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
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

2040-2051

Informations 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.

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Auteurs

Chen Yan (C)

Second Department of Spine Surgery, Changzheng Hospital, Second Military Medical University, Shanghai, China.
Undergraduate Incubation Center, Second Military Medical University, Shanghai, China.

Hao-Yuan Tan (HY)

Second Department of Spine Surgery, Changzheng Hospital, Second Military Medical University, Shanghai, China.
Undergraduate Incubation Center, Second Military Medical University, Shanghai, China.

Cheng-Long Ji (CL)

Second Department of Spine Surgery, Changzheng Hospital, Second Military Medical University, Shanghai, China.

Xue-Wei Yu (XW)

Second Department of Spine Surgery, Changzheng Hospital, Second Military Medical University, Shanghai, China.
Undergraduate Incubation Center, Second Military Medical University, Shanghai, China.

Huai-Cheng Jia (HC)

Second Department of Spine Surgery, Changzheng Hospital, Second Military Medical University, Shanghai, China.
Undergraduate Incubation Center, Second Military Medical University, Shanghai, China.

Fu-Dong Li (FD)

Second Department of Spine Surgery, Changzheng Hospital, Second Military Medical University, Shanghai, China.

Gui-Cheng Jiang (GC)

Second Department of Spine Surgery, Changzheng Hospital, Second Military Medical University, Shanghai, China.

Wei-Shi Li (WS)

Department of Orthopaedics, Peking University Third Hospital, Beijing, China.

Fei-Fei Zhou (FF)

Department of Orthopaedics, Peking University Third Hospital, Beijing, China.

Zhen Ye (Z)

Shanghai Electric Group Limited Liability Company Central Academe, Shanghai, China.

Jing-Chuan Sun (JC)

Second Department of Spine Surgery, Changzheng Hospital, Second Military Medical University, Shanghai, China.

Jian-Gang Shi (JG)

Second Department of Spine Surgery, Changzheng Hospital, Second Military Medical University, Shanghai, China.

Classifications MeSH