Spin-lattice Relaxation Research Articles

Preoperative MRI-based radiomic nomogram for distinguishing solitary fibrous tumor from angiomatous meningioma: a multicenter study.

This study evaluates the efficacy of radiomics-based machine learning methodologies in differentiating solitary fibrous tumor (SFT) from angiomatous meningioma (AM). A retrospective analysis was conducted on 171 pathologically confirmed cases (94 SFT and 77 AM) spanning from January 2009 to September 2020 across four institutions. The study comprised a training set (n=137) and a validation set (n=34). All patients underwent contrast-enhanced T1-weighted (CE-T1WI) and T2-weighted(T2WI) MRI scans, from which 1166 radiomics features were extracted. Subsequently, seventeen features were selected through minimum redundancy maximum relevance (mRMR) and the least absolute shrinkage and selection operator (LASSO). Multivariate logistic regression analysis was employed to assess the independence of these features as predictors. A clinical model, established via both univariate and multivariate logistic regression based on MRI morphological features, was integrated with the optimal radiomics model to formulate a radiomics nomogram. The performance of the models was assessed utilizing the area under the receiver operating characteristic curve (AUC), accuracy (ACC), sensitivity (SEN), specificity (SPE), positive predictive value (PPV), and negative predictive value (NPV). The radiomics nomogram demonstrated exceptional discriminative performance in the validation set, achieving an AUC of 0.989. This outperformance was evident when compared to both the radiomics algorithm (AUC= 0.968) and the clinical model (AUC = 0.911) in the same validation sets. Notably, the radiomics nomogram exhibited impressive values for ACC, SEN, and SPE at 97.1%, 93.3%, and 100%, respectively, in the validation set. The machine learning-based radiomic nomogram proves to be highly effective in distinguishing between SFT and AM.

Investigation of biomolecular dynamics by sensitivity-enhanced 1H–2H CPMAS NMR using matrix-free dynamic nuclear polarization

Molecular dynamics of functional groups contain valuable information about structural properties and functional activities in biomolecules. NMR spectroscopy is a sensitive tool for the investigation of molecular dynamics over a wide range of timescales and thus may deepen the understanding of the biomolecules of interest. Here, we present an approach to use DNP-enhanced 2H NMR to study dynamics of selectively deuterated methyl groups in insoluble proteins such as amyloid beta (Aβ) fibrils. We adopted and optimized the matrix-free DNP approach by varying the amount of added polarizing agent as well as the rehydration level of model proteins. We show that the DNP enhancement obtained in 1H–2H cross-polarization (CP) MAS spectra may increase the sensitivity for selectively deuterated Aβ fibril samples by more than one order of magnitude, accelerating the collection of spin-lattice relaxation data in the DNP-accessible temperature range between 100 and 150 K by up to 400-fold. However, below the coalescence temperature, which describes the transition from the fast to the slow exchange regime, the experimentally obtained relaxation time constants suffer from a paramagnetic relaxation enhancement effect due to the presence of the polarizing agent. This seems to be a general effect for biomolecules as it is also confirmed for two other protein model systems. Our demonstration opens the possibility to extend the scope of 2H NMR for dynamics measurements to effective concentrations and/or temperatures below what is currently accessible; however, the observed interplay between paramagnetic relaxation and molecular dynamics also emphasizes the necessity for a better understanding of relaxation effects in DNP-enhanced NMR.

Involvement of the cerebellum in structural connectivity enhancement in episodic migraine

BackgroundThe pathophysiology of migraine remains poorly understood, yet a growing number of studies have shown structural connectivity disruptions across large-scale brain networks. Although both structural and functional changes have been found in the cerebellum of migraine patients, the cerebellum has barely been assessed in previous structural connectivity studies of migraine. Our objective is to investigate the structural connectivity of the entire brain, including the cerebellum, in individuals diagnosed with episodic migraine without aura during the interictal phase, compared with healthy controls.MethodsTo that end, 14 migraine patients and 15 healthy controls were recruited (all female), and diffusion-weighted and T1-weighted MRI data were acquired. The structural connectome was estimated for each participant based on two different whole-brain parcellations, including cortical and subcortical regions as well as the cerebellum. The structural connectivity patterns, as well as global and local graph theory metrics, were compared between patients and controls, for each of the two parcellations, using network-based statistics and a generalized linear model (GLM), respectively. We also compared the number of connectome streamlines within specific white matter tracts using a GLM.ResultsWe found increased structural connectivity in migraine patients relative to healthy controls with a distinct involvement of cerebellar regions, using both parcellations. Specifically, the node degree of the posterior lobe of the cerebellum was greater in patients than in controls and patients presented a higher number of streamlines within the anterior limb of the internal capsule. Moreover, the connectomes of patients exhibited greater global efficiency and shorter characteristic path length, which correlated with the age onset of migraine.ConclusionsA distinctive pattern of heightened structural connectivity and enhanced global efficiency in migraine patients compared to controls was identified, which distinctively involves the cerebellum. These findings provide evidence for increased integration within structural brain networks in migraine and underscore the significance of the cerebellum in migraine pathophysiology.

Impacts of Small SBA-15 Mesopores on Translation and Rotational Diffusion of Benzyl Alcohol.

Small SBA-15 pores can enhance the catalytic activity of gold catalysts in the selective oxidation of benzyl alcohol reaction. The goal of this work is to probe the impact of SBA-15 pores on the translational and rotational diffusion of the reactive species (e.g., benzyl alcohol). Herein, we demonstrate the use of nuclear magnetic resonance-based diffusion-ordered spectroscopy (DOSY) and T1 relaxation techniques to measure the translational and rotational diffusion coefficients of liquid benzyl alcohol molecules in three distinct environments: bulk, pore, and near-surface. The DOSY and T1 relaxation techniques render the routine diffusion measurements for liquid molecules confined in small pores possible. Furthermore, we measure the translational and rotational diffusion coefficients of benzyl alcohol molecules in the bulk, pore, and near-surface environments at varying temperatures. These measurements are then correlated via the Arrhenius equation to determine the activation energy associated with their translational (Et) and rotational (Er) diffusion. A higher activation energy suggests a more difficult diffusion process, while a lower activation energy implies a facile diffusion process. Our findings demonstrate that the ranking of Et follows the order of bulk (difficult) > near-surface > pore (easy), whereas the ranking of Er follows the order of pore (difficult) > bulk > near-surface (easy). This result suggests that the small SBA-15 pores can facilitate the translational diffusion but hinder the rotational diffusion of benzyl alcohol molecules.

Evaluation of Inflammatory Disease Activity in the Sacroiliac Joints Using Magnetic Resonance Imaging: A Comparative Analysis of Short-Tau Inversion Recovery, Post-Contrast, and Diffusion-Weighted Imaging –Preliminary Study

Introduction: It is essential to detect sacroiliitis earlier to decrease morbidity and unwanted complications such as ankylosing of sacroiliac joints. In recent studies, magnetic resonance imaging (MRI) serves as a key diagnostic tool for identifying sacroiliitis and is now included in the diagnostic criteria. We aim to detect the utility of diffusion-weighted imaging on the MRI in diagnosing sacroiliitis and measure ADC values for the response to treatment in future studies. Materials -methods: There were 39 patients (16 male, 20 female). A 1.5 Tesla MR device with a pelvic coil was used. The sequences were T1 (before and after intravenous contrast administration of gadolinium), T2-weighted fast field echo, short tau inversion recovery (STIR), diffusion-weighted (DW) images, and apparent diffusion coefficient (ADC) mapping. Sacroiliac joints were divided into four quadrants, and two radiologists interpreted all the sequences by giving scores from 0 to 3 depending on bone marrow edema from none to severe. The concordance of scores assigned to STIR, T1-weighted gadolinium-enhanced images, ADC mapping, and diffusion-weighted MR images was evaluated by calculating intraclass correlation coefficients. Results: A statistically significant positive correlation was observed between the activity scores derived from short tau inversion recovery (STIR) and other magnetic resonance (MR) sequences, namely T1-weighted gadolinium-enhanced images, apparent diffusion coefficient (ADC) mapping, and diffusion-weighted MR images. Conclusion: Active bone marrow abnormalities were identified with comparable efficacy using STIR imaging and other MR sequences (T1W-Gad, ADC mapping, DW-MR). In our study, we tried to emphasize the role of the diffusion-weighted images near the other sequences. Diffusion is a fast, easy-applied sequence. After increased experience in the diffusion-weighted images, routine application of this sequence will increase, and even becoming one of the diagnostic criteria will be inevitable. The difference in DWI from the other sequences is that it is measurable. The response to treatment may be followed up by ADC values.

Comparison of Explainable AI Models for MRI-based Alzheimer's Disease Classification.

Deep learning models based on convolutional neural networks (CNNs) have been used to classify Alzheimer's disease or infer dementia severity from 3D T1-weighted brain MRI scans. Here, we examine the value of adding occlusion sensitivity analysis (OSA) and gradient-weighted class activation mapping (Grad-CAM) to these models to make the results more interpretable. Much research in this area focuses on specific datasets such as the Alzheimer's Disease Neuroimaging Initiative (ADNI) or National Alzheimer's Coordinating Center (NACC), which assess people of North American, predominantly European ancestry, so we examine how well models trained on these data generalize to a new population dataset from India (NIMHANS cohort). We also evaluate the benefit of using a combined dataset to train the CNN models. Our experiments show feature localization consistent with knowledge of AD from other methods. OSA and Grad-CAM resolve features at different scales to help interpret diagnostic inferences made by CNNs.

Advancements in opportunistic intracranial aneurysm screening: The impact of a deep learning algorithm on radiologists' analysis of T2-weighted cranial MRI

(1) Background: Unruptured Intracranial Aneurysms (UIAs) are common blood vessel malformations, occurring in up to 3 % of healthy adults. Magnetic Resonance Angiography (MRA) is frequently used for the screening of UIAs due to its high resolution in vascular anatomy. However, T2-Weighted Magnetic Resonance Imaging (T2WI) is a standard sequence utilized for the majority of outpatient head scans. By employing a sequence such as T2WI, there is a possible shift towards early detection of UIAs through opportunistic screening. Here, we assess a Deep Learning Algorithm (DLA) developed to assist radiologists in identifying and reporting UIAs on T2WI in a routine clinical setting. (2) Methods: A DLA was trained on a set of 110 patients undergoing an MR head scan with the gold standard set by two radiology experts. Eight radiologists were given a cohort of 50 cranial T2WI studies and asked for a routine report. After a 10-day washout period, they reviewed the same cases randomized and supported by the DLA predictions. We assessed changes in sensitivity, specificity, accuracy, and false positives. (3) Results: During routine reporting, the models’ assistance improved the sensitivity of the eight participants by an average of 36.19 and the accuracy by 10.00 percentage points. (4) Conclusion: Our results indicate the potential benefit of deep learning to improve radiologists' detection of UIAs during routine reporting. From this, we can infer that the combination of T2WI with our DLA supports opportunistic screening, suggesting potential approaches for future research and application.

Fluoropolymer-Gadolinium(III) Hybrids for Photoactivatable Dual-Mode T1-Weighted 1H MRI and 19F MRI Contrast Agents.

Multimodal imaging probes play a crucial role in overcoming the limitations associated with single-mode imaging for clinical medical diagnosis. This study focuses on the development of a photoresponsive fluorine-containing water-soluble polymer (PF) through RAFT polymerization. Subsequently, a polymer-gadolinium(III) hybrid (PF-Gd) dual-modal probe capable of T1-weighted 1H MRI and 19F MRI was synthesized via postmodification of PF with a Gd-DOTA derivative. Under physiological conditions (pH = 7.4), the hybrids exhibit UV-activated 19F NMR/MRI and enhanced 1H MRI. The inclusion of Gd3+ facilitates the acceleration of water molecule T1 relaxation, leading to high-intensity 1H MRI contrast. Leveraging the paramagnetic relaxation enhancement (PRE) effect between fluorine atoms and Gd3+, the restoration of Gd3+-accelerated 19F T2 relaxation enables precise photoactivation of 19F MRI signals, transitioning from the "OFF" to the "ON" state. This study provides an important reference for the development of hybrid systems that function as real-time diagnostic tools and offers controlled activation for multimodal imaging probes.

Investigation of ComBat Harmonization on Radiomic and Deep Features from Multi-Center Abdominal MRI Data.

ComBat harmonization has been developed to remove non-biological variations for data in multi-center research applying artificial intelligence (AI). We investigated the effectiveness of ComBat harmonization on radiomic and deep features extracted from large, multi-center abdominal MRI data. A retrospective study was conducted on T2-weighted (T2W) abdominal MRI data retrieved from individual patients with suspected or known chronic liver disease at three study sites. MRI data were acquired using systems from three manufacturers and two field strengths. Radiomic features and deep features were extracted using the PyRadiomics pipeline and a Swin Transformer. ComBat was used to harmonize radiomic and deep features across different manufacturers and field strengths. Student's t-test, ANOVA test, and Cohen's F score were applied to assess the difference in individual features before and after ComBat harmonization. Between two field strengths, 76.7%, 52.9%, and 26.7% of radiomic features, and 89.0%, 56.5%, and 0.1% of deep features from three manufacturers were significantly different. Among the three manufacturers, 90.1% and 75.0% of radiomic features and 89.3% and 84.1% of deep features from two field strengths were significantly different. After ComBat harmonization, there were no significant differences in radiomic and deep features among manufacturers or field strengths based on t-tests or ANOVA tests. Reduced Cohen's F scores were consistently observed after ComBat harmonization. ComBat harmonization effectively harmonizes radiomic and deep features by removing the non-biological variations due to system manufacturers and/or field strengths in large multi-center clinical abdominal MRI datasets.

Vertebral bone quality score as a new tool for osteoporosis diagnosis in patients undergoing lumbosacral fusion surgery: a single center cohort study.

Osteoporosis, a common bone disorder, increases fracture and spinal surgery complications risk. This study evaluates the potential of the Magnetic Resonance Imaging (MRI)-based Vertebral Bone Quality (VBQ) score as an alternative for assessing bone density in lumbosacral fusion surgery patients. In a prospective cohort study from April 2021 to November 2022, 134 patients with lumbar degenerative diseases underwent lumbar Dual-Energy X-ray Absorptiometry (DXA) and lumbosacral non-contrast T1-weighted MRI. VBQ scores were calculated and analyzed using IBM SPSS Statistics and MedCalc software. Osteopenia/Osteoporosis patients exhibited significantly higher VBQ scores than normal bone mineral density patients (3.37 ± 0.51 vs. 2.99 ± 0.44, P<0.001). VBQ correlated significantly with lumbar DXA T scores (r value= -0.415, p<0.001). Receiver Operating Characteristic (ROC) analysis showed VBQ AUC values of 0.730 (CI 95% 0.647-0.803, P<0.001) and 0.839 (CI 95% 0.765-0.897, P<0.001) for Osteopenia/Osteoporosis and osteoporosis diagnosis, respectively. The study suggests MRI-derived VBQ scores may benefit pre-lumbosacral fusion surgery bone density assessment, potentially improving patient care and aiding osteoporosis detection in spinal surgery candidates.

The Utility of Magnetic Resonance Imaging-based Vertebral Bone Quality Scores as a Predictor of Cage Subsidence Following Transforaminal and Posterior Lumbar Interbody Fusion.

Retrospective study. The objectives were to determine whether vertebral bone quality (VBQ) scores are associated with interbody cage subsidence following transforaminal (TLIF) and posterior (PLIF) lumbar interbody fusions and whether there is a clinically sensitive threshold for subsidence. Interbody cage subsidence following lumbar fusion is a complication that can generate poor surgical outcomes. Prior research has correlated cage subsidence with bone mineral density. VBQ scores derived from magnetic resonance imaging (MRI) have been proposed as a tool for measuring bone mineral density, offering a potential new and convenient preoperative risk assessment tool for subsidence. The study involved patients undergoing single-level PLIF or TLIF between 2007 and 2022. Exclusions were for nondegenerative diagnoses, multilevel/revision surgeries, inadequate radiographs, missing immediate postoperative radiographs, and preoperative MRI studies older than 1 year. VBQ was calculated at L1-L4 from preoperative T1-weighted MRI images. Subsidence was assessed by changes in disc height (DH; >2mm difference) and segmental lordosis (SL; >5 degrees difference) between immediate weight-bearing postoperative and latest postoperative lateral radiographs. Statistical analysis included descriptive and inferential statistics. Subsidence was observed in 27% (SL parameter) and 47% (DH parameter) of 51 total patients. VBQ scores were significantly associated with cage subsidence based on both SL (odds ratio = 7.750, P = 0.012; correlation coefficient = 0.382, P = 0.006) and DH (odds ratio = 4.074, P = 0.026; correlation coefficient = 0.258, P = 0.057) in the combined TLIF/PLIF cohorts. In the cohort of 36 patients undergoing TLIF, a VBQ of 2.70 yielded 100.0% sensitivity and 46.2% specificity in detecting subsidence with SL measurement (area under the curve = 0.812, P < 0.001) and 86.7% sensitivity and 47.6% specificity with the DH measurement (area under the curve = 0.692, P = 0.033). We found that MRI-based VBQ scores are effective predictors of cage subsidence following TLIF surgery. A VBQ score of 2.70 demonstrated a reliable model and high sensitivity for doing so, identifying a potential clinical threshold for preoperative subsidence risk assessment. Level III.

Morphometry of medial temporal lobe subregions using high-resolution T2-weighted MRI in ADNI3: Why, how, and what's next?

This paper for the 20th anniversary of the Alzheimer's Disease Neuroimaging Initiative (ADNI) provides an overview of magnetic resonance imaging (MRI) of medial temporal lobe (MTL) subregions in ADNI using a dedicated high-resolution T2-weighted sequence. A review of the work that supported the inclusion of this imaging modality into ADNI Phase 3 is followed by a brief description of the ADNI MTL imaging and analysis protocols and a summary of studies that have used these data. This review is supplemented by a new study that uses novel surface-based tools to characterize MTL neurodegeneration across biomarker-defined AD stages. This analysis reveals a pattern of spreading cortical thinning associated with increasing levels of tau pathology in the presence of elevated amyloid beta, with apparent epicenters in the transentorhinal region and inferior hippocampal subfields. The paper concludes with an outlook for high-resolution imaging of the MTL in ADNI Phase 4. HIGHLIGHTS: As of Phase 3, the Alzheimer's Disease Neuroimaging Initiative (ADNI) magnetic resonance imaging (MRI) protocol includes a high-resolution T2-weighted MRI scan optimized for imaging hippocampal subfields and medial temporal lobe (MTL) subregions. These scans are processed by the ADNI core to obtain automatic segmentations of MTL subregions and to derive morphologic measurements. More detailed granular examination of MTL neurodegeneration in response to disease progression is achieved by applying surface-based modeling techniques. Surface-based analysis of gray matter loss in MTL subregions reveals increasing and spatially expanding patterns of neurodegeneration with advancing stages of Alzheimer's disease (AD), as defined based on amyloid and tau positron emission tomography biomarkers in accordance with recently proposed criteria. These patterns closely align with post mortem literature on spread of pathological tau in AD, supporting the role of tau pathology in the presence of elevated levels of amyloid beta as the driver of neurodegeneration.

Incorporating patient-specific information for the development of rectal tumor auto-segmentation models for online adaptive magnetic resonance Image-guided radiotherapy

Background and purposeIn online adaptive magnetic resonance image (MRI)-guided radiotherapy (MRIgRT), manual contouring of rectal tumors on daily images is labor-intensive and time-consuming. Automation of this task is complex due to substantial variation in tumor shape and location between patients. The aim of this work was to investigate different approaches of propagating patient-specific prior information to the online adaptive treatment fractions to improve deep-learning based auto-segmentation of rectal tumors. Materials and methods243 T2-weighted MRI scans of 49 rectal cancer patients treated on the 1.5T MR-Linear accelerator (MR-Linac) were utilized to train models to segment rectal tumors. As benchmark, an MRI_only auto-segmentation model was trained. Three approaches of including a patient-specific prior were studied: 1. include the segmentations of fraction 1 as extra input channel for the auto-segmentation of subsequent fractions, 2. fine-tuning of the MRI_only model to fraction 1 (PSF_1) and 3. fine-tuning of the MRI_only model on all earlier fractions (PSF_cumulative). Auto-segmentations were compared to the manual segmentation using geometric similarity metrics. Clinical impact was assessed by evaluating post-treatment target coverage. ResultsAll patient-specific methods outperformed the MRI_only segmentation approach. Median 95th percentile Hausdorff (95HD) were 22.0 (range: 6.1–76.6) mm for MRI_only segmentation, 9.9 (range: 2.5–38.2) mm for MRI+prior segmentation, 6.4 (range: 2.4–17.8) mm for PSF_1 and 4.8 (range: 1.7–26.9) mm for PSF_cumulative. PSF_cumulative was found to be superior to PSF_1 from fraction 4 onward (p = 0.014). ConclusionPatient-specific fine-tuning of automatically segmented rectal tumors, using images and segmentations from all previous fractions, yields superior quality compared to other auto-segmentation approaches.

Associations between neuromelanin depletion and cortical rhythmic activity in Parkinson's disease.

Parkinson's disease (PD) is marked by the death of neuromelanin-rich dopaminergic and noradrenergic cells in the substantia nigra (SN) and the locus coeruleus (LC), respectively, resulting in motor and cognitive impairments. While SN dopamine dysfunction has clear neurophysiological effects, the association of reduced LC norepinephrine signaling with brain activity in PD remains to be established. We used neuromelanin-sensitive T1-weighted MRI (NPD = 58; NHC = 27) and task-free magnetoencephalography (NPD = 58; NHC = 65) to identify neuropathophysiological factors related to the degeneration of the LC and SN in patients with PD. We found pathological increases in rhythmic alpha (8-12 Hz) activity in patients with decreased LC neuromelanin, with a stronger association in patients with worse attentional impairments. This negative alpha-LC neuromelanin relationship is strongest in fronto-motor cortices, where alpha activity is inversely related to attention scores. Using neurochemical colocalization analyses with normative atlases of neurotransmitter transporters, we also show that this effect is more pronounced in regions with high densities of norepinephrine transporters. These observations support a noradrenergic association between LC integrity and alpha band activity. Our data also show that rhythmic beta (15-29 Hz) activity in the left somato-motor cortex decreases with lower levels of SN neuromelanin; the same regions where beta activity reflects axial motor symptoms. Together, our findings clarify the association of well-documented alterations of rhythmic neurophysiology in PD with cortical and subcortical neurochemical systems. Specifically, attention-related alpha activity is related to dysfunction of the noradrenergic system, and beta activity with relevance to motor impairments reflects dopaminergic dysfunction.

Pre- and post-skeletal muscle biopsy quantitative magnetic resonance imaging reveals correlations with histopathological findings.

Quantitative muscle magnetic resonance imaging (MRI) is a promising non-invasive method in the diagnostic workup as well as follow-up of neuromuscular disorders. The aim of this study was to correlate quantitative MRI (qMRI) parameters to histopathological changes in skeletal muscle tissue and thus to verify the data from our pilot study. Twenty-six patients (eight females, 46.4 ± 15.1 years) were examined within 72 h before and within 24 h after a skeletal muscle biopsy using quantitative muscle MRI. Post-biopsy MRI was employed to pinpoint the exact localization of the biopsy. qMRI parameters including fat fraction, water T2 relaxation time and diffusion metrics including fractional anisotropy, mean diffusivity, axial diffusivity and radial diffusivity were extracted from the localization of the biopsy and correlated with histopathological findings. Additionally, three different segmentation masks were applied to the qMRI dataset, to evaluate whether the whole muscle represents the exact biopsy location. Fat fraction and water T2 relaxation time in qMRI correlated significantly with the fat fraction in the muscle biopsy and histopathological inflammatory markers. Fractional anisotropy correlated with the quantity of type 2 fibres, whilst mean diffusivity correlated with p62. No differences were found using different segmentation masks in qMRI. In this follow-up study, the results from our previous study were verified regarding the correlation of qMRI parameters with histopathological features in muscle biopsies, indicating that qMRI serves as a suitable non-invasive method in the follow-up of patients with neuromuscular disorders. If post-biopsy MRI is not available, whole muscle volume can be used for histopathological correlations.

Magnetic Resonance Imaging-Based Monitoring of the Accumulation of Polyethylene Terephthalate Nanoplastics.

Polyethylene terephthalate (PET) is one of the most produced plastic materials in the world. The emergence of microplastics and nanoplastics (MPs/NPs) as a significant environmental contaminant has become a matter of increasing concern. While the toxicological effects of PET NPs have been widely researched, there is a lack of methodologies for studying their accumulation. The present study introduces a novel method to monitor the distribution of PET NPs in germinating wheat (Triticum aestivum L.) seeds. This involves the functionalization of superparamagnetic iron oxide nanoparticles (SPIONs) with PET NPs (PET-fSPIONs) coupled with magnetic resonance microimaging (µMRI) to provide insight into their distribution within the seed. The present study has demonstrated that PET-fSPIONs accumulate in specific regions of germinating wheat seeds, including the shoot apical meristem, the radicle, the coleoptile, the plumule, and the scutellum. Furthermore, the accumulation of PET-fSPIONs has been shown to exert a discernible effect on spin-spin relaxation (T2), as observed via MRI and quantitative T2 relaxation time analysis. The accumulation of PET NPs in embryo regions was also confirmed by SEM. Diffusion-weighted magnetic resonance imaging (DW-MRI) and non-invasive chemical shift imaging analyses demonstrated that PET NPs resulted in restricted diffusion within the highlighted areas, as well as an impact on lipid content. Our study reveals that using µMRI with fSPIONs provides a non-invasive method to monitor the biodistribution of PET nanoparticles in wheat seeds. Additionally, it offers valuable insights into the microstructural interactions of PET.

Hydrogen bonding in 2,2,2-trifluoroethanol.

2,2,2-Trifluoroethanol (TFE) is known as a membrane mimetic solvent. The IR spectrum, 1H NMR spectrum, 13C NMR spin‒lattice relaxation times (T1), and nuclear Overhauser effect (NOE) data are consistent with extensive hydrogen bonding in TFE, but do not lead to structural features of the hydrogen bonding. Hence, DFT computations were carried out. The results predict the existence of a set of H-bonded dimers and trimers. The bond lengths and dihedral angles in these complexes are obtained, together with their dissociation energies. Computations were also performed for the geometry of the two conformers of the isolated monomer. The structure of one of the dimers consists of a 7-member cyclic fragment with a free CF3CH2 side chain. One set of the trimer structures involves the OH of a third monomer H-bonding to one of the F atoms in the CF3 group of the side chain of this dimer, thereby creating three trimer isomers. A fourth trimer cluster is formed from three monomers in which three OH∙∙∙O bonds create a cyclic fragment with three CF3CH2 side chains. The high dissociation energy (with respect to three monomers) indicates the high stability of the trimer complexes. The structural features of the trimer complexes resemble the structure of a conventional liquid crystal molecule and are postulated to resemble the latter in properties and function in solution, but at a much shorter timescale because of the noncovalent bonding. This hydrogen bonding phenomenon of TFE may be related to its function as a membrane memetic solvent. Initially, IR and NMR spectroscopic methods were used. Standard procedures were followed. For the computations, a hybrid DFT method with empirical dispersion, ωB97X-D, was used. The basis set, 6-311++G**, is of triple-ζ quality, in which polarization functions and diffuse functions were added for all atoms.

Focally Enlarged Perivascular Spaces in Pediatric and Adolescent Patients with Polymicrogyria-an MRI Study.

Polymicrogyria (PMG) is acortical malformation frequently associated with epilepsy. Our aim was to investigate the frequency and conspicuity of enlarged perivascular spaces (EPVS) underneath dysplastic cortex as apotentially underrecognized feature of PMG in pediatric and adolescent patients undergoing clinical magnetic resonance imaging (MRI). We analyzed data from 28pediatric and adolescent patients with PMG and amatched control group, ranging in age from 2days to 21years, who underwent MRI at 1.5T or 3T. T2-weighted MR images were examined for the presence of EPVS underneath the dysplastic cortex. The quantity of EPVS was graded from 0to 4(0: none, 1: < 10, 2: 11-20, 3: 21-40, 4: > 40 EPVS). We then compared the presence and quantity of EPVS to the matched controls in terms of total EPVS scores, and EPVS scores underneath the dysplastsic cortex depending on the age groups, the localization of PMG, and the MRI field strength. In 23/28 (82%) PMG patients, EPVS spatially related to the dysplastic cortex were identified. EPVS scores were significantly higher in PMG patients compared to controls, independent from age or PMG location. No significant differences were observed in EPVS scores in patients examined at 1.5T compared to those examined at 3T. EPVS underneath the dysplastic cortex were identified in 82% of patients. EPVS may serve as an important clue for PMG and amarker for cortical malformation.

Impact of congenital spinal stenosis on the outcome of three-level anterior cervical discectomy and fusion in patients with cervical spondylotic myelopathy: a retrospective study.

To investigate whether congenital cervical spinal stenosis (CCSS) affects the outcome of three-level anterior cervical discectomy and fusion (ACDF) in patients with cervical spondylotic myelopathy (CSM). One hundred seventeen patients with CSM who underwent three-level ACDF between January 2019 and January 2023 were retrospectively examined. Patients were grouped according to presence of CCSS, which was defined as Pavlov ratio ≤ 0.75. The CCSS and no CCSS groups comprised 68 (58.1%) and 49 (41.9%) patients, respectively. The Japanese Orthopaedic Association (JOA) score did not significantly differ between the two groups at any postoperative time point (p > 0.05). The JOA improvement rate was lower in the CCSS group 1 month after surgery (41.7% vs. 45.5%, p < 0.05), but showed no difference at any follow-up time point after one month. Multivariate logistic regression identified preoperative age (OR = 10.639), JOA score (OR = 0.370), increased signal intensity (ISI) in the spinal cord on T2-weighted MRI (T2-WI) (Grade 1: OR = 6.135; Grade 2: OR = 29.892), and degree of spinal cord compression (30-60%: OR = 17.919; ≥60%: OR = 46.624) as independent predictors of a poor oneyear outcome (JOA recovery rate < 50%). Although early JOA improvement is slower in the CCSS group, it does not affect the final neurological improvement at 1 year. Therefore, CCSS should not be considered a contraindication for three-level ACDF in patients with CSM. The main factors influencing oneyear outcome were preoperative age, JOA score, ISI grade, and degree of spinal cord compression.

Fatty infiltration of extraocular muscles on magnetic resonance imaging

ABSTRACT Purpose To investigate the prevalence of fatty infiltration in normal orbits using magnetic resonance imaging (MRI) and its impact on muscle diameters. Methods A retrospective analysis was conducted on normal orbits in patients who underwent coronal T1-weighted MRI. Fatty infiltration was defined by a hyperintense signal within the extraocular muscle. Fatty infiltration area was calculated by dividing the cross-sectional fat area by the sum of the muscle and fat area in the coronal plane. Muscle diameters were measured perpendicular to the muscle belly at their maximum and the mean diameters of the infiltrated muscles were compared with the non-infiltrated muscles. Results Seventy-six orbits from 76 participants with a mean age of 55.7 ± 18 years were included. Fatty infiltration in at least one muscle was seen in 57 (75%) of participants. When infiltration was present, inferior rectus was most commonly involved (98%). The area of fatty infiltration ranged from 6% to 42%, with 5 participants in the <10% group, 36 in the 10–20% group, 20 in the 20–30% group, 9 in the 30–40% group and 2 in the 40–50% group. Participants with fatty infiltration were significantly older (mean 61 ± 15 years vs 40 ± 16 years, p < .01) and had a higher proportion of males (56% vs 16%, p < .01). No significant difference in muscle diameters were found between infiltrated and healthy muscles. Conclusion Fatty infiltration of the extraocular muscles is a reasonably common finding in normal orbits, most commonly involves the inferior rectus muscle and is associated with increasing age.