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

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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.
Original languageEnglish
Pages (from-to)194-201
Number of pages8
JournalNuclear Medicine Communications
Volume30
Issue number3
DOIs
Publication statusPublished - Mar 2009

Fingerprint

Nortropanes
Parkinsonian Disorders
Single-Photon Emission-Computed Tomography
Automated Pattern Recognition
Automation
ROC Curve

Keywords

  • case-control studies
  • female
  • follow-up studies
  • humans
  • male
  • neostriatum
  • Parkinsonian disorders
  • reproducibility of results
  • tomography, emission-computed, single-photon
  • tropanes
  • 123I-N-[omega]-fluoropropyl-2-[beta]-carbomethoxy-3[beta]-(4-iodophenyl) nortropane
  • neurodegenerative diseases
  • Parkinson's disease
  • pattern recognition
  • single-photon emission computed tomography

Cite this

@article{69d00aa03a4e4addbee4dde6f12c9e05,
title = "Shape analysis of 123I-N-ω-fluoropropyl-2-β-carbomethoxy-3β-(4-iodophenyl) nortropane single-photon emission computed tomography images in the assessment of patients with parkinsonian syndromes",
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.",
keywords = "case-control studies, female, follow-up studies, humans, male, neostriatum, Parkinsonian disorders, reproducibility of results, tomography, emission-computed, single-photon, tropanes, 123I-N-[omega]-fluoropropyl-2-[beta]-carbomethoxy-3[beta]-(4-iodophenyl) nortropane, neurodegenerative diseases, Parkinson's disease, pattern recognition, single-photon emission computed tomography",
author = "Staff, {Roger T} and Ahearn, {Trevor S} and Kevin Wilson and Counsell, {Carl E} and Kate Taylor and Robert Caslake and Davidson, {Joyce E.} and Gemmell, {Howard G} and Murray, {Alison D}",
year = "2009",
month = "3",
doi = "10.1097/MNM.0b013e328314b863",
language = "English",
volume = "30",
pages = "194--201",
journal = "Nuclear Medicine Communications",
issn = "0143-3636",
publisher = "Lippincott Williams and Wilkins",
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TY - JOUR

T1 - Shape analysis of 123I-N-ω-fluoropropyl-2-β-carbomethoxy-3β-(4-iodophenyl) nortropane single-photon emission computed tomography images in the assessment of patients with parkinsonian syndromes

AU - Staff, Roger T

AU - Ahearn, Trevor S

AU - Wilson, Kevin

AU - Counsell, Carl E

AU - Taylor, Kate

AU - Caslake, Robert

AU - Davidson, Joyce E.

AU - Gemmell, Howard G

AU - Murray, Alison D

PY - 2009/3

Y1 - 2009/3

N2 - 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.

AB - 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.

KW - case-control studies

KW - female

KW - follow-up studies

KW - humans

KW - male

KW - neostriatum

KW - Parkinsonian disorders

KW - reproducibility of results

KW - tomography, emission-computed, single-photon

KW - tropanes

KW - 123I-N-[omega]-fluoropropyl-2-[beta]-carbomethoxy-3[beta]-(4-iodophenyl) nortropane

KW - neurodegenerative diseases

KW - Parkinson's disease

KW - pattern recognition

KW - single-photon emission computed tomography

U2 - 10.1097/MNM.0b013e328314b863

DO - 10.1097/MNM.0b013e328314b863

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JO - Nuclear Medicine Communications

JF - Nuclear Medicine Communications

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ER -