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Noninvasive quantification of cerebrovascular pressure changes using 4D Flow MRI

dc.contributor.authorMarlevi, David
dc.contributor.authorSchollenberger, Jonas
dc.contributor.authorAristova, Maria
dc.contributor.authorFerdian, Edward
dc.contributor.authorMa, Yue
dc.contributor.authorYoung, Alistair A.
dc.contributor.authorEdelman, Elazer R.
dc.contributor.authorSchnell, Susanne
dc.contributor.authorFigueroa, C. Alberto
dc.contributor.authorNordsletten, David A.
dc.date.accessioned2021-12-02T02:28:54Z
dc.date.available2023-01-01 21:28:53en
dc.date.available2021-12-02T02:28:54Z
dc.date.issued2021-12
dc.identifier.citationMarlevi, David; Schollenberger, Jonas; Aristova, Maria; Ferdian, Edward; Ma, Yue; Young, Alistair A.; Edelman, Elazer R.; Schnell, Susanne; Figueroa, C. Alberto; Nordsletten, David A. (2021). "Noninvasive quantification of cerebrovascular pressure changes using 4D Flow MRI." Magnetic Resonance in Medicine (6): 3096-3110.
dc.identifier.issn0740-3194
dc.identifier.issn1522-2594
dc.identifier.urihttps://hdl.handle.net/2027.42/170966
dc.publisherWiley Periodicals, Inc.
dc.publisherAcademic Press
dc.subject.other4D Flow MRI
dc.subject.otherrelative pressure
dc.subject.otherpatient‐specific modeling
dc.subject.otherhemodynamics
dc.subject.othercerebrovascular
dc.titleNoninvasive quantification of cerebrovascular pressure changes using 4D Flow MRI
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbtoplevelHealth Sciences
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/170966/1/mrm28928_am.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/170966/2/mrm28928-sup-0001-Supinfo.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/170966/3/mrm28928.pdf
dc.identifier.doi10.1002/mrm.28928
dc.identifier.sourceMagnetic Resonance in Medicine
dc.identifier.citedreferenceMarlevi D, Ha H, Dillon‐Murphy D, et al. Non‐invasive estimation of relative pressure in turbulent flow using virtual work‐energy. Med Image Anal. 2020a; 60: 101627
dc.identifier.citedreferenceLeng X, Wong KS, Liebeskind DS. Evaluating intracranial atherosclerosis rather than intracranial stenosis. Stroke. 2014; 45: 645 ‐ 651.
dc.identifier.citedreferenceWu C, Ansari S, Honarmand A, et al. Evaluation of 4D vascular flow and tissue perfusion in cerebral arteriovenous malformations: influence of Spetzler‐Martin grade, clinical presentation, and AVM risk factors. Am J Neuroradiol. 2015; 36: 1142 ‐ 1149.
dc.identifier.citedreferenceHope TA, Hope MD, Purcell DD, et al. Evaluation of intracranial stenoses and aneurysms with accelerated 4D flow. Magn Reson Imaging. 2010; 28: 41 ‐ 46.
dc.identifier.citedreferenceRivera‐Rivera LA, Turski P, Johnson KM, et al. 4D flow MRI for intracranial hemodynamics assessment in Alzheimer’s disease. J Cerebral Blood Flow Metabolism. 2016; 36: 1718 ‐ 1730.
dc.identifier.citedreferenceMiller KB, Howery AJ, Rivera‐Rivera LA, et al. Age‐related reductions in cerebrovascular reactivity using 4d flow mri. Front Aging Neurosci. 2019; 11: 281.
dc.identifier.citedreferenceZhang J, Brindise MC, Rothenberger S, et al. 4d flow MRI pressure estimation using velocity measurement‐error‐based weighted least‐squares. IEEE Trans Med Imaging. 2019; 39: 1668 ‐ 1680.
dc.identifier.citedreferenceBertoglio C, Núnez R, Galarce F, Nordsletten D, Osses A. Relative pressure estimation from velocity measurements in blood flows: State‐of‐the‐art and new approaches. Int J Numer Methods Biomed Eng. 2018; 34: e2925
dc.identifier.citedreferenceDonati F, Nordsletten D A, Smith N P, Lamata P. Pressure mapping from flow imaging: enhancing computation of the viscous term through velocity reconstruction in near‐wall regions. In 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, pp. 5097 ‐ 5100.
dc.identifier.citedreferenceŠvihlová H, Hron J, Málek J, Rajagopal K, Rajagopal K. Determination of pressure data from velocity data with a view toward its application in cardiovascular mechanics. Part 1. Theoretical considerations. Inter J Eng Sci. 2016; 105: 108 ‐ 127.
dc.identifier.citedreferenceFirstenberg MS, Smedira NG, Greenberg NL, et al. Relationship between early diastolic intraventricular pressure gradients, an index of elastic recoil, and improvements in systolic and diastolic function. Circulation. 2001; 104: 1 ‐ 330.
dc.identifier.citedreferenceMarlevi D, Balmus M, Hessenthaler A, et al. Non‐invasive estimation of relative pressure for intracardiac flows using virtual work‐energy. Med Image Anal. 2020b; 101948.
dc.identifier.citedreferenceSchollenberger J, Figueroa CA, Nielsen J‐F, Hernandez‐Garcia L. Practical considerations for territorial perfusion mapping in the cerebral circulation using super‐selective pseudo‐continuous arterial spin labeling. Magn Reson Med. 2020; 83: 492 ‐ 504.
dc.identifier.citedreferenceSchollenberger J, Osborne NH, Hernandez‐Garcia L, Figueroa CA. A combined computational fluid dynamics and MRI arterial spin labeling modeling strategy to quantify patient‐specific cerebral hemodynamics in cerebrovascular occlusive disease. bioRxiv. 2021.
dc.identifier.citedreferenceArthurs CJ, Khlebnikov R, Melville A. CRIMSON: an open‐source software framework for cardiovascular integrated modelling and simulation. bioRxiv. 2020.
dc.identifier.citedreferenceSchnell S, Ansari SA, Wu C, et al. Accelerated dual‐venc 4D flow MRI for neurovascular applications. J Magn Reson Imaging. 2017; 46: 102 ‐ 114.
dc.identifier.citedreferenceWalker PG, Cranney GB, Scheidegger MB, Waseleski G, Pohost GM, Yoganathan AP. Semiautomated method for noise reduction and background phase error correction in MR phase velocity data. J Magn Reson Imaging. 1993; 3: 521 ‐ 530.
dc.identifier.citedreferenceBernstein MA, Zhou XJ, Polzin JA, et al. Concomitant gradient terms in phase contrast MR: analysis and correction. Magn Reson Med. 1998; 39: 300 ‐ 308.
dc.identifier.citedreferenceSchrauben E, Wåhlin A, Ambarki K, et al. Fast 4D flow MRI intracranial segmentation and quantification in tortuous arteries. J Magn Reson Imaging. 2015; 42: 1458 ‐ 1464.
dc.identifier.citedreferenceSegletes SB, Walters WP. A note on the application of the extended Bernoulli equation. Inter J Impact Eng. 2002; 27: 561 ‐ 576.
dc.identifier.citedreferenceSchirmer CM, Malek AM. Prediction of complex flow patterns in intracranial atherosclerotic disease using computational fluid dynamics. Neurosurgery. 2007; 61: 842 ‐ 852.
dc.identifier.citedreferenceLeng X, Scalzo F, Ip HL, et al. Computational fluid dynamics modeling of symptomatic intracranial atherosclerosis may predict risk of stroke recurrence. PLoS One. 2014; 9. e97531
dc.identifier.citedreferenceReymond P, Perren F, Lazeyras F, Stergiopulos N. Patient‐specific mean pressure drop in the systemic arterial tree, a comparison between 1‐D and 3‐D models. J Biomech. 2012; 45: 2499 ‐ 2505.
dc.identifier.citedreferenceBlanco PJ, Müller LO, Spence JD. Blood pressure gradients in cerebral arteries: a clue to pathogenesis of cerebral small vessel disease. Stroke Vasc Neurol. 2017; 2: 108 ‐ 117.
dc.identifier.citedreferenceRuedinger KL, Medero R, Roldán‐Alzate A. Fabrication of low‐cost patient‐specific vascular models for particle image velocimetry. Cardiovasc Eng Technol. 2019; 10: 500 ‐ 507.
dc.identifier.citedreferenceGottwald L, Töger J, Bloch KM, et al. High spatiotemporal resolution 4D flow MRI of intracranial aneurysms at 7T in 10 minutes. Am J Neuroradiol. 2020; 41: 1201 ‐ 1208.
dc.identifier.citedreferenceFerdian E, Suinesiaputra A, Dubowitz DJ, et al. 4DFlowNet: super‐resolution 4D Flow MRI using deep learning and computational fluid dynamics. Front Phys. 2020; 8: 138.
dc.identifier.citedreferenceSamuels OB, Joseph GJ, Lynn MJ, Smith HA, Chimowitz MI. A standardized method for measuring intracranial arterial stenosis. Am J Neuroradiol. 2000; 21: 643 ‐ 646.
dc.identifier.citedreferenceOrz Y, Kobayashi S, Osawa M, Tanaka Y. Aneurysm size: a prognostic factor for rupture. Br J Neurosurg. 1997; 11: 144 ‐ 149.
dc.identifier.citedreferenceLiebeskind DS, Feldmann E. Fractional flow in cerebrovascular disorders. Inter Neurol. 2012; 1: 87 ‐ 99.
dc.identifier.citedreferenceLiebeskind DS, Kosinski AS, Lynn MJ, et al. Noninvasive fractional flow on mra predicts stroke risk of intracranial stenosis. J Neuroimaging. 2015; 25: 87 ‐ 91.
dc.identifier.citedreferencePenn DL, Komotar RJ, Connolly ES. Hemodynamic mechanisms underlying cerebral aneurysm pathogenesis. J Clin Neurosci. 2011; 18: 1435 ‐ 1438.
dc.identifier.citedreferenceRivera‐Rivera LA, Johnson KM, Turski PA, Wieben O. Pressure mapping and hemodynamic assessment of intracranial dural sinuses and dural arteriovenous fistulas with 4D flow MRI. Am J Neuroradiol. 2018; 39: 485 ‐ 487.
dc.identifier.citedreferenceLi Y, Ahmed R, Rivera‐Rivera LA, Stadler JA III, Turski P, Aagaard‐Kienitz B. Serial quantitative and qualitative measurements of flow in vein of galen malformations using 4‐Dimensional flow magnetic resonance imaging [phase contrast vastly undersampled isotropic projection]. World Neurosurg. 2019; 126: 405 ‐ 412.
dc.identifier.citedreferenceThorin‐Trescases N, de Montgolfier O, Pinçon A, et al. Impact of pulse pressure on cerebrovascular events leading to age‐related cognitive decline. Am J Physiol Heart Circulatory Physiol. 2018; 314: H1214 ‐ H1224.
dc.identifier.citedreferencede Montgolfier O, Pinçon A, Pouliot P, et al. High systolic blood pressure induces cerebral microvascular endothelial dysfunction, neurovascular unit damage, and cognitive decline in mice. Hypertension. 2019; 73: 217 ‐ 228.
dc.identifier.citedreferenceHurn PD, Traystman RJ. Overview of Cerebrovascular Hemodynamics. San Diego, CA: Academic Press; 1997.
dc.identifier.citedreferenceWu C, Schnell S, Vakil P, et al. In vivo assessment of the impact of regional intracranial atherosclerotic lesions on brain arterial 3D hemodynamics. Am J Neuroradiol. 2017; 38: 515 ‐ 522.
dc.identifier.citedreferenceSmith SC, Feldman TE, Hirshfeld JW, et al. Guideline update for percutaneous coronary intervention: a report of the american college of cardiology/american heart association task force on practice guidelines (ACC/AHA/SCAI writing committee to update the 2001 guidelines for percutaneous coronary intervention). J Am College Cardiol. 2006; 47: e1 ‐ e121.
dc.identifier.citedreferenceNishimura RA, Otto CM, Bonow RO, et al. AHA/ACC focused update of the 2014 AHA/ACC guideline for the management of patients with valvular heart disease: a report of the American College of Cardiology/American Heart Association task force on clinical practice guidelines. J Am College Cardiol. 2017; 70: 252 ‐ 289.
dc.identifier.citedreferenceWyman RM, Safian RD, Portway V, Skillman JJ, McKAY RG, Baim DS. Current complications of diagnostic and therapeutic cardiac catheterization. J Am College Cardiol. 1988; 12: 1400 ‐ 1406.
dc.identifier.citedreferenceVitiello R, McCrindle BW, Nykanen D, Freedom RM, Benson LN. Complications associated with pediatric cardiac catheterization. J Am College Cardiol. 1998; 32: 1433 ‐ 1440.
dc.identifier.citedreferenceStamm RB, Martin RP. Quantification of pressure gradients across stenotic valves by Doppler ultrasound. J Am College Cardiol. 1983; 2: 707 ‐ 718.
dc.identifier.citedreferenceGarcia D, Dumesnil JG, Durand L‐G, Kadem L, Pibarot P. Discrepancies between catheter and Doppler estimates of valve effective orifice area can be predicted from the pressure recovery phenomenon: practical implications with regard to quantification of aortic stenosis severity. J Am College Cardiol. 2003; 41: 435 ‐ 442.
dc.identifier.citedreferenceFeldman T, Guerrero M. Invasive hemodynamic versus Doppler echocardiographic assessment of aortic stenosis severity. Catheter Cardiovasc Interv. 2016; 87: 498 ‐ 499.
dc.identifier.citedreferenceMarlevi D, Ruijsink B, Balmus M, et al. Estimation of cardiovascular relative pressure using virtual work‐energy. Sci Rep. 2019; 9: 1375.
dc.identifier.citedreferenceVali A, Aristova M, Vakil P, et al. Semi‐automated analysis of 4D flow MRI to assess the hemodynamic impact of intracranial atherosclerotic disease. Magn Reson Med. 2019; 82: 749 ‐ 762.
dc.identifier.citedreferenceYotti R, Bermejo J, Antoranz JC, et al. Noninvasive assessment of ejection intraventricular pressure gradients. J Am College Cardiol. 2004; 43: 1654 ‐ 1662.
dc.identifier.citedreferenceFirstenberg MS, Vandervoort PM, Greenberg NL, et al. Noninvasive estimation of transmitral pressure drop across the normal mitral valve in humans: importance of convective and inertial forces during left ventricular filling. J Am College Cardiol. 2000; 36: 1942 ‐ 1949.
dc.identifier.citedreferenceHan Y‐F, Liu W‐H, Chen X‐L, et al. Severity assessment of intracranial large artery stenosis by pressure gradient measurements: a feasibility study. Catheterization Cardiovasc Interventions. 2016; 88: 255 ‐ 261.
dc.identifier.citedreferenceMiao Z, Liebeskind DS, Lo W, et al. Fractional flow assessment for the evaluation of intracranial atherosclerosis: a feasibility study. Inter Neurol. 2016; 5: 65 ‐ 75.
dc.identifier.citedreferenceKirsch JD, Mathur M, Johnson MH, Gowthaman G, Scoutt LM. Advances in transcranial Doppler US: imaging ahead. Radiographics. 2013; 33: E1 ‐ E14.
dc.identifier.citedreferenceMarkl M, Frydrychowicz A, Kozerke S, Hope M, Wieben O. 4D flow MRI. J Magn Reson Imaging. 2012; 36: 1015 ‐ 1036.
dc.identifier.citedreferenceStankovic Z, Allen BD, Garcia J, Jarvis KB, Markl M. 4D flow imaging with MRI. Cardiovasc Diagnosis Therapy. 2014; 4: 173.
dc.identifier.citedreferenceMorgan A G, Thrippleton M J, Wardlaw J M, Marshall I . 4D flow MRI for non‐invasive measurement of blood flow in the brain: a systematic review. J Cerebral Blood Flow Metabolism. 2020;0271678X20952014.
dc.identifier.citedreferenceYoun SW, Lee J. From 2d to 4d phase‐contrast mri in the neurovascular system: Will it be a quantum jump or a fancy decoration? J Magn Reson Imaging. 2020. https://doi.org/10.1002/jmri.27430
dc.identifier.citedreferenceLiu J, Koskas L, Faraji F, et al. Highly accelerated intracranial 4D flow MRI: evaluation of healthy volunteers and patients with intracranial aneurysms. Magn Reson Mater Phys Biol Med. 2018; 31: 295 ‐ 307.
dc.identifier.citedreferenceHope M, Purcell D, Hope T, et al. Complete intracranial arterial and venous blood flow evaluation with 4D flow MR imaging. Am J Neuroradiol. 2009; 30: 362 ‐ 366.
dc.identifier.citedreferenceAristova M, Vali A, Ansari SA, et al. Standardized evaluation of cerebral arteriovenous malformations using flow distribution network graphs and dual‐venc 4D Flow MRI. J Magn Reson Imaging. 2019; 50: 1718 ‐ 1730.
dc.working.doiNOen
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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