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Administration of Traditional Chinese Medicine of Guangdong Province of China","award":["82302035"],"award-info":[{"award-number":["82302035"]}]},{"name":"National Natural Science Foundation of China","award":["2023K0604"],"award-info":[{"award-number":["2023K0604"]}]},{"name":"National Natural Science Foundation of China","award":["2022A0505020019"],"award-info":[{"award-number":["2022A0505020019"]}]},{"name":"National Natural Science Foundation of China","award":["0056\/2021\/AGJ"],"award-info":[{"award-number":["0056\/2021\/AGJ"]}]},{"name":"National Natural Science Foundation of China","award":["AM2023022"],"award-info":[{"award-number":["AM2023022"]}]},{"name":"National Natural Science Foundation of China","award":["pdjh2023b0011"],"award-info":[{"award-number":["pdjh2023b0011"]}]},{"name":"National Natural Science Foundation of China","award":["20241046"],"award-info":[{"award-number":["20241046"]}]},{"name":"National Natural Science Foundation of China","award":["82302035"],"award-info":[{"award-number":["82302035"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Bioengineering"],"abstract":"<jats:p>Objective: This study aims to apply different deep learning convolutional neural network algorithms to assess the grading of cervical spinal stenosis and to evaluate their consistency with clinician grading results as well as clinical manifestations of patients. Methods: We retrospectively enrolled 954 patients with cervical spine magnetic resonance imaging (MRI) data and medical records from the Fifth Affiliated Hospital of Sun-Yat Sen University. The Kang grading method for sagittal MR images of the cervical spine and the spinal cord compression ratio for horizontal MR images of the cervical spine were adopted for cervical spinal canal stenosis grading. The collected data were randomly divided into training\/validation and test sets. The training\/validation sets were processed by various image preprocessing and annotation methods, in which deep learning convolutional networks, including classification, target detection, and key point localization models, were applied. The predictive grading of the test set by the model was finally contrasted with the grading results of the clinicians, and correlation analysis was performed with the clinical manifestations of the patients. Result: The EfficientNet_B5 model achieved a five-fold cross-validated accuracy of 79.45% and near-perfect agreement with clinician grading on the test set (\u03ba= 0.848, 0.822), surpassing resident\u2013clinician consistency (\u03ba = 0.732, 0.702). The model-derived compression ratio (0.45 \u00b1 0.07) did not differ significantly from manual measurements (0.46 \u00b1 0.07). Correlation analysis showed moderate associations between model outputs and clinical symptoms: EfficientNet_B5 grades (r = 0.526) were comparable to clinician assessments (r = 0.517, 0.503) and higher than those of residents (r = 0.457, 0.448). Conclusion: CNN models demonstrate strong performance in the objective, consistent, and efficient grading of cervical spinal stenosis severity, offering potential clinical value in automated diagnostic support.<\/jats:p>","DOI":"10.3390\/bioengineering12060604","type":"journal-article","created":{"date-parts":[[2025,6,2]],"date-time":"2025-06-02T11:40:32Z","timestamp":1748864432000},"page":"604","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Deep-Learning-Based Computer-Aided Grading of Cervical Spinal Stenosis from MR Images: Accuracy and Clinical Alignment"],"prefix":"10.3390","volume":"12","author":[{"given":"Zhiling","family":"Wang","sequence":"first","affiliation":[{"name":"Fifth Affiliated Hospital of Sun Yat-sen University, Department of Spinal Surgery, 52 East Meihua Rd, Xiangzhou, Zhuhai 519000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinquan","family":"Chen","sequence":"additional","affiliation":[{"name":"Fifth Affiliated Hospital of Sun Yat-sen University, Department of Spinal Surgery, 52 East Meihua Rd, Xiangzhou, Zhuhai 519000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Liu","sequence":"additional","affiliation":[{"name":"Fifth Affiliated Hospital of Sun Yat-sen University, Department of Spinal Surgery, 52 East Meihua Rd, Xiangzhou, Zhuhai 519000, China"},{"name":"Department of Orthopedics, The First Affiliated Hospital of Jinan University, Guangzhou 510630, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinjin","family":"Hai","sequence":"additional","affiliation":[{"name":"Henan Key Laboratory of Imaging and Intelligence Processing, Information Engineering University, Zhengzhou 450001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kai","family":"Qiao","sequence":"additional","affiliation":[{"name":"Henan Key Laboratory of Imaging and Intelligence Processing, Information Engineering University, Zhengzhou 450001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3061-6263","authenticated-orcid":false,"given":"Zhen","family":"Yuan","sequence":"additional","affiliation":[{"name":"Faculty of Health Sciences, University of Macau, Taipa, Macau 999078, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lianjun","family":"Yang","sequence":"additional","affiliation":[{"name":"Fifth Affiliated Hospital of Sun Yat-sen University, Department of Spinal Surgery, 52 East Meihua Rd, Xiangzhou, Zhuhai 519000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Yan","sequence":"additional","affiliation":[{"name":"Henan Key Laboratory of Imaging and Intelligence Processing, Information Engineering University, Zhengzhou 450001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0355-1129","authenticated-orcid":false,"given":"Zhihai","family":"Su","sequence":"additional","affiliation":[{"name":"Fifth Affiliated Hospital of Sun Yat-sen University, Department of Spinal Surgery, 52 East Meihua Rd, Xiangzhou, Zhuhai 519000, China"},{"name":"Faculty of Health Sciences, University of Macau, Taipa, Macau 999078, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4212-3282","authenticated-orcid":false,"given":"Hai","family":"Lu","sequence":"additional","affiliation":[{"name":"Fifth Affiliated Hospital of Sun Yat-sen University, Department of Spinal Surgery, 52 East Meihua Rd, Xiangzhou, Zhuhai 519000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,6,1]]},"reference":[{"key":"ref_1","unstructured":"Russell, S.J., and Norvig, P. 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