Advance in Bioprinting for Tissue Engineering and Regenerative Medicine

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Regenerative Engineering".

Deadline for manuscript submissions: 31 August 2024 | Viewed by 872

Special Issue Editor


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Guest Editor
Singapore Centre for 3D Printing (SC3DP), School of Mechanical and Aerospace Engineering, Nanyang Technological University (NTU), 50 Nanyang Avenue, Singapore 639798, Singapore
Interests: 3D bioprinting; bio-inks; tissue engineering; cultivated meat; machine learning
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Special Issue Information

Dear Colleagues,

Over the years, significant advances have been made in the field of 3D bioprinting. This involves the deposition of biocompatible bio-inks and living cells for a wide variety of applications such as tissue engineering and regenerative medicine, food printing, pharmaceutical and chemical testing, and fundamental biological studies. Furthermore, the integration of machine learning with 3D bioprinting techniques can potentially help in the optimization of the printing process, in situ monitoring and correction, and bio-ink development.

In this Special Issue, “3D Bioprinting: Recent Advances and Applications”, we aim to solicit manuscripts that highlight the recent developments and advances in 3D bioprinting along with the various applications of 3D bioprinting. Original research, reviews, perspectives and opinions are welcome in this collection. This Special Issue aims to inspire, inform, and provide direction and guidance to researchers in this field.

  • 3D Bioprinting: tissue engineering and regenerative medicine;
  • Food printing;
  • Drug printing;
  • Machine learning in 3D bioprinting.

Dr. Wei Long Ng
Guest Editor

Manuscript Submission Information

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Keywords

  • 3D bioprinting
  • food printing
  • drug printing
  • machine learning

Published Papers (1 paper)

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12 pages, 3263 KiB  
Technical Note
Quantitative Assessment of Acetabular Defects in Revision Hip Arthroplasty Based on 3D Modeling: The Area Increase Ratio (AIR) Method
by Giuseppe Marongiu, Antonio Campacci and Antonio Capone
Bioengineering 2024, 11(4), 341; https://doi.org/10.3390/bioengineering11040341 - 30 Mar 2024
Viewed by 642
Abstract
The most common classifications for acetabular bone defects are based on radiographic two-dimensional imaging, with low reliability and reproducibility. With the rise of modern processing techniques based on 3D modelling, methodologies for the volumetric quantification of acetabular bone loss are available. Our study [...] Read more.
The most common classifications for acetabular bone defects are based on radiographic two-dimensional imaging, with low reliability and reproducibility. With the rise of modern processing techniques based on 3D modelling, methodologies for the volumetric quantification of acetabular bone loss are available. Our study aims to describe a new methodology for the quantitative assessment of acetabular defects based on 3D modelling, focused on surface analysis of the integrity of the main anatomical structures of the acetabulum represented by four corresponding sectors (posterior, superior, anterior, and medial). The defect entity is measured as the area increase ratio (AIR) detected in all the sectors analyzed on three planes of view (frontal, sagittal, and axial) compared to healthy hemipelvises. The analysis was performed on 3D models from the CT-scan of six exemplary specimens with a unilateral pathological hemipelvis. The AIR between the native and the pathological hemipelvis was calculated for each sector, for a total of 48 analyses (range, +0.93–+171.35%). An AIR of >50% were found in 22/48 (45.8%) sectors and affected mostly the posterior, medial, and superior sectors (20/22, 90.9%). Qualitative analysis showed consistency between the data and the morphological features of the defects. Further studies with larger samples are needed to validate the methodology and potentially develop a new classification scheme. Full article
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