Cervical Vestibular Evoked Myogenic Potentials in Menière's Disease: A Comparison of Response Metrics

Abstract

Objective: The cervical vestibular evoked myogenic potential (cVEMP) has been used to evaluate patients with Menière's disease (MD). Studied cVEMP metrics include: amplitude, threshold, frequency tuning, and interaural asymmetry ratio (IAR). However, few studies compared these metrics in the same set of MD patients, and methodological differences prevent such a comparison across studies. This study investigates the value of different cVEMP metrics in distinguishing one set of MD patients from age-matched controls.

Study design: Prospective study.

Setting: Tertiary care center.

Patients: Thirty patients with definite unilateral MD and 23 age-matched controls were prospectively included. All underwent cVEMP testing at 500, 750, 1000, and 2000 Hz on each side. Ears were separated into three groups: affected MD, unaffected MD, and control.

Main outcome measures: Sound level functions were obtained at each frequency, and normalized peak-to-peak amplitude (VEMPn), VEMP inhibition depth (VEMPid), threshold, frequency-tuning ratio, and IAR were calculated. For all metrics, the differentiation between MD and control ears was compared using receiver operating characteristic (ROC) curves.

Results: 500 Hz cVEMP threshold, VEMPn, and VEMPid were similarly good at distinguishing affected MD ears from healthy ears, with ROC area under the curves (AUCs) of more than 0.828 and optimal sensitivities and specificities of at least 80 and 70%. Combinations of these three metrics yielded slightly larger AUCs (>0.880). Tuning ratios and IAR were less effective in separating healthy from affected ears with AUCs ranging from 0.529 to 0.720.

Conclusion: The cVEMP metrics most useful in distinguishing MD patients from healthy controls are threshold, VEMPn, and VEMPid, using 500 Hz stimuli.

Figure 1.

Average bone conduction threshold for each group and frequency (A). Low-frequency bone conduction thresholds (averaged across 250, 500 and 1000 Hz) for each group (B). Error bars indicate 95% confidence intervals.

Figure 2.

Average normalized peak-to-peak amplitude (VEMPn; top row) and VEMP inhibition depth (VEMPid; bottom row) for 500, 750, 1000 and 2000 Hz. Comparisons across groups are best done using the thick dashed lines, which show the highest sound level that was used on all groups (123 dB peSPL). The 123 dB peSPL data are also displayed in the panels on the right to facilitate comparison across groups. On average, VEMPn and VEMPid were largest in the control group, followed by unaffected Meniere’s disease (MD) ears and were lowest for affected MD ears. Error bars indicate the 95% confidence intervals.

Figure 3.

Average cVEMP threshold for the control (open circles), unaffected (grey circles) and affected (black circles) groups at 500, 750, 1000 and 2000 Hz. Error bars indicate the 95% confidence intervals.

Figure 4.

cVEMP frequency tuning varied across groups. Group threshold tuning was compared by the fraction of ears with 500/1000 Hz ratios below, at, and above unity (A), and by average 500/1000 Hz threshold (B) and VEMPn (C) ratios. Error bars indicate the 95% confidence intervals.

Figure 5.

Interaural asymmetry ratios (IAR) calculated in five ways (see Methods). Symbols indicate average IARs using the 123 dB peSPL data for all frequencies; error bars indicate 95% confidence intervals. See Methods for formulas: Abs indicates the absolute values of the differences were used.

Figure 6.

Receiver operating characteristic (ROC) curves displaying the ability of various cVEMP statistics to separate Meniere’s from normal ears. Each panel shows the sensitivity of detecting Meniere’s disease (the true-positive rate) versus the false-positive rate (1 - specificity) for 500, 750 and 1000 Hz data at 123 dB peSPL. Top-row ROC statistics are threshold, normalized peak-to-peak amplitude (VEMPn) and VEMP inhibition depth (VEMPid). Bottom-row ROC statistics are 500/1000 Hz threshold ratio, VEMPn 500/1000 Hz ratio and ROCs created by combinations of the top-row metrics. Because the 500 Hz top-row data yielded the largest AUCs, this frequency was used to evaluate combinations of these metrics (bottom right panel). In each panel, the area under the curve (AUC) and 95% confidence interval (CI) of each line are displayed.