| 1. |
- Ahlgren, André, et al.
(författare)
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Quantification of microcirculatory parameters by joint analysis of flow-compensated and non-flow-compensated intravoxel incoherent motion (IVIM) data.
- 2016
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Ingår i: NMR in Biomedicine. - : Wiley. - 0952-3480 .- 1099-1492. ; 29:5, s. 640-649
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Tidskriftsartikel (refereegranskat)abstract
- The aim of this study was to improve the accuracy and precision of perfusion fraction and blood velocity dispersion estimates in intravoxel incoherent motion (IVIM) imaging, using joint analysis of flow-compensated and non-flow-compensated motion-encoded MRI data. A double diffusion encoding sequence capable of switching between flow-compensated and non-flow-compensated encoding modes was implemented. In vivo brain data were collected in eight healthy volunteers and processed using the joint analysis. Simulations were used to compare the performance of the proposed analysis method with conventional IVIM analysis. With flow compensation, strong rephasing was observed for the in vivo data, approximately cancelling the IVIM effect. The joint analysis yielded physiologically reasonable perfusion fraction maps. Estimated perfusion fractions were 2.43 ± 0.81% in gray matter, 1.81 ± 0.90% in deep gray matter, and 1.64 ± 0.72% in white matter (mean ± SD, n = 8). Simulations showed improved accuracy and precision when using joint analysis of flow-compensated and non-flow-compensated data, compared with conventional IVIM analysis. Double diffusion encoding with flow compensation was feasible for in vivo imaging of the perfusion fraction in the brain. The strong rephasing implied that blood flowing through the cerebral microvascular system was closer to the ballistic limit than the diffusive limit. © 2016 The Authors NMR in Biomedicine published by John Wiley & Sons Ltd.
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| 2. |
- Alexander, Daniel C., et al.
(författare)
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Imaging brain microstructure with diffusion MRI : Practicality and applications
- 2019
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Ingår i: NMR in Biomedicine. - : Wiley. - 0952-3480 .- 1099-1492. ; 32:4, s. 3841-3841
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Forskningsöversikt (refereegranskat)abstract
- This article gives an overview of microstructure imaging of the brain with diffusion MRI and reviews the state of the art. The microstructure-imaging paradigm aims to estimate and map microscopic properties of tissue using a model that links these properties to the voxel scale MR signal. Imaging techniques of this type are just starting to make the transition from the technical research domain to wide application in biomedical studies. We focus here on the practicalities of both implementing such techniques and using them in applications. Specifically, the article summarizes the relevant aspects of brain microanatomy and the range of diffusion-weighted MR measurements that provide sensitivity to them. It then reviews the evolution of mathematical and computational models that relate the diffusion MR signal to brain tissue microstructure, as well as the expanding areas of application. Next we focus on practicalities of designing a working microstructure imaging technique: model selection, experiment design, parameter estimation, validation, and the pipeline of development of this class of technique. The article concludes with some future perspectives on opportunities in this topic and expectations on how the field will evolve in the short-to-medium term.
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| 3. |
- Borga, Magnus, et al.
(författare)
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Validation of a Fast Method for Quantification of Intra-abdominal and Subcutaneous Adipose Tissue for Large Scale Human Studies
- 2015
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Ingår i: NMR in Biomedicine. - : John Wiley & Sons. - 1099-1492 .- 0952-3480. ; 28:12, s. 1747-1753
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Tidskriftsartikel (refereegranskat)abstract
- Central obesity is the hallmark of a number of non-inheritable disorders. The advent of imaging techniques such as magnetic resonance imaging (MRI) has allowed for a fast and accurate assessment of body fat content and distribution. However, image analysis continues to be one of the major obstacles for the use of MRI in large scale studies. In this study we assess the validity of the recently proposed fat-muscle-quantitation-system (AMRATM Profiler) for the quantification of intra-abdominal adipose tissue (IAAT) and abdominal subcutaneous adipose tissue (ASAT) from abdominal MR images. Abdominal MR images were acquired from 23 volunteers with a broad range of BMIs and analysed using SliceOmatic, the current gold-standard, and the AMRATM Profiler based on a non-rigid image registration of a library of segmented atlases. The results show that there was a highly significant correlation between the fat volumes generated by both analysis methods, (Pearson correlation r = 0.97 p<0.001), with the AMRATM Profiler analysis being significantly faster (~3 mins) than the conventional SliceOmatic approach (~40 mins). There was also excellent agreement between the methods for the quantification of IAAT (AMRA 4.73 ± 1.99 vs SliceOmatic 4.73 ± 1.75 litres, p=0.97). For the AMRATM Profiler analysis, the intra-observer coefficient of variation was 1.6 % for IAAT and 1.1 % for ASAT, the inter-observer coefficient of variation was 1.4 % for IAAT and 1.2 % for ASAT, the intra-observer correlation was 0.998 for IAAT and 0.999 for ASAT, and the inter-observer correlation was 0.999 for both IAAT and ASAT. These results indicate that precise and accurate measures of body fat content and distribution can be obtained in a fast and reliable form by the AMRATM Profiler, opening up the possibility of large-scale human phenotypic studies.
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| 4. |
- Brinkhof, S., et al.
(författare)
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Uncompromised MRI of knee cartilage while incorporating sensitive sodium MRI
- 2019
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Ingår i: NMR in Biomedicine. - : Wiley. - 0952-3480 .- 1099-1492.
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Tidskriftsartikel (refereegranskat)abstract
- Sodium imaging is able to assess changes in ion content, linked to glycosaminoglycan content, which is important to guide orthopeadic procedures such as articular cartilage repair. Sodium imaging is ideally performed using double tuned RF coils, to combine high resolution morphological imaging with biochemical information from sodium imaging to assess ion content. The proton image quality of such coils is often harshly degraded, with up to 50% of SNR or severe acceleration loss as compared to single tuned coils. Reasons are that the number of proton receive channels often severely reduced and double tuning will degrade the intrinsic sensitivity of the RF coil on at least one of the nuclei. However, the aim of this work was to implement a double-tuned sodium/proton knee coil setup without deterioration of the proton signal whilst being able to achieve acquisition of high SNR sodium images. A double-tuned knee coil was constructed as a shielded birdcage optimized for sodium and compromised for proton. To exclude any compromise, the proton part of the birdcage is used for transmit only and interfaced to RF amplifiers that can fully mitigate the reduced efficiency. In addition, a 15 channel single tuned proton receiver coil was embedded within the double-resonant birdcage to maintain optimal SNR and acceleration for proton imaging. To validate the efficiency of our coil, the designed coil was compared with the state-of-the-art single-tuned alternative at 7 T. B1+ corrected SNR maps were used to compare both coils on proton performance and g-factor maps were used to compare both coils on acceleration possibilities. The newly constructed double-tuned coil was shown to have comparable proton quality and acceleration possibilities to the single-tuned alternative while also being able to acquire high SNR sodium images.
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| 5. |
- Ferizi, U., et al.
(författare)
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Diffusion MRI microstructure models with in vivo human brain Connectome data: results from a multi-group comparison
- 2017
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Ingår i: NMR in Biomedicine. - : Wiley. - 0952-3480 .- 1099-1492. ; 30:9, s. Article no e3734 -
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Tidskriftsartikel (refereegranskat)abstract
- A large number of mathematical models have been proposed to describe the measured signal in diffusion-weighted (DW) magnetic resonance imaging (MRI). However, model comparison to date focuses only on specific subclasses, e.g. compartment models or signal models, and little or no information is available in the literature on how performance varies among the different types of models. To address this deficiency, we organized the White Matter Modeling Challenge' during the International Symposium on Biomedical Imaging (ISBI) 2015 conference. This competition aimed to compare a range of different kinds of models in their ability to explain a large range of measurable in vivo DW human brain data. Specifically, we assessed the ability of models to predict the DW signal accurately for new diffusion gradients and b values. We did not evaluate the accuracy of estimated model parameters, as a ground truth is hard to obtain. We used the Connectome scanner at the Massachusetts General Hospital, using gradient strengths of up to 300mT/m and a broad set of diffusion times. We focused on assessing the DW signal prediction in two regions: the genu in the corpus callosum, where the fibres are relatively straight and parallel, and the fornix, where the configuration of fibres is more complex. The challenge participants had access to three-quarters of the dataset and their models were ranked on their ability to predict the remaining unseen quarter of the data. The challenge provided a unique opportunity for a quantitative comparison of diverse methods from multiple groups worldwide. The comparison of the challenge entries reveals interesting trends that could potentially influence the next generation of diffusion-based quantitative MRI techniques. The first is that signal models do not necessarily outperform tissue models; in fact, of those tested, tissue models rank highest on average. The second is that assuming a non-Gaussian (rather than purely Gaussian) noise model provides little improvement in prediction of unseen data, although it is possible that this may still have a beneficial effect on estimated parameter values. The third is that preprocessing the training data, here by omitting signal outliers, and using signal-predicting strategies, such as bootstrapping or cross-validation, could benefit the model fitting. The analysis in this study provides a benchmark for other models and the data remain available to build up a more complete comparison in the future.
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| 6. |
- Lasič, Samo, et al.
(författare)
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Apparent exchange rate for breast cancer characterization.
- 2016
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Ingår i: NMR in Biomedicine. - : Wiley. - 0952-3480 .- 1099-1492. ; 29:5, s. 631-639
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Tidskriftsartikel (refereegranskat)abstract
- Although diffusion MRI has shown promise for the characterization of breast cancer, it has low specificity to malignant subtypes. Higher specificity might be achieved if the effects of cell morphology and molecular exchange across cell membranes could be disentangled. The quantification of exchange might thus allow the differentiation of different types of breast cancer cells. Based on differences in diffusion rates between the intra- and extracellular compartments, filter exchange spectroscopy/imaging (FEXSY/FEXI) provides non-invasive quantification of the apparent exchange rate (AXR) of water between the two compartments. To test the feasibility of FEXSY for the differentiation of different breast cancer cells, we performed experiments on several breast epithelial cell lines in vitro. Furthermore, we performed the first in vivo FEXI measurement of water exchange in human breast. In cell suspensions, pulsed gradient spin-echo experiments with large b values and variable pulse duration allow the characterization of the intracellular compartment, whereas FEXSY provides a quantification of AXR. These experiments are very sensitive to the physiological state of cells and can be used to establish reliable protocols for the culture and harvesting of cells. Our results suggest that different breast cancer subtypes can be distinguished on the basis of their AXR values in cell suspensions. Time-resolved measurements allow the monitoring of the physiological state of cells in suspensions over the time-scale of hours, and reveal an abrupt disintegration of the intracellular compartment. In vivo, exchange can be detected in a tumor, whereas, in normal tissue, the exchange rate is outside the range experimentally accessible for FEXI. At present, low signal-to-noise ratio and limited scan time allows the quantification of AXR only in a region of interest of relatively large tumors. © 2016 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.
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| 7. |
- Liu, Chunlei, et al.
(författare)
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Multimodal integration of diffusion MRI for better characterization of tissue biology
- 2019
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Ingår i: NMR in Biomedicine. - : John Wiley & Sons. - 0952-3480 .- 1099-1492. ; 32:4
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Forskningsöversikt (refereegranskat)abstract
- The contrast in diffusion-weighted MR images is due to variations of diffusion properties within the examined specimen. Certain microstructural information on the underlying tissues can be inferred through quantitative analyses of the diffusion-sensitized MR signals. In the first part of the paper, we review two types of approach for characterizing diffusion MRI signals: Blochs equations with diffusion terms, and statistical descriptions. Specifically, we discuss expansions in terms of cumulants and orthogonal basis functions, the confinement tensor formalism and tensor distribution models. Further insights into the tissue properties may be obtained by integrating diffusion MRI with other techniques, which is the subject of the second part of the paper. We review examples involving magnetic susceptibility, structural tensors, internal field gradients, transverse relaxation and functional MRI. Integrating information provided by other imaging modalities (MR based or otherwise) could be a key to improve our understanding of how diffusion MRI relates to physiology and biology.
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| 8. |
- Montelius, Mikael, 1979, et al.
(författare)
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Multiparametric MR for non-invasive evaluation of tumour tissue histological characteristics after radionuclide therapy.
- 2019
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Ingår i: NMR in biomedicine. - : Wiley. - 1099-1492 .- 0952-3480. ; 31:3
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Tidskriftsartikel (refereegranskat)abstract
- Early non-invasive tumour therapy response assessment requires methods sensitive to biological and physiological tumour characteristics. The aim of this study was to find and evaluate magnetic resonance imaging (MRI) derived tumour tissue parameters that correlate with histological parameters and that reflect effects of radionuclide therapy. Mice bearing a subcutaneous human small-intestine neuroendocrine tumour were i.v. injected with 177 Lu-octreotate. MRI was performed (7 T Bruker Biospec) on different post-therapy intervals (1 and 13 days) using T2-weighted imaging, mapping of T2* and T1 relaxation time constants, as well as diffusion and dynamic contrast enhancement (DCE-MRI) techniques. After MRI, animals were killed and tumours excised. Four differently stained histological sections of the most central imaged tumour plane were digitized, and segmentation techniques were used to produce maps reflecting fibrotic and vascular density, apoptosis, and proliferation. Histological maps were aligned with MRI-derived parametric maps using landmark-based registration. Correlations and predictive power were evaluated using linear mixed-effects models and cross-validation, respectively. Several MR parameters showed statistically significant correlations with histological parameters. In particular, three DCE-MRI-derived parameters reflecting capillary function additionally showed high predictive power regarding apoptosis (2/3) and proliferation (1/3). T1 could be used to predict vascular density, and perfusion fraction derived from diffusion MRI could predict fibrotic density, although with lower predictive power. This work demonstrates the potential to use multiparametric MRI to retrieve important information on the tumour microenvironment after radiotherapy. The non-invasiveness of the method also allows longitudinal tumour tissue characterization. Further investigation is warranted to evaluate the parameters highlighted in this study longitudinally, in larger studies, and with additional histological methods.
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| 9. |
- Nilsson, Markus, et al.
(författare)
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Resolution limit of cylinder diameter estimation by diffusion MRI : The impact of gradient waveform and orientation dispersion
- 2017
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Ingår i: NMR in Biomedicine. - : Wiley. - 0952-3480 .- 1099-1492. ; 30:7
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Tidskriftsartikel (refereegranskat)abstract
- Diffusion MRI has been proposed as a non-invasive technique for axonal diameter mapping. However, accurate estimation of small diameters requires strong gradients, which is a challenge for the transition of the technique from preclinical to clinical MRI scanners, since these have weaker gradients. In this work, we develop a framework to estimate the lower bound for accurate diameter estimation, which we refer to as the resolution limit. We analyse only the contribution from the intra-axonal space and assume that axons can be represented by impermeable cylinders. To address the growing interest in using techniques for diffusion encoding that go beyond the conventional single diffusion encoding (SDE) sequence, we present a generalised analysis capable of predicting the resolution limit regardless of the gradient waveform. Using this framework, waveforms were optimised to minimise the resolution limit. The results show that, for parallel cylinders, the SDE experiment is optimal in terms of yielding the lowest possible resolution limit. In the presence of orientation dispersion, diffusion encoding sequences with square-wave oscillating gradients were optimal. The resolution limit for standard clinical MRI scanners (maximum gradient strength 60-80mT/m) was found to be between 4 and 8μm, depending on the noise levels and the level of orientation dispersion. For scanners with a maximum gradient strength of 300mT/m, the limit was reduced to between 2 and 5μm.
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| 10. |
- Tobisch, Alexandra, et al.
(författare)
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Comparison of basis functions and q-space sampling schemes for robust compressed sensing reconstruction accelerating diffusion spectrum imaging
- 2019
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Ingår i: NMR in Biomedicine. - : WILEY. - 0952-3480 .- 1099-1492. ; 32:3
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Tidskriftsartikel (refereegranskat)abstract
- Time constraints placed on magnetic resonance imaging often restrict the application of advanced diffusion MRI (dMRI) protocols in clinical practice and in high throughput research studies. Therefore, acquisition strategies for accelerated dMRI have been investigated to allow for the collection of versatile and high quality imaging data, even if stringent scan time limits are imposed. Diffusion spectrum imaging (DSI), an advanced acquisition strategy that allows for a high resolution of intra-voxel microstructure, can be sufficiently accelerated by means of compressed sensing (CS) theory. CS theory describes a framework for the efficient collection of fewer samples of a data set than conventionally required followed by robust reconstruction to recover the full data set from sparse measurements. For an accurate recovery of DSI data, a suitable acquisition scheme for sparse q-space sampling and the sensing and sparsifying bases for CS reconstruction need to be selected. In this work we explore three different types of q-space undersampling schemes and two frameworks for CS reconstruction based on either Fourier or SHORE basis functions. After CS recovery, diffusion and microstructural parameters and orientational information are estimated from the reconstructed data by means of state-of-the-art processing techniques for dMRI analysis. By means of simulation, diffusion phantom and in vivo DSI data, an isotropic distribution of q-space samples was found to be optimal for sparse DSI. The CS reconstruction results indicate superior performance of Fourier-based CS-DSI compared to the SHORE-based approach. Based on these findings we outline an experimental design for accelerated DSI and robust CS reconstruction of the sparse measurements that is suitable for the application within time-limited studies.
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