Grant S Roberts¹, Zach S Bernhardt², Sarah Lose², Alyssa Pandos², Kevin M Johnson^1,3, Laura B Eisenmenger³, Ozioma Okonkwo², and Oliver Wieben^1,3
1Dept of Medical Physics, University of Wisconsin - Madison, Madison, WI, United States, ²Dept of Medicine, University of Wisconsin - Madison, Madison, WI, United States, ³Dept of Radiology, University of Wisconsin - Madison, Madison, WI, United States

Pulse wave velocity (PWV) is a non-invasive biomarker related to vascular stiffness and cardiovascular risk. Cine 2D phase contrast (2DPC) MRI can be used to assess aortic PWV. However, the effects of respiration on PWV measures remain unexplored. Here, we assessed the effects of respiration by retrospectively gating free breathing radially sampled 2DPC MRI data in both inspiration and expiration. Two axial slices were obtained in the aortic arch and abdominal aorta and time shift methods were used to calculate PWV between the ascending and abdominal aorta. PWV measurements from inspiration (7.58m/s) were significantly decreased relative to expiration (8.42m/s). 

Bharath Ambale Venkatesh¹, Nadjia Kachenoura², Kevin Bouaou², Thomas Dietenbeck², Rithvik Rithvik Swamynathan³, Alban Redheuil², Elie Mousseaux⁴, and Joao A C Lima^3
1Radiology, Johns Hopkins University, Baltimore, MD, United States, ²Sorbonne Université, Paris, France, ³Johns Hopkins University, Baltimore, MD, United States, ⁴Université de Paris, Hôpital Européen Georges Pompidou, Paris, France

We develop deep learning for full aortic wall shear stress assessment using 3D aortic shapes and ascending aortic waveforms as input flow. Technically, this would reduce the acquisition time to less than a minute and the post-processing time to a few seconds.

Martin Sieben¹, Andreas Deistung¹, Maik Rothe¹, Richard Brill¹, Walter Alexander Wohlgemuth¹, and Alexander Gussew^1
1University clinic and policlinic for Radiology, University Hospital Halle (Saale), Halle (Saale), Germany

Time-resolved 3D phase contrast MRA (4D flow MRA) is a technique providing morphological and quantitative 3D hemodynamic information of the blood vessel network without contrast agents and with a high temporal resolution. This study was performed to systematically validate flow measurements in peripheral vessels with high resolution, based on examinations in 4D flow phantom and in femoral vessels of healthy subjects. For this purpose, exams were run with varying spatial resolution and velocity encoding factors. It was shown, that the applied approach enables accurate and reproducible flow measurements by using v_enc factors of 120cm/s and isotrop spatial resolution of 1mm.

Patrick Winter^1,2, Kristina Andelovic^2,3, Thomas Kampf^2,4, Susanne Schnell¹, Alma Zernecke³, Wolfgang Rudolf Bauer⁵, Peter Michael Jakob², and Volker Herold^2
1Department of MR Physics, University of Greifswald, Greifswald, Germany, ²Department of Experimental Physics V, University of Wuerzburg, Wuerzburg, Germany, ³Institute of Experimental Biomedicine, University Clinics Wuerzburg, Wuerzburg, Germany, ⁴Department of Diagnostic and Interventional Neuroradiology, University Clinics Wuerzburg, Wuerzburg, Germany, ⁵Department of Medical Clinic and Policlinic I, University Clinics Wuerzburg, Wuerzburg, Germany

As atherosclerosis is one of the main causes of death in industrial nations, noninvasive imaging modalities for studying its underlying mechanisms are in great demand. The quantification of hemodynamic parameters such as pulse wave velocity (PWV) assessed by flow sensitive magnetic resonance imaging (MRI) is a promising tool to observe plaque progression in preclinical models. Mostly, a global PWV value is assessed, however, previous studies already pointed to heterogeneous elasticity profiles in the presence of atherosclerotic plaques. Here, we present the measurement of local PWV values in the murine aortic arch assessed by 4D-flow MRI for spatially resolved elasticity measurements.

Ethan M I Johnson¹, Haben Berhane¹, Michael Scott¹, Kelly Jarvis¹, Alex Barker², and Michael Markl^1
1Northwestern University, Chicago, IL, United States, ²University of Colorado Anschutz Medical Campus, Aurora, CO, United States

Pulse wave velocity (PWV) is an important measure of vessel stiffness and can be quantified from 4D flow MRI.  Accurate assessment of PWV requires placement of multiple analysis planes in an imaged volume, which typically is performed manually to some degree, such as through use of a vessel segmentation made by an experienced human observer.  Here we present evaluation of a fully-automated method for calculating PWV in the thoracic aorta, incorporating an artificial intelligence (AI) convolutional neural network to segment the aorta.  Estimates of PWV using AI segmentations were compared those from human-observer segmentations and found to be similarly reliable.

Tarun Naren¹, Grant Steven Roberts¹, and Oliver Wieben^1
1Medical Physics, University of Wisconsin - Madison, Madison, WI, United States

The flow-area (QA) method is a promising phase contrast (PC) technique to assess local aortic pulse wave velocity (PWV). However, validation for reduced temporal resolutions is lacking. Data analysis and automated post-processing are compromised because of varying PC image quality throughout the cardiac cycle. In this study, we acquire PC and bSSFP data at three temporal resolutions and measure QAPWV using PC data alone and by combining PC flow measures with bSSFP areas. We found that the highest temporal resolution datasets (10ms) provide the most accurate PWV measures and the method combining bSSFP and PC was less accurate.

Daniel P Seiter¹, Betty Allen^2,3, Diana M Tabima³, Timothy A Hacker⁴, Phil Corrado¹, Thekla H Oechtering⁵, Scott B Reeder^1,5, Naomi C Chesler^6,7, and Oliver Wieben^1,5
1Medical Physics, University of Wisconsin-Madison, Madison, WI, United States, ²Surgery, University of Wisconsin-Madison, Madison, WI, United States, ³Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States, ⁴Medicine, University of Wisconsin-Madison, Madison, WI, United States, ⁵Radiology, University of Wisconsin-Madison, Madison, WI, United States, ⁶Edwards Lifesciences Foundation Cardiovascular Innovation and Research Center, University of California, Irvine, Irvine, CA, United States, ⁷Biomedical Engineering, University of California, Irvine, Irvine, CA, United States

Pulmonary hypertension is a known consequence of left heart failure. However, little is known about the pulmonary vascular and right ventricular changes caused by increased pulmonary venous pressure independent of left heart failure. By surgically banding the inferior pulmonary vein confluence in swine, we created pulmonary venous hypertension without damage to the left heart. Here, we report results from 4D flow MRI analysis of vessel flow, vessel velocity, cardiac flow compartments, and pressures measured via right heart catheterization in this novel model. 

Jerome Lamy¹, Felicia Seemann², Ricardo Gonzales Vera³, Einar Heiberg⁴, and Dana Peters^1
1Yale University, New Haven, CT, United States, ²National Institutes of Health, Bethesda, MD, United States, ³University of Oxford, Oxford, United Kingdom, ⁴Lund University, Lund, Sweden

Tricuspid valve flow evaluation is important for evaluation of regurgitation, used as a surrogate of pressures in the RV and as a criterion for evaluation of diastolic dysfunction. While 4D flow methods have interesting possibilities for retrospective valve flow evaluation its practical use is still limited. Here we present a method for direct tricuspid valve flow evaluation in a single breath-hold using 2D valve-following phase contrast sequence with a dynamic slice plane.

Christine Quast¹, Christoph Jacoby¹, Malte Kelm¹, and Ulrich Flögel^1
1Heinrich Heine University, Düsseldorf, Germany

Aortic valve stenosis (AS) is one of the most frequent valve diseases in the elderly with relevant prognostic impact. Becausesufficient experimental models were lacking, we recently refined a murine model of gradable experimental AS closely mimicking disease progression in humans. Here, we aimed at developing a comprehensive MRI approach for simultaneous assessment of changes in valvular, myocardial as well as aortic function in mice. We demonstrate that in this murine model high resolution MRI is capable to reliably display transvalvular aortic flow profiles with concomitant quantification of structural and functional changes inaortic valve, left ventricle, and ascending aorta.

Ana Beatriz Solana¹, Savine C.S. Minderhoud^2,3, Piotr A. Wielopolski³, Juan A. Hernandez-Tamames^3,4, Ricardo P.J. Budde^2,3, Willem A. Helbing⁵, Martin A. Janich¹, and Alexander Hirsch^2,3
1GE Healthcare, Munich, Germany, ²Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands, ³Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands, ⁴Department of Imaging Physics, TU Delft, Delft, Netherlands, ⁵Department of Pediatric Cardiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands

Phase contrast (PC) cardiac MRI is clinically used to quantify flow. The quantification accuracy is diminished by background phase errors. Stationary tissue-based background phase correction algorithms are commercially available, but their accuracy is still under evaluation. Here, we investigate if a self-calibrated phase contrast (SCPC) algorithm which includes automatic failure mode classification, can improve accuracy in a large single-vendor multi-scanner study including 346 PC scans. Our results show that SCPC improves flow quantification accuracy and can identify most PC scans which are unreliable regardless of stationary tissue correction or not.