[123I]Metaiodobenzylguanidine (MIBG) Cardiac Scintigraphy and Automated Classification Techniques in Parkinsonian Disorders.
Purpose: To provide reliable and reproducible heart/mediastinum (H/M) ratio cut-off values for parkinsonian disorders using two machine learning techniques, Support Vector Machines (SVM) and Random Forest (RF) classifier, applied to [123I]MIBG cardiac scintigraphy.Procedures: We studied 85 subjects,...
| Publicado en: | Molecular Imaging & Biology Vol. 22; no. 3; pp. 703 - 711 |
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| Autores principales: | , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Jun2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=143439698&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 143439698 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15361632 KJU jtl: Molecular Imaging & Biology issn: 15361632 maglogo: N pubinfo: dt: Jun2020 vid: 22 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 143439698 143439698 NLM31309370 10.1007/s11307-019-01406-6 NLM31309370 143439698 ppf: 703 ppct: 8 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: [123I]Metaiodobenzylguanidine (MIBG) Cardiac Scintigraphy and Automated Classification Techniques in Parkinsonian Disorders. aug: au: Nuvoli, Susanna Spanu, Angela Fravolini, Mario Luca Bianconi, Francesco Cascianelli, Silvia Madeddu, Giuseppe Palumbo, Barbara affil: Unit of Nuclear Medicine, Department of Medicine, Surgical and Experimental Science, University of Sassari, Viale San Pietro 8, 07100, Sassari, Italy sug: subj: Mediastinum Parkinsonian Disorders Classification Parkinsonian Disorders Radionuclide Imaging Methods Iodine Radioisotopes Benzene Derivatives Benzene Derivatives Pharmacokinetics Heart Iodine Radioisotopes Pharmacokinetics Radiopharmaceuticals Metabolism Parkinsonian Disorders Pathology Retrospective Design Female Radiopharmaceuticals Male Aged Aged, 80 and Over Middle Age Adult Aged: 65+ years Aged, 80 & over Middle Aged: 45-64 years Adult: 19-44 years Female Male ab: Purpose: To provide reliable and reproducible heart/mediastinum (H/M) ratio cut-off values for parkinsonian disorders using two machine learning techniques, Support Vector Machines (SVM) and Random Forest (RF) classifier, applied to [123I]MIBG cardiac scintigraphy.Procedures: We studied 85 subjects, 50 with idiopathic Parkinson's disease, 26 with atypical Parkinsonian syndromes (P), and 9 with essential tremor (ET). All patients underwent planar early and delayed cardiac scintigraphy after [123I]MIBG (111 MBq) intravenous injection. Images were evaluated both qualitatively and quantitatively; the latter by the early and delayed H/M ratio obtained from regions of interest (ROIt1 and ROIt2) drawn on planar images. SVM and RF classifiers were finally used to obtain the correct cut-off value.Results: SVM and RF produced excellent classification performances: SVM classifier achieved perfect classification and RF also attained very good accuracy. The better cut-off for H/M value was 1.55 since it remains the same for both ROIt1 and ROIt2. This value allowed to correctly classify PD from P and ET: patients with H/M ratio less than 1.55 were classified as PD while those with values higher than 1.55 were considered as affected by parkinsonism and/or ET. No difference was found when early or late H/M ratio were considered separately thus suggesting that a single early evaluation could be sufficient to obtain the final diagnosis.Conclusions: Our results evidenced that the use of SVM and CT permitted to define the better cut-off value for H/M ratios both in early and in delayed phase thus underlining the role of [123I]MIBG cardiac scintigraphy and the effectiveness of H/M ratio in differentiating PD from other parkinsonism or ET. Moreover, early scans alone could be used for a reliable diagnosis since no difference was found between early and late. Definitely, a larger series of cases is needed to confirm this data. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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