{"id":800,"date":"2017-08-08T08:10:57","date_gmt":"2017-08-08T07:10:57","guid":{"rendered":"https:\/\/journals.myesr.org\/eur-radiol\/2017\/08\/08\/4d-flow-mri\/"},"modified":"2025-09-19T10:22:52","modified_gmt":"2025-09-19T09:22:52","slug":"4d-flow-mri","status":"publish","type":"post","link":"https:\/\/journals.myesr.org\/eur-radiol\/opinions\/4d-flow-mri\/","title":{"rendered":"Four-dimensional flow MRI for evaluation of post-stenotic turbulent flow in a phantom: comparison with flowmeter and computational fluid dynamics"},"content":{"rendered":"<p>Dear Editor,<\/p>\n<p>A recent study by Kweon et al evaluated 4D flow MRI for evaluation post-stenotic turbulent flow and conclude that phase-contrast magnetic resonance imaging (PC-MRI) has limitations in the assessment of turbulent characteristics [1]. Evaluation and understanding of the limitations of measurement techniques are important steps towards improvement of the techniques. Unfortunately, this study seems to be based on experiments using an uncommon measurement technique that does not seem to provide any information about the turbulent velocity fluctuation intensity (<img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/journals.myesr.org\/eur-radiol\/wp-content\/ql-cache\/quicklatex.com-b37959059f9ab9f3cf39831e7962f54a_l3.png\" class=\"ql-img-inline-formula quicklatex-auto-format\" alt=\"&#12310;&#117;&#39;&#12311;&#95;&#123;&#114;&#109;&#115;&#125;\" title=\"Rendered by QuickLaTeX.com\" height=\"18\" width=\"35\" style=\"vertical-align: -4px;\"\/>) that Kweon et al claim to estimate. Due to this seemingly improper choice of methodology, conclusions regarding any limitations of PC-MRI in the assessment of turbulent characteristics cannot be drawn.<br \/>\nIn turbulent flows, Reynolds decomposition can be used to decompose the velocity, <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/journals.myesr.org\/eur-radiol\/wp-content\/ql-cache\/quicklatex.com-43fe27dc3e528266a619764d90fce60b_l3.png\" class=\"ql-img-inline-formula quicklatex-auto-format\" alt=\"&#117;\" title=\"Rendered by QuickLaTeX.com\" height=\"8\" width=\"10\" style=\"vertical-align: 0px;\"\/>, into the ensemble averaged mean velocity, <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/journals.myesr.org\/eur-radiol\/wp-content\/ql-cache\/quicklatex.com-d3729884b4eecba0bf64ea4840ecc0db_l3.png\" class=\"ql-img-inline-formula quicklatex-auto-format\" alt=\"&#98;&#97;&#114;&#123;&#117;&#125;\" title=\"Rendered by QuickLaTeX.com\" height=\"12\" width=\"35\" style=\"vertical-align: 0px;\"\/>, and the fluctuating velocity <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/journals.myesr.org\/eur-radiol\/wp-content\/ql-cache\/quicklatex.com-2f577fff31135affbb965ba7a0b6f4e8_l3.png\" class=\"ql-img-inline-formula quicklatex-auto-format\" alt=\"&#117;&#39;&#58;&#32;&#117;&#39;&#61;&#117;&#45;&#98;&#97;&#114;&#123;&#117;&#125;\" title=\"Rendered by QuickLaTeX.com\" height=\"14\" width=\"135\" style=\"vertical-align: 0px;\"\/>. The root-mean-square of <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/journals.myesr.org\/eur-radiol\/wp-content\/ql-cache\/quicklatex.com-346556929d4de752a14d3b25ed1cf263_l3.png\" class=\"ql-img-inline-formula quicklatex-auto-format\" alt=\"&#117;&#39;\" title=\"Rendered by QuickLaTeX.com\" height=\"14\" width=\"14\" style=\"vertical-align: 0px;\"\/>, <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/journals.myesr.org\/eur-radiol\/wp-content\/ql-cache\/quicklatex.com-b37959059f9ab9f3cf39831e7962f54a_l3.png\" class=\"ql-img-inline-formula quicklatex-auto-format\" alt=\"&#12310;&#117;&#39;&#12311;&#95;&#123;&#114;&#109;&#115;&#125;\" title=\"Rendered by QuickLaTeX.com\" height=\"18\" width=\"35\" style=\"vertical-align: -4px;\"\/>, is a commonly used measure of turbulent velocity fluctuation intensity:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/journals.myesr.org\/eur-radiol\/wp-content\/ql-cache\/quicklatex.com-7eeb3a6349f67c07523d2f5e2506935a_l3.png\" class=\"ql-img-inline-formula quicklatex-auto-format\" alt=\"&#12310;&#117;&#39;&#12311;&#95;&#123;&#114;&#109;&#115;&#125;&#61;&#32;&#115;&#113;&#114;&#116;&#40;&#102;&#114;&#97;&#99;&#123;&#49;&#125;&#123;&#78;&#125;&#32;&#115;&#117;&#109;&#95;&#123;&#105;&#61;&#49;&#125;&#94;&#78;&#9618;&#12310;&#117;&#39;&#12311;&#94;&#50;&#32;&#41;&#61;&#115;&#113;&#114;&#116;&#40;&#102;&#114;&#97;&#99;&#123;&#49;&#125;&#123;&#78;&#125;&#32;&#115;&#117;&#109;&#95;&#123;&#105;&#61;&#49;&#125;&#94;&#78;&#9618;&#40;&#117;&#45;&#98;&#97;&#114;&#123;&#117;&#125;&#41;&#94;&#50;&#32;&#41;\" title=\"Rendered by QuickLaTeX.com\" height=\"20\" width=\"521\" style=\"vertical-align: -5px;\"\/> [Equation 1]<\/p>\n<p class=\"p1\" style=\"text-align: justify; line-height: 150%;\"><span style=\"line-height: 150%;\">Kweon et al refer to this this equation but do in fact use the following equation instead:<\/span><\/p>\n<p class=\"p1\" style=\"text-align: justify; line-height: 150%;\"><span style=\"line-height: 150%;\">\u00a0<img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/journals.myesr.org\/eur-radiol\/wp-content\/ql-cache\/quicklatex.com-0fd216ddc782d2176fe9690e8f47fd01_l3.png\" class=\"ql-img-inline-formula quicklatex-auto-format\" alt=\"&#12310;&#117;&#39;&#12311;&#95;&#123;&#114;&#109;&#115;&#75;&#119;&#101;&#111;&#110;&#125;&#61;&#32;&#115;&#113;&#114;&#116;&#40;&#102;&#114;&#97;&#99;&#123;&#49;&#125;&#123;&#78;&#125;&#32;&#115;&#117;&#109;&#95;&#123;&#105;&#61;&#49;&#125;&#94;&#78;&#9618;&#117;&#95;&#123;&#80;&#67;&#45;&#77;&#82;&#73;&#39;&#125;&#94;&#50;&#32;&#41;\" title=\"Rendered by QuickLaTeX.com\" height=\"20\" width=\"346\" style=\"vertical-align: -5px;\"\/>\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 [Equation 2]<\/span><\/p>\n<p>where uPC-MRI is the spatiotemporally averaged velocity estimated by PC-MRI, which is an estimate of <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/journals.myesr.org\/eur-radiol\/wp-content\/ql-cache\/quicklatex.com-d3729884b4eecba0bf64ea4840ecc0db_l3.png\" class=\"ql-img-inline-formula quicklatex-auto-format\" alt=\"&#98;&#97;&#114;&#123;&#117;&#125;\" title=\"Rendered by QuickLaTeX.com\" height=\"12\" width=\"35\" style=\"vertical-align: 0px;\"\/>. Kweon et al estimate <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/journals.myesr.org\/eur-radiol\/wp-content\/ql-cache\/quicklatex.com-9dcfac4f5ac48e7e02abce7eec88fc2b_l3.png\" class=\"ql-img-inline-formula quicklatex-auto-format\" alt=\"&#12310;&#117;&#39;&#12311;&#95;&#123;&#114;&#109;&#115;&#75;&#119;&#101;&#111;&#110;&#125;\" title=\"Rendered by QuickLaTeX.com\" height=\"19\" width=\"79\" style=\"vertical-align: -5px;\"\/> by performing repeated measurements of uPC-MRI.<\/p>\n<p>Consequently, <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/journals.myesr.org\/eur-radiol\/wp-content\/ql-cache\/quicklatex.com-9dcfac4f5ac48e7e02abce7eec88fc2b_l3.png\" class=\"ql-img-inline-formula quicklatex-auto-format\" alt=\"&#12310;&#117;&#39;&#12311;&#95;&#123;&#114;&#109;&#115;&#75;&#119;&#101;&#111;&#110;&#125;\" title=\"Rendered by QuickLaTeX.com\" height=\"19\" width=\"79\" style=\"vertical-align: -5px;\"\/> is not an estimate of <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/journals.myesr.org\/eur-radiol\/wp-content\/ql-cache\/quicklatex.com-454f8bce7515ba7f23e2428c16d33c2d_l3.png\" class=\"ql-img-inline-formula quicklatex-auto-format\" alt=\"&#12310;&#117;&#39;&#12311;&#95;&#114;&#109;&#115;\" title=\"Rendered by QuickLaTeX.com\" height=\"18\" width=\"42\" style=\"vertical-align: -4px;\"\/>. In fact, <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/journals.myesr.org\/eur-radiol\/wp-content\/ql-cache\/quicklatex.com-9dcfac4f5ac48e7e02abce7eec88fc2b_l3.png\" class=\"ql-img-inline-formula quicklatex-auto-format\" alt=\"&#12310;&#117;&#39;&#12311;&#95;&#123;&#114;&#109;&#115;&#75;&#119;&#101;&#111;&#110;&#125;\" title=\"Rendered by QuickLaTeX.com\" height=\"19\" width=\"79\" style=\"vertical-align: -5px;\"\/> should not contain any information of <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/journals.myesr.org\/eur-radiol\/wp-content\/ql-cache\/quicklatex.com-346556929d4de752a14d3b25ed1cf263_l3.png\" class=\"ql-img-inline-formula quicklatex-auto-format\" alt=\"&#117;&#39;\" title=\"Rendered by QuickLaTeX.com\" height=\"14\" width=\"14\" style=\"vertical-align: 0px;\"\/> at all. Any information seen in the <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/journals.myesr.org\/eur-radiol\/wp-content\/ql-cache\/quicklatex.com-9dcfac4f5ac48e7e02abce7eec88fc2b_l3.png\" class=\"ql-img-inline-formula quicklatex-auto-format\" alt=\"&#12310;&#117;&#39;&#12311;&#95;&#123;&#114;&#109;&#115;&#75;&#119;&#101;&#111;&#110;&#125;\" title=\"Rendered by QuickLaTeX.com\" height=\"19\" width=\"79\" style=\"vertical-align: -5px;\"\/> data should be related to artefacts in PC-MRI velocity estimates in turbulent flow that has no known relationship to turbulent quantities. The results shown in Figure 5, for example, are most probably results of so called view-to-view artefacts, which occur when the object is not consistent throughout the acquisition of k-space, such as in the fluctuating shear regions of a jet.<\/p>\n<p>Since one of the goals of the study of Kweon et al was to estimate turbulence characteristics, we are surprised that they did not use PC-MRI turbulence mapping, which does permit estimation of <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/journals.myesr.org\/eur-radiol\/wp-content\/ql-cache\/quicklatex.com-b37959059f9ab9f3cf39831e7962f54a_l3.png\" class=\"ql-img-inline-formula quicklatex-auto-format\" alt=\"&#12310;&#117;&#39;&#12311;&#95;&#123;&#114;&#109;&#115;&#125;\" title=\"Rendered by QuickLaTeX.com\" height=\"18\" width=\"35\" style=\"vertical-align: -4px;\"\/> and related turbulent quantities such as turbulent kinetic energy [2, 3]. This method uses the magnitude images of the individual flow encodings obtained in PC-MRI to estimate <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/journals.myesr.org\/eur-radiol\/wp-content\/ql-cache\/quicklatex.com-b37959059f9ab9f3cf39831e7962f54a_l3.png\" class=\"ql-img-inline-formula quicklatex-auto-format\" alt=\"&#12310;&#117;&#39;&#12311;&#95;&#123;&#114;&#109;&#115;&#125;\" title=\"Rendered by QuickLaTeX.com\" height=\"18\" width=\"35\" style=\"vertical-align: -4px;\"\/> by exploiting the effects of turbulent fluid motion on the magnitude of the MR signal. In their discussion about their low-quality <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/journals.myesr.org\/eur-radiol\/wp-content\/ql-cache\/quicklatex.com-9dcfac4f5ac48e7e02abce7eec88fc2b_l3.png\" class=\"ql-img-inline-formula quicklatex-auto-format\" alt=\"&#12310;&#117;&#39;&#12311;&#95;&#123;&#114;&#109;&#115;&#75;&#119;&#101;&#111;&#110;&#125;\" title=\"Rendered by QuickLaTeX.com\" height=\"19\" width=\"79\" style=\"vertical-align: -5px;\"\/> data, Kweon et al claim that MR turbulence mapping requires multipoint encoding and prolonged scan times. This is incorrect. While MR turbulence mapping indeed can be done with multipoint encoding [4], it is most commonly carried out with conventional 4-point PC-MRI with asymmetric motion-encoding [5]. While multiple studies, including studies by Kweon and colleagues, have evaluated this technique in a variety of flow conditions [6\u201312], evaluation should be a continuous process and we look forward to more studies of the capabilities of the increasingly common MR turbulence mapping method.<\/p>\n<p><em>If you would like to comment on this letter, please send your comments together with full contact data to <a href=\"mailto:office@european-radiology.org\">office@european-radiology.org<\/a>. Replies and comments will be reviewed by the Editorial Office and published on this website.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Dear Editor, A recent study by Kweon et al evaluated 4D flow MRI for evaluation post-stenotic turbulent flow and conclude that phase-contrast magnetic resonance imaging (PC-MRI) has limitations in the assessment of turbulent characteristics [1]. Evaluation and understanding of the limitations of measurement techniques are important steps towards improvement of the techniques. Unfortunately, this study [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":1830,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","inline_featured_image":false,"footnotes":""},"categories":[6],"tags":[],"class_list":["post-800","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-opinions"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Four-dimensional flow MRI for evaluation of post-stenotic turbulent flow in a phantom: comparison with flowmeter and computational fluid dynamics - European Radiology<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/journals.myesr.org\/eur-radiol\/opinions\/4d-flow-mri\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Four-dimensional flow MRI for evaluation of post-stenotic turbulent flow in a phantom: comparison with flowmeter and computational fluid dynamics - European Radiology\" \/>\n<meta property=\"og:description\" content=\"Dear Editor, A recent study by Kweon et al evaluated 4D flow MRI for evaluation post-stenotic turbulent flow and conclude that phase-contrast magnetic resonance imaging (PC-MRI) has limitations in the assessment of turbulent characteristics [1]. Evaluation and understanding of the limitations of measurement techniques are important steps towards improvement of the techniques. 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