Shetty Nikhitha, Koteshwar Prakashini
Department of Medical Imaging Technology, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, Karnataka, India.
Department of Medical Imaging Sciences, College of Health Sciences, Gulf Medical University, Ajman, UAE.
J Taibah Univ Med Sci. 2023 Jul 20;18(6):1577-1585. doi: 10.1016/j.jtumed.2023.07.004. eCollection 2023 Dec.
Parkinson's disease (PD) and progressive supranuclear palsy (PSP) are neurodegenerative conditions that have overlapping clinical and imaging features, thus making it difficult to distinguish and diagnose PSP from PD. Therefore, in this study, we aimed to investigate the optimal value of magnetic resonance planimetry and the parkinsonism index to differentiate between PSP and PD.
In this retrospective study, we recruited a total of 84 patients (27 patients with PSP, 27 patients with PD and 27 normal controls) who underwent MRI brain examinations. For each subject, we calculated the corpus callosum area, midbrain area, pons area, middle cerebellar peduncle (MCP) width and superior cerebellar peduncle (SCP) width on MRI brain images. We also calculated the pons to midbrain area (P/M) ratio, MCP/SCP ratio and magnetic resonance parkinsonism index (MRPI).
Receiver operating characteristic curve (ROC) analysis was used to identify the diagnostic value of each biomarker. MRPI had a sensitivity of 70.4%, a specificity of 88.9%, and a diagnostic accuracy of 79.6% with an optimum cut off of 24.3 for differentiating PSP from PD. P/M ratio had a sensitivity of 74.1%, a specificity of 77.8%, and a diagnostic accuracy of 75.9% with an optimal cutoff of 24.3 for differentiating PSP from PD. The MCP/SCP ratio had a sensitivity of 66.7%, a specificity of 77.8%, and an accuracy of 72.2% with an optimal cut off of 4.65 for differentiating PSP from PD.
The study revealed that MRPI and P/M ratio are accurate markers for differentiating PSP from PD. The optimal cut-off values derived from our study can help in the early diagnosis of PD.
帕金森病（PD）和进行性核上性麻痹（PSP）是具有重叠临床和影像学特征的神经退行性疾病，因此难以将PSP与PD区分和诊断开来。因此，在本研究中，我们旨在探讨磁共振平面测量法和帕金森症指数在区分PSP与PD方面的最佳价值。
在这项回顾性研究中，我们共招募了84例接受脑部MRI检查的患者（27例PSP患者、27例PD患者和27例正常对照）。对于每个受试者，我们在脑部MRI图像上计算胼胝体面积、中脑面积、脑桥面积、小脑中脚（MCP）宽度和小脑上脚（SCP）宽度。我们还计算了脑桥与中脑面积比（P/M）、MCP/SCP比和磁共振帕金森症指数（MRPI）。
采用受试者工作特征曲线（ROC）分析来确定每个生物标志物的诊断价值。MRPI区分PSP与PD的敏感性为70.4%，特异性为88.9%，诊断准确性为79.6%，最佳截断值为24.3。P/M比区分PSP与PD的敏感性为74.1%，特异性为77.8%，诊断准确性为75.9%，最佳截断值为24.3。MCP/SCP比区分PSP与PD的敏感性为66.7%，特异性为77.8%，准确性为72.2%，最佳截断值为4.65。
该研究表明，MRPI和P/M比是区分PSP与PD的准确标志物。我们研究得出的最佳截断值有助于PD的早期诊断。
