Lack of Association of CNS Lesion Number with Cognitive Performance and Cerebral Blood Flow in Sickle Cell Disease

Background:Neurocognitive studies demonstrate a deficit in performance for sickle cell anemia (SCA) patients as compared to age-matched peers. The underlying mechanism for this deficit is not yet understood, but possible contributors include CNS lesion load, perfusion deficits, oxygen deprivation and cerebrovascular autoregulatory impairment. We hypothesized that the number of white matter hyperintensities and the cerebral blood flow (CBF) might contribute to cerebral dysfunction in SCA patients. We sought to examine the relationship between cognition, laboratory parameters and brain perfusion in sickle cell patients as compared to non-sickle cell (AA) controls. 

Methods:  SCA (HbSS/HbSβ⁰) and AA subjects, ages 18-55 years old, with no evidence of TIA/Stroke, no clotting/bleeding disorders, and not on anticoagulation were recruited. Hydroxyurea use was noted but was neither an inclusion nor exclusion criterion. Evaluation included a routine questionnaire for basic social, educational and health information. Steady state laboratory evaluation was obtained within one week of imaging. Neurocognitive performance was evaluated by the Cogstate battery at the time of the MRI. Cogstate analysis included tests of executive function, recall, social and emotional cognition and learning. Lesion number and CBF were determined using 3T MRI, which included T1w 3D, T2 FLAIR, pseudo-continuous arterial spin labeling, diffusion tensor imaging, and blood oxygen level depending imaging before and during a brief period of hyperoxia. Oxygen saturation and blood pressure were monitored throughout the procedure at 5-minute intervals.

Results:To date, we have recruited 15 SCA and 7 AA subjects who answered a tailored questionnaire and underwent 3T MRI, routine laboratory testing and neurocognitive testing. Of the 15 SCA subjects, 6 had no lesions on 3T MRI and 9 had multiple lesions with 8 persons having more than 5.  Lesion number correlated only with age (p=0.02).  Of the 7 AA patients, 3 had no lesions, 2 had 1, 1 had 4 and 1 patient had >20 lesions.  SCA patients fared worse on only one of the cognitive tests, the Groton Maze Learning Test for executive function (GMLT), in which a higher GMLT demonstrates decreased ability (p=0.02). Amongst the SCA subjects, a worse score on GMLT correlated positively with age (p=0.03), ferritin (p=0.02), mean arterial pressure (p=.02) and %HbF (p=0.03) while GMLT correlated negatively with %S (p=0.007), indirect bilirubin (p=0.02) and absolute reticulocyte count (p=0.005). There did not appear to be a relationship of GMLT with LDH, Hb, MCV, MCHC, platelet count, white cell parameters, number of crisis, oxygen saturation, CBF or lesion load. Gray matter CBF in SCA patients was significantly greater than that in AA subjects (164 ml/100g/min vs 113 ml/100g/min in AA, p < 0.007) as was white matter CBF (93 ml/100g/min vs 71 ml/100g/min, p=0.03).  Both gray matter and white matter CBF correlated negatively with Hb/Hct levels in SCA patients (p=0.004). SCA patients also had a significantly lower average DP and MAP than the AA patients (p-0.004 and 0.015 respectively).

Discussion:This study was undertaken to assess the role of a variety of clinical parameters against neurocognitive performance in SCA patients who had not been diagnosed with prior CVA or stroke. None-the-less, with the use of more powerful 3T MRI technology, there is an increase in the measurement and prevalence of white matter lesions in both SCA and AA subjects and a significant proportion of subjects were found to have evidence of white matter lesions.  While white matter hyperintensities have been associated with cognitive outcomes, better detection of these lesions questions these assumptions and the prevailing theory that white matter hyperintensities are a marker of cerebral health and predict cognitive performance. Lesion number did not demonstrate an association with CBF or the GMLT; CBF correlated only with Hb levels and did not correlate with GMLT.  There was an association of age with both cognition, as measured by the GMLT, and with lesion number.

Conclusion: We suggest that diffuse cerebral dysfunction, rather than discrete infarct quantity, may be the more important mechanism of decreased cognition.  We are currently assessing the functional assessments by fMRI to better delineate the nature of this cerebral dysfunction.