The clinical value of three-dimensional measurement in the diagnosis of thoracic myelopathy caused by ossification of the ligamentum flavum.
Ossification of the ligamentum flavum (OLF)
computed tomography (CT)
diagnostic imaging
thoracic myelopathy
three-dimensional image (3D image)
Journal
Quantitative imaging in medicine and surgery
ISSN: 2223-4292
Titre abrégé: Quant Imaging Med Surg
Pays: China
ID NLM: 101577942
Informations de publication
Date de publication:
May 2021
May 2021
Historique:
entrez:
3
5
2021
pubmed:
4
5
2021
medline:
4
5
2021
Statut:
ppublish
Résumé
Thoracic ossification of the ligamentum flavum (OLF) is a major cause of thoracic myelopathy, which is often accompanied by multiple segmental stenosis or other degenerative spinal diseases. However, in the above situations, it is difficult to determine the exact segment responsible. The objective of this study was to analyze three-dimensional (3D) radiological parameters in order to establish a novel diagnostic method for discriminating the responsible segment in OLF-induced thoracic myelopathy, and to evaluate its superiority compared to the conventional diagnostic methods. Eighty-one patients who underwent surgery for thoracic myelopathy caused by OLF from 2016 to 2020 were enrolled in this study as the myelopathy group, and 79 patients who had thoracic OLF but displayed no definite neurological signs from 2018 to 2020 were enrolled as the non-myelopathy group. We measured the one-dimensional (1D), two-dimensional (2D), and 3D radiological parameters, calculated their optimal cutoff values, and compared their diagnostic values. Significant differences were observed in the 1D, 2D, and 3D radiological parameters between the myelopathy and non-myelopathy groups (P<0.01). As a 3D radiological parameter, the OLF volume (OLFV) ratio (OLFV ratio = OLFV/normal canal volume × 100%) was the most accurate parameter for diagnosing OLF-induced thoracic myelopathy, with a diagnostic coincidence rate of 88.1%. We also found that an OLFV ratio of 26.3% could be used as the optimal cutoff value, with a sensitivity of 87.7% and a specificity of 88.6%. Moreover, the OLFV ratio [area under the curve (AUC): 0.92, 95% confidence interval (CI): 0.86-0.95] showed a statistically higher diagnostic value than the 1D and 2D parameters (AUC: 0.75, 95% CI: 0.67-0.81; AUC: 0.84, 95% CI: 0.77-0.89, respectively) (P<0.05). Pearson correlation analysis illustrated that the OLFV ratio was significantly negatively correlated with preoperative modified Japanese Orthopedic Association (mJOA) score (r=-0.73, 95% CI: -0.81 to -0.60, P<0.01). Our results demonstrate the superiority of the OLFV ratio over the conventional 1D and 2D computed tomography (CT)-based radiological parameters for the diagnosis of OLF-induced thoracic myelopathy. The novel diagnostic method based on the OLFV ratio will help to determine the responsible segment in multi-segmental thoracic OLF or when thoracic OLF coexists with other degenerative spinal diseases. The OLFV ratio also accurately reflects the clinical state of symptomatic patients with thoracic OLF.
Sections du résumé
BACKGROUND
BACKGROUND
Thoracic ossification of the ligamentum flavum (OLF) is a major cause of thoracic myelopathy, which is often accompanied by multiple segmental stenosis or other degenerative spinal diseases. However, in the above situations, it is difficult to determine the exact segment responsible. The objective of this study was to analyze three-dimensional (3D) radiological parameters in order to establish a novel diagnostic method for discriminating the responsible segment in OLF-induced thoracic myelopathy, and to evaluate its superiority compared to the conventional diagnostic methods.
METHODS
METHODS
Eighty-one patients who underwent surgery for thoracic myelopathy caused by OLF from 2016 to 2020 were enrolled in this study as the myelopathy group, and 79 patients who had thoracic OLF but displayed no definite neurological signs from 2018 to 2020 were enrolled as the non-myelopathy group. We measured the one-dimensional (1D), two-dimensional (2D), and 3D radiological parameters, calculated their optimal cutoff values, and compared their diagnostic values.
RESULTS
RESULTS
Significant differences were observed in the 1D, 2D, and 3D radiological parameters between the myelopathy and non-myelopathy groups (P<0.01). As a 3D radiological parameter, the OLF volume (OLFV) ratio (OLFV ratio = OLFV/normal canal volume × 100%) was the most accurate parameter for diagnosing OLF-induced thoracic myelopathy, with a diagnostic coincidence rate of 88.1%. We also found that an OLFV ratio of 26.3% could be used as the optimal cutoff value, with a sensitivity of 87.7% and a specificity of 88.6%. Moreover, the OLFV ratio [area under the curve (AUC): 0.92, 95% confidence interval (CI): 0.86-0.95] showed a statistically higher diagnostic value than the 1D and 2D parameters (AUC: 0.75, 95% CI: 0.67-0.81; AUC: 0.84, 95% CI: 0.77-0.89, respectively) (P<0.05). Pearson correlation analysis illustrated that the OLFV ratio was significantly negatively correlated with preoperative modified Japanese Orthopedic Association (mJOA) score (r=-0.73, 95% CI: -0.81 to -0.60, P<0.01).
CONCLUSIONS
CONCLUSIONS
Our results demonstrate the superiority of the OLFV ratio over the conventional 1D and 2D computed tomography (CT)-based radiological parameters for the diagnosis of OLF-induced thoracic myelopathy. The novel diagnostic method based on the OLFV ratio will help to determine the responsible segment in multi-segmental thoracic OLF or when thoracic OLF coexists with other degenerative spinal diseases. The OLFV ratio also accurately reflects the clinical state of symptomatic patients with thoracic OLF.
Identifiants
pubmed: 33936985
doi: 10.21037/qims-20-713
pii: qims-11-05-2040
pmc: PMC8047373
doi:
Types de publication
Journal Article
Langues
eng
Pagination
2040-2051Informations de copyright
2021 Quantitative Imaging in Medicine and Surgery. All rights reserved.
Déclaration de conflit d'intérêts
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/qims-20-713). The authors have no conflicts of interest to declare.
Références
J Bone Joint Surg Am. 2019 Apr 3;101(7):606-612
pubmed: 30946194
Eur Spine J. 2019 Aug;28(8):1846-1854
pubmed: 30191306
Nat Rev Rheumatol. 2013 Dec;9(12):741-50
pubmed: 24189840
Spine J. 2018 May;18(5):747-754
pubmed: 28939168
J Korean Neurosurg Soc. 2015 Aug;58(2):112-8
pubmed: 26361526
J Neurosurg Spine. 2009 Aug;11(2):245-52
pubmed: 19769504
Spine J. 2011 Oct;11(10):927-32
pubmed: 21925953
Biometrics. 1988 Sep;44(3):837-45
pubmed: 3203132
Spine J. 2013 Sep;13(9):1032-8
pubmed: 23541451
Int Orthop. 2018 Apr;42(4):835-842
pubmed: 29067483
Eur Spine J. 2011 Feb;20(2):216-23
pubmed: 20628768
J Neurosurg Spine. 2010 Jul;13(1):116-22
pubmed: 20594026
J Korean Neurosurg Soc. 2017 Jul;60(4):441-447
pubmed: 28689393
Ann Surg. 2011 Jan;253(1):27-34
pubmed: 21294285
J Bone Joint Surg Am. 2018 Nov 21;100(22):1960-1968
pubmed: 30480600
Sci Rep. 2020 Jan 28;10(1):1305
pubmed: 31992790
Spine (Phila Pa 1976). 2015 Oct 1;40(19):1479-86
pubmed: 26208225
BMC Musculoskelet Disord. 2019 May 25;20(1):253
pubmed: 31128588
J Craniomaxillofac Surg. 2014 Oct;42(7):1428-36
pubmed: 24864074
Spine J. 2018 Oct;18(10):1779-1786
pubmed: 29526640
Asian Spine J. 2019 Jun 03;13(5):832-841
pubmed: 31154703
BMC Musculoskelet Disord. 2015 Aug 19;16:206
pubmed: 26286579
Spine (Phila Pa 1976). 1992 Nov;17(11):1291-5
pubmed: 1462203
Eur Spine J. 2011 Feb;20(2):205-15
pubmed: 20473624
Med Sci Monit. 2019 Dec 17;25:9666-9678
pubmed: 31847005
Quant Imaging Med Surg. 2019 Jun;9(6):952-959
pubmed: 31367549
Radiology. 1976 Jun;119(3):559-68
pubmed: 935390
Knee. 2019 Jun;26(3):787-793
pubmed: 30885546
Spine J. 2018 Apr;18(4):551-557
pubmed: 28823939
Eur Spine J. 2015 May;24(5):947-54
pubmed: 25744446
Clin Neurol Neurosurg. 2019 Feb;177:86-91
pubmed: 30634057
J Neurosurg Spine. 2006 Aug;5(2):133-9
pubmed: 16925079