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Rapid magnetic resonance quantification on the brain: Optimization for clinical usage
Linköping University, Faculty of Health Sciences. Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Center for Medical Image Science and Visualization (CMIV). Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
Linköping University, Faculty of Health Sciences. Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Health Sciences.
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 of Surgery and Oncology, Department of Radiation Physics. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.ORCID iD: 0000-0001-8661-2232
2008 (English)In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 60, no 2, 320-329 p.Article in journal (Refereed) Published
Abstract [en]

A method is presented for rapid simultaneous quantification of the longitudinal T1 relaxation, the transverse T2 relaxation, the proton density (PD), and the amplitude of the local radio frequency B 1 field. All four parameters are measured in one single scan by means of a multislice, multiecho, and multidelay acquisition. It is based on a previously reported method, which was substantially improved for routine clinical usage. The improvements comprise of the use of a multislice spin-echo technique, a background phase correction, and a spin system simulation to compensate for the slice-selective RF pulse profile effects. The aim of the optimization was to achieve the optimal result for the quantification of magnetic resonance parameters within a clinically acceptable time. One benchmark was high-resolution coverage of the brain within 5 min. In this scan time the measured intersubject standard deviation (SD) in a group of volunteers was 2% to 8%, depending on the tissue (voxel size = 0.8 x 0.8 x 5 mm). As an example, the method was applied to a patient with multiple sclerosis in whom the diseased tissue could clearly be distinguished from healthy reference values. Additionally it was shown that, using the approach of synthetic MRI, both accurate conventional contrast images as well as quantification maps can be generated based on the same scan. © 2008 Wiley-Liss, Inc.

Place, publisher, year, edition, pages
2008. Vol. 60, no 2, 320-329 p.
Keyword [en]
quantitatie MRI, T1 mapping, T2mapping, PD mapping, B1 mapping, synthetic MRI, neurodegenerative disease
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:liu:diva-42804DOI: 10.1002/mrm.21635ISI: 000258105800011Local ID: 68904OAI: oai:DiVA.org:liu-42804DiVA: diva2:263661
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2017-12-13Bibliographically approved
In thesis
1. Quantitative Magnetic Resonance in Diffuse Neurological and Liver Disease
Open this publication in new window or tab >>Quantitative Magnetic Resonance in Diffuse Neurological and Liver Disease
2010 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Introduction: Magnetic resonance (MR) imaging is one of the most important diagnostic tools in modern medicine. Compared to other imaging modalities, it provides superior soft tissue contrast of all parts of the body and it is considered to be safe for patients. Today almost all MR is performed in a nonquantitative manner, only comparing neighboring tissue in the search for pathology. It is possible to quantify MR-signals and relate them to their physical entities, but time consuming and complicated calibration procedures have prevented this being used in a practical manner for clinical routines. The aim of this work is to develop and improve quantification methods in MRspectroscopy (MRS) and MR-imaging (MRI). The techniques are intended to be applied to diffuse diseases, where conventional imaging methods are unable to perform accurate staging or to reveal metabolic changes associated with disease development.

Methods: Proton (1H) MRS was used to characterize the white matter in the brain of multiple sclerosis (MS) patients. Phosphorus (31P) MRS was used to evaluate the energy metabolism in patients with diffuse liver disease. A new quantitative MRI (qMRI) method was invented for accurate, rapid and simultaneous quantification of B1, T1, T2, and proton density. A method for automatic assessment of visceral adipose tissue volume based on an in- and out-ofphase imaging protocol was developed. Finally, a method for quantification of the hepatobiliary uptake of liver specific T1 enhancing contrast agents was demonstrated on healthy subjects.

Results: The 1H MRS investigations of white matter in MS-patients revealed a significant correlation between tissue concentrations of Glutamate and Creatine on the one hand and the disease progression rate on the other, as measured using the MSSS. High accuracy, both in vitro and in vivo, of the measured MR-parameters from the qMRI method was observed. 31P MRS showed lower concentrations of phosphodiesters, and a higher metabolic charge in patients with cirrhosis, compared to patients with mild fibrosis and to controls. The adipose tissue quantification method agreed with estimates obtained using manual segmentation, and enabled measurements which were insensitive to partial volume effects. The hepatobiliary uptake of Gd-EOB-DTPA and Gd-BOPTA was significantly correlated in healthy subjects.

Conclusion: In this work, new methods for accurate quantification of MR parameters in diffuse diseases in the liver and the brain were demonstrated. Several applications were shown where quantitative MR improves the interpretation of observed signal changes in MRI and MRS in relation to underlying differences in physiology and pathophysiology.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2010. 127 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1184
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:liu:diva-54728 (URN)978-91-7393-390-2 (ISBN)
Public defence
2010-04-29, Elsa Brändströmsalen, Campus US, Linköpings universitet, Linköping, 13:15 (English)
Opponent
Supervisors
Available from: 2010-04-07 Created: 2010-04-07 Last updated: 2017-01-31Bibliographically approved
2. 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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Warntjes, Marcel, Jan BertusDahlqvist, OlofWest, JanneLundberg, Peter

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