Research Article

The Prediction of Recurrence of Lumbar Disc Herniation at L5-S1 through Machine Learning Based on Endoscopic Discectomy via the Interlaminar Approach

DOI:

10.3791/68550

⸱

July 11th, 2025

 ,  ,  ,  , 
1Department of Spine Surgery, Affiliated Hospital 2 of Nantong University, 2Nantong Clinical Medical College of Kangda College of Nanjing Medical University, 3Nantong Hospital to Nanjing University of Chinese Medicine, 4Research Institute for Spine and Spinal Cord Disease of Nantong University

In This Article

Summary

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Machine learning models were developed to predict L5-S1 disc herniation recurrence after PEID surgery, analyzing data from 309 patients. Key predictors included BMI and PDHI, with random forest and extreme gradient boosting models showing the best performance.

Abstract

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This study aimed to develop machine learning (ML) models to predict the L5-S1 level recurrent lumbar disc herniation (rLDH) after percutaneous endoscopic interlaminar discectomy (PEID), a minimally invasive treatment for L5-S1 lumbar disc herniation. Data from 309 patients who underwent single-level L5-S1 PEID between January 2020 and June 2024, with at least 6 months of follow-up, were analyzed. Clinical records, preoperative imaging, and visual analog scale (VAS) scores were used. LASSO regression identified key predictors, and six ML models were built: support vector machine (SVM), decision tree (DT), adaptive boosting (ADA), light gradient boosting machine (LGBM), random forest (RF), and extreme gradient boosting (XGB). Among the patients, 10.7% experienced rLDH, defined as ≥60% VAS reduction followed by symptom recurrence and imaging confirmation. Key predictors included Body Mass Index (BMI), posterior disc height index (PDHI), spinal canal stenosis, disease duration, numbness or weakness, Modic changes, herniation type, and diabetes. The RF and XGB models performed best. Higher BMI, Higher PDHI, spinal canal stenosis, disease duration over six months, Modic changes, non-contained herniation, and diabetes increased rLDH risk. Variable importance was ranked for both models. Predicting rLDH preoperatively can enhance decision-making and reduce recurrence risk after PEID, with ML models improving accuracy and identifying critical risk factors.

Introduction

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Percutaneous endoscopic lumbar discectomy (PELD) encompasses various techniques, such as percutaneous endoscopic transforaminal discectomy (PETD) and percutaneous endoscopic interlaminar discectomy (PEID), with the choice of surgical approach depending on the lesion location and individual anatomical characteristics of the patient1. Recurrent lumbar disc herniation (rLDH) is one of the most common reasons for reoperation following PELD, with an incidence ranging from 0% to 12.5%2,3. As a minimally invasive technique, PEID has been widely applied in the treatment of lumbar conditions suc....

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Protocol

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This study is a retrospective analysis approved by the Institutional Ethics Committee of Nantong First People's Hospital. The trial has been registered on ClinicalTrials.gov (Registration Number: NCT06833099). As all participants' health information was anonymized, informed consent was not required. The consumables and equipment used are listed in the Table of Materials.

1. Study population

The study included clinical data and preoperative imaging records of 436 patients who underwent percutaneous endoscopic interlaminar discectomy (PEID) for low back pain and leg pain due to L5-S1....

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Results

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A total of 309 patients with L5-S1 lumbar disc herniation causing lower back and leg pain who underwent percutaneous endoscopic interlaminar discectomy (PEID) were included in this study. Preoperative imaging data, clinical physiological variables, and VAS scores, as well as postoperative imaging and VAS scores, were collected. Among these patients, 33 were classified into the recurrent lumbar disc herniation group (rLDH group), and 276 were categorized into the non-recurrence group (Non-.......

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Discussion

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Percutaneous endoscopic intervertebral discectomy (PEID) plays a significant role in treating L5-S1 disc herniation, which makes it highly important to predict postoperative recurrent lumbar disc herniation (rLDH)1,2. In the image selection and data cleaning phase, this study primarily measured MRI images. When image quality was poor or images were blurred, X-ray or CT scans were used for supplementary measurements. For patients with miss.......

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Disclosures

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The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgements

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The authors would like to thank them for their financial support (The work was supported by Science Foundation of Kangda College of Nanjing Medical University (Grant No. KD2024KYJJ292). The work was supported by Nantong University Special Research Fund for Clinical Medicine (Grant No. 2024JY002). This work was supported by the Science and Technology Project of Nantong Municipal Health Commission (grant no. MS2024045). This work was supported by Science and Technology Projects in Jiangsu Province [BE2023742], Project of Jiangsu Administration of Traditional Chinese Medicine (grant no. MS2023113).

....

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Materials

List of materials used in this article
NameCompanyCatalog NumberComments
Laptop GPUNVIDIA CorporationN/A
MRI MachineSiemens Healthineers11672453Prisma 3.0T
MRI MachineSiemens Healthineers10849662Ingenia CX 3.0T
MRI MachinePhilips Healthcare781341iCT 64-slice Spiral CT
CT MachinePhilips Healthcare728326Ysio
X-ray MachineSiemens Healthineers100925774.3.1
RThe R FoundationOpen-source software; available at https://www.r-project.org/.
readxlRStudio (Posit)Latest (CRAN)Open-source R package; install via CRAN (install.packages("readxl")).
tidyverseRStudio (Posit)Latest (CRAN)Collection of R packages; install via CRAN (install.packages("tidyverse")).
glmnetCRAN contributorsLatest (CRAN)Open-source R package; install via CRAN (install.packages("glmnet")).
pROCCRAN contributorsLatest (CRAN)Open-source R package; install via CRAN (install.packages("pROC")).
zeallotCRAN contributorsLatest (CRAN)Open-source R package; install via CRAN (install.packages("zeallot")).
reticulateRStudio (Posit)Latest (CRAN)Open-source R package; install via CRAN (install.packages("reticulate")).
showtextCRAN contributorsLatest (CRAN)Open-source R package; install via CRAN (install.packages("showtext")).
e1071CRAN contributorsLatest (CRAN)Open-source R package; install via CRAN (install.packages("e1071")).
rmsCRAN contributorsLatest (CRAN)Open-source R package; install via CRAN (install.packages("rms")).
rpartCRAN contributorsLatest (CRAN)Open-source R package; install via CRAN (install.packages("rpart")).
caretCRAN contributorsLatest (CRAN)Open-source R package; install via CRAN (install.packages("caret")).
rpart.plotCRAN contributorsLatest (CRAN)Open-source R package; install via CRAN (install.packages("rpart.plot")).
randomForestCRAN contributorsLatest (CRAN)Open-source R package; install via CRAN (install.packages("randomForest")).
corrplotCRAN contributorsLatest (CRAN)Open-source R package; install via CRAN (install.packages("corrplot")).
PRROCCRAN contributorsLatest (CRAN)Open-source R package; install via CRAN (install.packages("PRROC")).
MatrixCRAN contributorsLatest (CRAN)Open-source R package; install via CRAN (install.packages("Matrix")).
dplyrRStudio (Posit)Latest (CRAN)Part of tidyverse; install via CRAN (install.packages("dplyr")).
ggplot2RStudio (Posit)Latest (CRAN)Part of tidyverse; install via CRAN (install.packages("ggplot2")).
classCRAN contributorsLatest (CRAN)Open-source R package; install via CRAN (install.packages("class")).
adaCRAN contributorsLatest (CRAN)Open-source R package; install via CRAN (install.packages("ada")).
lightgbmMicrosoftLatest (CRAN/GitHub)Open-source R package; install via CRAN (install.packages("lightgbm")) or GitHub.
xgboostCRAN contributorsLatest (CRAN)Open-source R package; install via CRAN (install.packages("xgboost")).

References

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  1. Chen, Z., et al. Transforaminal versus interlaminar approach of full-endoscopic lumbar discectomy under local anesthesia for L5/S1 disc herniation: A randomized controlled trial. Pain Physician. 25 (8), E1191-E1198 (2022).
  2. Cheng, J., et al.

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Tags

Lumbar Disc HerniationL5 S1 RecurrenceMachine Learning PredictionEndoscopic DiscectomyInterlaminar ApproachPercutaneous DiscectomyRandom Forest ModelExtreme Gradient BoostingRisk Factor IdentificationSpinal Canal Stenosis
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