Automated quantification of myocardial infarction from MR images by accounting for partial volume effects: animal, phantom, and human study.
(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:
https://lup.lub.lu.se/record/1035684
- author
- Heiberg, Einar
LU
; Ugander, Martin
LU
; Engblom, Henrik
LU
; Götberg, Matthias
LU
; Olivecrona, Göran
LU
; Erlinge, David
LU
and Arheden, Håkan LU
- organization
- publishing date
- 2008
- 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 < .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}}, }