Quantitative proton density mapping: correcting the receiver sensitivity bias via pseudo proton densities

Volz, Steffen; Nöth, Ulrike; Jurcoane, Alina; Ziemann, Ulf; Hattingen, Elke; Deichmann, Ralf

doi:10.1016/j.neuroimage.2012.06.076

Cited by 60 publications

(112 citation statements)

References 35 publications

(61 reference statements)

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“…The method commonly used at 1.5 T of correcting B 1 − inhomogeneity with a B 1 + map is not successful at higher fields [27,31], so a number of groups [27,28,31,33,57] have replaced direct B 1 measurement and correction with a post-processing bias field correction algorithm available in the software SPM [58]. While this method was quite successful in healthy brain, it did not always perform well in the presence of brain abnormalities, such as tumors, and likely cannot be applied to map B 1 − in an external water standard [28].…”

Section: Challenges With B 1 − Inhomogeneity Correctionmentioning

confidence: 99%

“…Previous work utilized a B 1 − correction method based on calculation of a "pseudo PD" map from inverse T 1 [28,30,38]. The measured PD was divided by the pseudo PD and post-processed to generate an approximate B 1 − map.…”

Section: Challenges With B 1 − Inhomogeneity Correctionmentioning

confidence: 99%

“…As we move to higher magnetic field for improved signal to noise ratio (SNR), increased RF field inhomogeneities make it difficult to achieve accurate signal detection both inside and outside of the brain, and necessitate corrections for both transmit (B 1 + ) and receive (B 1 − ) inhomogeneity in order to accurately map TWC. A few relatively accurate methods for measuring TWC have been developed at 3 T [27][28][29][30][31][32][33]; however, they do not offer the additional myelin water information. Another method for simultaneous TWC and MWF measurement based on T 2 * relaxation was published previously, but the use of T 2 * relaxation meant that myelin water content measurements could be impacted by B o inhomogeneity, and large statistical errors in estimated myelin water contents resulted from the low SNR and sparse sampling of the T 2 * decay curve [34,35].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Simultaneous measurement of total water content and myelin water fraction in brain at 3 T using a T 2 relaxation based method

Meyers

Kolind

MacKay

2017

Magnetic Resonance Imaging

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Section: Challenges With B 1 − Inhomogeneity Correctionmentioning

confidence: 99%

Section: Challenges With B 1 − Inhomogeneity Correctionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Simultaneous measurement of total water content and myelin water fraction in brain at 3 T using a T 2 relaxation based method

Meyers

Kolind

MacKay

2017

Magnetic Resonance Imaging

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“…PD has also been found to strongly correlate with T1 in healthy brain tissue (63)(64)(65)(66). Therefore another approach to measuring PD is to measure the T1 relaxation and then calculate the PD:…”

Section: Measuring Proton Densitymentioning

confidence: 99%

Quantitative Magnetic Resonance Imaging of the Brain : Applications for Tissue Segmentation and Multiple Sclerosis

West¹

2014

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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.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 des...

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“…Going beyond physical models that describe the MRI signal as a function of scanner parameters, such as flip angle, repetition and echo times, biophysical models that describe the interdependence of MRI parameters, such as R 1 , proton density (PD) and macromolecular tissue volume fraction, have more recently been proposed 9, 10, 11. Combining such models with the concept of synthesizing images points towards an alternative approach: synthetic qMRI.…”

Section: Introductionmentioning

confidence: 99%

Synthetic quantitative MRI through relaxometry modelling

2016

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Quantitative MRI (qMRI) provides standardized measures of specific physical parameters that are sensitive to the underlying tissue microstructure and are a first step towards achieving maps of biologically relevant metrics through in vivo histology using MRI. Recently proposed models have described the interdependence of qMRI parameters. Combining such models with the concept of image synthesis points towards a novel approach to synthetic qMRI, in which maps of fundamentally different physical properties are constructed through the use of biophysical models. In this study, the utility of synthetic qMRI is investigated within the context of a recently proposed linear relaxometry model. Two neuroimaging applications are considered. In the first, artefact‐free quantitative maps are synthesized from motion‐corrupted data by exploiting the over‐determined nature of the relaxometry model and the fact that the artefact is inconsistent across the data. In the second application, a map of magnetization transfer (MT) saturation is synthesized without the need to acquire an MT‐weighted volume, which directly leads to a reduction in the specific absorption rate of the acquisition. This feature would be particularly important for ultra‐high field applications. The synthetic MT map is shown to provide improved segmentation of deep grey matter structures, relative to segmentation using T 1‐weighted images or R 1 maps. The proposed approach of synthetic qMRI shows promise for maximizing the extraction of high quality information related to tissue microstructure from qMRI protocols and furthering our understanding of the interrelation of these qMRI parameters.

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Quantitative proton density mapping: correcting the receiver sensitivity bias via pseudo proton densities

Cited by 60 publications

References 35 publications

Simultaneous measurement of total water content and myelin water fraction in brain at 3 T using a T 2 relaxation based method

Simultaneous measurement of total water content and myelin water fraction in brain at 3 T using a T 2 relaxation based method

Quantitative Magnetic Resonance Imaging of the Brain : Applications for Tissue Segmentation and Multiple Sclerosis

Synthetic quantitative MRI through relaxometry modelling

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