{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,3]],"date-time":"2026-11-03T04:25:39Z","timestamp":1793679939068,"version":"4.5.1"},"reference-count":25,"publisher":"SAGE Publications","issue":"8","license":[{"start":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T00:00:00Z","timestamp":1777334400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T00:00:00Z","timestamp":1777334400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"Quick Win Project of the Ratchadapiseksompoch Fund, Chulalongkorn University","award":["767006"],"award-info":[{"award-number":["767006"]}],"id":[{"id":"https:\/\/ror.org\/028wp3y58","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Global Spine Journal"],"published-print":{"date-parts":[[2026,11]]},"abstract":"<jats:sec>\n                    <jats:title>Study Design<\/jats:title>\n                    <jats:p>Retrospective validation study.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>To develop and validate VerteRo, a fully automated deep learning-based tool that estimates axial vertebral body rotation (VBR) from standard posteroanterior (PA) scoliosis radiographs with high accuracy, overcoming the limitations of categorical grading systems.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A multi-stage convolutional neural network pipeline incorporating automated region-of-interest (ROI) extraction, vertebral segmentation, pedicle localization, and geometric rotation estimation was trained on 97 AIS radiographs. Three object detection architectures (Faster R-CNN, YOLOv11\u00a0L, YOLOv12\u00a0L) were evaluated. The mean absolute error (MAE) relative to Stokes-derived reference angles was measured as the primary outcome and concordance with Nash\u2013Moe grading was measured as the secondary outcome.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Faster R-CNN demonstrated superior pedicle detection (F1 = 0.93) compared with YOLOv11\u00a0L and YOLOv12\u00a0L. VerteRo achieved a mean absolute error of 8.239\u00b0 relative to reference standards. 71.34% of vertebrae demonstrated exact grade agreement with the Nash\u2013Moe grading system.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This pilot study provides a proof-of-concept for a fully automated, end-to-end solution for quantitative axial rotation assessment from PA radiographs, offering improved objectivity over categorical grading methods. Its ability to generate quantitative axial rotation measures rather than coarse categorical grades has strong potential for supporting research applications and potential decision-support in clinical assessment following further validation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/21925682261448826","type":"journal-article","created":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T00:38:06Z","timestamp":1777423086000},"page":"3918-3926","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["VerteRo: A Fully Automated Deep Neural Network Tool for Estimating Axial Vertebral Body Rotation in Adolescent Idiopathic Scoliosis"],"prefix":"10.1177","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9593-429X","authenticated-orcid":false,"given":"Vit","family":"Kotheeranurak","sequence":"first","affiliation":[{"name":"Chulalongkorn University,"},{"name":"Chulalongkorn University,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-5550-3995","authenticated-orcid":false,"given":"Sompoom","family":"Sunpaweravong","sequence":"additional","affiliation":[{"name":"Chulalongkorn University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-3647-2660","authenticated-orcid":false,"given":"Kittanate","family":"Pongyanpat","sequence":"additional","affiliation":[{"name":"Chulalongkorn University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-8032-0079","authenticated-orcid":false,"given":"Jiraphat","family":"Thanasuttiwat","sequence":"additional","affiliation":[{"name":"Chulalongkorn University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-9573-875X","authenticated-orcid":false,"given":"Surachat","family":"Jaroenwareekul","sequence":"additional","affiliation":[{"name":"Chulalongkorn University,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0095-6697","authenticated-orcid":false,"given":"Thanita","family":"Panya-amornwat","sequence":"additional","affiliation":[{"name":"Rajavithi Hospital"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7166-1381","authenticated-orcid":false,"given":"Weerasak","family":"Singhatanadgige","sequence":"additional","affiliation":[{"name":"Chulalongkorn University,"},{"name":"Chulalongkorn University,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0116-8791","authenticated-orcid":false,"given":"Worawat","family":"Limthongkul","sequence":"additional","affiliation":[{"name":"Chulalongkorn University,"},{"name":"Chulalongkorn University,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3852-9092","authenticated-orcid":false,"given":"Sittisak","family":"Honsawek","sequence":"additional","affiliation":[{"name":"Department of Biochemistry, Faculty of Medicine, Chulalongkorn University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8306-2212","authenticated-orcid":false,"given":"Rajalida","family":"Lipikorn","sequence":"additional","affiliation":[{"name":"Chulalongkorn University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,4,28]]},"reference":[{"key":"e_1_3_4_2_2","doi-asserted-by":"publisher","DOI":"10.2174\/1874325001610010143"},{"key":"e_1_3_4_3_2","doi-asserted-by":"publisher","DOI":"10.1186\/1748-7161-3-16"},{"key":"e_1_3_4_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.prrv.2006.04.009"},{"key":"e_1_3_4_5_2","doi-asserted-by":"publisher","DOI":"10.1093\/pch\/12.9.771"},{"key":"e_1_3_4_6_2","doi-asserted-by":"publisher","DOI":"10.18999\/nagjms.85.2.333"},{"key":"e_1_3_4_7_2","doi-asserted-by":"publisher","DOI":"10.1097\/BRS.0b013e3181cdde47"},{"key":"e_1_3_4_8_2","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph13111057"},{"key":"e_1_3_4_9_2","doi-asserted-by":"publisher","DOI":"10.2174\/1874325001711011500"},{"key":"e_1_3_4_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/0021-9290(84)90005-8"},{"key":"e_1_3_4_11_2","doi-asserted-by":"publisher","DOI":"10.1097\/00007632-198604000-00006"},{"key":"e_1_3_4_12_2","doi-asserted-by":"publisher","DOI":"10.1097\/00007632-198511000-00001"},{"key":"e_1_3_4_13_2","first-page":"243","volume-title":"Studies in Health Technology and Informatics: Three-Dimensional Analysis of Spinal Deformities","author":"Weiss HR","year":"1995","unstructured":"Weiss HR. 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