Diagnosis Of Regional Cerebral Blood Flow By Partitioning.

Alexander Zemcov; Joseph Sansone; Laurie Barclay

doi:10.1117/12.975411

12 June 1986 Diagnosis Of Regional Cerebral Blood Flow By Partitioning.

Alexander Zemcov, Joseph Sansone, Laurie Barclay

Proceedings Volume 0626, Application of Optical Instrumentation in Medicine XIV and Picture Archiving and Communication Systems; (1986) https://doi.org/10.1117/12.975411
Event: Application of Optical Instrumentation in Medicine XIV and Picture Archiving and Communication Systems (PACS IV) for Medical Applications, 1986, Newport Beach, CA, United States

Abstract

A scheme is proposed for discriminating between patients with Alzheimer's disease and age-matched normals using regional cerebral blood flow data measured by the noninvasive Xe-133 inhalation technique. Regional blood flows which are known to be decreased in Alzheimer's disease but are known to overlap to some degree with flows from normals are usually interpreted subjectively. In the scheme presented these flow values are used to form cumulative distributions for each subject group and for each detector. Pairs of distributions for homologous detectors are compared and the blood flow value at which this difference is the greatest is identified as the cutoff value. The 32 pairs of distributions give rise to 32 cutoff values. For each individual and detector the flow values are compared to their respective cutoffs. Those flow values which exceed their cutoff are assigned a 1 and those that are less than the cutoff a 0. For each subject and hemisphere these binary values are cummed where the sums for each hemisphere range in value from 0 to 16. A new cutoff for this sum is chosen and the sums for each patient are compared to this value. In the two groups sited the cutoff was set at a sum of 12 for each hemisphere. The majority of the normals had hemispheric sums of 14 or greater. The patients with Alzheimer's disease had sums that were equally distributed over the whole range of possible sums. This result indicated that the classification scheme was unlikely to classify a normal as an abnormal. However, there was a significant likelihood that an abnormal could be classified as a normal. These two qualities are defined as the sensitivity and specificity respectively. The test was sensitive (90%) but less specific (70%). The results of this classification scheme compared favorably with the subjective interpretation of experienced readers.

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Alexander Zemcov, Joseph Sansone, and Laurie Barclay "Diagnosis Of Regional Cerebral Blood Flow By Partitioning.", Proc. SPIE 0626, Application of Optical Instrumentation in Medicine XIV and Picture Archiving and Communication Systems, (12 June 1986); https://doi.org/10.1117/12.975411

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KEYWORDS

Sensors

Alzheimer's disease

Blood circulation

Binary data

Cerebral blood flow

Computed tomography

Xenon

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