Data mining using SPECT can predict neurological symptom development in Parkinson's patients

We have compared in Parkinson's diseases patients neurological data with the local cerebral blood flow measured by the Single-Photon Emission Computed Tomography. Most of our patients underwent Deep Brain Stimulation surgery or were qualified for one in relation to the advanced disease progression. Local cerebral blood flow in different areas has correlated to the Unified Parkinson's Disease Rating Scale (UPDRS). We have used two different data mining methods: WEKA and Rough Set Exploration System to explore these correlations. We have demonstrated that cerebral blood flow changes gave good predictions for the UPDRS IV (84 %) that suggest that a general state of Parkinson Disease are stronger related to the cerebral blood flow than to only motor symptoms.

[1]  Eileen O. Smith,et al.  Decreased single‐photon emission computed tomographic {123I}β‐CIT striatal uptake correlates with symptom severity in parkinson's disease , 1995, Annals of neurology.

[2]  Zdzislaw Pawlak,et al.  Rough Set Theory and its Applications to Data Analysis , 1998, Cybern. Syst..

[3]  P. Tienari,et al.  How useful is [123I]β-CIT SPECT in clinical practice? , 2005, Journal of Neurology, Neurosurgery & Psychiatry.

[4]  Dirk Van den Poel,et al.  FACULTEIT ECONOMIE , 2007 .

[5]  J. Obeso,et al.  Functional organization of the basal ganglia: Therapeutic implications for Parkinson's disease , 2008, Movement disorders : official journal of the Movement Disorder Society.

[6]  J. Seibyl,et al.  [123I]β-CIT SPECT imaging assessment of the rate of Parkinson’s disease progression , 2001, Neurology.

[7]  K. Mewes,et al.  The subthalamic nucleus in Parkinson's disease: somatotopic organization and physiological characteristics. , 2001, Brain : a journal of neurology.

[8]  D J Wyper,et al.  Correlation of Parkinson's disease severity and duration with 123I‐FP‐CIT SPECT striatal uptake , 2000, Movement disorders : official journal of the Movement Disorder Society.

[9]  K L Chou,et al.  Diagnostic accuracy of [99mTc]TRODAT-1 SPECT imaging in early Parkinson's disease. , 2004, Parkinsonism & related disorders.

[10]  Orazio Schillaci,et al.  123I-FP-CIT semi-quantitative SPECT detects preclinical bilateral dopaminergic deficit in early Parkinson's disease with unilateral symptoms , 2005, Nuclear medicine communications.

[11]  Artur Szymanski,et al.  Rough Set Rules Help to Optimize Parameters of Deep Brain Stimulation in Parkinson's Patients , 2014, Brain Informatics and Health.