Late Gadolinium Enhancement MRI Research Articles

Imaging of Cardiac Fibrosis: An Update, From the AJR Special Series on Imaging of Fibrosis.

Myocardial fibrosis (MF) is defined as excessive production and deposition of extra-cellular matrix (ECM) proteins that result in pathologic myocardial remodeling. Three types of MF have been identified: replacement fibrosis from tissue necrosis, reactive fibrosis from myocardial stress, and infiltrative interstitial fibrosis from progressive deposition of nondegradable material such as amyloid. Although echocardiography, nuclear medicine, and CT play important roles in the assessment of MF, MRI is pivotal in the evaluation of MF, with the late gadolinium enhancement (LGE) technique used as a primary end point. The LGE technique focuses on the pattern and distribution of gadolinium accumulation in the myocardium and assists in the diagnosis and establishment of the cause of both ischemic and nonischemic cardiomyopathy. LGE MRI also aids prognostication and risk stratification. In addition, LGE MRI is used to guide the management of patients considered for ablation for arrhythmias. Parametric mapping techniques, including T1 mapping and extracellular volume measurement, allow detection and quantification of diffuse fibrosis, which may not be detected by LGE MRI. These techniques also allow monitoring of disease progression and therapy response. This review provides an update on the imaging of MF, including prognostication and risk stratification tools, electrophysiologic considerations, and disease monitoring.

Usformer: A small network for left atrium segmentation of 3D LGE MRI

Left atrial (LA) fibrosis plays a vital role as a mediator in the progression of atrial fibrillation. 3D late gadolinium-enhancement (LGE) MRI has been proven effective in identifying LA fibrosis. Image analysis of 3D LA LGE involves manual segmentation of the LA wall, which is both lengthy and challenging. Automated segmentation poses challenges owing to the diverse intensities in data from various vendors, the limited contrast between LA and surrounding tissues, and the intricate anatomical structures of the LA. Current approaches relying on 3D networks are computationally intensive since 3D LGE MRIs and the networks are large. Regarding this issue, most researchers came up with two-stage methods: initially identifying the LA center using a scaled-down version of the MRIs and subsequently cropping the full-resolution MRIs around the LA center for final segmentation. We propose a lightweight transformer-based 3D architecture, Usformer, designed to precisely segment LA volume in a single stage, eliminating error propagation associated with suboptimal two-stage training. The transposed attention facilitates capturing the global context in large 3D volumes without significant computation requirements. Usformer outperforms the state-of-the-art supervised learning methods in terms of accuracy and speed. First, with the smallest Hausdorff Distance (HD) and Average Symmetric Surface Distance (ASSD), it achieved a dice score of 93.1% and 92.0% in the 2018 Atrial Segmentation Challenge and our local institutional dataset, respectively. Second, the number of parameters and computation complexity are largely reduced by 2.8x and 3.8x, respectively. Moreover, Usformer does not require a large dataset. When only 16 labeled MRI scans are used for training, Usformer achieves a 92.1% dice score in the challenge dataset. The proposed Usformer delineates the boundaries of the LA wall relatively accurately, which may assist in the clinical translation of LA LGE for planning catheter ablation of atrial fibrillation.

Oxidation–reduction imaging of myoglobin reveals two-phase oxidation in the reperfused myocardium

Myocardial infarction (MI) is a serious acute cardiovascular syndrome that causes myocardial injury due to blood flow obstruction to a specific myocardial area. Under ischemic–reperfusion settings, a burst of reactive oxygen species is generated, leading to redox imbalance that could be attributed to several molecules, including myoglobin. Myoglobin is dynamic and exhibits various oxidation–reduction states that have been an early subject of attention in the food industry, specifically for meat consumers. However, rarely if ever have the myoglobin optical properties been used to measure the severity of MI. In the current study, we develop a novel imaging pipeline that integrates tissue clearing, confocal and light sheet fluorescence microscopy, combined with imaging analysis, and processing tools to investigate and characterize the oxidation–reduction states of myoglobin in the ischemic area of the cleared myocardium post-MI. Using spectral imaging, we have characterized the endogenous fluorescence of the myocardium and demonstrated that it is partly composed by fluorescence of myoglobin. Under ischemia–reperfusion experimental settings, we report that the infarcted myocardium spectral signature is similar to that of oxidized myoglobin signal that peaks 3 h post-reperfusion and decreases with cardioprotection. The infarct size assessed by oxidation–reduction imaging at 3 h post-reperfusion was correlated to the one estimated with late gadolinium enhancement MRI at 24 h post-reperfusion. In conclusion, this original work suggests that the redox state of myoglobin can be used as a promising imaging biomarker for characterizing and estimating the size of the MI during early phases of reperfusion.

Ultrashort VIBE-Dixon versus Cine and late gadolinium enhancement MRI sequences for cardiac thrombus detection

PurposeTo determine the diagnostic accuracy of volumetric interpolated breath-hold examination sequences with fat suppression in Dixon technique (VIBE-Dixon) for cardiac thrombus detection. MethodFrom our clinical database, we retrospectively identified consecutive patients between 2014 and 2022 who had definite diagnosis or exclusion of cardiac thrombus confirmed by an independent adjudication committee, serving as the reference standard. All patients received 2D-Cine plus 2D-Late-Gadolinium-Enhancement (Cine + LGE) and VIBE-Dixon sequences. Two blinded readers assessed all images for the presence of cardiac thrombus. The diagnostic accuracy of Cine + LGE and VIBE-Dixon was determined and compared. ResultsAmong 141 MRI studies (116 male, mean age: 61 years) mean image examination time was 28.8 ± 3.1 s for VIBE-Dixon and 23.3 ± 2.5 min for Cine + LGE. Cardiac thrombus was present in 49 patients (prevalence: 35 %). For both readers sensitivity for thrombus detection was significantly higher in VIBE-Dixon compared with Cine + LGE (Reader 1: 96 % vs.73 %, Reader 2: 96 % vs. 78 %, p < 0.01 for both readers), whereas specificity did not differ significantly (Reader 1: 96 % vs. 98 %, Reader 2: 92 % vs. 93 %, p > 0.1). Overall diagnostic accuracy of VIBE-Dixon was higher than for Cine + LGE (95 % vs. 89 %, p = 0.02) and was non-inferior to the reference standard (Delta ≤ 5 % with probability > 95 %). ConclusionsBiplanar VIBE-Dixon sequences, acquired within a few seconds, provided a very high diagnostic accuracy for cardiac thrombus detection. They could be used as stand-alone sequences to rapidly screen for cardiac thrombus in patients not amenable to lengthy acquisition times.

Prediction of an impaired myocardial work using infarct size in acute myocardial infarction.

The relationship between myocardial infarct size (MIS) on late gadolinium-enhanced cardiac MRI (LGE MRI) and myocardial work (MW) indices assessed with MW echocardiography (MWE) has not been well characterized. This study aimed to determine an impaired MW using MIS in patients with acute myocardial infarction. Left ventricular (LV) two-dimensional speckle-tracking echocardiography, MWE, and LGE MRI were performed in 33 patients with ST-segment elevation myocardial infarction and in 30 age- and sex-comparable controls. LV global longitudinal strain (GLS), global work index (GWI), global constructive work (GCW), global wasted work (GWW), and global work efficiency (GWE) and MIS were acquired, respectively. MIS was negatively correlated with GWI (r = -0.60, P = 0.005), GCW (r =- 0.66, P = 0.002) and GWE (r = -0.71, P = 0.0004), but positively correlated with GLS (r = 0.68, P = 0.001). With the receiver operating characteristic curve, the cutoff value of MIS for the prediction of an impaired GLS was 16.5% [area under the curve (AUC) = 0.867)], an impaired GWI was 19.2% (AUC = 0.727), an impaired GCW was 19.2% (AUC = 0.725), an increased GWW was 15.8% (AUC = 0.656), an impaired GWE was 15.8% (AUC = 0.880). MIS is a strong predictor of impaired MW. Timely reduction of infarct size is essential to improve myocardial function.

Incorporation of view sharing and KWIC filtering into GRASP-Pro improves spatial resolution of single-shot, multi-TI, late gadolinium enhancement MRI.

While single-shot late gadolinium enhancement (LGE) is useful for imaging patients with arrhythmia and/or dyspnea, it produces low spatial resolution. One approach to improve spatial resolution is to accelerate data acquisition using compressed sensing (CS). Our previous work described a single-shot, multi-inversion time (TI) LGE pulse sequence using radial k-space sampling and CS, but over-regularization resulted in significant image blurring that muted the benefits of data acceleration. The purpose of the present study was to improve the spatial resolution of the single-shot, multi-TI LGE pulse sequence by incorporating view sharing (VS) and k-space weighted contrast (KWIC) filtering into a GRASP-Pro reconstruction. In 24 patients (mean age = 61 ± 16 years; 9/15 females/males), we compared the performance of our improved multi-TI LGE and standard multi-TI LGE, where clinical standard LGE was used as a reference. Two clinical raters independently graded multi-TI images and clinical LGE images visually on a five-point Likert scale (1, nondiagnostic; 3, clinically acceptable; 5, best) for three categories: the conspicuity of myocardium or scar, artifact, and noise. The summed visual score (SVS) was defined as the sum of the three scores. Myocardial scar volume was quantified using the full-width at half-maximum method. The SVS was not significantly different between clinical breath-holding LGE (median 13.5, IQR 1.3) and multi-TI LGE (median 12.5, IQR 1.6) (P = 0.068). The myocardial scar volumes measured from clinical standard LGE and multi-TI LGE were strongly correlated (coefficient of determination, R2 = 0.99) and in good agreement (mean difference = 0.11%, lower limit of the agreement = -2.13%, upper limit of the agreement = 2.34%). The inter-rater agreement in myocardial scar volume quantification was strong (intraclass correlation coefficient = 0.79). The incorporation of VS and KWIC into GRASP-Pro improved spatial resolution. Our improved 25-fold accelerated, single-shot LGE sequence produces clinically acceptable image quality, multi-TI reconstruction, and accurate myocardial scar volume quantification.

Synthetic multi-contrast late gadolinium enhancement imaging using post-contrast magnetic resonance fingerprinting.

Late gadolinium enhancement (LGE) MRI is the non-invasive reference standard for identifying myocardial scar and fibrosis but has limitations, including difficulty delineating subendocardial scar and operator dependence on image quality. The purpose of this work is to assess the feasibility of generating multi-contrast synthetic LGE images from post-contrast T1 and T2 maps acquired using magnetic resonance fingerprinting (MRF). Fifteen consecutive patients with a history of prior ischemic cardiomyopathy (12 men; mean age 63 13 years) were prospectively scanned at 1.5 T between Oct 2020 and May 2021 using conventional LGE and MRF after injection of gadolinium contrast. Three classes of synthetic LGE images were derived from MRF post-contrast T1 and T2 maps: bright-blood phase-sensitive inversion recovery (PSIR), black- and gray-blood T2 -prepared PSIR (T2 -PSIR), and a novel "tissue-optimized" image to enhance differentiation among scar, viable myocardium, and blood. Image quality was assessed on a 1-5 Likert scale by two cardiologists, and contrast was quantified as the mean absolute difference (MAD) in pixel intensities between two tissues, with different methods compared using Kruskal-Wallis with Bonferroni post hoc tests. Per-patient and per-segment scar detection rates were evaluated using conventional LGE images as reference. Image quality scores were highest for synthetic PSIR (4.0) and reference images (3.8), followed by synthetic tissue-optimized (3.3), gray-blood T2 -PSIR (3.0), and black-blood T2 -PSIR (2.6). Among synthetic images, PSIR yielded the highest myocardium/scar contrast (MAD = 0.42) but the lowest blood/scar contrast (MAD = 0.05), and vice versa for T2 -PSIR, while tissue-optimized images achieved a balance among all tissues (myocardium/scar MAD = 0.16, blood/scar MAD = 0.26, myocardium/blood MAD = 0.10). Based on reference mid-ventricular LGE scans, 13/15 patients had myocardial scar. The per-patient sensitivity/accuracy for synthetic images were the following: PSIR, 85/87%; black-blood T2 -PSIR, 62/53%; gray-blood T2 -PSIR, 100/93%; tissue optimized, 100/93%. Synthetic multi-contrast LGE images can be generated from post-contrast MRF data without additional scan time, with initial feasibility shown in ischemic cardiomyopathy patients.

Optimizing fibrosis detection: a comparison of electroanatomical mapping and late enhancement gadolinium magnetic resonance imaging.

Fibrotic atrial cardiomyopathy plays an important role in determining the outcome of ablation in patients with atrial fibrillation (AF). Two main methods are being used for the evaluation of fibrosis: voltage-based high-density (HD) electroanatomical mapping (EAM) and late gadolinium enhancement MRI (LGE-MRI). The comparability between both methods in detecting fibrosis has not been systematically investigated. LGE-MRIs of the left atrium (LA) were performed in 21 patients. LA-fibrosis was evaluated using a custom-designed software generating a 3D-model of the LA. HD-electroanatomical maps were recorded in each patient. After processing the maps and the MRI models by excluding the mitral valve, pulmonary veins, and the left atrial appendage, the LGE areas were measured and compared to the low voltage areas (LVA) in the HD maps using three different cutoff values of 0.5 mV, 0.7 mV, and 1.0 mV. The analysis revealed significant differences between EAM and LGE-MRI in assessing LA-fibrosis at 0.5-mV (for anterior and posterior walls) and 1.0-mV cutoffs (for anterior and posterior wall and septum). However, no significant differences were found between EAM and LGE-MRI when using a 0.7-mV cutoff for all the investigated areas. A voltage cutoff of 0.7 mV provided the best correlation between EAM and LGE MRI for detecting left atrial fibrosis. It supports the idea that a 0.5-mV cutoff may underestimate fibrosis, as areas with local signal voltages between 0.6 and 0.8 mV could also show LGE on MRI. Further research is needed to determine the ideal voltage cutoff for detecting left atrial fibrosis.

Impact of late gadolinium-enhanced cardiac MRI on arrhythmic and mortality outcomes in nonischemic dilated cardiomyopathy: updated systematic review and meta-analysis

Risk stratification based mainly on the impairment of left ventricular ejection fraction has limited performance in patients with nonischemic dilated cardiomyopathy (NIDCM). Evidence is rapidly growing for the impact of myocardial scar identified by late gadolinium enhancement (LGE) cardiac magnetic resonance imaging (CMR) on cardiovascular events. We aim to assess the prognostic value of LGE on long-term arrhythmic and mortality outcomes in patients with NIDCM. PubMed, Scopus, and Cochrane databases were searched from inception to January 21, 2022. Studies that included disease-specific subpopulations of NIDCM were excluded. Data were independently extracted and combined via random-effects meta-analysis using a generic inverse-variance strategy. Data from 60 studies comprising 15,217 patients were analyzed with a 3-year median follow-up. The presence of LGE was associated with major ventricular arrhythmic events (pooled OR: 3.99; 95% CI 3.08, 5.16), all-cause mortality (pooled OR: 2.14; 95% CI 1.81, 2.52), cardiovascular mortality (pooled OR 2.83; 95% CI 2.23, 3.60), and heart failure hospitalization (pooled OR: 2.53; 95% CI 1.78, 3.59). Real-world evidence suggests that the presence of LGE on CMR was a strong predictor of adverse long-term outcomes in patients with NIDCM. Scar assessment should be incorporated as a primary determinant in the patient selection criteria for primary prophylactic implantable cardioverter-defibrillator placement.

Number of segments with motion abnormalities is better correlated with infarct size in acute myocardial infarction.

The relationship between the number of segments with motion abnormalities (SMA) on the bull's-eye plots of speckle-tracking echocardiography (STE) and myocardial infarct size (MIS) on late gadolinium-enhanced cardiac MRI (LGE-cMRI) has not been well characterized. This study aimed to determine MIS using the number of SMA in patients with acute myocardial infarction (MI). Left ventricular two-dimensional STE and LGE-cMRI were performed in 380 patients with ST-segment elevation MI within 48 h and 5-6 days after primary percutaneous intervention, respectively. Patients with impaired global and regional myocardial strain, work and greater number of SMA had significantly larger infarcts ( P < 0.05). Multivariate logistic regression analysis that included myocardial strain, work, and number of SMA showed that total number of SMA [odds ratio (OR) = 1.976; 95% confidence interval (CI): 1.539-2.538, P < 0.0001], the number of segments with paradoxalic systolic movements (SPSM, OR = 3.703; 95% CI: 2.112-6.493, P < 0.0001) were independent risk factors of large MIS (>19%). The area under receiver operating characteristic curve (AUC) of 0.904 (0.866~0.942) for total number of SMA was superior to that for global longitudinal strain (GLS, AUC = 0.813, 0.761~0.865), global work efficiency (GWE, AUC = 0.794, 0.730~0.857) and number of SPSM (AUC = 0.851, 0.804-0.899) to predict a large MIS ( P < 0.05). The optimal cutoff value of total number of SMA was 7, with a sensitivity of 85.31%, a specificity of 81.48%, and an accuracy of 83.27%. Total number of SMA is better associated with infarct size, which provided an incremental prognostic value above established prognostic parameters such as GLS and GWE.

Three-dimensional High-Resolution Dark-Blood Late Gadolinium Enhancement Imaging for Improved Atrial Scar Evaluation.

Background Radiofrequency ablation (RFA) is a widely used treatment for atrial fibrillation, reducing the risk of cardiac arrhythmia. Detailed visualization and quantification of atrial scarring has the potential to improve preprocedural decision-making and postprocedural prognosis. Conventional bright-blood late gadolinium enhancement (LGE) MRI can help detect atrial scars; however, its suboptimal myocardium to blood contrast inhibits accurate scar estimation. Purpose To develop and test a free-breathing LGE cardiac MRI approach that simultaneously provides high-spatial-resolution dark-blood and bright-blood images for improved atrial scar detection and quantification. Materials and Methods A free-breathing, independent navigator-gated, dark-blood phase-sensitive inversion recovery (PSIR) sequence with whole-heart coverage was developed. Two coregistered high-spatial-resolution (1.25 × 1.25 × 3 mm3) three-dimensional (3D) volumes were acquired in an interleaved manner. The first volume combined inversion recovery and T2 preparation to achieve dark-blood imaging. The second volume functioned as the reference for phase-sensitive reconstruction with built-in T2 preparation for improved bright-blood contrast. The proposed sequence was tested in prospectively enrolled participants who had undergone RFA for atrial fibrillation (mean time since RFA, 89 days ± 26 [SD]) from October 2019 to October 2021. Image contrast was compared with conventional 3D bright-blood PSIR images using the relative signal intensity difference. Furthermore, native scar area quantification obtained from both imaging approaches was compared with measurements obtained with electroanatomic mapping (EAM) as the reference standard. Results A total of 20 participants (mean age, 62 years ± 9; 16 male) who underwent RFA for atrial fibrillation were included. The proposed PSIR sequence successfully acquired 3D high-spatial-resolution volumes in all participants, with a mean scan time of 8.3 minutes ± 2.4. The developed PSIR sequence improved scar to blood contrast compared with conventional PSIR sequence (mean contrast, 0.60 arbitrary units [au] ± 0.18 vs 0.20 au ± 0.19, respectively; P < .01) and correlated with EAM regarding scar area quantification (r = 0.66 [P < .01] vs r = 0.13 [P = .63]). Conclusion In participants who had undergone RFA for atrial fibrillation, an independent navigator-gated dark-blood PSIR sequence produced high-spatial-resolution dark-blood and bright-blood images with improved image contrast and native scar quantification compared with conventional bright-blood images. © RSNA, 2023 Supplemental material is available for this article.

Multimodality Imaging of Cardiac Angiolipoma

HomeRadiologyVol. 307, No. 5 PreviousNext Reviews and CommentaryFree AccessImages in RadiologyMultimodality Imaging of Cardiac AngiolipomaSimin Lin, Haojun Chen Simin Lin, Haojun Chen Author AffiliationsFrom the Department of Radiology, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, No. 2999 Jinshan Rd, Xiamen 361006, China (S.L.); and Department of Nuclear Medicine & Minnan PET Center, First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China (H.C.).Address correspondence to H.C. (email: [email protected]).Simin LinHaojun Chen Published Online:Jun 13 2023https://doi.org/10.1148/radiol.230116MoreSectionsPDF ToolsImage ViewerAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked In A 39-year-old man presented with a history of abdominal pain for 2 months. A routine chest radiograph showed an increased cardiothoracic ratio, and US was subsequently performed. At transthoracic echocardiography, an isoechoic cardiac mass was incidentally found in the anterior wall of the right atrium. The patient had no symptoms of chest tightness, chest pain, or dyspnea. His tumor markers showed a mild elevation of cancer antigen 125 (36.50 U/mL) and cancer antigen 724 (14.98 U/mL). The patient was scheduled for cardiac MRI to further characterize the lesion. A static four-chamber view obtained with a steady-state free precession sequence showed a 7.3 × 4.0-cm mass with heterogeneous signal intensity in the right atrium and atrioventricular groove (Figure, A). First-pass perfusion imaging indicated no apparent perfusion in the mass, which encased the right coronary artery (Figure, B). Inhomogeneous enhancement was detected with late gadolinium enhancement sequences (Figure, C), raising suspicion for malignancy. Hence, correlative fluorine 18 (18F) fluorodeoxyglucose (FDG) PET/CT was performed for tumor staging. Axial PET/CT images (Figure, D) revealed areas of fat attenuation and low 18F-FDG uptake, yielding a tumor-to-background ratio of 1:1. No abnormal radioactivity was observed in the extracardiac areas. The patient subsequently underwent radical tumor resection and surgical reconstruction of the right atrium. Histopathologic workup showed adipose tissue and interspersed proliferating blood vessels, consistent with the diagnosis of cardiac angiolipoma.(A) Cardiac MRI scan obtained with steady-state free precession (SSFP) shows a soft-tissue mass with heterogeneous signal intensity in the right atrium and atrioventricular groove (arrow). (B) First-pass perfusion MRI scan shows the mass encasing the right coronary artery (coronary vessel floating sign) without evident perfusion (arrowheads). (C) Short-axial late gadolinium enhancement (LGE) MRI scan shows inhomogeneous enhancement of the mass (arrow). (D) Axial fluorine 18 (18F) fluorodeoxyglucose (FDG) PET/CT image reveals areas of fat attenuation and mild 18F-FDG uptake (arrow) within the lesion (maximum standardized uptake value, 2.9), with a tumor-to-background ratio of 1:1.Download as PowerPointOpen in Image Viewer Disclosures of conflicts of interest: S.L. No relevant relationships. H.C. No relevant relationships.Article HistoryReceived: Jan 17 2023Revision requested: Feb 15 2023Revision received: Feb 17 2023Accepted: Mar 10 2023Published online: June 13 2023 FiguresReferencesRelatedDetailsRecommended Articles Dissection of a Giant Coronary AneurysmRadiology: Cardiothoracic Imaging2023Volume: 5Issue: 1Multimodality Imaging of Transposition of the Great ArteriesRadioGraphics2021Volume: 41Issue: 2pp. 338-360Fibrous Skeleton of the Heart: Anatomic Overview and Evaluation of Pathologic Conditions with CT and MR ImagingRadioGraphics2017Volume: 37Issue: 5pp. 1330-1351Cinematic Rendering of Complex Coronary Artery Left Atrial FistulaRadiology2022Volume: 307Issue: 1Active Cardiac Sarcoidosis Imitating Cardiac MetastasesRadiology: Cardiothoracic Imaging2020Volume: 2Issue: 6See More RSNA Education Exhibits Pearls and Pitfalls in Cardiac ImagingDigital Posters2022Multimodal Imaging Characterization of Cardiac Tumors Emphasizing PET with Pathology Correlation Using the New 2021 WHO ClassificationDigital Posters2022Mulmodality Imaging of Atrioventricular Groove Masses - Diagnostic ApproachDigital Posters2022 RSNA Case Collection Cardiac metastasis from melanomaRSNA Case Collection2022Cardiac myxomaRSNA Case Collection2020Primary Cardiac ParagangliomaRSNA Case Collection2022 Vol. 307, No. 5 Metrics Altmetric Score PDF download

PO-01-151 DEGREE OF FIBROSIS REMODELING ALTERS ATRIAL FIBRILLATION INDUCIBILITY

Mechanistically, the role of remodeled substrate in atrial fibrillation (AF) inducibility is not well understood. Here we assess the changes in AF reentrant-drivers (RDs) based on different levels of fibrotic remodeling – as visualized by degree of enhancement in late gadolinium enhancement (LGE) MRI. We compare the inducibility of the native fibrotic substrates in patients undergoing first-time ablation (FtA) and in those of repeat ablation (ReA) and characterize the regions most involved in RD maintenance. To investigate how different levels of fibrotic remodeling (enhancement in LGE MRI) affect AF inducibility. Ten LGE MRIs were obtained from AF patients undergoing FtA (n=5) or ReA (n=5). Fibrotic tissue was differentiated using personalized image intensity ratio (IIR) threshold; for scar, we used IIR=1.61; and the IIR for dense fibrosis was the midpoint between the two (Fig. 1B). For each patient, two personalized bi-atrial models were constructed: baseline and multi-level fibrosis. The baseline model includes only two tissue types – normal myocardium and fibrotic tissue; the multi-level fibrosis model for FtA has the addition of dense fibrosis, and for ReA, dense fibrosis and scar (Fig. 1C). Each model was tested for AF inducibility by rapid pacing from 40 uniformly distributed bi-atrial sites (Fig. 1D). RD-harboring regions were “cut out” (Fig. 1E) and the volumetric fraction of each substrate in each region was calculated (Fig. 1F). The ReA group had on average more remodeled tissue (29.11%) than the FtA group (20.05%). While the ReA group did not have more RDs than the FtA group, their RDs were more frequently inducible (from different pacing sites) compared to the RDs in the FtA group (usually inducible from just one pacing site). In general, one model was not found to be more arrhythmogenic than the other. For 7/10 patients, the model-pair produced at least one common RD. In all models, RDs required at least 30% of remodeled tissue within the local RD region. In ReA multi-level fibrosis models, RD-harboring regions had tissue significantly more remodeled (72.34%) than RD-harboring regions in baseline models (36.59%; p<0.0001). Different levels of fibrotic remodeling result in different levels of AF inducibility. These insights might be important in predicting ablation targets in AF patients.

PO-01-204 AN ARTIFICIAL INTELLIGENCE (AI)-ASSISTED END-TO-END COMPUTATIONAL PLATFORM FOR PREDICTION OF EXTRA-PULMONARY VEIN (EXTRA-PVI) ABLATION TARGETS IN ATRIAL FIBRILLATION (AF) PATIENTS WITH FIBROSIS REMODELING

Existing strategies targeting the extra-PVI AF substrate have failed to improve outcomes, as shown by clinical trials. There is an urgent need to establish new approaches that overcome existing limitations. We have shown previously, in a feasibility study, that bi-atrial personalized computational modeling can guide ablation in patients with fibrosis detected on late gadolinium enhancement MRI (LGE-MRI). However, the approach had laborious aspects, such as segmentation of both atria and fibrosis distribution, and determining substrate locations capable of sustaining rotors. These prevented the approach from being directly implementable in clinical workflows. To develop an AI-assisted computational platform for personalized extra-PVI substrate ablation target prediction in patients with atrial fibrosis detected by LGE-MRI, as part of an FDA-approved randomized clinical trial. We designed an AI-assisted platform enabling end-to-end modeling workflow for predicting extra-PVI ablation targets. The platform consists of 3 main components (Figure): i) personalized bi-atrial model construction from LGE-MRI, ii) personalized simulation of substrate AF inducibility, and iii) personalized extra-PVI ablation strategy implementable in the clinical workflow. For the first component, we developed, validated, and tested a deep learning approach to bi-atrial geometry and fibrosis segmentation, which consisted of a cascade of 4 neural networks (NNs). Extra-PVI substrate rotor inducibility was probed by pacing from numerous sites; locations capable of sustaining persistent drivers were determined using a novel NN approach and ablated. Each ablation was followed by the inducibility test, repeated until full substrate non-inducibility from any pacing site was achieved. The platform was successfully tested on 17 AF patients by multiple operators of differing expertise, with consistent results. Atrial geometry/fibrosis segmentation was achieved in 15 min, as compared to 5 hours pre-AI implementation. Using the NN approach for targeted substrate ablation ensured robustness and reproducibility of the predicted targets. Finally, a seamless import of atrial geometry and the optimal set of targets was achieved in a number of EAM systems. We developed a robust AI-assisted computational platform for prediction of extra-PVI atrial substrate ablation targets in AF patients with fibrosis, enabling our FDA-approved randomized clinical trial.

Prediction of Recurrence of Atrial Fibrillation Post-ablation Based on Atrial Fibrosis Seen on Late Gadolinium Enhancement MRI: A Metaanalysis.

This meta-analysis aims to investigate the recurrence of atrial fibrillation (AF) post-ablation based on the various stages of fibrosis seen in the late gadolinium enhancement magnetic resonance imaging (LGE-MRI). Electronic databases were searched using specific terms and identified nine studies that met the inclusion criteria. A total of 1,787 patients underwent LGE-MRI to assess atrial fibrosis before catheter ablation for AF. We performed three analyses: first, we compared stage IV versus stage I (reference group). The second set examined the combined stages III and IV versus stages I and II (reference group). The third set compared stage IV versus combined stages I, II, and III. The metanalysis relied on a random-effects model to pool the odds ratios (OR) and 95% confidence intervals (CI) using the DerSimonian and Laird method. The data was analyzed using StatsDirect software in England. The study showed a higher rate of AF recurrence after ablation in stage IV atrial fibrosis than in stage I (OR, 9.54; 95% CI, 3.81 to 28.89; P<00001). Also, in patients with combined stages III & IV of atrial fibrosis, AF recurrence was significantly higher after ablation than in stages I & II groups (OR, 2.37; 95% CI, 1.61 to 3.50; P<00001). Similarly, compared to combined stages I, II, and III, patients with stage IV have higher odds of recurrence post-ablation (OR, 4.24; 95% CI, 2.39- 7.52, P < 0.001). This metanalysis demonstrates the strong association between left atrial fibrosis in LGE-MRI and AF post-ablation recurrence. The finding of this study will further assist clinicians in predicting the recurrence rate of AF based on the amount of fibrosis and tailor therapeutic decisions for further management.

Myocardial Scar Detection Using High-Resolution Free-Breathing 3D Dark-Blood and Standard Breath-Holding 2D Bright-Blood Late Gadolinium Enhancement MRI: A Comparison of Observer Confidence.

To compare observer confidence for myocardial scar detection using 3 different late gadolinium enhancement (LGE) data sets by 2 observers with different levels of experience. Forty-one consecutive patients, who were referred for 3D dark-blood LGE MRI before implantable cardioverter-defibrillator implantation or ablation therapy and who underwent 2D bright-blood LGE MRI within a time frame of 3 months, were prospectively included. From all 3D dark-blood LGE data sets, a stack of 2D short-axis slices was reconstructed. All acquired LGE data sets were anonymized and randomized and evaluated by 2 independent observers with different levels of experience in cardiovascular imaging (beginner and expert). Confidence in detection of ischemic scar, nonischemic scar, papillary muscle scar, and right ventricular scar for each LGE data set was scored using a using a 3-point Likert scale (1 = low, 2 = medium, or 3 = high). Observer confidence scores were compared using the Friedman omnibus test and Wilcoxon signed-rank post hoc test. For the beginner observer, a significant difference in confidence regarding ischemic scar detection was observed in favor of reconstructed 2D dark-blood LGE compared with standard 2D bright-blood LGE (p = 0.030) while for the expert observer, no significant difference was found (p = 0.166). Similarly, for right ventricular scar detection, a significant difference in confidence was observed in favor of reconstructed 2D dark-blood LGE compared with standard 2D bright-blood LGE (p = 0.006) while for the expert observer, no significant difference was found (p = 0.662). Although not significantly different for other areas of interest, 3D dark-blood LGE and its derived 2D dark-blood LGE data set showed a tendency to score higher for all areas of interest at both experience levels. The combination of dark-blood LGE contrast and high isotropic voxels may contribute to increased observer confidence in myocardial scar detection, independent of observer's experience level but in particular for beginner observers.

Comparison of Biplane Area-Length Method and 3D Volume Quantification by Using Cardiac MRI for Assessment of Left Atrial Volume in Atrial Fibrillation

To compare maximum left atrial (LA) volume (LAV) from the routinely used biplane area-length (BAL) method with three-dimensional (3D)-based volumetry from late gadolinium-enhanced MRI (3D LGE MRI) and contrast-enhanced MR angiography (3D CE-MRA) in patients with atrial fibrillation (AF). Sixty-four patients with AF (mean age, 63 years ± 9 [SD]; 40 male patients) were retrospectively included from a prospective cohort acquired between October 2018 and February 2021. All patients underwent a research MRI examination that included standard two- and four-chamber cine acquisitions, 3D CE-MRA, and 3D LGE MRI performed prior to the atrial kick. Contour delineation on cine imaging and LA 3D segmentations were performed by a radiologist. Maximum LAV (BALmax) was extracted from the BAL volume-time curve and compared with LAV from 3D CE-MRA and 3D LGE MRI. The Kruskal-Wallis test was performed, followed by the Dunn post hoc test and Bland-Altman analyses. Interobserver variability was assessed in 10 patients. BALmax underestimated LAV compared with 3D CE-MRA (bias: -23.5 mL ± 46.2, P < .001) and 3D LGE MRI (bias: -31.3 mL ± 58.3, P < .001), whereas 3D LGE MRI volumes showed no evidence of a difference from 3D CE-MRA (bias: 7.8 mL ± 45.7, P = .38). Interobserver variability yielded excellent agreement for each method (intraclass correlation coefficient, 0.96-0.98). BALmax underestimated LAV in patients with AF compared with 3D LGE MRI and 3D CE-MRA, suggesting that the geometric assumption of an ellipsoidal LA shape in BAL does not reflect LA geometry in patients with AF.Keywords: Left Atrial Volume, Biplane Area-Length, Late Gadolinium-enhanced 3D MRI, Contrast-enhanced 3D MR Angiography, Atrial Fibrillation Supplemental material is available for this article. © RSNA, 2023.

The diagnostic utility of cardiac imaging (echocardiogram and cardiac magnetic resonance) in covid 19 patients and cardiac complications: retrospective cohort study in Saudi Arabia

Objectives: Coronavirus disease (COVID-19) continues to cause considerable morbidity and mortality worldwide. The complication in patients with severe COVID-19 disease include arrhythmias, peri-myocarditis (PM), and heart failure (HF). The important role of echocardiogram (ECHO) and cardiac MRI (CMRI) in the diagnosis of myocarditis in COVID-19 patients in Saudi Arabia has not been assessed. The objective is to assess the diagnostic value of ECHO and CMRI and define phenotypes patterns in the COVID 19 subgroup. Methods: In this retrospective study, adults with suspected COVID-19 presented with dyspnea and cardiovascular comorbidities were studied between January 2021 and December 2021. We collected 329 patients, (LVEF by ECHO was 44±11%). Fifty-two percent (173/329), had HF (HFrEF or HFpEF), thirty-six percent presented with acute coronary syndrome ACS (120/329), and four percent had adult congenital heart disease (ACHD). CMRI was performed in 160 patients (LVEF is 40±11%), and fifty-two were COVID-19 positive. Based on the Lake Louis criteria, CMRI was performed at siemens 3 T can identify myocardial function and damage using Late Gadolinium Enhancement (LGE) images phenotypes pattern were described as normal, ischemic, or nonischemic (peri-myocarditis). LVEF was divided by CMRI as (EF≥50 or EF&lt;50%). Comparison of Cardiac MRI LGE in the COVID 19 subgroups according to the LVEF was analyzed. The average time interval from diagnosis to CMRI was 4-8weeks. Results: Sixty percent of patients (221/329) were confirmed COVID-19 infection, the mean age is 54±13 years. Ten patients were diagnosed with pulmonary embolism (2/10 were ACHD). Peri-myocarditis patterns were found in sixty percent of COVID-19 patients (31/52), five percent (3/52) had an ischemic pattern, and thirty- five percent (18/52) had normal LGE (X2 =21.8 and P value&lt;0.001). However, in COVID-19 negative patients, Eighty percent (85/108) had an ischemic pattern, and twenty percent (23/108) had normal LGE. (X2 =37.7 and P value&lt;0.001). Conclusion: In this observational study, CMRI confirms its high diagnostic tool in evaluating myocarditis activity. In COVID-19 patients, two third of the population were found to have peri-myocarditis, with half of them reporting LVEF was ≥50 %. (X2 =67.1 and P value&lt;0.001).

Cardiac LGE MRI Segmentation With Cross-Modality Image Augmentation and Improved U-Net.

Image segmentation is a challenging problem in imaging informatics, which stems from the intersection of imaging techniques, computer science and biomedicine. In particular, accurate segmentation of cardiac structures in late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) is of great clinical importance for cardiac function assessment and myocardial disease diagnosis. However, it is a well-known challenge due to its special imaging modality and the lack of labeled LGE samples. In this paper, we propose an unsupervised ventricular segmentation algorithm that can perform biventricular segmentation of LGE images in the absence of labeled LGE data. There are two primary modules, the data augmentation procedure and the segmentation network. The easily available annotated balanced-Steady State Free Precession (bSSFP) images are employed for cross-modal data augmentation by image translation, where a single bSSFP image is converted into multiple synthetic LGE images while preserving the original morphological structure. Then, the proposed segmentation network is trained with the synthetic LGE images and used for segmenting real LGE images. Validation experiments demonstrated the effectiveness and advantages of the proposed algorithm.

A Two-stage Method with a Shared 3D U-Net for Left Atrial Segmentation of Late Gadolinium-Enhanced MRI Images

Objective: This study was aimed at validating the accuracy of a proposed algorithm for fully automatic 3D left atrial segmentation and to compare its performance with existing deep learning algorithms. Methods: A two-stage method with a shared 3D U-Net was proposed to segment the 3D left atrium. In this architecture, the 3D U-Net was used to extract 3D features, a two-stage strategy was used to decrease segmentation error caused by the class imbalance problem, and the shared network was designed to decrease model complexity. Model performance was evaluated with the DICE score, Jaccard index and Hausdorff distance. Results: Algorithm development and evaluation were performed with a set of 100 late gadolinium-enhanced cardiovascular magnetic resonance images. Our method achieved a DICE score of 0.918, a Jaccard index of 0.848 and a Hausdorff distance of 1.211, thus, outperforming existing deep learning algorithms. The best performance of the proposed model (DICE: 0.851; Jaccard: 0.750; Hausdorff distance: 4.382) was also achieved on a publicly available 2013 image data set. Conclusion: The proposed two-stage method with a shared 3D U-Net is an efficient algorithm for fully automatic 3D left atrial segmentation. This study provides a solution for processing large datasets in resource-constrained applications. Significance Statement: Studying atrial structure directly is crucial for comprehending and managing atrial fibrillation (AF). Accurate reconstruction and measurement of atrial geometry for clinical purposes remains challenging, despite potential improvements in the visibility of AF-associated structures with late gadolinium-enhanced magnetic resonance imaging. This difficulty arises from the varying intensities caused by increased tissue enhancement and artifacts, as well as variability in image quality. Therefore, an efficient algorithm for fully automatic 3D left atrial segmentation is proposed in the present study.