, a readability measurement tool. Recommendations for increasing readability of consent forms in order to improve the informed consent process are also provided. Cette affiche présente une étude pilote qui a analysé un corpus restreint de formulaires de consentement éclairé utilisés dans la recherche avec les enfants, les adolescents et les lecteurs précoces adultes,  utilisant Coh-Metrix, un outil de mesure de la lisibilité. Nous fournissons également des recommandations pour augmenter la lisibilité des formulaires de consentement afin d'améliorer le processus de consentement éclairé.

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.

Sign in / Sign up

Export Citation Format

Share Document