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Automated Assessment of Blood Flow in the Cardiovascular System Using 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).ORCID iD: 0000-0002-1958-1672
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
Keywords [en]
MRI, 4D Flow MRI, Image Analysis, Segmentation
National Category
Medical Image Processing
Identifiers
URN: urn:nbn:se:liu:diva-145729DOI: 10.3384/diss.diva-145729ISBN: 9789176853467 (print)OAI: oai:DiVA.org:liu-145729DiVA, id: diva2:1192619
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 2013.0076Available from: 2018-03-23 Created: 2018-03-22 Last updated: 2019-09-30Bibliographically approved
List of papers
1. Improving left ventricular segmentation in four-dimensional flow MRI using intramodality image registration for cardiac blood flow analysis
Open this publication in new window or tab >>Improving left ventricular segmentation in four-dimensional flow MRI using intramodality image registration for cardiac blood flow analysis
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2018 (English)In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 79, no 1, p. 554-560Article in journal (Refereed) Published
Abstract [en]

PurposeAssessment of blood flow in the left ventricle using four-dimensional flow MRI requires accurate left ventricle segmentation that is often hampered by the low contrast between blood and the myocardium. The purpose of this work is to improve left-ventricular segmentation in four-dimensional flow MRI for reliable blood flow analysis. MethodThe left ventricle segmentations are first obtained using morphological cine-MRI with better in-plane resolution and contrast, and then aligned to four-dimensional flow MRI data. This alignment is, however, not trivial due to inter-slice misalignment errors caused by patient motion and respiratory drift during breath-hold based cine-MRI acquisition. A robust image registration based framework is proposed to mitigate such errors automatically. Data from 20 subjects, including healthy volunteers and patients, was used to evaluate its geometric accuracy and impact on blood flow analysis. ResultsHigh spatial correspondence was observed between manually and automatically aligned segmentations, and the improvements in alignment compared to uncorrected segmentations were significant (Pamp;lt;0.01). Blood flow analysis from manual and automatically corrected segmentations did not differ significantly (Pamp;gt;0.05). ConclusionOur results demonstrate the efficacy of the proposed approach in improving left-ventricular segmentation in four-dimensional flow MRI, and its potential for reliable blood flow analysis. Magn Reson Med 79:554-560, 2018. (c) 2017 International Society for Magnetic Resonance in Medicine.

Place, publisher, year, edition, pages
WILEY, 2018
Keywords
four-dimensional flow MRI; image registration; blood flow analysis; cardiology; MRI; 4D flow MRI; image registration; blood flow analysis; cardiology; MRI
National Category
Medical Image Processing
Identifiers
urn:nbn:se:liu:diva-143887 (URN)10.1002/mrm.26674 (DOI)000417926300054 ()28303611 (PubMedID)
Note

Funding Agencies|ERC [310612]; 310612; Grant sponsor: Vetenskapsradet [621-2014-6191]; Hjart-Lungfonden [20140398]; Knut och Alice Wallenbergs Stiftelse [KAW 2013.0076]

Available from: 2017-12-29 Created: 2017-12-29 Last updated: 2018-03-22
2. Atlas-based analysis of 4D flow CMR: Automated vessel segmentation and flow quantification
Open this publication in new window or tab >>Atlas-based analysis of 4D flow CMR: Automated vessel segmentation and flow quantification
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2015 (English)In: Journal of Cardiovascular Magnetic Resonance, ISSN 1097-6647, E-ISSN 1532-429X, Vol. 17, no 87Article in journal (Refereed) Published
Abstract [en]

Background: Flow volume quantification in the great thoracic vessels is used in the assessment of several cardiovascular diseases. Clinically, it is often based on semi-automatic segmentation of a vessel throughout the cardiac cycle in 2D cine phase-contrast Cardiovascular Magnetic Resonance (CMR) images. Three-dimensional (3D), time-resolved phase-contrast CMR with three-directional velocity encoding (4D flow CMR) permits assessment of net flow volumes and flow patterns retrospectively at any location in a time-resolved 3D volume. However, analysis of these datasets can be demanding. The aim of this study is to develop and evaluate a fully automatic method for segmentation and analysis of 4D flow CMR data of the great thoracic vessels. Methods: The proposed method utilizes atlas-based segmentation to segment the great thoracic vessels in systole, and registration between different time frames of the cardiac cycle in order to segment these vessels over time. Additionally, net flow volumes are calculated automatically at locations of interest. The method was applied on 4D flow CMR datasets obtained from 11 healthy volunteers and 10 patients with heart failure. Evaluation of the method was performed visually, and by comparison of net flow volumes in the ascending aorta obtained automatically (using the proposed method), and semi-automatically. Further evaluation was done by comparison of net flow volumes obtained automatically at different locations in the aorta, pulmonary artery, and caval veins. Results: Visual evaluation of the generated segmentations resulted in good outcomes for all the major vessels in all but one dataset. The comparison between automatically and semi-automatically obtained net flow volumes in the ascending aorta resulted in very high correlation (r(2) = 0.926). Moreover, comparison of the net flow volumes obtained automatically in other vessel locations also produced high correlations where expected: pulmonary trunk vs. proximal ascending aorta (r(2) = 0.955), pulmonary trunk vs. pulmonary branches (r(2) = 0.808), and pulmonary trunk vs. caval veins (r(2) = 0.906). Conclusions: The proposed method allows for automatic analysis of 4D flow CMR data, including vessel segmentation, assessment of flow volumes at locations of interest, and 4D flow visualization. This constitutes an important step towards facilitating the clinical utility of 4D flow CMR.

Place, publisher, year, edition, pages
BIOMED CENTRAL LTD, 2015
Keywords
4D flow cardiovascular magnetic resonance (4D flow CMR); Flow volume; Image segmentation; Image registration; Phase contrast
National Category
Clinical Medicine
Identifiers
urn:nbn:se:liu:diva-122197 (URN)10.1186/s12968-015-0190-5 (DOI)000362164100002 ()26438074 (PubMedID)
Note

Funding Agencies|Swedish Heart and Lung foundation; Swedish Research Council; European Research Council (HEART4FLOW) [310612]

Available from: 2015-10-26 Created: 2015-10-23 Last updated: 2018-03-22
3. Improving visualization of 4D flow cardiovascular magnetic resonance with four-dimensional angiographic data: generation of a 4D phase-contrast magnetic resonance CardioAngiography (4D PC-MRCA)
Open this publication in new window or tab >>Improving visualization of 4D flow cardiovascular magnetic resonance with four-dimensional angiographic data: generation of a 4D phase-contrast magnetic resonance CardioAngiography (4D PC-MRCA)
2017 (English)In: Journal of Cardiovascular Magnetic Resonance, ISSN 1097-6647, E-ISSN 1532-429X, Vol. 19, article id 47Article in journal (Refereed) Published
Abstract [en]

Magnetic Resonance Angiography (MRA) and Phase-Contrast MRA (PC-MRA) approaches used for assessment of cardiovascular morphology typically result in data containing information from the entire cardiac cycle combined into one 2D or 3D image. Information specific to each timeframe of the cardiac cycle is, however, lost in this process. This study proposes a novel technique, called Phase-Contrast Magnetic Resonance CardioAngiography (4D PC-MRCA), that utilizes the full potential of 4D Flow CMR when generating temporally resolved PC-MRA data to improve visualization of the heart and major vessels throughout the cardiac cycle. Using non-rigid registration between the timeframes of the 4D Flow CMR acquisition, the technique concentrates information from the entire cardiac cycle into an angiographic dataset at one specific timeframe, taking movement over the cardiac cycle into account. Registration between the timeframes is used once more to generate a time-resolved angiography. The method was evaluated in ten healthy volunteers. Visual comparison of the 4D PC-MRCAs versus PC-MRAs generated from 4D Flow CMR using the traditional approach was performed by two observers using Maximum Intensity Projections (MIPs). The 4D PC-MRCAs resulted in better visibility of the main anatomical regions of the cardiovascular system, especially where cardiac or vessel motion was present. The proposed method represents an improvement over previous PC-MRA generation techniques that rely on 4D Flow CMR, as it effectively utilizes all the information available in the acquisition. The 4D PC-MRCA can be used to visualize the motion of the heart and major vessels throughout the entire cardiac cycle.

Place, publisher, year, edition, pages
BIOMED CENTRAL LTD, 2017
Keywords
Computer-Assisted Image Analysis; 4D flow cardiovascular magnetic resonance (4D flow CMR); Phase-Contrast Magnetic Resonance Angiography (PC-MRA)
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:liu:diva-139277 (URN)10.1186/s12968-017-0360-8 (DOI)000404063800001 ()28645326 (PubMedID)
Note

Funding Agencies|European Research Council [310612]; Swedish Heart and Lung foundation [20140398]; Swedish Research Council [621-2014-6191]

Available from: 2017-07-07 Created: 2017-07-07 Last updated: 2018-03-22
4. Creating Hemodynamic Atlases of Cardiac 4D Flow MRI
Open this publication in new window or tab >>Creating Hemodynamic Atlases of Cardiac 4D Flow MRI
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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
National Category
Medical Image Processing
Identifiers
urn:nbn:se:liu:diva-142968 (URN)10.1002/jmri.25691 (DOI)000412894800015 ()28295788 (PubMedID)
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

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