TY - JOUR
T1 - Components of day-to-day variability of cerebral perfusion measurements – Analysis of phase contrast mapping magnetic resonance imaging measurements in healthy volunteers
AU - Ismaili, Abd R.A.
AU - Vestergaard, Mark B.
AU - Hansen, Adam E.
AU - Larsson, Henrik B.W.
AU - Johannesen, Helle H.
AU - Law, Ian
AU - Henriksen, Otto M.
PY - 2018
Y1 - 2018
N2 - Purpose The aim of the study was to investigate the components of day-to-day variability of repeated phase contrast mapping (PCM) magnetic resonance imaging measurements of global cerebral blood flow (gCBF). Materials and methods Two dataset were analyzed. In Dataset 1 duplicated PCM measurements of total brain flow were performed in 11 healthy young volunteers on two separate days applying a strictly standardized setup. For comparison PCM measurements obtained from a previously published study (Dataset 2) were analyzed in order to assess long-term variability in an aged population in a less strictly controlled setup. Global CBF was calculated by normalizing total brain flow to brain volume. On each day measurements of hemoglobin, caffeine and glucose were obtained. Linear mixed models were applied to estimate coefficients of variation (CV) of total (CVt), between-subject (CVb), within-subject day-to-day (CVw), and intra-session residual variability (CVr). Results In Dataset 1 CVt, CVb, CVw and CVr were estimated to be 11%, 9.4%, 4% and 4.2%, respectively, and to 8.8%, 7.2%, 2.7% and 4.3%, respectively, when adjusting for hemoglobin and plasma caffeine. In Dataset 2 CVt, CVb and CVw were estimated to be 25.4%, 19.2%, and 15.0%, respectively, and decreased to 16.6%, 8.2% and 12.5%, respectively, when adjusting for the same covariates. Discussion Our results suggest that short-term day-to-day variability of gCBF is relatively low compared to between-subject variability when studied in standardized conditions, whereas long-term variability in an aged population appears to be much larger when studied in less a standardized setup. The results further showed that from 20% to 35% of the total variability in gCBF can be attributed to the effects of hemoglobin and caffeine.
AB - Purpose The aim of the study was to investigate the components of day-to-day variability of repeated phase contrast mapping (PCM) magnetic resonance imaging measurements of global cerebral blood flow (gCBF). Materials and methods Two dataset were analyzed. In Dataset 1 duplicated PCM measurements of total brain flow were performed in 11 healthy young volunteers on two separate days applying a strictly standardized setup. For comparison PCM measurements obtained from a previously published study (Dataset 2) were analyzed in order to assess long-term variability in an aged population in a less strictly controlled setup. Global CBF was calculated by normalizing total brain flow to brain volume. On each day measurements of hemoglobin, caffeine and glucose were obtained. Linear mixed models were applied to estimate coefficients of variation (CV) of total (CVt), between-subject (CVb), within-subject day-to-day (CVw), and intra-session residual variability (CVr). Results In Dataset 1 CVt, CVb, CVw and CVr were estimated to be 11%, 9.4%, 4% and 4.2%, respectively, and to 8.8%, 7.2%, 2.7% and 4.3%, respectively, when adjusting for hemoglobin and plasma caffeine. In Dataset 2 CVt, CVb and CVw were estimated to be 25.4%, 19.2%, and 15.0%, respectively, and decreased to 16.6%, 8.2% and 12.5%, respectively, when adjusting for the same covariates. Discussion Our results suggest that short-term day-to-day variability of gCBF is relatively low compared to between-subject variability when studied in standardized conditions, whereas long-term variability in an aged population appears to be much larger when studied in less a standardized setup. The results further showed that from 20% to 35% of the total variability in gCBF can be attributed to the effects of hemoglobin and caffeine.
U2 - 10.1371/journal.pone.0197807
DO - 10.1371/journal.pone.0197807
M3 - Journal article
C2 - 29879126
AN - SCOPUS:85048165479
SN - 1932-6203
VL - 13
JO - PLoS Computational Biology
JF - PLoS Computational Biology
IS - 6
M1 - e0197807
ER -