Publications

Neuropsychiatric malignancies frequently manifest at the level of individual cortical layers. The resolutions currently available for medical magnetic resonance imaging (MRI) prevent the study of these pathologies at clinically available field strengths of 3 T. Previous studies have claimed to have overcome these issues by extensions of quantitative MRI. Following this, the feasibility of multiexponential T1 relaxometry was assessed as a basis for in vivo delineation of cortical lamination. Three methods of non-linear least-squares-based multiexponential analysis were examined across key degrees of freedom identified in the literature. The methods employ a wide variety of ways to overcome the common pitfalls of multiexponential analysis, such as regularization, bound constraints, and repeated optimization from multiple starting points. A custom MRI phantom was 3D-printed and filled with various MnCL2 mixtures that represent the spin-lattice relaxation times that commonly occur in neocortical gray and white matter at 3 T. A 96 × 96-voxel image consisting of a single slice was acquired using a FLASH sequence and used to create 10 composite datasets with known distributions of T1 decay constants. The results showed that lowest relative error achieved across multiexponential models was approximately 20%. As achieving even this level of estimation accuracy requires either T1 ratios that rarely occur in the cerebral cortex or knowledge of the number of relaxation components and their expected values to a degree that is seldom feasible, the visualization of cortical layers based on these estimates is unlikely to represent their true distribution. In conclusion, the current methodological approaches do not allow for sufficiently precise estimation of T1 decay constants spanning the range of cortical gray and white matter.

Background: The heterogeneous diagnostic methods for sarcopenic obesity lack standardization across clinical practice. The 2022 ESPEN/EASO consensus established standardized diagnostic criteria emphasizing weight-adjusted muscle mass indices, yet implementation feasibility in bariatric surgery populations remains unexplored. The absence of validated cutoff values for Class III obesity and limited evidence on dual-modality assessment protocols represent critical barriers to clinical implementation. Objective: This pilot study objectively assessed the implementation of ESPEN/EASO consensus criteria using dual-modality DXA and MRI assessment in women undergoing sleeve gastrectomy, with primary focus on protocol completion rates, technical precision, and preliminary evaluation of weight-adjusted diagnostic indices. Methods: Following CONSORT 2010 pilot trial extension guidelines, this feasibility study analyzed eleven women (age 41.3 ± 7.9 years (95 % CI: 36.6–46.0 years), 41.0 ± 5.0 kg/m2 (95 % CI: 38.0–44.0 kg/m2) undergoing laparoscopic sleeve gastrectomy. Primary feasibility outcomes included dual-modality assessment completion rates, MRI segmentation algorithm performance, and protocol adherence. Secondary outcomes encompassed preliminary body composition changes and ASM/weight diagnostic utility evaluation using ESPEN/EASO recommended cutoffs. Results: Dual-modality assessment achieved 100 % completion rates with excellent technical precision (MRI segmentation Dice coefficient: 0.95 ± 0.01 for muscle, 0.95 ± 0.03 for adipose tissue). Protocol adherence was optimal with all participants completing scheduled assessments. Preliminary body composition analysis demonstrated substantial weight reduction of 29.4 ± 25.3 kg (95 % CI: 14.4–44.4 kg) at six months. ASM/weight ratios showed potential diagnostic utility, though wide confidence intervals reflect substantial uncertainty inherent in small sample analysis. Conclusions: Implementation of ESPEN/EASO consensus criteria demonstrates 100 % protocol completion rates and MRI segmentation precision with Dice coefficients of 0.95 ± 0.01 for muscle and 0.95 ± 0.03 for adipose tissue in bariatric surgery populations. This pilot study establishes the methodological foundation and demonstrates feasibility for larger-scale validation studies to develop diagnostic thresholds and optimize sarcopenic obesity assessment protocols in bariatric medicine.

Purpose Quantifying proton density fat fraction (PDFF) in small abdominal organs is challenging due to low T1/T2 contrast and susceptibility artifacts. We develop a hybrid 7-echo CSE-MRI sequence with arbitrary echo spacing, inspired by GRASE-type imaging, aiming for distortion-free PDFF mapping in small animals. The method is designed to be comparable to established conventional methods, with potential for increased robustness. Methods We developed a Fast Spin Echo Asymmetric Bipolar Multi-Gradient Echo (FSE-AbMGE) sequence by integrating a fast spin-echo readout with an asymmetrically placed bipolar multi-echo gradient-echo train. The sequence was implemented at 9.4 T and combined with robust phase unwrapping and water-fat reconstruction algorithms using full fat spectral modeling. Validation was performed using phantoms with known PDFF values (0–22 %) and in vivo experiments on several female mice (n = 2). Reference PDFF values were obtained using single-voxel 1H-MRS. Results The proposed method enabled high-resolution PDFF mapping with minimal chemical shift and susceptibility artifacts. Phantom experiments showed strong agreement with both spectroscopic and ground truth values (R2 > 0.98, p < 0.001). The method was also tested in vivo, demonstrating robust water-fat separation and quantification. Conclusion The FSE-AbMGE sequence is well-suited for accurate abdominal fat quantification in small animals. While additional validation is needed, especially in reproducibility and broader biological settings, the method shows promise for high-field fat quantification and may offer a framework adaptable to lower-field pre-clinical applications.

Magnetic resonance imaging (MRI) is a powerful tool for studying nanoparticle biodistribution in vivo. However, conventional approaches usually rely on qualitative assessment from T1-, T2-, or T2*-weighted images. These methods provide only indirect estimates of nanoparticle concentration and are sensitive to motion artifacts. We present a new quantitative MRI methodology for evaluating biodistribution of Gadolinium-labeled nanoparticles in small animals. The method is based on T1 mapping and designed to be robust against respiratory and potentially also cardiac motion, ensuring reliable longitudinal measurements of nanoparticle concentrations. The approach was tested in six tumor-bearing mice (Balb/c, 4T1 tumor), each imaged at five fixed time points within 48 hours after intravenous administration of Gadolinium-labeled lipid nanoparticles carrying ellipticine, or, as a reference, the standard contrast agent Gadovist. Our results demonstrate reproducible T1 quantification in the tumor, kidney, liver, and spleen, enabling direct and quantitative analysis of nanoparticle accumulation and clearance over time. This methodology represents a robust, noninvasive strategy for assessing nanoparticle biodistribution and may facilitate the development of novel nanomedicine therapies.

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.