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Right putamen and age are the most discriminant features to diagnose Parkinson's disease by using 123I-FP-CIT brain SPET data by using an artificial neural network classifier, a classification tree (ClT).

Right putamen and age are the most discriminant features to diagnose Parkinson's disease by using 123I-FP-CIT brain SPET data by using an artificial neural network classifier, a classification tree (ClT). Hell J Nucl Med. 2017 Sep-Dec;20 Suppl:165 Authors: Cascianelli S, Tranfaglia C, Fravolini ML, Bianconi F, Minestrini M, Nuvoli S, Tambasco N, Dottorini ME, Palumbo B Abstract OBJECTIVE: The differential diagnosis of Parkinson's disease (PD) and other conditions, such as essential tremor and drug-induced parkinsonian syndrome or normal aging brain, represents a diagnostic challenge. 123I-FP-CIT brain SPET is able to contribute to the differential diagnosis. Semiquantitative analysis of radiopharmaceutical uptake in basal ganglia (caudate nuclei and putamina) is very useful to support the diagnostic process. An artificial neural network classifier using 123I-FP-CIT brain SPET data, a classification tree (CIT), was applied. CIT is an automatic classifier composed of a set of logical rules, organized as a decision tree to produce an optimised threshold based classification of data to provide discriminative cut-off values. We applied a CIT to 123I-FP-CIT brain SPET semiquantitave data, to obtain cut-off values of radiopharmaceutical uptake ratios in caudate nuclei and putamina with the aim to diagnose PD versus other conditions. SUBJECTS AND METHOD: We retrospectively investigated 187 patients undergoing 123I-FP-CIT brain SPET (Millenium VG, G.E.M.S.) wi...
Source: Hellenic Journal of Nuclear Medicine - Category: Nuclear Medicine Tags: Hell J Nucl Med Source Type: research

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ConclusionsThe length of the striatal region uptake is clinically useful and highly valuable to confirm dopaminergic degeneration “in vivo” as an aid to the diagnosis of Parkinson’s disease. It compares fairly well to the standard uptake ratio-based features, reaching, at least, similar accuracies and is easier to obtain automatically. Thus, we propose its day to day clinical use, jointly with the uptake ratio-based feat ures, in the computer-aided diagnosis of dopaminergic degeneration in Parkinson’s disease.
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