Radiomics Analysis Based on MRI to Detect Brucella Spondylitis

Last updated: January 22, 2024
Sponsor: The Affiliated Hospital of Inner Mongolia Medical University
Overall Status: Active - Recruiting

Phase

N/A

Condition

N/A

Treatment

N/A

Clinical Study ID

NCT06220500
AHInnerMongolia-BS
  • Ages 18-70
  • All Genders

Study Summary

Brucella spondylitis, an infectious spinal disease caused by the invasion of Brucella bacteria into the body. Its diagnosis relies mainly on laboratory and imaging tests. Due to the limited diagnostic ability of X-ray and CT for Brucella spondylitis, MRI has become the main diagnostic tool. In recent years, functional magnetic resonance technology has demonstrated great advantages in the diagnosis and therapeutic evaluation of brucellosis spondylitis, which can provide pathophysiologic information about the disease and is also a noninvasive and noninvasive diagnostic tool with a broader application prospect. Radiomics, an emerging approach, has also shown better diagnostic efficacy for this disease.

Eligibility Criteria

Inclusion

Inclusion Criteria:

  1. Outpatients/Inpatients
  2. Age 18-70 years
  3. Meet diagnostic criteria for brucellosis
  4. Meet symptoms of brucellosis spondylitis
  5. Voluntarily sign an informed consent form
  6. Can cooperate with MRI examination

Exclusion

Exclusion Criteria:

  1. Patients with serious diseases of other systems
  2. History of malignant tumors of the vertebral body
  3. History of tuberculosis
  4. Contraindications to magnetic resonance imaging

Study Design

Total Participants: 100
Study Start date:
January 01, 2023
Estimated Completion Date:
December 31, 2024

Study Description

The investigators will incorporate 100 confirmed cases of Brucella spondylitis (BS) patients diagnosed at Affiliated Hospital of Inner Mongolia Medical University. The patients receive routine scan with a Siemens Skyra 3.0T MRI scanner and the investigators collect clinical data and blood test results from the patients.The investigators segment the affected vertebral bodies by ITK-SNAP software on STIR images to create three-dimensional regions of interest. Then use Onekey software to extract radiomics features from the affected vertebral bodies. Employed t-tests and Lasso regression to select radiomics features. Then separately use radiomics features and combining it with clinical information to build random vector machine(SVM) and random forest(RF) models . All the models are constructed in the training set and their performance are evaluated on the validation set.

Connect with a study center

  • Affiliated Hospital of Inner Mongolia Medical University

    Hohhot, Inner Mongolia
    China

    Active - Recruiting

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