Exploring the Intricacies of Finite Element Modeling of 3D-Printed Scaffolds for Musculoskeletal Applications: An In-Depth Review

Finite element analysis (FEA) is redefining how three-dimensional (3D)-printed bone scaffolds are designed and validated. By digitally predicting stress, strain, and deformation before fabrication, FEA is transforming the field of 3D-printed bone scaffolds by offering a predictive framework to design and validate mechanically robust, biologically active constructs. This review summarizes how FEA-driven strategies optimize scaffold geometry, pore architecture, and material properties, ranging from polymer-ceramic composites to hydrogel blends, under physiological loads. We highlight multiscale modeling approaches that connect microscale porosity to overall strength and discuss live integration of printer feedback for rapid design iterations. Experimental and early clinical validations reveal FEA predictions within single-digit error margins and demonstrate scaffold-guided bone ingrowth in patient-specific implants. Finally, we examine emerging AI-enhanced methodologies for real-time optimization, challenges in modeling degradation and cell remodeling, and propose standardized workflows to accelerate the clinical translation of FEA-informed bioprinted bone scaffolds.

Authors

Institutions

Publication Details

Journal
Cureus
Published
2026-01-08
DOI
https://doi.org/10.7759/cureus.101070
Primary Topic
Bone Tissue Engineering Materials
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploring the Intricacies of Finite Element Modeling of 3D-Printed Scaffolds for Musculoskeletal Applications: An In-Depth Review

D. R. Paul, Mishraz Shaikh, Huma Shahzad, SM Anwar Sadat et al.
Cureus
Bone Tissue Engineering Materials
article

Exploring the Intricacies of Finite Element Modeling of 3D-Printed Scaffolds for Musculoskeletal Applications: An In-Depth Review

D. R. Paul, Mishraz Shaikh, Huma Shahzad, SM Anwar Sadat, Ehsanul Hoque Apu, Md Ataur Rahman, David Sta Maria
article en

Abstract

Finite element analysis (FEA) is redefining how three-dimensional (3D)-printed bone scaffolds are designed and validated. By digitally predicting stress, strain, and deformation before fabrication, FEA is transforming the field of 3D-printed bone scaffolds by offering a predictive framework to design and validate mechanically robust, biologically active constructs. This review summarizes how FEA-driven strategies optimize scaffold geometry, pore architecture, and material properties, ranging from polymer-ceramic composites to hydrogel blends, under physiological loads. We highlight multiscale modeling approaches that connect microscale porosity to overall strength and discuss live integration of printer feedback for rapid design iterations. Experimental and early clinical validations reveal FEA predictions within single-digit error margins and demonstrate scaffold-guided bone ingrowth in patient-specific implants. Finally, we examine emerging AI-enhanced methodologies for real-time optimization, challenges in modeling degradation and cell remodeling, and propose standardized workflows to accelerate the clinical translation of FEA-informed bioprinted bone scaffolds.

CureusVol. 18(1)
Wayne State University (US), The University of Texas Rio Grande Valley (US), The Barbara Ann Karmanos Cancer Institute (US), University of Tennessee at Knoxville (US), Northeast Ohio Medical University (US), Dhaka Medical College and Hospital (BD)
Openalex Percentile: Top 95%
Bone Tissue Engineering Materials
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.