Browsing by Author "Kooi, M. Eline"

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    Automated Segmentation of Thoracic Aortic Lumen and Vessel Wall on 3D Bright- and Black-Blood MRI using nnU-Net
    (2025) Cesario, Matteo; Littlewood, Simon J.; Nadel, James; Fletcher, Thomas J.; Fotaki, Anastasia; Castillo Passi, Carlos; Hajhosseiny, Reza; Pouliopoulos, Jim; Jabbour, Andrew; Olivero, Ruperto; Rodríguez Palomares, José; Kooi, M. Eline; Prieto Vásquez, Claudia; Botnar, René Michael
    BACKGROUND: Magnetic resonance angiography (MRA) is an important tool for aortic assessment in several cardiovascular diseases. Assessment of MRA images relies on manual segmentation; a time-intensive process that is subject to operator variability. We aimed to optimize and validate two deep-learning models for automatic segmentation of the aortic lumen and vessel wall in high-resolution ECG-triggered free-breathing respiratory motion-corrected 3D bright- and black-blood MRA images. METHODS: Manual segmentation, serving as the ground truth, was performed on 25 bright-blood and 15 black-blood 3D MRA image sets acquired with the iT2PrepIR-BOOST sequence (1.5T) in thoracic aortopathy patients. The training was performed with nnU-Net for bright-blood (lumen) and black-blood image sets (lumen and vessel wall). Training consisted of a 70:20:10% training: validation: testing split. Inference was run on datasets (single vendor) from different centres (UK, Spain, and Australia), sequences (iT2PrepIR-BOOST, T2 prepared CMRA, and TWIST MRA), acquired resolutions (from 0.9 mm 3 to 3 mm 3), and field strengths (0.55T, 1.5T, and 3T). Predictive measurements comprised Dice Similarity Coefficient (DSC), and Intersection over Union (IoU). Postprocessing (3D slicer) included centreline extraction, diameter measurement, and curved planar reformatting (CPR). RESULTS: The optimal configuration was the 3D U-Net. Bright blood segmentation at 1.5T on iT2PrepIR-BOOST datasets (1.3 and 1.8 mm 3) and 3D CMRA datasets (0.9 mm 3) resulted in DSC ≥ 0.96 and IoU ≥ 0.92. For bright-blood segmentation on 3D CMRA at 0.55T, the nnUNet achieved DSC and IoU scores of 0.93 and 0.88 at 1.5 mm³, and 0.68 and 0.52 at 3.0 mm³, respectively. DSC and IoU scores of 0.89 and 0.82 were obtained for CMRA image sets (1 mm 3) at 1.5T (Barcelona dataset). DSC and IoU score of the BRnnUNet model were 0.90 and 0.82 respectively for the contrast-enhanced dataset (TWIST MRA). Lumen segmentation on black blood 1.5T iT2PrepIR-BOOST image sets achieved DSC ≥ 0.95 and IoU ≥ 0.90, and vessel wall segmentation resulted in DSC ≥ 0.80 and IoU ≥ 0.67. Automated centreline tracking, diameter measurement and CPR were successfully implemented in all subjects. CONCLUSION: Automated aortic lumen and wall segmentation on 3D bright- and black-blood image sets demonstrated excellent agreement with ground truth. This technique demonstrates a fast and comprehensive assessment of aortic morphology with great potential for future clinical application in various cardiovascular diseases.
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    Late Gadolinium Enhancement Cardiac Magnetic Resonance Imaging: From Basic Concepts to Emerging Methods
    (2022) Holtackers, Robert J.; Emrich, Tilman; Botnar, René Michael; Kooi, M. Eline; Wildberger, Joachim E.; Kreitner, K.-F.
    Late gadolinium enhancement (LGE) is a widely used cardiac magnetic resonance imaging (MRI) technique to diagnose a broad range of ischemic and non-ischemic cardiomyopathies. Since its development and validation against histology already more than two decades ago, the clinical utility of LGE and its span of applications have increased considerably. Methods In this review we will present the basic concepts of LGE imaging and its diagnostic and prognostic value, elaborate on recent developments and emerging methods, and finally discuss future prospects. Results Continuous developments in 3D imaging methods, motion correction techniques, water/fat-separated imaging, dark-blood methods, and scar quantification improved the performance and further expanded the clinical utility of LGE imaging. Conclusion LGE imaging is the current noninvasive reference standard for the assessment of myocardial viability. Improvements in spatial resolution, scar-to-blood contrast, and water/fat-separated imaging further strengthened its position. Key Points: LGE MRI is the reference standard for the noninvasive assessment of myocardial viability LGE MRI is used to diagnose a broad range of non-ischemic cardiomyopathies in everyday clinical practice. Improvements in spatial resolution and scar-to-blood contrast further strengthened its position Continuous developments improve its performance and further expand its clinical utility Citation Format Holtackers RJ, Emrich T, Botnar RM etal. Late Gadolinium Enhancement Cardiac Magnetic Resonance Imaging: From Basic Concepts to Emerging Methods. Fortschr Röntgenstr 2022; DOI: 10.1055/a-1718-4355.
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    PET/MRI of atherosclerosis
    (2020) Aizaz, Mueez; Moonen, Rik P.M.; Pol, Jochem A.J. van der; Prieto Vásquez, Claudia; Botnar, René Michael; Kooi, M. Eline
    Myocardial infarction and stroke are the most prevalent global causes of death. Each year 15 million people worldwide die due to myocardial infarction or stroke. Rupture of a vulnerable atherosclerotic plaque is the main underlying cause of stroke and myocardial infarction. Key features of a vulnerable plaque are inflammation, a large lipid-rich necrotic core (LRNC) with a thin or ruptured overlying fibrous cap, and intraplaque hemorrhage (IPH). Noninvasive imaging of these features could have a role in risk stratification of myocardial infarction and stroke and can potentially be utilized for treatment guidance and monitoring. The recent development of hybrid PET/MRI combining the superior soft tissue contrast of MRI with the opportunity to visualize specific plaque features using various radioactive tracers, paves the way for comprehensive plaque imaging. In this review, the use of hybrid PET/MRI for atherosclerotic plaque imaging in carotid and coronary arteries is discussed. The pros and cons of different hybrid PET/MRI systems arc reviewed. The challenges in the development of PET/MRI and potential solutions are described. An overview of PET and MRI acquisition techniques for imaging of atherosclerosis including motion correction is provided, followed by a summary of vessel wall imaging PET/MRI studies in patients with carotid and coronary artery disease. Finally, the future of imaging of atherosclerosis with PET/MRI is discussed.