Dixon MRI Imaging Histology for Predicting Postoperative Infection in Posterior Lumbar Fusion for Myasthenia Gravis

NCT ID: NCT06805643

Last Updated: 2025-02-03

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Total Enrollment

1300 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-02-28

Study Completion Date

2026-02-28

Brief Summary

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Sarcopenia is an age-related condition that manifests itself as a persistent decrease in muscle mass and function, which may lead to decreased physical function, increased risk of disease, and reduced quality of life. In surgical patients, sarcopenia has been shown to be associated with increased postoperative complications, prolonged hospitalization, and decreased survival. In patients undergoing lumbar fusion, the presence of sarcopenia may increase the risk of postoperative infection.Lumbar fusion is a common procedure to treat lumbar spine disorders such as lumbar disc herniation, lumbar spondylolisthesis, or lumbar spinal stenosis. However, this procedure is associated with a high rate of complications, especially postoperative infections, which can lead to reoperation, prolonged hospitalization, and even affect patient survival. In recent years, more and more studies have found a significant association between sarcopenia and postoperative infections after lumbar fusion surgery.Imagingomics belongs to a branch of machine learning, which is the process of acquiring images from various imaging devices such as CT, MRI and ultrasound, outlining the region of interest through image segmentation, extracting the features of the image within the region of interest, downscaling the features, and finally building an imagingomics model. MRI Imagingomics, utilizing its rich data information, has shown great potential for application in several medical fields. Among them, the accuracy of Dixon MRI imaging histology in muscle mass and texture assessment makes it particularly important in predicting postoperative infections.Based on this, it is reasonable to believe that Dixon MRI imaging histology can be a powerful tool to help us predict a patient's risk of postoperative infection.

Detailed Description

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Conditions

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Lumbar Vertebrae Surgical Site Infection Radiomics

Study Design

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Observational Model Type

OTHER

Study Time Perspective

RETROSPECTIVE

Study Groups

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postoperative infection

No interventions assigned to this group

Non-operative infections

No interventions assigned to this group

Eligibility Criteria

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Inclusion Criteria

* Male and female patients over 18 years of age.
* Inclusion of patients with sarcopenia is subject to the definition and diagnostic criteria of the European Consensus on Definition and Diagnosis of Sarcopenia.
* The patient underwent posterior lumbar fusion and had a Dixon MRI scan within 2 weeks prior to surgery.
* Patients were able to understand the purpose and procedures of the study and were willing to sign an informed consent form.
* The patient's clinical consultation and follow-up information was complete.

Exclusion Criteria

* The patient has contraindications to MRI, such as implanted metal devices (e.g., pacemakers) or severe claustrophobia.
* Patients with serious other medical conditions, such as heart disease, kidney disease or liver disease, which may affect their post-operative recovery.
* Patients have known immune system disorders or are on immunosuppressive therapy, which may affect their risk of infection.
* The patient has had other spinal surgery within the last 6 months.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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The First People's Hospital of Yunnan

OTHER

Sponsor Role lead

Responsible Party

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Yijin Wang

doc

Responsibility Role PRINCIPAL_INVESTIGATOR

Central Contacts

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Zhisong Liang doc

Role: CONTACT

0871-63648772

Other Identifiers

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KHLL2023-KY209-GZ2024-12-23

Identifier Type: -

Identifier Source: org_study_id

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