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Sub-aortic Complex is a Simple and Accurate Parameter to Predict Obstruction in Hypertrophic Cardiomyopathy: A CMR and Doppler Study1Department of Radiology, The First Hospital of Lanzhou University, Intelligent Imaging Medical Engineering Research Center of Gansu Province, Accurate Image Collaborative Innovation International Science and Technology Cooperation Base of Gansu Province, Radiological Clinical Medicine Research Center of Gansu Province, Lanzhou, China, 2Radiology, The First Hospital of Lanzhou University, Intelligent Imaging Medical Engineering Research Center of Gansu Province, Accurate Image Collaborative Innovation International Science and Technology Cooperation Base of Gansu Province, Radiological Clinical Medicine Research Center of Gansu Province, Lanzhou, China, 3Department of Cardiology, The first Hospital of Lanzhou University, Lanzhou, China, 4Department of Magnetic Resonance Imaging, Cardiovascular Imaging and Intervention Center, State Key Laboratory of Cardiovascular Disease，Fuwai Hospital, National Center for Cardiovascular Diseases，Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
Synopsis
To investigate the “sub-aortic complex (SAC)”, a new cardiac magnetic resonance (CMR) derived parameter, for the detection and grading of left ventricular outflow tract (LVOT) obstruction in hypertrophic cardiomyopathy (HCM) patients, compared with echocardiography and CMR 2D flow.
Methods
157 consecutive patients with HCM were retrospectively enrolled. The SAC parameters（D1, D2 and D3）were measured on the LV 3-chamber steady-state free precession (SSFP) cine imaging at the end-systolic phase. The relations between the existence and severity of hemodynamic obstruction and SAC index (SACi) were evaluated by Pearson correlation coefficient, receiver operating characteristic (ROC) curves and logistic regressions.Results
The SAC were well correlated with anterior mitral valve leaflet (AMVL) length (R=0.33, p<0.001)and LVOT diameter(R=0.48, p<0.001). The ROC curves indicated that SACi was able to discriminate the obstructive and non-obstructive patients with the best predictive accuracy (AUC=0.949, p<0.001). The cutoff value of 0.424 yielding a sensitivity and specificity of 94.3% and 87.4%, respectively. Further Spearman correlation analysis demonstrated significant inverse relationship between SACi (R=0.86 p<0.001), CMR PG (R=0.43, p<0.001 ) and the resting LVOT pressure gradient.Conclusion
The SACi is a simple and accurate parameter, which can detect LVOT obstruction. It was also better than the relatively low temporal resolution CMR 2D to detect and grade the severity of obstruction in patients with HCM.Acknowledgements
This work was also partially supported by the Division of Intramural Research, National Heart, Lung and Blood Institute, National Institutes of Health, USA.References
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