This approach develops a quality control algorithm for cerebrovascular reactivity mapping, indicating enhanced accuracy across different scanning protocols.
Motivation: Cerebrovascular reactivity (CVR) mapping derived from resting-state BOLD has potential for vascular research in large-scale clinical studies. However, it is prone to poor-quality due to the small fluctuation in CO2 concentration during resting breathing, limiting its wide application. Goal(s): To develop an automatic quality control algorithm for resting-state CVR. Approach: Parameters reflecting common characteristics of poor-quality CVR were combined into one comprehensive quality evaluation index (QEI), which was further validated through leave-one-out method and reproducibility studies. Results: The proposed QEI performed not only in good agreement with visual inspection, but can also adapt in resting-state CVR from multiple age groups and scanning protocols. Impact: This work proposed an automatic, objective and quantitative method for quality control of resting-state CVR mapping.
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Wang et al. (2025) studied this question.
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