Image Quality and Reliability of a Novel Dark-Blood Late Gadolinium Enhancement Sequence in Ischemic Cardiomyopathy

2019 ◽  
Vol 35 (5) ◽  
pp. 326-333
Author(s):  
Giuseppe Muscogiuri ◽  
Marco Gatti ◽  
Serena Dell’Aversana ◽  
Andrea I. Guaricci ◽  
Marco Guglielmo ◽  
...  
Keyword(s):  
Late Gadolinium Enhancement ◽  
Image Quality ◽  
Ischemic Cardiomyopathy ◽  
Gadolinium Enhancement ◽  
Dark Blood ◽  
Quality And Reliability

scholarly journals Implications of multiple late gadolinium enhancement lesions on the frequency of left ventricular reverse remodeling and prognosis in patients with non‐ischemic cardiomyopathy

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Shingo Ota ◽  
Makoto Orii ◽  
Tsuyoshi Nishiguchi ◽  
Mao Yokoyama ◽  
Ryoko Matsushita ◽  
...  
Keyword(s):  
Heart Failure ◽  
Late Gadolinium Enhancement ◽  
Ischemic Cardiomyopathy ◽  
Left Ventricular ◽  
Reverse Remodeling ◽  
Cardiac Events ◽  
Gadolinium Enhancement ◽  
Systolic Volume ◽  
Linear Pattern ◽  
Multiple Lesions

Abstract Background Non-ischemic cardiomyopathy (NICM) is a heterogeneous disease, and its prognosis varies. Although late gadolinium enhancement (LGE)-cardiovascular magnetic resonance (CMR) demonstrates a linear pattern in the mid-wall of the septum or multiple LGE lesions in patients with NICM, the therapeutic response and prognosis of multiple LGE lesions have not been elucidated. This study aimed to investigate the frequency of left ventricular (LV) reverse remodeling (LVRR) and prognosis in patients with NICM who have multiple LGE lesions. Methods This single-center retrospective study included 101 consecutive patients with NICM who were divided into 3 groups according to LGE-CMR results: patients without LGE (no LGE group = 48 patients), patients with a typical mid-wall LGE pattern (n = 29 patients), and patients with multiple LGE lesions (n = 24 patients). LVRR was defined as an increase in LV ejection fraction (LVEF) ≥ 10 % and a final value of LVEF > 35 %, which was accompanied by a decrease in LV end-systolic volume ≥ 15 % at 12-month follow-up using echocardiography. The frequency of composite cardiac events, defined as sudden cardiac death (SCD), aborted SCD (non-fatal ventricular fibrillation, sustained ventricular tachycardia, or adequate implantable cardioverter-defibrillator therapies), and heart failure death or hospitalization for worsening heart failure, were summarized and compared between the groups. Results Among the 3 groups, the frequency of LVRR was significantly lower in the multiple lesions group than in the no LGE and mid-wall groups (no LGE vs. mid-wall vs. multiple lesions: 49 % vs. 52 % vs. 19 %, p = 0.03). There were 24 composite cardiac events among the patients: 2 in patients without LGE (hospitalization for worsening heart failure; 2), 7 in patients of the mid-wall group (SCD; 1, aborted SCD; 1 and hospitalization for worsening heart failure; 5), and 15 in patients of the multiple lesions group (SCD; 1, aborted SCD; 8 and hospitalization for worsening heart failure; 6). The multiple LGE lesions was an independent predictor of composite cardiac events (hazard ratio: 11.40 [95 % confidence intervals: 1.49−92.01], p = 0.020). Conclusions Patients with multiple LGE lesions have a higher risk of cardiac events and poorer LVRR. The LGE pattern may be useful for an improved risk stratification in patients with NICM.

scholarly journals Novel dark-blood versus conventional bright-blood late gadolinium enhancement CMR: A pilot study comparing impact on myocardial ischaemic burden

2021 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
R Franks ◽  
R Holtackers ◽  
M Nazir ◽  
S Plein ◽  
A Chiribiri
Keyword(s):  
Late Gadolinium Enhancement ◽  
Perfusion Imaging ◽  
Stress Perfusion ◽  
Strong Positive Correlation ◽  
Gadolinium Enhancement ◽  
Dark Blood ◽  
Scar Burden ◽  
Perfusion Defects ◽  
Bright Blood ◽  
Ischaemic Burden

Abstract Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): British Heart Foundation Background In patients with coronary artery disease (CAD), increasing myocardial ischaemic burden (MIB) is a strong predictor of adverse events. When measured by cardiovascular magnetic resonance (CMR), a MIB ≥12.5% is considered significant and often used as a threshold to guide revascularisation. Ischaemic scar can cause stress perfusion defects which do not represent ischaemia and should be excluded from the MIB calculation. Conventional bright-blood late gadolinium enhancement (LGE) is able to identify ischaemic scar but can suffer from poor scar-to-blood contrast, making accurate assessment of scar volume difficult. Dark-blood LGE methods increase scar-to-blood contrast and improve scar conspicuity which may impact the calculated scar burden and consequently the estimation of MIB when read in conjunction with perfusion images. Purpose To evaluate the impact of dark-blood LGE versus conventional bright-blood LGE on the estimation of MIB in patients with CAD. Methods 37 patients with suspected or known CAD who had evidence of CMR stress perfusion defects and ischaemic scar on LGE imaging were recruited. Patients underwent adenosine stress perfusion imaging followed by dark-blood LGE then conventional bright-blood LGE imaging at 3T. For dark-blood LGE, phase sensitive inversion recovery imaging with a shorter inversion time to null the LV blood-pool was used without any additional magnetization preparation. For each patient, three short-axis LGE slices were selected to match the three perfusion slice locations. Images were anonymised and analysed in random order. Ischaemic scar burden (ISB) was quantified for both LGE methods using a threshold >5 standard deviations above remote myocardium. Perfusion defect burden (PDB) was quantified by manual contouring of perfusion defects. MIB was calculated by subtracting the ISB from the PDB. Results MIB calculated using dark-blood LGE was 19% less compared to bright-blood LGE (15.7 ± 15.2% vs 19.4 ± 15.2%, p < 0.001). There was a strong positive correlation between the two LGE methods (rs = 0.960, p < 0.001, Figure 1A). Bland-Altman analysis revealed a significant fixed bias (mean bias = -3.6%, bias 95% CI: -2.6 to -4.7%, 95% limits of agreement: -9.8 to 2.5%) with no proportional bias (Figure 1B). MIB was calculated ≥12.5% and <12.5% by both LGE methods in 19 (51%) and 12 (32%) patients respectively. In 6 patients (16%), MIB was ≥12.5% using bright-blood LGE and <12.5% using dark-blood LGE (Figure 1A – orange data points). Overall, when used to classify MIB as <12.5% or ≥12.5%, there was only substantial agreement between the two LGE methods (κ=0.67, 95% CI: 0.45 to 0.90). Conclusions The use of dark-blood LGE in conjunction with perfusion imaging results in a lower estimate of MIB compared to conventional bright-blood LGE. This can cause disagreement around the threshold of clinically significant ischaemia which could impact clinical management in patients being considered for coronary revascularisation. Abstract Figure. Linear regression with corresponding B&A

scholarly journals The impact of dark-blood versus conventional bright-blood late gadolinium enhancement on the myocardial ischemic burden

2021 ◽  
pp. 109728
Author(s):  
Russell Franks ◽  
Robert J. Holtackers ◽  
Muhummad Sohaib Nazir ◽  
Brian Clapp ◽  
Joachim E. Wildberger ◽  
...  
Keyword(s):  
Late Gadolinium Enhancement ◽  
Gadolinium Enhancement ◽  
Dark Blood ◽  
The Impact ◽  
Bright Blood

The impact of dark-blood versus conventional bright-blood late gadolinium enhancement the on myocardial ischemic burden

2021 ◽  
pp. 109947
Author(s):  
Russell Franks ◽  
Mr. Robert J. Holtackers ◽  
Ebraham Alskaf ◽  
Muhummad Sohaib Nazir ◽  
Brian Clapp ◽  
...  
Keyword(s):  
Late Gadolinium Enhancement ◽  
Gadolinium Enhancement ◽  
Dark Blood ◽  
The Impact ◽  
Bright Blood

scholarly journals Improvement of late gadolinium enhancement image quality using a deep learning–based reconstruction algorithm and its influence on myocardial scar quantification

2020 ◽  
Author(s):  
Nikki van der Velde ◽  
H. Carlijne Hassing ◽  
Brendan J. Bakker ◽  
Piotr A. Wielopolski ◽  
R. Marc Lebel ◽  
...  
Keyword(s):  
Deep Learning ◽  
Late Gadolinium Enhancement ◽  
Image Quality ◽  
Noise Reduction ◽  
Reconstruction Algorithm ◽  
Remote Myocardium ◽  
Full Width ◽  
Half Maximum ◽  
Gadolinium Enhancement ◽  
Scar Size

Abstract Objectives The aim of this study was to assess the effect of a deep learning (DL)–based reconstruction algorithm on late gadolinium enhancement (LGE) image quality and to evaluate its influence on scar quantification. Methods Sixty patients (46 ± 17 years, 50% male) with suspected or known cardiomyopathy underwent CMR. Short-axis LGE images were reconstructed using the conventional reconstruction and a DL network (DLRecon) with tunable noise reduction (NR) levels from 0 to 100%. Image quality of standard LGE images and DLRecon images with 75% NR was scored using a 5-point scale (poor to excellent). In 30 patients with LGE, scar size was quantified using thresholding techniques with different standard deviations (SD) above remote myocardium, and using full width at half maximum (FWHM) technique in images with varying NR levels. Results DLRecon images were of higher quality than standard LGE images (subjective quality score 3.3 ± 0.5 vs. 3.6 ± 0.7, p < 0.001). Scar size increased with increasing NR levels using the SD methods. With 100% NR level, scar size increased 36%, 87%, and 138% using 2SD, 4SD, and 6SD quantification method, respectively, compared to standard LGE images (all p values < 0.001). However, with the FWHM method, no differences in scar size were found (p = 0.06). Conclusions LGE image quality improved significantly using a DL-based reconstruction algorithm. However, this algorithm has an important impact on scar quantification depending on which quantification technique is used. The FWHM method is preferred because of its independency of NR. Clinicians should be aware of this impact on scar quantification, as DL-based reconstruction algorithms are being used. Key Points • The image quality based on (subjective) visual assessment and image sharpness of late gadolinium enhancement images improved significantly using a deep learning–based reconstruction algorithm that aims to reconstruct high signal-to-noise images using a denoising technique. • Special care should be taken when scar size is quantified using thresholding techniques with different standard deviations above remote myocardium because of the large impact of these advanced image enhancement algorithms. • The full width at half maximum method is recommended to quantify scar size when deep learning algorithms based on noise reduction are used, as this method is the least sensitive to the level of noise and showed the best agreement with visual late gadolinium enhancement assessment.

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