Professor of Radiology (Veterans Affairs)


Daniel Ennis {he/him} is a Professor in the Department of Radiology. As an MRI scientist for nearly twenty years, he has worked to develop advanced translational cardiovascular MRI methods for quantitatively assessing structure, function, flow, and remodeling in both adult and pediatric populations. He began his research career as a Ph.D. student in the Department of Biomedical Engineering at Johns Hopkins University during which time he formed an active collaboration with investigators in the Laboratory of Cardiac Energetics at the National Heart, Lung, and Blood Institute (NIH/NHLBI). Thereafter, he joined the Departments of Radiological Sciences and Cardiothoracic Surgery at Stanford University as a postdoc and began to establish an independent research program with an NIH K99/R00 award focused on “Myocardial Structure, Function, and Remodeling in Mitral Regurgitation.” For ten years he led a group of clinicians and scientists at UCLA working to develop and evaluate advanced cardiovascular MRI exams as PI of several NIH funded studies. In 2018 he returned to the Department of Radiology at Stanford University as faculty in the Radiological Sciences Lab to bolster programs in cardiovascular MRI. He is also the Director of Radiology Research for the Veterans Administration Palo Alto Health Care System where he oversees a growing radiology research program.


  • Hemodynamic Effects of Entry Versus Exit Tear Size and Tissue Stiffness in Simulations of Aortic Dissection Baumler, K., Zimmermann, J., Ennis, D. B., Marsden, A. L., Fleischmann, D., Tavares, J. M., Bourauel, C., Geris, L., Slote, J. V. SPRINGER INTERNATIONAL PUBLISHING AG. 2023: 143-152
  • 4D flow cardiovascular magnetic resonance recovery profiles following pulmonary endarterectomy in chronic thromboembolic pulmonary hypertension. Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Dong, M. L., Azarine, A., Haddad, F., Amsallem, M., Kim, Y., Yang, W., Fadel, E., Aubrege, L., Loecher, M., Ennis, D., Pavec, J. L., Vignon-Clementel, I., Feinstein, J. A., Mercier, O., Marsden, A. L. 2022; 24 (1): 59


    BACKGROUND: Four-dimensional flow cardiovascular magnetic resonance imaging (4D flow CMR) allows comprehensive assessment of pulmonary artery (PA) flow dynamics. Few studies have characterized longitudinal changes in pulmonary flow dynamics and right ventricular (RV) recovery following a pulmonary endarterectomy (PEA) for patients with chronic thromboembolic pulmonary hypertension (CTEPH). This can provide novel insights of RV and PA dynamics during recovery. We investigated the longitudinal trajectory of 4D flow metrics following a PEA including velocity, vorticity, helicity, and PA vessel wall stiffness.METHODS: Twenty patients with CTEPH underwent pre-PEA and >6 months post-PEA CMR imaging including 4D flow CMR; right heart catheter measurements were performed in 18 of these patients. We developed a semi-automated pipeline to extract integrated 4D flow-derived main, left, and right PA (MPA, LPA, RPA) volumes, velocity flow profiles, and secondary flow profiles. We focused on secondary flow metrics of vorticity, volume fraction of positive helicity (clockwise rotation), and the helical flow index (HFI) that measures helicity intensity.RESULTS: Mean PA pressures (mPAP), total pulmonary resistance (TPR), and normalized RV end-systolic volume (RVESV) decreased significantly post-PEA (P<0.002). 4D flow-derived PA volumes decreased (P<0.001) and stiffness, velocity, and vorticity increased (P<0.01) post-PEA. Longitudinal improvements from pre- to post-PEA in mPAP were associated with longitudinal decreases in MPA area (r=0.68, P=0.002). Longitudinal improvements in TPR were associated with longitudinal increases in the maximum RPA HFI (r=-0.85, P<0.001). Longitudinal improvements in RVESV were associated with longitudinal decreases in MPA fraction of positive helicity (r=0.75, P=0.003) and minimum MPA HFI (r=-0.72, P=0.005).CONCLUSION: We developed a semi-automated pipeline for analyzing 4D flow metrics of vessel stiffness and flow profiles. PEA was associated with changes in 4D flow metrics of PA flow profiles and vessel stiffness. Longitudinal analysis revealed that PA helicity was associated with pulmonary remodeling and RV reverse remodeling following a PEA.

    View details for DOI 10.1186/s12968-022-00893-x

    View details for PubMedID 36372884

  • Electrohydraulic Vascular Compression Device (e-VaC) with Integrated Sensing and Controls ADVANCED MATERIALS TECHNOLOGIES Pirozzi, I., Kight, A., Liang, X., Han, A., Ennis, D. B., Hiesinger, W., Dual, S. A., Cutkosky, M. R. 2022
  • Accelerated two-dimensional phase-contrast for cardiovascular MRI using deep learning-based reconstruction with complex difference estimation. Magnetic resonance in medicine Oscanoa, J. A., Middione, M. J., Syed, A. B., Sandino, C. M., Vasanawala, S. S., Ennis, D. B. 2022


    PURPOSE: To develop and validate a deep learning-based reconstruction framework for highly accelerated two-dimensional (2D) phase contrast (PC-MRI) data with accurate and precise quantitative measurements.METHODS: We propose a modified DL-ESPIRiT reconstruction framework for 2D PC-MRI, comprised of an unrolled neural network architecture with a Complex Difference estimation (CD-DL). CD-DL was trained on 155 fully sampled 2D PC-MRI pediatric clinical datasets. The fully sampled data ( n = 29

  • Validation of the Reduced Unified Continuum Formulation Against In Vitro 4D-Flow MRI. Annals of biomedical engineering Lan, I. S., Liu, J., Yang, W., Zimmermann, J., Ennis, D. B., Marsden, A. L. 2022


    We previously introduced and verified the reduced unified continuum formulation for vascular fluid-structure interaction (FSI) against Womersley's deformable wall theory. Our present work seeks to investigate its performance in a patient-specific aortic setting in which assumptions of idealized geometries and velocity profiles are invalid. Specifically, we leveraged 2D magnetic resonance imaging (MRI) and 4D-flow MRI to extract high-resolution anatomical and hemodynamic information from an in vitro flow circuit embedding a compliant 3D-printed aortic phantom. To accurately reflect experimental conditions, we numerically implemented viscoelastic external tissue support, vascular tissue prestressing, and skew boundary conditions enabling in-plane vascular motion at each inlet and outlet. Validation of our formulation is achieved through close quantitative agreement in pressures, lumen area changes, pulse wave velocity, and early systolic velocities, as well as qualitative agreement in late systolic flow structures. Our validated suite of FSI techniques offers a computationally efficient approach for numerical simulation of vascular hemodynamics. This study is among the first to validate a cardiovascular FSI formulation against an in vitro flow circuit involving a compliant vascular phantom of complex patient-specific anatomy.

    View details for DOI 10.1007/s10439-022-03038-4

    View details for PubMedID 35963921