{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T03:27:18Z","timestamp":1789702038472,"version":"4.0.1"},"reference-count":51,"publisher":"Public Library of Science (PLoS)","issue":"7","license":[{"start":{"date-parts":[[2025,7,9]],"date-time":"2025-07-09T00:00:00Z","timestamp":1752019200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:sec id=\"sec017\">\n<jats:title>Objective<\/jats:title>\n<jats:p>To develop a severity classification model for symptoms of cervical spondylotic radiculopathy (CSR) based on magnetic resonance imaging (MRI) radiomics and to evaluate the predictive value of MRI radiomics features in the classification of symptoms severity, providing an objective basis for personalized therapeutic interventions.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec018\">\n<jats:title>Methods<\/jats:title>\n<jats:p>This retrospective study included 99 patients diagnosed with CSR, admitted between August 2022 and April 2023. Symptom severity was assessed using the neck disability index (NDI) scale, which facilitated the categorization of participants into mild and severe symptoms groups. A comprehensive set of 3,404 quantitative radiomics features was extracted from four predefined regions of interest (ROIs) using the 3D Slicer software. The least absolute shrinkage and selection operator (LASSO) regression analysis was used to identify the optimal subsets of radiomics features, which were subsequently used to develop a support vector machine (SVM) classification model. Model performance was evaluated using receiver operating characteristic (ROC) curve analysis with area under the curve (AUC) calculations, complemented by accuracy, precision, sensitivity and F1 score evaluations.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec019\">\n<jats:title>Results<\/jats:title>\n<jats:p>Analysis of cervical T2-weighted MRI resulted in the extraction of 3,404 radiomics features from four ROIs. Using the LASSO regression for feature selection, 96 radiomics features were retained for model construction. The most discriminatory characteristics were in the intervertebral discs at levels C4\/5, C5\/6, and C6\/7 in the mid-sagittal plane. The model demonstrated an AUC of 0.91. The accuracy of the model is 0.917, the precision is 0.979, the sensitivity is 0.833, and the F1 score is 0.890.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec020\">\n<jats:title>Conclusion<\/jats:title>\n<jats:p>The severity classification model of CSR symptoms based on MRI radiomics demonstrates robust predictive performance in assessing the severity of CSR symptoms, serving as an effective decision-support tool for guiding personalized therapeutic strategies in clinical practice.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pone.0327756","type":"journal-article","created":{"date-parts":[[2025,7,9]],"date-time":"2025-07-09T17:35:22Z","timestamp":1752082522000},"page":"e0327756","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":1,"title":["A severity classification model of cervical spondylotic radiculopathy symptoms based on MRI radiomics: A retrospective study"],"prefix":"10.1371","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1345-8232","authenticated-orcid":true,"given":"Xi","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiaoli","family":"Tao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huanwen","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huangbo","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Honglai","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2025,7,9]]},"reference":[{"key":"pone.0327756.ref001","doi-asserted-by":"crossref","first-page":"955367","DOI":"10.3389\/fneur.2022.955367","article-title":"Global, regional, and national neck pain burden in the general population, 1990-2019: An analysis of the global burden of disease study 2019","volume":"13","author":"DW Shin","year":"2022","journal-title":"Front Neurol"},{"issue":"8","key":"pone.0327756.ref002","doi-asserted-by":"crossref","first-page":"1912","DOI":"10.1177\/21925682221075290","article-title":"Management of Cervical Spondylotic Radiculopathy: A Systematic review","volume":"12","author":"H Luyao","year":"2022","journal-title":"Global Spine J"},{"issue":"1","key":"pone.0327756.ref003","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.spinee.2010.10.023","article-title":"An evidence-based clinical guideline for the diagnosis and treatment of cervical radiculopathy from degenerative disorders","volume":"11","author":"CM Bono","year":"2011","journal-title":"Spine J"},{"issue":"4","key":"pone.0327756.ref004","doi-asserted-by":"crossref","first-page":"791","DOI":"10.1016\/j.mcna.2014.04.001","article-title":"Cervical radiculopathy","volume":"98","author":"DL Corey","year":"2014","journal-title":"Med Clin North Am"},{"issue":"3","key":"pone.0327756.ref005","doi-asserted-by":"crossref","first-page":"144","DOI":"10.4103\/jcvjs.JCVJS_82_19","article-title":"Cervical spondylosis in patients presenting with \u201csevere\u201d myelopathy: Analysis of treatment by multisegmental spinal fixation \u2013 A case series","volume":"10","author":"A Goel","year":"2019","journal-title":"J Craniovert Jun Spine"},{"issue":"4","key":"pone.0327756.ref006","doi-asserted-by":"crossref","DOI":"10.1097\/BRS.0000000000001784","article-title":"Evaluation of DTI Parameter Ratios and Diffusion Tensor Tractography Grading in the Diagnosis and Prognosis Prediction of Cervical Spondylotic Myelopathy","volume":"42","author":"K Wang","year":"2017","journal-title":"Spine (Phila Pa 1976)"},{"issue":"7","key":"pone.0327756.ref007","doi-asserted-by":"crossref","first-page":"800","DOI":"10.1111\/papr.13252","article-title":"2. Cervical radicular pain","volume":"23","author":"L Peene","year":"2023","journal-title":"Pain Pract"},{"issue":"12","key":"pone.0327756.ref008","doi-asserted-by":"crossref","first-page":"2341","DOI":"10.1007\/s00256-023-04329-0","article-title":"The imaging of cervical spondylotic myeloradiculopathy","volume":"52","author":"S Hesni","year":"2023","journal-title":"Skeletal Radiol"},{"issue":"8","key":"pone.0327756.ref009","doi-asserted-by":"crossref","first-page":"1178","DOI":"10.2106\/00004623-199072080-00008","article-title":"Abnormal magnetic-resonance scans of the cervical spine in asymptomatic subjects. A prospective investigation","volume":"72","author":"SD Boden","year":"1990","journal-title":"J Bone Joint Surg Am"},{"key":"pone.0327756.ref010","doi-asserted-by":"crossref","DOI":"10.1016\/j.wneu.2019.06.067","article-title":"Are Modic Vertebral End-Plate Signal Changes Associated with Degeneration or Clinical Outcomes in the Cervical Spine?","volume":"129","author":"X Yang","year":"2019","journal-title":"World Neurosurg"},{"key":"pone.0327756.ref011","doi-asserted-by":"crossref","first-page":"2041","DOI":"10.2147\/JPR.S144814","article-title":"Modic changes of the cervical spine: T1 slope and its impact on axial neck pain","author":"J Li","year":"2017","journal-title":"JPR"},{"issue":"1","key":"pone.0327756.ref012","doi-asserted-by":"crossref","DOI":"10.1186\/s41747-018-0068-z","article-title":"Radiomics: the facts and the challenges of image analysis","volume":"2","author":"S Rizzo","year":"2018","journal-title":"Eur Radiol Exp"},{"issue":"12","key":"pone.0327756.ref013","doi-asserted-by":"crossref","first-page":"749","DOI":"10.1038\/nrclinonc.2017.141","article-title":"Radiomics: the bridge between medical imaging and personalized medicine","volume":"14","author":"P Lambin","year":"2017","journal-title":"Nat Rev Clin Oncol"},{"issue":"9","key":"pone.0327756.ref014","doi-asserted-by":"crossref","first-page":"1234","DOI":"10.1016\/j.mri.2012.06.010","article-title":"Radiomics: the process and the challenges","volume":"30","author":"V Kumar","year":"2012","journal-title":"Magn Reson Imaging"},{"issue":"2","key":"pone.0327756.ref015","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1148\/radiol.2015151169","article-title":"Radiomics: Images Are More than Pictures, They Are Data","volume":"278","author":"RJ Gillies","year":"2016","journal-title":"Radiology"},{"key":"pone.0327756.ref016","doi-asserted-by":"crossref","first-page":"890371","DOI":"10.3389\/fendo.2022.890371","article-title":"Automatic Grading of Disc Herniation, Central Canal Stenosis and Nerve Roots Compression in Lumbar Magnetic Resonance Image Diagnosis","volume":"13","author":"Z-H Su","year":"2022","journal-title":"Front Endocrinol (Lausanne)"},{"issue":"2","key":"pone.0327756.ref017","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1097\/RLI.0000000000000709","article-title":"A Deep Learning Model for the Accurate and Reliable Classification of Disc Degeneration Based on MRI Data","volume":"56","author":"F Niemeyer","year":"2020","journal-title":"Invest Radiol"},{"issue":"4","key":"pone.0327756.ref018","doi-asserted-by":"crossref","first-page":"590","DOI":"10.1016\/j.spinee.2019.11.010","article-title":"Spine Explorer: a deep learning based fully automated program for efficient and reliable quantifications of the vertebrae and discs on sagittal lumbar spine MR images","volume":"20","author":"J Huang","year":"2020","journal-title":"Spine J"},{"issue":"4","key":"pone.0327756.ref019","doi-asserted-by":"crossref","first-page":"1841","DOI":"10.1007\/s00330-018-5730-6","article-title":"Comparison of radiomics machine-learning classifiers and feature selection for differentiation of sacral chordoma and sacral giant cell tumour based on 3D computed tomography features","volume":"29","author":"P Yin","year":"2018","journal-title":"Eur Radiol"},{"key":"pone.0327756.ref020","doi-asserted-by":"crossref","first-page":"109586","DOI":"10.1016\/j.ejrad.2021.109586","article-title":"Radiomic Machine Learning Classifiers in Spine Bone Tumors: A Multi-Software, Multi-Scanner Study","volume":"137","author":"V Chianca","year":"2021","journal-title":"Eur J Radiol"},{"issue":"5","key":"pone.0327756.ref021","doi-asserted-by":"crossref","DOI":"10.3171\/2019.2.FOCUS18723","article-title":"Machine learning-based preoperative predictive analytics for lumbar spinal stenosis","volume":"46","author":"A Siccoli","year":"2019","journal-title":"Neurosurg Focus"},{"issue":"8","key":"pone.0327756.ref022","doi-asserted-by":"crossref","first-page":"2176","DOI":"10.1007\/s00586-020-06613-2","article-title":"Artificial intelligence facilitates decision-making in the treatment of lumbar disc herniations","volume":"30","author":"A Wirries","year":"2021","journal-title":"Eur Spine J"},{"issue":"10","key":"pone.0327756.ref023","doi-asserted-by":"crossref","first-page":"1591","DOI":"10.1007\/s11548-018-1818-3","article-title":"Fully automatic cross-modality localization and labeling of vertebral bodies and intervertebral discs in 3D spinal images","volume":"13","author":"M Wimmer","year":"2018","journal-title":"Int J Comput Assist Radiol Surg"},{"key":"pone.0327756.ref024","doi-asserted-by":"crossref","first-page":"115972","DOI":"10.1016\/j.bone.2021.115972","article-title":"A deep learning system for automated, multi-modality 2D segmentation of vertebral bodies and intervertebral discs","volume":"149","author":"A Suri","year":"2021","journal-title":"Bone"},{"key":"pone.0327756.ref025","doi-asserted-by":"crossref","first-page":"1281506","DOI":"10.3389\/fphys.2023.1281506","article-title":"MRI radiomics-based decision support tool for a personalized classification of cervical disc degeneration: a two-center study","volume":"14","author":"J Xie","year":"2024","journal-title":"Front Physiol"},{"key":"pone.0327756.ref026","doi-asserted-by":"crossref","DOI":"10.1016\/j.wneu.2019.03.165","article-title":"Machine Learning for the Prediction of Cervical Spondylotic Myelopathy: A Post Hoc Pilot Study of 28 Participants","volume":"127","author":"BS Hopkins","year":"2019","journal-title":"World Neurosurg"},{"key":"pone.0327756.ref027","doi-asserted-by":"crossref","DOI":"10.1016\/j.wneu.2024.01.072","article-title":"Associating T1-Weighted and T2-Weighted Magnetic Resonance Imaging Radiomic Signatures With Preoperative Symptom Severity in Patients With Cervical Spondylotic Myelopathy","volume":"184","author":"N Alan","year":"2024","journal-title":"World Neurosurgery"},{"issue":"1","key":"pone.0327756.ref028","doi-asserted-by":"crossref","first-page":"15509","DOI":"10.1038\/s41598-022-19770-9","article-title":"A radiomics-based study for differentiating parasellar cavernous hemangiomas from meningiomas","volume":"12","author":"C Wang","year":"2022","journal-title":"Sci Rep"},{"issue":"11","key":"pone.0327756.ref029","doi-asserted-by":"crossref","first-page":"2428","DOI":"10.1002\/jor.24973","article-title":"T2 -weighted magnetic resonance imaging texture as predictor of low back pain: A texture analysis-based classification pipeline to symptomatic and asymptomatic cases","volume":"39","author":"JHJ Ketola","year":"2021","journal-title":"J Orthop Res"},{"issue":"7592","key":"pone.0327756.ref030","doi-asserted-by":"crossref","first-page":"527","DOI":"10.1136\/bmj.39127.608299.80","article-title":"Cervical spondylosis and neck pain","volume":"334","author":"AI Binder","year":"2007","journal-title":"BMJ"},{"issue":"2","key":"pone.0327756.ref031","doi-asserted-by":"crossref","first-page":"1750036","DOI":"10.1142\/S0129065717500368","article-title":"Classification of Diffusion Tensor Metrics for the Diagnosis of a Myelopathic Cord Using Machine Learning","volume":"28","author":"S Wang","year":"2018","journal-title":"Int J Neural Syst"},{"issue":"4","key":"pone.0327756.ref032","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1016\/j.spinee.2022.12.003","article-title":"Diffusion basis spectrum imaging predicts long-term clinical outcomes following surgery in cervical spondylotic myelopathy","volume":"23","author":"JK Zhang","year":"2023","journal-title":"Spine J"},{"key":"pone.0327756.ref033","doi-asserted-by":"crossref","first-page":"108929","DOI":"10.1016\/j.ejrad.2020.108929","article-title":"Machine-learning-based computed tomography radiomic analysis for histologic subtype classification of thymic epithelial tumours","volume":"126","author":"J Hu","year":"2020","journal-title":"Eur J Radiol"},{"issue":"6","key":"pone.0327756.ref034","doi-asserted-by":"crossref","first-page":"4042","DOI":"10.1007\/s00330-020-07483-4","article-title":"MRI-Based radiomics nomogram for differentiation of benign and malignant lesions of the parotid gland","volume":"31","author":"Y Zheng","year":"2020","journal-title":"Eur Radiol"},{"key":"pone.0327756.ref035","doi-asserted-by":"crossref","first-page":"48510","DOI":"10.1109\/ACCESS.2018.2868098","article-title":"Oriented Feature Selection SVM Applied to Cancer Prediction in Precision Medicine","volume":"6","author":"Y Shen","year":"2018","journal-title":"IEEE Access"},{"issue":"4","key":"pone.0327756.ref036","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0300641","article-title":"Data reduction for SVM training using density-based border identification","volume":"19","author":"M Shalaby","year":"2024","journal-title":"PLoS One"},{"key":"pone.0327756.ref037","first-page":"81","author":"MHH Hisham","year":"2023"},{"issue":"4","key":"pone.0327756.ref038","article-title":"Optimal machine learning methods for radiomic prediction models: Clinical application for preoperative T2*-weighted images of cervical spondylotic myelopathy","volume":"4","author":"M-Z Zhang","year":"2021","journal-title":"JOR Spine"},{"issue":"11","key":"pone.0327756.ref039","doi-asserted-by":"crossref","first-page":"3892","DOI":"10.1007\/s00586-023-07887-y","article-title":"MRI-based radiomics assessment of the imminent new vertebral fracture after vertebral augmentation","volume":"32","author":"J Cai","year":"2023","journal-title":"Eur Spine J"},{"key":"pone.0327756.ref040","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.jclinepi.2020.03.005","article-title":"Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury","volume":"122","author":"BY Gravesteijn","year":"2020","journal-title":"J Clin Epidemiol"},{"issue":"12","key":"pone.0327756.ref041","doi-asserted-by":"crossref","first-page":"1565","DOI":"10.1038\/nbt1206-1565","article-title":"What is a support vector machine?","volume":"24","author":"WS Noble","year":"2006","journal-title":"Nat Biotechnol"},{"key":"pone.0327756.ref042","doi-asserted-by":"crossref","first-page":"1657","DOI":"10.2147\/JPR.S138361","article-title":"Characteristics of Modic changes in cervical kyphosis and their association with axial neck pain","volume":"10","author":"Y An","year":"2017","journal-title":"J Pain Res"},{"issue":"5","key":"pone.0327756.ref043","doi-asserted-by":"crossref","first-page":"754","DOI":"10.1016\/j.spinee.2019.11.002","article-title":"Association between Modic changes, disc degeneration, and neck pain in the cervical spine: a systematic review of literature","volume":"20","author":"X Yang","year":"2020","journal-title":"Spine J"},{"issue":"2","key":"pone.0327756.ref044","doi-asserted-by":"crossref","first-page":"1675","DOI":"10.1007\/s10143-021-01698-9","article-title":"Risk factors for the development of degenerative cervical myelopathy: a review of the literature","volume":"45","author":"G Baucher","year":"2022","journal-title":"Neurosurg Rev"},{"issue":"2","key":"pone.0327756.ref045","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1080\/03009734.2017.1319441","article-title":"Anxiety and depression affect pain drawings in cervical degenerative disc disease","volume":"122","author":"A MacDowall","year":"2017","journal-title":"Ups J Med Sci"},{"issue":"1","key":"pone.0327756.ref046","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1038\/nrrheum.2013.160","article-title":"Role of cytokines in intervertebral disc degeneration: pain and disc content","volume":"10","author":"MV Risbud","year":"2014","journal-title":"Nat Rev Rheumatol"},{"key":"pone.0327756.ref047","first-page":"339","article-title":"Cervical spondylotic myelopathy and radiculopathy","volume":"49","author":"E Truumees","year":"2000","journal-title":"Instr Course Lect"},{"issue":"16","key":"pone.0327756.ref048","doi-asserted-by":"crossref","first-page":"1357","DOI":"10.1097\/BRS.0b013e31824ba710","article-title":"Sensory and autonomic innervation of the cervical intervertebral disc in rats: the pathomechanics of chronic discogenic neck pain","volume":"37","author":"K Fujimoto","year":"2012","journal-title":"Spine (Phila Pa 1976)"},{"issue":"1","key":"pone.0327756.ref049","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1097\/00007632-198801000-00002","article-title":"The innervation of the cervical intervertebral discs","volume":"13","author":"N Bogduk","year":"1988","journal-title":"Spine"},{"issue":"2","key":"pone.0327756.ref050","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1136\/ard.28.2.121","article-title":"Disc degeneration. Its frequency and relationship to symptoms","volume":"28","author":"JS Lawrence","year":"1969","journal-title":"Ann Rheum Dis"},{"issue":"8","key":"pone.0327756.ref051","doi-asserted-by":"crossref","first-page":"2335","DOI":"10.1111\/os.13134","article-title":"Morphology of herniated disc as a predictor for outcomes of posterior percutaneous full\u2010endoscopic cervical discectomy in treating cervical spondylotic radiculopathy","volume":"13","author":"Y Liu","year":"2021","journal-title":"Orthopaedic Surgery"}],"container-title":["PLOS One"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0327756","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,9]],"date-time":"2025-07-09T17:35:36Z","timestamp":1752082536000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0327756"}},"subtitle":[],"editor":[{"given":"Aloysius Gonzaga","family":"Mubuuke","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2025,7,9]]},"references-count":51,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2025,7,9]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pone.0327756","relation":{},"ISSN":["1932-6203"],"issn-type":[{"value":"1932-6203","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,9]]}}}