Comparison of two neural network classifiers in the differential diagnosis of essential tremor and Parkinson's disease by (123)I-FP-CIT brain SPECT

To contribute to the differentiation of Parkinson's disease (PD) and essential tremor (ET), we compared two different artificial neural network classifiers using (123)I-FP-CIT SPECT data, a probabilistic neural network (PNN) and a classification tree (ClT). (123)I-FP-CIT brain SPECT with semiqu...

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Bibliographic Details
Published in:European journal of nuclear medicine and molecular imaging 2010-11, Vol.37 (11), p.2146-2153
Main Authors: Palumbo, Barbara, Fravolini, Mario Luca, Nuvoli, Susanna, Spanu, Angela, Paulus, Kai Stephan, Schillaci, Orazio, Madeddu, Giuseppe
Format: Article
Language:English
Subjects:
Adult
Aged
Aged, 80 and over
Brain - diagnostic imaging
Data Interpretation, Statistical
Diagnosis, Differential
Essential Tremor - diagnostic imaging
Female
Humans
Male
Middle Aged
Neural Networks (Computer)
Parkinson Disease - diagnostic imaging
Probability
Tomography, Emission-Computed, Single-Photon - methods
Tropanes
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Summary:To contribute to the differentiation of Parkinson's disease (PD) and essential tremor (ET), we compared two different artificial neural network classifiers using (123)I-FP-CIT SPECT data, a probabilistic neural network (PNN) and a classification tree (ClT). (123)I-FP-CIT brain SPECT with semiquantitative analysis was performed in 216 patients: 89 with ET, 64 with PD with a Hoehn and Yahr (H&Y) score of ≤2 (early PD), and 63 with PD with a H&Y score of ≥2.5 (advanced PD). For each of the 1,000 experiments carried out, 108 patients were randomly selected as the PNN training set, while the remaining 108 validated the trained PNN, and the percentage of the validation data correctly classified in the three groups of patients was computed. The expected performance of an "average performance PNN" was evaluated. In analogy, for ClT 1,000 classification trees with similar structures were generated. For PNN, the probability of correct classification in patients with early PD was 81.9±8.1% (mean±SD), in patients with advanced PD 78.9±8.1%, and in ET patients 96.6±2.6%. For ClT, the first decision rule gave a mean value for the putamen of 5.99, which resulted in a probability of correct classification of 93.5±3.4%. This means that patients with putamen values >5.99 were classified as having ET, while patients with putamen values
ISSN:1619-7089
DOI:10.1007/s00259-010-1481-6