背景:扩散张量成像(DTI)因其研究脑部疾病神经病理学微观结构变化的能力而越来越被认可。然而,最佳DTI指标及其对多种脊髓疾病的诊断效用仍在研究中.
目的:评估DTI指标对颈椎病的诊断效能,脊髓炎,和脊柱肿瘤。
方法:这项回顾性研究分析了68例患者的DTI扫描(22例颈椎病,23患有脊髓炎,和23患有脊柱肿瘤)。DTI指标,包括分数各向异性(FA),平均扩散率(MD),径向扩散率(RD)和轴向扩散率(AD),被计算。Kruskal-Wallis测试用于比较这些指标,其次是接收器工作特性(ROC)曲线分析,评估各疾病对各指标的诊断效能。此外,我们探讨了DTI指标与具体临床测量值的相关性.
结果:与颈椎病(p<0.0001)和脊髓炎(p<0.05)相比,肿瘤患者的FA值显着降低。此外,与脊椎病和脊髓炎组相比,肿瘤患者的MD和RD值显著升高.ROC曲线分析强调了FA的优越判别性能,用于区分肿瘤和颈椎病的曲线下面积(AUC)为0.902,区分颈椎病和脊髓炎的AUC为0.748。此外,脊髓炎患者的FA值与扩展残疾状态评分(EDSS)之间存在显着负相关(r=-0.62,p=0.002),以及肿瘤患者的FA值和Ki-67评分之间(r=-0.71,p=0.0002)。
结论:DTI指标,尤其是FA,有潜力区分脊椎病,脊髓炎,和脊髓肿瘤.FA值与临床指标之间的显着相关性突出了FA在脊柱疾病的临床评估和预后中的价值,并可能在将来的诊断方案中应用。
BACKGROUND: Diffusion tensor imaging (DTI) has been increasingly recognized for its capability to study microstructural changes in the neuropathology of brain diseases. However, the optimal DTI metric and its diagnostic utility for a variety of spinal cord diseases are still under investigation.
OBJECTIVE: To evaluate the diagnostic efficacy of DTI metrics for differentiating between cervical spondylosis,
myelitis, and spinal tumors.
METHODS: This retrospective study analyzed DTI scans from 68 patients (22 with cervical spondylosis, 23 with
myelitis, and 23 with spinal tumors). DTI indicators, including fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD), were calculated. The Kruskal-Wallis test was used to compare these indicators, followed by Receiver Operating Characteristic (ROC) curve analysis, to evaluate the diagnostic efficacy of each indicator across disease pairs. Additionally, we explored the correlations of DTI indicators with specific clinical measurements.
RESULTS: FA values were significantly lower in tumor patients compared to those with cervical spondylosis (p < 0.0001) and
myelitis (p < 0.05). Additionally, tumor patients exhibited significantly elevated MD and RD values relative to the spondylosis and myelitis groups. ROC curve analysis underscored FA\'s superior discriminative performance, with an area under the curve (AUC) of 0.902 for differentiating tumors from cervical spondylosis, and an AUC of 0.748 for distinguishing cervical myelitis from spondylosis. Furthermore, a significant negative correlation was observed between FA values and Expanded Disability Status Scores (EDSSs) in
myelitis patients (r = -0.62, p = 0.002), as well as between FA values and Ki-67 scores in tumor patients (r = -0.71, p = 0.0002).
CONCLUSIONS: DTI indicators, especially FA, have the potential in distinguishing spondylosis,
myelitis, and spinal cord tumors. The significant correlation between FA values and clinical indicators highlights the value of FA in the clinical assessment and prognosis of spinal diseases and may be applied in diagnostic protocols in the future.