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Objective: We present a novel pipeline that consists of various algorithms for the estimation of the cardiac output (CO) during ventricular assist devices (VADs) support using a single pump inlet pressure (PIP) sensor as well as pump intrinsic signals. Methods: A machine learning (ML) model was constructed for the prediction of the aortic valve opening status. When a closed aortic valve is detected, the estimated CO equals the estimated pump flow. Otherwise, the estimated CO equals the sum of the estimated pump flow and the aortic valve flow, estimated via a Kalman-filter approach. Both the pathophysiological conditions and the pump speed of an in-vitro test bench were adjusted in various combinations to evaluate the performance of the pipeline, as well as the individual estimators. Results: The ML model yielded a Matthews correlation coefficient of 0.771, a sensitivity of 0.913 and a specificity of 0.871. An overall CO root mean square error (RMSE) of 0.69 L/min was achieved. Replacing the pump flow and aortic pressure estimators with sensors would decrease the RMSE below 0.5 L/min. Conclusion: The performance of the proposed pipeline is considered the state of the art for VADs with an integrated PIP sensor. The effect of the individual estimators on the overall performance of the pipeline was thoroughly investigated and their limitations were identified for future research. Significance: The clinical application of the proposed solution could provide the clinicians with essential information about the interaction between the patient's heart and the VAD to further improve the VAD therapy.

We report a case of a 35-year-old active duty male with a rare quadricuspid aortic valve identified via transthoracic echocardiography following the detection of an incidental grade I/VI diastolic murmur. Further characterization of the anatomical findings and aortic valve flow dynamics were evaluated with cardiac magnetic resonance imaging. Accurate assessment of the various valve morphologies is essential, as it guides surgical treatment options to correct the defect. Our case highlights the complimentary role of cardiac magnetic resonance imaging in defining the anatomy and functional consequences of a quadricuspid aortic valve.

Estudou-se o fluxo sangüíneo através das quatro valvas cardíacas em 30 gatos clinicamente sadios, com idade entre um e cinco anos e peso médio de 4,08kg, por meio da ecocardiografia modo Doppler pulsado. Foram medidas a velocidade máxima e a velocidade média dos fluxos, e realizou-se uma análise qualitativa dos seus perfis. Os animais foram sedados pela combinação de quetamina (12mg/kg) e acepromazina (0,04mg/kg), aplicados por via intramuscular. Observou-se correlação positiva entre os parâmetros avaliados e a freqüência cardíaca, com exceção daqueles medidos no fluxo da valva aórtica. Não se observou correlação entre velocidades máxima e média e freqüência cardíaca e entre aquelas e peso corporal, e não houve diferença entre sexos. Pulsed wave Doppler echocardiography was used to study blood flow across the cardiac valves in 30 five-year-old cats (average body weight = 4.08kg). Animals were sedated using a combination of ketamin (12mg/kg, IM) and acepromazin (0.04mg/kg, IM). Peak and mean velocities were determined, and blood flow patterns were recorded at the four cardiac valves. All variables, except those characterizing aortic valve flow, were positively correlated with heart rate. Blood flow variables were not correlated, however, with body weight; and there were no differences between males and females.

BACKGROUND An exaggerated decrease in diastolic blood pressure (DBP) upon raising the upper extremity is a sign of severe chronic aortic regurgitation (AR) (Mayne's sign). However, this finding was proposed prior to the widespread use of Doppler echocardiography. OBJECTIVE To determine the relation between Doppler echo determined AR and changes in DBP. METHODS We prospectively studied 30 controls without AR and 40 patients (69±15 years) with AR ranging from mild to severe and measured DBP before and during upper extremity raising. RESULTS The change in DBP was inversely correlated with age (r=-0.41, P

Phase contrast MRI is an emerging tool for evaluating valvular pathology. However, the effects of variable image position and valvular pathology on velocity measurements have not been explored. We compare velocity maps with correlation methods, used in image processing to align images and quantify their similarity, to define these effects on calculations of valve orifice area. Quantitative flow images were acquired in four parallel planes (2 in aortic root, 2 in outflow tract), in patients (n = 22) with aortic stenosis. Velocity-time integrals (VTIs) were computed and cross-correlations were performed to quantitatively compare the shapes and relative positions of three-dimensional flow profiles between scans at various positions. Supravalvular VTIs correlated well with one another (R = 0.96), with comparable values. The two subvalvular VTIs exhibited a linear relationship (R = 0.93) but with a 23% difference in mean values. Cross-correlations between supravalvular levels were maximized at (0, 0) offset (indicating concentrically aligned jets) for 19/23 patients, with an average maximum value of 0.957 +/- 0.028; the average for the remainder was 0.800 +/- 0.037. For subvalvular levels, all cross-correlations were maximized at (0, 0) with average maximum 0.968 +/- 0.160. The aortic VTI measurements were comparable, indicating relative insensitivity to the position of the imaging plane; in the LVOT, measurements were only somewhat position-dependent. We conclude that phase contrast MRI is a robust tool for the evaluation of aortic stenosis.