Evidence map›Paper›PMID 41258174›Full record

ArticleScientific reports2025

Deformation mechanisms in marathon running shoes elucidated by X-ray micro-computed tomography and digital volume correlation analysis.

Eshan Ganju, Henry Hanson, Maximilian Wormser, Nikhilesh Chawla

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Eshan GanjuSchool of Materials Engineering, Purdue University, West Lafayette, IN, USA.
Henry HansonAdidas AG, Adi-Dassler-Strasse 1, 91074, Herzogenaurach, Germany.
Maximilian WormserAdidas AG, Adi-Dassler-Strasse 1, 91074, Herzogenaurach, Germany.
Nikhilesh ChawlaSchool of Materials Engineering, Purdue University, West Lafayette, IN, USA. nikc@purdue.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The design of high-performance marathon running shoes plays a critical role in optimizing energy return, reducing fatigue, and enhancing comfort for elite athletes. A comprehensive understanding of the internal deformation mechanisms within these complex, multi-material structures is essential for developing new strategies to optimize their performance under realistic loading conditions. In this study, we have integrated x-ray micro-computed tomography (XCT) and digital volume correlation (DVC) to investigate the internal mechanics of a marathon shoe's stiffening element, a critical component used for optimization of energy return and stability to the athlete. Using XCT, we non-destructively imaged the shoe's internal architecture, revealing the intricate geometry of midsole and the stiffening elements within the sole of the shoe. Using a unique 3D printed bending frame, were able to deform the midsole of the shoe and used DVC analyses to quantify the three-dimensional displacement and strain fields under the simulated loading conditions. Our results demonstrate that localized strain patterns near the metatarsophalangeal joint can be used to accurately replicate and understand the foot's natural biomechanics during propulsion. By bridging advanced imaging techniques and computational modeling, this research provides actionable insights for the rapid prototyping of next-generation marathon shoes. The findings and frameworks discussed here help contribute to optimizing performance, setting a new standard for athletic footwear design tailored to the rigorous demands of endurance running.

Indexed as

Marathon RunningRunningShoesX-Ray MicrotomographyBiomechanical PhenomenaHumansBiomechanicsDigital volume correlationRunning shoesStiffening elementX-ray Micro-Computed tomography

Identifiers

PMID41258174
PMCPMC12630606

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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.