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- Atar, Dan, et al.
(författare)
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Rationale and Design of the 'MITOCARE' Study: A Phase II, Multicenter, Randomized, Double-Blind, Placebo-Controlled Study to Assess the Safety and Efficacy of TRO40303 for the Reduction of Reperfusion Injury in Patients Undergoing Percutaneous Coronary Intervention for Acute Myocardial Infarction
- 2012
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Ingår i: Cardiology. - : S. Karger AG. - 1421-9751 .- 0008-6312. ; 123:4, s. 201-207
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Tidskriftsartikel (refereegranskat)abstract
- Treatment of acute ST-elevation myocardial infarction (STEMI) by reperfusion using percutaneous coronary intervention (PCI) or thrombolysis has provided clinical benefits; however, it also induces considerable cell death. This process is called reperfusion injury. The continuing high rates of mortality and heart failure after acute myocardial infarction (AMI) emphasize the need for improved strategies to limit reperfusion injury and improve clinical outcomes. The objective of this study is to assess safety and efficacy of TRO40303 in limiting reperfusion injury in patients treated for STEMI. TRO40303 targets the mitochondrial permeability transition pore, a promising target for the prevention of reperfusion injury. This multicenter, double-blind study will randomize patients with STEMI to TRO40303 or placebo administered just before balloon inflation or thromboaspiration during PCI. The primary outcome measure will be reduction in infarct size (assessed as plasma creatine kinase and troponin I area under the curve over 3 days). The main secondary endpoint will be infarct size normalized to the myocardium at risk (expressed by the myocardial salvage index assessed by cardiac magnetic resonance). The study is being financed under an EU-FP7 grant and conducted under the auspices of the MITOCARE research consortium, which includes experts from clinical and basic research centers, as well as commercial enterprises, throughout Europe. Results from this study will contribute to a better understanding of the complex pathophysiology underlying myocardial injury after STEMI. The present paper describes the rationale, design and the methods of the trial. Copyright (c) 2012 S. Karger AG, Basel
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- Engblom, Henrik, et al.
(författare)
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A new automatic algorithm for quantification of myocardial infarction imaged by late gadolinium enhancement cardiovascular magnetic resonance : Experimental validation and comparison to expert delineations in multi-center, multi-vendor patient data
- 2016
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Ingår i: Journal of Cardiovascular Magnetic Resonance. - : Springer Science and Business Media LLC. - 1097-6647 .- 1532-429X. ; 18:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) using magnitude inversion recovery (IR) or phase sensitive inversion recovery (PSIR) has become clinical standard for assessment of myocardial infarction (MI). However, there is no clinical standard for quantification of MI even though multiple methods have been proposed. Simple thresholds have yielded varying results and advanced algorithms have only been validated in single center studies. Therefore, the aim of this study was to develop an automatic algorithm for MI quantification in IR and PSIR LGE images and to validate the new algorithm experimentally and compare it to expert delineations in multi-center, multi-vendor patient data. Methods: The new automatic algorithm, EWA (Expectation Maximization, weighted intensity, a priori information), was implemented using an intensity threshold by Expectation Maximization (EM) and a weighted summation to account for partial volume effects. The EWA algorithm was validated in-vivo against triphenyltetrazolium-chloride (TTC) staining (n = 7 pigs with paired IR and PSIR images) and against ex-vivo high resolution T1-weighted images (n = 23 IR and n = 13 PSIR images). The EWA algorithm was also compared to expert delineation in 124 patients from multi-center, multi-vendor clinical trials 2-6 days following first time ST-elevation myocardial infarction (STEMI) treated with percutaneous coronary intervention (PCI) (n = 124 IR and n = 49 PSIR images). Results: Infarct size by the EWA algorithm in vivo in pigs showed a bias to ex-vivo TTC of -1 ± 4%LVM (R = 0.84) in IR and -2 ± 3%LVM (R = 0.92) in PSIR images and a bias to ex-vivo T1-weighted images of 0 ± 4%LVM (R = 0.94) in IR and 0 ± 5%LVM (R = 0.79) in PSIR images. In multi-center patient studies, infarct size by the EWA algorithm showed a bias to expert delineation of -2 ± 6 %LVM (R = 0.81) in IR images (n = 124) and 0 ± 5%LVM (R = 0.89) in PSIR images (n = 49). Conclusions: The EWA algorithm was validated experimentally and in patient data with a low bias in both IR and PSIR LGE images. Thus, the use of EM and a weighted intensity as in the EWA algorithm, may serve as a clinical standard for the quantification of myocardial infarction in LGE CMR images. Clinical trial registration: CHILL-MI: NCT01379261. MITOCARE: NCT01374321.
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| 5. |
- Engblom, Henrik, et al.
(författare)
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Sample Size in Clinical Cardioprotection Trials Using Myocardial Salvage Index, Infarct Size, or Biochemical Markers as Endpoint.
- 2016
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Ingår i: Journal of the American Heart Association. - 2047-9980. ; 5:3, s. 002708-002708
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Tidskriftsartikel (refereegranskat)abstract
- Cardiac magnetic resonance (CMR) can quantify myocardial infarct (MI) size and myocardium at risk (MaR), enabling assessment of myocardial salvage index (MSI). We assessed how MSI impacts the number of patients needed to reach statistical power in relation to MI size alone and levels of biochemical markers in clinical cardioprotection trials and how scan day affect sample size.
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| 6. |
- Gonzales, Ricardo A., et al.
(författare)
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MVnet : automated time-resolved tracking of the mitral valve plane in CMR long-axis cine images with residual neural networks: a multi-center, multi-vendor study
- 2021
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Ingår i: Journal of Cardiovascular Magnetic Resonance. - : Springer Science and Business Media LLC. - 1097-6647 .- 1532-429X. ; 23, s. 1-15
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Tidskriftsartikel (refereegranskat)abstract
- Background: Mitral annular plane systolic excursion (MAPSE) and left ventricular (LV) early diastolic velocity (e’) are key metrics of systolic and diastolic function, but not often measured by cardiovascular magnetic resonance (CMR). Its derivation is possible with manual, precise annotation of the mitral valve (MV) insertion points along the cardiac cycle in both two and four-chamber long-axis cines, but this process is highly time-consuming, laborious, and prone to errors. A fully automated, consistent, fast, and accurate method for MV plane tracking is lacking. In this study, we propose MVnet, a deep learning approach for MV point localization and tracking capable of deriving such clinical metrics comparable to human expert-level performance, and validated it in a multi-vendor, multi-center clinical population. Methods: The proposed pipeline first performs a coarse MV point annotation in a given cine accurately enough to apply an automated linear transformation task, which standardizes the size, cropping, resolution, and heart orientation, and second, tracks the MV points with high accuracy. The model was trained and evaluated on 38,854 cine images from 703 patients with diverse cardiovascular conditions, scanned on equipment from 3 main vendors, 16 centers, and 7 countries, and manually annotated by 10 observers. Agreement was assessed by the intra-class correlation coefficient (ICC) for both clinical metrics and by the distance error in the MV plane displacement. For inter-observer variability analysis, an additional pair of observers performed manual annotations in a randomly chosen set of 50 patients. Results: MVnet achieved a fast segmentation (<1 s/cine) with excellent ICCs of 0.94 (MAPSE) and 0.93 (LV e’) and a MV plane tracking error of −0.10 ± 0.97 mm. In a similar manner, the inter-observer variability analysis yielded ICCs of 0.95 and 0.89 and a tracking error of −0.15 ± 1.18 mm, respectively. Conclusion: A dual-stage deep learning approach for automated annotation of MV points for systolic and diastolic evaluation in CMR long-axis cine images was developed. The method is able to carefully track these points with high accuracy and in a timely manner. This will improve the feasibility of CMR methods which rely on valve tracking and increase their utility in a clinical setting.
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| 7. |
- Heiberg, Einar, et al.
(författare)
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Infarct quantification with cardiovascular magnetic resonance using "standard deviation from remote" is unreliable : validation in multi-centre multi-vendor data
- 2022
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Ingår i: Journal of Cardiovascular Magnetic Resonance. - : Springer Science and Business Media LLC. - 1097-6647 .- 1532-429X. ; 24:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: The objective of the study was to investigate variability and agreement of the commonly used image processing method “n-SD from remote” and in particular for quantifying myocardial infarction by late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR). LGE-CMR in tandem with the analysis method “n-SD from remote” represents the current reference standard for infarct quantification. This analytic method utilizes regions of interest (ROIs) and defines infarct as the tissue with a set number of standard deviations (SD) above the signal intensity of remote nulled myocardium. There is no consensus on what the set number of SD is supposed to be. Little is known about how size and location of ROIs and underlying signal properties in the LGE images affect results. Furthermore, the method is frequently used elsewhere in medical imaging often without careful validation. Therefore, the usage of the “n-SD” method warrants a thorough validation. Methods: Data from 214 patients from two multi-center cardioprotection trials were included. Infarct size from different remote ROI positions, ROI size, and number of standard deviations (“n-SD”) were compared with reference core lab delineations. Results: Variability in infarct size caused by varying ROI position, ROI size, and “n-SD” was 47%, 48%, and 40%, respectively. The agreement between the “n-SD from remote” method and the reference infarct size by core lab delineations was low. Optimal “n-SD” threshold computed on a slice-by-slice basis showed high variability, n = 5.3 ± 2.2. Conclusion: The “n-SD from remote” method is unreliable for infarct quantification due to high variability which depends on different placement and size of remote ROI, number “n-SD”, and image signal properties related to the CMR-scanner and sequence used. Therefore, the “n-SD from remote” method should not be used, instead methods validated against an independent standard are recommended.
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