Gabor Perlaki1, Sarolta Szekeres2, Gergely Orsi1, Laszlo Papp3, Balazs Suha2, Szilvia Anett Nagy4, Tamas Doczi5, Jozsef Janszky6, Katalin Zambo2, Norbert Kovacs7. 1. MTA-PTE Clinical Neuroscience MR Research Group, H-7623 Pecs, Hungary; Pecs Diagnostic Centre, H-7623 Pecs, Hungary. 2. Department of Nuclear Medicine, University of Pecs, H-7624 Pecs, Hungary. 3. Mediso Medical Imaging Systems, H-1022 Budapest, Hungary. 4. Pecs Diagnostic Centre, H-7623 Pecs, Hungary; MTA-PTE Neurobiology of Stress Research Group, H-7624 Pecs, Hungary. 5. MTA-PTE Clinical Neuroscience MR Research Group, H-7623 Pecs, Hungary; Pecs Diagnostic Centre, H-7623 Pecs, Hungary; Department of Neurosurgery, University of Pecs, H-7623 Pecs, Hungary. 6. MTA-PTE Clinical Neuroscience MR Research Group, H-7623 Pecs, Hungary; Department of Neurology, University of Pecs, H-7623 Pecs, Hungary. 7. MTA-PTE Clinical Neuroscience MR Research Group, H-7623 Pecs, Hungary; Department of Neurology, University of Pecs, H-7623 Pecs, Hungary. Electronic address: kovacs.norbert@pte.hu.
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.
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.
Authors: Antonio M Durán-Rosal; Julio Camacho-Cañamón; Pedro Antonio Gutiérrez; Maria Victoria Guiote Moreno; Ester Rodríguez-Cáceres; Juan Antonio Vallejo Casas; César Hervás-Martínez Journal: Sci Rep Date: 2021-03-29 Impact factor: 4.379