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Novel whole brain segmentation and volume estimation using quantitative MRI
Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences.
Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Centre, Department of Clinical Physiology UHL.
Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping.ORCID iD: 0000-0001-8661-2232
2012 (English)In: European Radiology, ISSN 0938-7994, E-ISSN 1432-1084, Vol. 22, no 5, 998-1007 p.Article in journal (Refereed) Published
Abstract [en]

OBJECTIVES:

Brain segmentation and volume estimation of grey matter (GM), white matter (WM) and cerebro-spinal fluid (CSF) are important for many neurological applications. Volumetric changes are observed in multiple sclerosis (MS), Alzheimer's disease and dementia, and in normal aging. A novel method is presented to segment brain tissue based on quantitative magnetic resonance imaging (qMRI) of the longitudinal relaxation rate R(1), the transverse relaxation rate R(2) and the proton density, PD.

METHODS:

Previously reported qMRI values for WM, GM and CSF were used to define tissues and a Bloch simulation performed to investigate R(1), R(2) and PD for tissue mixtures in the presence of noise. Based on the simulations a lookup grid was constructed to relate tissue partial volume to the R(1)-R(2)-PD space. The method was validated in 10 healthy subjects. MRI data were acquired using six resolutions and three geometries.

RESULTS:

Repeatability for different resolutions was 3.2% for WM, 3.2% for GM, 1.0% for CSF and 2.2% for total brain volume. Repeatability for different geometries was 8.5% for WM, 9.4% for GM, 2.4% for CSF and 2.4% for total brain volume.

CONCLUSION:

We propose a new robust qMRI-based approach which we demonstrate in a patient with MS. KEY POINTS : • A method for segmenting the brain and estimating tissue volume is presented • This method measures white matter, grey matter, cerebrospinal fluid and remaining tissue • The method calculates tissue fractions in voxel, thus accounting for partial volume • Repeatability was 2.2% for total brain volume with imaging resolution <2.0 mm.

Place, publisher, year, edition, pages
Springer, 2012. Vol. 22, no 5, 998-1007 p.
Keyword [en]
Brain segmentation – Tissue classification – Quantitative MRI – Brain volume estimation – Partial volume
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:liu:diva-73625DOI: 10.1007/s00330-011-2336-7ISI: 000303875900007PubMedID: 22113264OAI: oai:DiVA.org:liu-73625DiVA: diva2:475284
Note
funding agencies|CMIV||Research Council of South-East Sweden (FORSS)||National Research Council (VR/NT)||Knowledge Foundation (KK)||University Hospital Research Funds||Available from: 2012-01-10 Created: 2012-01-10 Last updated: 2017-12-08
In thesis
1. Quantitative Magnetic Resonance Imaging of the Brain: Applications for Tissue Segmentation and Multiple Sclerosis
Open this publication in new window or tab >>Quantitative Magnetic Resonance Imaging of the Brain: Applications for Tissue Segmentation and Multiple Sclerosis
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Magnetic resonance imaging (MRI) is a sensitive technique for assessing white matter (WM) lesions in multiple sclerosis (MS), but there is a low correlation between MRI findings and clinical disability. Because of this, other pathological changes are of interest, including changes in normal appearing white matter (NAWM) and diffusely abnormal white matter (DAWM). Even so, the mechanisms leading to permanent disability in MS remain unclear.

In contrast to conventional MRI, quantitative MRI (qMRI) is aimed at the direct measurement of the physical tissue properties, such as the relaxation times, T1 and T2, as well as the proton density (PD). QMRI is promising for characterising and quantifying changes in MS and for brain tissue segmentation.

The present work describes a novel method of qMRI for the human brain (QMAP), and a segmentation method based on this. The developed methods were validated in control subjects and MR phantoms. Furthermore, an application in diseased human brain was demonstrated in MS patients. In all, 50 healthy controls and 35 MS patients were scanned with qMRI in a total of 225 acquisitions.

One major finding of this work was that qMRI was able to detect and quantify changes in the MS disease that were not visible using conventional MRI. In particular, it was found that DAWM appears to constitute an intermediate between focal white matter (WM) lesions and NAWM. These changes may be caused by pathological processes that are not entirely attributable to Wallerian degeneration.

This study showed that the QMAP method had high accuracy and relatively high precision, within a clinically acceptable time. This work also demonstrated that qMRI could be used for brain tissue segmentation and volume estimation of the whole brain, using pre-defined tissue characteristics. The results showed that brain tissue segmentation had high repeatability, which was somewhat lower when different geometries were acquired or different field strengths used. In particular, small differences were found between 1.5 T and 3.0 T in deep brain structures, the cerebellum and the brain stem.

This work leads the way for early clinical applications of qMRI, and the challenge for the years to come is to understand the connection between qMRI properties of the brain and underlying biology.

Abstract [sv]

Bildtagning med magnetresonanstomografi (MRT) är en teknik som kan användas för att upptäcka lesioner i vit substans hos patienter med multipel skleros (MS), men sambandet mellan lesioner och klinisk funktionsnedsättning är svagt. På grund av detta har intresset för andra patologiska processer i hjärnan ökat. Exempel är förändringar i vit substans som ser normal ut vid MRT (NAWM) och även så kallad diffus vit vävnad (DAWM). Det är emellertid fortfarande oklart vilka mekanismer i MS som leder till klinisk funktionsnedsättning.

Med kvantitativ MRT (qMRT) kan fysiologiska egenskaper i vävnaden, som till exempel relaxationstiderna (T1 och T2) samt protontäthet (PD), mätas. QMRT kan användas för att mäta förändringar i hjärnan hos MS patienter och dessutom för segmentering av hjärnvävnad vid neurodegenerativa sjukdomar.

I detta arbete beskrivs en ny metod för qMRT applicerat på den mänskliga hjärnan (QMAP) och en segmenteringsmetod som baserades på denna. Metoderna validerades både i friska kontroller och i MR fantom. Slutligen användes qMRT för att undersöka hjärnan hos MS patienter. I studierna inkluderades 50 friska kontroller och 35 MS patienter, där totalt 225 bildtagningar med QMAP utfördes.

Ett viktigt resultat var att qMRT kunde användas för att upptäcka och mäta förändringar i hjärnan hos MS patienter som inte var synliga vid konventionell MRT. DAWM utgjorde en intermediär mellan NAWM och lesioner i vit vävnad. Resultaten pekade mot att dessa förändringar inte endast orsakades av Wallerisk degeneration.

QMAP metoden hade hög noggrannhet och relativt hög precision samt kunde användas med en kliniskt relevant tid för bildtagningen. Genom att använda förhandsdefinierade vävnadsegenskaper kunde qMRT tekniken även användas för segmentering av hjärnvävnad och för att beräkna volymer. Segmenteringen hade hög repeterbarhet men den minskade något när olika geometrier eller fältstyrkor användes. Små skillnader mellan 1.5 T och 3.0 T detekterades framför allt i djupa hjärnstrukturer, lillhjärnan och hjärnstammen.

I detta arbete demonstrerades två applikationer av qMRT för hjärnan. Den största utmaningen för kommande år blir att förstå och förklara sambanden mellan qMRT och underliggande biologiska egenskaper.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2014. 101 p.
Series
Linköping University Medical Dissertations, ISSN 0345-0082 ; 1384
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:liu:diva-103043 (URN)10.3384/diss.diva-103043 (DOI)978-91-7519-472-1 (ISBN)
Public defence
2014-02-14, Eken, ingång 65 (HU) plan 9, Campus US, Linkööpings universitet, Linköping, 13:02 (Swedish)
Opponent
Supervisors
Available from: 2014-01-10 Created: 2014-01-10 Last updated: 2014-10-02Bibliographically approved

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West, JanneWarntjes, MarcelLundberg, Peter

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Center for Medical Image Science and Visualization, CMIVRadiation PhysicsFaculty of Health SciencesClinical PhysiologyDepartment of Clinical Physiology UHLRadiologyDepartment of Radiation Physics UHLDepartment of Radiology in Linköping
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