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CLINICAL OBSERVATIONS, INTERVENTIONS, AND THERAPEUTIC TRIALS
From the Departments of Medical Pathology and Internal
Medicine, University of California Davis School of Medicine, Davis, CA;
Departments of Gastroenterology and Hematology/Oncology, Children's
Hospital, Oakland, CA; Department of Bioengineering, University of
California San Diego, La Jolla, CA; and Department of Neurology,
Medical College of Georgia, Augusta, GA.
The Stroke Prevention Trial has confirmed that utilization of
transcranial Doppler ultrasonography (TCD), which examines blood flow
in large intracranial vessels, can identify children with sickle cell
disease (SCD) who are at high risk of developing a premature stroke. It
is not known to what extent the vasculopathy in SCD involves small
vessels and whether the abnormalities, if present, correlate with
large-vessel vasculopathy. Eighteen children with SCD were examined
with TCD to determine middle cerebral artery (MCA) velocity and
computer-assisted intravital microscopy (CAIM) to determine bulbar
conjunctival vessel velocity during the same visit for vasculopathy
correlation. High MCA velocity ( Cerebrovascular disease, the most serious
complication in homozygous (HbSS) sickle cell disease (SCD) patients,
most often results from occlusion or reduction of cerebral blood flow
of major intracranial arteries.1,2 Cerebral infarction
with acute neurologic deficits affects 5% to 17% of SCD patients by 15 years of age.1-6 The Cooperative Study of SCD recently
reported the chances of having a first cerebrovascular accident by 20, 30, and 45 years of age were 11%, 15%, and 24%, respectively, for
HbSS patients.7 Using magnetic resonance imaging, it has been demonstrated that up to 34% of HbSS patients who did not have a
clinically apparent neurologic event had silent cerebral infarctions
often associated with neuropsychological impairments.8,9 Cerebral infarctions and strokes in SCD often result from occlusion of
major intracranial vessels and reduction of cerebral blood flow.10
Transcranial Doppler ultrasonography (TCD) has been used to
measure blood flow velocity in the intracranial arteries of the circle of Willis, including the internal carotid artery (ICA) and
the middle cerebral artery (MCA).10,11 Focal elevation of
velocity, via TCD measurement, usually indicates arterial stenosis because flow velocity is directly related to cerebral blood flow and
inversely related to arterial diameter.10 The Stroke
Prevention Trial in Sickle Cell Anemia (STOP) has confirmed that
utilization of TCD to identify high MCA velocity is predictive of high
risk and vulnerability for stroke in children with
SCD.2,3,8,10 Small vessels can readily be noninvasively
assessed in the bulbar conjunctiva, but it is not known whether
large-vessel (MCA) vasculopathy correlates with small-vessel
(conjunctival) abnormalities.
Computer-assisted intravital microscopy (CAIM) has recently been
developed as an objective quantitative technology to study vasculopathy
in small vessels, using the readily accessible microcirculation of the
bulbar conjunctiva as a noninvasive research site.12-14 It
has been used successfully to assess and quantify the improvements in
diabetic microangiopathy in diabetic patients after successful simultaneous pancreas-kidney transplantation.12 This
report describes a correlative study on the vasculopathy of large and small vessels in the same SCD patients, using TCD to measure MCA (large-vessel) velocities and CAIM to measure conjunctival vessel (small-vessel) velocities.
SCD patients
Research design
Transcranial Doppler ultrasonography TCD measurements of MCA velocity were made following a protocol similar to that used in adults,15 but modified for children with SCD.10,16 A 2-MHz pulsed Nicolet Doppler Ultrasonograph, model EME TC2000 (Madison, WI), was used. The highest time-averaged mean blood flow velocities in 2-mm increments in the MCA (at 3 points) were recorded for each SCD patient. Experts assigned by the STOP TCD Reading Center to read the coded TCD diskettes were unaware of the patient's medical record, identity, location, or prior TCD results. The diskettes were read, and the MCA velocities were identified as normal, conditional, high or abnormal, or unmeasurable. The assignment of at least 200 cm/sec as high MCA velocity was taken from Adams et al and was associated with a 40% risk of stroke within 3 years.10CAIM Under CAIM, the conjunctival vessels appear as crisp black lines or tubes on a white background.12 In any video frame showing the conjunctival microvasculature, active blood flow was always visible in at least some, if not most, of the conjunctival vessels. Normal blood flow could range widely, and the flow velocities in different vessels could vary considerably even in the same video frame. However, the conjunctival blood flow velocity of an SCD patient would be considered normal if the averaged flow velocity of the patient was computed via image analysis to be more than 0.3 mm/sec (historical median steady-state velocity for HbSS patients at the UC Davis Sickle Cell Clinic was 1.6 mm/sec; n = 30 [A.T.W.C., unpublished data, 1998-2000]). The steady-state conjunctival velocity of any SCD patient would be considered abnormal if the flow velocity fell below 0.3 mm/sec. At times, one could see the conjunctival blood flow reduced to a trickle in SCD and diabetic patients (with recognizable sluggish red blood cell translocation box car phenomenon); in such cases, the velocities could not be reliably computed and were reported as abnormal intermittent trickle flow.
The CAIM procedure has been adapted to noninvasively study the conjunctival microcirculation in human subjects.12-14 To record the conjunctival blood flow for objective measurement, a charge-coupled device video camera (COHU model CCD-6415-3000; San Diego, CA) was used for image acquisition via videotaping using CAIM.12 All videotapes were viewed in their entirety. Videotape sequences to be analyzed were chosen and coded for subsequent analysis. The imaging system was PC-based, equipped with an imaging board/frame-grabber (Data Translation model DT2851; La Habra, CA), and was put on-line with a video system via a FOR-A timer-integrator (FOR-A model VTG-33; Scientific Instruments, Sunnyvale, CA). Video images were frame-captured, digitized, and quantified for conjunctival microvascular characteristics including morphometry and flow velocity via in-house-developed imaging software: VASCAN using a nearest neighboring averaging and local thresholding with subsequent thinning algorithm and VASVEL using a single-step acquisition multiple-frame tracing algorithm.12-14 An area of 8.53 mm2 on the bulbar conjunctival surface of each captured frame was used for data analysis. At least 5 video sequences from each patient (using 1 frame for each morphometric measurement and 8 successive frames for each velocity measurement per sequence) were used. Morphometric (diameter, vessel density, and distribution) and dynamic (velocity) measurements from all 5 sequences of each patient were averaged. Hematology Venous blood was obtained from each patient for the determination of hemoglobin level, reticulocyte count, and fetal hemoglobin (F-hemoglobin) measurement. All hematologic measurements were made at the hematology laboratory at CHO by standard methods.Statistics Statistical analysis was performed using Systat Version 8 (SSPS, Chicago, IL), and the averaged results were presented as the mean and SD whenever appropriate. Comparison of MCA velocities with conjunctival blood flow abnormalities were made using the Fisher exact test. Correlation of hematologic parameters with TCD and CAIM velocities was conducted using analysis of variance (ANOVA). A significance level of .05 was adopted for all analysis. Positive and negative predictive values were calculated using standard equations,17 considering high and conditional MCA velocities to be abnormal and excluding the unmeasurable MCA velocity.
A total of 18 SCD patients and 2 non-SCD subjects were studied. The video sequences of their conjunctival microcirculations were coded and analyzed blindly. Using morphometric characteristics (vessel diameter, vessel density and distribution, vessel tortuosity, arteriole:venule ratio, sludging, box car phenomenon, and damaged vessel and hemosiderin deposit) as criteria,12-14 the 2 non-SCD subjects and the 18 SCD patients were identified correctly. The 18 SCD patients had the following (mean ± SD) hematologic
values: hemoglobin (8.2 ± 0.9 g/dL), reticulocyte count
(9.1% ± 3.3%), and F-hemoglobin (8.5% ± 3.2%). These values
were consistent with SCD values in the literature and did not differ
significantly within MCA velocity or conjunctival velocity
categories (Tables 1 and
2). None of the patients with high or
conditional MCA velocities have experienced a stroke in the 3 years
following the study. Of the patients confirmed with high MCA
velocities, 2 have subsequently been started on hydroxyurea
therapy and 1 was put on hydroxyurea therapy after initial chronic
transfusion treatment.
The values of MCA velocities measured by TCD and conjunctival
velocities measured by CAIM for the 18 SCD patients were
tabulated and correlated (Table 3). High
MCA velocity (201, 204, 201, and 207 cm/sec) was found in 4 SCD
patients. The same 4 patients also showed significantly abnormal
conjunctival blood flow velocities (0.1, 0.1, and 0.2 mm/sec and
intermittent trickle flow) compared with normal steady-state SCD
velocities in this study (1.1-2.4 mm/sec) and historical steady-state
SCD velocities in this laboratory (A.T.W.C., unpublished data,
1998-2000) (P < .001, ANOVA). Three SCD patients
had conditional (193, 171, and 191 cm/sec) MCA velocities; 2 of the 3 showed abnormal (trickle) conjunctival velocities, while the remaining
1 showed normal conjunctival velocity (1.9 mm/sec). One SCD patient who
had unmeasurable MCA velocity showed abnormal conjunctival velocity
(trickle). Of the remaining 10 SCD patients who had normal MCA
velocities (< 170 cm/sec), 2 showed abnormal (0.05 mm/sec and 0.1 mm/sec) and 8 showed normal steady-state SCD conjunctival velocities
(1.1-2.4 mm/sec). The MCA velocities correlated significantly with the
bulbar conjunctival velocities in this study (P
Identification of SCD children at high risk for stroke is important, because this is the major criterion for initiating chronic red blood cell transfusion and is also a criterion for bone marrow transplantation. Because these therapies involve significant risks, a high predictability of future stroke is necessary to justify their selection. In the STOP study, TCD was used to identify SCD children at high risk for strokes.2,18,19 Using survival analysis, Adams et al clearly showed that SCD patients having MCA or ICA velocities more than 200 cm/sec have a 40% chance of having a stroke during a 40-month period, while patients with velocities between 170 and 200 cm/sec had only a less than 7% chance of stroke during the same period.2,10,18 Using these data as basis, Adams et al selected an MCA or ICA velocity of at least 200 cm/sec for inclusion in a recently completed study that demonstrated the efficacy of chronic transfusion in preventing first stroke in children with SCD.3,10 Despite demonstrating a high correlation of high intracranial vessel (MCA and ICA) velocity with the risk of stroke, Adams et al also identified SCD children in the normal velocity range (< 170 cm/sec) who experienced strokes.3,8,16,18 In a study of 315 SCD children, strokes occurred in 17 patients.3 While most (n = 12) of the SCD patients experiencing a stroke had intracranial vessel velocity values of more than 200 cm/sec, 5 children with velocities less than 170 cm/sec also had ischemic cerebral infarctions. Two of these 5 children had MCA velocity measurements in the very low to unmeasurable category. One of these 5 children had normal MCA velocity but was shown to have 75% to 99% stenosis of the right ICA and occlusion of the left ICA. A subgroup of patients with normal, low, or unmeasurable velocities are clearly at risk for stroke. Adams et al suggested that low TCD measurements could result when the angle of insonation is greater than 0 or from a poor temporal acoustic window.18,19 In addition, they noted that the intracranial velocities measured by TCD might decrease when the stenosis reached a critical level or might, in fact, be absent (unmeasurable) when total or close to total occlusion has occurred. In this study, we have identified 3 patients (1 with unmeasurable MCA flow velocity and 2 with normal MCA velocity) who have abnormal conjunctival velocity and may represent subgroups at high risk for stroke without high MCA velocities. There is a significant correlation (P
The assistance from the UC Davis Department of Pathology Hugh Edmondson fellows (Matthew Chan, Jessica Chow, Brian Ng, and Colleen Shannon) in the objective data quantitation phase of this study is very much appreciated.
Submitted October 4, 2000; accepted February 1, 2001.
Supported in part by a University of California Professional Development Award (A.T.W.C.); discretionary gifts to the Biomedical Engineering Division at University of California Davis Medical Center (A.T.W.C.); a gift from the W.G. Gilmore Foundation (A.T.W.C.); and grants from the National Institutes of Health: NIH-R29-HL-55181 (T.W. and A.T.W.C.), NIH-M01-RR01271 (P.H. and E.P.V.), NIH-HL-20985 (P.H. and E.P.V.), and NIH-U10-HL52 193 (R.J.A.).
The publication costs of this article were defrayed in part by page charge payment. Therefore, and solely to indicate this fact, this article is hereby marked "advertisement" in accordance with 18 U.S.C. section 1734.
Reprints: Anthony T. W. Cheung, Dept of Medical Pathology, UC Davis Medical Center, Research-III Bldg (Rm #3400B), 4645 Second Ave, Sacramento, CA 95817; e-mail: atcheung{at}ucdavis.edu.
1. Adams RJ. Neurological complications. In: Embury SJ,Hebbel RP,Mohandas N,Steinberg MH, eds. Sickle Cell Disease: Basic Principles and Clinical Practice. New York, NY: Raven Press; 1994:599-621. 2. Adams RJ, McKie VC, Nichols F, et al. The use of transcranial ultrasound to predict stroke in sickle cell disease. N Engl J Med. 1992;326:605-610[Abstract].
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Adams RJ, McKie VC, Hsu L, et al.
Prevention of a first stroke by transfusion in children with sickle cell anemia and abnormal results on transcranial Doppler ultrasonography.
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1998;339:5-11 4. Powars ER, Wilson B, Imbus C, Pegelow C, Allen J. The natural history of stroke in sickle cell disease. Am J Med. 1978;65:461-471[CrossRef][Medline] [Order article via Infotrieve]. 5. Adams RJ, Nichols FT. Sickle cell anemia, sickle cell trait and thalassemia. In: Vinken PJ,Bruyn GW,Klawans HL,Toole JF, eds. Handbook of Clinical Neurology. Vascular Diseases. Part 3. Vol 55. Amsterdam, The Netherlands: Elsevier Press; 1989:503-515. 6. Pavlakis SG. Neurologic complications of sickle cell disease. Adv Pediatr. 1989;36:247-276[Medline] [Order article via Infotrieve].
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Ohene-Frempong K, Weiner SJ, Sleeper LA, et al.
Cerebrovascular accidents in sickle cell disease: rates and risk factors.
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1998;91:288-294 8. Adams RJ, McKie V, Files B, et al. Stroke prevention in sickle cell disease (STOP): results of transcranial Doppler ultrasound screening stroke risk. In: Proceeding of the National Sickle Cell Disease Conference; September 18, 1997; Washington, DC. Abstract 180. 9. Craft S, Schatz J, Glauser TA, Lee B, DeBaun MR. Neuropsychologic effects of stroke in children with sickle cell anemia. J Pediatr. 1993;123:712-717[CrossRef][Medline] [Order article via Infotrieve]. 10. Adams RJ, McKie VC, Brambilla D, et al. Stroke prevention trial in sickle cell anemia. Control Clin Trials. 1997;1:110-129. 11. Aaslid R, Markwalder TM, Nornes H. Non-invasive transcranial Doppler ultrasound recording of flow velocity in basal cerebral arteries. J Neurosurg. 1982;57:769-774[Medline] [Order article via Infotrieve]. 12. Cheung ATW, Perez RV, Chen PCY. Improvements in diabetic microangiopathy after successful simultaneous pancreas-kidney transplantation (SPK): a computer-assisted intravital microscopy study on the conjunctival microcirculation. Transplantation. 1999;68:927-932[CrossRef][Medline] [Order article via Infotrieve]. 13. Cheung ATW, Chan MS, Ng BC, et al. Vascular abnormalities in sickle cell disease [abstract]. FASEB J. 1999;13:A881. 14. Cheung ATW, Chen PCY, Chan MS, et al. Development of a severity index to objectively characterize microvascular abnormalities in sickle cell disease [abstract]. Blood. 1997;90(suppl 1, pt 1):127A. 15. Aaslid R. Developments and principles of transcranial Doppler. In: Newell DW,Aaslid R, eds. Transcranial Doppler. New York, NY: Raven Press; 1992:1-8. 16. Adams RJ, Litaker M, Nicols FT. Anemia and sickle cell disease. In: Babikian V,Wechsler LR, eds. Transcranial Doppler Ultrasonography. St Louis, MO: Mosby-Year Book; 1993:160-171. 17. Dawson B, Trapp RG. Basic and Clinical Biostatistics. 3rd ed. New York, NY: Lange Medical Books/McGraw-Hill; 2001. 18. Adams RJ, McKie VC, Carl EM, et al. Long term stroke risk in children with sickle cell disease screened with transcranial Doppler. Ann Neurol. 1997;42:699-704[CrossRef][Medline] [Order article via Infotrieve]. 19. Rorick MB, Nichols FT, Adams RJ. Transcranial Doppler correlation with angiography in detection of intracranial stenosis. Stroke. 1994;25:1931-1934[Abstract]. 20. Chen PCY, Kovalcheck BW, Zweifach BW. Analysis of microvascular network in bulbar conjunctiva by image processing. Int J Microcirc Clin Exp. 1987;6:245-255[Medline] [Order article via Infotrieve].
© 2001 by The American Society of Hematology.
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  R. Zennadi, B. J. Moeller, E. J. Whalen, M. Batchvarova, K. Xu, S. Shan, M. Delahunty, M. W. Dewhirst, and M. J. Telen Epinephrine-induced activation of LW-mediated sickle cell adhesion and vaso-occlusion in vivo Blood, October 1, 2007; 110(7): 2708 - 2717. [Abstract] [Full Text] [PDF]
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R. Zennadi, P. C. Hines, L. M. De Castro, J.-P. Cartron, L. V. Parise, and M. J. Telen Epinephrine acts through erythroid signaling pathways to activate sickle cell adhesion to endothelium via LW-{alpha}v{beta}3 interactions Blood, December 1, 2004; 104(12): 3774 - 3781. [Abstract] [Full Text] [PDF]
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A. T. W. Cheung, P. C. Y. Chen, E. C. Larkin, P. L. Duong, S. Ramanujam, F. Tablin, and T. Wun Microvascular abnormalities in sickle cell disease: a computer-assisted intravital microscopy study Blood, May 13, 2002; 99(11): 3999 - 4005. [Abstract] [Full Text] [PDF]
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| Copyright © 2001 by American Society of Hematology Online ISSN: 1528-0020 | |||||||||
Top
Abstract
Introduction
200 cm/sec) was found by TCD in 4 patients who also showed abnormal conjunctival velocity (< 0.2 mm/sec
or intermittent trickle flow) by CAIM. Three patients had conditional
(
.008, Fisher exact test). A correlation exists
between MCA (large-vessel) and conjunctival (small-vessel) flow
velocities. CAIM is a noninvasive quantitative technique that might
contribute to the identification of SCD patients at high risk of
stroke. Small-vessel vasculopathy might be an important pathological
indicator and should be further explored in a large-scale study.
(Blood. 2001;97:3401-3404)