Automated Dual-energy Computed Tomography-based Extracellular Volume Estimation for Myocardial Characterization in Patients With Ischemic and Nonischemic Cardiomyopathy

医学 计算机断层摄影术 心肌病 细胞外液 缺血性心肌病 核医学 心脏病学 放射科 双重能量 断层摄影术 内科学 细胞外 心力衰竭 射血分数 细胞生物学 生物 骨质疏松症 骨矿物
作者
Andres F. Abadia,Gilberto J. Aquino,U. Joseph Schoepf,Michael Wels,Bernhard Schmidt,Pooyan Sahbaee,Danielle M. Dargis,Jeremy R. Burt,Ákos Varga‐Szemes,Tilman Emrich
出处
期刊:Journal of Thoracic Imaging [Lippincott Williams & Wilkins]
卷期号:37 (5): 307-314 被引量:7
标识
DOI:10.1097/rti.0000000000000656
摘要

Objectives: We aimed to validate and test a prototype algorithm for automated dual-energy computed tomography (DECT)-based myocardial extracellular volume (ECV) assessment in patients with various cardiomyopathies. Methods: This retrospective study included healthy subjects (n=9; 61±10 y) and patients with cardiomyopathy (n=109, including a validation cohort n=60; 68±9 y; and a test cohort n=49; 69±11 y), who had previously undergone cardiac DECT. Myocardial ECV was calculated using a prototype-based fully automated algorithm and compared with manual assessment. Receiver-operating characteristic analysis was performed to test the algorithm’s ability to distinguish healthy subjects and patients with cardiomyopathy. Results: The fully automated method led to a significant reduction of postprocessing time compared with manual assessment (2.2±0.4 min and 9.4±0.7 min, respectively, P <0.001). There was no significant difference in ECV between the automated and manual methods ( P =0.088). The automated method showed moderate correlation and agreement with the manual technique ( r =0.68, intraclass correlation coefficient=0.66). ECV was significantly higher in patients with cardiomyopathy compared with healthy subjects, regardless of the method used ( P <0.001). In the test cohort, the automated method yielded an area under the curve of 0.98 for identifying patients with cardiomyopathies. Conclusion: Automated ECV estimation based on DECT showed moderate agreement with the manual method and matched with previously reported ECV values for healthy volunteers and patients with cardiomyopathy. The automatically derived ECV demonstrated an excellent diagnostic performance to discriminate between healthy and diseased myocardium, suggesting that it could be an effective initial screening tool while significantly reducing the time of assessment.
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