Abdominal adipose tissue components quantification in MRI as a relevant biomarker of metabolic profile

Automated abdominal adipose tissue segmentation and volume quantification on longitudinal MRI using 3D convolutional neural networks with multi-contrast inputs

OBJECTIVE

Increased subcutaneous and visceral adipose tissue (SAT/VAT) volume is associated with risk for cardiometabolic diseases. This work aimed to develop and evaluate automated abdominal SAT/VAT segmentation on longitudinal MRI in adults with overweight/obesity using attention-based competitive dense (ACD) 3D U-Net and 3D nnU-Net with full field-of-view volumetric multi-contrast inputs.

MATERIALS AND METHODS

920 adults with overweight/obesity were scanned twice at multiple 3 T MRI scanners and institutions. The first scan was divided into training/validation/testing sets (n = 646/92/182). The second scan from the subjects in the testing set was used to evaluate the generalizability for longitudinal analysis. Segmentation performance was assessed by measuring Dice scores (DICE-SAT, DICE-VAT), false negatives (FN), and false positives (FP). Volume agreement was assessed using the intraclass correlation coefficient (ICC).

RESULTS

ACD 3D U-Net achieved rapid (< 4.8 s/subject) segmentation with high DICE-SAT (median ≥ 0.994) and DICE-VAT (median ≥ 0.976), small FN (median ≤ 0.7%), and FP (median ≤ 1.1%). 3D nnU-Net yielded rapid (< 2.5 s/subject) segmentation with similar DICE-SAT (median ≥ 0.992), DICE-VAT (median ≥ 0.979), FN (median ≤ 1.1%) and FP (median ≤ 1.2%). Both models yielded excellent agreement in SAT/VAT volume versus reference measurements (ICC > 0.997) in longitudinal analysis.

DISCUSSION

ACD 3D U-Net and 3D nnU-Net can be automated tools to quantify abdominal SAT/VAT volume rapidly, accurately, and longitudinally in adults with overweight/obesity.

Associations of aortic stiffness and intra-aortic flow parameters with epicardial adipose tissue in patients with type-2 diabetes

Background

It has been shown that increased aortic stiffness is related to type-2 diabetes (T2D) which is considered as a risk factor for cardiovascular disease. Among other risk factors is epicardial adipose tissue (EAT) which is increased in T2D and is a relevant biomarker of metabolic severity and adverse outcome.

Purpose

To assess aortic flow parameters in T2D patients as compared to healthy individuals and to evaluate their associations with EAT accumulation as an index of cardiometabolic severity in T2D patients.

Materials and methods

Thirty-six T2D patients as well as 29 healthy controls matched by age and sex were included in this study. Participants had cardiac and aortic MRI exams at 1.5 T. Imaging sequences included cine SSFP for left ventricle (LV) function and EAT assessment and aortic cine and phase-contrast imaging for strain and flow parameters quantification.

Results

In this study, we found LV phenotype to be characterized by concentric remodeling with decreased stroke volume index despite global LV mass within a normal range. EAT was increased in T2D patients compared to controls (p<0.0001). Moreover, EAT, a biomarker of metabolic severity, was negatively correlated to ascending aortic (AA) distensibility (p=0.048) and positively to the normalized backward flow volume (p=0.001). These relationships remained significant after further adjustment for age, sex and central mean blood pressure. In a multivariate model, presence/absence of T2D and AA normalized backward flow (BF) to forward flow (FF) volumes ratio are both significant and independent correlates of EAT.

Conclusion

In our study, aortic stiffness as depicted by an increased backward flow volume and decreased distensibility seems to be related to EAT volume in T2D patients. This observation should be confirmed in the future on a larger population while considering additional biomarkers specific to inflammation and using a longitudinal prospective study design.

Feasibility of a New Regional Myocardial Strain Parameter for the Detection of Wall Motion Abnormalities in Arrhythmogenic Right Ventricular Cardiomyopathy

Purpose

To evaluate a cardiac MRI feature tracking (FT)-derived parameter that combines right ventricular (RV) longitudinal and radial motions in detecting arrhythmogenic right ventricular cardiomyopathy (ARVC).

Materials and Methods

Patients with ARVC (n = 47; median age, 46 [IQR, 30-52] years; 31 men) were compared with controls (n = 39; median age, 46 [IQR, 33-53] years; 23 men) and separated into two groups based on fulfillment of major structural 2020 International criteria. Cine data from 1.5-T cardiac MRI examinations were analyzed using FT, resulting in conventional strain parameters and a novel composite index named the longitudinal-to-radial strain loop (LRSL). Receiver operating characteristic (ROC) analysis was used to assess diagnostic performance of RV parameters.

Results

Volumetric parameters differed significantly between patients in the major structural criteria group and controls but not between patients in the no major structural criteria group and controls. Patients in the major structural criteria group had significantly lower magnitudes of all FT parameters than controls, including RV basal longitudinal strain, radial motion fraction, circumferential strain, and LRSL (-15.6% ± 6.4 vs -26.7% ± 13.9; -9.6% ± 4.89 vs -13.8% ± 4.7; -6.9% ± 4.6 vs -10.1% ± 3.8; and 217.0 ± 128.9 versus 618.6 ± 356.3, respectively). Only LRSL differed between patients in the no major structural criteria group and controls (359.5 ± 195.8 vs 618.6 ± 356.3; P < .0001). Parameters with the highest area under the ROC curve values for discriminating patients in the no major structural criteria group from controls were LRSL, RV ejection fraction, and RV basal longitudinal strain (0.75, 0.70, and 0.61, respectively).

Conclusion

A new parameter combining RV longitudinal and radial motions showed good diagnostic performance in ARVC, even in patients without major structural abnormalities.Keywords: Arrhythmogenic Right Ventricular Dysplasia, Strain, Wall Motion Abnormalities, Right Ventricle, MRI, Inherited Cardiomyopathy Supplemental material is available for this article. © RSNA, 2023.

Cardiac adipose tissue volume and IL-6 level at admission are complementary predictors of severity and short-term mortality in COVID-19 diabetic patients

BACKGROUND

COVID-19 diabetic adults are at increased risk of severe forms irrespective of obesity. In patients with type-II diabetes, fat distribution is characterized by visceral and ectopic adipose tissues expansion, resulting in systemic inflammation, which may play a role in driving the COVID-19 cytokine storm. Our aim was to determine if cardiac adipose tissue, combined to interleukin-6 levels, could predict adverse short-term outcomes, death and ICU requirement, in COVID-19 diabetic patients during the 21 days after admission.

METHODS

Eighty one consecutive patients with type-II diabetes admitted for COVID-19 were included. Interleukin-6 measurement and chest computed tomography with total cardiac adipose tissue index (CATi) measurement were performed at admission. The primary outcome was death during the 21 days following admission while intensive care requirement with or without early death (ICU-R) defined the secondary endpoint. Associations of CATi and IL-6 and threshold values to predict the primary and secondary endpoints were determined.

RESULTS

Of the enrolled patients (median age 66 years [IQR: 59-74]), 73% male, median body mass index (BMI) 27 kg/m² [IQR: 24-31]) 20 patients had died from COVID-19, 20 required intensive care and 41 were in conventional care at day 21 after admission. Increased CATi and IL-6 levels were both significantly related to increased early mortality (respectively OR = 6.15, p = 0.002; OR = 18.2, p < 0.0001) and ICU-R (respectively OR = 3.27, p = 0.01; OR = 4.86, p = 0.002). These associations remained significant independently of age, sex, BMI as well as troponin-T level and pulmonary lesion extension in CT. We combined CATi and IL-6 levels as a multiplicative interaction score (CATi*IL-6). The cut-point for this score was ≥ 6386 with a sensitivity of 0.90 and a specificity of 0.87 (AUC = 0.88) and an OR of 59.6 for early mortality (p < 0.0001).

CONCLUSIONS

Cardiac adipose tissue index and IL-6 determination at admission could help physicians to better identify diabetic patients with a potentially severe and lethal short term course irrespective of obesity. Diabetic patients with high CATi at admission, a fortiori associated with high IL-6 levels could be a relevant target population to promptly initiate anti-inflammatory therapies.