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Kilinc O, Chu S, Baraboo J, Weiss EK, Engel J, Maroun A, Giese D, Jin N, Chow K, Bi X, Davids R, Mehta C, Malaisrie SC, Hoel A, Carr J, Markl M, Allen BD. Hemodynamic Evaluation of Type B Aortic Dissection Using Compressed Sensing Accelerated 4D Flow MRI. J Magn Reson Imaging 2023; 57:1752-1763. [PMID: 36148924 PMCID: PMC10033465 DOI: 10.1002/jmri.28432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 08/30/2022] [Accepted: 09/03/2022] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND 4D Flow MRI is a quantitative imaging technique to evaluate blood flow patterns; however, it is unclear how compressed sensing (CS) acceleration would impact aortic hemodynamic quantification in type B aortic dissection (TBAD). PURPOSE To investigate CS-accelerated 4D Flow MRI performance compared to GRAPP-accelerated 4D Flow MRI (GRAPPA) to evaluate aortic hemodynamics in TBAD. STUDY TYPE Prospective. POPULATION Twelve TBAD patients, two volunteers. FIELD STRENGTH/SEQUENCE 1.5T, 3D time-resolved cine phase-contrast gradient echo sequence. ASSESSMENT GRAPPA (acceleration factor [R] = 2) and two CS-accelerated (R = 7.7 [CS7.7] and 10.2 [CS10.2]) 4D Flow MRI scans were acquired twice for interscan reproducibility assessment. Voxelwise kinetic energy (KE), peak velocity (PV), forward flow (FF), reverse flow (RF), and stasis were calculated. Plane-based mid-lumen flows were quantified. Imaging times were recorded. TESTS Repeated measures analysis of variance, Pearson correlation coefficients (r), intraclass correlation coefficients (ICC). P < 0.05 indicated statistical significance. RESULTS The KE and FF in true lumen (TL) and PV in false lumen (FL) did not show difference among three acquisition types (P = 0.818, 0.065, 0.284 respectively). The PV and stasis in TL were higher, KE, FF, and RF in FL were lower, and stasis was higher in GRAPPA compared to CS7.7 and CS10.2. The RF was lower in GRAPPA compared to CS10.2. The correlation coefficients were strong in TL (r = [0.781-0.986]), and low to strong in FL (r = [0.347-0.948]). The ICC levels demonstrated moderate to excellent interscan reproducibility (0.732-0.989). The FF and net flow in mid-descending aorta TL were significantly different between CS7.7 and CS10.2. CONCLUSION CS-accelerated 4D Flow MRI has potential for clinical utilization with shorter scan times in TBAD. Our results suggest similar hemodynamic trends between acceleration types, but CS-acceleration impacts KE, FF, RF, and stasis more in FL. EVIDENCE LEVEL 1 Technical Efficacy: Stage 2.
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Affiliation(s)
- Ozden Kilinc
- Department of Radiology, Northwestern University, Chicago, Illinois
| | - Stanley Chu
- Department of Radiology, Northwestern University, Chicago, Illinois
| | - Justin Baraboo
- Department of Radiology, Northwestern University, Chicago, Illinois
- Department of Biomedical Engineering, Northwestern University, Chicago, Illinois
| | - Elizabeth K. Weiss
- Department of Radiology, Northwestern University, Chicago, Illinois
- Department of Biomedical Engineering, Northwestern University, Chicago, Illinois
| | - Joshua Engel
- Department of Radiology, Northwestern University, Chicago, Illinois
| | - Anthony Maroun
- Department of Radiology, Northwestern University, Chicago, Illinois
| | - Daniel Giese
- Magnetic Resonance, Siemens Healthcare GmbH, Erlangen, Germany
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Ning Jin
- Cardiovascular MR R&D, Siemens Medical Solutions USA, Inc., Cleveland, Ohio
| | - Kelvin Chow
- Department of Radiology, Northwestern University, Chicago, Illinois
- Cardiovascular MR R&D, Siemens Medical Solutions USA, Inc., Chicago, Illinois
| | - Xiaoming Bi
- Cardiovascular MR R&D, Siemens Medical Solutions USA, Inc., Chicago, Illinois
| | - Rachel Davids
- Cardiovascular MR R&D, Siemens Medical Solutions USA, Inc., Chicago, Illinois
| | - Christopher Mehta
- Department of Surgery (Cardiac Surgery), Northwestern University, Chicago, Illinois
| | | | - Andrew Hoel
- Department of Surgery (Vascular Surgery), Northwestern University, Chicago, Illinois
| | - James Carr
- Department of Radiology, Northwestern University, Chicago, Illinois
| | - Michael Markl
- Department of Radiology, Northwestern University, Chicago, Illinois
- Department of Biomedical Engineering, Northwestern University, Chicago, Illinois
| | - Bradley D. Allen
- Department of Radiology, Northwestern University, Chicago, Illinois
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Mastrodicasa D, Codari M, Bäumler K, Sandfort V, Shen J, Mistelbauer G, Hahn LD, Turner VL, Desjardins B, Willemink MJ, Fleischmann D. Artificial Intelligence Applications in Aortic Dissection Imaging. Semin Roentgenol 2022; 57:357-363. [PMID: 36265987 PMCID: PMC10013132 DOI: 10.1053/j.ro.2022.07.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 06/25/2022] [Accepted: 07/02/2022] [Indexed: 11/11/2022]
Affiliation(s)
- Domenico Mastrodicasa
- Department of Radiology, Stanford University School of Medicine, Stanford, CA; Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA.
| | - Marina Codari
- Department of Radiology, Stanford University School of Medicine, Stanford, CA
| | - Kathrin Bäumler
- Department of Radiology, Stanford University School of Medicine, Stanford, CA
| | - Veit Sandfort
- Department of Radiology, Stanford University School of Medicine, Stanford, CA
| | - Jody Shen
- Department of Radiology, Stanford University School of Medicine, Stanford, CA
| | - Gabriel Mistelbauer
- Department of Radiology, Stanford University School of Medicine, Stanford, CA
| | - Lewis D Hahn
- University of California San Diego, Department of Radiology, La Jolla, CA
| | - Valery L Turner
- Department of Radiology, Stanford University School of Medicine, Stanford, CA
| | - Benoit Desjardins
- Department of Radiology, Stanford University School of Medicine, Stanford, CA; Department of Radiology, University of Pennsylvania, Philadelphia, PA
| | - Martin J Willemink
- Department of Radiology, Stanford University School of Medicine, Stanford, CA
| | - Dominik Fleischmann
- Department of Radiology, Stanford University School of Medicine, Stanford, CA
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Fleischmann D, Afifi RO, Casanegra AI, Elefteriades JA, Gleason TG, Hanneman K, Roselli EE, Willemink MJ, Fischbein MP. Imaging and Surveillance of Chronic Aortic Dissection: A Scientific Statement From the American Heart Association. Circ Cardiovasc Imaging 2022; 15:e000075. [PMID: 35172599 DOI: 10.1161/hci.0000000000000075] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
All patients surviving an acute aortic dissection require continued lifelong surveillance of their diseased aorta. Late complications, driven predominantly by chronic false lumen degeneration and aneurysm formation, often require surgical, endovascular, or hybrid interventions to treat or prevent aortic rupture. Imaging plays a central role in the medical decision-making of patients with chronic aortic dissection. Accurate aortic diameter measurements and rigorous, systematic documentation of diameter changes over time with different imaging equipment and modalities pose a range of practical challenges in these complex patients. Currently, no guidelines or recommendations for imaging surveillance in patients with chronic aortic dissection exist. In this document, we present state-of-the-art imaging and measurement techniques for patients with chronic aortic dissection and clarify the need for standardized measurements and reporting for lifelong surveillance. We also examine the emerging role of imaging and computer simulations to predict aortic false lumen degeneration, remodeling, and biomechanical failure from morphological and hemodynamic features. These insights may improve risk stratification, individualize contemporary treatment options, and potentially aid in the conception of novel treatment strategies in the future.
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