The importance of hybrid imaging methods in the qualitative and quantitative evaluation of brain receptor scintigraphy

A 123I-FP-CIT dopamin transzporter SPECT képalkotás egy érzékeny módszer a működőképes striatális dopaminerg idegvégződések működésének megítélésére. A módszer évek óta Magyarországon is elérhető. Két fő indikációja a (i) klinikailag bizonytalan, vagy korai tüneteket produkáló Parkinsonizmus és az esszenciális tremor elkülönítése, valamint a (ii) Lewy-testes demenciának az Alzheimer-kórtól való megkülönböztetése. Jelen értekezés célja, hogy a nemzetközi adatok és ajánlások, valamint saját tapasztalatok alapján bemutassa a 123I-FP-CIT SPECT képalkotást, ezzel segítve a gyakorló nukleáris medicina szakemberek és a neurológusok munkáját

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

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