MSK Validation Study

Sponsor
NuVasive (Industry)
Overall Status
Enrolling by invitation
CT.gov ID
NCT04422288
Collaborator
(none)
200
2
26.5
100
3.8

Study Details

Study Description

Brief Summary

Spinal posture and imbalance are known to be related to increased muscle expenditure, with narrow "cone of economy" of muscle effort defining the most comfortable postures. Therefore, it is hypothesized that predicting the posture of the lowest muscle effort available for a patient with a given spinal alignment and body properties will correspond to the posture the patient will most likely assume. Based on established musculoskeletal models, a model application was configured to allow prediction of this optimal posture. This study aims to assess the validity of this approach and the value of using biomechanical modeling for pre-operative planning.

Condition or Disease Intervention/Treatment Phase

    Detailed Description

    The objective of this study is to validate a novel method of post-operative posture prediction - a full-body biomechanical model based on an established technology and physiological reasoning. Specifically, the model ability to predict postoperative global sagittal alignment, including compensatory and reciprocal changes, from pre-operative radiographic imaging and the information about planned posture correction will be evaluated. This will be realized by comparing model-predicted radiographic measures and overall balance to follow-up patient radiographs.

    Having demonstrated model validity to predict postoperative posture will allow to use this method for simulating various "what-if" scenarios to empower surgical planning by predicting expected outcomes. This can be used to optimizing preoperative planning, which has a potential to substantially improved surgery predictability and patient outcomes.

    Furthermore, validated model will allow scientific investigation of the principles governing human posture and biomechanics of the pathological spine. Generated scientific knowledge of biomechanical factors influencing sagittal posture and surgery outcomes (e.g. number of levels fused, amount and distribution of posture correction, etc.) can lead to improvements in clinical management of spinal disorders.

    Study Design

    Study Type:
    Observational
    Anticipated Enrollment :
    200 participants
    Observational Model:
    Cohort
    Time Perspective:
    Retrospective
    Official Title:
    Prediction of Postoperative Global Sagittal Alignment Using Musculoskeletal Modeling - Validation Study
    Actual Study Start Date :
    May 15, 2020
    Anticipated Primary Completion Date :
    Jul 31, 2022
    Anticipated Study Completion Date :
    Jul 31, 2022

    Outcome Measures

    Primary Outcome Measures

    1. Difference between model-predicted and observed postural measures - Thoracic Kyphosis (TK) [3 months]

      The simulation-predicted posture will be compared against the posture observed at follow-up, using the thoracic kyphosis (TK) angle.

    2. Difference between model-predicted and observed postural measures - Lumbar Lordosis (LL) [3 Months]

      The simulation-predicted posture will be compared against the posture observed at follow-up, using the LL - lumbar lordosis (LL) angle.

    3. Difference between model-predicted and observed postural measures - T1 Pelvic Angle (TPA) [3 Months]

      The simulation-predicted posture will be compared against the posture observed at follow-up, using the T1 pelvic angle (TPA).

    4. Difference between model-predicted and observed postural measures - Pelvic Incidence-Lumbar Lordosis Mismatch (∆PILL) [3 Months]

      The simulation-predicted posture will be compared against the posture observed at follow-up, using the pelvic incidence-lumbar lordosis mismatch (∆PILL).

    Secondary Outcome Measures

    1. Model sensitivity and specificity in predicting posture imbalance [3 months]

      A McNemar's test (a paired Chi-squared test) will be used to test the null hypothesis that the balance prediction is due to chance, allowing to assess if the model predictive power is better than random.

    Eligibility Criteria

    Criteria

    Ages Eligible for Study:
    18 Years and Older
    Sexes Eligible for Study:
    All
    Inclusion Criteria:
    1. Male or female patients

    2. Any ethnicity

    3. At least 18 years of age

    4. Has undergone a thoracolumbar spinal fusion procedure

    Exclusion Criteria:
    1. Patient has had a prior spinal surgery in the thoracic and/or lumbar spine;

    2. Patient presents scoliosis greater or equal to 20° T4-T12 Cobb angle;

    3. Patient has been diagnosed with idiopathic adolescent scoliosis (treated or untreated);

    4. Patient has other implants that obstruct the spine and/or pelvis in the lateral view;

    5. Patient presents any of the following complications: pseudoarthrosis, instrumentation failure, instrumentation pull-out and/or requires a revision surgery at any time following the primary surgery and prior to 3 months post-op;

    6. Patient is a prisoner.

    Contacts and Locations

    Locations

    Site City State Country Postal Code
    1 University of Colorado Aurora Colorado United States 80045
    2 Univerisity of Pittsburgh Medical Center Pittsburgh Pennsylvania United States 15213

    Sponsors and Collaborators

    • NuVasive

    Investigators

    • Study Director: Kyle Malone, MS, NuVasive

    Study Documents (Full-Text)

    None provided.

    More Information

    Publications

    None provided.
    Responsible Party:
    NuVasive
    ClinicalTrials.gov Identifier:
    NCT04422288
    Other Study ID Numbers:
    • NUVA.MSK1901
    First Posted:
    Jun 9, 2020
    Last Update Posted:
    Feb 18, 2022
    Last Verified:
    Feb 1, 2022
    Studies a U.S. FDA-regulated Drug Product:
    No
    Studies a U.S. FDA-regulated Device Product:
    No
    Additional relevant MeSH terms:

    Study Results

    No Results Posted as of Feb 18, 2022