Subject‐level reliability analysis of fast fMRI with application to epilepsy

• Published in: Magnetic resonance in medicine Vol. 78; no. 1; pp. 370 - 382
• Main Authors: Hao, Yongfu, Khoo, Hui Ming, von Ellenrieder, Nicolas, Gotman, Jean
• Format: Journal Article
• Language: English
• Published: United States Wiley Subscription Services, Inc 01.07.2017
• Subjects: Activation; Activation analysis; Adult; Autoregressive models; Autoregressive processes; Brain - diagnostic imaging; Brain - physiopathology; Brain Mapping - methods; Criteria; Data processing; Datasets; Discharge; EEG; Electroencephalography; Epilepsy; Epilepsy - diagnostic imaging; Epilepsy - physiopathology; Female; fMRI; Functional magnetic resonance imaging; Generalized linear models; GLM; Ground truth; Head; Humans; Image Interpretation, Computer-Assisted - methods; Latency; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Male; Medicine; Observer Variation; Patients; Regression analysis; reliability; Reliability analysis; Reproducibility of Results; Sampling; Sensitivity and Specificity; Signal Processing, Computer-Assisted; epilepsy; fMRI; GLM; EEG; reliability
• ISSN: 0740-3194; 1522-2594; 1522-2594
• DOI: 10.1002/mrm.26365

Purpose Recent studies have applied the new magnetic resonance encephalography (MREG) sequence to the study of interictal epileptic discharges (IEDs) in the electroencephalogram (EEG) of epileptic patients. However, there are no criteria to quantitatively evaluate different processing methods, to properly use the new sequence. Methods We evaluated different processing steps of this new sequence under the common generalized linear model (GLM) framework by assessing the reliability of results. A bootstrap sampling technique was first used to generate multiple replicated data sets; a GLM with different processing steps was then applied to obtain activation maps, and the reliability of these maps was assessed. Results We applied our analysis in an event‐related GLM related to IEDs. A higher reliability was achieved by using a GLM with head motion confound regressor with 24 components rather than the usual 6, with an autoregressive model of order 5 and with a canonical hemodynamic response function (HRF) rather than variable latency or patient‐specific HRFs. Comparison of activation with IED field also favored the canonical HRF, consistent with the reliability analysis. Conclusion The reliability analysis helps to optimize the processing methods for this fast fMRI sequence, in a context in which we do not know the ground truth of activation areas. Magn Reson Med 78:370–382, 2017. © 2016 International Society for Magnetic Resonance in Medicine