Department of Radiology, Shahid Beheshti University, Tehran, Iran.
Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
PLoS One. 2024 Nov 21;19(11):e0310045. doi: 10.1371/journal.pone.0310045. eCollection 2024.
The diagnosis of Meniere's Disease (MD) presents significant challenges due to its complex symptomatology and the absence of definitive biomarkers. Advancements in MRI technology have spotlighted endolymphatic hydrops (EH) as a key pathological marker, necessitating a reevaluation of its diagnostic utility amidst the need for standardized and validated MRI-based grading scales.
Our meta-analysis scrutinized the diagnostic efficacy of semi-quantitative MRI-based cochlear endolymphatic hydrops (EH) and perilymphatic enhancement (PLE) grading systems in delineating clinically relevant discriminations: "Spotting" the shift from normal or asymptomatic ears to possible/probable MD (pMD), "Confirming" the progression to definite MD (dMD), and "Establishing" the presence of dMD. A thorough literature search up to October 2023 resulted in 35 pertinent studies, forming the basis of our analysis through a bivariate mixed-effects regression model.
Using criteria from the American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS) and Barany Society, across varying thresholds and disease probabilities; the Establishment model at an EH grade 1 threshold revealed a sensitivity of 85.4% and a specificity of 82.7%. Adjusting the threshold to EH grade 2 results in a sensitivity increase to 92.1% (CI: 85.9-95.7) and a specificity decrease to 70.6% (CI: 64.5-76.1), with a DOR of 28.056 (CI: 14.917-52.770). The Confirmation model yields a DOR of 5.216, indicating a lower diagnostic accuracy. The Spotting model demonstrates a sensitivity of 48.3% (CI: 34.8-62.1) and a specificity of 88.0% (CI: 77.8-93.9), with a DOR of 6.882. The normal ears subgroup demonstrated a notably high specificity of 89.7%, while employing Nakashima's criteria resulted in a reduced sensitivity of 74.9%, significantly diverging from other systems (p-value < 0.001). The PLE grading system showcased exceptional sensitivity of 98.4% (CI: 93.7-99.6, p-value < 0.001).
Our meta-analysis supports a tailored diagnostic approach for MD, emphasizing the need for effective grading systems at each stage. For "Spotting," the model shows high specificity but requires improved sensitivity, suggesting additional criteria are needed. The "Confirming" stage highlights the need for refined, sensitive grading systems due to lower diagnostic accuracy. In the "Establishing" stage, an EH grade 1 threshold is effective, but grade 2 enhances sensitivity while reducing specificity, indicating a need for balance. The PLE grading system excels in sensitivity, making it highly reliable. High specificity in the normal ears subgroup confirms accurate non-pathological distinction, though Nakashima's criteria show reduced sensitivity, underscoring variability in grading systems. These findings advocate for a standardized, unified grading system balancing sensitivity and specificity across all MD stages to optimize diagnostics and clinical outcomes.
梅尼埃病(MD)的诊断具有挑战性,因为其症状复杂,且缺乏明确的生物标志物。磁共振成像(MRI)技术的进步突显了内淋巴积水(EH)作为关键病理标志物的作用,这需要在需要标准化和验证的 MRI 分级量表的情况下重新评估其诊断效用。
我们的荟萃分析研究了基于 MRI 的耳蜗内淋巴积水(EH)和外淋巴增强(PLE)分级系统在区分临床相关表现方面的诊断效能:“发现”正常或无症状耳向可能/可能 MD(pMD)的转变,“确认”进展为明确 MD(dMD),以及“确定”存在 dMD。截至 2023 年 10 月,我们进行了全面的文献检索,共检索到 35 项相关研究,通过双变量混合效应回归模型对这些研究进行了分析。
使用美国耳鼻喉科学-头颈外科学会(AAO-HNS)和 Barany 学会的标准,在不同的阈值和疾病概率下;EH 分级 1 级阈值的“确定”模型显示出 85.4%的敏感性和 82.7%的特异性。将阈值调整为 EH 分级 2 级时,敏感性增加至 92.1%(CI:85.9-95.7),特异性降低至 70.6%(CI:64.5-76.1),DOR 为 28.056(CI:14.917-52.770)。“确认”模型的 DOR 为 5.216,表明诊断准确性较低。“发现”模型的敏感性为 48.3%(CI:34.8-62.1),特异性为 88.0%(CI:77.8-93.9),DOR 为 6.882。正常耳亚组的特异性非常高,为 89.7%,而采用 Nakashima 标准时,敏感性降低至 74.9%,与其他系统显著不同(p 值<0.001)。PLE 分级系统的敏感性为 98.4%(CI:93.7-99.6,p 值<0.001),表现出色。
我们的荟萃分析支持针对 MD 的个体化诊断方法,强调每个阶段都需要有效的分级系统。对于“发现”,该模型显示出高特异性但需要提高敏感性,表明需要添加其他标准。“确认”阶段突出了需要改进、敏感的分级系统,因为其诊断准确性较低。在“确定”阶段,EH 分级 1 级阈值是有效的,但分级 2 级增加了敏感性,同时降低了特异性,表明需要平衡。PLE 分级系统在敏感性方面表现出色,因此非常可靠。正常耳亚组的高特异性证实了准确的非病理性区分,尽管 Nakashima 标准的敏感性降低,但突显了分级系统的差异。这些发现支持采用标准化、统一的分级系统,在所有 MD 阶段平衡敏感性和特异性,以优化诊断和临床结果。