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Methodological improvements in quantitative MRI : Perfusion estimation and partial volume considerations

Ahlgren, André LU (2017)
Abstract (Swedish)
Magnetkameran är en fantastisk medicinsk bildutrustning som kan producera detaljerade bilder av insidan av kroppen. Förutom bilder av vävnaden och dess struktur så kan magnetkameran också användas till att mäta olika egenskaper hos vävnaden. Om en vävnadsegenskap mäts i varje bildpixel så kan den resulterande bilden (parameterkartan) visas och användas för medicinsk bedömning, vilket kallas för kvantitativ magnetresonansavbildning (kvantitativ MRI). Vävnadsegenskaper som vanligtvis mäts inkluderar traditionella MR-parametrar såsom T1, T2 och protontäthet (PD), men även funktionella parametrar såsom vävnadsperfusion, hjärnaktivitet, diffusion och flöde.

Kvantitativ MRI kräver kontinuerlig utveckling av nya och förbättrade metoder... (More)
Magnetkameran är en fantastisk medicinsk bildutrustning som kan producera detaljerade bilder av insidan av kroppen. Förutom bilder av vävnaden och dess struktur så kan magnetkameran också användas till att mäta olika egenskaper hos vävnaden. Om en vävnadsegenskap mäts i varje bildpixel så kan den resulterande bilden (parameterkartan) visas och användas för medicinsk bedömning, vilket kallas för kvantitativ magnetresonansavbildning (kvantitativ MRI). Vävnadsegenskaper som vanligtvis mäts inkluderar traditionella MR-parametrar såsom T1, T2 och protontäthet (PD), men även funktionella parametrar såsom vävnadsperfusion, hjärnaktivitet, diffusion och flöde.

Kvantitativ MRI kräver kontinuerlig utveckling av nya och förbättrade metoder för
insamling av data (pulssekvenser), för modellering och bearbetning av data, och för att tolka resultaten ur ett medicinskt perspektiv. Denna avhandling beskriver nyutvecklade metoder, specifikt framtagna för att förbättra resultaten inom vissa kvantitativa MRI-tekniker. Mer specifikt så har arbetet fokuserat på förbättrad bearbetning av perfusions-MRI-data samt metoder för att hantera svårigheten med partiella volymer.

Konstant inflöde av syre och näring via blodet är avgörande för att vävnaden ska
fungera. Perfusions-MRI är en teknik för att mäta det regionala inflödet av blod, och perfusionsbilderna kan användas för att utvärdera vävnadens hälsotillstånd. Även om ungefärliga perfusionsvärden kan vara tillräckligt i vissa fall, så kan mer korrekta värden öppna möjligheter för bättre medicinsk forskning och diagnostik. Därför var ett centralt syfte med detta avhandlingsarbete att utvärdera alternativa metoder som kan tillhandahålla mer korrekta perfusionsvärden.

Ett sätt att förbättra perfusionsmätningar är att korrigera för den så kallade partialvolymseffekten, det vill säga att begränsad bildupplösning medför att en bildpixel kan innehålla signal från flera olika vävnadstyper. Det betyder att signalen kan vara blandad, och det beräknade perfusionsvärdet motsvarar en blandning av den faktiska perfusionen för de olika vävnadstyperna. Genom att först använda en annan kvantitativ MRI-metod som mäter volymen av varje vävnadstyp i alla pixlar (kallas partialvolymsmätning), så kan partialvolymseffekten korrigeras genom så kallad partialvolymskorrigering.

Partialvolymsmätning relaterar även till så kallad MRI-segmentering, vilket betyder att dela upp en bild i olika vävnadstyper. I detta arbete utvärderades och expanderades även en ny metod för partialvolymsmätning och segmentering. Metoden visade sig vara mycket användbar och robust, och samtidigt enkel att använda. En generell beskrivning presenteras i denna avhandling, med förhoppningen att fler forskare ska kunna implementera och
utvärdera metoden och undersöka dess potential i olika applikationer.

Sammanfattningsvis presenterar detta arbete förbättringar inom kvantitativ perfusionsMRI, liksom vidareutveckling av en ny metod för partialvolymsmätning. Metoderna
kommer förhoppningsvis vara värdefulla för medicinska applikationer i framtiden. (Less)
Abstract
The magnetic resonance imaging (MRI) scanner is a remarkable medical imaging device, capable of producing detailed images of the inside of the body. In addition to imaging internal tissue structures, the scanner can also be used to measure various properties of the tissue. If a tissue property is measured in every image pixel, the resulting property image (the parameter map) can be displayed and used for medical interpretation — a concept referred to as ‘quantitative MRI’. Tissue properties that are commonly probed include traditional MR parameters such as T1, T2 and proton density, as well as functional parameters such as tissue perfusion, brain activation, diffusion and flow.

Quantitative MRI relies on the continuous development... (More)
The magnetic resonance imaging (MRI) scanner is a remarkable medical imaging device, capable of producing detailed images of the inside of the body. In addition to imaging internal tissue structures, the scanner can also be used to measure various properties of the tissue. If a tissue property is measured in every image pixel, the resulting property image (the parameter map) can be displayed and used for medical interpretation — a concept referred to as ‘quantitative MRI’. Tissue properties that are commonly probed include traditional MR parameters such as T1, T2 and proton density, as well as functional parameters such as tissue perfusion, brain activation, diffusion and flow.

Quantitative MRI relies on the continuous development of new and improved ways to acquire data with the scanner (pulse sequences), to model and analyze the data (postprocessing), and to interpret the output from a medical perspective. This thesis describes methods that have been developed with the specific aim to improve certain quantitative MRI techniques. In particular, the work is focused on improved analysis of perfusion MRI data, and ways to handle the partial volume issue.

Constant delivery of oxygen and nutrients via the blood is vital for tissue viability. Perfusion MRI is designed to measure the properties of the local blood delivery, and perfusion images can be used as a marker for tissue health. Whereas rough estimates of perfusion properties can suffice in some cases, more accurate information can provide improved medical research and diagnostics. Most of the methods described in this work aim to provide tissue perfusion information with higher accuracy than previous approaches.

One particular way to improve perfusion information is to account for the so-called partial volume effect. This means that limited image resolution implies that a single pixel may contain signal from more than one type of tissue. In other words, the signal can be mixed, and the calculated perfusion represents a mixture of the underlying perfusion of the different tissue types. By first using another quantitative MRI method that estimates the partial volume of each tissue type in every pixel (referred to as partial volume mapping), the partial volume effect can be corrected for by so-called partial volume correction.

Partial volume mapping also relates to the field of MRI segmentation, that is, methods to segment an image into different tissue types and anatomical regions. This work also explores and expands a new partial volume mapping and segmentation method, referred to as fractional signal modeling, which seems to be exceptionally versatile and robust, as well as simple to implement and use. A general framework is laid out, with the hope of inspiring more researchers to adapt it and assess its value in different applications.

In conclusion, this work improved the quantification in different perfusion MRI methods, as well as presented a new partial volume mapping method. The described methods will hopefully yield value in medical applications in the future. (Less)
Please use this url to cite or link to this publication:
author
supervisor
opponent
  • Associate Professor Chappell, Michael, IBME, Department of Engineering Science, University of Oxford, United Kingdom
organization
publishing date
type
Thesis
publication status
published
subject
pages
61 pages
publisher
Lund University, Faculty of Science, Department of Medical Radiation Physics
defense location
Lecture hall F3 at Skåne University Hospital, Lund
defense date
2017-02-17 09:00
ISBN
978-91-7753-098-5
978-91-7753-099-2
language
English
LU publication?
yes
id
5000ebb6-30fe-4613-a7a6-5f9621d2b99e
date added to LUP
2017-01-23 13:32:05
date last changed
2017-02-02 16:56:19
@phdthesis{5000ebb6-30fe-4613-a7a6-5f9621d2b99e,
  abstract     = {The magnetic resonance imaging (MRI) scanner is a remarkable medical imaging device, capable of producing detailed images of the inside of the body. In addition to imaging internal tissue structures, the scanner can also be used to measure various properties of the tissue. If a tissue property is measured in every image pixel, the resulting property image (the parameter map) can be displayed and used for medical interpretation — a concept referred to as ‘quantitative MRI’. Tissue properties that are commonly probed include traditional MR parameters such as T1, T2 and proton density, as well as functional parameters such as tissue perfusion, brain activation, diffusion and flow.<br/><br/>Quantitative MRI relies on the continuous development of new and improved ways to acquire data with the scanner (pulse sequences), to model and analyze the data (postprocessing), and to interpret the output from a medical perspective. This thesis describes methods that have been developed with the specific aim to improve certain quantitative MRI techniques. In particular, the work is focused on improved analysis of perfusion MRI data, and ways to handle the partial volume issue.<br/><br/>Constant delivery of oxygen and nutrients via the blood is vital for tissue viability. Perfusion MRI is designed to measure the properties of the local blood delivery, and perfusion images can be used as a marker for tissue health. Whereas rough estimates of perfusion properties can suffice in some cases, more accurate information can provide improved medical research and diagnostics. Most of the methods described in this work aim to provide tissue perfusion information with higher accuracy than previous approaches.<br/><br/>One particular way to improve perfusion information is to account for the so-called partial volume effect. This means that limited image resolution implies that a single pixel may contain signal from more than one type of tissue. In other words, the signal can be mixed, and the calculated perfusion represents a mixture of the underlying perfusion of the different tissue types. By first using another quantitative MRI method that estimates the partial volume of each tissue type in every pixel (referred to as partial volume mapping), the partial volume effect can be corrected for by so-called partial volume correction.<br/><br/>Partial volume mapping also relates to the field of MRI segmentation, that is, methods to segment an image into different tissue types and anatomical regions. This work also explores and expands a new partial volume mapping and segmentation method, referred to as fractional signal modeling, which seems to be exceptionally versatile and robust, as well as simple to implement and use. A general framework is laid out, with the hope of inspiring more researchers to adapt it and assess its value in different applications.<br/><br/>In conclusion, this work improved the quantification in different perfusion MRI methods, as well as presented a new partial volume mapping method. The described methods will hopefully yield value in medical applications in the future.},
  author       = {Ahlgren, André},
  isbn         = {978-91-7753-098-5},
  language     = {eng},
  pages        = {61},
  publisher    = {Lund University, Faculty of Science, Department of Medical Radiation Physics},
  school       = {Lund University},
  title        = {Methodological improvements in quantitative MRI : Perfusion estimation and partial volume considerations},
  year         = {2017},
}