OBJECTIVES: Atrial thrombi are a potential source for cerebral and peripheral emboli. Objective of this study was to evaluate the diagnostic accuracy of 64-slice cardiac computed tomography (CT) for detection of atrial thrombi in comparison with transesophageal echocardiography (TEE) and cardiac surgery. MATERIAL AND METHODS: Sixty-four patients were examined with ECG-gated multidetector CT coronary or pulmonary vein angiography. All patients underwent TEE. Cardiac surgery was performed in 31 patients. The Hounsfield units (HU) of atrial lesions were measured. RESULTS: The diagnostic accuracy of 64-slice CT for the detection of atrial thrombi was 77%: sensitivity 100% (9/9), specificity 73% (40/55), positive predictive value (PPV) 38% (9/24), and negative predictive value (NPV) 100% (40/40). All 15 false positive (FP) findings by CT were located in the left atrial appendage (LAA). Four characteristic imaging features suggesting incomplete filling of the LAA were noted in FP: "hypostatic layering," 5/15 (33%); "flow phenomenon," 9/15 (60%); "HU-run-off," 8/15 (53%); higher intralesional HU in FP when compared with thrombi (153.8 HU +/- 71 vs. 46.6 HU +/- 10; P < 0.0001). The diagnostic accuracy of CT in detecting atrial thrombi improved significantly (P = 0.03) to 86% after defining "typical filling defects" as "flow phenomenon/>180 HU" (sensitivity 100%; specificity 84%; PPV 50%; NPV 100%). On receiver operating curve (ROC) analysis, a threshold of 60.7 HU showed a specificity of 100% and a sensitivity of 86.7% to distinguish between FP and thrombi. CONCLUSIONS: Cardiac ECG-gated 64-slice CT is accurate to exclude atrial thrombi, which can be applied eg, in patients before radiofrequency (RF) ablation. Left atrial appendage "filling defects" cause a high number of false positive findings, and there are radiologic features, which are helpful to differentiate them from true thrombi.
OBJECTIVES:Atrial thrombi are a potential source for cerebral and peripheral emboli. Objective of this study was to evaluate the diagnostic accuracy of 64-slice cardiac computed tomography (CT) for detection of atrial thrombi in comparison with transesophageal echocardiography (TEE) and cardiac surgery. MATERIAL AND METHODS: Sixty-four patients were examined with ECG-gated multidetector CT coronary or pulmonary vein angiography. All patients underwent TEE. Cardiac surgery was performed in 31 patients. The Hounsfield units (HU) of atrial lesions were measured. RESULTS: The diagnostic accuracy of 64-slice CT for the detection of atrial thrombi was 77%: sensitivity 100% (9/9), specificity 73% (40/55), positive predictive value (PPV) 38% (9/24), and negative predictive value (NPV) 100% (40/40). All 15 false positive (FP) findings by CT were located in the left atrial appendage (LAA). Four characteristic imaging features suggesting incomplete filling of the LAA were noted in FP: "hypostatic layering," 5/15 (33%); "flow phenomenon," 9/15 (60%); "HU-run-off," 8/15 (53%); higher intralesional HU in FP when compared with thrombi (153.8 HU +/- 71 vs. 46.6 HU +/- 10; P < 0.0001). The diagnostic accuracy of CT in detecting atrial thrombi improved significantly (P = 0.03) to 86% after defining "typical filling defects" as "flow phenomenon/>180 HU" (sensitivity 100%; specificity 84%; PPV 50%; NPV 100%). On receiver operating curve (ROC) analysis, a threshold of 60.7 HU showed a specificity of 100% and a sensitivity of 86.7% to distinguish between FP and thrombi. CONCLUSIONS: Cardiac ECG-gated 64-slice CT is accurate to exclude atrial thrombi, which can be applied eg, in patients before radiofrequency (RF) ablation. Left atrial appendage "filling defects" cause a high number of false positive findings, and there are radiologic features, which are helpful to differentiate them from true thrombi.
Authors: Olga Lazoura; Tevfik F Ismail; Christopher Pavitt; Alistair Lindsay; Mona Sriharan; Michael Rubens; Simon Padley; Alison Duncan; Tom Wong; Edward Nicol Journal: Int J Cardiovasc Imaging Date: 2015-09-29 Impact factor: 2.357
Authors: Kenneth C Bilchick; Augustus Mealor; Jorge Gonzalez; Patrick Norton; David Zhuo; Pamela Mason; John D Ferguson; Rohit Malhotra; J Michael Mangrum; Andrew E Darby; John DiMarco; Klaus Hagspiel; John Dent; Christopher M Kramer; George J Stukenborg; Michael Salerno Journal: Heart Rhythm Date: 2015-09-01 Impact factor: 6.343
Authors: Sang Yun Lee; Jae Suk Baek; Gi Beom Kim; Bo Sang Kwon; Eun Jung Bae; Chung Il Noh; Jung Yun Choi; Hong Kuk Lim; Woong Han Kim; Jeong Ryul Lee; Yong Jin Kim Journal: Pediatr Cardiol Date: 2011-08-05 Impact factor: 1.655
Authors: Petr Kuchynka; Jana Podzimkova; Martin Masek; Lukas Lambert; Vladimir Cerny; Barbara Danek; Tomas Palecek Journal: Biomed Res Int Date: 2015-07-07 Impact factor: 3.411