We have performed a quantitative analysis of the amyloid load (plaques), neuritic plaques and neurofibrillary tangles (NFT) in the frontal, temporal and parietal association cortices of autopsied brains from 49 prospectively evaluated patients with Alzheimer''s disease (AD) diagnosed according to three sets of published pathological criteria. These patients had been assessed clinically with psychological testing of cognitive abilities within 6 months of death. Correlations were sought between severity of pathological change and cognitive status before death, duration of disease and age at death. Using Khachaturian and CERAD criteria highly positive correlations were obtained between the extent of cognitive deficit and the density of NFT in frontal and parietal lobes. The percentage area of cortex occupied by amyloid in the parietal lobe was correlated to the cognitive deficit only in the CERAD-diagnosed cases. The density of all amyloid plaques (AP) showed no correlation with the extent of cognitive deficit, but the densities of neuritic plaques did correlate with cognitive deficit. Both amyloid load and tangle densities were positively correlated with disease duration. All these correlations were reduced or absent in a sub-group of cases fulfilling the Tierney et al. A3 diagnostic criteria for AD. We found no pathological measure that correlated with the age of patients at death. Amyloid loads and NFT densities showed highly significant but selective positive correlations, the most striking being between temporal lobe NFT density and frontal and parietal lobe amyloid load and between temporal lobe NFT density and frontal and parietal lobe NFT densities. Correlations involving AP density as a measure of amyloid load were almost always less significant than those involving the percentage area of cortex occupied by amyloid, suggesting that the latter measures amyloid load more accurately. However, the highest correlations of NFT densities were with neuritic plaque densities. Overall this study highlights the relevance of neuritic changes (revealed by NFT and neuritic plaques) and the irrelevance of amyloid plaques to the dementia of AD.
Neurofibrillary tangles (NFT), neuritic plaques and amyloid load were quantified in sections of the hippocampus at the level of the lateral geniculate body in 41 consecutive cases fulfilling pathological criteria for diagnosis of Alzheimer’s disease (AD) and coming to autopsy after longitudinal study during life. A strong correlation was found between NFT density in the hippocampus and cognitive impairment scores obtained shortly before death, particularly with scores of memory impairment. Weaker and less consistent correlations were found for hippocampal neuritic plaques and amyloid load with cognitive/ memory deficits. No significant correlations were found between hippocampal pathology and either age of onset or disease duration. All three measures of hippocampal pathology were inversely correlated with the minimum medial temporal lobe (MTL) width, a measure of the MTL atrophy made from temporal-lobe-oriented X-ray computed tomography scans performed during life; the strongest correlation being between atrophy of the MTL and NFT density in the hippocampus.
In this study we analysed the accuracy of two sets of clinical diagnostic criteria, the NINCDS/ADRDA and DSM-III-R, in relation to the currently used pathological diagnostic criteria for Alzheimer’s disease (AD), the Khachaturian criteria, the Tierney A3 criteria and the CERAD protocol. The sensitivity of the individual clinical diagnostic criteria, NINCDS/ADRDA and DSM-III-R, is poor (34–58%) irrespective of the pathological diagnostic criteria applied for the definite diagnosis of AD. The combination of the NINCDS/ADRDA ‘possible’ and ‘probable dementia of the Alzheimer type’ (DAT) categories has a high sensitivity (91–98%). However the combination resulted in very poor specificity (40–61%). Thus, none of the clinical diagnostic criteria is satisfactory. We found similar results when we analysed the predictive value of these clinical diagnostic criteria. The positive predictive value of NINCDS ‘probable DAT’ category and that of the DAT diagnosis by DSM-III-R is very high (89–100%). This makes the use of these categories suitable for research purposes. However, the negative predictive value of both diagnoses is poor (33–63%), making these criteria unsuitable for diagnostic purposes in clinical practice.
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