Semi-automatic segmentation of myocardium at risk in T2-weighted cardiovascular magnetic resonance
(2012) In Journal of Cardiovascular Magnetic Resonance 14.- Abstract
- Background: T2-weighted cardiovascular magnetic resonance (CMR) has been shown to be a promising technique for determination of ischemic myocardium, referred to as myocardium at risk (MaR), after an acute coronary event. Quantification of MaR in T2-weighted CMR has been proposed to be performed by manual delineation or the threshold methods of two standard deviations from remote (2SD), full width half maximum intensity (FWHM) or Otsu. However, manual delineation is subjective and threshold methods have inherent limitations related to threshold definition and lack of a priori information about cardiac anatomy and physiology. Therefore, the aim of this study was to develop an automatic segmentation algorithm for quantification of MaR using... (More)
- Background: T2-weighted cardiovascular magnetic resonance (CMR) has been shown to be a promising technique for determination of ischemic myocardium, referred to as myocardium at risk (MaR), after an acute coronary event. Quantification of MaR in T2-weighted CMR has been proposed to be performed by manual delineation or the threshold methods of two standard deviations from remote (2SD), full width half maximum intensity (FWHM) or Otsu. However, manual delineation is subjective and threshold methods have inherent limitations related to threshold definition and lack of a priori information about cardiac anatomy and physiology. Therefore, the aim of this study was to develop an automatic segmentation algorithm for quantification of MaR using anatomical a priori information. Methods: Forty-seven patients with first-time acute ST-elevation myocardial infarction underwent T2-weighted CMR within 1 week after admission. Endocardial and epicardial borders of the left ventricle, as well as the hyper enhanced MaR regions were manually delineated by experienced observers and used as reference method. A new automatic segmentation algorithm, called Segment MaR, defines the MaR region as the continuous region most probable of being MaR, by estimating the intensities of normal myocardium and MaR with an expectation maximization algorithm and restricting the MaR region by an a priori model of the maximal extent for the user defined culprit artery. The segmentation by Segment MaR was compared against inter observer variability of manual delineation and the threshold methods of 2SD, FWHM and Otsu. Results: MaR was 32.9 +/- 10.9% of left ventricular mass (LVM) when assessed by the reference observer and 31.0 +/- 8.8% of LVM assessed by Segment MaR. The bias and correlation was, -1.9 +/- 6.4% of LVM, R = 0.81 (p < 0.001) for Segment MaR, -2.3 +/- 4.9%, R = 0.91 (p < 0.001) for inter observer variability of manual delineation, -7.7 +/- 11.4%, R = 0.38 (p = 0.008) for 2SD, -21.0 +/- 9.9%, R = 0.41 (p = 0.004) for FWHM, and 5.3 +/- 9.6%, R = 0.47 (p < 0.001) for Otsu. Conclusions: There is a good agreement between automatic Segment MaR and manually assessed MaR in T2-weighted CMR. Thus, the proposed algorithm seems to be a promising, objective method for standardized MaR quantification in T2-weighted CMR. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/2826861
- author
- Tufvesson, Jane LU ; Ubachs, Joey LU ; Engblom, Henrik LU ; Carlsson, Marcus LU ; Arheden, Håkan LU and Heiberg, Einar LU
- organization
- publishing date
- 2012
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Journal of Cardiovascular Magnetic Resonance
- volume
- 14
- publisher
- BioMed Central (BMC)
- external identifiers
-
- wos:000303860300001
- scopus:84865143393
- pmid:22293146
- ISSN
- 1097-6647
- DOI
- 10.1186/1532-429X-14-10
- language
- English
- LU publication?
- yes
- additional info
- The information about affiliations in this record was updated in December 2015. The record was previously connected to the following departments: Department of Clinical Physiology (Lund) (013013000), Numerical Analysis (011015004)
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- cd314040-b0c4-4c31-a426-db4265ae50e6 (old id 2826861)
- date added to LUP
- 2016-04-01 10:27:52
- date last changed
- 2022-01-25 23:26:21
@article{cd314040-b0c4-4c31-a426-db4265ae50e6, abstract = {{Background: T2-weighted cardiovascular magnetic resonance (CMR) has been shown to be a promising technique for determination of ischemic myocardium, referred to as myocardium at risk (MaR), after an acute coronary event. Quantification of MaR in T2-weighted CMR has been proposed to be performed by manual delineation or the threshold methods of two standard deviations from remote (2SD), full width half maximum intensity (FWHM) or Otsu. However, manual delineation is subjective and threshold methods have inherent limitations related to threshold definition and lack of a priori information about cardiac anatomy and physiology. Therefore, the aim of this study was to develop an automatic segmentation algorithm for quantification of MaR using anatomical a priori information. Methods: Forty-seven patients with first-time acute ST-elevation myocardial infarction underwent T2-weighted CMR within 1 week after admission. Endocardial and epicardial borders of the left ventricle, as well as the hyper enhanced MaR regions were manually delineated by experienced observers and used as reference method. A new automatic segmentation algorithm, called Segment MaR, defines the MaR region as the continuous region most probable of being MaR, by estimating the intensities of normal myocardium and MaR with an expectation maximization algorithm and restricting the MaR region by an a priori model of the maximal extent for the user defined culprit artery. The segmentation by Segment MaR was compared against inter observer variability of manual delineation and the threshold methods of 2SD, FWHM and Otsu. Results: MaR was 32.9 +/- 10.9% of left ventricular mass (LVM) when assessed by the reference observer and 31.0 +/- 8.8% of LVM assessed by Segment MaR. The bias and correlation was, -1.9 +/- 6.4% of LVM, R = 0.81 (p < 0.001) for Segment MaR, -2.3 +/- 4.9%, R = 0.91 (p < 0.001) for inter observer variability of manual delineation, -7.7 +/- 11.4%, R = 0.38 (p = 0.008) for 2SD, -21.0 +/- 9.9%, R = 0.41 (p = 0.004) for FWHM, and 5.3 +/- 9.6%, R = 0.47 (p < 0.001) for Otsu. Conclusions: There is a good agreement between automatic Segment MaR and manually assessed MaR in T2-weighted CMR. Thus, the proposed algorithm seems to be a promising, objective method for standardized MaR quantification in T2-weighted CMR.}}, author = {{Tufvesson, Jane and Ubachs, Joey and Engblom, Henrik and Carlsson, Marcus and Arheden, Håkan and Heiberg, Einar}}, issn = {{1097-6647}}, language = {{eng}}, publisher = {{BioMed Central (BMC)}}, series = {{Journal of Cardiovascular Magnetic Resonance}}, title = {{Semi-automatic segmentation of myocardium at risk in T2-weighted cardiovascular magnetic resonance}}, url = {{https://lup.lub.lu.se/search/files/1867682/3052964.pdf}}, doi = {{10.1186/1532-429X-14-10}}, volume = {{14}}, year = {{2012}}, }