Evidence map›Paper›PMID 35347880›Full record

ArticleInternational journal for numerical methods in biomedical engineering2022

A digital twin for simulating the vertebroplasty procedure and its impact on mechanical stability of vertebra in cancer patients.

Hossein Ahmadian, Prasath Mageswaran, Benjamin A Walter, Dukagjin M Blakaj, Eric C Bourekas, Ehud Mendel, William S Marras, Soheil Soghrati

Open access · hybridAbstract read
In one paragraph

Article in International journal for numerical methods in biomedical engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
9.4field-weighted citation impact, top 1% of its field
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

25 citing papers in PubMed, 1 synthesis or guideline pooled it, 44 citations in OpenAlex.

  1. Pooled it
  2. Review
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  5. Current progress of digital twin construction using medical imaging.Journal of applied clinical medical physics · 2025
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  15. Digital twins: a new paradigm in oncology in the era of big data.ESMO real world data and digital oncology · 2024
    Review
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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

8 authors at 2 institutions in 1 country.

Hossein AhmadianDepartment of Integrated Systems Engineering, The Ohio State University, Columbus, Ohio, USA.
Prasath MageswaranDepartment of Integrated Systems Engineering, The Ohio State University, Columbus, Ohio, USA.
Benjamin A WalterDepartment of Biomedical Engineering, The Ohio State University, Columbus, Ohio, USA.
Dukagjin M BlakajDepartment of Radiation Oncology, The Ohio State University, Columbus, Ohio, USA.
Eric C BourekasDepartment of Neurological Surgery, The Ohio State University, Columbus, Ohio, USA.
Ehud MendelDepartment of Radiation Oncology, The Ohio State University, Columbus, Ohio, USA.
William S MarrasDepartment of Integrated Systems Engineering, The Ohio State University, Columbus, Ohio, USA.
Soheil SoghratiDepartment of Mechanical and Aerospace Engineering, The Ohio State University, Columbus, USA.ORCID 0000-0003-2668-9750
The Ohio State University · USNeurological Surgery · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present the application of ReconGAN, introduced in a previous study, for simulating the vertebroplasty (VP) operation and its impact on the fracture response of a vertebral body. ReconGAN consists of a Deep Convolutional Generative Adversarial Network (DCGAN) and a finite element based shape optimization algorithm to virtually reconstruct the trabecular bone microstructure. The VP procedure involves injecting shear-thinning liquid bone cement through a needle in the trabecular region to reinforce a diseased or fractured vertebra. To simulate this treatment modality, computational fluid dynamics (CFD) is employed to predict the morphology of the injected cement within the bone microstructure. A power-law equation is utilized to characterize the non-Newtonian shear-thinning behavior of the polymethyl methacrylate (PMMA) bone cement during injection simulations. The CFD model is coupled with the level-set method to simulate the motion of the interface separating bone cement and bone marrow. After predicting the cement morphology, a data co-registration algorithm is employed to transform the CFD model to a high-fidelity continuum damage mechanics (CDM) finite element model of the augmented vertebra for predicting the fracture response. A feasibility study is presented to demonstrate the ability of this CFD-CDM framework to investigate the effect of VP on the mechanical integrity of the vertebral body in a cancer patient with a lytic metastatic tumor.

Indexed as

NeoplasmsSpinal FracturesVertebroplastyBone CementsHumansSpineBone Cementscomputational fluid dynamicsfinite element methodspinal metastasisvertebral fractureVertebroplasty

Identifiers

PMID35347880
PMCPMC9287026
OpenAlexW4221007258

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.