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Rapid dynamic CT scanning in primary degenerative dementia and age-matched controls
BIOL PSYCHIATRY i990;28:425-434
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Rapid Dynamic CT Scanning in Primary Degenerative Dementia and Age-Matched Controls Maurice W. Dysken, Mary Jo Nelson, Katl,.leen Maxwell Hoover, Michael Kuskowski, and Robert. McGeachie
Dynamic computed tomography (CT) scanning of the brain was performed in 26 patients with primary degenerative dementia (PDD) and in 15 age-matched controls without evidence of a dementing illness. Changes in CT density values over time were obtained for 16 regions of interest (ROls) that were carefully chosen to avoid overlap with adjacent cerebrospinai fluid (CSF), sulsi, or bone. CT density washout curves were compared between patients and controls to detect regions where blood brain barrier (BBB) permeability might be increased. Although the patients' washout curves declined more gradually than control curves in 11 of the 14 ROls with a functioning BBB, in no case did the difference reach statistical significance. Intrarater correlation coefficients indicated good overall reliability ir the selection of ROls.
Introduction The pathogenesis of Alzheimer's disease may be related to a disruption in blood brain barrier (BBB) functioning as :ecently suggested by Glenner (1985) and Hardy et al. (1986). Evidence in favor of this hypothesis has come !from two sources: the presence of serum proteins in the brain's extravascular compartment (Wisniewski and Kozlowski 1982) and elevated CSF/serum ratios of albumin and IgG (Alafuzoff et al. 1983; Elovaara et al. 1985). More recently, the role of altered BBB permeability in the pathogenesis of Alzlleimer~s disease has been challenged by Masters and Beyreuther (1988), who argue that the most likely explanation for the presence of serum proteins in brain is artffactitious postmortem leakage into the neuropil. In addition, several recent studies of albumin and IgG concentrations in CSF and serum have failed to show any differences between Alzheimer patients and controls (Kay e~ al. 1987; Leonarbi et al. 1985). To pursue the problem of assessing BBB integrity in patients with Alzheimer's disease, we utilized a relatively new imaging technique known as dynamic CT scanning (Sage 1982). First described by Anderson et al. (1981) as a method for measuring regional circulation in the brain, dynamic CT scanning is characterized by a series of contrastenhanced CT scans that are rapidly recorded after an antecubital injection of a nonradio-
From the Geriatric Research, Education, and Clinical Center and Department of Radiology, Minneapol;.sVA Medical Center, Minneapolis, MN. Supported by Grant IPOI-AG 05309-01 from the National Institute on Aging (NIA) to M.D. Address reprint requests to Maurice W. Dysken, M.D., GRECC Program (IlG), Minneapolis VA Medical Center, One Veterans Drive, Minneapolis, MN 55417. Received September 30, 1989; revised February 12, 1990. Published 1990 by Elsevier Science Publishing Company, Inc.
0006-3223/90/$00.00
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active, iodinated contrast material. Changes in CT density versus time are then plotted for any brain region of interest (ROD. A normal curve increases monotonically for approximately 15 sec (washin phase) and then decreases monotonically (washout phase) following the same general pattern as an arterial blood curve (Dysken et al. 1987). A prolongation in the washout phase results in a plateau curve and is associated with brain regions that lack a BBB, e.g., choroid plexus or tumors such as meningiomas (Dysken et al. 1987). This observation forms the basis for associating an increase in BBB permeability with regions of the brain demonstrating a plateau curve. Because dynamic CT scanning is readily available, reliable, safe, relatively noninvasive, and cost-effective, we carried out a dynamic CT scan study in Alzheimer patients and age-matched controls to compare differences in washout curves for selected ROB.
Me~thods We performed dynamic CT scanning in 26 patients who met both DSM-III-R criteria for primary degenerative dementia (PDD) (American Psychiatric Association 1987) and NINCDS-ADRDA criteria for probable Alzheimer's disease (McKhann et al. 1984). In addition, we performed dynamic CT scanning in 15-age matched controls without evidence of a dementing illness. All patients participated in a comprehensive diagnostic assessment that included a physical and neurological examination, neuropsychological testing, screening laboratory evaluations, an electrocardiogram (ECG), an electroencephalogram (EEG), and an unenhanced CT scan of the head. Patient selection criteria included an age range of 50-90 years and a Global Deterioration Scale (GDS) score from 3 to 6 (Reisberg et al. 1982). Exclusion criteria consisted of (1) a history of either alcoholism or drug addiction or current use of alcohol or addictive drugs; (2) a history of schizophrenia, epilepsy, stroke, or mental retardation; (3) DSM-III-R criteria for multiinfarct dementia or CT scan evidence for cerebral infarction; (4) primary affective disorder as defined by DSM-IH-R or a 21-item Hamilton Depression Rating Scale score above 18; (5) concurrent administration of 13-blockers, calcium antagonists, vasodilators, anticoagulants, antithrombotic and thrombolytic drugs, or any medication with intrinsic CNS activity; (6) systolic blood pressure greater than 160 mm Hg or a diastolic blood pressure greater than 95 mm Hg during the screening period; mid (7) a history of any allergic reaction to iodinated contrast material. Control subjects were recruited from a ~oup of relatives and friends of the patients. Potential controls were excluded if they had a history of any significant medical or psychiatric disorder: ~r if they were currently taking any central nervous system (CNS) active medications. Each patient and a relative of that patient gave written informed consent; control subjects also gave written informed consent. To select a level for dynamic scanning, the unenhanced CT ~cap. was used to identify a supratentorial level at approximately the caudate p-.clei. Each subject was given an antecubit~ L,ljection of 45 ~I of Hypaque-76 by a power injector (Med-Rad) at a rate of 9 ml/sec. A fourth generation CT scanner (Picker 1200) was used to display eight consecutive 3.7-sec scans of the selected slice with interscan pauses of 1.7 sec. CT scans were oriented parallel to Reid's baseline. The first or baseline 8 ram-thick scan represents the slice without contrast whereas each subsequent 8 mm-thick scan depicts the same region as contrast material enters and then exits. For any selected ROI, an E-GRASP program (Picker) was used to generate on the scanner's cathode ray tube (CRT) a graph showing CT density values over time. Each slice was displayed on a 256 > 256 matrix
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Figure 1. Two CT density versus time curves are shown corresponding to two temporoparietal (TP) region~ of inte~'est (ROD in 1 subject. The curve in the upper portion represents changes in CT density over thne for a ROI in right TP (RTPG) marked by a round cursor. The curve in the lower portion represents the change in CT density over time for a ROI in the left I ~' gray (LTPG), also marked by a round cursor.
and average CT density numbers for a particular ROI were expressed in Hounsfield units at each time point (Figure l). A total of 16 ROIs (Figure 2) were defined by a round cursor (0.3 cm 2, 4 pixels; volume = 0.24 cm 3) that was positioned by a neuroradiologist (MJN) in areas tha*. included right and left frontal gray, right and left frontal white, fight and left temporoparietal (TP) gray, fight and left TP white, fight and left occipital gray, fight and left occipital white, fight and left thalamus, and fight and left choroid plexus. These small ROis were carefully chosen to avoid overlap with adjacent CSF, sulsi, or bone. We did not include any patient who was unable to cooperate with the scanning procedure. Each CT density versus time curve was videotaped for permanent storage. As the curve for a particular ROI was produced on the scanner's CRT, the CT density numbers for each time point were displayed sequentially and rapidly in the fight upper comer of the CRT. The videotape was later played back frame by frame to record these CT numbers. These values were then compared with the E-GRASP generated graph of CT density versus time to verify the CT density values. The E-GRASP program also displayed the
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Figure. 2. The anatomic location of 14 of the ROIs are indicated by blackened, round circles. The other two ROIs are both choroid plexuses, which are calcified in this particular patient.
appropriate time point value on each scan in the series. Thus, for each of the 16 ROIs, a total of 8 CT density values corresponding to eight time points were recorded for each subject. To establish the intrarater reliability of CT density measurements for each ROI, the neuroradiologist (MIN) selected, on two separate occasions, the same 16 designated ROIs in 10 dynamic CT scans (5 patients, 5 controls). The purpose of this reliability assessment was to determine how accurate the neuroradiologist was in the selection of the same ROIs. For each RO!, a CT density correlation coefficient was computed for each of the eight time points. An average correlation coefficient for each ROI was then determined by averaging the individual time point correlations. To evaluate "u,v ^ u,t,c, -' cH~c ,,1 wu~ll~,ut cuF~es for patients eaad controls, a peak CT density value was determined for each ROI curve. In those cases in which the peak value occurred more than once, the first value was selected as the peak. To normalize for differing peak values, each subsequent CT density value in a given curve was expressed as a percentage of the peak value. A repeated measures analysis of variance (two groups, four post-peak time points) was then carried out to detect any significant differences in washout rates between patients and controls. A significant group × time point interaction would indicate such a difference in washout rates. In addition, CT density peak v~,l~:c.s ."
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Table 1. Average Intrarater Correlation Coeffidents (_+SD) of CT Density Values for Each ROI ROI RIG R_b'W RTPG RTPW ROG ROW RT RCP
M e a n ± sD 0.91 0.93 0.91 0.75 0.90 0.96 0.87 0.69
± ± ± ± ± ± ± ±
0.08 0.05 0.12 0.08 0.05 0.03 0.08 0.14
ROI LFG LRW LTPG LTPW LOG LOW LT LCP
M e a n __ SD 0.91 0.93 0.90 0.82 0.89 0.97 0.93 0.75
± ± ± ± ± ± ±
0.05 0.03 0.08 0.08 0.09 0.02 0.04 0.15
RF~ = fight frontal gray, LFG = left frontal gray, RFW -- fight f~ontal white, Lr--CV = left frontal white, RTPG = fight temporoparietal gray, LTPG = leR temporoparietal gray, RTPW = fight temporopafietal white, LTPW = left temporopafietal white, ROG = fight occipital gray, LOG = left occipital gray, ROW = fight occipital white, LOW = left occipital white, RT = fiqht t__h8!a~us, LT = left thalamus, RCP = right choroid ~4exus, and LCP = left ¢horoid plexus.
and time-to-peak values were compared between patients and controls using the Student's t-test. To test for any hemispheric asymmetries, peak values and time-to-peak values were compared using the Student's t-test between right and left ROIs separately for patients and controls. Results The 26 PDD patients (19 men, 7 women) ranged in age from 52 to 84 years (mean _+ SD = 67 +-- 8) and the 15 controls (10 men, 5 women), from 51 to 76 years (mean _+ SD = 62 _ 7). The duration of the dementia was determined from the family's report of symptom onset and ranged from 10 to 130 months (mean +- SD = 42 +_ 25). The severity of the dementia was assessed by the Mini-mental State Examination (MMSE) (Folstein et al. 1975), which ranged from 6 to 26 (mean _ SD = 17 +-- 6), and the GDS, which ranged from 3 to 6 (mean -+ so - 4.4 +_ 0.7). All CNS-active medications were discontinued at least 1 week before obtaining the dynamic CT scan. The average intrarater correlation coefficients ( _ so) for each ROI are presented in Table 1 and represent one measure of reliability for the selection of ROIs. Ten of the 16 ROIs had correlations equal to or exceeding 0.90. The lowest correlations were found in the right choroid plexus (0.69) and left choroid plexus (0.75) curves. Regional CT density versus time curves in control subjects are presented in Figure 3 for the eight right-sided ROIs. Each CT density value represents the average for all controls over the eight time points. With the exception of the right choroid plexus (top graph, Figure 3), these normal curves reach a peak at 15 sec (washin phase) and then decline somewhat more slowly over the nent 20 sec (washout phase). Gray matter is known to have a higher brain density than white matter (Arimitsu et al. 1977; Brooks et al. 1980) and this difference is reflected in higher CT density baselines for gray matter ROIs. The CT density baseline for the right choroid plexus is approximately 2.5 times as great as the other ROIs because of the presence of choroid plexus calcification, which is much more common in elderly subjects. The choroid plexus CT density curve, unlike the other curves, ~'eaches a plateau after a normal washin phase and is characteristic of brain regions devoid of blood brain barrier (Dysken et al. 1987). To test for possible differences in BBB permeability between patients and controls, washout curves were compared between groups for the 14 ROIs with a BBB. The four
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Regional Curves in Control Subjects 120
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Figure 3. Right-sided regional CT density versus time curves are presented for control subjects. The upper panel represents average CT densities over time from the fight choroid plexus (RCP). The lower panel represents average CT densities over time from fight temporoparietal gray (RTPG), fight occipital gray (ROG), and fight frontal gray (RFG), fight occipital white (ROW), fight thalamus (RT), right temporopafietal white (RTPW), and fight frontal white (RFW). CT density values after the peak were expressed as a percent of the peak and the means were examined between groups for each ROI (Figure 4). Although the patients' washout curves declined more gradually than control curves in ! 1 of the 14 ROIs (exceptions were left TP white, right occipital gray, and left occipital gray), in no case did the difference reach statistical significance. A trend toward a significantly slower patient washout curve was noted, however, for the right TP gray region (F - 3.7, p - 0.6) (top graph, Figure
Dynamic CT Scanning in Alzheimer's Dementia
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Figure 4. Washout curves for patients and controls (mean _+ SD) are depicted as a percent of the CT density peak for RTPG (upper panel) and LTPG (lower panel). 4). No meaningful n~tt~m of ~ignifit'ant ~nrr~.latinn~ e.marge~ hetwe~n the __MMSEtotal scores or GDS sceres and washout curve densities over all the patients' ROIs. Differences in CT density peak values and time-to-peak values (sec) between patients and controls and between symmetrical ROIs were examined. There were no significant differences in peak values between patients and controls for any ROI. A significantly longer time-to-peak (me?~ - SD) was found for right TP gray (RTPG) in patients (4.1 +_ 0.4) compared with controls (3.5 - 0.5) (t = 3.1, df = 34,p < 0.005). A significantly higher CT density peak (~xie~ ± so) was found i~ t/atients for leR frontal white (LFW) ,L.. t . . ~ v
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(39.6 _ 3~7) compared ~o right frontal white (RFW) (39.0 - 4.1) (paired t = 2.3, df = 25, p < 0.05). Significantly greater time-to-peak differences were found in patients for left frontal gray (LFG) (3.8 +-. 0.6) compared to right frontal gray (RFG) (3.6 0.7) (paired t = 2.1, df = 25, p < 0.05) and in controls for RFW (4.0 _ 0.5) compared to LFW (3.8 ± 0.04) (paired t = 2.3, df = 14, p < 0.05).
Discussion Dynamic CT scanning in patients with Alzheimer's disease and age-matched controls did not demonstrate any significant differences in the decline of CT density washout curves for any of the grey or white matter ROIs. "~us, the results with this imaging technique do not support the hypothesis of an increas~ in BBB permeability in Alzbeimer's disease. Our study is consistent with recent positron emission tomography (PET) studies that have also failed to demonstrate a breakdown in BBB in Alzheimer patients (Friedland et al. 1985a, 1985b; Schlageter et al. 1987). It is also consistent with the absence of demonstrable edema in Alzheimer's disease (Klatzo ct al. 1980; Rapoport 1976, 1978). The few statistically significant differences in CT density peaks and times-to-peak between Alzheimer patients and controls and between right- and left-sided ROIs did not follow any particular pattern and may have resulted by chance due to the numerous comparisons that were done. It is not surprising that the right and left choroid plexus ROIs produced the greatest intrarater variability in CT density values. The choroid plexuses were often small in size and irregular in shape, which made it difficult at times to position the cursor exactly over this area without including some portion of the adjacent CSF area. In general, however, the overall high correlation coefficients for the ROls demonstrate good intrarater reliability, particularly for those gray matter regions of the brain where the neuropathology of Alzheirner's disease is prominent and where an increase in BBB permeability may be most likely (Wisniewski and Kozlowski 1982). Several methodological changes that were adopted in this study developed from our previous experience in assessing dynamic CT scan washout curves in another patient sample and control group (Dysken et al. 1987). In this earlier study, the classification of CT density curves was approached qualitatively as a pattern-recognition problem (plateau curves versus normal curves). The cursor was moved systematic~ly from region to adjacent region, omitting only the skull and ventricles, so that the entire breJn slice was examined. The number of plateau curves for each subject was counted and used in detemma~ng statistically significant differences between patients and controls. In addition, only six CT density time points were available for analyses. In the present study, CT density curves over eight time points were sampled from specific anatomical regions that would vary in the severity of neuropathological lesions found in Alzheimer's disease. It was postulated that prolonged washout curves would be found preferentially in gray matter regions as neuritic plaques and neurofibrillary "t~,,gles are in greater abundance in cortex than in subcortical white matter. It was, therefore, the desire to assess quantitatively specific anatomic areas of disrupted BBB functioning that resulted in a modification of our initial approach. We would like to thank Glen D. Dobben, M.D. for his helpful suggestions and support in study.
carrying out this
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References Alafuzoff I, Adolfsson R, Bucht G, Winblad B (1983): Albumin and immunoglobulin in plasma and cerebrospinal fluid, and blood-cerebrospinal fluid barrier function in patients with dementia of Alzheimer ~ and multi-infarct dementia. J Neurol $ci 60:465-472. American Psychiatric Association (1987): Diagnostic and Statistical Manual of Mental Disorders, (ed 3). Washington, DC: American Psychiatric Association. Anderson EM, Carney AL, Dobben GD, Maffee MF, Valvassori G, Burns EM (1981): Measurement of regional brain blood circulation by computed mmography. In Carney At., Anderson EM (eds), Advances in Neurology: Diagnosis and Treatment of Brain lschemia, vol. 30. New York: Raven Press, pp 97-139. Arimitsu T, DiChiro G, Brooks RA, Smith PB (1977): White-grey matter differentiation in computed tomography. J Comput Assist Tomogr 1:437-442. Brooks RA, DiChiro G, Eeller MR (1980): Explanation of cerebral white-grey contrast in computed tomography. J Comput Assist Tomogr 4:489-491. Dysken MW, Patlak CS, Dobben GD, et al (1987): Rap~ dynamic CT scanning to distinguish schizophrenic from normal subjects. Psychiatry Res 20:165-175. Elovaara I, Icen A, Palo J, Erkinjuntti T (1985): CSF in Alzheimer's disease: Studies on bloodbrain barrier function in intrathecal protein synthesis. J Neurol Sci 70:73-80. Folstein MF, Folstein SE, McHugh PR (1975): Mini-mente! state: A practical method for grading the cognitive state of patients for the clinician. 3 Psychiatr Res 12:189--198. Friedland RP, Jagust WJ, Budinger "IF, Huesman RH, Knittel B (1985a): Blood brain barrier permeability studies in Alzheimer's disease. Neurology 35(Suppl 1):220. F6edland RP~ Jagu~t WJ, Budhlger TF, Yano Y, Huesm~n RH, Knittel B (1985b): D~aa_micPET studies of blood-brain barrier permeability in Alzheimer's disease. J Nucl bled 26:103. Glermer GG (1985): On causative t-heories in Alzheimer's disease. Hum Pathol 16:433-435. Ha~dy JA, Mann DMA, Wester P, Winblad B (198ti): Aa integrative hypothesis concerning the pathogenesis and progression of Alzb.e.~mer's dise~:se. _,reurobiol Aging 7:489-502. Kay AD, May C, Papadopoulos NM, et al (1987): CSF and serum concentrations of albumin and lgG in Alzheimer's disease. Neurobiol Aging 8:21-25. Klatzo I, Chui E, Fujiwara K, Spatz M (1980): Resolution of vasogenic brain edema. Adv Neurol 28:359-373. Leonardi A, Gandolfo C, Caponnetto C, Arata L, Vecchia R (1985): The integrity of the bloodbrain barrier in Alzheimer's type and ~ulti-infarct ~e~aentia e,¢aluated by the study of albumin and IgG in serum and cerebrospinal fluid. J Neurol Sci 67:253-261. Masters CL, Beyreuther K (1988): The blood-brain barrier in AJzheimer's disease and normal aging. Neurobiol Aging 9:43-44. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM (1984): Ciinical diagnosis of Alzheimer's disease: Report of the NINCDS-ADRDA work group under the auspices of department of health and human services task force on Alzheimer's disease. Neurology 34:939944. Rapoport SI (1976): Blood-Brain Barrier in Physiology and Medicine. New York: Raven Press, pp 87-127. Rapoport SI (1978): A mathematical model for vasogenic brain edema. J Theor Bio174:439--467. Reisberg B, Ferris SH, de Leon MJ, Crook T (1982): The global deterioro,tion sere (GDS): An instrument for the as~ssment of primary degenerative dementia (PDD). Am J Psychiatry 139:11361139. Sage MR (1982): Blood-brain barrier: Phenomenon of increasing importance to the imaging clinician. AJR 3:127-138.
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Schlageter NL, Carson RE, Rapoport SI (1987): Examination of blood-brain barrier permeability in dementia of the Alzheimer type with (C'SGa)EDTAand positron emission tomography. J Cereb Blood Flow Metab 7:1-8. Wisniewski HM, Kozlowski PB (1982): Evidence for blood-brain barrier changes in senile dementia of the Alzheimer type (SDAT). Ann NY Acad Sci 396:119-129.
425
Rapid Dynamic CT Scanning in Primary Degenerative Dementia and Age-Matched Controls Maurice W. Dysken, Mary Jo Nelson, Katl,.leen Maxwell Hoover, Michael Kuskowski, and Robert. McGeachie
Dynamic computed tomography (CT) scanning of the brain was performed in 26 patients with primary degenerative dementia (PDD) and in 15 age-matched controls without evidence of a dementing illness. Changes in CT density values over time were obtained for 16 regions of interest (ROls) that were carefully chosen to avoid overlap with adjacent cerebrospinai fluid (CSF), sulsi, or bone. CT density washout curves were compared between patients and controls to detect regions where blood brain barrier (BBB) permeability might be increased. Although the patients' washout curves declined more gradually than control curves in 11 of the 14 ROls with a functioning BBB, in no case did the difference reach statistical significance. Intrarater correlation coefficients indicated good overall reliability ir the selection of ROls.
Introduction The pathogenesis of Alzheimer's disease may be related to a disruption in blood brain barrier (BBB) functioning as :ecently suggested by Glenner (1985) and Hardy et al. (1986). Evidence in favor of this hypothesis has come !from two sources: the presence of serum proteins in the brain's extravascular compartment (Wisniewski and Kozlowski 1982) and elevated CSF/serum ratios of albumin and IgG (Alafuzoff et al. 1983; Elovaara et al. 1985). More recently, the role of altered BBB permeability in the pathogenesis of Alzlleimer~s disease has been challenged by Masters and Beyreuther (1988), who argue that the most likely explanation for the presence of serum proteins in brain is artffactitious postmortem leakage into the neuropil. In addition, several recent studies of albumin and IgG concentrations in CSF and serum have failed to show any differences between Alzheimer patients and controls (Kay e~ al. 1987; Leonarbi et al. 1985). To pursue the problem of assessing BBB integrity in patients with Alzheimer's disease, we utilized a relatively new imaging technique known as dynamic CT scanning (Sage 1982). First described by Anderson et al. (1981) as a method for measuring regional circulation in the brain, dynamic CT scanning is characterized by a series of contrastenhanced CT scans that are rapidly recorded after an antecubital injection of a nonradio-
From the Geriatric Research, Education, and Clinical Center and Department of Radiology, Minneapol;.sVA Medical Center, Minneapolis, MN. Supported by Grant IPOI-AG 05309-01 from the National Institute on Aging (NIA) to M.D. Address reprint requests to Maurice W. Dysken, M.D., GRECC Program (IlG), Minneapolis VA Medical Center, One Veterans Drive, Minneapolis, MN 55417. Received September 30, 1989; revised February 12, 1990. Published 1990 by Elsevier Science Publishing Company, Inc.
0006-3223/90/$00.00
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active, iodinated contrast material. Changes in CT density versus time are then plotted for any brain region of interest (ROD. A normal curve increases monotonically for approximately 15 sec (washin phase) and then decreases monotonically (washout phase) following the same general pattern as an arterial blood curve (Dysken et al. 1987). A prolongation in the washout phase results in a plateau curve and is associated with brain regions that lack a BBB, e.g., choroid plexus or tumors such as meningiomas (Dysken et al. 1987). This observation forms the basis for associating an increase in BBB permeability with regions of the brain demonstrating a plateau curve. Because dynamic CT scanning is readily available, reliable, safe, relatively noninvasive, and cost-effective, we carried out a dynamic CT scan study in Alzheimer patients and age-matched controls to compare differences in washout curves for selected ROB.
Me~thods We performed dynamic CT scanning in 26 patients who met both DSM-III-R criteria for primary degenerative dementia (PDD) (American Psychiatric Association 1987) and NINCDS-ADRDA criteria for probable Alzheimer's disease (McKhann et al. 1984). In addition, we performed dynamic CT scanning in 15-age matched controls without evidence of a dementing illness. All patients participated in a comprehensive diagnostic assessment that included a physical and neurological examination, neuropsychological testing, screening laboratory evaluations, an electrocardiogram (ECG), an electroencephalogram (EEG), and an unenhanced CT scan of the head. Patient selection criteria included an age range of 50-90 years and a Global Deterioration Scale (GDS) score from 3 to 6 (Reisberg et al. 1982). Exclusion criteria consisted of (1) a history of either alcoholism or drug addiction or current use of alcohol or addictive drugs; (2) a history of schizophrenia, epilepsy, stroke, or mental retardation; (3) DSM-III-R criteria for multiinfarct dementia or CT scan evidence for cerebral infarction; (4) primary affective disorder as defined by DSM-IH-R or a 21-item Hamilton Depression Rating Scale score above 18; (5) concurrent administration of 13-blockers, calcium antagonists, vasodilators, anticoagulants, antithrombotic and thrombolytic drugs, or any medication with intrinsic CNS activity; (6) systolic blood pressure greater than 160 mm Hg or a diastolic blood pressure greater than 95 mm Hg during the screening period; mid (7) a history of any allergic reaction to iodinated contrast material. Control subjects were recruited from a ~oup of relatives and friends of the patients. Potential controls were excluded if they had a history of any significant medical or psychiatric disorder: ~r if they were currently taking any central nervous system (CNS) active medications. Each patient and a relative of that patient gave written informed consent; control subjects also gave written informed consent. To select a level for dynamic scanning, the unenhanced CT ~cap. was used to identify a supratentorial level at approximately the caudate p-.clei. Each subject was given an antecubit~ L,ljection of 45 ~I of Hypaque-76 by a power injector (Med-Rad) at a rate of 9 ml/sec. A fourth generation CT scanner (Picker 1200) was used to display eight consecutive 3.7-sec scans of the selected slice with interscan pauses of 1.7 sec. CT scans were oriented parallel to Reid's baseline. The first or baseline 8 ram-thick scan represents the slice without contrast whereas each subsequent 8 mm-thick scan depicts the same region as contrast material enters and then exits. For any selected ROI, an E-GRASP program (Picker) was used to generate on the scanner's cathode ray tube (CRT) a graph showing CT density values over time. Each slice was displayed on a 256 > 256 matrix
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Figure 1. Two CT density versus time curves are shown corresponding to two temporoparietal (TP) region~ of inte~'est (ROD in 1 subject. The curve in the upper portion represents changes in CT density over thne for a ROI in right TP (RTPG) marked by a round cursor. The curve in the lower portion represents the change in CT density over time for a ROI in the left I ~' gray (LTPG), also marked by a round cursor.
and average CT density numbers for a particular ROI were expressed in Hounsfield units at each time point (Figure l). A total of 16 ROIs (Figure 2) were defined by a round cursor (0.3 cm 2, 4 pixels; volume = 0.24 cm 3) that was positioned by a neuroradiologist (MJN) in areas tha*. included right and left frontal gray, right and left frontal white, fight and left temporoparietal (TP) gray, fight and left TP white, fight and left occipital gray, fight and left occipital white, fight and left thalamus, and fight and left choroid plexus. These small ROis were carefully chosen to avoid overlap with adjacent CSF, sulsi, or bone. We did not include any patient who was unable to cooperate with the scanning procedure. Each CT density versus time curve was videotaped for permanent storage. As the curve for a particular ROI was produced on the scanner's CRT, the CT density numbers for each time point were displayed sequentially and rapidly in the fight upper comer of the CRT. The videotape was later played back frame by frame to record these CT numbers. These values were then compared with the E-GRASP generated graph of CT density versus time to verify the CT density values. The E-GRASP program also displayed the
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Figure. 2. The anatomic location of 14 of the ROIs are indicated by blackened, round circles. The other two ROIs are both choroid plexuses, which are calcified in this particular patient.
appropriate time point value on each scan in the series. Thus, for each of the 16 ROIs, a total of 8 CT density values corresponding to eight time points were recorded for each subject. To establish the intrarater reliability of CT density measurements for each ROI, the neuroradiologist (MIN) selected, on two separate occasions, the same 16 designated ROIs in 10 dynamic CT scans (5 patients, 5 controls). The purpose of this reliability assessment was to determine how accurate the neuroradiologist was in the selection of the same ROIs. For each RO!, a CT density correlation coefficient was computed for each of the eight time points. An average correlation coefficient for each ROI was then determined by averaging the individual time point correlations. To evaluate "u,v ^ u,t,c, -' cH~c ,,1 wu~ll~,ut cuF~es for patients eaad controls, a peak CT density value was determined for each ROI curve. In those cases in which the peak value occurred more than once, the first value was selected as the peak. To normalize for differing peak values, each subsequent CT density value in a given curve was expressed as a percentage of the peak value. A repeated measures analysis of variance (two groups, four post-peak time points) was then carried out to detect any significant differences in washout rates between patients and controls. A significant group × time point interaction would indicate such a difference in washout rates. In addition, CT density peak v~,l~:c.s ."
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Table 1. Average Intrarater Correlation Coeffidents (_+SD) of CT Density Values for Each ROI ROI RIG R_b'W RTPG RTPW ROG ROW RT RCP
M e a n ± sD 0.91 0.93 0.91 0.75 0.90 0.96 0.87 0.69
± ± ± ± ± ± ± ±
0.08 0.05 0.12 0.08 0.05 0.03 0.08 0.14
ROI LFG LRW LTPG LTPW LOG LOW LT LCP
M e a n __ SD 0.91 0.93 0.90 0.82 0.89 0.97 0.93 0.75
± ± ± ± ± ± ±
0.05 0.03 0.08 0.08 0.09 0.02 0.04 0.15
RF~ = fight frontal gray, LFG = left frontal gray, RFW -- fight f~ontal white, Lr--CV = left frontal white, RTPG = fight temporoparietal gray, LTPG = leR temporoparietal gray, RTPW = fight temporopafietal white, LTPW = left temporopafietal white, ROG = fight occipital gray, LOG = left occipital gray, ROW = fight occipital white, LOW = left occipital white, RT = fiqht t__h8!a~us, LT = left thalamus, RCP = right choroid ~4exus, and LCP = left ¢horoid plexus.
and time-to-peak values were compared between patients and controls using the Student's t-test. To test for any hemispheric asymmetries, peak values and time-to-peak values were compared using the Student's t-test between right and left ROIs separately for patients and controls. Results The 26 PDD patients (19 men, 7 women) ranged in age from 52 to 84 years (mean _+ SD = 67 +-- 8) and the 15 controls (10 men, 5 women), from 51 to 76 years (mean _+ SD = 62 _ 7). The duration of the dementia was determined from the family's report of symptom onset and ranged from 10 to 130 months (mean +- SD = 42 +_ 25). The severity of the dementia was assessed by the Mini-mental State Examination (MMSE) (Folstein et al. 1975), which ranged from 6 to 26 (mean _ SD = 17 +-- 6), and the GDS, which ranged from 3 to 6 (mean -+ so - 4.4 +_ 0.7). All CNS-active medications were discontinued at least 1 week before obtaining the dynamic CT scan. The average intrarater correlation coefficients ( _ so) for each ROI are presented in Table 1 and represent one measure of reliability for the selection of ROIs. Ten of the 16 ROIs had correlations equal to or exceeding 0.90. The lowest correlations were found in the right choroid plexus (0.69) and left choroid plexus (0.75) curves. Regional CT density versus time curves in control subjects are presented in Figure 3 for the eight right-sided ROIs. Each CT density value represents the average for all controls over the eight time points. With the exception of the right choroid plexus (top graph, Figure 3), these normal curves reach a peak at 15 sec (washin phase) and then decline somewhat more slowly over the nent 20 sec (washout phase). Gray matter is known to have a higher brain density than white matter (Arimitsu et al. 1977; Brooks et al. 1980) and this difference is reflected in higher CT density baselines for gray matter ROIs. The CT density baseline for the right choroid plexus is approximately 2.5 times as great as the other ROIs because of the presence of choroid plexus calcification, which is much more common in elderly subjects. The choroid plexus CT density curve, unlike the other curves, ~'eaches a plateau after a normal washin phase and is characteristic of brain regions devoid of blood brain barrier (Dysken et al. 1987). To test for possible differences in BBB permeability between patients and controls, washout curves were compared between groups for the 14 ROIs with a BBB. The four
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Figure 3. Right-sided regional CT density versus time curves are presented for control subjects. The upper panel represents average CT densities over time from the fight choroid plexus (RCP). The lower panel represents average CT densities over time from fight temporoparietal gray (RTPG), fight occipital gray (ROG), and fight frontal gray (RFG), fight occipital white (ROW), fight thalamus (RT), right temporopafietal white (RTPW), and fight frontal white (RFW). CT density values after the peak were expressed as a percent of the peak and the means were examined between groups for each ROI (Figure 4). Although the patients' washout curves declined more gradually than control curves in ! 1 of the 14 ROIs (exceptions were left TP white, right occipital gray, and left occipital gray), in no case did the difference reach statistical significance. A trend toward a significantly slower patient washout curve was noted, however, for the right TP gray region (F - 3.7, p - 0.6) (top graph, Figure
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Figure 4. Washout curves for patients and controls (mean _+ SD) are depicted as a percent of the CT density peak for RTPG (upper panel) and LTPG (lower panel). 4). No meaningful n~tt~m of ~ignifit'ant ~nrr~.latinn~ e.marge~ hetwe~n the __MMSEtotal scores or GDS sceres and washout curve densities over all the patients' ROIs. Differences in CT density peak values and time-to-peak values (sec) between patients and controls and between symmetrical ROIs were examined. There were no significant differences in peak values between patients and controls for any ROI. A significantly longer time-to-peak (me?~ - SD) was found for right TP gray (RTPG) in patients (4.1 +_ 0.4) compared with controls (3.5 - 0.5) (t = 3.1, df = 34,p < 0.005). A significantly higher CT density peak (~xie~ ± so) was found i~ t/atients for leR frontal white (LFW) ,L.. t . . ~ v
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(39.6 _ 3~7) compared ~o right frontal white (RFW) (39.0 - 4.1) (paired t = 2.3, df = 25, p < 0.05). Significantly greater time-to-peak differences were found in patients for left frontal gray (LFG) (3.8 +-. 0.6) compared to right frontal gray (RFG) (3.6 0.7) (paired t = 2.1, df = 25, p < 0.05) and in controls for RFW (4.0 _ 0.5) compared to LFW (3.8 ± 0.04) (paired t = 2.3, df = 14, p < 0.05).
Discussion Dynamic CT scanning in patients with Alzheimer's disease and age-matched controls did not demonstrate any significant differences in the decline of CT density washout curves for any of the grey or white matter ROIs. "~us, the results with this imaging technique do not support the hypothesis of an increas~ in BBB permeability in Alzbeimer's disease. Our study is consistent with recent positron emission tomography (PET) studies that have also failed to demonstrate a breakdown in BBB in Alzheimer patients (Friedland et al. 1985a, 1985b; Schlageter et al. 1987). It is also consistent with the absence of demonstrable edema in Alzheimer's disease (Klatzo ct al. 1980; Rapoport 1976, 1978). The few statistically significant differences in CT density peaks and times-to-peak between Alzheimer patients and controls and between right- and left-sided ROIs did not follow any particular pattern and may have resulted by chance due to the numerous comparisons that were done. It is not surprising that the right and left choroid plexus ROIs produced the greatest intrarater variability in CT density values. The choroid plexuses were often small in size and irregular in shape, which made it difficult at times to position the cursor exactly over this area without including some portion of the adjacent CSF area. In general, however, the overall high correlation coefficients for the ROls demonstrate good intrarater reliability, particularly for those gray matter regions of the brain where the neuropathology of Alzheirner's disease is prominent and where an increase in BBB permeability may be most likely (Wisniewski and Kozlowski 1982). Several methodological changes that were adopted in this study developed from our previous experience in assessing dynamic CT scan washout curves in another patient sample and control group (Dysken et al. 1987). In this earlier study, the classification of CT density curves was approached qualitatively as a pattern-recognition problem (plateau curves versus normal curves). The cursor was moved systematic~ly from region to adjacent region, omitting only the skull and ventricles, so that the entire breJn slice was examined. The number of plateau curves for each subject was counted and used in detemma~ng statistically significant differences between patients and controls. In addition, only six CT density time points were available for analyses. In the present study, CT density curves over eight time points were sampled from specific anatomical regions that would vary in the severity of neuropathological lesions found in Alzheimer's disease. It was postulated that prolonged washout curves would be found preferentially in gray matter regions as neuritic plaques and neurofibrillary "t~,,gles are in greater abundance in cortex than in subcortical white matter. It was, therefore, the desire to assess quantitatively specific anatomic areas of disrupted BBB functioning that resulted in a modification of our initial approach. We would like to thank Glen D. Dobben, M.D. for his helpful suggestions and support in study.
carrying out this
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