Venous cerebral blood flow quantification and cognition in patients with sickle cell anemia

1. Stotesbury, H, Kawadler, JM, Hales, PW, et al. Vascular instability and neurological morbidity in sickle cell disease: an integrative framework. Front Neurol 2019; 10: 871.
Google Scholar | Crossref | Medline2. Ludwig, NN, Sil, S, Khowaja, MK, et al. Executive functioning mediates the relationship between pain coping and quality of life in youth with sickle cell disease. J Pediatr Psychol 2018; 43: 1160–1169.
Google Scholar | Crossref | Medline3. Nath, KA, Katusic, ZS, Gladwin, MT. The perfusion paradox and vascular instability in sickle cell disease. Microcirculation 2004; 11: 179–193.
Google Scholar | Crossref | Medline4. Gladwin, MT, Sachdev, V. Cardiovascular abnormalities in sickle cell disease. J Am Coll Cardiol 2012; 59: 1123–1133.
Google Scholar | Crossref | Medline | ISI5. Jordan, LC, DeBaun, MR. Cerebral hemodynamic assessment and neuroimaging across the lifespan in sickle cell disease. J Cereb Blood Flow Metab 2018; 38: 1438–1448.
Google Scholar | SAGE Journals | ISI6. Bush, AM, Borzage, MT, Choi, S, et al. Determinants of resting cerebral blood flow in sickle cell disease. Am J Hematol 2016; 91: 912–917.
Google Scholar | Crossref | Medline7. Chai, Y, Bush, AM, Coloigner, J, et al. White matter has impaired resting oxygen delivery in sickle cell patients. Am J Hematol 2019; 94: 467–474.
Google Scholar | Crossref | Medline8. Ford, AL, Ragan, DK, Fellah, S, et al. Silent infarcts in sickle cell disease occur in the border zone region and are associated with low cerebral blood flow. Blood 2018; 132: 1714–1723.
Google Scholar | Crossref | Medline9. Novelli, EM, Elizabeth Sarles, C, Jay Aizenstein, H, et al. Brain venular pattern by 7T MRI correlates with memory and haemoglobin in sickle cell anaemia. Psychiatry Res 2015; 233: 18–22.
Google Scholar | Crossref | Medline10. Prohovnik, I, Hurlet-Jensen, A, Adams, R, et al. Hemodynamic etiology of elevated flow velocity and stroke in sickle-cell disease. J Cereb Blood Flow Metab 2009; 29: 803–810.
Google Scholar | SAGE Journals | ISI11. Kosinski, PD, Croal, PL, Leung, J, et al. The severity of anaemia depletes cerebrovascular dilatory reserve in children with sickle cell disease: a quantitative magnetic resonance imaging study. Br J Haematol 2017; 176: 280–287.
Google Scholar | Crossref | Medline12. Nur, E, Kim, Y-S, Truijen, J, et al. Cerebrovascular reserve capacity is impaired in patients with sickle cell disease. Blood 2009; 114: 3473–3478.
Google Scholar | Crossref | Medline | ISI13. Václavů, L, Meynart, BN, Mutsaerts, HJMM, et al. Hemodynamic provocation with acetazolamide shows impaired cerebrovascular reserve in adults with sickle cell disease. Haematologica 2019; 104: 690–699.
Google Scholar | Crossref | Medline14. Kim, JA, Leung, J, Lerch, JP, et al. Reduced cerebrovascular reserve is regionally associated with cortical thickness reductions in children with sickle cell disease. Brain Res 2016; 1642: 263–269.
Google Scholar | Crossref | Medline15. Wang, Y, Fellah, S, Fields, ME, et al. Cerebral oxygen metabolic stress, microstructural injury, and infarction in adults with sickle cell disease. Neurology 2021; 97: e902–e912.
Google Scholar | Crossref | Medline16. Kapustin, D, Leung, J, Odame, I, et al. Hydroxycarbamide treatment in children with sickle cell anaemia is associated with more intact white matter integrity: a quantitative MRI study. Br J Haematol 2019; 187: 238–245.
Google Scholar | Crossref | Medline17. Fields, ME, Guilliams, KP, Ragan, DK, et al. Regional oxygen extraction predicts border zone vulnerability to stroke in sickle cell disease. Neurology 2018; 90: e1134–e1142.
Google Scholar | Crossref | Medline18. Jordan, LC, Gindville, MC, Scott, AO, et al. Non-invasive imaging of oxygen extraction fraction in adults with sickle cell anaemia. Brain 2016; 139: 738–750.
Google Scholar | Crossref | Medline19. Watchmaker, JM, Juttukonda, MR, Davis, LT, et al. Hemodynamic mechanisms underlying elevated oxygen extraction fraction (OEF) in moyamoya and sickle cell anemia patients. J Cereb Blood Flow Metab 2018; 38: 1618–1630.
Google Scholar | SAGE Journals | ISI20. Vaclavu, L, Petersen, ET, VanBavel, ET, et al. Reduced cerebral metabolic rate of oxygen in adults with sickle cell disease. Blood 2018; 132: 11–11.
Google Scholar | Crossref21. Bush, AM, Coates, TD, Wood, JC. Diminished cerebral oxygen extraction and metabolic rate in sickle cell disease using T2 relaxation under spin tagging MRI. Magn Reson Med 2018; 80: 294–303.
Google Scholar | Crossref | Medline22. Bush, A, Vu, C, Choi, S, et al. Calibration of T2 oximetry MRI for subjects with sickle cell disease. Magn Reson Med 2021; 86: 1019–1028.
Google Scholar | Crossref | Medline23. Parkes, LM, Tofts, PS. Improved accuracy of human cerebral blood perfusion measurements using arterial spin labeling: accounting for capillary water permeability. Magn Reson Med 2002; 48: 27–41.
Google Scholar | Crossref | Medline | ISI24. Hales, PW, Phipps, KP, Kaur, R, et al. A two-stage model for in vivo assessment of brain tumor perfusion and abnormal vascular structure using arterial spin labeling. PLoS One 2013; 8: e75717.
Google Scholar | Crossref | Medline25. Juttukonda, MR, Donahue, MJ, Davis, LT, et al. Preliminary evidence for cerebral capillary shunting in adults with sickle cell anemia. J Cereb Blood Flow Metab 2019; 39: 1099–1110.
Google Scholar | SAGE Journals | ISI26. Juttukonda, MR, Donahue, MJ, Waddle, SL, et al. Reduced oxygen extraction efficiency in sickle cell anemia patients with evidence of cerebral capillary shunting. J Cereb Blood Flow Metab 2021; 41: 546–560.
Google Scholar | SAGE Journals27. Buxton, RB, Frank, LR, Wong, EC, et al. A general kinetic model for quantitative perfusion imaging with arterial spin labeling. Magn Reson Med 1998; 40: 383–396.
Google Scholar | Crossref | Medline | ISI28. Amukotuwa, SA, Marks, MP, Zaharchuk, G, et al. Arterial spin-labeling improves detection of intracranial dural arteriovenous fistulas with MRI. AJNR Am J Neuroradiol 2018; 39: 669–677.
Google Scholar | Crossref | Medline29. Le, TT, Fischbein, NJ, André, JB, et al. Identification of venous signal on arterial spin labeling improves diagnosis of dural arteriovenous fistulas and small arteriovenous malformations. AJNR Am J Neuroradiol 2012; 33: 61–68.
Google Scholar | Crossref | Medline30. Sunwoo, L, Sohn, C-H, Lee, JY, et al. Evaluation of the degree of arteriovenous shunting in intracranial arteriovenous malformations using pseudo-continuous arterial spin labeling magnetic resonance imaging. Neuroradiology 2015; 57: 775–782.
Google Scholar | Crossref | Medline31. Juttukonda, MR, Jordan, LC, Gindville, MC, et al. Cerebral hemodynamics and pseudo-continuous arterial spin labeling considerations in adults with sickle cell anemia. NMR Biomed 2017; 30: e3681.
Google Scholar | Crossref32. Kawadler, JM, Hales, PW, Barker, S, et al. Cerebral perfusion characteristics show differences in younger versus older children with sickle cell anaemia: results from a multiple-inflow-time arterial spin labelling study. NMR Biomed 2018; 31: e3915.
Google Scholar | Crossref | Medline33. Rosen, CL, Debaun, MR, Strunk, RC, et al. Obstructive sleep apnea and sickle cell anemia. Pediatrics 2014; 134: 273–281.
Google Scholar | Crossref | Medline34. Howard, J, Slee, AE, Skene, S, et al. Overnight auto-adjusting continuous airway pressure + standard care compared with standard care alone in the prevention of morbidity in sickle cell disease phase II (POMS2b): study protocol for a randomised controlled trial. Trials 2018; 19: 55.
Google Scholar | Crossref | Medline35. Wechsler, D, Wasi, II. Wechsler abbreviated scale of intelligence – second edition J Psychoeduc Assess 2013; 31: 337–341.
Google Scholar | SAGE Journals36. Wechsler, D. Wechsler adult intelligence scale – fourth edition (WAIS-IV). Wechsler, San Antonio, 2008, pp.1–3.
Google Scholar | Crossref37. Delis, D, Kaplan, E, Kramer, J. Delis-Kaplan executive function system (D-KEFS). Psychological Corporation, 2001.
Google Scholar | Crossref38. DCLG . The English indices of deprivation 2015 statistical release. 2015. https://www.gov.uk/government/statistics/english-indices-of-deprivation-2015.
Google Scholar39. Stotesbury, H, Kirkham, FJ, Kölbel, M, et al. White matter integrity and processing speed in sickle cell anemia. Neurology 2018; 90: e2042–e2050.
Google Scholar | Crossref | Medline40. Castro, OL, Haddy, TB, Rana, SR. Age- and sex-related blood cell values in healthy black Americans. Public Health Rep 1987; 102: 232–237.
Google Scholar | Medline41. Luh, WM, Wong, EC, Bandettini, PA, et al. QUIPSS II with thin-slice TI1 periodic saturation: a method for improving accuracy of quantitative perfusion imaging using pulsed arterial spin labeling. Magn Reson Med 1999; 41: 1246–1254.
Google Scholar | Crossref | Medline | ISI42. DeBaun, MR, Gordon, M, McKinstry, RC, et al. Controlled trial of transfusions for silent cerebral infarcts in sickle cell anemia. N Engl J Med 2014; 371: 699–710.
Google Scholar | Crossref | Medline | ISI43. van der Land, V, Hijmans, CT, de Ruiter, M, et al. Volume of white matter hyperintensities is an independent predictor of intelligence quotient and processing speed in children with sickle cell disease. Br J Haematol 2015; 168: 553–556.
Google Scholar | Crossref | Medline44. Hales, PW, Kirkham, FJ, Clark, CA. A general model to calculate the spin-lattice (T1) relaxation time of blood, accounting for haematocrit, oxygen saturation and magnetic field strength. J Cereb Blood Flow Metab 2016; 36: 370–374.
Google Scholar | SAGE Journals | ISI45. Alsop, DC, Detre, JA, Golay, X, et al. Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: a consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia. Magn Reson Med 2015; 73: 102–116.
Google Scholar | Crossref | Medline | ISI46. Wu, W-C, Lin, S-C, Wang, DJ, et al. Measurement of cerebral white matter perfusion using pseudocontinuous arterial spin labeling 3T magnetic resonance imaging – an experimental and theoretical investigation of feasibility. PLoS One 2013; 8: e82679.
Google Scholar | Crossref | Medline | ISI47. Ward, PGD, Ferris, NJ, Raniga, P, et al. Combining images and anatomical knowledge to improve automated vein segmentation in MRI. Neuroimage 2018; 165: 294–305.
Google Scholar | Crossref | Medline48. Peña, EA, Slate, EH. Global validation of linear model assumptions. J Am Stat Assoc 2006; 101: 341–354.
Google Scholar | Crossref | Medline49. Benjamini, Y, Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B 1995; 57: 289–300.
Google Scholar | Crossref50. DeBeer, T, Jordan, LC, Lee, CA, et al. Evidence of transfusion‐induced reductions in cerebral capillary shunting in sickle cell disease. Am J Hematol 2020; 95: E228–E230.
Google Scholar |

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