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Creating Hemodynamic Atlases of Cardiac 4D Flow MRI
Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences.
Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).ORCID iD: 0000-0003-2198-9690
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2017 (English)In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 46, no 5, p. 1389-1399Article in journal (Refereed) Published
Abstract [en]

Purpose: Hemodynamic atlases can add to the pathophysiological understanding of cardiac diseases. This study proposes a method to create hemodynamic atlases using 4D Flow magnetic resonance imaging (MRI). The method is demonstrated for kinetic energy (KE) and helicity density (Hd). Materials and Methods: Thirteen healthy subjects underwent 4D Flow MRI at 3T. Phase-contrast magnetic resonance cardioangiographies (PC-MRCAs) and an average heart were created and segmented. The PC-MRCAs, KE, and Hd were nonrigidly registered to the average heart to create atlases. The method was compared with 1) rigid, 2) affine registration of the PC-MRCAs, and 3) affine registration of segmentations. The peak and mean KE and Hd before and after registration were calculated to evaluate interpolation error due to nonrigid registration. Results: The segmentations deformed using nonrigid registration overlapped (median: 92.3%) more than rigid (23.1%, P amp;lt; 0.001), and affine registration of PC-MRCAs (38.5%, P amp;lt; 0.001) and affine registration of segmentations (61.5%, P amp;lt; 0.001). The peak KE was 4.9 mJ using the proposed method and affine registration of segmentations (P50.91), 3.5 mJ using rigid registration (P amp;lt; 0.001), and 4.2 mJ using affine registration of the PC-MRCAs (P amp;lt; 0.001). The mean KE was 1.1 mJ using the proposed method, 0.8 mJ using rigid registration (P amp;lt; 0.001), 0.9 mJ using affine registration of the PC-MRCAs (P amp;lt; 0.001), and 1.0 mJ using affine registration of segmentations (P50.028). The interpolation error was 5.262.6% at mid-systole, 2.863.8% at early diastole for peak KE; 9.669.3% at mid-systole, 4.064.6% at early diastole, and 4.964.6% at late diastole for peak Hd. The mean KE and Hd were not affected by interpolation. Conclusion: Hemodynamic atlases can be obtained with minimal user interaction using nonrigid registration of 4D Flow MRI. Level of Evidence: 2 Technical Efficacy: Stage 1

Place, publisher, year, edition, pages
WILEY , 2017. Vol. 46, no 5, p. 1389-1399
National Category
Medical Image Processing
Identifiers
URN: urn:nbn:se:liu:diva-142968DOI: 10.1002/jmri.25691ISI: 000412894800015PubMedID: 28295788OAI: oai:DiVA.org:liu-142968DiVA, id: diva2:1156567
Note

Funding Agencies|ERC [Heart4flow, 310612]; Swedish Research Council [621-2014-6191]; Swedish Heart and Lung Foundation [20140398]

Available from: 2017-11-13 Created: 2017-11-13 Last updated: 2018-03-22
In thesis
1. Automated Assessment of Blood Flow in the Cardiovascular System Using 4D Flow MRI
Open this publication in new window or tab >>Automated Assessment of Blood Flow in the Cardiovascular System Using 4D Flow MRI
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Medical image analysis focuses on the extraction of meaningful information from medical images in order to facilitate clinical assessment, diagnostics and treatment. Image processing techniques have gradually become an essential part of the modern health care system, a consequence of the continuous technological improvements and the availability of a variety of medical imaging techniques.

Magnetic Resonance Imaging (MRI) is an imaging technique that stands out as non-invasive, highly versatile, and capable of generating high quality images without the use of ionizing radiation. MRI is frequently performed in the clinical setting to assess the morphology and function of the heart and vessels. When focusing on the cardiovascular system, blood flow visualization and quantification is essential in order to fully understand and identify related pathologies. Among the variety of MR techniques available for cardiac imaging, 4D Flow MRI allows for full three-dimensional spatial coverage over time, also including three-directional velocity information. It is a very powerful technique that can be used for retrospective analysis of blood flow dynamics at any location in the acquired volume.

In the clinical routine, however, flow analysis is typically done using two-dimensional imaging methods. This can be explained by their shorter acquisition times, higher in-plane spatial resolution and signal-to-noise ratio, and their relatively simpler post-processing requirements when compared to 4D Flow MRI. The extraction of useful knowledge from 4D Flow MR data is especially challenging due to the large amount of information included in these images, and typically requires substantial user interaction.

This thesis aims to develop and evaluate techniques that facilitate the post-processing of thoracic 4D Flow MRI by automating the steps necessary to obtain hemodynamic parameters of interest from the data. The proposed methods require little to no user interaction, are fairly quick, make effective use of the information available in the four-dimensional images, and can easily be applied to sizable groups of data.The addition of the proposed techniques to the current pipeline of 4D Flow MRI analysis simplifies and expedites the assessment of these images, thus bringing them closer to the clinical routine.

Abstract [sv]

Medicinsk bildanalys fokuserar på extrahering av meningsfull information från medicinska bilder för att underlätta klinisk bedömning, diagnostik, och behandling. Bildbehandlingsteknik har gradvis blivit en viktig del av det moderna sjukvårdsystemet, en följd av de kontinuerliga tekniska förbättringarna och tillgången till en mängd olika medicinska bildtekniker.

Magnetic resonanstomografi (MRT) är en bildteknik som är ickeinvasiv, flexibel och kan generera bilder av hög kvalitet utan joniserande strålning. MRT utförs ofta i klinisk miljö för att bedöma anatomi och funktion av hjärtat och blodkärlen. När man fokuserar på hjärt-kärlsystemet är bedömning av blodflödet viktigt för att kunna förstå och identifiera sjukdomar fullt ut. Bland de olika MRT-teknikerna som är tillgängliga för avbildning av hjärtat möjliggör 4D flödes-MRT komplett täckning av hjärtat i tre dimensioner över tid, och med hastighetsinformation i tre riktningar. 4D flödes-MRT är en mycket effektiv metod som kan användas för retrospektiv analys av blodflödesdynamik på vilken position som helst i den avbildade volymen.

Till vardags görs dock blodflödesanalysen vanligtvis på bilder tagna med tvådimensionella avbildningsmetoder. Detta kan förklaras av deras kortare insamlingstider, högre spatiella upplösning, bättre signal-brusförhållandet, och att de är relativt enklare att efterbehandla jämfört med 4D flödes-MRT. Utvinningen av användbar information från 4D flödes-MRT-data är väldigt utmanande på grund av den stora mängden information som dessa bilder innehåller och kräver vanligtvis väsentlig användarinteraktion.

Denna avhandling syftar till att utveckla och utvärdera metoder som underlättar efterbehandlingen av 4D flödes-MRT genom att automatisera de steg som är nödvändiga för att härleda hemodynamiska parametrarna av intresse från dessa data. De föreslagna metoderna kräver liten eller ingen användarinteraktion, är relativt snabba, använder all information som finns i de fyrdimensionella bilderna, och kan enkelt appliceras på stora datamängder. Tillägget av de i avhandlingen beskrivna metoderna till den nuvarande analysen av 4D flödes-MRT medger en avsevärd förenkling och uppsnabbad utvärdering, vilket gör att den avancerade 4D flödes MRT-tekniken kommer närmare att kunna användas i kliniskt rutinarbete.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2018. p. 77
Series
Linköping University Medical Dissertations, ISSN 0345-0082 ; 1613
Keyword
MRI, 4D Flow MRI, Image Analysis, Segmentation
National Category
Medical Image Processing
Identifiers
urn:nbn:se:liu:diva-145729 (URN)10.3384/diss.diva-145729 (DOI)9789176853467 (ISBN)
Public defence
2018-05-03, Eken, Building 421, Floor 9, Entrance 65, Campus US, Linköping, 13:00 (English)
Opponent
Supervisors
Funder
EU, European Research Council, 310612EU, European Research Council, 223615Swedish Research Council, 621-2014-6191Swedish Heart Lung Foundation, 20140398Wallenberg Foundations, KAW 2013.0076
Available from: 2018-03-23 Created: 2018-03-22 Last updated: 2018-04-09Bibliographically approved

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Cibis, MerihBustamante, MarianaEriksson, JonatanCarlhäll, CarljohanEbbers, Tino
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