Objective: Myocardial extracellular volume (ECV) fraction is an important imaging biomarker in clinical decision-making. CT-ECV is a potential alternative to MRI for ECV quantification. We conducted a meta-analysis to comprehensively assess the reliability of CT for ECV quantification with MRI as a reference.
Methods: We systematically searched PubMed, EMBASE, and the Cochrane Library for relevant articles published since the establishment of the database in July 2022. The articles comparing CT-ECV with MRI as a reference were included. Meta-analytic methods were applied to determine the pooled weighted bias, limits of agreement (LOA), and correlation coefficient (r) between CT-ECV and MRI-ECV.
Results: Seventeen studies with a total of 459 patients and 2231 myocardial segments were included. The pooled mean difference (MD), LOA, and r for ECV quantification at the per-patient level was (0.07%; 95% LOA: - 0.42 to 0.55%) and 0.89 (95% CI: 0.86-0.91), respectively, while on the per-segment level was (0.44%; 95% LOA: 0.16-0.72%) and 0.84 (95% CI: 0.82-0.85), respectively. The pooled r from studies with the ECV method for ECV quantification was significantly higher compared to those with the ECV method (0.94 (95% CI: 0.91-0.96) vs. 0.84 (95% CI: 0.80-0.88), respectively, p = 0.03). The pooled r from septal segments was significantly higher than those from non-septal segments (0.88 (95% CI: 0.86-0.90) vs. 0.76 (95% CI: 0.71-0.90), respectively, p = 0.009).
Conclusion: CT showed a good agreement and excellent correlation with MRI for ECV quantification and is a potentially attractive alternative to MRI.
Clinical Relevance Statement: The myocardial extracellular volume fraction can be acquired using a CT scan, which is not only a viable alternative to myocardial extracellular volume fraction derived from MRI but is also less time-consuming and costly for patients.
Key Points: • Noninvasive CT-ECV is a viable alternative to MRI-ECV for ECV quantification. • CT-ECV using the ECV method showed more accurate myocardial ECV quantification than ECV. • Septal myocardial segments showed lower measurement variability than non-septal segments for the ECV quantification.
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http://dx.doi.org/10.1007/s00330-023-09872-x | DOI Listing |
Eur Radiol
December 2024
Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Objectives: To develop and validate deep learning (DL)-models that denoise late iodine enhancement (LIE) images and enable accurate extracellular volume (ECV) quantification.
Methods: This study retrospectively included patients with chest discomfort who underwent CT myocardial perfusion + CT angiography + LIE from two hospitals. Two DL models, residual dense network (RDN) and conditional generative adversarial network (cGAN), were developed and validated.
Eur Radiol
December 2024
Department of Radiology, Qilu Hospital, Shandong University, Jinan, China.
Objectives: To analyze the performance of multiparametric magnetic resonance imaging (MRI) in quantification of pancreatic ductal adenocarcinoma (PDAC) fibrosis grading.
Method: This prospective study enrolled 79 patients with PDAC confirmed by pathology. Multiparametric MRI including native T1 mapping, intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI), diffusion kurtosis imaging diffusion-weighted imaging (DKI-DWI), and enhanced T1 mapping were performed before surgery.
Front Cardiovasc Med
December 2024
Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, United States.
Purpose: Evaluate the feasibility of quantification of Relaxation Along a Fictitious Field in the 2nd rotating frame (RAFF2) relaxation times in the human myocardium at 3 T.
Methods: mapping was performed using a breath-held ECG-gated acquisition of five images: one without preparation, three preceded by RAFF2 trains of varying duration, and one preceded by a saturation prepulse. Pixel-wise maps were obtained after three-parameter exponential fitting.
Eur J Nucl Med Mol Imaging
November 2024
Department of Nuclear Medicine, The Third Xiangya Hospital, Central South University, Changsha, China.
Purpose: To evaluate right ventricular (RV) uptake measured by quantitative [Tc]Tc-DPD SPECT/CT to investigate its role in predicting and evaluating prognosis and therapeutic outcomes in patients with transthyretin amyloid cardiomyopathy (ATTR-CA).
Methods: Patients with ATTR-CA were consecutively enrolled for quantitative [Tc]Tc-DPD SPECT/CT. Ventricular amyloid burden was quantified by SUV and TBR.
J Cardiovasc Dev Dis
October 2024
Department of Diagnostic Radiology, Yokohama City University Graduate School of Medicine, Yokohama 236-0004, Kanagawa, Japan.
Background: The utility of synthetic ECV, which does not require hematocrit values, has been reported; however, high-quality CT images are essential for accurate quantification. Second-generation Deep Learning Reconstruction (DLR) enables low-noise and high-resolution cardiac CT images. The aim of this study is to compare the differences among four reconstruction methods (hybrid iterative reconstruction (HIR), model-based iterative reconstruction (MBIR), DLR, and second-generation DLR) in the quantification of synthetic ECV.
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