Literature DB >> 19262280

Shape analysis of 123I-N-omega-fluoropropyl-2-beta-carbomethoxy-3beta-(4-iodophenyl) nortropane single-photon emission computed tomography images in the assessment of patients with parkinsonian syndromes.

Roger T Staff1, Trevor S Ahearn, Kevin Wilson, Carl E Counsell, Kate Taylor, Robert Caslake, Joyce E Davidson, Howard G Gemmell, Alison D Murray.   

Abstract

PURPOSE: The purpose of this study was to show the viability and performance of a shape-based pattern recognition technique applied to I-N-omega-fluoropropyl-2-beta-carbomethoxy-3beta-(4-iodophenyl) nortropane single-photon emission computed tomography (FP-CIT SPECT) in patients with parkinsonism.
METHODS: A fully automated pattern recognition tool, based on the shape of FP-CIT SPECT images, was written using Java. Its performance was evaluated and compared with QuantiSPECT, a region-of-interest-based quantitation tool, and observer performance using receiver operating characteristic analysis and kappa statistics. The techniques were compared using a sample of patients and controls recruited from a prospective community-based study of first presentation of parkinsonian symptoms with longitudinal follow up (median 3 years).
RESULTS: The shape-based technique as well as the conventional semiquantitative approach was performed by experienced observers. The technique had a high level of automation, thereby avoiding observer/operator variability.
CONCLUSION: A pattern recognition approach is a viable alternative to traditional methods of analysis in FP-CIT SPECT and has additional advantages.

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Year:  2009        PMID: 19262280     DOI: 10.1097/MNM.0b013e328314b863

Source DB:  PubMed          Journal:  Nucl Med Commun        ISSN: 0143-3636            Impact factor:   1.690


  6 in total

1.  Visual assessment of dopaminergic degeneration pattern in 123I-FP-CIT SPECT differentiates patients with atypical parkinsonian syndromes and idiopathic Parkinson's disease.

Authors:  Deniz Kahraman; Carsten Eggers; Harald Schicha; Lars Timmermann; Matthias Schmidt
Journal:  J Neurol       Date:  2011-07-13       Impact factor: 4.849

2.  Visual versus automated analysis of [I-123]FP-CIT SPECT scans in parkinsonism.

Authors:  Elina Mäkinen; Juho Joutsa; Jarkko Johansson; Maija Mäki; Marko Seppänen; Valtteri Kaasinen
Journal:  J Neural Transm (Vienna)       Date:  2016-06-20       Impact factor: 3.575

Review 3.  Imaging approaches for dementia.

Authors:  A D Murray
Journal:  AJNR Am J Neuroradiol       Date:  2011-12-01       Impact factor: 3.825

Review 4.  What can imaging tell us about cognitive impairment and dementia?

Authors:  Leela Narayanan; Alison Dorothy Murray
Journal:  World J Radiol       Date:  2016-03-28

5.  Combined visual and semi-quantitative assessment of 123I-FP-CIT SPECT for the diagnosis of dopaminergic neurodegenerative diseases.

Authors:  Jun Ueda; Hajime Yoshimura; Keiji Shimizu; Megumu Hino; Nobuo Kohara
Journal:  Neurol Sci       Date:  2017-04-07       Impact factor: 3.307

6.  Improvement of classification performance of Parkinson's disease using shape features for machine learning on dopamine transporter single photon emission computed tomography.

Authors:  Takuro Shiiba; Yuki Arimura; Miku Nagano; Tenma Takahashi; Akihiro Takaki
Journal:  PLoS One       Date:  2020-01-24       Impact factor: 3.240

  6 in total

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