Tom Y Zhao¹, Guy Elisha¹, Ethan M I Johnson², Sourav Halder¹, Ben C Smith², Bradley D Allen², Michael Markl², and Neelesh A Patankar^1
1Northwestern University, Evanston, IL, United States, ²Northwestern University, Chicago, IL, United States

We present a novel analysis of 4D flow MRI in the thoracic aorta that identifies fluid structure instabilities, which are elevated in a cohort of 117 suspected-aortopathy patients as compared to 100 healthy subjects, and which are predictive of later complications shown in a follow-up analysis for 72 patients in the cohort.

Elizabeth K. Weiss^1,2, Cynthia K. Rigsby³, Joshua D. Robinson³, Justin Baraboo^1,2, Liliana Ma^1,2, Mariana B. L. Falcão⁴, Christopher W. Roy⁴, Matthias Stuber⁴, and Michael Markl^1,2
1Biomedical Engineering, Northwestern University, Evanston, IL, United States, ²Radiology, Feinberg School of Medicine, Chicago, IL, United States, ³Medical Imaging, Lurie Children's Hospital, Chicago, IL, United States, ⁴Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland

The flexible reconstruction of 5D flow MRI data may be particularly beneficial in pediatric cases where cardiac cycle length varies greatly. We compared flow measurements from 5D flow and 2D phase contrast. 5D flow data was reconstructed using either a cardiac bin width of 40ms or that matching the 2D phase contrast reconstruction. We find excellent correlation of both 5D flow reconstructions with 2D phase contrast. There is overestimation of arterial flow measures by 5D flow, with most overestimation by the short temporal resolution reconstruction. Further study should additionally compare with 4D flow MRI.

Kyoung-Jin Park^1,2, Ho-Jin Ha³, Dong-Hyun Yang², Kang-Hyun Ryu⁴, Jae-Hun Lee¹, and Dong-Hyun Kim^1
1Electrical & Electronic Engineering, Yonsei university, Seoul, Korea, Republic of, ²Radiology (Cardiovascular Imaging), Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea, Republic of, ³Department of Mechanical and Biomedical Engineering, Kangwon National University, GANGWON-DO, Korea, Republic of, ⁴Radiology, Stanford University, Stanford, CA, United States

Compressed sensing (CS) technique has recently been used to accelerate long acquisition time in 4D Flow. However, it aggravates underestimation in velocity calculation and overestimation in turbulent kinetic energy (TKE) estimation, when under-sampling is applied. An asymmetric undersampling scheme method of the reference image and velocity encoding images could alleviate problems. The purpose of this paper is investigation of improving velocity and turbulence kinetic energy estimation with an asymmetric reduction for two motion encoding schemes (i.e., conventional 4D Flow vs ICOSA6 Flow)

Morgane Garreau^1,2, Thomas Puiseux^2,3, Ramiro Moreno^3,4, Solenn Toupin⁵, Daniel Giese⁶, Simon Mendez¹, and Franck Nicoud^1
1IMAG, Univ. Montpellier, CNRS UMR 5149, Montpellier, France, ²Spin Up, Toulouse, France, ³I2MC, INSERM/UPS UMR 1297, Toulouse, France, ⁴ALARA Expertise, Strasbourg, France, ⁵Siemens Healthcare France, Saint-Denis, France, ⁶Siemens Healthcare, Erlangen, Germany

Fully-sampled and accelerated (GRAPPA R=3 and compressed sensing R=7.6) 4D Flow MRI acquisitions were compared for velocity profiles, flow rates and peak velocities in a rigid cardiovascular phantom under complex pulsatile flow conditions. Compatible CFD simulations were performed under the same flow conditions as a complementary modality. Good agreement was found between the three MR techniques, but discrepancies relative to the principle of mass conservation were noticed. Even though CFD presents some limitations as well, it appears to be a useful tool to investigate these differences.

Isil Unal¹, Duygu Dengiz², Eva Peschke¹, Echard Quandt², Mona Salehi Ravesh¹, Mariya Pravdivtseva¹, Jan-Bernd Hövener¹, and Olav Jansen^1
1Section Biomedical Imaging, Molecular Imaging North Competence Center (MOIN CC), Department for Radiology and Neuroradiology, University Medical Center Schleswig-Holstein, Kiel, Germany, ²Institute for Materials Science, Faculty of Engineering, University of Kiel, Kiel, Germany

2D phase-contrast (PC) MRI or 4D flow MRI allows to quantify the blood flow in vivo. However, the accuracy of these methods is influenced by many parameters. To optimize and validate these methods, patient-derived vascular models are key. Here, 3D printing is revolutionizing the manufacturing process, but realistic wall properties are essential for meaningful results. In this study, commercial elastic printing materials were used to fabricate vascular models. A tensile test was applied to all samples. Then the effect of wall elasticity on flow was investigated with 2D PC and 4D flow MRI. Wall motion was quantified using CINE MRI.

Jorge Mariscal-Harana¹, Ciaran O'Hanlon¹, Carlota Asegurado Marquez¹, Marwenie Petalcorin¹, Reza Razavi^1,2, Andrew P King¹, Bram Ruijsink^1,2,3, and Esther Puyol-Antón^1
1School of Biomedical Engineering and Imaging Science, King's College London, London, United Kingdom, ²Department of Adult and Paediatric Cardiology, Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom, ³Department of Cardiology, Heart and Lung Division, University Medical Center Utrecht, Utrecht, Netherlands

Cardiovascular magnetic resonance (CMR) based flow volume quantification in the great thoracic vessels is used in the assessment of several cardiovascular diseases such as valvular regurgitation, cardiac shunts and vascular health. Clinically, flow volume quantification is often performed based on semi-automatic segmentation of a vessel throughout the cardiac cycle in a manually positioned 2D phase-contrast (PC) CMR plane. In this work, we proposed a quality-controlled AI-based framework for automatic flow quantification from a full CMR scan that includes automated view selection. Results show high accuracy in view selection and excellent agreement between manual and automated flow quantification analysis.

Maren Friederike Balks¹, Hiroyuki Saisho², Buntaro Fujita², Tim Schaller², Najla Sadat², Stephan Ensminger², Jörg Barkhausen¹, Alex Frydrychowicz¹, and Thekla Helene Oechtering^3
1Department of Radiology and Nuclear Medicine, Universität zu Lübeck, Lübeck, Germany, ²Department of Cardiac and Thoracic Vascular Surgery, Universität zu Lübeck, Lübeck, Germany, ³Department of Radiology, University of Wisconsin, Madison, WI, United States

Hemodynamic outcome after aortic valve replacement (AVR) seems dependent on the type of replacement. The impact of the surgical pathway (aortotomy) itself on hemodynamics is still unclear. We proposed an ex-vivo swine model for comprehensive evaluation of aortic hemodynamics after different types of AVR with 4D flow MRI. Postoperative flow changes could be attributed not only to the implanted valve but also to the aortotomy. The new neocuspidization Ozaki procedure compared favorably to a biological valve as it induced fewer secondary flow patterns. Among the three different AVR methods, the mechanical valve allowed for hemodynamics that most closely approached physiology.

Corina Kräuter^1,2, Ursula Reiter¹, Gabor Kovacs^3,4, Clemens Reiter¹, Marc Masana⁵, Horst Olschewski^3,4, Michael Fuchsjäger¹, Rudolf Stollberger², and Gert Reiter^1,6
1Department of Radiology, Medical University of Graz, Graz, Austria, ²Institute of Medical Engineering, Graz University of Technology, Graz, Austria, ³Department of Internal Medicine, Medical University of Graz, Graz, Austria, ⁴Ludwig Boltzmann Institute for Lung Vascular Research Graz, Graz, Austria, ⁵Institute of Computer Graphics and Vision, Graz University of Technology, Graz, Austria, ⁶Research and Development, Siemens Healthcare Diagnostics GmbH, Graz, Austria

Pulmonary hypertension is characterized by elevated mean pulmonary arterial pressure. Visual vortex analysis revealed a strong relation between elevated mean pulmonary arterial pressure and the duration of vortical blood flow along the pulmonary artery, however, automated pulmonary hypertension-related vortex detection methods are lacking. We propose a method for automated detection and tracking of the pulmonary hypertension-related vortex from 4D flow data and aim to compare it with visual analysis and to validate automatically estimated mean pulmonary arterial pressure against invasively measured results. The automated method agreed very well with visual vortex detection and accurately estimated elevated mean pulmonary arterial pressure.