{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T17:31:46Z","timestamp":1781803906803,"version":"3.54.5"},"reference-count":36,"publisher":"Journal of Neurosurgery Publishing Group (JNSPG)","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,9,1]]},"abstract":"<jats:sec>\n                    <jats:title>OBJECTIVE<\/jats:title>\n                    <jats:p>Neurosurgical evaluation is required in the setting of spinal metastases at high risk for leading to a vertebral body fracture. Both irradiated and nonirradiated vertebrae are affected. Understanding fracture risk is critical in determining management, including follow-up timing and prophylactic interventions. Herein, the authors report the results of a machine learning model that predicts the development or progression of a pathological vertebral compression fracture (VCF) in metastatic tumor\u2013infiltrated thoracolumbar vertebrae in an all-comer population.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>A multi-institutional all-comer cohort of patients with tumor containing vertebral levels spanning T1 through L5 and at least 1 year of follow-up was included in the study. Clinical features of the patients, diseases, and treatments were collected. CT radiomic features of the vertebral bodies were extracted from tumor-infiltrated vertebrae that did or did not subsequently fracture or progress. Recursive feature elimination (RFE) of both radiomic and clinical features was performed. The resulting features were used to create a purely clinical model, purely radiomic model, and combined clinical-radiomic model. A Spine Instability Neoplastic Score (SINS) model was created for a baseline performance comparison. Model performance was assessed using the area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity (with 95% confidence intervals) with tenfold cross-validation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>Within 1 year from initial CT, 123 of 977 vertebrae developed VCF. Selected clinical features included SINS, SINS component for &lt; 50% vertebral body collapse, SINS component for \"none of the prior 3\" (i.e., \"none of the above\" on the SINS component for vertebral body involvement), histology, age, and BMI. Of the 2015 radiomic features, RFE selected 19 to be used in the pure radiomic model and the combined clinical-radiomic model. The best performing model was a random forest classifier using both clinical and radiomic features, demonstrating an AUROC of 0.86 (95% CI 0.82\u20130.9), sensitivity of 0.78 (95% CI 0.70\u20130.84), and specificity of 0.80 (95% CI 0.77\u20130.82). This performance was significantly higher than the best SINS-alone model (AUROC 0.75, 95% CI 0.70\u20130.80) and outperformed the clinical-only model but not in a statistically significant manner (AUROC 0.82, 95% CI 0.77\u20130.87).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSIONS<\/jats:title>\n                    <jats:p>The authors developed a clinically generalizable machine learning model to predict the risk of a new or progressing VCF in an all-comer population. This model addresses limitations from prior work and was trained on the largest cohort of patients and vertebrae published to date. If validated, the model could lead to more consistent and systematic identification of high-risk vertebrae, resulting in faster, more accurate triage of patients for optimal management.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3171\/2025.2.spine24872","type":"journal-article","created":{"date-parts":[[2025,6,20]],"date-time":"2025-06-20T21:16:49Z","timestamp":1750454209000},"page":"273-282","source":"Crossref","is-referenced-by-count":1,"title":["Generalizable model to predict new or progressing compression fractures in tumor-infiltrated thoracolumbar vertebrae in an all-comer population"],"prefix":"10.3171","volume":"43","author":[{"given":"Alex","family":"Flores","sequence":"first","affiliation":[{"name":"Department of Neurosurgery,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vijay","family":"Nitturi","sequence":"additional","affiliation":[{"name":"Baylor College of Medicine, Houston; and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arman","family":"Kavoussi","sequence":"additional","affiliation":[{"name":"Baylor College of Medicine, Houston; and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Max","family":"Feygin","sequence":"additional","affiliation":[{"name":"Baylor College of Medicine, Houston; and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Romulo A.","family":"Andrade de Almeida","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Esteban","family":"Ramirez Ferrer","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adrish","family":"Anand","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shervin","family":"Nouri","sequence":"additional","affiliation":[{"name":"Baylor College of Medicine, Houston; and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anthony K.","family":"Allam","sequence":"additional","affiliation":[{"name":"Baylor College of Medicine, Houston; and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ashley","family":"Ricciardelli","sequence":"additional","affiliation":[{"name":"Baylor College of Medicine, Houston; and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gabriel","family":"Reyes","sequence":"additional","affiliation":[{"name":"Baylor College of Medicine, Houston; and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sandy","family":"Reddy","sequence":"additional","affiliation":[{"name":"Baylor College of Medicine, Houston; and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ihika","family":"Rampalli","sequence":"additional","affiliation":[{"name":"Baylor College of Medicine, Houston; and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laurence","family":"Rhines","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Claudio E.","family":"Tatsui","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert Y.","family":"North","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amol","family":"Ghia","sequence":"additional","affiliation":[{"name":"Radiation Oncology, and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeffrey H.","family":"Siewerdsen","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery,"},{"name":"Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexander E.","family":"Ropper","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher","family":"Alvarez-Breckenridge","sequence":"additional","affiliation":[{"name":"Departments of Neurosurgery,"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1754","reference":[{"issue":"1)(suppl 1","key":"b1","series-title":"Neurooncol Pract","first-page":"i5","article-title":"Epidemiology of spinal cord and column tumors","volume":"7","author":"Wewel JT","year":"2020","unstructured":"Wewel JT, O\u2019Toole JE. Epidemiology of spinal cord and column tumors. Neurooncol Pract. 2020;7(1)(suppl 1):i5\u2013i9."},{"key":"b2","article-title":"National Center for Health Statistics","author":"Cancer deaths","unstructured":"Cancer deaths. National Center for Health Statistics. Updated June 2023. Accessed March 26, 2025. https:\/\/www.cdc.gov\/nchs\/hus\/topics\/cancer-deaths.htm"},{"issue":"7","key":"b3","series-title":"J Bone Joint Surg Am","first-page":"1479","article-title":"Mortality following the diagnosis of a vertebral compression fracture in the Medicare population","volume":"90","author":"Lau E","year":"2008","unstructured":"Lau E, Ong K, Kurtz S, Schmier J, Edidin A. Mortality following the diagnosis of a vertebral compression fracture in the Medicare population. J Bone Joint Surg Am. 2008;90(7):1479\u20131486."},{"issue":"22","key":"b4","series-title":"Spine (Phila Pa 1976).","first-page":"E1221","article-title":"A novel classification system for spinal instability in neoplastic disease: an evidence-based approach and expert consensus from the Spine Oncology Study Group","volume":"35","author":"Fisher CG","year":"2010","unstructured":"Fisher CG, DiPaola CP, Ryken TC,  A novel classification system for spinal instability in neoplastic disease: an evidence-based approach and expert consensus from the Spine Oncology Study Group. Spine (Phila Pa 1976).2010;35(22):E1221\u2013E1229."},{"issue":"3","key":"b5","series-title":"Spine (Phila Pa 1976).","first-page":"298","article-title":"Surgical strategy for spinal metastases","volume":"26","author":"Tomita K","year":"2001","unstructured":"Tomita K, Kawahara N, Kobayashi T, Yoshida A, Murakami H, Akamaru T. Surgical strategy for spinal metastases. Spine (Phila Pa 1976).2001;26(3):298\u2013306."},{"issue":"2","key":"b6","series-title":"J Neurosurg Spine","first-page":"294","article-title":"Radiomic modeling to predict risk of vertebral compression fracture after stereotactic body radiation therapy for spinal metastases","volume":"36","author":"Gui C","year":"2021","unstructured":"Gui C, Chen X, Sheikh K,  Radiomic modeling to predict risk of vertebral compression fracture after stereotactic body radiation therapy for spinal metastases. J Neurosurg Spine. 2021;36(2):294\u2013302."},{"key":"b7","article-title":"Cement augmentation in preventing vertebral body compression fracture following spine stereotactic radiosurgery in patients with solid tumors and spinal metastases","unstructured":"Cement augmentation in preventing vertebral body compression fracture following spine stereotactic radiosurgery in patients with solid tumors and spinal metastases. Accessed March 26, 2025. https:\/\/clinicaltrials.gov\/study\/NCT02387905"},{"issue":"1","key":"b8","series-title":"J Clin Oncol","first-page":"38","article-title":"Prophylactic radiation therapy versus standard of care for patients with high-risk asymptomatic bone metastases: a multicenter, randomized Phase II clinical trial","volume":"42","author":"Gillespie EF","year":"2024","unstructured":"Gillespie EF, Yang JC, Mathis NJ,  Prophylactic radiation therapy versus standard of care for patients with high-risk asymptomatic bone metastases: a multicenter, randomized Phase II clinical trial. J Clin Oncol. 2024;42(1):38\u201346."},{"issue":"8","key":"b9","series-title":"Eur Spine J","first-page":"3221","article-title":"Predicting vertebral compression fracture prior to spinal SBRT using radiomics from planning CT","volume":"33","author":"Seol Y","year":"2024","unstructured":"Seol Y, Song JH, Choi KH, Lee YK, Choi BO, Kang YN. Predicting vertebral compression fracture prior to spinal SBRT using radiomics from planning CT. Eur Spine J. 2024;33(8):3221\u20133229."},{"issue":"9","key":"b10","series-title":"Magn Reson Imaging","first-page":"1323","article-title":"3D Slicer as an image computing platform for the Quantitative Imaging Network","volume":"30","author":"Fedorov A","year":"2012","unstructured":"Fedorov A, Beichel R, Kalpathy-Cramer J,  3D Slicer as an image computing platform for the Quantitative Imaging Network. Magn Reson Imaging. 2012;30(9):1323\u20131341."},{"issue":"3","key":"b11","series-title":"Neuroimage","first-page":"1116","article-title":"User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability","volume":"31","author":"Yushkevich PA","year":"2006","unstructured":"Yushkevich PA, Piven J, Hazlett HC,  User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage. 2006;31(3):1116\u20131128."},{"issue":"21","key":"b12","series-title":"Cancer Res","first-page":"e104","article-title":"Computational radiomics system to decode the radiographic phenotype","volume":"77","author":"van Griethuysen JJM","year":"2017","unstructured":"van Griethuysen JJM, Fedorov A, Parmar C,  Computational radiomics system to decode the radiographic phenotype. Cancer Res. 2017;77(21):e104\u2013e107."},{"issue":"5","key":"b13","series-title":"J Biomech","first-page":"453","article-title":"Ultimate strength of the lumbar spine in flexion\u2014an in vitro study","volume":"23","author":"Osvalder AL","year":"1990","unstructured":"Osvalder AL, Neumann P, L\u00f6vsund P, Nordwall A. Ultimate strength of the lumbar spine in flexion\u2014an in vitro study. J Biomech. 1990;23(5):453\u2013460."},{"issue":"9","key":"b14","series-title":"AJNR Am J Neuroradiol","first-page":"1605","article-title":"Metastatic spinal lesions: state-of-the-art treatment options and future trends","volume":"29","author":"Georgy BA","year":"2008","unstructured":"Georgy BA. Metastatic spinal lesions: state-of-the-art treatment options and future trends. AJNR Am J Neuroradiol. 2008;29(9):1605\u20131611."},{"issue":"7","key":"b15","series-title":"Am J Surg Pathol","first-page":"745","article-title":"Primary melanocytic neoplasms of the central nervous systems","volume":"23","author":"Brat DJ","year":"1999","unstructured":"Brat DJ, Giannini C, Scheithauer BW, Burger PC. Primary melanocytic neoplasms of the central nervous systems. Am J Surg Pathol. 1999;23(7):745\u2013754."},{"key":"b16","series-title":"Bone.","first-page":"116028","article-title":"Type, size, and position of metastatic lesions explain the deformation of the vertebrae under complex loading conditions","volume":"151","author":"Palanca M","year":"2021","unstructured":"Palanca M, Barbanti-Br\u00f2dano G, Marras D,  Type, size, and position of metastatic lesions explain the deformation of the vertebrae under complex loading conditions. Bone.2021;151:116028."},{"key":"b17","series-title":"Bone.","first-page":"116814","article-title":"The role of bone metastases on the mechanical competence of human vertebrae","volume":"173","author":"Palanca M","year":"2023","unstructured":"Palanca M, Cavazzoni G, Dall\u2019Ara E. The role of bone metastases on the mechanical competence of human vertebrae. Bone.2023;173:116814."},{"issue":"1","key":"b18","series-title":"Eur Radiol Exp","first-page":"40","article-title":"The effect of preprocessing filters on predictive performance in radiomics","volume":"6","author":"Demircio\u011flu A","year":"2022","unstructured":"Demircio\u011flu A. The effect of preprocessing filters on predictive performance in radiomics. Eur Radiol Exp. 2022;6(1):40."},{"issue":"1)(suppl 1","key":"b1","series-title":"Neurooncol Pract","first-page":"i5","article-title":"Epidemiology of spinal cord and column tumors","volume":"7","author":"Wewel JT","year":"2020","unstructured":"Wewel JT, O\u2019Toole JE. Epidemiology of spinal cord and column tumors. Neurooncol Pract. 2020;7(1)(suppl 1):i5\u2013i9."},{"key":"b2","article-title":"National Center for Health Statistics","author":"Cancer deaths","unstructured":"Cancer deaths. National Center for Health Statistics. Updated June 2023. Accessed March 26, 2025. https:\/\/www.cdc.gov\/nchs\/hus\/topics\/cancer-deaths.htm"},{"issue":"7","key":"b3","series-title":"J Bone Joint Surg Am","first-page":"1479","article-title":"Mortality following the diagnosis of a vertebral compression fracture in the Medicare population","volume":"90","author":"Lau E","year":"2008","unstructured":"Lau E, Ong K, Kurtz S, Schmier J, Edidin A. Mortality following the diagnosis of a vertebral compression fracture in the Medicare population. J Bone Joint Surg Am. 2008;90(7):1479\u20131486."},{"issue":"22","key":"b4","series-title":"Spine (Phila Pa 1976).","first-page":"E1221","article-title":"A novel classification system for spinal instability in neoplastic disease: an evidence-based approach and expert consensus from the Spine Oncology Study Group","volume":"35","author":"Fisher CG","year":"2010","unstructured":"Fisher CG, DiPaola CP, Ryken TC,  A novel classification system for spinal instability in neoplastic disease: an evidence-based approach and expert consensus from the Spine Oncology Study Group. Spine (Phila Pa 1976).2010;35(22):E1221\u2013E1229."},{"issue":"3","key":"b5","series-title":"Spine (Phila Pa 1976).","first-page":"298","article-title":"Surgical strategy for spinal metastases","volume":"26","author":"Tomita K","year":"2001","unstructured":"Tomita K, Kawahara N, Kobayashi T, Yoshida A, Murakami H, Akamaru T. Surgical strategy for spinal metastases. Spine (Phila Pa 1976).2001;26(3):298\u2013306."},{"issue":"2","key":"b6","series-title":"J Neurosurg Spine","first-page":"294","article-title":"Radiomic modeling to predict risk of vertebral compression fracture after stereotactic body radiation therapy for spinal metastases","volume":"36","author":"Gui C","year":"2021","unstructured":"Gui C, Chen X, Sheikh K,  Radiomic modeling to predict risk of vertebral compression fracture after stereotactic body radiation therapy for spinal metastases. J Neurosurg Spine. 2021;36(2):294\u2013302."},{"key":"b7","article-title":"Cement augmentation in preventing vertebral body compression fracture following spine stereotactic radiosurgery in patients with solid tumors and spinal metastases","unstructured":"Cement augmentation in preventing vertebral body compression fracture following spine stereotactic radiosurgery in patients with solid tumors and spinal metastases. Accessed March 26, 2025. https:\/\/clinicaltrials.gov\/study\/NCT02387905"},{"issue":"1","key":"b8","series-title":"J Clin Oncol","first-page":"38","article-title":"Prophylactic radiation therapy versus standard of care for patients with high-risk asymptomatic bone metastases: a multicenter, randomized Phase II clinical trial","volume":"42","author":"Gillespie EF","year":"2024","unstructured":"Gillespie EF, Yang JC, Mathis NJ,  Prophylactic radiation therapy versus standard of care for patients with high-risk asymptomatic bone metastases: a multicenter, randomized Phase II clinical trial. J Clin Oncol. 2024;42(1):38\u201346."},{"issue":"8","key":"b9","series-title":"Eur Spine J","first-page":"3221","article-title":"Predicting vertebral compression fracture prior to spinal SBRT using radiomics from planning CT","volume":"33","author":"Seol Y","year":"2024","unstructured":"Seol Y, Song JH, Choi KH, Lee YK, Choi BO, Kang YN. Predicting vertebral compression fracture prior to spinal SBRT using radiomics from planning CT. Eur Spine J. 2024;33(8):3221\u20133229."},{"issue":"9","key":"b10","series-title":"Magn Reson Imaging","first-page":"1323","article-title":"3D Slicer as an image computing platform for the Quantitative Imaging Network","volume":"30","author":"Fedorov A","year":"2012","unstructured":"Fedorov A, Beichel R, Kalpathy-Cramer J,  3D Slicer as an image computing platform for the Quantitative Imaging Network. Magn Reson Imaging. 2012;30(9):1323\u20131341."},{"issue":"3","key":"b11","series-title":"Neuroimage","first-page":"1116","article-title":"User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability","volume":"31","author":"Yushkevich PA","year":"2006","unstructured":"Yushkevich PA, Piven J, Hazlett HC,  User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage. 2006;31(3):1116\u20131128."},{"issue":"21","key":"b12","series-title":"Cancer Res","first-page":"e104","article-title":"Computational radiomics system to decode the radiographic phenotype","volume":"77","author":"van Griethuysen JJM","year":"2017","unstructured":"van Griethuysen JJM, Fedorov A, Parmar C,  Computational radiomics system to decode the radiographic phenotype. Cancer Res. 2017;77(21):e104\u2013e107."},{"issue":"5","key":"b13","series-title":"J Biomech","first-page":"453","article-title":"Ultimate strength of the lumbar spine in flexion\u2014an in vitro study","volume":"23","author":"Osvalder AL","year":"1990","unstructured":"Osvalder AL, Neumann P, L\u00f6vsund P, Nordwall A. Ultimate strength of the lumbar spine in flexion\u2014an in vitro study. J Biomech. 1990;23(5):453\u2013460."},{"issue":"9","key":"b14","series-title":"AJNR Am J Neuroradiol","first-page":"1605","article-title":"Metastatic spinal lesions: state-of-the-art treatment options and future trends","volume":"29","author":"Georgy BA","year":"2008","unstructured":"Georgy BA. Metastatic spinal lesions: state-of-the-art treatment options and future trends. AJNR Am J Neuroradiol. 2008;29(9):1605\u20131611."},{"issue":"7","key":"b15","series-title":"Am J Surg Pathol","first-page":"745","article-title":"Primary melanocytic neoplasms of the central nervous systems","volume":"23","author":"Brat DJ","year":"1999","unstructured":"Brat DJ, Giannini C, Scheithauer BW, Burger PC. Primary melanocytic neoplasms of the central nervous systems. Am J Surg Pathol. 1999;23(7):745\u2013754."},{"key":"b16","series-title":"Bone.","first-page":"116028","article-title":"Type, size, and position of metastatic lesions explain the deformation of the vertebrae under complex loading conditions","volume":"151","author":"Palanca M","year":"2021","unstructured":"Palanca M, Barbanti-Br\u00f2dano G, Marras D,  Type, size, and position of metastatic lesions explain the deformation of the vertebrae under complex loading conditions. Bone.2021;151:116028."},{"key":"b17","series-title":"Bone.","first-page":"116814","article-title":"The role of bone metastases on the mechanical competence of human vertebrae","volume":"173","author":"Palanca M","year":"2023","unstructured":"Palanca M, Cavazzoni G, Dall\u2019Ara E. The role of bone metastases on the mechanical competence of human vertebrae. Bone.2023;173:116814."},{"issue":"1","key":"b18","series-title":"Eur Radiol Exp","first-page":"40","article-title":"The effect of preprocessing filters on predictive performance in radiomics","volume":"6","author":"Demircio\u011flu A","year":"2022","unstructured":"Demircio\u011flu A. The effect of preprocessing filters on predictive performance in radiomics. Eur Radiol Exp. 2022;6(1):40."}],"container-title":["Journal of Neurosurgery: Spine"],"original-title":[],"link":[{"URL":"https:\/\/thejns.org\/view\/journals\/j-neurosurg-spine\/43\/3\/article-p273.xml","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/thejns.org\/downloadpdf\/journals\/j-neurosurg-spine\/43\/3\/article-p273.xml","content-type":"text\/html","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/thejns.org\/downloadpdf\/journals\/j-neurosurg-spine\/43\/3\/article-p273.xml","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T13:44:06Z","timestamp":1772804646000},"score":1,"resource":{"primary":{"URL":"https:\/\/thejns.org\/view\/journals\/j-neurosurg-spine\/43\/3\/article-p273.xml"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,1]]},"references-count":36,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.3171\/2025.2.spine24872","relation":{},"ISSN":["1547-5654"],"issn-type":[{"value":"1547-5654","type":"print"}],"subject":[],"published":{"date-parts":[[2025,9,1]]}}}