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Texture Analysis of Spinal Cord Signal in Pre- and Post-Operative T2-Weighted Magnetic Resonance Images of Patients With Cervical Spondylotic Myelopathy

机译:宫颈脊柱型髓病患者前后术后T2加权磁共振图像中脊髓信号的纹理分析

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Cervical Spondylotic Myelopathy (CSM) represent the most commonly acquired cause of spinal cord dysfunction among individuals over 55 years old. The pathophysiology of the condition involves mechanical factors, which result to injury of the cervical spinal cord. In T-2 weighted Magnetic Resonance (MR) images of the spine the site of injury is depicted as a region of high intensity signal within the cervical spine cord. The present study aims to investigate whether texture analysis of MR signal in CSM could provide novel quantitative prognostic factors, rendering possible the prognostic estimation of the outcome of a therapeutic surgical intervention for CSM. The sample of the study comprised 12 MR images of the cervical spine, corresponding to 6 CSM patients, who had undergone surgical intervention with anterior cervical discectomy and spinal canal decompression. Following a specific MR imaging protocol a pair of T2-weighted sagittal images of the spine, corresponding to pre and post-operative MR scans, were obtained for each of the patients. Employing custom developed software, the region of high intensity signal, associated to CSM, was automatically segmented from each MR image. Utilizing custom developed algorithms a number of textural features were extracted from the segmented ROIs and employed in the design of a classification system, based on the Quadratic classifier. The latter was used for the discrimination between pre-operative and post-operative MR images. Statistical analysis revealed the existence of statistically significant differences between textural features, corresponding to pre- and post-operative CSM MR signals. The Quadratic classifier characterized correctly all the pre- and post-operative MR images (100% classification accuracy). The results of the present study indicate that textural features, generated from MR images of the spine, may serve as prognostic factors regarding the prediction of the post-operative outcome of CSM patients.
机译:颈椎性脊椎病(CSM)代表55岁以上个体中脊髓功能障碍最常见的原因。病症的病理生理学涉及机械因素,这导致颈脊髓损伤。在T-2加权磁共振(MR)图像的脊柱的图像损伤部位被描绘为宫颈脊髓内部的高强度信号区域。本研究旨在研究CSM MR信号的质地分析是否可以提供新的定量预后因素,呈现可能对CSM治疗手术干预结果的预后估算。该研究的样品包含12例颈椎的MR图像,对应于6名CSM患者,后者具有前宫颈椎间盘切除术和椎管减压的手术干预。在特定的MR成像协议之后,对于每个患者,获得了对应于前后和后期MR扫描的脊柱的一对T2加权矢状图像。采用自定义开发的软件,与CSM相关联的高强度信号的区域自动从每个MR图像分段。利用自定义开发的算法,从分段的ROI中提取了许多纹理特征,并基于二次分类器在分类系统的设计中采用。后者用于术前和操作后MR图像之间的歧视。统计分析揭示了纹理特征之间存在统计学上显着差异的存在,对应于术前和后后CSM MR信号。二次分类器表征了所有先前和操作后的MR图像(100%的分类准确性)。本研究结果表明,从脊柱的MR图像产生的纹理特征可以作为关于预测CSM患者的术后结果的预后因素。

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