Leveraging Task FMRI Data to Extract Resting-State Metrics in Brain Tumor and Healthy Populations

PURPOSE: This study examined whether task-based functional MRI (fMRI) can provide metrics of local brain activity and hemodynamics typically derived from resting-state fMRI (rsfMRI). METHODS: Two publicly open datasets from healthy individuals and brain tumor patients were retrospectively used to compare amplitude of low-frequency fluctuations (ALFF) and global signal metrics, namely, global signal correlation (GSC), global signal cross-correlation (GSXC), and global signal time delay (GSTD) derived from motor and language fMRI with those from a reference rsfMRI scan (rest-1). Factors influencing the correlations between each measurement were examined using a mixed-effects model with post-hoc pairwise comparisons. RESULTS: Our study included 50 healthy subjects (mean age: 29 ± 3 years; 32 women) and 38 patients (45 ± 14 years; 24 men). Significant correlations (p < 0.001) were found for all metrics between those derived from motor, language, or a second rest scan (rest-2) against rest-1 scans for both healthy subjects and patients. Both fMRI type and motion magnitude affected the measurements of healthy subjects' GSC (fMRI type: F [2, 69.1] = 15.4, p < 0.001; motion: F [1, 123.1] = 8.5, p = 0.004), GSXC (fMRI type: F [2, 69.5] = 18.9, p < 0.001; motion: F [1, 123.2] = 9.89, p = 0.002), and GSTD (fMRI type: F [2, 58.7] = 9.89, p < 0.001; motion: F [1, 123.2] = 15.26, p < 0.001). FMRI type by motion interaction was significant for ALFF (F [2, 65.9] = 6.13, p = 0.004). The effects were less pronounced and observed only for GSC (F [2, 40.4] = 6.1, p = 0.005) and GSXC (F [2, 41.2] = 6.4, p = 0.004) in the clinical dataset. CONCLUSION: Repurposing existing task-based functional MRI data for evaluating local brain activities and hemodynamics is feasible in the entire brain in healthy and brain tumor subjects.