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The elusive metric of lesion load

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Abstract

One of the widely used metrics in lesion-symptom mapping is lesion load that codes the amount of damage to a given brain region of interest. Lesion load aims to reduce the complex 3D lesion information into a feature that can reflect both site of damage, defined by the location of the region of interest, and size of damage within that region of interest. Basically, the process of estimation of lesion load converts a voxel-based lesion map into a region-based lesion map, with regions defined as atlas-based or data-driven spatial patterns. Here, after examining current definitions of lesion load, four methodological issues are discussed: (1) lesion load is agnostic to the location of damage within the region of interest, and it disregards damage outside the region of interest, (2) lesion load estimates are prone to errors introduced by the uncertainty in lesion delineation, spatial warping of the lesion/region, and binarization of the lesion/region, (3) lesion load calculation depends on brain parcellation selection, and (4) lesion load does not necessarily reflect a white matter disconnection. Overall, lesion load, when calculated in a robust way, can serve as a clinically-useful feature for explaining and predicting post-stroke outcome and recovery.

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Data sharing not applicable as no datasets were generated or analysed in this work.

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Funding

 This work was funded by Khalifa University (grant number:  FSU-2022-006 and RC2-2018-022).

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  1. Department of Biomedical Engineering, Khalifa University of Science and Technology, Abu Dhabi, UAE

    Mohamed L. Seghier

  2. Healthcare Engineering Innovation Center (HEIC), Khalifa University of Science and Technology, Abu Dhabi, UAE

    Mohamed L. Seghier

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  1. Mohamed L. Seghier
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M.L.S. wrote and revised the manuscript.

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Correspondence to Mohamed L. Seghier.

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Seghier, M.L. The elusive metric of lesion load. Brain Struct Funct 228, 703–716 (2023). https://doi.org/10.1007/s00429-023-02630-1

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