Evidence map›Paper›PMID 36246391›Full record

ArticleFrontiers in bioengineering and biotechnology2022

Computational evaluation of psoas muscle influence on walking function following internal hemipelvectomy with reconstruction.

Marleny M Vega, Geng Li, Mohammad S Shourijeh, Di Ao, Robert C Weinschenk, Carolynn Patten, Josep M Font-Llagunes, Valerae O Lewis, Benjamin J Fregly

Open access · goldAbstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

12 citing papers in PubMed, 15 citations in OpenAlex.

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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 at 5 institutions in 2 countries.

Marleny M VegaRice Computational Neuromechanics Lab, Department of Mechanical Engineering, Rice University, Houston, TX, United States.
Geng LiRice Computational Neuromechanics Lab, Department of Mechanical Engineering, Rice University, Houston, TX, United States.
Mohammad S ShourijehRice Computational Neuromechanics Lab, Department of Mechanical Engineering, Rice University, Houston, TX, United States.
Di AoRice Computational Neuromechanics Lab, Department of Mechanical Engineering, Rice University, Houston, TX, United States.
Robert C WeinschenkDepartment of Orthopaedic Surgery, University of Texas Southwestern Medical Center, Dallas, TX, United States.
Carolynn PattenBiomechanics, Rehabilitation, and Integrative Neuroscience (BRaIN) Lab, UC Davis School of Medicine, Sacramento, CA, United States.
Josep M Font-LlagunesBiomechanical Engineering Lab, Department of Mechanical Engineering and Research Centre for Biomedical Engineering, Universitat Politècnica de Catalunya, Barcelona, Spain.
Valerae O LewisDepartment of Orthopaedic Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, United States.
Benjamin J FreglyRice Computational Neuromechanics Lab, Department of Mechanical Engineering, Rice University, Houston, TX, United States.
Rice University · USInstitut de Recerca Sant Joan de DéuThe University of Texas MD Anderson Cancer Center · USThe University of Texas Southwestern Medical Center · USUniversity of California, Davis · US

Funding

RRD VA IK6 RX003543
6 · The paper itself

Abstract

An emerging option for internal hemipelvectomy surgery is custom prosthesis reconstruction. This option typically recapitulates the resected pelvic bony anatomy with the goal of maximizing post-surgery walking function while minimizing recovery time. However, the current custom prosthesis design process does not account for the patient's post-surgery prosthesis and bone loading patterns, nor can it predict how different surgical or rehabilitation decisions (e.g., retention or removal of the psoas muscle, strengthening the psoas) will affect prosthesis durability and post-surgery walking function. These factors may contribute to the high observed failure rate for custom pelvic prostheses, discouraging orthopedic oncologists from pursuing this valuable treatment option. One possibility for addressing this problem is to simulate the complex interaction between surgical and rehabilitation decisions, post-surgery walking function, and custom pelvic prosthesis design using patient-specific neuromusculoskeletal models. As a first step toward developing this capability, this study used a personalized neuromusculoskeletal model and direct collocation optimal control to predict the impact of ipsilateral psoas muscle strength on walking function following internal hemipelvectomy with custom prosthesis reconstruction. The influence of the psoas muscle was targeted since retention of this important muscle can be surgically demanding for certain tumors, requiring additional time in the operating room. The post-surgery walking predictions emulated the most common surgical scenario encountered at MD Anderson Cancer Center in Houston. Simulated post-surgery psoas strengths included 0% (removed), 50% (weakened), 100% (maintained), and 150% (strengthened) of the pre-surgery value. However, only the 100% and 150% cases successfully converged to a complete gait cycle. When post-surgery psoas strength was maintained, clinical gait features were predicted, including increased stance width, decreased stride length, and increased lumbar bending towards the operated side. Furthermore, when post-surgery psoas strength was increased, stance width and stride length returned to pre-surgery values. These results suggest that retention and strengthening of the psoas muscle on the operated side may be important for maximizing post-surgery walking function. If future studies can validate this computational approach using post-surgery experimental walking data, the approach may eventually influence surgical, rehabilitation, and custom prosthesis design decisions to meet the unique clinical needs of pelvic sarcoma patients.

Indexed as

computational modelinginternal hemipelvectomy surgeryneuromusculoskeletal modelingoptimal controlorthopedic biomechanicspelvic sarcomapredictive simulationtreatment optimization

Identifiers

PMID36246391
PMCPMC9559731
OpenAlexW4297540181

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.