Validation of an automated morphological MRI-based (123)I-FP-CIT SPECT evaluation method

Perlaki, Gábor and Szekeres, Sarolta and Orsi, Gergely and Papp, László and Suha, Balázs and Nagy, Szilvia Anett and Dóczi, Tamás and Janszky, József and Zámbó, Katalin and Kovács, Norbert (2016) Validation of an automated morphological MRI-based (123)I-FP-CIT SPECT evaluation method. Parkinsonism and Related Disorders, 29. pp. 24-29. ISSN 1353-8020

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Abstract

INTRODUCTION Dopamine transporter imaging with (123)I-FP-CIT single photon emission computed tomography (SPECT) is helpful for the differential diagnosis between Parkinsonian syndrome (PS) and essential tremor (ET). Although visual assessment and time-consuming manual evaluation techniques are readily available, a fully objective and automated dopamine transporter quantification technique is always preferable, at least in research and follow-up investigations. Our aim was to develop a novel automated magnetic resonance imaging (MRI)-based evaluation technique of dopamine transporter SPECT images and to compare its diagnostic accuracy with those of the gold-standard visual grading and manual dopamine transporter binding quantification methods. METHODS (123)I-FP-CIT SPECT and MRI sessions were conducted in 33 patients with PS (15 men; mean age: 60.3 ± 9.7 years) and 15 patients with ET (8 men; mean age: 54.7 ± 16.3 years). Striatal dopamine transporter binding was visually classified by 2 independent experts as normal or abnormal grade I, II and III. Caudal and putaminal specific uptake ratios were calculated by both automated MRI-based and manual evaluation techniques. RESULTS We found almost perfect agreement (κ = 0.829) between the visual scores by the 2 observers. The automated method showed strong correlation with the visual and manual evaluation techniques and its diagnostic accuracy (sensitivity = 97.0%; specificity = 93.3%) was also comparable to these methods. The automatically determined uptake parameters showed negative correlation with the clinical severity of parkinsonism. Based on ordinal regression modelling, the automated MRI-based method could reliably determine the visual grading scores. CONCLUSION The novel MRI-based evaluation of (123)I-FP-CIT SPECT images is useful for the differentiation of PS from ET.

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