Evidence map›Paper›PMID 41559198›Full record

ArticleClinical neuroradiology2026

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

Shiori Amemiya, Jun Kanzawa, Hidemasa Takao, Osamu Abe

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Article in Clinical neuroradiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Shiori AmemiyaDepartment of Radiology, The University of Tokyo, Tokyo, Japan. mamemiya@g.ecc.u-tokyo.ac.jp.
Jun KanzawaDepartment of Radiology, The University of Tokyo, Tokyo, Japan.
Hidemasa TakaoDepartment of Radiology, The University of Tokyo, Tokyo, Japan.
Osamu AbeDepartment of Radiology, The University of Tokyo, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study examined whether task-based functional MRI (fMRI) can provide metrics of local brain activity and hemodynamics typically derived from resting-state fMRI (rsfMRI).

methodsTwo 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.

resultsOur 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.

conclusionRepurposing 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.

Indexed as

BrainBrain MappingBrain NeoplasmsMagnetic Resonance ImagingAdultFemaleHumansMaleMiddle AgedRestRetrospective StudiesHemodynamicsPerfusionResting-state fMRITask fMRI

Identifiers

PMID41559198
PMCPMC13319268

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.