Publications

Target audience: Researchers working in DCE-MRI, in situations where it isn’t possible to measure arterial input functions (AIFs). Purpose: To assess and validate the performance of blind deconvolution as a technique for estimating patient-specific AIFs. Methods: The study implements a blind deconvolution technique to estimate patient-specific AIFs for comparison with direct measurements of the aorta. The method involves clustering the tumour region of interest (ROI) into channels to maximize variation and SNR. An iterative, model-constrained process was employed, alternating between the optimisation of tissue model and AIF model parameters until convergence [1]. The study uses the Horsfield AIF model [2], with a representative AIF as the initial guess [3] alongside the Kety-Tofts (KT) tissue model. For an additional comparison, the two-compartment exchange model (2CXM) [4] is used in place of KT. The blind deconvolution was implemented using Perflab software [5]. Twenty-four patients with invasive breast cancer were scanned on a 1.5 T Aera MR scanner (Siemens), using a spoiled gradient echo sequence [3]. In addition to a bilateral breast coil, a flexible matrix coil was placed on the patients’ back to increase SNR in the descending aorta. The excited volume included the heart, lungs, and descending aorta which reduces inflow effects, allowing for direct AIF measurement in the descending aorta with a temporal resolution of 2 s over a period of 7.5 minutes. The SI-time data were converted to contrast agent (CA) concentration using bookend T1 measurements [6]. As the measured AIFs were sampled upstream of the tumour, the blindly estimated local AIFs are expected to exhibit dispersion in comparison. Consequently, error metrics such as mean squared error are unsuitable. Instead, the mean transit time (MTT, a measure of the width of the first-pass peak of the AIF) is used to assess the difference in dispersion. MTT is calculated as the ratio of the area under the first-pass peak to the maximum value of the first-pass peak, which is invariant to AIF scaling.

Purpose: The aim of this study was to develop a simple, robust, and easy-to-use calibration procedure for correcting misalignments in rosette MRI k-space sampling, with the objective of producing images with minimal artifacts. Methods: Quick automatic calibration scans were proposed for the beginning of the measurement to collect information on the time course of the rosette acquisition trajectory. A two-parameter model was devised to match the measured time-varying readout gradient delays and approximate the actual rosette sampling trajectory. The proposed calibration approach was implemented, and performance assessment was conducted on both phantoms and human subjects. Results: The fidelity of phantom and in vivo images exhibited significant improvement compared with uncorrected rosette data. The two-parameter calibration approach also demonstrated enhanced precision and reliability, as evidenced by quantitative T*(2) relaxometry analyses. Conclusion: Adequate correction of data sampling is a crucial step in rosette MRI. The presented experimental results underscore the robustness, ease of implementation, and suitability for routine experimental use of the proposed two-parameter rosette trajectory calibration approach.

Extracellular matrix (ECM) is a network of macromolecules which has two forms—perineuronal nets (PNNs) and a diffuse ECM (dECM)—both influence brain development, synapse formation, neuroplasticity, CNS injury and progression of neurodegenerative diseases. ECM remodeling can influence extrasynaptic transmission, mediated by diffusion of neuroactive substances in the extracellular space (ECS). In this study we analyzed how disrupted PNNs and dECM influence brain diffusibility. Two months after oral treatment of rats with 4-methylumbelliferone (4-MU), an inhibitor of hyaluronan (HA) synthesis, we found downregulated staining for PNNs, HA, chondroitin sulfate proteoglycans, and glial fibrillary acidic protein. These changes were enhanced after 4 and 6 months and were reversible after a normal diet. Morphometric analysis further indicated atrophy of astrocytes. Using real-time iontophoretic method dysregulation of ECM resulted in increased ECS volume fraction α in the somatosensory cortex by 35%, from α = 0.20 in control rats to α = 0.27 after the 4-MU diet. Diffusion-weighted magnetic resonance imaging revealed a decrease of mean diffusivity and fractional anisotropy (FA) in the cortex, hippocampus, thalamus, pallidum, and spinal cord. This study shows the increase in ECS volume, a loss of FA, and changes in astrocytes due to modulation of PNNs and dECM that could affect extrasynaptic transmission, cell-to-cell communication, and neural plasticity.

Purpose Focused ultrasound-induced blood–brain barrier (BBB) opening is a promising method for neurotherapeutic delivery. The standard for quantifying induced BBB permeability is the Ktrans parameter, which reflects both permeability and plasma flow. The influence of plasma flow can be eliminated by estimating the PS parameter. However, this parameter has been largely unexplored in this application. This study aims to compare permeability estimates based on Ktrans and PS in focused ultrasound–induced BBB opening experiments. Methods We used the extended Tofts model (ETM) and the two-compartment exchange model (2CXM) to estimate Ktrans and PS parameters, respectively. Permeability estimates were compared using simulated concentration curves, simulated DCE-MRI data, and real datasets. We explored the influence of spatially-regularized model fitting on the results. Results For opened BBB, Ktrans was minimally influenced by plasma flow under the tested conditions. However, fitting the ETM often introduced outliers in Ktrans estimates in regions with closed BBB. The 2CXM outperformed the ETM at high signal-to-noise ratios, but its higher complexity led to lower precision at low signal-to-noise ratios. Both these issues were successfully compensated by spatially-regularized model fitting. Conclusion Both Ktrans and PS seem to be eligible options for the quantification of BBB opening, and the correct choice depends on the specifics of the acquired DCE-MRI data. Additionally, spatial regularization has demonstrated its importance in enhancing the accuracy and reproducibility of results for both models.

Major depressive disorder (MDD) is a chronic mental disease affecting over 300 million people worldwide with limited treatment options. Understanding the neurochemical processes in MDD is essential for developing innovative medications, and magnetic resonance spectroscopy (1H MRS) is especially well-suited for its in vivo exploration. This chapter compares the consistent 1H MRS evidence from the animal models to the clinical findings. The clinical results largely correspond to the animal studies in the prefrontal cortex, where the higher choline and lower Glx (glutamate + glutamine) levels are reported. These markers indicate cell membrane turnover and neuronal metabolism dysfunction. The hippocampus in MDD patients is understudied in the clinical field making an assessment of consistency of preclinical and clinical findings impossible. The use of 1H MRS method provides new insights into neuro-molecular process in MDD and has a potential to become a useful biomarker for tracking the success of treatment interventions in MDD.

Alterations in tricarboxylic acid (TCA) cycle metabolism are associated with hepatic metabolic disorders. Elevated hepatic acetate concentrations, often attributed to high caloric intake, are recognized as a pivotal factor in the etiology of obesity and metabolic syndrome. Therefore, the assessment of acetate breakdown and TCA cycle activity plays a central role in understanding the impact of diet-induced alterations on liver metabolism. Magnetic resonance-based deuterium metabolic imaging (DMI) could help to unravel the underlying mechanisms involved in disease development and progression, however, the application of conventional deuterated glucose does not lead to substantial enrichment in hepatic glutamine and glutamate. This study aimed to demonstrate the feasibility of DMI for tracking deuterated acetate breakdown via the TCA cycle in lean and diet-induced fatty liver (FL) rats using 3D DMI after an intraperitoneal infusion of sodium acetate-d3 at 9.4T. Localized and nonlocalized liver spectra acquired at 10 time points post-injection over a 130-min study revealed similar intrahepatic acetate uptake in both animal groups (AUCFL = 717.9 +/- 131.1 mMmin-1, AUClean = 605.1 +/- 119.9 mMmin-1, p = 0.62). Metabolic breakdown could be observed in both groups with an emerging glutamine/glutamate (Glx) peak as a downstream metabolic product (AUCFL = 113.6 +/- 23.8 mMmin-1, AUClean = 136.7 +/- 41.7 mMmin-1, p = 0.68).This study showed the viability of DMI for tracking substrate flux through the TCA cycle, underscoring its methodological potential for imaging metabolic processes in the body.

Myocardial remodelling involves structural and functional changes in the heart, potentially leading to heart failure. The deoxycorticosterone acetate (DOCA)/salt model is a widely used experimental approach to study hypertension-induced cardiac remodelling. It allows to investigate the mechanisms underlying myocardial fibrosis and hypertrophy, which are key contributors to impaired cardiac function. In this study, myocardial remodelling in rat deoxycorticosterone acetate/salt model was examined over a three-week period. The experiment involved 11 male Sprague-Dawley rats, divided into two groups: fibrosis (n=6) and control (n=5). Myocardial remodelling was induced in the fibrosis group through unilateral nephrectomy, deoxyco-rticosterone acetate administration, and increased salt intake. The results revealed significant structural changes, including increased left ventricular wall thickness, myocardial fractional volume, and development of myocardial fibrosis. Despite these changes, left ventricular ejection fraction was preserved and even increased. ECG analysis showed significant prolongation of the PR interval and widening of the QRS complex in the fibrosis group, indicating disrupted atrioventricular and ventricular conduction, likely due to fibrosis and hypertrophy. Correlation analysis suggested a potential relationship between QRS duration and myocardial hypertrophy, although no significant correlations were found among other ECG parameters and structural changes detected by MRI. The study highlights the advantage of the DOCA/salt model in exploring the impact of myocardial remodelling on electrophysiological properties. Notably, this study is among the first to show that early myocardial remodelling in this model is accompanied by distinct electrophysiological changes, suggesting that advanced methods combined with established animal models can open new opportunities for research in this field. Key words Myocardial fibrosis, Remodelling, Animal model, DOCA-salt, Magnetic resonance imaging.

Background Major depressive disorder (MDD) is a mental illness with a high worldwide prevalence and suboptimal pharmacological treatment, which necessitates the development of novel, more efficacious MDD medication. Nuclear magnetic resonance (NMR) can non-invasively provide insight into the neurochemical state of the brain using proton magnetic resonance spectroscopy (1H MRS), and an assessment of regional cerebral blood flow (rCBF) by perfusion imaging. These methods may provide valuable in vivo markers of the pathological processes underlying MDD. Methods This study examined the effects of the chronic antidepressant medication, citalopram, in a well-validated MDD model induced by bilateral olfactory bulbectomy (OB) in rats. 1H MRS was utilized to assess key metabolite ratios in the dorsal hippocampus and sensorimotor cortex bilaterally, and arterial spin labelling was employed to estimate rCBF in several additional brain regions. Results The 1H MRS data results suggest lower hippocampal Cho/tCr and lower cortical NAA/tCr levels as a characteristic of the OB phenotype. Spectroscopy revealed lower hippocampal Tau/tCr in citalopram-treated rats, indicating a potentially deleterious effect of the drug. However, the significant OB model–citalopram treatment interaction was observed using 1H MRS in hippocampal mI/tCr, Glx/tCr and Gln/tCr, indicating differential treatment effects in the OB and control groups. The perfusion data revealed higher rCBF in the whole brain, hippocampus and thalamus in the OB rats, while citalopram appeared to normalise it without affecting the control group. Conclusion Collectively, 1H MRS and rCBF approaches demonstrated their capacity to capture an OB-induced phenotype and chronic antidepressant treatment effect in multiple brain regions.

Magnetic resonance spectroscopic imaging (MRSI) enables the simultaneous noninvasive acquisition of MR spectra from multiple spatial locations inside the brain. Although 1H-MRSI is increasingly used in the human brain, it is not yet widely applied in the preclinical setting, mostly because of difficulties specifically related to very small nominal voxel size in the rat brain and low concentration of brain metabolites, resulting in low signal-to-noise ratio (SNR). In this context, we implemented a free induction decay 1H-MRSI sequence (1H-FID-MRSI) in the rat brain at 14.1 T. We combined the advantages of 1H-FID-MRSI with the ultra-high magnetic field to achieve higher SNR, coverage, and spatial resolution in the rat brain and developed a custom dedicated processing pipeline with a graphical user interface for Bruker 1H-FID-MRSI: MRS4Brain toolbox. LCModel fit, using the simulated metabolite basis set and in vivo measured MM, provided reliable fits for the data at acquisition delays of 1.30 ms. The resulting Cramér–Rao lower bounds were sufficiently low (< 30%) for eight metabolites of interest (total creatine, N-acetylaspartate, N-acetylaspartate + N-acetylaspartylglutamate, total choline, glutamine, glutamate, myo-inositol, and taurine), leading to highly reproducible metabolic maps. Similar spectral quality and metabolic maps were obtained with one and two averages, with slightly better contrast and brain coverage due to increased SNR in the latter case. Furthermore, the obtained metabolic maps were accurate enough to confirm the previously known brain regional distribution of some metabolites. The acquisitions proved high reproducibility over time. We demonstrated that the increased SNR and spectral resolution at 14.1 T can be translated into high spatial resolution in 1H-FID-MRSI of the rat brain in 13 min using the sequence and processing pipeline described herein. High-resolution 1H-FID-MRSI at 14.1 T provided robust, reproducible, and high-quality metabolic mapping of brain metabolites with minimal technical limitations.

The paper aims at improved reliability of magnetic resonance perfusion imaging and estimation of an extended set of biomarkers using these techniques. Magnetic resonance perfusion imaging is an important experimental methodology with main applications in diagnostics and therapy monitoring in oncology. The main two methods are Dynamic Contrast-Enhanced (DCE) Magnetic Resonance Imaging (MRI) and Dynamic Susceptibility Contrast (DSC) MRI. We combine these two methods in a simultaneous acquisition and data processing approach. For simultaneous DCE-DSC-MRI data processing, we suggest a conventional non-linear least-squares method and a method based on convolutional neural networks. We evaluated the proposed methods on realistically simulated synthetic datasets and illustrated their performance on a real dataset. Compared to the standard approach, the methods of simultaneous DCE-DSC-MRI analysis were more reliable. The two proposed methods of simultaneous DCE-DSC-MRI analysis were comparable, with the neural-network approach being computationally far more effective.