{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T01:11:03Z","timestamp":1778202663919,"version":"3.51.4"},"reference-count":42,"publisher":"The Korean Spinal Neurosurgery Society","issue":"2","license":[{"start":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T00:00:00Z","timestamp":1777507200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/3.0\/"}],"content-domain":{"domain":["e-neurospine.org"],"crossmark-restriction":true},"short-container-title":["NS"],"published-print":{"date-parts":[[2026,4,30]]},"abstract":"<jats:p>Objective: To develop and externally validate a dual-mechanism deep learning (DL) model that integrates vertebral segmentation and lesion detection for automated evaluation of lumbar degeneration and structured report generation on plain radiographs.Methods: In this retrospective study, 5,964 patients who underwent standing anteroposterior and lateral lumbar radiographs at a single institution and 600 patients from a public dataset (BUU-Spine) were included. Vertebral corners from T11\u2013L5 (and S1 on lateral views) and 7 degenerative findings (scoliosis, straightened\/preserved lordosis, spondylolisthesis, disc space narrowing, osteophytes, vertebral compression, and abdominal aortic calcification) were annotated by 3 spine surgeons. Two independently trained, parallel networks were developed, including a ResNet-based segmentation network and a YOLOv8-based detection network. A rule-based integration strategy reconciled both outputs and generated structured diagnostic reports. Segmentation accuracy, quantitative measurement agreement, diagnostic performance, and clinical acceptability of reports were evaluated.Results: Intra- and interobserver landmark distances within 3 mm reached 96% and &gt;95%, respectively. On the internal test set, the percentage of correct keypoints within 3 mm was 95.7%\u201398.6%, with intraclass correlation coefficients of 0.84\u20130.89 and Pearson correlation coefficient (r) of 0.90\u20130.94 for key radiographic parameters. The segmentation- and detection-based models achieved precision of 92.2%\u201396.9% and 91.7%\u201395.5%, and recall of 91.6%\u201394.8% and 93.3%\u201395.2%, respectively. Under the dual-positive condition, the integrated model yielded the highest precision (93.8%\u201397.3%), whereas the any-positive condition achieved the highest recall (94.1%\u201397.6%). Of 596 automatically generated structured reports, 557 (93.4%) were deemed clinically acceptable.Conclusion: The proposed dual-mechanism DL framework enables accurate, multilesion assessment of lumbar degeneration and generation of clinically acceptable structured reports from plain radiographs, supporting workflow optimization in lumbar spine imaging.<\/jats:p>","DOI":"10.14245\/ns.2551672.836","type":"journal-article","created":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T00:07:03Z","timestamp":1777421223000},"page":"393-403","update-policy":"https:\/\/doi.org\/10.14245\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deep Learning-Assisted Lumbar Degeneration Evaluation Using Plain Radiographs: Development and Validation of a Novel Dual-Mechanism Architecture"],"prefix":"10.14245","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1245-378X","authenticated-orcid":true,"given":"Ziqian","family":"Ma","sequence":"first","affiliation":[{"name":"Department of Orthopedics, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3271-1953","authenticated-orcid":true,"given":"Aobo","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Orthopedics, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-4716-9968","authenticated-orcid":true,"given":"Xingyu","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Life Sciences, Tsinghua University, Beijing, China"},{"name":"Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China"},{"name":"Institute of Biomedical and Health Engineering (iBHE), Tsinghua Shenzhen International Graduate School, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-0745-4427","authenticated-orcid":true,"given":"Ruiyuan","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Orthopedics, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5016-858X","authenticated-orcid":true,"given":"Tianyi","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Orthopedics, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-3022-9281","authenticated-orcid":true,"given":"Yu","family":"Xi","sequence":"additional","affiliation":[{"name":"Department of Orthopedics, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-4010-0243","authenticated-orcid":true,"given":"Minghui","family":"Liang","sequence":"additional","affiliation":[{"name":"Department of Orthopedics, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0095-9476","authenticated-orcid":true,"given":"Ning","family":"Fan","sequence":"additional","affiliation":[{"name":"Department of Orthopedics, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5668-9527","authenticated-orcid":true,"given":"Shuo","family":"Yuan","sequence":"additional","affiliation":[{"name":"Department of Orthopedics, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5017-8507","authenticated-orcid":true,"given":"Peng","family":"Du","sequence":"additional","affiliation":[{"name":"Department of Orthopedics, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0242-8484","authenticated-orcid":true,"given":"Dong","family":"Liu","sequence":"additional","affiliation":[{"name":"Longwood Valley Medical Technology Co. 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