Analysis of the reliability of quantitative parameters of diffusion measured by magnetic resonance methods of diffusion tensor and diffusion kurtosis imaging

Táto práca sa zameriava na vysvetlenie problematiky zobrazovania parametrov difúzie pomocou MRI. V prvej časti popisuje základné princípy difúzie, princípy stanovenia koeficientu difúzie pomocou MRI a metódy DTI a DKI. V praktickej časti sa venuje popisu simulačného modelu voľnej a obmedzenej difúzie. Popisuje vplyv difúzneho času a intenzity gradientu na výsledný signál. V ďalšej časti sa zameriava stanovenie konfidenčných intervalov parametrov difúzie a ich grafickú reprezentáciu.This thesis deals with the understanding of the diffusion tensor imaging and the diffusion kurtosis imaging. In the first part, thesis describes principles of diffusion, estimation of diffusion coefficient with the usage of the MRI and methods DTI and DKI. In practical part, thesis describes simulation model of free and restricted diffusion, the influence of diffusion time and the strength of gradients on diffusion weighted signal. Thesis also describes estimations of confidence intervals of diffusion parameters and graphical representation of them.

Normalized STEAM-based diffusion tensor imaging provides a robust assessment of muscle tears in football players: preliminary results of a new approach to evaluate muscle injuries

Objectives: To assess acute muscle tears in professional football players by diffusion tensor imaging (DTI) and evaluate the impact of normalization of data. Methods: Eight football players with acute lower limb muscle tears were examined. DTI metrics of the injured muscle and corresponding healthy contralateral muscle and of ROIs drawn in muscle tears (ROItear) in the corresponding healthy contralateral muscle (ROIhc_t) in a healthy area ipsilateral to the injury (ROIhi) and in a corresponding contralateral area (ROIhc_i) were compared. The same comparison was performed for ratios of the injured (ROItear/ROIhi) and contralateral sides (ROIhc_t/ROIhc_i). ANOVA, Bonferroni corrected post-hoc and Students t-tests were used. Results: Analyses of the entire muscle did not show any differences (p>0.05 each) except for axial diffusivity (AD; p=0.048). ROItear showed higher mean diffusivity (MD) and AD than ROIhc_t (p<0.05). Fractional anisotropy (FA) was lower in ROItear than in ROIhi and ROIhc_t (p<0.05). Radial diffusivity (RD) was higher in ROItear than in any other ROI (p<0.05). Ratios revealed higher MD and RD and lower FA and reduced number and length of fibre tracts on the injured side (p<0.05 each). Conclusions: DTI allowed a robust assessment of muscle tears in athletes especially after normalization to healthy muscle tissue. Key Points STEAM-based DTI allows the investigation of muscle tears affecting professional football players. Fractional anisotropy and mean diffusivity differ between injured and healthy muscle areas. Only normalized data show differences of fibre tracking metrics in muscle tears. The normalization of DTI-metrics enables a more robust characterization of muscle tears.(VLID)475075

Improving MRSI spectral quality using high-resolution B0 inhomogeneity maps

In der Magnetresonanz-Spektroskopiebildgebung (MRSI) führen Inhomogenitäten im statischen Magnetfeld (B0) zu einer Verschlechterung der spektralen Qualität. Das Ziel dieser Diplomarbeit war es deshalb eine Nachverarbeitungsmethode zu implementieren, welche die spektrale Qualität durch zusätzlich akquirierte hochaufgelöste B0 Bilder verbessert. Hierfür wurden zwei Methoden implementiert. Die erste Methode basiert auf einer B0 Korrektur mittels überdiskretisierter MRSI (odMRSI) Rekonstruktion, in welcher die MRSI Datensätze im k-Raum durch Zerofilling interpoliert werden, sodass sie der Auflösung der B0 Inhomogenitätsbilder entsprechen. Nach der B0 Korrektur werden die Subvoxel der interpolierten MRSI Daten gemittelt, sodass die ursprüngliche Auflösung wieder erreicht wird. Die zweite Methode, genannt Spectral Resolution Amelioration by Deconvolution (SPREAD), schlägt vor, dass die Profile der spektralen Resonanzen in jedem Voxel durch eine zusätzliche B0 Map abgeschätzt werden und die im orginalen MRSI Datensat gemessenen spektralen Resonanzlinien simuliert werden können. Dann kann eine spektrale Entfaltung in der Time Domain durchgeführt werden zwischen den gemessenen MRSI Daten und den Simulierten Profilen der Resonanzen. odMRSI Rekonstruktion erhöht hauptsächlich das Signal-zu-Rausch (SNR) Verhältnis durch Entkoppelung des spektralen Rauschens zwischen den Subspektren wähend des Interpolationsschrittes. SPREAD erhöht die spektrale Auflösung durch Reduktion der spektralen Linienbreite, welche durch B0 Inhomogenitäten verursacht wird. Beide Methoden wurden zuerst in Simulationen validiert und dann auf Phantom und in vivo Daten angewendet. Eine wesentliche Verbesserung der spektralen Qualität wäre deshalb ein wertvoller Teil der bereits etablierten Nachbearbeitungspipeline. Letztendlich, kann ein höheres SNR in eine Reduktion der Messzeit, höhere spektrale Auflösung oder für eine zuverlässigere Detektierung von niedrig konzentrierten Metaboliten umgewandelt werden. Unsere Ergebnisse validieren frühere Ergebnisse die eine Verbesserung der spektralen Eigenschaften (höheres SNR) durch odMRSI beobachtet haben. odMRSI Rekonstruktion war robust gegen Einflüsse durch niedriges SNR und kann ebenso auf Frequenzshiftmaps, welche aus den MRSI Daten selbst gewonnen werden, basieren. Das heisst, dass odMRSI ohne zusätzliche Messzeit angewendet werden kann. Allerdings konnte diese Verbesserung in der spektralen Qualität nicht in bessere Metabolitenkarten , welche durch spektrale Quantifizierung gewonnen werden, umgewandelt werden. Stattdessen lässt dies darauf schliessen, dass die Verbesserung der spektralen Eigenschaften lediglich 'kosmetisch' sind. Im Gegensatz dazu war SPREAD in der Lage die spektralen Eigenschaften nur dann zu verbessern, wenn bereits ein hohes SNR vorhanden war, was in der klinischen Realität kaum der Fall ist. Basierend darauf können wir rückschliessen, dass sowohl SPREAD als auch odMRSI Rekonstruktion nicht in der Lage sind in einem (klinischen) In vivo Setting Metbolitenkarten von höherer Qualität zu liefern.In Magnetic Resonance Spectroscopic Imaging (MRSI) inhomogeneities of the static magnetic field (B0) cause degradation of spectral quality. The aim of the thesis is to implement post processing methods to improve spectral quality by using additionally acquired high resolution B0 maps. For this purpose two methods were implemented. The first method suggests B0 correction in Overdiscrete MRSI (odMRSI) reconstruction in which the MRSI dataset is interpolated by k-space zero filling to match the resolution of the B0 inhomogeneity map. After the B0 correction the subvoxels of the interpolated MRSI data are averaged to reach the initial resolution. The second method, called Spectral Resolution Amelioration by Deconvolution (SPREAD), suggests to estimate lineshape profiles of each voxel from the B0 inhomogeneities map and to simulate the acquisition of the lineshape profiles at the resolution of the original MRSI dataset. Then spectral deconvolution in time domain is performed between the measured MRSI data and the simulated lineshape profiles. odMRSI reconstruction mainly increases the signal-to-noise ratio (SNR) by decorrelating the spectral noise between subspectra in the interpolation step. SPREAD increases spectral Resolution by reduction of linebroadening caused by B0 inhomogeneities. Both methods were first validated in simulations and then applied on phantom and in-vivo data. If the outputs of the two methods improve spectral quality significantly they can be used as valuable part of the established postprocessing pipeline. Ultimately, increased SNR can be traded for reduced acquisition time, higher spatial resolutions or to detect low abundant metabolites more confidently. Our results validated a previous report that odMRSI improved the spectral properties (higher SNR). odMRSI reconstruction was robust against influences from low SNR and can be even based on the shifts maps obtained from MRSI data themselves. This means that the odMRSI can be applied with no additional acquisition time. However, this spectral quality improvement was not translated into better metabolic maps as obtained via spectral quantification. Rather this suggests that the improvement of the spectral properties is just 'cosmetic' . In contrast, SPREAD was capable to improve spectral properties only in a situation with high SNR, which is not present in clinical reality. Based on this we conclude that both SPREAD and odMRSI reconstruction are both not able to provide metabolic maps of improved quality in a (clinical) in vivo Setting.7

Intra-session and inter-subject variability of 3D-FID-MRSI using single-echo volumetric EPI navigators at 3T

Purpose: In this study, we demonstrate the first combination of 3D FID proton MRSI and spatial encoding via concentric-ring trajectories (CRTs) at 3T. FID-MRSI has many benefits including high detection sensitivity, in particular for J-coupled metabolites (e.g., glutamate/glutamine). This makes it highly attractive, not only for clinical, but also for, potentially, functional MRSI. However, this requires excellent reliability and temporal stability. We have, therefore, augmented this 3D-FID-MRSI sequence with single-echo, imaging-based volumetric navigators (se-vNavs) for real-time motion/shim-correction (SHMOCO), which is 2× quicker than the original double-echo navigators (de-vNavs), hence allowing more efficient integration also in short-TR sequences. Methods: The tracking accuracy (position and B-field) of our proposed se-vNavs was compared to the original de-vNavs in phantoms (rest and translation) and in vivo (voluntary head rotation). Finally, the intra-session stability of a 5:40 min 3D-FID-MRSI scan was evaluated with SHMOCO and no correction (NOCO) in 5 resting subjects. Intra/inter-subject coefficients of variation (CV) and intra-class correlations (ICC) over the whole 3D volume and in selected regions of interest ROI were assessed. Results: Phantom and in vivo scans showed highly consistent tracking performance for se-vNavs compared to the original de-vNavs, but lower frequency drift. Up to ~30% better intra-subject CVs were obtained for SHMOCO (P < 0.05), with values of 9.3/6.9/6.5/7.8% over the full VOI for Glx/tNAA/tCho/m-Ins ratios to tCr. ICCs were good-to-high (91% for Glx/tCr in motor cortex), whereas the inter-subject variability was ~11–19%. Conclusion: Real-time motion/shim corrected 3D-FID-MRSI with time-efficient CRT-sampling at 3T allows reliable, high-resolution metabolic imaging that is fast enough for clinical use and even, potentially, for functional MRSI

The influence of spatial resolution on the spectral quality and quantification accuracy of whole-brain MRSI at 1.5T, 3T, 7T, and 9.4T

PURPOSE: Inhomogeneities in the static magnetic field (B0 ) deteriorate MRSI data quality by lowering the spectral resolution and SNR. MRSI with low spatial resolution is also prone to lipid bleeding. These problems are increasingly problematic at ultra-high fields. An approach to tackling these challenges independent of B0 -shim hardware is to increase the spatial resolution. Therefore, we investigated the effect of improved spatial resolution on spectral quality and quantification at 4 field strengths. METHODS: Whole-brain MRSI data was simulated for 3 spatial resolutions and 4 B0 s based on experimentally acquired MRI data and simulated free induction decay signals of metabolites and lipids. To compare the spectral quality and quantification, we derived SNR normalized to the voxel size (nSNR), linewidth and metabolite concentration ratios, their Cramer-Rao-lower-bounds (CRLBs), and the absolute percentage error (APE) of estimated concentrations compared to the gold standard for the whole-brain and 8 brain regions. RESULTS: At 7T, we found up to a 3.4-fold improved nSNR (in the frontal lobe) and a 2.8-fold reduced linewidth (in the temporal lobe) for 1 cm3 versus 0.25 cm3 resolution. This effect was much more pronounced at higher and less homogenous B0 (1.6-fold improved nSNR and 1.8-fold improved linewidth in the parietal lobe at 3T). This had direct implications for quantification: the volume of reliably quantified spectra increased with resolution by 1.2-fold and 1.5-fold (when thresholded by CRLBs or APE, respectively). CONCLUSION: MRSI data quality benefits from increased spatial resolution particularly at higher B0 , and leads to more reliable metabolite quantification. In conjunction with the development of better B0 shimming hardware, this will enable robust whole-brain MRSI at ultra-high field

7T HR FID-MRSI Compared to Amino Acid PET: Glutamine and Glycine as Promising Biomarkers in Brain Tumors

(1) Background: Recent developments in 7T magnetic resonance spectroscopic imaging (MRSI) made the acquisition of high-resolution metabolic images in clinically feasible measurement times possible. The amino acids glutamine (Gln) and glycine (Gly) were identified as potential neuro-oncological markers of importance. For the first time, we compared 7T MRSI to amino acid PET in a cohort of glioma patients. (2) Methods: In 24 patients, we co-registered 7T MRSI and routine PET and compared hotspot volumes of interest (VOI). We evaluated dice similarity coefficients (DSC), volume, center of intensity distance (CoI), median and threshold values for VOIs of PET and ratios of total choline (tCho), Gln, Gly, myo-inositol (Ins) to total N-acetylaspartate (tNAA) or total creatine (tCr). (3) Results: We found that Gln and Gly ratios generally resulted in a higher correspondence to PET than tCho. Using cutoffs of 1.6-times median values of a control region, DSCs to PET were 0.53 ± 0.36 for tCho/tNAA, 0.66 ± 0.40 for Gln/tNAA, 0.57 ± 0.36 for Gly/tNAA, and 0.38 ± 0.31 for Ins/tNAA. (4) Conclusions: Our 7T MRSI data corresponded better to PET than previous studies at lower fields. Our results for Gln and Gly highlight the importance of future research (e.g., using Gln PET tracers) into the role of both amino acids