Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Automated quantification of myocardial infarction from MR images by accounting for partial volume effects: animal, phantom, and human study.

Heiberg, Einar LU ; Ugander, Martin LU ; Engblom, Henrik LU ; Götberg, Matthias LU ; Olivecrona, Göran LU ; Erlinge, David LU orcid and Arheden, Håkan LU (2008) In Radiology 246(2). p.581-588
Abstract
Ethics committees approved human and animal study components; informed written consent was provided (prospective human study [20 men; mean age, 62 years]) or waived (retrospective human study [16 men, four women; mean age, 59 years]). The purpose of this study was to prospectively evaluate a clinically applicable method, accounting for the partial volume effect, to automatically quantify myocardial infarction from delayed contrast material-enhanced magnetic resonance images. Pixels were weighted according to signal intensity to calculate infarct fraction for each pixel. Mean bias +/- variability (or standard deviation), expressed as percentage left ventricular myocardium (%LVM), were -0.3 +/- 1.3 (animals), -1.2 +/- 1.7 (phantoms), and 0.3... (More)
Ethics committees approved human and animal study components; informed written consent was provided (prospective human study [20 men; mean age, 62 years]) or waived (retrospective human study [16 men, four women; mean age, 59 years]). The purpose of this study was to prospectively evaluate a clinically applicable method, accounting for the partial volume effect, to automatically quantify myocardial infarction from delayed contrast material-enhanced magnetic resonance images. Pixels were weighted according to signal intensity to calculate infarct fraction for each pixel. Mean bias +/- variability (or standard deviation), expressed as percentage left ventricular myocardium (%LVM), were -0.3 +/- 1.3 (animals), -1.2 +/- 1.7 (phantoms), and 0.3 +/- 2.7 (patients), respectively. Algorithm had lower variability than dichotomous approach (2.7 vs 7.7 %LVM, P < .01) and did not differ from interobserver variability for bias (P = .31) or variability (P = .38). The weighted approach provides automatic quantification of myocardial infarction with higher accuracy and lower variability than a dichotomous algorithm. (Less)
Please use this url to cite or link to this publication:
author
; ; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Three-Dimensional/methods* Magnetic Resonance Imaging/instrumentation Magnetic Resonance Imaging/methods* Male Middle Aged Myocardial Infarction/complications Myocardial Infarction/diagnosis* Pattern Recognition, Algorithms Animals Artificial Intelligence* Female Humans Image Enhancement/methods Image Interpretation, Imaging Reproducibility of Results Sensitivity and Specificity Swine Ventricular Dysfunction, Automated/methods* Phantoms, Computer-Assisted/methods* Imaging, Left/diagnosis* Ventricular Dysfunction, Left/etiology
in
Radiology
volume
246
issue
2
pages
581 - 588
publisher
Radiological Society of North America
external identifiers
  • pmid:18055873
  • wos:000252796300029
  • scopus:39549100798
ISSN
1527-1315
DOI
10.1148/radiol.2461062164
language
English
LU publication?
yes
id
8cf383a5-bc03-4aa3-b50d-5133214d6f32 (old id 1035684)
alternative location
http://www.ncbi.nlm.nih.gov/pubmed/18055873?dopt=Abstract
date added to LUP
2016-04-01 11:58:24
date last changed
2022-03-20 21:39:12
@article{8cf383a5-bc03-4aa3-b50d-5133214d6f32,
  abstract     = {{Ethics committees approved human and animal study components; informed written consent was provided (prospective human study [20 men; mean age, 62 years]) or waived (retrospective human study [16 men, four women; mean age, 59 years]). The purpose of this study was to prospectively evaluate a clinically applicable method, accounting for the partial volume effect, to automatically quantify myocardial infarction from delayed contrast material-enhanced magnetic resonance images. Pixels were weighted according to signal intensity to calculate infarct fraction for each pixel. Mean bias +/- variability (or standard deviation), expressed as percentage left ventricular myocardium (%LVM), were -0.3 +/- 1.3 (animals), -1.2 +/- 1.7 (phantoms), and 0.3 +/- 2.7 (patients), respectively. Algorithm had lower variability than dichotomous approach (2.7 vs 7.7 %LVM, P &lt; .01) and did not differ from interobserver variability for bias (P = .31) or variability (P = .38). The weighted approach provides automatic quantification of myocardial infarction with higher accuracy and lower variability than a dichotomous algorithm.}},
  author       = {{Heiberg, Einar and Ugander, Martin and Engblom, Henrik and Götberg, Matthias and Olivecrona, Göran and Erlinge, David and Arheden, Håkan}},
  issn         = {{1527-1315}},
  keywords     = {{Three-Dimensional/methods* Magnetic Resonance Imaging/instrumentation Magnetic Resonance Imaging/methods* Male Middle Aged Myocardial Infarction/complications Myocardial Infarction/diagnosis* Pattern Recognition; Algorithms Animals Artificial Intelligence* Female Humans Image Enhancement/methods Image Interpretation; Imaging Reproducibility of Results Sensitivity and Specificity Swine Ventricular Dysfunction; Automated/methods* Phantoms; Computer-Assisted/methods* Imaging; Left/diagnosis* Ventricular Dysfunction; Left/etiology}},
  language     = {{eng}},
  number       = {{2}},
  pages        = {{581--588}},
  publisher    = {{Radiological Society of North America}},
  series       = {{Radiology}},
  title        = {{Automated quantification of myocardial infarction from MR images by accounting for partial volume effects: animal, phantom, and human study.}},
  url          = {{http://dx.doi.org/10.1148/radiol.2461062164}},
  doi          = {{10.1148/radiol.2461062164}},
  volume       = {{246}},
  year         = {{2008}},
}