Development and Validation of Interpretable Machine Learning Models Incorporating Paraspinal Muscle Quality for to Predict Cage Subsidence Risk Followingposterior Lumbar Interbody Fusion

NCT06888739 | Completed

• 1 other identifier: （2025）Lun Yan Grant No. 220
• Study Type: observational
• Target: 720
• Locations: 1 country
• Sites: 1

Brief Summary

The study focuses on identifying risk factors for cage subsidence after posterior lumbar interbody fusion (PLIF) and developing an interpretable machine learning model to predict these risks. It analyzes patients from two large teaching hospitals, using clinical, radiographic, and surgical parameters, including paraspinal muscle indices and bone density markers. A web-based application was developed to facilitate real-time clinical risk assessments using the machine learning model, enhancing surgical planning and reducing subsidence risks.

Conditions

Degenerative Lumbar Diseases; Cage; Machine Learning

Keywords

Degenerative lumbar disease; Cage subsidence; Machine learning

Outcome Measures

Primary Outcomes (1)

• Bone density imaging indicator: Vertebral Bone Quality (VBQ)

  VBQ is calculated by dividing the mean T1 signal intensity (L1-L4) by the cerebrospinal fluid (CSF) signal at L3

  Preoperative measurement for PLIF (Posterior Lumbar Interbody Fusion)

Study Arms (2)

Non-Subsidence Group

Group A (n = 390): Lost IH value \<2 mm.Cage subsidence was defined as a lost IH value ≥2 mm during the follow-up period

Procedure: MR4

Subsidence Group

Lost IH value ≥2 mm.Cage subsidence was defined as a lost IH value ≥2 mm during the follow-up period

Procedure: MR4

Interventions

MR4 PROCEDURE

The study is a clinical retrospective study and does not involve any interventional measures.

Non-Subsidence Group; Subsidence Group

Eligibility Criteria

• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

This retrospective study included patients with degenerative lumbar diseases who underwent single-level PLIF at the First and Second Affiliated Hospitals of Soochow University (January 2018-October 2023).A total of 620 patients from the First Affiliated Hospital comprised the training set, while 100 patients from the Second Affiliated Hospital formed the external validation set. The study adhered to the Declaration of Helsinki and was approved by the institutional ethics committee.

You may qualify if:

• confirmed lumbar disc herniation, spinal stenosis, or spondylolisthesis based on clinical and imaging findings;
• patients who failed conservative treatment for ≥3 months or experienced recurrence and underwent surgery for the first time;
• minimum 12-month follow-up.

You may not qualify if:

• prior spinal surgery;
• spinal deformity or severe instability;
• lumbar tuberculosis, infection, tumor, or severe bone destruction;
• incomplete or lost follow-up.

Sponsors & Collaborators

• Hao Liu: lead

Study Sites (1)

The First Affiliated Hospital of Soochow University Medical Record and Imaging System

Jiangsu, SuZhou, 215006, China

Location

Biospecimen

Retention: SAMPLES WITHOUT DNA

The study does not include biological samples.

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Department of Orthopedics, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, China

Study Record Dates

• First Submitted: March 17, 2025
• First Posted: March 21, 2025
• Study Start: March 1, 2025
• Primary Completion: March 10, 2025
• Study Completion: March 15, 2025
• Last Updated: March 21, 2025

Record last verified: 2025-03

Data Sharing

• IPD Sharing: Will share

Locations

CN (1)