PURPOSE: Intra-plaque hemorrhage (IPH) is associated with plaque instability. Therefore, the presence and volume of IPH in carotid arteries may be relevant in predicting the progression of atherosclerotic disease and the occurrence of clinical events. The aim of our work was to develop and evaluate a method for semi-automatic IPH segmentation in T1-weighted (T1w)-magnetic resonance imaging (MRI). MATERIAL AND METHODS: IPH segmentation is performed by a regional level set method that models the intensity of the IPH and the background in T1w-MRI to be smoothly varying. The method only requires minimal user interaction, i.e., one or more mouse clicks inside the hemorrhage serve as initialization. The parameters of the method are optimized using a leave-one-out strategy by maximizing the Dice similarity coefficient (DSC) between manual and semi-automatic segmentations. We evaluated the IPH segmentation method on 22 carotid arteries; 10 of which were annotated by two observers and 12 were scanned twice within a 2 week period. RESULTS: We obtained a DSC of 0.52 between the manual and level set segmentations on all 22 carotids. The inter-observer DSC on 10 arteries is 0.57, which is comparable to the DSC between the method and the manual segmentation (0.55). The correlation between the IPH volumes extracted from the level set segmentation and the manual segmentation is 0.88, which is close to the inter-observer volume correlation of 0.92. The reproducibility after rescanning 12 carotids yield an IPH volume correlation of 0.97. The robustness with respect to the initialization by manually clicking two sets of seed points in these 12 carotid artery pairs yields a volume correlation of 0.99. CONCLUSION: Semi-automatic segmentation and quantification of IPHs are feasible with an accuracy in the range of the inter-observer variability. The method has excellent reproducibility with respect to rescanning and manual initialization.
PURPOSE:Intra-plaque hemorrhage (IPH) is associated with plaque instability. Therefore, the presence and volume of IPH in carotid arteries may be relevant in predicting the progression of atherosclerotic disease and the occurrence of clinical events. The aim of our work was to develop and evaluate a method for semi-automatic IPH segmentation in T1-weighted (T1w)-magnetic resonance imaging (MRI). MATERIAL AND METHODS:IPH segmentation is performed by a regional level set method that models the intensity of the IPH and the background in T1w-MRI to be smoothly varying. The method only requires minimal user interaction, i.e., one or more mouse clicks inside the hemorrhage serve as initialization. The parameters of the method are optimized using a leave-one-out strategy by maximizing the Dice similarity coefficient (DSC) between manual and semi-automatic segmentations. We evaluated the IPH segmentation method on 22 carotid arteries; 10 of which were annotated by two observers and 12 were scanned twice within a 2 week period. RESULTS: We obtained a DSC of 0.52 between the manual and level set segmentations on all 22 carotids. The inter-observer DSC on 10 arteries is 0.57, which is comparable to the DSC between the method and the manual segmentation (0.55). The correlation between the IPH volumes extracted from the level set segmentation and the manual segmentation is 0.88, which is close to the inter-observer volume correlation of 0.92. The reproducibility after rescanning 12 carotids yield an IPH volume correlation of 0.97. The robustness with respect to the initialization by manually clicking two sets of seed points in these 12 carotid artery pairs yields a volume correlation of 0.99. CONCLUSION: Semi-automatic segmentation and quantification of IPHs are feasible with an accuracy in the range of the inter-observer variability. The method has excellent reproducibility with respect to rescanning and manual initialization.
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