Longitudinally Confirmed Database of Normal Elderly Subjects
The accurate diagnosis of Alzheimer's Disease and its precursor states requires a Normals reference
data set that is truly Normal.  Because Alzheimer's Disease progresses over a period of up to two
decades, many "Normals" actually have imaging biomarker values that are characteristic of emerging
disease.  Including these patients in a Normal reference set  blurs the difference between the Normal
baseline and the image data of patients with developing disease.  
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Researchers at the New York University
Center for Brain Health (NYU), led by Dr.
Mony de Leon, collected an extensive
history of image and other data from
patients who were initially classified as
Normal.  Some of these patients
remained Normal as evaluated using
clinical tests for at least 4 years, whereas
others declined.  Mosconi et al (
J Nuclear
July 2007) demonstrated that
the accuracy of classifying patients as
Normal, Mild Cognitive Impairment, or
Alzheimer's Disease was significantly
improved when using a Normals
reference that included  only those
subjects who had remained clinically
Normal for at least 4 years.
ABOVE:  Percent correctly identified cases using mixed Normals
database (white bars) vs. database including only Normals who
remained clinically Normal for at least 4 years (hatched).
Reference values from this unique, longitudinally confirmed reference set of Normal subjects are another
improtant element that Abiant is integrating into its Alzheimer's Disease diagnostic.