Evidence map›Paper›PMID 38955891›Full record

ArticleAnnals of biomedical engineering2026

Probabilistic Finite Element Analysis of Human Rib Biomechanics: A Framework for Improved Generalizability.

Vivek Bhaskar Kote, Lance L Frazer, Avani Shukla, Ashley Bailly, Sydney Hicks, Derek A Jones, Drew D DiSerafino, Matthew L Davis, Daniel P Nicolella

Abstract read
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Article in Annals of biomedical engineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

9 authors.

Vivek Bhaskar KoteMaterials Engineering, Southwest Research Institute, San Antonio, TX, USA. vivek.kote@swri.org.ORCID http://orcid.org/0000-0002-9144-5835
Lance L FrazerMaterials Engineering, Southwest Research Institute, San Antonio, TX, USA.
Avani ShuklaMechanical and Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA.
Ashley BaillyBiomedical Engineering, Texas A&M University, College Station, TX, USA.
Sydney HicksCollege of Natural Science and Mathematics, University of Houston, Houston, TX, USA.
Derek A JonesElemance, LLC, Winston-Salem, NC, USA.
Drew D DiSerafinoElemance, LLC, Winston-Salem, NC, USA.
Matthew L DavisElemance, LLC, Winston-Salem, NC, USA.
Daniel P NicolellaMaterials Engineering, Southwest Research Institute, San Antonio, TX, USA.

Funding

Office of Naval Research MTEC 18-04-I-PREDICT (W81XWH1590001)
6 · The paper itself

Abstract

In dynamic impact events, thoracic injuries often involve rib fractures, which are closely related to injury severity. Previous studies have investigated the behavior of isolated ribs under impact loading conditions, but often neglected the variability in anatomical shape and tissue material properties. In this study, we used probabilistic finite element analysis and statistical shape modeling to investigate the effect of population-wide variability in rib cortical bone tissue mechanical properties and rib shape on the biomechanical response of the rib to impact loading. Using the probabilistic finite element analysis results, a response surface model was generated to rapidly investigate the biomechanical response of an isolated rib under dynamic anterior-posterior load given the variability in rib morphometry and tissue material properties. The response surface was used to generate pre-fracture force-displacement computational corridors for the overall population and a population sub-group of older mid-sized males. When compared to the experimental data, the computational mean response had a RMSE of 4.28N (peak force 94N) and 6.11N (peak force 116N) for the overall population and sub-group respectively, whereas the normalized area metric when comparing the experimental and computational corridors ranged from 3.32% to 22.65% for the population and 10.90% to 32.81% for the sub-group. Furthermore, probabilistic sensitivities were computed in which the contribution of uncertainty and variability of the parameters of interest was quantified. The study found that rib cortical bone elastic modulus, rib morphometry and cortical thickness are the random variables that produce the largest variability in the predicted force-displacement response. The proposed framework offers a novel approach for accounting biological variability in a representative population and has the potential to improve the generalizability of findings in biomechanical studies.

Indexed as

Models, BiologicalRib FracturesRibsAdultAgedBiomechanical PhenomenaFinite Element AnalysisHumansMaleMiddle AgedProbabilistic finite-element modelingRib dynamic A–P loadingStatistical-shape-modeling

Identifiers

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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.