Epicardial and pericardial fat analysis on CT images and artificial intelligence: a literature review

Greco, Federico; Salgado, Rodrigo; Hecke, Wim Van; Buono, Romualdo Del; Parizel, Paul M.; Mallio, Carlo Augusto

doi:10.21037/qims-21-945

Cited by 23 publications

(10 citation statements)

References 54 publications

(69 reference statements)

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“…Body composition imaging is a novel concept based on quantitative analysis of body tissues. Machine learning is a group of techniques that extrapolate or classify data through complex mathematical models [ 44 ].…”

Section: Discussionmentioning

confidence: 99%

Cardiac Computed Tomography Evaluation of Association of Left Ventricle Disfunction and Epicardial Adipose Tissue Density in Patients with Low to Intermediate Cardiovascular Risk

et al. 2023

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Background and objectives: Epicardial adipose tissue density (EAD) has been associated with coronary arteries calcium score, a higher load of coronary artery disease (CAD) and plaque vulnerability. This effect can be related to endocrine and paracrine effect of molecules produced by epicardial adipose tissue (EAT), that may influence myocardial contractility. Using coronary computed tomography angiography (CCT) the evaluation of EAD is possible in basal scans. The aim of the study is to investigate possible associations between EAD and cardiac function. Material and Methods: 93 consecutive patients undergoing CCT without and with contrast medium for known or suspected coronary CAD were evaluated. EAD was measured on basal scans, at the level of the coronary ostia, the lateral free wall of the left ventricle, at the level of the cardiac apex, and at the origin of the posterior interventricular artery. Cardiac function was evaluated in post-contrast CT scans in order to calculate ejection fraction (EF), end-diastolic volume (EDV), end-systolic volume (ESV), and stroke volume (SV). Results: A statistically significant positive correlation between EAD and ejection fraction (r = 0.29, p-value < 0.01) was found. Additionally, a statistically significant negative correlation between EAD and ESV (r = −0.25, p-value < 0.01) was present. Conclusion: EAD could be considered a new risk factor associated with reduced cardiac function. The evaluation of this parameter with cardiac CT in patients with low to intermediate cardiovascular risk is possible.

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Section: Discussionmentioning

confidence: 99%

Cardiac Computed Tomography Evaluation of Association of Left Ventricle Disfunction and Epicardial Adipose Tissue Density in Patients with Low to Intermediate Cardiovascular Risk

et al. 2023

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“…Recent evidence supports the crucial involvement of EAT accumulation in the pathogenesis of AF and coronary artery disease ( 15 , 25 ). The emergence of automatic segmentation models based on CT angiography and CACS scans has significantly advanced research on the relationship between EAT and cardiovascular adverse events, such as myocardial infarction ( 10 , 11 , 26 , 27 ). However, the investigation into the association between EAT and AF still lacks validation from large-scale cohorts ( 16 , 28 , 29 ).…”

Section: Discussionmentioning

confidence: 99%

Automatic epicardial adipose tissue segmentation in pulmonary computed tomography venography using nnU-Net

Hu,

Jiang,

et al. 2023

Quant Imaging Med Surg

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Background Epicardial adipose tissue (EAT) is a key aspect in the investigation of cardiac pathophysiology. We sought to develop a deep learning (DL) model for fully automatic extraction and quantification of EAT through pulmonary computed tomography venography (PCTV) images. Methods In this retrospective study, we included 128 patients with atrial fibrillation and PCTV from 2 hospitals. A DL model for automated EAT segmentation was developed from a training set of 51 patients and a validation set of 13 patients from hospital A. The algorithm was further validated using an internal test set of 16 patients from hospital A and an external test set of 48 patients from hospital B. The consistency and measurement agreement of EAT quantification were compared between the DL model and the conventional manual protocol using the Dice score coefficient (DSC), Hausdorff distance (HD95), Pearson correlation coefficient, and Bland-Altman plot. Results In the internal and external test set, automated segmentation with DL was successful in all cases. The total analysis time was shorter for DL than for manual reconstruction (5.43±2.52 vs. 106.20±15.90 min; P<0.001). The EAT segmented with the DL model had good consistency with manual segmentation (the DSC of the internal and external test sets were 0.92±0.02 and 0.88±0.03, respectively). The quantification of EAT evaluated with the 2 methods showed excellent correlation (all correlation coefficients >0.9; all P values <0.001) and minimal measurement difference. Conclusions The proposed DL model achieved fully automatic quantification of EAT from PCTV images. The yielded results were highly consistent with those of manual quantification.

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“…Using this method to diagnose prostate disease could reduce the number of unnecessary biopsy procedures and prevent overdiagnosis. With the development of artificial intelligence (AI), it will integrate MRI with PI-RADS, elastography, and clinical laboratory data such as PSA, fPSA, e.g., to automate and rapidly obtain high-quality information to assist in clinical decision, like AI working in other areas of medical imaging (25).…”

Section: Discussionmentioning

confidence: 99%

Assessment of elastographic Q-analysis score combined with Prostate Imaging-Reporting and Data System (PI-RADS) based on transrectal ultrasound (TRUS)/multi-parameter magnetic resonance imaging (MP-MRI) fusion-guided biopsy in differentiating benign and malignant prostate

Tian

Ding

et al. 2022

Quant Imaging Med Surg

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Background: Magnetic resonance imaging (MRI) has advantages in the diagnosis of prostate diseases, but there is also overdiagnosis. We compensate for this with fusion imaging and elastography. In this study, we want to evaluate Elastographic Q-analysis score (EQS) combined with Prostate Imaging Reporting and Data System (PI-RADS), based on transrectal ultrasound (TRUS)/multi-parameter magnetic resonance imaging (MP-MRI) fusion biopsy in differentiating benign and malignant prostate lesions.Methods: A total of 296 patients with 318 prostate lesions who underwent TRUS/MP-MRI fusion biopsy between October 2017 and October 2019 were retrospectively analysed. The performance of the EQS was evaluated on the sites of the suspicious areas of MP-MRI. The cut-off value of EQS was obtained according to receiver operating characteristic (ROC) curve, which was used to upgrade and downgrade the PI-RADS scores. The area under the curve (AUC), integrated discrimination improvement, and decision curve analysis were used to assess the new PI-RADS performance.Results: In total, 318 MP-MRI suspicious prostate lesions (94 malignant vs. 224 benign lesions). The EQS optimal threshold was 1.85, and the AUC was 0.816. All cases were constructed three models by using 1.85 as the cut-off value: upgrade-PI-RADS, downgrade-PI-RADS and complex-PI-RADS. The AUC of PI-RADS, upgrade-PI-RADS, downgrade-PI-RADS and complex-PI-RADS were 0.869, 0.867, 0.872 and 0.873 respectively. The diagnostic coincidence rate of PI-RADS was increased from 0.667 to 0.874 by using strain elastography, among which the diagnostic rate of prostate cancer was increased from 0.557 to 0.806, and the diagnostic rate of non-prostate cancer was increased from 0.775 to 0.967. The integrated discrimination improvement indicated that downgrade-PI-RADS had a better diagnostic capability (P<0.05). The net benefit of all models, which downgrade-PI-RADS can maximize the net benefit value of patients by decision curve analysis. Conclusions:The combination of PI-RADS and EQS with TRUS/MP-MRI fusion, particularly downgrade-PI-RADS, can reduce unnecessary biopsy procedures and prevent overdiagnosis.

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Epicardial and pericardial fat analysis on CT images and artificial intelligence: a literature review

Cited by 23 publications

References 54 publications

Cardiac Computed Tomography Evaluation of Association of Left Ventricle Disfunction and Epicardial Adipose Tissue Density in Patients with Low to Intermediate Cardiovascular Risk

Cardiac Computed Tomography Evaluation of Association of Left Ventricle Disfunction and Epicardial Adipose Tissue Density in Patients with Low to Intermediate Cardiovascular Risk

Automatic epicardial adipose tissue segmentation in pulmonary computed tomography venography using nnU-Net

Assessment of elastographic Q-analysis score combined with Prostate Imaging-Reporting and Data System (PI-RADS) based on transrectal ultrasound (TRUS)/multi-parameter magnetic resonance imaging (MP-MRI) fusion-guided biopsy in differentiating benign and malignant prostate

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