Evidence map›Paper›PMID 35701504›Full record

ArticleScientific reports2022

Enhancing biomedical data validity with standardized segmentation finite element analysis.

Matthew A Wysocki, Scott Doyle

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

2 authors.

Matthew A WysockiDepartment of Pathology and Anatomical Sciences, University at Buffalo, Buffalo, 14203, USA. mawysock@buffalo.edu.
Scott DoyleDepartment of Pathology and Anatomical Sciences, University at Buffalo, Buffalo, 14203, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Finite element analysis is a powerful computational technique for augmenting biomedical research, prosthetics design, and preoperative surgical assessment. However, the validity of biomechanical data obtained from finite element analysis is dependent on the quality of the preceding data processing. Until now, little information was available about the effect of the segmentation process on finite element models and biomechanical data. The current investigation applied 4 segmentation approaches to 129 femur specimens, yielding a total of 516 finite element models. Biomechanical data including average displacement, pressure, stress, and strain were collected from experimental groups based on the different segmentation approaches. The results indicate that only a 5.0% variation in the segmentation process leads to statistically significant differences in all 4 biomechanical measurements. These results suggest that it is crucial for consistent segmentation procedures to be applied to all specimens within a study. This methodological advancement will help to ensure that finite element data will be more accurate and that research conclusions will have greater validity.

Indexed as

FemurBiomechanical PhenomenaFinite Element Analysis

Identifiers

PMID35701504
PMCPMC9198234

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.