Sei Hyun Chun1, Young Joo Suh2, Kyunghwa Han1, Sang Joon Park3, Chi Young Shim4, Geu-Ru Hong4, Sak Lee5, Seung-Hyun Lee5, Young Jin Kim1, Byoung Wook Choi1. 1. Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea. 2. Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea. rongzusuh@gmail.com. 3. Department of Radiology, Seoul National University College of Medicine, Institute of Radiation Medicine, Seoul National University Medical Research Center, Cancer Research Institute, Seoul National University, Seoul, Republic of Korea. 4. Division of Cardiology, Department of Internal Medicine, Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea. 5. Department of Cardiothoracic Surgery, Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
Abstract
OBJECTIVES: To determine whether quantitative radiomic features from cardiac CT could differentiate the left atrial appendage (LAA) thrombus from circulatory stasis in patients with valvular heart disease. METHODS: Ninety-five consecutive patients with valvular heart disease and filling defects in LAA on two-phase cardiac CT from March 2016 to August 2018 were retrospectively enrolled and classified as having thrombus or stasis by transesophageal echocardiography or cardiac surgery. The ratio of Hounsfield units in the filling defects to those in the ascending aorta (AA) was calculated on early- and late-phase CT (LAA/AAE and LAA/AAL, respectively). Radiomic features were extracted from semi-automated three-dimensional segmentation of the filling defect on early-phase CT. The diagnostic ability of radiomic features for differentiating thrombus from stasis was assessed and compared to LAA/AAE and LAA/AAL by comparing the AUC of ROC curves. Diagnostic performances of CT attenuation ratios and radiomic features were validated with an independent validation set. RESULTS: Thrombus was diagnosed in 25 cases and stasis in 70. Sixty-eight radiomic features were extracted. Values of 8 wavelet-transformed features were lower in thrombus than in stasis (p < 0.001). The AUC value of a radiomic feature, wavelet_LHL, for diagnosing thrombus was 0.78, which was higher than that of LAA/AAE (AUC = 0.54, p = 0.025) and similar to that of LAA/AAL (AUC = 0.76, p = 0.773). In the validation set, the AUC of wavelet_LHL was 0.71, which was higher than that of LAA/AAE (AUC = 0.57, p = 0.391) and similar to that of LAA/AAL (AUC = 0.75, p = 0.707). CONCLUSIONS: Quantitative radiomic features from the early phase of cardiac CT may help diagnose LAA thrombus in patients with valvular heart disease. KEY POINTS: • Wavelet-transformed grey-level non-uniformity values from radiomic analysis are significantly lower for LAA thrombus than for circulatory stasis. • Radiomic features may have an additional value for differentiating LAA thrombus from circulatory stasis when interpreting single-phase cardiac CT. • Radiomic features extracted from single-phase images may show similar diagnostic ability as conventional quantitative analysis from two-phase images.
OBJECTIVES: To determine whether quantitative radiomic features from cardiac CT could differentiate the left atrial appendage (LAA) thrombus from circulatory stasis in patients with valvular heart disease. METHODS: Ninety-five consecutive patients with valvular heart disease and filling defects in LAA on two-phase cardiac CT from March 2016 to August 2018 were retrospectively enrolled and classified as having thrombus or stasis by transesophageal echocardiography or cardiac surgery. The ratio of Hounsfield units in the filling defects to those in the ascending aorta (AA) was calculated on early- and late-phase CT (LAA/AAE and LAA/AAL, respectively). Radiomic features were extracted from semi-automated three-dimensional segmentation of the filling defect on early-phase CT. The diagnostic ability of radiomic features for differentiating thrombus from stasis was assessed and compared to LAA/AAE and LAA/AAL by comparing the AUC of ROC curves. Diagnostic performances of CT attenuation ratios and radiomic features were validated with an independent validation set. RESULTS:Thrombus was diagnosed in 25 cases and stasis in 70. Sixty-eight radiomic features were extracted. Values of 8 wavelet-transformed features were lower in thrombus than in stasis (p < 0.001). The AUC value of a radiomic feature, wavelet_LHL, for diagnosing thrombus was 0.78, which was higher than that of LAA/AAE (AUC = 0.54, p = 0.025) and similar to that of LAA/AAL (AUC = 0.76, p = 0.773). In the validation set, the AUC of wavelet_LHL was 0.71, which was higher than that of LAA/AAE (AUC = 0.57, p = 0.391) and similar to that of LAA/AAL (AUC = 0.75, p = 0.707). CONCLUSIONS: Quantitative radiomic features from the early phase of cardiac CT may help diagnose LAA thrombus in patients with valvular heart disease. KEY POINTS: • Wavelet-transformed grey-level non-uniformity values from radiomic analysis are significantly lower for LAA thrombus than for circulatory stasis. • Radiomic features may have an additional value for differentiating LAA thrombus from circulatory stasis when interpreting single-phase cardiac CT. • Radiomic features extracted from single-phase images may show similar diagnostic ability as conventional quantitative analysis from two-phase images.
Authors: Valentin Fuster; Lars E Rydén; Davis S Cannom; Harry J Crijns; Anne B Curtis; Kenneth A Ellenbogen; Jonathan L Halperin; G Neal Kay; Jean-Yves Le Huezey; James E Lowe; S Bertil Olsson; Eric N Prystowsky; Juan Luis Tamargo; L Samuel Wann; Sidney C Smith; Silvia G Priori; N A Mark Estes; Michael D Ezekowitz; Warren M Jackman; Craig T January; James E Lowe; Richard L Page; David J Slotwiner; William G Stevenson; Cynthia M Tracy; Alice K Jacobs; Jeffrey L Anderson; Nancy Albert; Christopher E Buller; Mark A Creager; Steven M Ettinger; Robert A Guyton; Jonathan L Halperin; Judith S Hochman; Frederick G Kushner; Erik Magnus Ohman; William G Stevenson; Lynn G Tarkington; Clyde W Yancy Journal: Circulation Date: 2011-03-07 Impact factor: 29.690