CT measurement of suprasellar cistern predicts rate of cognitive decline in Alzheimer's disease
Previous studies reveal significant relationships between some quantitative computed tomography (CT) measures and level of cognitive functioning in patients with Alzheimer's disease (AD). This study was designed to determine whether measurements from CT scans of AD patients could predict future rates of decline in cognitive function. Subjects were 8 men and 19 women diagnosed with probable AD. CT measures included bifrontal ratio, bicaudate ratio, and areas of lateral ventricles, third ventricle, and suprasellar cistern (SSC). Measures of cognitive and adaptive functioning were obtained at the time of the scan and on follow-up. Of the CT measures, the SSCR (SSC corrected for intracranial area) was the most highly correlated with Mini-Mental State Exam (MMSE) score and other cognitive measures at the time of the scan. Follow-up data were obtained for those 20 individuals who were mildly to moderately demented at the time of the scan (MMSE > or = 10). Rate of change was calculated for each neuropsychological measure. The SSCR correlated significantly with rate of change for MMSE and other measures of cognitive and adaptive functioning. This study demonstrates that CT measurement of the SSC can predict the subsequent rate of neurocognitive decline in AD patients.
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ABSTRACT: Functional imaging of the brain can aid in the diagnosis of Alzheimer’s disease. Tc-HMPAO SPECT is widely available and relatively
inexpensive to use. Combined with computer-based analysis of images, SPECT is a powerful tool in detecting decreases in brain
perfusion caused by Alzheimer’s disease. However, analysis can falsely elevate the perfusion of normal areas and diminish
the perfusion of atrophic areas in the Alzheimer’s brain when used with conventional scaling methods. In this paper, we present
a technique for scaling images that overcomes the problems associated with conventional scaling methods. Our technique was
successful in eliminating or attenuating the false increases in perfusion shown in probable Alzheimer’s patients in over 90%
of cases (n=17), and in enhancing the sensitivity of detection of degenerative changes by Statistical Parametric Mapping.
Available from: Abdullah Bin Zahid
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ABSTRACT: Purpose: To determine if brain atrophy can be calculated by performing volumetric analysis on conventional computed tomography (CT) scans in spite of relatively low contrast for this modality.
Materials & Method: CTs for 73 patients from the local Veteran Affairs database were selected. Exclusion criteria: AD, NPH, tumor, and alcohol abuse. Protocol: conventional clinical acquisition (Toshiba; helical, 120 kVp, X-ray tube current 300mA, slice thickness 3-5mm). Locally developed, automatic algorithm was used to segment intracranial cavity (ICC) using (a) white matter seed (b) constrained growth, limited by inner skull layer and (c) topological connectivity. ICC was further segmented into CSF and brain parenchyma using a threshold of 16 Hu.
Results: Age distribution: 25–95yrs.; (Mean 67±17.5yrs.). Significant correlation was found between age and CSF/ICC(r=0.695, p<0.01 2-tailed). A quadratic model(y=0.06–0.001x+2.56x10-5x2; where y=CSF/ICC and x=age) was a better fit to data(r=0.716, p<0.01). This is in agreement with MRI literature. For example, Smith et al (1) found annual CSF/ICC increase in 58 – 94.5 y.o. individuals to be 0.2%/year, whereas our data, restricted to the same age group yield 0.3%/year(0.2–0.4%/yrs. 95%C.I.). Slightly increased atrophy among elderly VA patients is attributable to the presence of other comorbidities.
Conclusion: Brain atrophy can be reliably calculated using automated software and conventional CT. Compared to MRI, CT is more widely available, cheaper, and less affected by head motion due to ~100 times shorter scan time. Work is in progress to improve the precision of CT by allowing the measurement of longitudinal changes within the patient.
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