Evidence map›Paper›PMID 31235704›Full record

ArticleScientific reports2019

Optimization of Bone Scaffold Porosity Distributions.

Patrina S P Poh, Dvina Valainis, Kaushik Bhattacharya, Martijn van Griensven, Patrick Dondl

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed.

  1. A review of 3D printed medical implant design.3D printing in medicine · 2026
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  4. Long-term follow-up of patients with large segmental bone defects treated with 3D-printed polycaprolactone/tricalcium phosphate scaffolds.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Patrina S P PohDepartment of Experimental Trauma Surgery, Klinikum Rechts der Isar, Technische Universität München, Munich, Germany.
Dvina ValainisDepartment of Experimental Trauma Surgery, Klinikum Rechts der Isar, Technische Universität München, Munich, Germany.
Kaushik BhattacharyaDivision of Engineering and Applied Sciences, California Institute of Technology, Pasadena, CA, USA.
Martijn van GriensvenDepartment of Experimental Trauma Surgery, Klinikum Rechts der Isar, Technische Universität München, Munich, Germany.ORCID http://orcid.org/0000-0001-5104-9881
Patrick DondlAbteilung für Angewandte Mathematik, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany. patrick.dondl@mathematik.uni-freiburg.de.ORCID http://orcid.org/0000-0003-3035-7230

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Additive manufacturing (AM) is a rapidly emerging technology that has the potential to produce personalized scaffolds for tissue engineering applications with unprecedented control of structural and functional design. Particularly for bone defect regeneration, the complex coupling of biological mechanisms to the scaffolds' properties has led to a predominantly trial-and-error approach. To mitigate this, shape or topology optimization can be a useful tool to design a scaffold architecture that matches the desired design targets, albeit at high computational cost. Here, we consider an efficient macroscopic optimization routine based on a simple one-dimensional time-dependent model for bone regeneration in the presence of a bioresorbable polymer scaffold. The result of the optimization procedure is a scaffold porosity distribution which maximizes the stiffness of the scaffold and regenerated bone system over the entire regeneration time, so that the propensity for mechanical failure is minimized.

Indexed as

Bone and BonesBone RegenerationComputer-Aided DesignTissue ScaffoldsHumansPolymersPorosityTissue EngineeringPolymers

Identifiers

PMID31235704
PMCPMC6591284

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.