Impact of region of interest definition on visual stimulation-based cerebral vascular reactivity functional MRI with a special focus on applications in cerebral amyloid angiopathy.

NMR in biomedicine(2023)

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Abstract
Cerebral vascular reactivity quantified using blood oxygen level-dependent functional MRI in conjuncture with a visual stimulus has been proven to be a potent and early marker for cerebral amyloid angiopathy. This work investigates the influence of different postprocessing methods on the outcome of such vascular reactivity measurements. Three methods for defining the region of interest (ROI) over which the reactivity is measured are investigated: structural (transformed V1), functional (template based on the activation of a subset of subjects), and percentile (11.5 cm most responding voxels). Evaluation is performed both in a test-retest experiment in healthy volunteers (N = 12), as well as in 27 Dutch-type cerebral amyloid angiopathy patients and 33 age- and sex-matched control subjects. The results show that the three methods select a different subset of voxels, although all three lead to similar outcome measures in healthy subjects. However, in (severe) pathology, the percentile method leads to higher reactivity measures than the other two, due to circular analysis or "double dipping" by defining a subject-specific ROI based on the strongest responses within each subject. Furthermore, while different voxels are included in the presence of lesions, this does not necessarily result in different outcome measures. In conclusion, to avoid bias created by the method, either a structural or a functional method is recommended. Both of these methods provide similar reactivity measures, although the functional ROI appears to be less reproducible between studies, because slightly different subsets of voxels were found to be included. On the other hand, the functional method did include fewer lesion voxels than the structural method.
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Key words
cerebral amyloid angiopathy,cerebral vascular reactivity,functional MRI,postprocessing
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