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Although arterial spin labeling (ASL) is appealing for mapping long-term changes in functional activity, inter-sessional variations in basal blood flow, arterial transit times (ATTs), and alignment errors, can result in significant false activation when comparing images from separate sessions. By taking steps to reduce these sources of noise, this study assessed the ability of ASL to detect functional CBF changes between sessions. ASL data were collected in three sessions to image ATT, resting CBF and CBF changes associated with motor activation (7 participants). Activation maps were generated using rest and task images acquired in the same session and from sessions separated by up to a month. Good agreement was found when comparing between-session activation maps to within-session activation maps with only a 16% decrease in precision (within-session: 90 ± 7%) and a 13% decrease in the Dice similarity (within-session: 0.75 ± 0.07) coefficient after a month. In addition, voxel-wise reproducibility (within-session: 4.7 ± 4.5%) and reliability (within-session: 0.89 ± 0.20) of resting grey-matter CBF decreased by less than 18% for the betweensession analysis relative to within-session values. ATT variability between sessions (5.0 ± 2.7%) was roughly half the between-subject variability, indicating that its effects on longitudinal CBF were minimal. These results demonstrate that conducting voxel-wise analysis on CBF images acquired on different days is feasible with only modest loss in precision, highlighting the potential of ASL for longitudinal studies.