Evidence map›Paper›PMID 40785581›Full record

ArticleInternational journal for numerical methods in biomedical engineering2025

Computational Assessment of Fracture Risk in Vertebral Bodies With Simulated Defects: The Role of Baseline Strength and Tumor Size.

Mehran Fereydoonpour, Asghar Rezaei, Areonna Schreiber, Lichun Lu, Mariusz Ziejewski, Ghodrat Karami

Abstract read
In one paragraph

Article in International journal for numerical methods in biomedical engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

5 citing papers in PubMed.

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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

6 authors.

Mehran FereydoonpourDepartment of Mechanical Engineering, North Dakota State University, Fargo, North Dakota, USA.ORCID https://orcid.org/0009-0004-0195-9843
Asghar RezaeiDepartment of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, USA.
Areonna SchreiberDepartment of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, USA.
Lichun LuDepartment of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, USA.ORCID https://orcid.org/0000-0002-3862-6493
Mariusz ZiejewskiDepartment of Mechanical Engineering, North Dakota State University, Fargo, North Dakota, USA.
Ghodrat KaramiDepartment of Mechanical Engineering, North Dakota State University, Fargo, North Dakota, USA.

Funding

Metastatic Spine Tumors: Minimally Invasive Fracture Risk Analysis and Treatment - MasterR01AR056212 · NIAMS · MAYO CLINIC ROCHESTER · PI Benjamin D Elder, Lichun Lu · 2008 to 2026
$6.2M
A patient-specific computational technique to predict spine injury risks associated with physical activitiesK25AG068368 · NIA · MAYO CLINIC ROCHESTER · PI REZAEI, ASGHAR · 2021 to 2025
$737k
Fifth District Eagles Cancer TelethonNIAMS NIH HHS R01 AR056212NIAMS NIH HHS R01AR56212NIA NIH HHS K25 AG068368NIA NIH HHS K25AG068368North Dakota State University Foundation
6 · The paper itself

Abstract

Accurately predicting vertebral fracture risk in metastatic spines remains a critical challenge in clinical practice. This study developed and validated a QCT-based finite element analysis (QCT/FEA) approach to investigate the combined effects of baseline bone strength and tumor size on vertebral structural integrity. Areal bone mineral density (aBMD) was also calculated from QCT data to evaluate the reduction in bone density with increasing defect size. Nine cadaveric vertebral bodies were analyzed under varying tumor sizes (0%, 20%, 35%, and 50%). The results demonstrated a strong correlation between experimentally measured and computationally predicted failure forces (r = 0.97, p < 0.001) and aBMD values (r = 0.96, p < 0.001). Vertebral strength decreased linearly with increasing tumor size. Importantly, the study revealed that baseline vertebral strength plays a crucial role in fracture risk assessment, often surpassing the impact of tumor size alone. Tumor size reduced vertebral strength at a rate 84% faster than bone density (p = 0.009), highlighting a greater impact of tumor defects on bone fracture force than on bone density. These findings suggest that relying solely on tumor size for fracture risk prediction may be insufficient. Incorporating baseline bone strength into predictive models significantly enhances accuracy and reliability, providing valuable insights for clinical decision-making and personalized treatment strategies. This study underscores the importance of advanced computational tools in improving vertebral fracture risk assessment in metastatic spine cases.

Indexed as

Spinal FracturesSpinal NeoplasmsVertebral BodyBiomechanical PhenomenaBone DensityComputer SimulationFemaleFinite Element AnalysisHumansMaleMiddle Ageddefect sizefinite element analysismetastatic spinevertebral fracture

Identifiers

PMID40785581
PMCPMC12694744

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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.