ECoG high-gamma modulation versus electrical stimulation for presurgical language mapping

Abstract

Objective: This meta-analysis compared diagnostic validity of electrocorticographic (ECoG) high-γ modulation (HGM) with electrical stimulation mapping (ESM) for presurgical language localization.

Methods: From a structured literature search, studies with electrode level data comparing ECoG HGM and ESM for language localization were included in the meta-analysis. Outcomes included global measures of diagnostic validity: area under the summary receiver operating characteristic (SROC) curve (AUC), and diagnostic odds ratio (DOR); as well as pooled estimates of sensitivity and specificity. Clinical and technical determinants of sensitivity/specificity were explored.

Results: Fifteen studies were included in qualitative synthesis, and 10 studies included in the meta-analysis (number of patients 1-17, mean age 10.3-53.6years). Overt picture naming was the most commonly used task for language mapping with either method. Electrocorticographic high-γ modulation was analyzed at 50-400Hz with different bandwidths in individual studies. For ESM, pulse duration, train duration, and maximum current varied greatly among studies. Sensitivity (0.23-0.99), specificity (0.48-0.96), and DOR (1.45-376.28) varied widely across studies. The pooled estimates are: sensitivity 0.61 (95% CI 0.44, 0.76), specificity 0.79 (95% CI 0.68, 0.88), and DOR 6.44 (95% CI 3.47, 11.94). Area under the SROC curve was 0.77. Results of bivariate meta-regression were limited by small samples for individual variables.

Conclusion: Electrocorticographic high-γ modulation is a specific but not sensitive method for language localization compared with gold-standard ESM. Given the pooled DOR of 6.44 and AUC of 0.77, ECoG HGM can fairly reliably ascertain electrodes overlying ESM cortical language sites.

Keywords: Epilepsy surgery; Functional brain mapping; Language localization.

Figure 1

The PRISMA flow diagram

Figure 2

Forest plots of sensitivity, specificity, and diagnostic odds ratio (DOR) showing study specific estimates with 95% confidence intervals for these metrics. The estimates for DOR are on a logarithmic scale. Since the sensitivity/specificity pairs from all studies are correlated, separate pooled estimates are not calculated for them. Instead, a pooled estimate for DOR is obtained.

Figure 3

Confidence ellipsoids for the uncertainty in the pair of sensitivity and false positive rate Confidence regions for the study specific paired estimates of sensitivity and false positive rate (colored bubble), plotted in the receiver operating characteristic (ROC) space. The size of the bubble is proportional to the total number or electrodes in the study.

Figure 4

Summary Receiver Operating Characteristic (SROC) curve SROC curve is shown with pooled estimate (open circle), 95% confidence region (solid closed curve), and 95% prediction region (dotted closed curve). This curve is obtained by modeling its slope in the logit space as the geometric mean of the slopes of the two regression lines, logit (sensitivity) on logit (false positive rate) and vice versa (Rutter-Gatsonis Hierarchical SROC). Study specific estimates (colored bubbles) are also shown. The size of the bubble is proportional to the total number or electrodes in the study.

Figure 5

Determinants of pairs of sensitivity and false positive rate on bi-variate meta-regression Bi-variate meta-regression showed maximum frequency used for electrocorticographic (ECoG) high-γ modulation (HGM), and maximum current used for electrical stimulation mapping (ESM) to be significant determinants of sensitivity (upper panel). Studies including native speakers of languages other than English showed significantly lower sensitivity and higher specificity (lower panel).