{"id":2798,"date":"2024-04-23T09:12:13","date_gmt":"2024-04-23T07:12:13","guid":{"rendered":"https:\/\/www.mr-physik.med.fau.de\/?p=2798"},"modified":"2024-04-23T09:13:53","modified_gmt":"2024-04-23T07:13:53","slug":"new-paper-phase-distribution-graphs","status":"publish","type":"post","link":"https:\/\/www.mr-physik.med.fau.de\/en\/2024\/04\/23\/new-paper-phase-distribution-graphs\/","title":{"rendered":"New Paper: Phase Distribution Graphs"},"content":{"rendered":"<p>In this paper (<a href=\"https:\/\/onlinelibrary.wiley.com\/doi\/full\/10.1002\/mrm.30055\">https:\/\/onlinelibrary.wiley.com\/doi\/full\/10.1002\/mrm.30055<\/a>) <a href=\"https:\/\/www.mr-physik.med.fau.de\/en\/team\/jonathan-endres\/\">Jonathan Endres<\/a>\u00a0and Co-Authors present an analytical Bloch simulation approach for arbitrary MRI sequence simulation called Phase Distribution Graphs. It is a general implementation of the Extended Phase Graph (EPG) concept, based on the Fourier-domain Bloch equation, but with arbitrary timing, and including the exact contribution of dephased states resulting from spatial encoding and T2\u2019 relaxation effects. In contrast to EPG, which was limited to echo amplitudes only, this allows calculation of full echo shapes. The Pytorch implementation provides full differentiability in all input parameters allowing gradient descent optimization. A major problem of phase graphs, the generation of an \u201eastronomical number of states\u201c is solved by an efficient state selection algorithm. The simulation compares well to results of conventional Bloch simulations with quasi-random isochromat distribution, which it outperformed in simulation time by at least one order of magnitude. Different sequences and their artifacts are analyzed and improved, underlining that Phase Distribution Graphs allow efficient simulation and optimization of arbitrary MRI sequences, which was previously only possible via high isochromat counts.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-2771\" src=\"https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/Fig-1.png\" alt=\"\" srcset=\"https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/Fig-1.png 2126w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/Fig-1-300x70.png 300w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/Fig-1-1024x240.png 1024w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/Fig-1-768x180.png 768w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/Fig-1-1536x360.png 1536w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/Fig-1-2048x480.png 2048w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/Fig-1-60x14.png 60w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/Fig-1-140x33.png 140w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/Fig-1-480x112.png 480w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/Fig-1-940x220.png 940w\" \/><\/p>\n<p>Figure 1: The PDG simulation matches an analytical solution of the steady-state bSSFP.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-2772\" src=\"https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/PDG_Fig2.png\" alt=\"\" srcset=\"https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/PDG_Fig2.png 1434w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/PDG_Fig2-300x253.png 300w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/PDG_Fig2-1024x862.png 1024w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/PDG_Fig2-768x646.png 768w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/PDG_Fig2-60x51.png 60w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/PDG_Fig2-131x110.png 131w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/PDG_Fig2-285x240.png 285w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/PDG_Fig2-380x320.png 380w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/PDG_Fig2-558x470.png 558w\" \/><\/p>\n<p>Figure 2: PDG converges faster than isochromat solutions. In many sequences simulation is more than an order of magnitude faster.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-2773\" src=\"https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/IMG_0367.jpeg\" alt=\"\" srcset=\"https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/IMG_0367.jpeg 1448w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/IMG_0367-300x273.jpeg 300w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/IMG_0367-1024x931.jpeg 1024w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/IMG_0367-768x699.jpeg 768w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/IMG_0367-60x55.jpeg 60w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/IMG_0367-121x110.jpeg 121w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/IMG_0367-264x240.jpeg 264w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/IMG_0367-352x320.jpeg 352w, https:\/\/www.mr-physik.med.fau.de\/files\/2024\/04\/IMG_0367-517x470.jpeg 517w\" \/><\/p>\n<p>Figure 3: PDG provides deep insight into the contributing echo paths to each signal via the newly introduced latent signal.<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this paper (https:\/\/onlinelibrary.wiley.com\/doi\/full\/10.1002\/mrm.30055) Jonathan Endres\u00a0and Co-Authors present an analytical Bloch simulation approach for arbitrary MRI sequence simulation called Phase Distribution Graphs. It is a general implementation of the Extended Phase Graph (EPG) concept, based on the Fourier-domain Bloch equation, but with arbitrary timing, and including the exact contribution of dephased states resulting from spatial [&hellip;]<\/p>\n","protected":false},"author":4505,"featured_media":2771,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_rrze_cache":"enabled","_rrze_multilang_single_locale":"en_US","_rrze_multilang_single_source":"https:\/\/www.mr-physik.med.fau.de\/?p=2770","footnotes":""},"categories":[14,1,21],"tags":[],"class_list":["post-2798","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ag-zaiss","category-allgemein","category-startseite","en-US"],"_links":{"self":[{"href":"https:\/\/www.mr-physik.med.fau.de\/wp-json\/wp\/v2\/posts\/2798","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.mr-physik.med.fau.de\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.mr-physik.med.fau.de\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.mr-physik.med.fau.de\/wp-json\/wp\/v2\/users\/4505"}],"replies":[{"embeddable":true,"href":"https:\/\/www.mr-physik.med.fau.de\/wp-json\/wp\/v2\/comments?post=2798"}],"version-history":[{"count":1,"href":"https:\/\/www.mr-physik.med.fau.de\/wp-json\/wp\/v2\/posts\/2798\/revisions"}],"predecessor-version":[{"id":2800,"href":"https:\/\/www.mr-physik.med.fau.de\/wp-json\/wp\/v2\/posts\/2798\/revisions\/2800"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.mr-physik.med.fau.de\/wp-json\/wp\/v2\/media\/2771"}],"wp:attachment":[{"href":"https:\/\/www.mr-physik.med.fau.de\/wp-json\/wp\/v2\/media?parent=2798"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.mr-physik.med.fau.de\/wp-json\/wp\/v2\/categories?post=2798"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.mr-physik.med.fau.de\/wp-json\/wp\/v2\/tags?post=2798"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}