Background: Three-dimensional printing is increasingly recognized as a valuable tool for congenital heart disease (CHD) procedural planning and education. Cost and complexity currently limit the more widespread adoption of this technology. We sought to demonstrate the accuracy of 3D printed CHD models created from contrast-enhanced magnetic resonance imaging (MRI) and computed tomography (CT) scans using free software and an inexpensive desktop fused filament fabrication (FFF) printer.
Methods: Solid segmentations of the intracardiac blood pool were created with the program ITK-SNAP. Using the computer program Meshmixer, the segmentation model was hollowed to create a 0.8 mm shell with the inner surface representing endocardium. Three-dimensional models were created on an FFF printer. Four arteries and a ventricular septal defect (VSD) were 3D printed and measured for accuracy. Five models were used to assess candidacy for biventricular surgical repair and one to guide an interventional catheterization.
Results: All six patients underwent intervention planned with the 3D models. The computer model shell walls all achieved specifications within 0.05 mm of the designated 0.8 mm thickness and the original solid blood pool segmentation fit within the hollowed 3D model. The 3D printed arteries and VSD all measured accurately to within 0.5 mm of their source computer model.
Conclusion: Accurate 3D printed models of complex, pediatric CHD may be created from volumetric MRI and CT studies using free online software and printed on an inexpensive desktop printer.
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http://dx.doi.org/10.1177/2150135120952072 | DOI Listing |
BMC Oral Health
January 2025
Affiliated Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, People's Republic of China.
Objective: The aim of this study was to establish a three-dimensional finite element (FE) hydraulic pressure technique model and compare the biomechanical characteristics of the osteotome technique and the hydraulic pressure technique using three-dimensional finite element analysis (FEA).
Methods: Three FE models were created: the hydraulic pressure technique (M1), the osteotome technique with a Ø 1.6-mm osteotome (M2), and the osteotome technique with a Ø 3.
Orphanet J Rare Dis
January 2025
Laboratory of Neurogenetics and Molecular Medicine, Center for Genomic Sciences in Medicine, Institut de Recerca Sant Joan de Déu, Únicas SJD Center, Hospital Sant Joan de Déu, Barcelona, Spain.
Background: Rare diseases (RDs) are a heterogeneous group of complex and low-prevalence conditions in which the time to establish a definitive diagnosis is often too long. In addition, for most RDs, few to no treatments are available and it is often difficult to find a specialized care team.
Objectives: The project "acERca las enfermedades raras" (in English: "bringing RDs closer") is an initiative primary designed to generate a consensus by a multidisciplinary group of experts to detect the strengths and weaknesses in the public healthcare system concerning the comprehensive care of persons living with a RD (PLWRD) in the region of Catalonia, Spain, where a Network of Clinical Expert Units (Xarxa d'Unitats de Expertesa Clínica or XUEC) was created and is being implemented since 2015.
BMC Gastroenterol
January 2025
Health Management Center, the First Affiliated Hospital of Zhejiang University School of Medicine, No.79 Qingchun Road, Shangcheng District, Hangzhou, Zhejiang, China.
Objectives: Over 30% of people worldwide suffer from metabolic dysfunction-associated steatotic liver disease (MASLD), a significant global health issue. Identifying and preventing high-risk individuals for MASLD early is crucial. The purpose of our study is to investigate the factors related to the development of MASLD and develop a risk prediction model for its occurrence.
View Article and Find Full Text PDFCommun Psychol
January 2025
School of Psychological Science, University of Bristol, Bristol, UK.
The practice of microtargeting in politics, involving tailoring persuasive messages to individuals based on personal vulnerabilities, has raised manipulation concerns. As microtargeting's persuasive benefits are well-established and its use facilitated by AI tools and personality-inference models, ethical and regulatory concerns are magnified. Here, we explore countering microtargeting effects by creating a warning signal deployed when users encounter personality-tailored political ads.
View Article and Find Full Text PDFSci Rep
January 2025
Division of Plastic, Craniofacial and Hand Surgery, Sidra Medicine, and Weill Cornell Medical College, C1-121, Al Gharrafa St, Ar Rayyan, Doha, Qatar.
Training a machine learning system to evaluate any type of facial deformity is impeded by the scarcity of large datasets of high-quality, ethics board-approved patient images. We have built a deep learning-based cleft lip generator called CleftGAN designed to produce an almost unlimited number of high-fidelity facsimiles of cleft lip facial images with wide variation. A transfer learning protocol testing different versions of StyleGAN as the base model was undertaken.
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