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Three-dimensional printing and porous metallic surfaces: A new orthopedic application

2001· article· en· W1975709397 on OpenAlexaff
Mora C. Melican, Mark C. Zimmerman, Manjit Dhillon, Amrit R. Ponnambalam, Alain Curodeau, J. Russell Parsons

Bibliographic record

VenueJournal of Biomedical Materials Research · 2001
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMaterials sciencePorosity3D printingComposite materialLayer (electronics)CeramicFabricationMoldTexture (cosmology)Biomedical engineering

Abstract

fetched live from OpenAlex

As-cast, porous surfaced CoCr implants were tested for bone interfacial shear strength in a canine transcortical model. Three-dimensional printing (3DP) was used to create complex molds with a dimensional resolution of 175 microm. 3DP is a solid freeform fabrication technique that can generate ceramic pieces by printing binder onto a bed of ceramic powder. A printhead is rastered across the powder, building a monolithic mold, layer by layer. Using these 3DP molds, surfaces can be textured "as-cast," eliminating the need for additional processing as with commercially available sintered beads or wire mesh surfaces. Three experimental textures were fabricated, each consisting of a surface layer and deep layer with distinct individual porosities. The surface layer ranged from a porosity of 38% (Surface Y) to 67% (Surface Z), whereas the deep layer ranged from 39% (Surface Z) to 63% (Surface Y). An intermediate texture was fabricated that consisted of 43% porosity in both surface and deep layers (Surface X). Control surfaces were commercial sintered beaded coatings with a nominal porosity of 37%. A well-documented canine transcortical implant model was utilized to evaluate these experimental surfaces. In this model, five cylindrical implants were placed in transverse bicortical defects in each femur of purpose bred coonhounds. A Latin Square technique was used to randomize the experimental implants left to right and proximal to distal within a given animal and among animals. Each experimental site was paired with a porous coated control site located at the same level in the contralateral limb. Thus, for each of the three time periods (6, 12, and 26 weeks) five dogs were utilized, yielding a total of 24 experimental sites and 24 matched pair control sites. At each time period, mechanical push-out tests were used to evaluate interfacial shear strength. Other specimens were subjected to histomorphometric analysis. Macrotexture Z, with the highest surface porosity, failed at a significantly higher shear stress (p = 0.05) than the porous coated controls at 26 weeks. It is postulated that an increased volume of ingrown bone, resulting from a combination of high surface porosity and a high percentage of ingrowth, was responsible for the observed improvement in strength. Macrotextures X and Y also had significantly greater bone ingrowth than the controls (p = 0.05 at 26 weeks), and displayed, on average, greater interfacial shear strengths than controls, although they were not statistically significant.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.056
GPT teacher head0.359
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations68
Published2001
Admission routes1
Has abstractyes

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