Presurgical language fMRI: Clinical practices and patient outcomes in epilepsy surgical planning

Benjamin, Christopher; Li, Alexa X.; Blumenfeld, Hal; Constable, R. Todd; Alkawadri, Rafeed; Bickel, Stephan; Helmstaedter, Christoph; Meletti, Stefano; Bronen, Richard A.; Warfield, Simon K.; Peters, Jurriaan M.; Reutens, David C.; Połczyńska, Monika; Spencer, Dennis D.; Hirsch, Lawrence J.

doi:10.1002/hbm.24039

Cited by 48 publications

(52 citation statements)

References 28 publications

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“…Based on these results, the authors recommended routine follow-up for patients with atypical language fMRI with a Wada test. Other authors have voiced similar concerns and recommended routinely repeating language fMRIs that indicate right dominance (Benjamin et al, 2018). Therefore, the present work is useful in showing that fMRI can identify right-lateralized cases with high confidence.…”

Section: Discussionmentioning

confidence: 70%

“…While the advantages of different implementations of the laterality index are under debate (Wilke and Lidzba, 2007;Bradshaw et al, 2017a), they have proven to be robust, provided that the data are of sufficient quality (Wegrzyn et al, 2019). With fMRI being able to predict the results of the Wada test with accuracies around 90% (Dym et al, 2011;Bauer et al, 2014) it has become an established tool for lateralizing language (Binder, 2011;Szaflarski et al, 2017;Benjamin et al, 2018). Its non-invasive nature is an important asset for a biomarker, as it can be easily repeated, extended and used on many patients, as well as healthy normative samples (Gabrieli et al, 2015;Dubois and Adolphs, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…However, there are a number of challenges yet to be solved. A number of studies have shown that fMRI is able to predict typical left-lateralization with high accuracy, but it is less reliable for atypical cases (Benke et al, 2006;Arora et al, 2009;Janecek et al, 2013;Benjamin et al, 2018). One meta-analysis showed accuracies around 95% for typical and only around 50% for atypical cases (Bauer et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

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Volume-wise analysis of fMRI time series allows accurate prediction of language lateralization

Wegrzyn

Mertens

Bien

et al. 2019

Preprint

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Using fMRI as a clinical tool, for example for lateralizing language, requires that it provides accurate results on the individual level. However, using a single voxel-wise activity map per patient limits how well the uncertainty associated with a decision can be estimated. Here, we explored how using a "volume-wise" analysis, where the lateralization of each time point of a patient's fMRI session is evaluated independently, could support clinical decision making. Ninety-six patients with epilepsy who performed a language fMRI were analyzed retrospectively. Results from Wada testing were used as an indication of true language lateralization. Each patient's 200 fMRI volumes were correlated with an independent template of prototypical lateralization. Depending on the strength of correlation with the template, each volume was classified as indicating either left-lateralized, bilateral or right-lateralized language. A decision about the patient's language lateralization was then made based on how most volumes were classified. The results show that, using a simple majority vote, accuracies of 84% were reached in a sample of 63 patients with high-quality data. When 33 patients with datasets previously deemed inconclusive were added, the same accuracy was reached when more than 43% of a patient's volumes were in agreement with each other. Increasing this cutoff to 51% volumes with agreeing classifications allowed for excluding all inconclusive cases and reaching accuracies over 90% for the remaining cases. Further increasing the cutoff to 65% agreeing volumes resulted in correct predictions for all remaining patients. The study confirms the usefulness of fMRI for language lateralization in patients with epilepsy, by demonstrating high accuracies. Furthermore, it illustrates how the diagnostic yield of individual volumes of fMRI data can be increased using simple similarity measures. The accuracy of our approach increased with the number of agreeing volumes, and thus allowed estimating the uncertainty associated with each individual diagnosis.

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Section: Discussionmentioning

confidence: 70%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Volume-wise analysis of fMRI time series allows accurate prediction of language lateralization

Wegrzyn

Mertens

Bien

et al. 2019

Preprint

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“…A second survey, focused on clinicians' interpretation of fMRI and patient outcomes, was also forwarded to the "epilepsy surgical program [director], or a senior clinician involved in determining patients' surgical eligibility" with this survey. While these surveys were intended to be paired, most sites did not submit paired responses, and thus the clinical survey is reported separately [Benjamin et al, 2018]. Nine respondents from that manuscript completed both surveys; their responses on accuracy and outcomes are also included here (Section 3.6).…”

Section: Surveymentioning

confidence: 99%

“…The optimal choices for each variable continue to be subject to debate, though they clearly alter the precise language map obtained [e.g., Benjamin et al, 2018 Figure 3]. While this variation may be less likely to impact lateralization, it will certainly impact localization; and we recently reported that 44% of epilepsy surgical programs use fMRI for this purpose [Benjamin et al, 2018].…”

Section: Introductionmentioning

confidence: 96%

Presurgical language fMRI: Current technical practices in epilepsy surgical planning

Benjamin

Dhingra

et al. 2018

Preprint

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Little is known about how language functional MRI (fMRI) is executed in clinical practice in spite of its widespread use. Here we comprehensively documented its execution in surgical planning in epilepsy. A questionnaire focusing on cognitive design, imaging acquisition, analysis and interpretation and practical considerations was developed. Individuals responsible for collecting, analyzing, and interpreting clinical language fMRI data at 63 epilepsy surgical programs responded. The central finding was of marked heterogeneity in all aspects of fMRI. Most programs use multiple tasks, with a fifth routinely using 2, 3, 4 or 5 tasks with a modal run duration of five minutes. Variants of over fifteen protocols are in routine use with forms of noun-verb generation, verbal fluency, and semantic decision-making used most often. Nearly all aspects of data acquisition and analysis vary markedly. Neither of the two best-validated protocols were used by more than 10% of respondents. Preprocessing steps are broadly consistent across sites, language-related blood flow is most often identified using general linear modeling (76% of respondents), and statistical thresholding typically varies by patient (79%). The software SPM is most often used. fMRI programs inconsistently include input from experts with all required skills (imaging, cognitive assessment, MR physics, statistical analysis, brain-behavior relationships). These data highlight marked gaps between the evidence supporting fMRI and its clinical application. Teams performing language fMRI may benefit from evaluating practice with reference to the best-validated protocols to date and ensuring individuals trained in all aspects of fMRI are involved to optimize patient care.

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Standardization of presurgical language fMRI in Greek population: Mapping of six critical regions

et al. 2022

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Background Mapping the language system has been crucial in presurgical evaluation especially when the area to be resected is near relevant eloquent cortex. Functional magnetic resonance imaging (fMRI) proved to be a noninvasive alternative of Wada test that can account not only for language lateralization but also for localization when appropriate tasks and MRI sequences are being used. The tasks utilized during the fMRI acquisition are playing a crucial role as to which areas will be activated. Recent studies demonstrated that key language regions exist outside the classical model of “Wernicke–Lichtheim–Geschwind,” but sensitive tasks must take place in order to be revealed. On top of that, the tasks should be in mother tongue for appropriate language mapping to be possible. Methods For that reason, in this study, we adopted an English protocol that can reveal six language critical regions even in clinical setups and we translated it into Greek to prove its efficacy in Greek population. Twenty healthy right‐handed volunteers were recruited and performed the fMRI acquisition in a standardized manner. Results Results demonstrated that all six language critical regions were activated in all subjects as well as the group mean map. Furthermore, activations were found in the thalamus, the caudate, and the contralateral cerebellum. Conclusion In this study, we standardized an fMRI protocol in Greek and proved that it can reliably activate six language critical regions. We have validated its efficacy for presurgical language mapping in Greek patients capable to be adopted in clinical setup.

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Presurgical language fMRI: Clinical practices and patient outcomes in epilepsy surgical planning

Cited by 48 publications

References 28 publications

Volume-wise analysis of fMRI time series allows accurate prediction of language lateralization

Volume-wise analysis of fMRI time series allows accurate prediction of language lateralization

Presurgical language fMRI: Current technical practices in epilepsy surgical planning

Standardization of presurgical language fMRI in Greek population: Mapping of six critical regions

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