Feasibility of Laminar Functional Quantitative Susceptibility Mapping

PURPOSE: Layer fMRI is an increasingly utilized technique that provides insights into the laminar organization of brain activity. However, both blood-oxygen-level-dependent (BOLD) fMRI and vascular space occupancy data (VASO) have certain limitations, such as bias towards larger cortical veins in BOLD fMRI and high specific absorption rate in VASO. This study aims to explore the feasibility of whole-brain laminar functional quantitative susceptibility mapping (fQSM) compared to laminar BOLD fMRI and VASO at ultra-high field. METHODS: Data were acquired using 3D EPI techniques. Complex data were denoised with NORDIC and susceptibility maps were computed using 3D path-based unwrapping, the variable-kernel sophisticated harmonic artifact reduction, as well as the streaking artifact reduction for QSM algorithms. To assess layer-specific activation, 20 layers were segmented in the somatosensory and motor cortices, obtained from a finger tapping paradigm, and further averaged into six anatomical cortical layers. The magnitude of signal change and z-scores were compared across layers for each technique. RESULTS: fQSM showed the largest activation-dependent mean susceptibility decrease in Layers II/III in M1 and Layers I/II in S1 with up to -1.3 ppb while BOLD showed the strongest mean signal increase in Layer I. Our data suggest that fQSM demonstrates less bias towards activation in superficial layers compared to BOLD. Moreover, activation-based susceptibility change was comparable to VASO data. CONCLUSION: Studying whole-brain, layer-dependent activation with submillimeter fQSM is feasible and reduces bias towards venous drainage effects on the cortical surface compared to BOLD, thereby enabling better localization of laminar activation.

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Publication Details

Journal
Magnetic Resonance in Medicine
Published
2026-09-06
DOI
https://doi.org/10.1002/mrm.70576
Citations
1
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
1.86
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article

Feasibility of Laminar Functional Quantitative Susceptibility Mapping

Erin Westerhold, Erik H. Middlebrooks, Shengzhen Tao, Xiangzhi Zhou et al.
1 citations
Magnetic Resonance in Medicine
Machine Learning in Materials Science
1.86
article

Feasibility of Laminar Functional Quantitative Susceptibility Mapping

Erin Westerhold, Erik H. Middlebrooks, Shengzhen Tao, Xiangzhi Zhou, Sina Straub, Jin Jin
article en
1 citations

Abstract

PURPOSE: Layer fMRI is an increasingly utilized technique that provides insights into the laminar organization of brain activity. However, both blood-oxygen-level-dependent (BOLD) fMRI and vascular space occupancy data (VASO) have certain limitations, such as bias towards larger cortical veins in BOLD fMRI and high specific absorption rate in VASO. This study aims to explore the feasibility of whole-brain laminar functional quantitative susceptibility mapping (fQSM) compared to laminar BOLD fMRI and VASO at ultra-high field. METHODS: Data were acquired using 3D EPI techniques. Complex data were denoised with NORDIC and susceptibility maps were computed using 3D path-based unwrapping, the variable-kernel sophisticated harmonic artifact reduction, as well as the streaking artifact reduction for QSM algorithms. To assess layer-specific activation, 20 layers were segmented in the somatosensory and motor cortices, obtained from a finger tapping paradigm, and further averaged into six anatomical cortical layers. The magnitude of signal change and z-scores were compared across layers for each technique. RESULTS: fQSM showed the largest activation-dependent mean susceptibility decrease in Layers II/III in M1 and Layers I/II in S1 with up to -1.3 ppb while BOLD showed the strongest mean signal increase in Layer I. Our data suggest that fQSM demonstrates less bias towards activation in superficial layers compared to BOLD. Moreover, activation-based susceptibility change was comparable to VASO data. CONCLUSION: Studying whole-brain, layer-dependent activation with submillimeter fQSM is feasible and reduces bias towards venous drainage effects on the cortical surface compared to BOLD, thereby enabling better localization of laminar activation.

Magnetic Resonance in Medicine
Jacksonville College (US), Mayo Clinic in Florida (US), Siemens (Australia) (AU)
Openalex Percentile: Top 23%
Machine Learning in Materials Science
1.86
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