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(¹²³I) -CIT and Single-Photon Emission Computed Tomographic Imaging vs Clinical Evaluation in Parkinsonian Syndrome

Unmasking an Early Diagnosis

Danna L. Jennings, MD; John P. Seibyl, MD; David Oakes, PhD; Shirley Eberly, PhD; John Murphy, MD; Ken Marek, MD

Arch Neurol. 2004;61:1224-1229.

Background  The diagnosis of Parkinson disease is currently based on clinical evaluation. Functional neuroimaging using (¹²³I) -carboxymethyoxy-3--(4-iodophenyl) tropane (CIT) and single-photon emission computed tomography (SPECT) provides information on the integrity of the dopaminergic system in vivo and is a promising diagnostic tool in early Parkinson disease.

Objective  To evaluate the diagnostic accuracy of dopamine transporter imaging using (¹²³I)-CIT in patients with suspected parkinsonian syndrome (PS).

Design  Community neurologists referred patients with suspected PS for imaging evaluation. Clinical diagnoses (positive PS or negative PS) were provided by the community neurologists and 2 movement disorder experts. We performed (¹²³I)-CIT and SPECT imaging, and imaging diagnoses of positive PS or negative PS were assigned. A 6-month follow-up clinical diagnosis was assigned by a movement disorder expert blind to the imaging data, which represented the "gold standard" diagnosis for the study.

Results  Thirty-five patients with suspected PS were referred. Diagnoses in question included essential tremor, psychogenic parkinsonism, drug-induced parkinsonism, primary dystonia, and unspecified gait disorder. Comparing the community neurologist’s diagnoses at referral with the gold standard diagnosis, there was dis agreement in 25.7% (sensitivity, 0.92; specificity, 0.30). Comparing the quantitative imaging diagnoses with the gold standard, there was disagreement in 8.6% (sensitivity, 0.92; specificity, 1.00).

Conclusion  Performing (¹²³I)-CIT and SPECT imaging at baseline appears to be a useful diagnostic tool to detect patients thought to have PS at baseline but who, after follow-up, do not have PS.

Author Affiliations: Institute for Neurodegenerative Disorders, New Haven, Conn (Drs Jennings, Seibyl, and Marek); Department of Biostatistic and Computational Biology, University of Rochester, Rochester, NY (Dr Oakes and Eberly); and Associated Neurologists, Danbury, Conn (Dr Murphy).

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