{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T03:13:32Z","timestamp":1787022812062,"version":"build-2736575974"},"reference-count":110,"publisher":"Bioscientifica","issue":"7","license":[{"start":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T00:00:00Z","timestamp":1770854400000},"content-version":"vor","delay-in-days":226,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"Hunan Provincial Health Commission","award":["202204072756"],"award-info":[{"award-number":["202204072756"]}]}],"content-domain":{"domain":["journals.bioscientifica.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,7,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>While conventional structural magnetic resonance imaging (MRI) can detect cruciate ligament anatomy and injuries, it has inherent limitations. Recently, novel MRI technologies such as quantitative MRI and artificial intelligence (AI) have emerged to mitigate these shortcomings, providing critical quantitative insights beyond gross morphological imaging and poised to expand current knowledge in assessing cruciate ligament injuries and to facilitate clinical decision making. Quantitative MRI serves as a noninvasive histological and quantification tool, which significantly improves the evaluation of degeneration and repair processes. AI plays a crucial role in automating radiological estimations and enabling data-driven predictions of future events. Despite the transformative impact of advanced MRI techniques on the analytical and diagnostic algorithms related to cruciate ligament disorders, future efforts are warranted to address challenges such as economic burdens and ethical considerations.<\/jats:p>","DOI":"10.1530\/eor-2024-0093","type":"journal-article","created":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T13:44:35Z","timestamp":1751377475000},"page":"475-486","update-policy":"https:\/\/doi.org\/10.1530\/crossmarkpolicy-16","source":"Crossref","is-referenced-by-count":3,"title":["Magnetic resonance imaging of cruciate ligament disorders: current updates"],"prefix":"10.1530","volume":"10","author":[{"given":"Tanda","family":"Yang","sequence":"first","affiliation":[{"name":"Xiangya School of Medicine, Central South University 1 , , ,","place":["Changsha, Hunan, P.R. China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yexin","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Orthopaedics, The Second Xiangya Hospital, Central South University 2 , ,","place":["Changsha, P.R. China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Longtao","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Radiology, The Second Xiangya Hospital, Central South University 3 , ,","place":["Changsha, P.R. China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6906-5350","authenticated-orcid":true,"given":"Qian","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Orthopaedics, The Second Xiangya Hospital, Central South University 2 , ,","place":["Changsha, P.R. China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"416","published-online":{"date-parts":[[2025,7,1]]},"reference":[{"key":"2026070711150220600_bib1","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1007\/978-3-030-05396-3_2","article-title":"Anatomy and biomechanics of the cruciate ligaments and their surgical implications","volume-title":"The Multiple Ligament Injured Knee: A Practical Guide to Management","author":"Hassebrock","year":"2019"},{"key":"2026070711150220600_bib2","doi-asserted-by":"crossref","first-page":"2363","DOI":"10.1177\/0363546514542796","article-title":"Incidence and trends of anterior cruciate ligament reconstruction in the United States","volume":"42","author":"Mall","year":"2014","journal-title":"Am J Sports Med"},{"key":"2026070711150220600_bib3","doi-asserted-by":"crossref","first-page":"1890","DOI":"10.1016\/j.joca.2016.06.006","article-title":"Epidemiology of intra- and peri-articular structural injuries in traumatic knee joint hemarthrosis \u2013 data from 1145 consecutive knees with subacute MRI","volume":"24","author":"Olsson","year":"2016","journal-title":"Osteoarthr Cartil"},{"key":"2026070711150220600_bib4","doi-asserted-by":"crossref","first-page":"697","DOI":"10.1148\/radiology.213.3.r99dc26697","article-title":"Anterior cruciate ligament tears: MR imaging-based diagnosis in a pediatric population","volume":"213","author":"Lee","year":"1999","journal-title":"Radiology"},{"key":"2026070711150220600_bib5","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1148\/radiol.2211010105","article-title":"MR imaging of the posterior cruciate ligament graft: initial experience in 15 patients with clinical correlation","volume":"221","author":"Sherman","year":"2001","journal-title":"Radiology"},{"key":"2026070711150220600_bib6","doi-asserted-by":"crossref","first-page":"921","DOI":"10.1259\/0007-1285-51-611-921","article-title":"Human whole body line-scan imaging by NMR","volume":"51","author":"Mansfield","year":"2014","journal-title":"Br J Radiol"},{"key":"2026070711150220600_bib7","doi-asserted-by":"crossref","first-page":"1756","DOI":"10.1177\/0363546507307396","article-title":"The long-term consequence of anterior cruciate ligament and meniscus injuries: osteoarthritis","volume":"35","author":"Lohmander","year":"2007","journal-title":"Am J Sports Med"},{"key":"2026070711150220600_bib8","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1063\/PT.3.4408","article-title":"State of the art in magnetic resonance imaging","volume":"73","author":"Jordan","year":"2020","journal-title":"Phys Today"},{"key":"2026070711150220600_bib9","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1186\/s13075-020-02156-5","article-title":"Post-traumatic osteoarthritis following ACL injury","volume":"22","author":"Wang","year":"2020","journal-title":"Arthritis Res Ther"},{"key":"2026070711150220600_bib10","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.ejrad.2019.02.038","article-title":"The present and future of deep learning in radiology","volume":"114","author":"Saba","year":"2019","journal-title":"Eur J Radiol"},{"key":"2026070711150220600_bib11","doi-asserted-by":"crossref","first-page":"265","DOI":"10.3389\/fnhum.2016.00265","article-title":"The brain from within","volume":"10","author":"di Porzio","year":"2016","journal-title":"Front Hum Neurosci"},{"key":"2026070711150220600_bib12","doi-asserted-by":"crossref","first-page":"649","DOI":"10.1186\/s12891-022-05595-0","article-title":"Evaluating the diagnostic pathway for acute ACL injuries in trauma centres: a systematic review","volume":"23","author":"Allott","year":"2022","journal-title":"BMC Muscoskelet Disord"},{"key":"2026070711150220600_bib13","first-page":"234","volume-title":"MRI of the Knee","author":"Bolog"},{"key":"2026070711150220600_bib14","first-page":"49","volume-title":"Rotatory Knee Instability: An Evidence Based Approach","author":"Pereira"},{"key":"2026070711150220600_bib15","first-page":"1207","article-title":"Anterior cruciate ligament injuries: MR imaging diagnosis with surgical implications","volume":"10","author":"Kang","year":"2023","journal-title":"Ann Sports Med Res"},{"key":"2026070711150220600_bib16","doi-asserted-by":"crossref","first-page":"W155","DOI":"10.2214\/AJR.07.2921","article-title":"MRI appearance of posterior cruciate ligament tears","volume":"191","author":"Rodriguez","year":"2008","journal-title":"AJR Am J Roentgenol"},{"key":"2026070711150220600_bib17","doi-asserted-by":"crossref","first-page":"1106","DOI":"10.1016\/j.crad.2008.04.008","article-title":"Three Tesla MRI for the diagnosis of meniscal and anterior cruciate ligament pathology: a comparison to arthroscopic findings","volume":"63","author":"Sampson","year":"2008","journal-title":"Clin Radiol"},{"key":"2026070711150220600_bib18","doi-asserted-by":"crossref","first-page":"1336","DOI":"10.1002\/jmri.21333","article-title":"Characterization of spontaneous healing of chronic posterior cruciate ligament injury: analysis of instability and magnetic resonance imaging","volume":"27","author":"Jung","year":"2008","journal-title":"J Magn Reson Imaging"},{"key":"2026070711150220600_bib19","doi-asserted-by":"crossref","first-page":"638","DOI":"10.5312\/wjo.v7.i10.638","article-title":"Magnetic resonance imaging after anterior cruciate ligament reconstruction: a practical guide","volume":"7","author":"Grassi","year":"2016","journal-title":"World J Orthop"},{"key":"2026070711150220600_bib20","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1007\/s12178-018-9505-0","article-title":"Clinical and radiologic evaluation of the posterior cruciate ligament-injured knee","volume":"11","author":"Badri","year":"2018","journal-title":"Curr Rev Musculoskelet Med"},{"key":"2026070711150220600_bib21","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1055\/s-0036-1579711","article-title":"Rupture of the posterior cruciate ligament: preoperative and postoperative assessment","volume":"20","author":"Parkar","year":"2016","journal-title":"Semin Musculoskelet Radiol"},{"key":"2026070711150220600_bib22","doi-asserted-by":"crossref","first-page":"1790","DOI":"10.3390\/diagnostics11101790","article-title":"Micro- and macroscale assessment of posterior cruciate ligament functionality based on advanced MRI techniques","volume":"11","author":"Wilms","year":"2021","journal-title":"Diagnostics"},{"key":"2026070711150220600_bib23","doi-asserted-by":"crossref","first-page":"805","DOI":"10.1002\/jmri.23718","article-title":"Practical medical applications of quantitative MR relaxometry","volume":"36","author":"Cheng","year":"2012","journal-title":"J Magn Reson Imaging"},{"key":"2026070711150220600_bib24","doi-asserted-by":"crossref","first-page":"506","DOI":"10.2214\/AJR.19.21117","article-title":"Artificial intelligence in musculoskeletal imaging: current status and future directions","volume":"213","author":"Gyftopoulos","year":"2019","journal-title":"Am J Roentgenol"},{"key":"2026070711150220600_bib25","first-page":"807","volume-title":"Proceedings of International Conference on Emerging Technologies and Intelligent Systems. Lecture Notes in Networks and Systems","author":"Arpaci","year":"2022"},{"key":"2026070711150220600_bib26","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1097\/00003086-198907000-00002","article-title":"Image formation by induced local interactions. Examples employing nuclear magnetic resonance. 1973","volume":"244","author":"Lauterbur","year":"1989","journal-title":"Clin Orthop Relat Res"},{"key":"2026070711150220600_bib27","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.mri.2018.09.013","article-title":"The rotating stretched curved planar reconstruction of 3D-FIESTA MR imaging for evaluating the anterior cruciate ligament of the knee joint","volume":"55","author":"Zhang","year":"2019","journal-title":"Magn Reson Imaging"},{"key":"2026070711150220600_bib28","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1007\/s00117-020-00788-x","article-title":"[Diagnostic value of a 3D-SPACE-sequence with compressed sensing technology for the knee joint]","volume":"61","author":"Pfeifer","year":"2021","journal-title":"Radiologe"},{"key":"2026070711150220600_bib29","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1186\/s12968-022-00866-0","article-title":"T2 mapping in myocardial disease: a comprehensive review","volume":"24","author":"O\u2019Brien","year":"2022","journal-title":"J Cardiovasc Magn Reson"},{"key":"2026070711150220600_bib30","doi-asserted-by":"crossref","first-page":"1429","DOI":"10.1007\/s00256-014-1852-3","article-title":"T2* mapping for articular cartilage assessment: principles, current applications, and future prospects","volume":"43","author":"Hesper","year":"2014","journal-title":"Skelet Radiol"},{"key":"2026070711150220600_bib31","first-page":"858","article-title":"T1\u03c1 magnetic resonance: basic physics principles and applications in knee and intervertebral disc imaging","volume":"5","author":"W\u00e1ng","year":"2015","journal-title":"Quant Imaging Med Surg"},{"key":"2026070711150220600_bib32","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1002\/jmri.28689","article-title":"Updates on compositional MRI mapping of the cartilage: emerging techniques and applications","volume":"58","author":"Zibetti","year":"2023","journal-title":"J Magn Reson Imaging"},{"key":"2026070711150220600_bib33","doi-asserted-by":"crossref","first-page":"1874","DOI":"10.1002\/jmri.28981","article-title":"Does T1\u03c1 measure proteoglycan concentration in cartilage?","volume":"59","author":"Casula","year":"2023","journal-title":"J Magn Reson Imaging"},{"key":"2026070711150220600_bib34","doi-asserted-by":"crossref","first-page":"1489","DOI":"10.1177\/02841851211043834","article-title":"Quantitative differentiation of tendon and ligament using magnetic resonance imaging ultrashort echo time T2* mapping of normal knee joint","volume":"63","author":"Okuda","year":"2022","journal-title":"Acta Radiol"},{"key":"2026070711150220600_bib35","doi-asserted-by":"crossref","first-page":"916","DOI":"10.1186\/s12891-021-04755-y","article-title":"Quantitative analysis of the ACL and PCL using T1rho and T2 relaxation time mapping: an exploratory, cross-sectional comparison between OA and healthy control knees","volume":"22","author":"Ranmuthu","year":"2021","journal-title":"BMC Musculoskelet Disord"},{"key":"2026070711150220600_bib36","doi-asserted-by":"crossref","first-page":"738","DOI":"10.1007\/s43465-020-00062-1","article-title":"Comparing ACL and PCL publication trends on PubMed in the last four decades","volume":"54","author":"Vaishya","year":"2020","journal-title":"Indian J Orthop"},{"key":"2026070711150220600_bib37","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1186\/s40634-019-0188-2","article-title":"Quantitative mapping of acute and chronic PCL pathology with 3 T MRI: a prospectively enrolled patient cohort","volume":"6","author":"Wilson","year":"2019","journal-title":"J Exp Orthop"},{"key":"2026070711150220600_bib38","doi-asserted-by":"crossref","first-page":"4190","DOI":"10.21037\/qims-22-251","article-title":"UTE-T2* versus conventional T2* mapping to assess posterior cruciate ligament ultrastructure and integrity-an in-situ study","volume":"12","author":"Wilms","year":"2022","journal-title":"Quant Imaging Med Surg"},{"key":"2026070711150220600_bib39","first-page":"121","volume-title":"Return to Sport after ACL Reconstruction and Other Knee Operations: Limiting the Risk of Reinjury and Maximizing Athletic Performance","author":"Smith"},{"key":"2026070711150220600_bib40","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1186\/s13018-019-1193-y","article-title":"Feasibility of T1rho and T2 map magnetic resonance imaging for evaluating graft maturation after anatomic double-bundle anterior cruciate ligament reconstruction","volume":"14","author":"Niki","year":"2019","journal-title":"J Orthop Surg Res"},{"key":"2026070711150220600_bib41","doi-asserted-by":"crossref","DOI":"10.1177\/2325967119863056","article-title":"Quantitative MRI UTE-T2* and T2* show progressive and continued graft maturation over 2 years in human patients after anterior cruciate ligament reconstruction","volume":"7","author":"Chu","year":"2019","journal-title":"Orthop J Sports Med"},{"key":"2026070711150220600_bib42","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0271935","article-title":"Ligamentization of the reconstructed ACL differs between the intraarticular and intraosseous regions: a quantitative assessment using UTE-T2* mapping","volume":"17","author":"Yoshimizu","year":"2022","journal-title":"PLoS One"},{"key":"2026070711150220600_bib43","doi-asserted-by":"crossref","first-page":"789","DOI":"10.1016\/j.joca.2007.01.011","article-title":"In vivo T1\u03c1 arid T2 mapping of articular cartilage in osteoarthritis of the knee using 3 T MRI","volume":"15","author":"Li","year":"2007","journal-title":"Osteoarthr Cartil"},{"key":"2026070711150220600_bib44","doi-asserted-by":"crossref","first-page":"1585","DOI":"10.1002\/jor.25045","article-title":"Visualizing pre-osteoarthritis: integrating MRI UTE-T2* with mechanics and biology to combat osteoarthritis-the 2019 Elizabeth Winston Lanier Kappa Delta Award","volume":"39","author":"Chu","year":"2021","journal-title":"J Orthop Res"},{"key":"2026070711150220600_bib45","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1002\/jor.24110","article-title":"MRI UTE-T2* shows high incidence of cartilage subsurface matrix changes 2 years after ACL reconstruction","volume":"37","author":"Williams","year":"2019","journal-title":"J Orthop Res"},{"key":"2026070711150220600_bib46","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1186\/s41747-020-00191-0","article-title":"Compositional MRI of the anterior cruciate ligament of professional alpine ski racers: preliminary report on seasonal changes and load sensitivity","volume":"4","author":"Csapo","year":"2020","journal-title":"Eur Radiol Exp"},{"key":"2026070711150220600_bib47","doi-asserted-by":"crossref","DOI":"10.1016\/j.ocarto.2022.100320","article-title":"Medial meniscus extrusion is directly correlated with medial tibial osteophyte in patients received reconstruction surgery for anterior cruciate ligament injury: a longitudinal study","volume":"4","author":"Hada","year":"2022","journal-title":"Osteoarthr Cartil Open"},{"key":"2026070711150220600_bib48","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1177\/03635465221142323","article-title":"Quantitative MRI biomarkers to predict risk of reinjury within 2 Years after bridge-enhanced ACL restoration","volume":"51","author":"Barnes","year":"2023","journal-title":"Am J Sports Med"},{"key":"2026070711150220600_bib49","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijscr.2023.107922","article-title":"Single bundle vs double bundle for anterior cruciate ligament reconstruction evaluated with T2 mapping: a case series","volume":"104","author":"Nelwan","year":"2023","journal-title":"Int J Surg Case Rep"},{"key":"2026070711150220600_bib50","article-title":"Single- and bicomponent analyses of T2\u2217 relaxation in knee tendon and ligament by using 3D ultrashort echo time cones (UTE cones) magnetic resonance imaging","volume":"2019","author":"Liu","year":"2019","journal-title":"Biomed Res Int."},{"key":"2026070711150220600_bib51","doi-asserted-by":"crossref","first-page":"2908","DOI":"10.1002\/jor.25319","article-title":"Reproducibility and postacquisition correction methods for quantitative magnetic resonance imaging of the anterior cruciate ligament (ACL)","volume":"40","author":"Flannery","year":"2022","journal-title":"J Orthop Res"},{"key":"2026070711150220600_bib52","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1148\/radiology.161.2.3763909","article-title":"MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders","volume":"161","author":"Le Bihan","year":"1986","journal-title":"Radiology"},{"key":"2026070711150220600_bib53","first-page":"740","article-title":"Diffusion-weighted imaging in musculoskeletal radiology-clinical applications and future directions","volume":"5","author":"Bhojwani","year":"2015","journal-title":"Quant Imaging Med Surg"},{"key":"2026070711150220600_bib54","doi-asserted-by":"crossref","first-page":"632","DOI":"10.3174\/ajnr.A1051","article-title":"Diffusion tensor MR imaging and fiber tractography: theoretic underpinnings","volume":"29","author":"Mukherjee","year":"2008","journal-title":"AJNR Am J Neuroradiol"},{"key":"2026070711150220600_bib55","first-page":"610","article-title":"[Diffusion tensor imaging map of anterior cruciate ligament contrasted with MRI in healthy adults]","volume":"38","author":"Chen","year":"2013","journal-title":"Zhong Nan Da Xue Xue Bao Yi Xue Ban"},{"key":"2026070711150220600_bib56","doi-asserted-by":"crossref","first-page":"1318","DOI":"10.1002\/jor.24684","article-title":"Diffusion tensor imaging of the anterior cruciate ligament following primary repair with internal bracing: a longitudinal study","volume":"39","author":"Van Dyck","year":"2021","journal-title":"J Orthop Res"},{"key":"2026070711150220600_bib57","doi-asserted-by":"crossref","first-page":"6673","DOI":"10.1007\/s00330-020-07051-w","article-title":"Diffusion tensor imaging of the anterior cruciate ligament graft following reconstruction: a longitudinal study","volume":"30","author":"Van Dyck","year":"2020","journal-title":"Eur Radiol"},{"key":"2026070711150220600_bib58","doi-asserted-by":"crossref","DOI":"10.1177\/03000605221121954","article-title":"The ultrastructural and morphological characteristics of the anterior cruciate ligament of the pig: a study using 7.0-tesla diffusion tensor imaging","volume":"50","author":"You","year":"2022","journal-title":"J Int Med Res"},{"key":"2026070711150220600_bib59","doi-asserted-by":"crossref","first-page":"1475","DOI":"10.1002\/jmri.27322","article-title":"Diffusion tensor imaging for quantitative assessment of anterior cruciate ligament injury grades and graft","volume":"52","author":"Liu","year":"2020","journal-title":"J Magn Reson Imaging"},{"key":"2026070711150220600_bib60","doi-asserted-by":"crossref","first-page":"1485","DOI":"10.1002\/jmri.27317","article-title":"Editorial for \u201cdiffusion tensor imaging for quantitative assessment of anterior cruciate ligament injury grades and graft","volume":"52","author":"Kessler","year":"2020","journal-title":"J Magn Reson Imaging"},{"key":"2026070711150220600_bib61","doi-asserted-by":"crossref","DOI":"10.1016\/j.nicl.2019.102157","article-title":"Corticospinal tract structure and excitability in patients with anterior cruciate ligament reconstruction: a DTI and TMS study","volume":"25","author":"Lepley","year":"2020","journal-title":"Neuroimage Clin"},{"key":"2026070711150220600_bib62","first-page":"1","volume-title":"Handbook of Functional MRI Data Analysis","author":"Mumford"},{"key":"2026070711150220600_bib63","doi-asserted-by":"crossref","first-page":"1267","DOI":"10.1007\/s00221-019-05499-x","article-title":"Quadriceps muscle function following anterior cruciate ligament reconstruction: systemic differences in neural and morphological characteristics","volume":"237","author":"Lepley","year":"2019","journal-title":"Exp Brain Res"},{"key":"2026070711150220600_bib64","first-page":"1479","article-title":"[A preliminary study on resting-state functional magnetic resonance imaging of brain after anterior cruciate ligament preservation reconstruction with autologous tendon]","volume":"99","author":"Wang","year":"2019","journal-title":"Zhonghua Yi Xue Za Zhi"},{"key":"2026070711150220600_bib65","doi-asserted-by":"crossref","DOI":"10.1016\/j.neulet.2020.134985","article-title":"Neural activity for hip-knee control in those with anterior cruciate ligament reconstruction: a task-based functional connectivity analysis","volume":"730","author":"Criss","year":"2020","journal-title":"Neurosci Lett"},{"key":"2026070711150220600_bib66","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1016\/j.bjpt.2019.07.004","article-title":"Alterations in knee sensorimotor brain functional connectivity contributes to ACL injury in male high-school football players: a prospective neuroimaging analysis","volume":"24","author":"Diekfuss","year":"2020","journal-title":"Braz J Phys Ther"},{"key":"2026070711150220600_bib67","doi-asserted-by":"crossref","DOI":"10.3389\/fnhum.2022.841874","article-title":"Brain response to a knee proprioception task among persons with anterior cruciate ligament reconstruction and controls","volume":"16","author":"Strong","year":"2022","journal-title":"Front Hum Neurosci"},{"key":"2026070711150220600_bib68","doi-asserted-by":"crossref","DOI":"10.3389\/fnhum.2023.1263292","article-title":"Organization of sensorimotor activity in anterior cruciate ligament reconstructed individuals: an fMRI conjunction analysis","volume":"17","author":"Schnittjer","year":"2023","journal-title":"Front Hum Neurosci"},{"key":"2026070711150220600_bib69","doi-asserted-by":"crossref","DOI":"10.1002\/brb3.2879","article-title":"The relationship between drop vertical jump action-observation brain activity and kinesiophobia after anterior cruciate ligament reconstruction: a cross-sectional fMRI study","volume":"13","author":"Kim","year":"2023","journal-title":"Brain Behav"},{"key":"2026070711150220600_bib70","doi-asserted-by":"crossref","first-page":"70","DOI":"10.26603\/001c.57782","article-title":"A preliminary investigation into the neural correlates of knee loading during a change of direction task in individuals after anterior cruciate ligament reconstruction","volume":"18","author":"Culiver","year":"2023","journal-title":"Int J Sports Phys Ther"},{"key":"2026070711150220600_bib71","doi-asserted-by":"crossref","first-page":"415","DOI":"10.2519\/jospt.2023.11489","article-title":"Combining neurocognitive and functional tests to improve return-to-sport decisions following ACL reconstruction","volume":"53","author":"Grooms","year":"2023","journal-title":"J Orthop Sports Phys Ther"},{"key":"2026070711150220600_bib72","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0272578","article-title":"Preliminary brain-behavioral neural correlates of anterior cruciate ligament injury risk landing biomechanics using a novel bilateral leg press neuroimaging paradigm","volume":"17","author":"Grooms","year":"2022","journal-title":"PLoS One"},{"key":"2026070711150220600_bib73","article-title":"Attention is all you need","author":"Vaswani","year":"2017","journal-title":"arXiv"},{"key":"2026070711150220600_bib74","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1186\/s12880-023-01091-6","article-title":"Effective automatic detection of anterior cruciate ligament injury using convolutional neural network with two attention mechanism modules","volume":"23","author":"Liang","year":"2023","journal-title":"BMC Med Imaging"},{"key":"2026070711150220600_bib75","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pmed.1002699","article-title":"Deep-learning-assisted diagnosis for knee magnetic resonance imaging: development and retrospective validation of MRNet","volume":"15","author":"Bien","year":"2018","journal-title":"PLoS Med"},{"key":"2026070711150220600_bib76","doi-asserted-by":"crossref","first-page":"8394","DOI":"10.1007\/s00330-022-08923-z","article-title":"Deep learning to detect anterior cruciate ligament tear on knee MRI: multi-continental external validation","volume":"32","author":"Tran","year":"2022","journal-title":"Eur Radiol"},{"key":"2026070711150220600_bib77","doi-asserted-by":"crossref","DOI":"10.1177\/2325967119866732","article-title":"A definition of significant instability and a scoring system for predicting meniscal tears in ACL-deficient knees","volume":"7","author":"Joshi","year":"2019","journal-title":"Orthop J Sports Med"},{"key":"2026070711150220600_bib78","doi-asserted-by":"crossref","first-page":"1745","DOI":"10.1002\/jmri.27266","article-title":"Deep learning approach for anterior cruciate ligament lesion detection: evaluation of diagnostic performance using arthroscopy as the reference standard","volume":"52","author":"Zhang","year":"2020","journal-title":"J Magn Reson Imaging"},{"key":"2026070711150220600_bib79","doi-asserted-by":"crossref","first-page":"980","DOI":"10.1007\/s10278-019-00193-4","article-title":"Deep learning for detection of complete anterior cruciate ligament tear","volume":"32","author":"Chang","year":"2019","journal-title":"J Digit Imaging"},{"key":"2026070711150220600_bib80","doi-asserted-by":"crossref","DOI":"10.1148\/ryai.2019180091","article-title":"Fully automated diagnosis of anterior cruciate ligament tears on knee MR images by using deep learning","volume":"1","author":"Liu","year":"2019","journal-title":"Radiol Artif Intell"},{"key":"2026070711150220600_bib81","doi-asserted-by":"crossref","first-page":"2388","DOI":"10.1109\/JBHI.2021.3081355","article-title":"Interpretable and lightweight 3-D deep learning model for automated ACL diagnosis","volume":"25","author":"Jeon","year":"2021","journal-title":"IEEE J Biomed Health Inform"},{"key":"2026070711150220600_bib82","doi-asserted-by":"crossref","DOI":"10.1161\/CIRCIMAGING.122.014519","article-title":"Explainable artificial intelligence and cardiac imaging: toward more interpretable models","volume":"16","author":"Salih","year":"2023","journal-title":"Circ Cardiovasc Imaging"},{"key":"2026070711150220600_bib83","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1186\/s12891-022-05524-1","article-title":"Automated detection of anterior cruciate ligament tears using a deep convolutional neural network","volume":"23","author":"Minamoto","year":"2022","journal-title":"BMC Musculoskelet Disord"},{"key":"2026070711150220600_bib84","doi-asserted-by":"crossref","DOI":"10.1097\/MD.0000000000031510","article-title":"Development of convolutional neural network model for diagnosing tear of anterior cruciate ligament using only one knee magnetic resonance image","volume":"101","author":"Shin","year":"2022","journal-title":"Medicine (Baltim)"},{"key":"2026070711150220600_bib85","doi-asserted-by":"crossref","first-page":"105","DOI":"10.3390\/diagnostics11010105","article-title":"Efficient detection of knee anterior cruciate ligament from magnetic resonance imaging using deep learning approach","volume":"11","author":"Javed Awan","year":"2021","journal-title":"Diagnostics"},{"key":"2026070711150220600_bib86","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1186\/s40537-021-00444-8","article-title":"Review of deep learning: concepts, CNN architectures, challenges, applications, future directions","volume":"8","author":"Alzubaidi","year":"2021","journal-title":"J Big Data"},{"key":"2026070711150220600_bib87","doi-asserted-by":"crossref","first-page":"1552","DOI":"10.3390\/s22041552","article-title":"Automated knee MR images segmentation of anterior cruciate ligament tears","volume":"22","author":"Awan","year":"2022","journal-title":"Sensors"},{"key":"2026070711150220600_bib88","doi-asserted-by":"crossref","first-page":"831","DOI":"10.1002\/jor.24926","article-title":"Automated magnetic resonance image segmentation of the anterior cruciate ligament","volume":"39","author":"Flannery","year":"2021","journal-title":"J Orthop Res"},{"key":"2026070711150220600_bib89","doi-asserted-by":"crossref","first-page":"426","DOI":"10.1186\/s12891-022-05378-7","article-title":"Automatic segmentation model of intercondylar fossa based on deep learning: a novel and effective assessment method for the notch volume","volume":"23","author":"Li","year":"2022","journal-title":"BMC Musculoskelet Disord"},{"key":"2026070711150220600_bib90","doi-asserted-by":"crossref","first-page":"649","DOI":"10.1002\/jor.25390","article-title":"Automated segmentation of the healed anterior cruciate ligament from T(2) * relaxometry MRI scans","volume":"41","author":"Flannery","year":"2023","journal-title":"J Orthop Res"},{"key":"2026070711150220600_bib91","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1016\/j.diii.2022.10.010","article-title":"End-to-end deep learning model for segmentation and severity staging of anterior cruciate ligament injuries from MRI","volume":"104","author":"Dung","year":"2023","journal-title":"Diagn Interv Imaging"},{"key":"2026070711150220600_bib92","doi-asserted-by":"crossref","DOI":"10.7717\/peerj-cs.1483","article-title":"MGACA-Net: a novel deep learning based multi-scale guided attention and context aggregation for localization of knee anterior cruciate ligament tears region in MRI images","volume":"9","author":"Awan","year":"2023","journal-title":"PeerJ Comput Sci"},{"key":"2026070711150220600_bib93","doi-asserted-by":"crossref","DOI":"10.1016\/j.compmedimag.2020.101793","article-title":"The optimisation of deep neural networks for segmenting multiple knee joint tissues from MRIs","volume":"86","author":"Kessler","year":"2020","journal-title":"Comput Med Imaging Graph"},{"key":"2026070711150220600_bib94","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1186\/s12891-023-06153-y","article-title":"Automatic segmentation of human knee anatomy by a convolutional neural network applying a 3D MRI protocol","volume":"24","author":"Kulseng","year":"2023","journal-title":"BMC Musculoskelet Disord"},{"key":"2026070711150220600_bib95","doi-asserted-by":"crossref","DOI":"10.1016\/j.compmedimag.2022.102142","article-title":"Deep convolutional feature details for better knee disorder diagnoses in magnetic resonance images","volume":"102","author":"Dunnhofer","year":"2022","journal-title":"Comput Med Imaging Graph"},{"key":"2026070711150220600_bib96","article-title":"Automatic deep learning-assisted detection and grading of abnormalities in knee MRI studies","volume":"3","author":"Astuto","year":"2021","journal-title":"Radiol Artif Intell"},{"key":"2026070711150220600_bib97","doi-asserted-by":"crossref","DOI":"10.1148\/ryai.210315","article-title":"RadImageNet: an open radiologic deep learning research dataset for effective transfer learning","volume":"4","author":"Mei","year":"2022","journal-title":"Radiol Artif Intell"},{"key":"2026070711150220600_bib98","doi-asserted-by":"crossref","first-page":"1684","DOI":"10.1093\/jamia\/ocad118","article-title":"Artificial intelligence suppression as a strategy to mitigate artificial intelligence automation bias","volume":"30","author":"Wang","year":"2023","journal-title":"J Am Med Inform Assoc"},{"key":"2026070711150220600_bib99","doi-asserted-by":"crossref","first-page":"1197","DOI":"10.1016\/j.arthro.2023.08.010","article-title":"A deep learning model enhances clinicians' diagnostic accuracy to more than 96% for anterior cruciate ligament ruptures on magnetic resonance imaging","volume":"40","author":"Wang","year":"2024","journal-title":"Arthroscopy"},{"key":"2026070711150220600_bib100","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1007\/s11604-022-01385-9","article-title":"A transfer learning approach for staging diagnosis of anterior cruciate ligament injury on a new modified MR dual precision positioning of thin-slice oblique sagittal FS-PDWI sequence","volume":"41","author":"Chen","year":"2023","journal-title":"Jpn J Radiol"},{"key":"2026070711150220600_bib101","article-title":"LigaNET: a multi-modal deep learning approach to predict the risk of subsequent anterior cruciate ligament injury after surgery","author":"Han","year":"2023","journal-title":"medRxiv"},{"key":"2026070711150220600_bib102","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1186\/s13018-021-02437-y","article-title":"Texture analysis to differentiate anterior cruciate ligament in patients after surgery with platelet-rich plasma","volume":"16","author":"Alves","year":"2021","journal-title":"J Orthop Surg Res"},{"key":"2026070711150220600_bib103","doi-asserted-by":"crossref","first-page":"3524","DOI":"10.1038\/s41598-023-30637-5","article-title":"Predicting anterior cruciate ligament failure load with T(2)* relaxometry and machine learning as a prospective imaging biomarker for revision surgery","volume":"13","author":"Flannery","year":"2023","journal-title":"Sci Rep"},{"key":"2026070711150220600_bib104","doi-asserted-by":"crossref","DOI":"10.1177\/23259671211027543","article-title":"A prediction model for primary anterior cruciate ligament injury using artificial intelligence","volume":"9","author":"Tamimi","year":"2021","journal-title":"Orthop J Sports Med"},{"key":"2026070711150220600_bib105","doi-asserted-by":"crossref","first-page":"2680","DOI":"10.1177\/03635465221107082","article-title":"Trends in health care expenditures and patient out-of-pocket expenses in primary anterior cruciate ligament reconstruction","volume":"50","author":"Carbone","year":"2022","journal-title":"Am J Sports Med"},{"key":"2026070711150220600_bib106","doi-asserted-by":"crossref","first-page":"e23","DOI":"10.1016\/j.eats.2011.12.004","article-title":"Individualized anatomic anterior cruciate ligament reconstruction","volume":"1","author":"Rabuck","year":"2012","journal-title":"Arthrosc Tech"},{"key":"2026070711150220600_bib107","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1007\/s00167-022-07049-5","article-title":"Smaller intercondylar notch size and smaller ACL volume increase posterior cruciate ligament rupture risk","volume":"31","author":"van Kuijk","year":"2023","journal-title":"Knee Surg Sports Traumatol Arthrosc"},{"key":"2026070711150220600_bib108","first-page":"4076175","article-title":"Deep learning-based magnetic resonance imaging image features for diagnosis of anterior cruciate ligament injury","volume":"2021","author":"Li","year":"2021","journal-title":"J Healthc Eng"},{"key":"2026070711150220600_bib109","doi-asserted-by":"crossref","first-page":"2314","DOI":"10.3390\/diagnostics12102314","article-title":"Anterior cruciate ligament tear detection based on deep convolutional neural network","volume":"12","author":"Joshi","year":"2022","journal-title":"Diagnostics"},{"key":"2026070711150220600_bib110","doi-asserted-by":"crossref","DOI":"10.3389\/fbioe.2023.1268543","article-title":"Automated diagnosis of anterior cruciate ligament via a weighted multi-view network","volume":"11","author":"Li","year":"2023","journal-title":"Front Bioeng Biotechnol"}],"container-title":["EFORT Open Reviews"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/eor.bioscientifica.com\/view\/journals\/eor\/10\/7\/EOR-2024-0093.xml","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/eor.bioscientifica.com\/downloadpdf\/journals\/eor\/10\/7\/EOR-2024-0093.xml","content-type":"text\/html","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/journals.bioscientifica.com\/eor\/article-pdf\/10\/7\/475\/13983\/eor-2024-0093.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/journals.bioscientifica.com\/eor\/article-pdf\/10\/7\/475\/13983\/eor-2024-0093.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T15:47:53Z","timestamp":1783439273000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.bioscientifica.com\/eor\/article\/10\/7\/475\/1751\/Magnetic-resonance-imaging-of-cruciate-ligament"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,1]]},"references-count":110,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2025,7,1]]},"published-print":{"date-parts":[[2025,7,1]]}},"URL":"https:\/\/doi.org\/10.1530\/eor-2024-0093","relation":{},"ISSN":["2058-5241"],"issn-type":[{"value":"2058-5241","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,1]]}}}