BackgroundEthnic differences in the progression and outcome of diabetic kidney disease (DKD) remain to be elucidated. MRI-quantified renal sinus fat volume could be a potential biomarker to help... Show moreBackgroundEthnic differences in the progression and outcome of diabetic kidney disease (DKD) remain to be elucidated. MRI-quantified renal sinus fat volume could be a potential biomarker to help investigate the changes of DKD risk in response to glucose regulation.PurposeTo evaluate whether the effect of glucose-lowering treatment on renal sinus fat volume differed in West Europeans (WE) compared to South Asians (SA), and whether ethnic-related difference exists regarding the effect of liraglutide on renal sinus fat.Study TypeRetrospective.PopulationNinety-three patients with type 2 diabetes mellitus, including 47 WE (27 males) aged 59.3 +/- 6.5 years, and 46 SA (19 males) aged 54.4 +/- 9.8 years.Field Strength/Sequence3.0 T dual-echo fast gradient-echo pulse sequence using two-point Dixon technique with a phase-correction algorithm.AssessmentChanges of renal sinus fat volume were measured by a radiologist (LL) with 4-years' experience, and were compared between the two ethnic groups, together with glycemic level, metabolic risk factors and renal function. The effects of liraglutide were assessed.Statistical TestsNormality of the data was visually evaluated by histograms and Q-Q plots. Within-group and between-group differences were analyzed using paired t-tests and analysis of covariance. Associations were analyzed by person's correlation and multiple linear regression models.ResultsRenal sinus fat decreased in SA patients (Delta% = -7.6% +/- 14.8%), but increased in WE patients (Delta% = 5.0% +/- 13.1%), with a significant difference between the two ethnic groups. In the WE group, the increase of sinus fat volume was significant in the placebo subgroup (Delta% = 6.8% +/- 12.5%), in contrast to the nonsignificant increase in the liraglutide subgroup (Delta% = 3.0% +/- 13.8%, P = 0.444).Data ConclusionRenal sinus fat accumulation responds differently to glucose regulation, showing a reduction in SA patients in contrast to a persistent accumulation in WE patients. A trend of less accumulation of sinus fat in WE patients receiving liraglutide has been observed.Evidence Level4Technical EfficacyStage 4 Show less
Sramko, M.; Fi, S.A.K.; Wijnmaalen, A.P.; Tao, Q.; Geest, R.J.V.; Lamb, H.J.; Zeppenfeld, K. 2023
BACKGROUND Electroanatomical voltage mapping (EAVM) has been compared with late gadolinium enhancement cardiovascular magnetic resonance (LGE-CMR), which cannot delineate diffuse fibrosis. T1... Show moreBACKGROUND Electroanatomical voltage mapping (EAVM) has been compared with late gadolinium enhancement cardiovascular magnetic resonance (LGE-CMR), which cannot delineate diffuse fibrosis. T1-mapping CMR overcomes the limitations of LGE-CMR, but it has not been directly compared against EAVM. OBJECTIVES This study aims to assess the relationship between left ventricular (LV) endocardial voltage obtained by EAVM and extracellular volume (ECV) obtained by T1 mapping. METHODS The study investigated patients who underwent endocardial EAVM for ventricular arrhythmias (CARTO 3, Biosense Webster) together with preprocedural contrast-enhanced T1 mapping (Ingenia 3T, Philips Healthcare). After image integration, EAVM datapoints were projected onto LGE-CMR and ECV-encoded images. Average values of unipolar voltage (UV), bipolar voltage (BV), LGE transmurality, and ECV were merged from corresponding cardiac segments (6 per slice) and pooled for analysis. RESULTS The analysis included data from 628 segments from 18 patients (57 +/- 13 years of age, 17% females, LV ejection fraction 48% +/- 14%, nonischemic/ischemic cardiomyopathy/controls: 8/6/4 patients). Based on the 95th and 5th percentile values obtained from the controls, ECV >33%, BV <2.9 mV, and UV <6.7 mV were considered abnormal. There was a significant inverse association between voltage and ECV, but only in segments with abnormal ECV. Increased ECV could predict abnormal BV and UV with acceptable accuracy (area under the curve of 0.78 [95% CI: 0.74-0.83] and 0.84 [95% CI: 0.79-0.88]). CONCLUSIONS This study found a significant inverse relationship between LV endocardial voltage and ECV. Real-time integration of T1 mapping may guide catheter mapping and may allow identification of areas of diffuse fibrosis potentially related to ventricular arrhythmias. (J Am Coll Cardiol EP 2023;9:740-748) (c) 2023 Published by Elsevier on behalf of the American College of Cardiology Foundation. Show less
Purpose: To develop automated vestibular schwannoma measurements on contrast-enhanced T1- and T2-weighted MRI scans.Materials and Methods: MRI data from 214 patients in 37 different centers were... Show morePurpose: To develop automated vestibular schwannoma measurements on contrast-enhanced T1- and T2-weighted MRI scans.Materials and Methods: MRI data from 214 patients in 37 different centers were retrospectively analyzed between 2020 and 2021. Patients with hearing loss (134 positive for vestibular schwannoma [mean age 6 SD, 54 years 6 12; 64 men] and 80 negative for vestibular schwannoma) were randomly assigned to a training and validation set and to an independent test set. A convolutional neural network (CNN) was trained using fivefold cross-validation for two models (T1 and T2). Quantitative analysis, including Dice index, Hausdorff distance, surface-to-surface distance (S2S), and relative volume error, was used to compare the computer and the human delineations. An observer study was performed in which two experienced physicians evaluated both delineations.Results: The T1-weighted model showed state-of-the-art performance, with a mean S2S distance of less than 0.6 mm for the whole tumor and the intrameatal and extrameatal tumor parts. The whole tumor Dice index and Hausdorff distance were 0.92 and 2.1 mm in the independent test set, respectively. T2-weighted images had a mean S2S distance less than 0.6 mm for the whole tumor and the intrameatal and extrameatal tumor parts. The whole tumor Dice index and Hausdorff distance were 0.87 and 1.5 mm in the independent test set. The observer study indicated that the tool was similar to human delineations in 85%-92% of cases.Conclusion: The CNN model detected and delineated vestibular schwannomas accurately on contrast-enhanced T1- and T2-weighted MRI scans and distinguished the clinically relevant difference between intrameatal and extrameatal tumor parts. (C) RSNA, 2022 Show less
Huang, L.; Tao, Q.; Zhao, P.J.; Ji, S.Q.; Jiang, J.G.; Geest, R.J. van der; Xia, L.M. 2022
Idiopathic inflammatory myopathies (IIM) is a group of heterogeneous autoimmune systemic diseases, which not only involve skeletal muscle but also myocardium. Cardiac involvement in IIM, which... Show moreIdiopathic inflammatory myopathies (IIM) is a group of heterogeneous autoimmune systemic diseases, which not only involve skeletal muscle but also myocardium. Cardiac involvement in IIM, which eventually develops into heart failure, is difficult to identify by conventional examinations at early stage. The aim of this study was to investigate if multi-parametric cardiac magnetic resonance (CMR) imaging can screen for early cardiac involvement in IIM, compared with clinical score (Myositis Disease Activity Assessment Tool, MDAAT). Forty-nine patients of IIM, and 25 healthy control subjects with comparable age-range and sex-ratio were enrolled in this study. All subjects underwent CMR examination, and multi-slice short-axis and 4-chamber cine MRI were acquired to evaluate biventricular global circumferential strain (GCS) and global longitudinal strain (GLS). Native T1 and T2 mapping were performed, and post-contrast T1 mapping and LGE were acquired after administration of contrast. A CMR score was developed from native T1 mean and T2 mean for the identification of cardiac involvement in the IIM cohort. Using contingency tables MDAAT and CMR were compared and statistically analyzed using McNemar test. McNemar's test revealed no significant difference between CMR score and MDAAT (p = 0.454). CMR score had potential to screen for early cardiac involvement in IIM patients, compared to MDAAT. Show less
OBJECTIVES This study sought to evaluate the ability of uni-and bipolar electrograms collected with a multielectrode catheter with smaller electrodes to: 1) delineate scar; and 2) determine local... Show moreOBJECTIVES This study sought to evaluate the ability of uni-and bipolar electrograms collected with a multielectrode catheter with smaller electrodes to: 1) delineate scar; and 2) determine local scar complexity. BACKGROUND Early reperfusion results in variable endocardial scar, often overlaid with surviving viable myocardium. Although bipolar voltage (BV) mapping is considered the pillar of substrate-based ablation, the role of unipolar voltage (UV) mapping has not been sufficiently explored. It has been suggested that bipolar electrograms collected with small electrode catheters can better identify complex scar geometries. METHODS Twelve swine with early reperfusion infarctions were mapped with the 48-electrode OctaRay catheter and a conventional catheter during sinus rhythm. BV electrograms with double components were identified. Transmural (n = 933) biopsy specimens corresponding to mapping points were obtained, histologically assessed, and classified by scar geometry. RESULTS OctaRay UV (UVOcta) and BV (BVOcta) amplitude were associated with the amount of viable myocardium at a given location, with a stronger association for UVOcta (R2 = 0.767 vs 0.473). Cutoff values of 3.7 mV and 1.0 mV could delineate scar (area under the curve: 0.803 and 0.728 for UVOcta and BVOcta, respectively). The morphology of bipolar electrograms collected with the OctaRay catheter more frequently identified areas with 2 layers of surviving myocardium than electrograms collected with the conventional catheter (84% vs 71%). CONCLUSIONS UV mapping can generate a map to delineate the area of interest when using a multielectrode catheter. Within this area of interest, the morphology of bipolar electrograms can identify areas in which a surviving epicardial layer may overlay a poorly coupled, potentially arrhythmogenic, endocardium. (C) 2022 by the American College of Cardiology Foundation. Show less
Embedding high-dimensional data onto a low-dimensional manifold is of both theoretical and practical value. In this article, we propose to combine deep neural networks (DNN) with mathematics-guided... Show moreEmbedding high-dimensional data onto a low-dimensional manifold is of both theoretical and practical value. In this article, we propose to combine deep neural networks (DNN) with mathematics-guided embedding rules for high-dimensional data embedding. We introduce a generic deep embedding network (DEN) framework, which is able to learn a parametric mapping from high-dimensional space to low-dimensional space, guided by well-established objectives such as Kullback-Leibler (KL) divergence minimization. We further propose a recursive strategy, called deep recursive embedding (DRE), to make use of the latent data representations for boosted embedding performance. We exemplify the flexibility of DRE by different architectures and loss functions, and benchmarked our method against the two most popular embedding methods, namely, t-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP). The proposed DRE method can map out-of-sample data and scale to extremely large datasets. Experiments on a range of public datasets demonstrated improved embedding performance in terms of local and global structure preservation, compared with other state-of-the-art embedding methods. Code is available at https://github.com/tao-aimi/DeepRecursiveEmbedding. Show less
Background Myocardial extracellular volume fraction (ECV) assessment can be affected by various technical and subject-related factors. Purpose To evaluate the role of contour-based registration in... Show moreBackground Myocardial extracellular volume fraction (ECV) assessment can be affected by various technical and subject-related factors. Purpose To evaluate the role of contour-based registration in quantification of ECV and investigate normal segment-based myocardial ECV values at 3T. Material and Methods Pre- and post-contrast T1 mapping images of the left ventricular basal, mid-cavity, and apical slices were obtained in 26 healthy volunteers. ECV maps were generated using motion correction with and without contour-based registration. The image quality of all ECV maps was evaluated by a 4-point scale. Slices were dichotomized according to the occurrence of misregistration in the source data. Contour-registered ECVs and standard ECVs were compared within each subgroup using analysis of variance for repeated measurements and generalized linear mixed models. Results In all three slices, higher quality of ECV maps were found using contour-registered method than using standard method. Standard ECVs were statistically different from contour-registered ECVs in global (26.8% +/- 2.8% vs. 25.8% +/- 2.4%; P = 0.001), mid-cavity (25.4% +/- 3.1% vs. 24.3% +/- 2.5%; P = 0.016), and apical slices (28.7% +/- 4.1% vs. 27.2% +/- 3.4%; P = 0.010). In the misregistration subgroups, contour-registered ECVs were lower with smaller SDs (basal: 25.2% +/- 1.8% vs. 26.7% +/- 2.6%; P = 0.038; mid-cavity: 24.4% +/- 2.3% vs. 26.8% +/- 3.1%; P = 0.012; apical: 27.5% +/- 3.6% vs. 29.7% +/- 4.5%; P = 0.016). Apical (27.2% +/- 3.4%) and basal-septal ECVs (25.6% +/- 2.6%) were statistically higher than mid-cavity ECV (24.3% +/- 2.5%; both P < 0.001). Conclusion Contour-based registration can optimize image quality and improve the precision of ECV quantification in cases demonstrating ventricular misregistration among source images. Show less
Aims We aimed to compare renal sinus fat volume assessed by MRI between patients with type 2 diabetes and healthy volunteers, and investigate the association between renal sinus fat and metabolic... Show moreAims We aimed to compare renal sinus fat volume assessed by MRI between patients with type 2 diabetes and healthy volunteers, and investigate the association between renal sinus fat and metabolic traits.Methods In this cross-sectional study, renal sinus fat and parenchyma volumes measured on abdominal MRI were compared between patients and controls using analysis of covariance. Associations of renal parameters with clinical characteristics were analyzed using linear regression analysis.Results A total of 146 participants were enrolled, consisting of 95 type 2 diabetes patients (57.2 +/- 8.8 years, 49.5% male) and 51 controls (54.0 +/- 9.2 years, 43.1% male). Patients with diabetes demonstrated larger sinus fat volumes (15.4 +/- 7.5 cm(3) vs. 10.3 +/- 7.1 cm(3), p < 0.001) and sinus fat-parenchyma ratio than controls. In the total population, renal sinus fat was positively associated with HbA1c, abdominal VAT, cholesterol and triglycerides, after adjustment for age, sex, ethnicity and type 2 diabetes. In type 2 diabetes patients, increased sinus fat volume was significantly associated with urinary albumin-to-creatinine ratio.Conclusion Renal sinus fat volume is positively associated with several metabolic risk factors including HbA1c level and urinary albumin-to-creatinine ratio in type 2 diabetes patients, indicating a potential role of renal sinus fat in the development of diabetic nephropathy. Future studies are needed to investigate whether sinus fat volume can serve as an early biomarker for diabetic nephropathy. Show less
Objectives Our study aimed to evaluate myocardial strain and tissue characteristics by multiparametric cardiovascular magnetic resonance (CMR) imaging in end-stage renal disease (ESRD) patients on... Show moreObjectives Our study aimed to evaluate myocardial strain and tissue characteristics by multiparametric cardiovascular magnetic resonance (CMR) imaging in end-stage renal disease (ESRD) patients on peritoneal dialysis with preserved left ventricular ejection fraction (LVEF).Methods ESRD patients on peritoneal dialysis with echocardiographic LVEF > 50% and age- and sex-matched healthy volunteers underwent multiparametric CMR at 3 T. LV function, LV myocardial native T1 and T2, and biventricular strain were measured and compared between the patients and controls. Associations of LV myocardial mass index (LVMI) with tissue characterization and strain were evaluated by multiple linear regression.Results A total of 65 subjects (42 healthy volunteers and 23 ESRD patients) were enrolled. ESRD group demonstrated larger LVMI, higher native T1 and T2 (1301.9 +/- 30.6 ms, 44.6 +/- 2.6 ms) than those of the control group (1255.8 +/- 45.2 ms, 40.5 +/- 1.6 ms; both p < 0.001). Decreased LV strain and increased right ventricular circumferential strain were observed in the ESRD group. In ESRD patients with normal diastolic function on echocardiography, native T1 and T2 values were higher than those of the control group (p = 0.006, p = 0.001). Increased LVMI was associated with increased native T1 (p = 0.001) and T2 value (p < 0.001) after adjusting for age and sex. Increased myocardial native T1 value was associated with reduced LV strain after adjusting age, sex, and LVMI.Conclusions ESRD patients on peritoneal dialysis with preserved LVEF demonstrated higher myocardial mass, higher native T1 and T2 values, decreased LV strain, and increased RVGCS compared with healthy controls. Increased myocardial T1 and T2 were found in ESRD even when no systolic or diastolic dysfunction was detected by routine echocardiography. Show less
OBJECTIVES This study sought to assess the relative effect of catheter, tissue, and catheter-tissue parameters, on the ability to determine the amount of viable myocardium in vivo.BACKGROUND... Show moreOBJECTIVES This study sought to assess the relative effect of catheter, tissue, and catheter-tissue parameters, on the ability to determine the amount of viable myocardium in vivo.BACKGROUND Although multiple variables impact bipolar voltages (BVs), electrode size, interelectrode spacing, and directional dependency are of particular interest with the development of catheters incorporating mini and microelectrodes.METHODS Nine swine with early reperfusion myocardial infarctions were mapped using the QDot catheter and then remapped using a Pentaray catheter. All QDot points were matched with Pentaray points within 5 mm. The swine were sacrificed, and mapping data projected onto the heart. Transmural biopsies corresponding to mapping points were obtained, allowing a comparison of electrograms recorded by mini, micro-, and conventional electrodes with histology.RESULTS The conventional BV of 2,322 QDot points was 1.9 +/- 1.3 mV. The largest of the 3 microelectrode BVs (BV mu Max) average 4.8 +/- 3.1 mV. The difference between the largest (BV mu Max) and smallest (BV mu Min) at a given location was 53.7 +/- 18.1%. The relationships between both BV mu Max and BV mu Min and between the conventional BV and BV mu Max were positively related but with a significant spread in data, which was more pronounced for the latter. Pentaray points positively related to the BV mu Max with poor fit. On histology, increasing viable myocardium increased voltage, but both the slope coefficient and fit were best for BV mu Max.CONCLUSIONS Using histology, we could demonstrate that BV mu Max is superior to identify viable myocardium compared with BVC and BV using the Pentaray catheter. The ability to simultaneously record 3 BV(mu)s with different orientations, for the same beat, with controllable contact and selecting BV mu Max for local BV may partially compensate for wave front direction. (C) 2021 by the American College of Cardiology Foundation. Show less
Segmentation of medical images, particularly late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) used for visualizing diseased atrial structures, is a crucial first step for ablation... Show moreSegmentation of medical images, particularly late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) used for visualizing diseased atrial structures, is a crucial first step for ablation treatment of atrial fibrillation. However, direct segmentation of LGE-MRIs is challenging due to the varying intensities caused by contrast agents. Since most clinical studies have relied on manual, labor-intensive approaches, automatic methods are of high interest, particularly optimized machine learning approaches. To address this, we organized the 2018 Left Atrium Segmentation Challenge using 154 3D LGE-MRIs, currently the world's largest atrial LGE-MRI dataset, and associated labels of the left atrium segmented by three medical experts, ultimately attracting the participation of 27 international teams. In this paper, extensive analysis of the submitted algorithms using technical and biological metrics was performed by undergoing subgroup analysis and conducting hyper-parameter analysis, offering an overall picture of the major design choices of convolutional neural networks (CNNs) and practical considerations for achieving state-of-the-art left atrium segmentation. Results show that the top method achieved a Dice score of 93.2% and a mean surface to surface distance of 0.7 mm, significantly outperforming prior state-of-the-art. Particularly, our analysis demonstrated that double sequentially used CNNs, in which a first CNN is used for automatic region-of-interest localization and a subsequent CNN is used for refined regional segmentation, achieved superior results than traditional methods and machine learning approaches containing single CNNs. This large-scale benchmarking study makes a significant step towards much-improved segmentation methods for atrial LGE-MRIs, and will serve as an important benchmark for evaluating and comparing the future works in the field. Furthermore, the findings from this study can potentially be extended to other imaging datasets and modalities, having an impact on the wider medical imaging community. (C) 2020 Elsevier B.V. All rights reserved. Show less
OBJECTIVES This study evaluated cardiac involvement in patients recovered from coronavirus disease-2019 (COVID-19) using cardiac magnetic resonance (CMR).BACKGROUND Myocardial injury caused by... Show moreOBJECTIVES This study evaluated cardiac involvement in patients recovered from coronavirus disease-2019 (COVID-19) using cardiac magnetic resonance (CMR).BACKGROUND Myocardial injury caused by COVID-19 was previously reported in hospitalized patients. It is unknown if there is sustained cardiac involvement after patients' recovery from COVID-19.METHODS Twenty-six patients recovered from COVID-19 who reported cardiac symptoms and underwent CMR examinations were retrospectively included. CMR protocols consisted of conventional sequences (cine, T2-weighted imaging, and late gadolinium enhancement [LGE]) and quantitative mapping sequences (T1, T2, and extracellular volume [ECV] mapping). Edema ratio and LGE were assessed in post-COVID-19 patients. Cardiac function, native T1/T2, and ECV were quantitatively evaluated and compared with controls.RESULTS Fifteen patients (58%) had abnormal CMR findings on conventional CMR sequences: myocardial edema was found in 14 (54%) patients and LGE was found in 8 (31%) patients. Decreased right ventricle functional parameters including ejection fraction, cardiac index, and stroke volume/body surface area were found in patients with positive conventional CMR findings. Using quantitative mapping, global native T1, T2, and ECV were all found to be significantly elevated in patients with positive conventional CMR findings, compared with patients without positive findings and controls (median [interquartile range]: native T1 1,271 ms [1,243 to 1,298 ms] vs. 1,237 ms [1,216 to 1,262 ms] vs. 1,224 ms [1,217 to 1,245 ms]; mean +/- SD: T2 42.7 +/- 3.1 ms vs. 38.1 ms +/- 2.4 vs. 39.1 ms +/- 3.1; median [interquartile range]: 28.2% [24.8% to 36.2%] vs. 24.8% [23.1% to 25.4%] vs. 23.7% [22.2% to 25.2%]; p = 0.002; p < 0.001, and p =0.002, respectively).CONCLUSIONS Cardiac involvement was found in a proportion of patients recovered from COVID-19. CMR manifestation included myocardial edema, fibrosis, and impaired right ventricle function. Attention should be paid to the possible myocardial involvement in patients recovered from COVID-19 with cardiac symptoms. (C) 2020 by the American College of Cardiology Foundation. Show less
Background: There is a growing interest in fast and reliable assessment of abdominal visceral adipose tissue (VAT) volume for risk stratification of metabolic disorders. However, imaging based... Show moreBackground: There is a growing interest in fast and reliable assessment of abdominal visceral adipose tissue (VAT) volume for risk stratification of metabolic disorders. However, imaging based measurement of VAT is costly and limited by scanner availability. Therefore, we aimed to develop equations to estimate abdominal VAT volume from simple anthropometric parameters and to assess whether linear regression based equations differed in performance from artificial neural network (ANN) based equations.Methods: MRI-measured abdominal VAT volumes and anthropometric parameters of 5772 subjects (White ethnicity, age 45-76 years, 52.7% females) were obtained from the UK Biobank. Subjects were divided into the derivation sample (n = 5195) and the validation sample (n = 577). Basic models (age, sex, height, weight) and expanded models (basic model + waist circumference and hip circumference) were constructed from the derivation sample by linear regression and ANN respectively. Performance of the linear regression and ANN based equations in the validation sample were compared and estimating accuracies were evaluated by receiver-operating characteristic curves (ROC).Results: The basic and expanded equations based on linear regression and ANN demonstrated the adjusted coefficient of determination (R-2) ranging from 0.71 to 0.78, with bias ranging from less than 0.001 L-0.07 L in comparison with MRI-measured VAT. Both basic and expanded ANN based equations demonstrated slightly higher adjusted R-2 and lower error measurements than linear regression equations. However, no statistical difference was found between linear regression equations and their ANN based counterparts in ROC analysis. Both linear regression and ANN based expanded equations presented higher estimating accuracies (76.9%-90.1%) than the basic equations (74.5%-87.5%) in ROC analysis.Conclusions: We present equations based on linear regression and artificial neural networks to estimate abdominal VAT volume by simple anthropometric parameters for middle-aged and elderly White population. These equations can be used to estimate VAT volume in general practice as well as population-based studies. (C) 2020 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved. Show less
Venlet, J.; Tao, Q.; Graaf, M.A. de; Glashan, C.A.; Silva, M.D.; Geest, R.J. van der; ... ; Zeppenfeld, K. 2020
OBJECTIVES This study sought to evaluate whether right ventricular (RV) tissue heterogeneity on computed tomography (CT): 1) is associated with conduction delay in arrhythmogenic right ventricular... Show moreOBJECTIVES This study sought to evaluate whether right ventricular (RV) tissue heterogeneity on computed tomography (CT): 1) is associated with conduction delay in arrhythmogenic right ventricular cardiomyopathy (ARVC); and 2) distinguishes patients with ARVC from those with exercise-induced arrhythmogenic remodeling (EIAR) and control individuals.BACKGROUND ARVC is characterized by fibrofatty replacement, related to conduction delay and ventricular tachycardiac. Distinguishing ARVC from acquired, EIAR is challenging.METHODS Patients with ARVC or EIAR and combined endocardial-epicardiat electroanatomic voltage mapping for VT ablation with CT integration were enrolled. Patients without structural heart disease served as control individuals. Tissue heterogeneity on CT (CT heterogeneity) was automatically quantified within the 2-mm subepicardium of the entire RV free wall at normal sites and tow voltage sites harboring late potentials (LP+) in ARVC/EIAR.RESULTS Seventeen patients with ARVC (15 mates; age: 50 17 years), 9 patients with EIAR (7 males; age: 45 14 years) and 17 control individuals (14 males; age: 50 +/- 15 years) were enrolled. Of 5,215 ARVC mapping points, 560 (11%) showed LP+ . CT heterogeneity was higher at sites with LP-i compared to normal sites (median: 31 HU/mm; IQR: 23 to 46 HU/mm vs. median: 16 HU/mm; IQR: 13 to 21 HU/mm; p < 0.001). The optimal CT heterogeneity cutoff for detection of LP+ was 25 HU/mm (area under the curve [AUG 0.80; sensitivity: 72%; specificity: 78%). Overall CT heterogeneity allowed highly accurate differentiation between patients with ARVC and control individuals (AUC: 0.97; sensitivity: 100%; specificity: 82%) and between ARVC and EIAR (AUC: 0.78; sensitivity: 65%; spedficity: 89%).CONCLUSIONS In patients with ARVC, tissue heterogeneity on CT can be used to identify LP+ as a surrogate for ventricular tachycardia substrate. The overall tissue heterogeneity on CT allows the distinguishing of patients with ARVC from those with EIAR and control individuals. (C) 2020 by the American College of Cardiology Foundation. Show less
Noortman, W.A.; Vriens, D.; Grootjans, W.; Tao, Q.; Geus-Oei, L.F. de; Velden, F.H. van 2020
In recent years, radiomics, defined as the extraction of large amounts of quantitative features from medical images, has gained emerging interest. Radiomics consists of the extraction of... Show moreIn recent years, radiomics, defined as the extraction of large amounts of quantitative features from medical images, has gained emerging interest. Radiomics consists of the extraction of handcrafted features combined with sophisticated statistical methods or machine learning algorithms for modelling, or deep learning algorithms that both learn features from raw data and perform modelling. These features have the potential to serve as non-invasive biomarkers for tumor characterization, prognostic stratification and response prediction. thereby contributing to precision medicine. However, especially in nuclear medicine, variable results are obtained when using radiomics for these purposes. Individual studies show promising results, but due to small numbers of patients per study and little standardization, it is difficult to compare and validate results on other datasets. This review describes the radiomic pipeline, its applications and the increasing role of artificial intelligence within the field. Furthermore, the challenges that need to be overcome to achieve clinical translation are discussed, so that, eventually, radiomics, combined with clinical data and other biomarkers, can contribute to precision medicine, by providing the right treatment to the right patient, with the right dose. at the right time. Show less
Background: Chest CT is used in the diagnosis of coronavirus disease 2019 (COVID-19) and is an important complement to reverse-transcription polymerase chain reaction (RT-PCR) tests.Purpose: To... Show moreBackground: Chest CT is used in the diagnosis of coronavirus disease 2019 (COVID-19) and is an important complement to reverse-transcription polymerase chain reaction (RT-PCR) tests.Purpose: To investigate the diagnostic value and consistency of chest CT as compared with RT-PCR assay in COVID-19.Materials and Methods: This study included 1014 patients in Wuhan, China, who underwent both chest CT and RT-PCR tests between January 6 and February 6, 2020. With use of RT-PCR as the reference standard, the performance of chest CT in the diagnosis of COVID-19 was assessed. In addition, for patients with multiple RT-PCR assays, the dynamic conversion of RT-PCR results (negativeto positive, positive to negative) was analyzed as compared with serial chest CT scans for those with a time interval between RT-PCR tests of 4 days or more.Results: Of the 1014 patients, 601 of 1014 (59%) had positive RT-PCR results and 888 of 1014 (88%) had positive chest CT scans. The sensitivity of chest CT in suggesting COVID-19 was 97% (95% confidence interval: 95%, 98%; 580 of 601 patients) based on positive RT-PCR results. In the 413 patients with negative RT-PCR results, 308 of 413 (75%) had positive chest CT findings. Of those 308 patients, 48% (103 of 308) were considered as highly likely cases and 33% (103 of 308) as probable cases. At analysis of serial RT-PCR assays and CT scans, the mean interval between the initial negative to positive RT-PCR results was 5.1 days +/- 1.5; the mean interval between initial positive to subsequent negative RT-PCR results was 6.9 days +/- 2.3. Of the 1014 patients, 60% (34 of 57) to 93% (14 of 15) had initial positive CT scans consistent with COVID-19 before (or parallel to) the initial positive RT-PCR results. Twenty-four of 57 patients (42%) showed improvement on follow-up chest CT scans before the RT-PCR results turned negative.Conclusion: Chest CT has a high sensitivity for diagnosis of coronavirus disease 2019 (COVID-19). Chest CT may be considered as a primary tool for the current COVID-19 detection in epidemic areas. (C) RSNA, 2020 Show less
Purpose Cardiac motion tracking enables quantitative evaluation of myocardial strain, which is clinically interesting in cardiovascular disease research. However, motion tracking is difficult to... Show morePurpose Cardiac motion tracking enables quantitative evaluation of myocardial strain, which is clinically interesting in cardiovascular disease research. However, motion tracking is difficult to perform manually. In this paper, we aim to develop and compare two fully automated motion tracking methods for the steady state free precession (SSFP) cine magnetic resonance imaging (MRI), and explore their use in real clinical scenario with different patient groups. Methods We proposed two automated cardiac motion tracking method: (a) a traditional registration-based method, named full cardiac cycle registration, which simultaneously tracks all cine frames within a full cardiac cycle by joint registration of all frames; and (b) a modern convolutional neural network (CNN)-based method, named Groupwise MotionNet, which enhances the temporal coherence by fusing motion along a continuous time scale. Both methods were evaluated on the healthy volunteer data from the MICCAI 2011 STACOM Challenge, as well as on patient data including hypertrophic cardiomyopathy (HCM) and myocardial infarction (MI). Results The full cardiac cycle registration method achieved an average end-point error (EPE) 2.89 +/- 1.57 mm for cardiac motion tracking, with computation time of around 9 min per short-axis cine MRI (size 128 x 128, 30 cardiac phases). In comparison, the Groupwise MotionNet achieved an average EPE of 0.94 +/- 1.59 mm, taking < 1 s for a full cardiac phases. Further experiments showed that registration method had stable performance, independent of patient cohort and MRI machine, while the CNN-based method relied on the training data to deliver consistently accurate results. Conclusion Both registration-based and CNN-based method can track the cardiac motion from SSFP cine MRI in a fully automated manner, while taking temporal coherence into account. The registration method is generic, robust, but relatively slow; the CNN-based method trained with heterogeneous data was able to achieve high tracking accuracy with real-time performance. Show less
Objectives Coronary CT angiography (cCTA) has been used to non-invasively assess both the anatomical and hemodynamic significance of coronary stenosis. The current study investigated a new CFD... Show moreObjectives Coronary CT angiography (cCTA) has been used to non-invasively assess both the anatomical and hemodynamic significance of coronary stenosis. The current study investigated a new CFD-based method of evaluating pressure-flow curves across a stenosis to further enhance the diagnostic value of cCTA imaging. Methods Fifty-eight patients who underwent both cCTA imaging and invasive coronary angiography (ICA) with fractional flow reserve (FFR) within 2 weeks were enrolled. The pressure-flow curve-derived parameters, viscous friction (VF) and expansion loss (EL), were compared with conventional cCTA parameters including percent area stenosis (AS) and minimum lumen area (MLA) by receiver operating characteristic (ROC) curve analysis. FFR <= 0.80 was used to indicate ischemia-causing stenosis. Correlations between FFR and other measurements were calculated by Spearman's rank correlation coefficient (rho). Results Sixty-eight stenoses from 58 patients were analyzed. VF, EL, and AS were significantly larger in the group of FFR <= 0.8 while smaller MLA values were observed. The ROC-AUC of VF (0.91, 95% CI 0.81-0.96) was better than that of AS (change in AUC (Delta AUC) 0.27, p < 0.05) and MLA (Delta AUC 0.17, p < 0.05), and ROC-AUC of EL (0.90, 95%CI 0.80-0.96) was also better than that of AS (Delta AUC 0.26, p < 0.05) and MLA (Delta AUC 0.16, p < 0.05). FFR values correlated well with VF (rho = - 0.74 (95% CI - 0.83 to - 0.61, p < 0.0001) and EL (rho = - 0.74 (95% CI - 0.83 to - 0.61, p < 0.0001). Conclusion Pressure-flow curve-derived parameters enhance the diagnostic value of cCTA examination. Show less
