A Gadolinium(III) Complex Based on Pyridoxine Molecule with Single-Ion Magnet and Magnetic Resonance Imaging Properties.

Pyridoxine (pyr) is a versatile molecule that forms part of the family of B vitamins. It is used to treat and prevent vitamin B6 deficiency and certain types of metabolic disorders. Moreover, the pyridoxine molecule has been investigated as a suitable ligand toward metal ions. Nevertheless, the study of the magnetic properties of metal complexes containing lanthanide(III) ions and this biomolecule is unexplored. We have synthesized and characterized a novel pyridoxine-based GdIII complex of formula [GdIII(pyr)2(H2O)4]Cl3 · 2 H2O (1) [pyr = pyridoxine]. 1 crystallizes in the triclinic system and space group Pi. In its crystal packing, cationic [Gd(pyr)2(H2O)4]3+ entities are connected through H-bonding interactions involving non-coordinating water molecules and chloride anions. In addition, Hirshfeld surfaces of 1 were calculated to further investigate their intermolecular interactions in the crystal lattice. Our investigation of the magnetic properties of 1, through ac magnetic susceptibility measurements, reveals the occurrence of a slow relaxation in magnetization in this mononuclear GdIII complex, indicating an unusual single-ion magnet (SIM) behavior for this pseudo-isotropic metal ion at very low temperatures. We also studied the relaxometric properties of 1, as a potential contrast agent for high-field magnetic resonance imaging (MRI), from solutions of 1 prepared in physiological serum (0.0-3.2 mM range) and measured at 3 T on a clinical MRI scanner. The values of relaxivity obtained for 1 are larger than those of some commercial MRI contrast agents based on mononuclear GdIII systems.

Development and validation of an image biomarker to identify metabolic dysfunction associated steatohepatitis: MR-MASH score.

BACKGROUND AND AIMS: Diagnosis of metabolic dysfunction-associated steatohepatitis (MASH) requires histology. In this study, a magnetic resonance imaging (MRI) score was developed and validated to identify MASH in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). Secondarily, a screening strategy for MASH diagnosis was investigated. METHODS: This prospective multicentre study included 317 patients with biopsy-proven MASLD and contemporaneous MRI. The discovery cohort (Spain, Portugal) included 194 patients. NAFLD activity score (NAS) and fibrosis were assessed with the NASH-CRN histologic system. MASH was defined by the presence of steatosis, lobular inflammation, and ballooning, with NAS ≥4 with or without fibrosis. An MRI-based composite biomarker of Proton Density Fat Fraction and waist circumference (MR-MASH score) was developed. Findings were afterwards validated in an independent cohort (United States, Spain) with different MRI protocols. RESULTS: In the derivation cohort, 51% (n = 99) had MASH. The MR-MASH score identified MASH with an AUC = .88 (95% CI .83-.93) and strongly correlated with NAS (r = .69). The MRI score lower cut-off corresponded to 88% sensitivity with 86% NPV, while the upper cut-off corresponded to 92% specificity with 87% PPV. MR-MASH was validated with an AUC = .86 (95% CI .77-.92), 91% sensitivity (lower cut-off) and 87% specificity (upper cut-off). A two-step screening strategy with sequential MR-MASH examination performed in patients with indeterminate-high FIB-4 or transient elastography showed an 83-84% PPV to identify MASH. The AUC of MR-MASH was significantly higher than that of the FAST score (p < .001). CONCLUSIONS: The MR-MASH score has clinical utility in the identification and management of patients with MASH at risk of progression.

Brain network functional connectivity changes in patients with anterior knee pain: a resting-state fMRI exploratory study.

BACKGROUND: This study investigates the functional brain connectivity in patients with anterior knee pain (AKP). While biomechanical models are frequently employed to investigate AKP, it is important to recognize that pain can manifest even in the absence of structural abnormalities. Leveraging the capabilities of functional magnetic resonance imaging (fMRI), this research aims to investigate the brain mechanisms present in AKP patients. METHODS: Forty-five female subjects (24 AKP patients, 21 controls) underwent resting-state fMRI and T1-weighted structural MRI. Functional brain connectivity patterns were analyzed, focusing on pain network areas, and the influence of catastrophizing thoughts was evaluated. RESULTS: Comparing patients and controls, several findings emerged. First, patients with AKP exhibited increased correlation between the right supplementary motor area and cerebellum I, as well as decreased correlation between the right insula and the left rostral prefrontal cortex and superior frontal gyrus. Second, in AKP patients with catastrophizing thoughts, there was increased correlation of the left lateral parietal cortex with two regions of the right cerebellum (II and VII) and the right pallidum, and decreased correlation between the left medial frontal gyrus and the right thalamus. Furthermore, the correlation between these regions showed promising results for discriminating AKP patients from controls, achieving a cross-validation accuracy of 80.5%. CONCLUSIONS: Resting-state fMRI revealed correlation differences in AKP patients compared to controls and based on catastrophizing thoughts levels. These findings shed light on neural correlates of chronic pain in AKP, suggesting that functional brain connectivity alterations may be linked to pain experience in this population. RELEVANCE STATEMENT: Etiopathogenesis of pain in anterior knee pain patients might not be limited to the knee, but also to underlying alterations in the central nervous system: cortical changes might lead a perpetuation of pain. KEY POINTS: • Anterior knee pain patients exhibit distinct functional brain connectivity compared to controls, and among catastrophizing subgroups. • Resting-state fMRI reveals potential for discriminating anterior knee pain patients with 80.5% accuracy. • Functional brain connectivity differences improve understanding of pain pathogenesis and objective anterior knee pain identification.

Pancreatic steatosis and iron overload increases cardiovascular risk in non-alcoholic fatty liver disease.

Objective: To assess the prevalence of pancreatic steatosis and iron overload in non-alcoholic fatty liver disease (NAFLD) and their correlation with liver histology severity and the risk of cardiometabolic diseases. Method: A prospective, multicenter study including NAFLD patients with biopsy and paired Magnetic Resonance Imaging (MRI) was performed. Liver biopsies were evaluated according to NASH Clinical Research Network, hepatic iron storages were scored, and digital pathology quantified the tissue proportionate areas of fat and iron. MRI-biomarkers of fat fraction (PDFF) and iron accumulation (R2*) were obtained from the liver and pancreas. Different metabolic traits were evaluated, cardiovascular disease (CVD) risk was estimated with the atherosclerotic CVD score, and the severity of iron metabolism alteration was determined by grading metabolic hiperferritinemia (MHF). Associations between CVD, histology and MRI were investigated. Results: In total, 324 patients were included. MRI-determined pancreatic iron overload and moderate-to severe steatosis were present in 45% and 25%, respectively. Liver and pancreatic MRI-biomarkers showed a weak correlation (r=0.32 for PDFF, r=0.17 for R2*). Pancreatic PDFF increased with hepatic histologic steatosis grades and NASH diagnosis (p<0.001). Prevalence of pancreatic steatosis and iron overload increased with the number of metabolic traits (p<0.001). Liver R2* significantly correlated with MHF (AUC=0.77 [0.72-0.82]). MRI-determined pancreatic steatosis (OR=3.15 [1.63-6.09]), and iron overload (OR=2.39 [1.32-4.37]) were independently associated with high-risk CVD. Histologic diagnosis of NASH and advanced fibrosis were also associated with high-risk CVD. Conclusion: Pancreatic steatosis and iron overload could be of utility in clinical decision-making and prognostication of NAFLD.

Quantitative magnetic resonance imaging assessment of muscle composition in myotonic dystrophy mice.

Myotonic dystrophy type 1 (DM1) is a severe autosomal dominant neuromuscular disease in which the musculoskeletal system contributes substantially to overall mortality and morbidity. DM1 stems from a noncoding CTG trinucleotide repeat expansion in the DMPK gene. The human skeletal actin long repeat (HSALR) mouse model reproduces several aspects of the disease, but the muscle-wasting phenotype of this model has never been characterized in vivo. Herein, we used quantitative MRI to measure the fat and muscle volumes in the leg compartment (LC) of mice. These acquired data were processed to extract relevant parameters such as fat fraction and fat infiltration (fat LC/LC) in HSALR and control (FBV) muscles. These results showed increased fat volume (fat LC) and fat infiltration within the muscle tissue of the leg compartment (muscle LC), in agreement with necropsies, in which fatty clumps were observed, and consistent with previous findings in DM1 patients. Model mice did not reproduce the characteristic impaired fat fraction, widespread fat replacement through the muscles, or reduced muscle volume reported in patients. Taken together, the observed abnormal replacement of skeletal muscle by fat in the HSALR mice indicates that these mice partially reproduced the muscle phenotype observed in humans.

Knee Cartilage and Subchondral Bone Evaluations by Magnetic Resonance Imaging Correlate with Histological Biomarkers in an Osteoarthritis Rabbit Model.

OBJECTIVE: To evaluate pathological changes in cartilage and subchondral bone MRI biomarkers in a rabbit model of osteoarthritis (OA) and correlate these with histological variations. DESIGN: Transection of the anterior cruciate ligament was performed on the right knee of eighteen 12-week-old New Zealand white rabbits to induce OA. 3-Tesla MR images were obtained from 18 healthy control knees (left) and 18 knees with OA (right). Imaging biomarkers included volume, thickness, T1 and T2* cartilage parametric maps, and several subchondral bone features: bone volume to total volume ratio, trabecular thickness, trabecular spacing, trabecular number (TbN), 2D and 3D fractal dimensions, and quality of trabecular score (QTS). Microscopic analysis of the lateral femoral condyles was set as the ground truth. RESULTS: When healthy and osteoarthritic knees were compared, significant differences were seen in the T1 and T2* values of the femur and tibia cartilage and in the subchondral bone volume to total volume, TbN, and QTS of both the lateral and medial aspects of the femur and tibia. Histological findings revealed significant osteoarthritic changes between healthy and osteoarthritic knees in stain, structure, chondrocyte density, total score, and subchondral bone biomarker levels. A positive correlation was found between histological staining, structure, chondrocyte density, and total score variables in T1 and T2* cartilage biomarkers. A negative correlation was observed between histological subchondral bone variables and magnetic resonance D2D and QTS biomarkers. CONCLUSION: Quantification of several cartilage and subchondral bone imaging biomarkers in a rabbit model of OA allows the detection of significant changes, which are correlated with histological findings.

Improved Joint Health Following Oral Administration of Glycosaminoglycans with Native Type II Collagen in a Rabbit Model of Osteoarthritis.

A prospective, experimental, randomized, double blinded study was designed to evaluate the effects of glycosaminoglycans, with or without native type II collagen (NC), in an osteoarthritis model induced by cranial cruciate ligament transection. The following compounds were tested: chondroitin sulfate (CS), glucosamine hydrochloride (GlHCl), hyaluronic acid (HA) and NC. Fifty-four female 12-week-old New Zealand rabbits were classified into three groups: CTR (control-no treatment), CGH (CS + GlHCl + HA) and CGH-NC (CS + GlHCl + HA + NC). Each group was subdivided into three subgroups according to survival times of 24, 56 and 84 days. Over time, all rabbits developed degenerative changes associated with osteoarthritis. CGH-NC showed significantly improved values on macroscopic evaluation, compared to CTR and CGH. Microscopically, significantly better results were seen with CGH and CGH-NC, compared to CTR, and synovial membrane values were significantly better with CGH-NC compared to CGH. A significant improvement in magnetic resonance imaging biomarkers was also observed with CGH-NC in cartilage transversal relaxation time (T2) and subchondral bone D2D fractal dimension in the lateral condyle. In conclusion, our results show beneficial effects on joint health of CGH and CGH-NC and also supports that adding NC to CGH results in even greater efficacy.

Intravenous SPION-labeled adipocyte-derived stem cells targeted to the brain by magnetic attraction in a rat stroke model: An ultrastructural insight into cell fate within the brain.

Mesenchymal stem cell therapy after stroke is a promising option investigated in animal models and clinical trials. The intravenous route is commonly used in clinical settings guaranteeing an adequate safety profile although low yields of engraftment. In this report, rats subjected to ischemic stroke were injected with adipose-derived stem cells (ADSCs) labeled with superparamagnetic iron oxide nanoparticles (SPIONs) applying an external magnetic field in the skull to retain the cells. Although most published studies demonstrate viability of ADSCs, only a few have used ultrastructural techniques. In our study, the application of a local magnetic force resulted in a tendency for higher yields of SPION-ADSCs targeting the brain. However, grafted cells displayed morphological signs of death, one day after administration, and correlative microscopy showed active microglia and astrocytes associated in the process of scavenging. Thus, we conclude that, although successfully targeted within the brain, SPION-ADSCs viability was rapidly compromised.

Medical imaging clinical trials unit: A professional need.

PURPOSE: To design and describe a management and control tool and the human resources needed to efficiently manage the imaging process within clinical trials for a better quality of care for the patient. METHODS: A unit was created to efficiently organise the participation of our Medical Imaging Department in clinical trials. This entity was defined and monitored using a customized, flexible and modular software package that provides the necessary information to execute and monitor requests (appointments, protocols, reports, complaints, billing). Various indicators of activity and professional satisfaction were parameterised. RESULTS: From 2016 to 2020, 367 trials were participated and monitored, 50% of all the hospital clinical trials. The budget of the Medical Imaging Department grew by 47% in this period. The coordination with other departments and principal investigators improved, as shown by surveys (62% fluid and 38% very fluid), with a high perception of collaboration (86%). CONCLUSIONS: The implementation of a Medical Imaging Clinical Trials Unit involve identifying the tasks, personnel, organisational needs, workflow, monitoring and invoicing. The creation of this Unit has improved the control and traceability of clinical trials within the Department.

Quantification of H217O by 1H-MR imaging at 3 T: a feasibility study.

BACKGROUND: Indirect 1H-magnetic resonance (MR) imaging of 17O-labelled water allows imaging in vivo dynamic changes in water compartmentalisation. Our aim was to describe the feasibility of indirect 1H-MR methods to evaluate the effect of H217O on the MR relaxation rates by using conventional a 3-T equipment and voxel-wise relaxation rates. METHODS: MR images were used to calculate the R1, R2, and R2* relaxation rates in phantoms (19 vials with different H217O concentrations, ranging from 0.039 to 5.5%). Afterwards, an experimental animal pilot study (8 rats) was designed to evaluate the in vivo relative R2 brain dynamic changes related to the intravenous administration of 17O-labelled water in rats. RESULTS: There were no significant changes on the R1 and R2* values from phantoms. The R2 obtained with the turbo spin-echo T2-weighted sequence with 20-ms echo time interval had the higher statistical difference (0.67 s-1, interquartile range 0.34, p < 0.001) and Spearman correlation (rho 0.79). The R2 increase was adjusted to a linear fit between 0.25 and 5.5%, represented with equation R2 = 0.405 concentration + 0.3215. The highest significant differences were obtained for the higher concentrations (3.1-5.5%). The rat brain MR experiment showed a mean 10% change in the R2 value after the H217O injection with progressive normalisation. CONCLUSIONS: Indirect 1H-MR imaging method is able to measure H217O concentration by using R2 values and conventional 3-T MR equipment. Normalised R2 relative dynamic changes after the intravenous injection of a H217O saline solution provide a unique opportunity to map water pathophysiology in vivo, opening the analysis of aquaporins status and modifications by disease at clinically available 3-T proton MR scanners.

Predictive Clinical Decision Support System Using Machine Learning and Imaging Biomarkers in Patients With Neurostimulation Therapy: A Pilot Study.

BACKGROUND: Chronic pain is correlated with alterations in brain structure and function. The selection process for the ideal candidate for spinal cord stimulation (SCS) therapy is based on functional variables analysis and pain evaluation scores. In addition to the difficulties involved in the initial selection of patients and the predictive analysis of the trial phase, the large rate of explants is one of the most important concerns in the analysis of the suitability of implanted candidates. OBJECTIVE: To investigate the usefulness of imaging biomarkers, functional connectivity (FC) and volumetry of the whole brain in patients with Failed back surgery syndrome (FBSS) and to create a clinical patient-based decision support system (CDSS) combining neuroimaging and clinical data for predicting the effectiveness of neurostimulation therapy after a trial phase. STUDY DESIGN: A prospective, consecutive, observational, single center study. SETTING: The Multidisciplinary Pain Management Department of the General University Hospital in Valencia, Spain. METHODS: A prospective, consecutive, and observational single-center study. Using Resting-state functional magnetic resonance imaging (rs-fMRI) and Region of interest (ROI) to ROI analysis, we compared the functional connectivity between regions to detect differences in FC and volume changes. Basal magnetic resonance images were obtained in a 1.5T system and clinical variables were collected twice, at the basal condition and at 6-months post-SCS implant. We also conducted a seed-to-voxel analysis with 9 items as seed-areas characterizing the functional connectivity networks. A decreased in 10 units in the Pain Detect Questionnaire (PD-Q) score was established to define the subgroup of Responders Group (R-G) to neurostimulation therapy. The clinical variables collected and the imaging biomarkers obtained (FC and volumes) were tested on a set of 6 machine learning approaches in an effort to find the best classifier system for predicting the effectiveness of the neurostimulator. RESULTS: Twenty-four patients were analyzed and only seven were classified in the R-G. Volumetric differences were found in the left putamen, F = 34.06, P = 0.02. Four pairwise brain areas showed statistical differences in the rs-fMRI including the right insular cortex. Linear Discriminant Analysis showed the best performance for building the CDSS combining clinical variables and significant imaging biomarkers, the prediction increased diagnostic accuracy in the R-G patients from 29% in current practice to 96% of long-term success. CONCLUSION: These findings confirm a major role of the left putamen and the four pairs of brain regions in FBBS patients and suggest that a CDSS would be able to select patients susceptible to benefitting from SCS therapy adding imaging biomarkers.

A Gadolinium(III) Complex Based on the Thymine Nucleobase with Properties Suitable for Magnetic Resonance Imaging.

The paramagnetic gadolinium(III) ion is used as contrast agent in magnetic resonance (MR) imaging to improve the lesion detection and characterization. It generates a signal by changing the relaxivity of protons from associated water molecules and creates a clearer physical distinction between the molecule and the surrounding tissues. New gadolinium-based contrast agents displaying larger relaxivity values and specifically targeted might provide higher resolution and better functional images. We have synthesized the gadolinium(III) complex of formula [Gd(thy)2(H2O)6](ClO4)3·2H2O (1) [thy = 5-methyl-1H-pyrimidine-2,4-dione or thymine], which is the first reported compound based on gadolinium and thymine nucleobase. 1 has been characterized through UV-vis, IR, SEM-EDAX, and single-crystal X-ray diffraction techniques, and its magnetic and relaxometric properties have been investigated by means of SQUID magnetometer and MR imaging phantom studies, respectively. On the basis of its high relaxivity values, this gadolinium(III) complex can be considered a suitable candidate for contrast-enhanced magnetic resonance imaging.

Machine Learning-Based Integration of Prognostic Magnetic Resonance Imaging Biomarkers for Myometrial Invasion Stratification in Endometrial Cancer.

BACKGROUND: Estimation of the depth of myometrial invasion (MI) in endometrial cancer is pivotal in the preoperatively staging. Magnetic resonance (MR) reports suffer from human subjectivity. Multiparametric MR imaging radiomics and parameters may improve the diagnostic accuracy. PURPOSE: To discriminate between patients with MI ≥ 50% using a machine learning-based model combining texture features and descriptors from preoperatively MR images. STUDY TYPE: Retrospective. POPULATION: One hundred forty-three women with endometrial cancer were included. The series was split into training (n = 107, 46 with MI ≥ 50%) and test (n = 36, 16 with MI ≥ 50%) cohorts. FIELD STRENGTH/SEQUENCES: Fast spin echo T2-weighted (T2W), diffusion-weighted (DW), and T1-weighted gradient echo dynamic contrast-enhanced (DCE) sequences were obtained at 1.5 or 3 T magnets. ASSESSMENT: Tumors were manually segmented slice-by-slice. Texture metrics were calculated from T2W and ADC map images. Also, the apparent diffusion coefficient (ADC), wash-in slope, wash-out slope, initial area under the curve at 60 sec and at 90 sec, initial slope, time to peak and peak amplitude maps from DCE sequences were obtained as parameters. MR diagnostic models using single-sequence features and a combination of features and parameters from the three sequences were built to estimate MI using Adaboost methods. The pathological depth of MI was used as gold standard. STATISTICAL TEST: Area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, accuracy, positive predictive value, negative predictive value, precision and recall were computed to assess the Adaboost models performance. RESULTS: The diagnostic model based on the features and parameters combination showed the best performance to depict patient with MI ≥ 50% in the test cohort (accuracy = 86.1% and AUROC = 87.1%). The rest of diagnostic models showed a worse accuracy (accuracy = 41.67%-63.89% and AUROC = 41.43%-63.13%). DATA CONCLUSION: The model combining the texture features from T2W and ADC map images with the semi-quantitative parameters from DW and DCE series allow the preoperative estimation of myometrial invasion. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 3.

The Brain Resting-State Functional Connectivity Underlying Violence Proneness: Is It a Reliable Marker for Neurocriminology? A Systematic Review.

Introduction: There is growing scientific interest in understanding the biological mechanisms affecting and/or underlying violent behaviors in order to develop effective treatment and prevention programs. In recent years, neuroscientific research has tried to demonstrate whether the intrinsic activity within the brain at rest in the absence of any external stimulation (resting-state functional connectivity; RSFC) could be employed as a reliable marker for several cognitive abilities and personality traits that are important in behavior regulation, particularly, proneness to violence. Aims: This review aims to highlight the association between the RSFC among specific brain structures and the predisposition to experiencing anger and/or responding to stressful and distressing situations with anger in several populations. Methods: The scientific literature was reviewed following the PRISMA quality criteria for reviews, using the following digital databases: PubMed, PsycINFO, Psicodoc, and Dialnet. Results: The identification of 181 abstracts and retrieval of 34 full texts led to the inclusion of 17 papers. The results described in our study offer a better understanding of the brain networks that might explain the tendency to experience anger. The majority of the studies highlighted that diminished RSFC between the prefrontal cortex and the amygdala might make people prone to reactive violence, but that it is also necessary to contemplate additional cortical (i.e. insula, gyrus [angular, supramarginal, temporal, fusiform, superior, and middle frontal], anterior and posterior cingulated cortex) and subcortical brain structures (i.e. hippocampus, cerebellum, ventral striatum, and nucleus centralis superior) in order to explain a phenomenon as complex as violence. Moreover, we also described the neural pathways that might underlie proactive violence and feelings of revenge, highlighting the RSFC between the OFC, ventral striatal, angular gyrus, mid-occipital cortex, and cerebellum. Conclusions. The results from this synthesis and critical analysis of RSFC findings in several populations offer guidelines for future research and for developing a more accurate model of proneness to violence, in order to create effective treatment and prevention programs.

Imaging Biomarkers for the Diagnosis and Prognosis of Neurodegenerative Diseases. The Example of Amyotrophic Lateral Sclerosis.

The term amyotrophic lateral sclerosis (ALS) comprises a heterogeneous group of fatal neurodegenerative disorders of largely unknown etiology characterized by the upper motor neurons (UMN) and/or lower motor neurons (LMN) degeneration. The development of brain imaging biomarkers is essential to advance in the diagnosis, stratification and monitoring of ALS, both in the clinical practice and clinical trials. In this review, the characteristics of an optimal imaging biomarker and common pitfalls in biomarkers evaluation will be discussed. Moreover, the development and application of the most promising brain magnetic resonance (MR) imaging biomarkers will be reviewed. Finally, the integration of both qualitative and quantitative multimodal brain MR biomarkers in a structured report will be proposed as a support tool for ALS diagnosis and stratification.

Discrete particle model for cement infiltration within open-cell structures: Prevention of osteoporotic fracture.

This paper proposes a discrete particle model based on the random-walk theory for simulating cement infiltration within open-cell structures to prevent osteoporotic proximal femur fractures. Model parameters consider the cement viscosity (high and low) and the desired direction of injection (vertical and diagonal). In vitro and in silico characterizations of augmented open-cell structures validated the computational model and quantified the improved mechanical properties (Young's modulus) of the augmented specimens. The cement injection pattern was successfully predicted in all the simulated cases. All the augmented specimens exhibited enhanced mechanical properties computationally and experimentally (maximum improvements of 237.95 ± 12.91% and 246.85 ± 35.57%, respectively). The open-cell structures with high porosity fraction showed a considerable increase in mechanical properties. Cement augmentation in low porosity fraction specimens resulted in a lesser increase in mechanical properties. The results suggest that the proposed discrete particle model is adequate for use as a femoroplasty planning framework.