Individual Watershed Areas in Sickle Cell Anemia: An Arterial Spin Labeling Study

Abstract

Previous studies have pointed to a role for regional cerebral hemodynamic stress in neurological complications in patients with sickle cell anemia (SCA), with watershed regions identified as particularly at risk of ischemic tissue injury. Using single- and multi-inflow time (TI) arterial spin labeling sequences (ASL) in 94 patients with SCA and 42 controls, the present study sought to investigate cerebral blood flow (CBF) and bolus arrival times (BAT) across gray matter, white matter with early arrival times, and in individual watershed areas (iWSAs). In iWSAs, associations between hemodynamic parameters, lesion burden, white matter integrity, and general cognitive performance were also explored. In patients, increases in CBF and reductions in BAT were observed in association with reduced arterial oxygen content across gray matter and white matter with early arrival times using both sequences (all p < 0.001, d = -1.55--2.21). Across iWSAs, there was a discrepancy between sequences, with estimates based on the single-TI sequence indicating higher CBF in association with reduced arterial oxygen content in SCA patients, and estimates based on the multi-TI sequence indicating no significant between-group differences or associations with arterial oxygen content. Lesion burden was similar between white matter with early arrival times and iWSAs in both patients and controls, and using both sequences, only trend-level associations between iWSA CBF and iWSA lesion burden were observed in patients. Further, using the multi-TI sequence in patients, increased iWSA CBF was associated with reduced iWSA microstructural tissue integrity and slower processing speed. Taken together, the results highlight the need for researchers to consider BAT when estimating CBF using single-TI sequences. Moreover, the findings demonstrate the feasibility of multi-TI ASL for objective delineation of iWSAs and for detection of regional hemodynamic stress that is associated with reduced microstructural tissue integrity and slower processing speed. This technique may hold promise for future studies and treatment trials.

Keywords: MRI; arterial spin labeling; cerebral hemodynamics; cognition; hemoglobinopathies; intelligence quotient (IQ); processing speed index; silent cerebral infarction.

FIGURE 1

Regions of interest. Showing regions of interest (i.e., grey matter (GM), white matter with early arrival times (WM early), white matter with late arrival times/individual watershed areas (WM late, iWSA) overlaid in white on cerebral blood flow (CBF) and bolus arrival time (BAT) maps from the single inflow time (SingleTI) and multi inflow time (multiTI) sequences in a representative participant with sickle cell anemia (male, 12 years of age).

FIGURE 2

Individual Watershed Area. Showing the individual watershed area (iWSA) region of interest overlaid in white on a single inflow time cerebral blood blow (CBF) map from a representative participant with sickle cell anemia (male, 8 years of age).

FIGURE 3

Participant flow-chart. Visualization of reasons for participant exclusion (Stotesbury et al., 2022). Note that while most participants had usable data for both sequences (N = 75 patients, n = 36 controls), others only had usable data for the single TI sequence (n = 14 patients, n = 6 controls), or the multiTI sequence (n = 5 patients, 0 controls). ASL Arterial Spin Labeling; MRI magnetic resonance imaging; POMS, Prevention of Morbidity in Sickle Cell Disease; SAC, Sleep Asthma Cohort; TI, inflow time.

FIGURE 4

Kinetic curves. Line-plots showing raw kinetic curves (i.e., difference signal at each timepoint) from the multi inflow time sequence across regions of interest in patients (bottom: shown in red) and controls (top: shown in blue). Abbreviations: GM, gray matter; WM, white matter; iWSAs, individual watershed areas.

FIGURE 5

Hemodynamic parameters across regions of interest. Boxplots showing mean cerebral blood flow (CBF) and bolus arrival times (BAT) based on the single- and multi-inflow time sequences (rows) across different regions of interest (ROIs; columns) in patients with sickle cell anemia (shown in red) and healthy controls (shown in blue). Standardized mean differences (d) and probability values from independent t-tests (p) adjusted within parameter types for multiple comparisons using the Benjamini and Hochberg false discovery rate (p adj.) are displayed. ^ between-group differences in iWSA CBF reported with outlying control excluded. Between group differences remain non-significant when the outlier is included (p = 0.51). Abbreviations: GM, gray matter; WM, white matter; iWSAs, individual watershed areas.

FIGURE 6

Correlations with arterial oxygen content. Scatterplots showing the relationship between arterial oxygen content and age- and sex-adjusted mean cerebral blood flow (CBF) and bolus arrival time (BAT) based on the single- and multi-inflow time sequences (rows) across different regions of interest (columns) in patients with sickle cell anemia (shown in red). Pearson’s correlation coefficients (r), Spearmans Rho (r) and p-values (p) adjusted within parameter types for multiple comparisons using the Benjamini and Hochberg false discovery rate (p adj.) are displayed. Abbreviations: GM, gray matter; WM, white matter; iWSAs, individual watershed areas.

FIGURE 7

Correlations with lesion burden and microstructural integrity in iWSAs. (A) Pie charts showing the proportion of total lesion voxels in white matter with early arrival times, individual watershed areas (iWSAs), and that were unclassified (i.e., excluded due to unreliable signal or eroded to avoid potential partial volume effects) in patients with SCA (top; shown in red) and controls (bottom; shown in blue). (B) Boxplot comparing the median proportion of classified lesion voxels in white matter with late arrival times/iWSAs between SCA patients (shown in red) and controls (shown in blue). (C) Scatterplots showing the association between age-and sex-adjusted median fractional anisotropy (FA) and age- and sex-mean adjusted cerebral blood flow (CBF) based on the single inflow time sequence (top), CBF based on the multi inflow time sequence (middle) and bolus arrival time (BAT) based on the multi inflow time sequence (bottom) across iWSAs in patients with SCA (shown in red) and controls (shown in blue). Values are Spearman’s correlation coefficients (rho) and p-values (p).

FIGURE 8

Exploratory Mediation Analysis. (A) Scatterplots showing the relationship between PSI and age- and sex-adjusted mean cerebral blood flow (CBF) across individual watershed areas (iWSA) based on the multi-inflow time sequence (left) and fractional anisotropy across iWSA in patients with sickle cell anemia (shown in red) and controls (shown in blue). (B): A path diagram showing the direct effect of mean cerebral blood flow (CBF) across white matter with late arrival times/individual watershed areas (iWSAs) on processing speed index (PSI) along with the indirect effect of CBF on PSI through fractional anisotropy across this region (FA iWSA) in SCD patients. Values are unstandardized regression coefficients. *p < 0.05, **p < 0.01, ***p < 0.001.