Spin-lattice Relaxation Research Articles

Association between T2 relaxation time and biomechanical loading of the anterior cruciate ligament in healthy individuals

ABSTRACT Anterior cruciate ligament (ACL) injury is common in sports that include ‘change in direction’ tasks. The aim of the current study was to determine the association between T2 relaxation time (an indicator of ACL integrity) of the distal portion of the ACL sub-region, biomechanical loading factors of the ACL, sex, and sport status of the participants. Participants between 18 to 35 years performed unanticipated ‘change in direction’ trials at their maximal self-preferred speed. The maximal knee flexion angle and the valgus moment of the right knee during the weight acceptance phase were analysed. MRI data (T2 relaxation time) of the ACL was also collected. Among the independent variables involved in the linear regression model, the association of the valgus moment and sex were statistically significant (p = 0.01 and p = 0.001 respectively). In conclusion, the main finding of the study is that higher T2 was significantly associated with a higher valgus moment as acute response to the ‘change in direction’ tasks. New sentence: In conclusion, the main finding of the study is that higher T2 was significantly associated with a higher valgus moment during ‘change in direction’ tasks.

Concentric Ring Trajectory Sampling With k-Space Reordering Enables Assessment of Tissue-Specific T1 and T2 Relaxation for 2H-Labeled Substrates in the Human Brain at 7 T.

Deuterium metabolic imaging (DMI) is an emerging Magnetic Resonance technique providing valuable insight into the dynamics of cellular glucose (Glc) metabolism of the human brain invivo using deuterium-labeled (2H) glucose as non-invasive tracer. Reliable concentration estimation of 2H-Glc and downstream synthesized neurotransmitters glutamate + glutamine (Glx) requires accurate knowledge of relaxation times, but so far tissue-specific T1 and T2 relaxation times (e.g., in gray and white matter) have not been determined. Such measurements are time-consuming and particularly challenging in the presence of dynamically changing metabolite levels (e.g. 2H Glc and 2H Glx). This study aimed to assess T1 and T2 relaxation times of deuterated resonances, i.e., water, Glc and Glx in human gray and white matter using inversion recovery and Hahn spin-echo 2H MRSI (magnetic resonance spectroscopic imaging), respectively, with non-Cartesian concentric ring trajectory readout (CRT) including specific k-space reordering at 7 T. The sequence was validated using phantom measurements and all results were compared to unlocalized acquisitions. Thirteen healthy volunteers participated in the study, with 10 of them scanned ~90 min after oral administration of 0.8 g/kg [6,6'-2H]-glucose. Significantly different T1 and T2 relaxation was observed between GM and WM for 2H water (T1 GM/WM/unlocalized = 358 ± 21/328 ± 12/335 m ± 6 ms, p = 0.01) and 2H Glx (T2 GM/WM/unlocalized = 37 ± 2/35 ± 2/33 ± 3 ms, p = 0.02), respectively, consistent with unlocalized acquisitions. No significant regional differences were found for 2H water (T2 GM/WM/unlocalized = 36 ± 2/34 ± 2/31 ± 2 ms, p = 0.08), 2H Glc (T1 GM/WM/unlocalized = 70 ± 5/73 ± 4/80 ± 5 ms, p = 0.13; T2 GM/WM/unlocalized = 36 ± 1/34 ± 2/34 ± 2 ms, p = 0.24) and Glx (T1 GM/WM/unlocalized = 172 ± 15/172 ± 12/165 ± 11 ms, p = 1.00). Knowledge of tissue-specific relaxation times can enhance the accuracy of concentration estimation and metabolic flux rates in future studies, potentially improving our understanding of various brain diseases such as cancer, neurodegenerative diseases or diabetes, which are often linked to impaired glucose metabolism.

Impact of sleep disruptions on gray matter structural covariance networks across the Alzheimer's disease continuum.

This study explores the impact of sleep disturbances on gray matter structural covariance networks (SCNs) across the Alzheimer's disease (AD) continuum. Amyloid-negative participants served as controls, whereas amyloid positive (A+) individuals were categorized into six groups based on cognitive status and sleep quality. SCNsfor the default mode network (DMN), salience network (SN), and executive control network (ECN) were derived from T1-weighted magnetic resonance images. In the DMN, increased structural associations were observed in cognitive unimpaired (CU) A+ and mild cognitive impairment (MCI) groups regardless of sleep quality, whereas AD with poor sleep (PS) showed a decrease and AD with normal sleep (NS) an increase. For the ECN, AD-NS showed increased and AD-PS showed reduced associations. In the SN, reduced associations were observed in CU A+ NS and MCI-NS, whereas AD-NS displayed increased associations; only AD-PS had decreased associations. Distinct SCN damage patterns between normal and poor sleepers provide insights into sleep disturbances in AD. We delineated distinct patterns of structural covariance networks (SCN) impairment across the Alzheimer's disease (AD) continuum, uncovering significant disparities between individuals with normal sleep architecture and those afflicted by sleep disturbances.These observations underscore the pivotal importance of addressing sleep disruptions in AD therapeutics, providing a refined understanding of their detrimental impact on brain networks implicated in the disease.Our investigation epitomizes methodological precision by constructing an AD continuum using amyloid positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarkers to minimize diagnostic heterogeneity, further enhanced by a substantial cohort size that bolsters the robustness and generalizability of our findings.

Utilizing Quantitative Analysis of CSF Volume from Clinical T1-Weighted MRI to Predict Thrombectomy Outcomes.

Endovascular thrombectomy (EVT) is the standard for acute ischemic stroke from large vessel occlusion, but post-EVT functional independence varies. Brain atrophy, linked to higher cerebrospinal fluid volume (CSFV), may affect outcomes. Baseline CSFV could predict EVT benefit by assessing brain health. We aimed to quantify total CSFV from clinical T1-weighted (w) magnetic resonance imaging (MRI) to assess global brain atrophy and its association with functional outcomes following successful EVT. We performed a retrospective analysis of patients achieving thrombolysis-in-cerebral-infarction ≥2b revascularization via prospectively maintained single-institution stroke thrombectomy registry (n = 432) between 2015 and 2021. We included 214 patients (mean age 67.5±14.6, 49% female) with acceptable quality MRI within 14days of EVT and available modified Rankin-scale (mRS) at 90days post EVT. Clinical T1w images were transformed into high-resolution images using the convolutional neural-network SynthSR. FreeSurfer software was then used to estimate total cranial CSFV. To correct for head size, percentage of CSFV to intracranial volume was used. Baseline CSFV% significantly predicted 90-day mRS in an ordinal regression model adjusted for baseline mRS (p<0.001). Further modeling was performed to account for age, sex, 24-h National-Institutes-Health-Stroke-Scale (NIHSS), smoking history, prior stroke, hypertension, congestive heart failure, hemoglobin-A1c, atrial fibrillation, and Alberta-Stroke-Program-Early-CT-Score (ASPECTS). Total CSFV% remained an independent predictor of 90-day mRS (p = 0.012). CSFV% did not significantly predict the occurrence of any type of hemorrhagic transformation in a logistic regression model. Increased CSFV% correlates with poorer functional outcomes post EVT. Total CSFV% may serve as a useful imaging biomarker for clinicians determining patient prognostication prior to EVT.

A novel MSN-II feature extracted from T1-weighted MRI for discriminating between BD patients and MDD patients.

Differentiating between patients with bipolar disorder (BD) and major depressive disorder (MDD) is clinically challenging. This study aimed to explore the potential of radiomic textural features for discriminating BD and MDD. A total 253 subjects (114 patients with BD, 139 patients with MDD) with T1-weighted MRI data were recruited. Radiomics features and gray matter volume (GMV) features were extracted from each brain region. A novel high-level MSN_II feature method based on radiomic features was proposed. And a total of 21 MSN features (5 MSN_I and 16 MSN_II) based on different combinations of the 5 types of radiomic textural feature were calculated. Classification models were constructed using various combinations of MSNs or GMV, and their performance and stability was evaluated through 2000 repeated experiments. The model built with combined features (GMV and GMV+MSN_II_GLCM_GLSZM_NGTDM) showed the best classification performance (AUC=0.896±0.058, ACC=0.831±0.064) in the validation cohort. After MANOVA analysis and FDR correlation, the MSN_II_GLCM_GLSZM_NGTDM values in 4 regions (right rectus gyrus, right temporal pole: middle temporal gyrus, Vermis3 and Vermis10) showed significant difference between BD and MDD. The main limitation of this study is that the data is derived from a single center without an external independent test set. Incorporating the high-level MSN_II based on radiomics features can improve the classification performance compared to models solely relying on GMV features alone. This result implied the potential application of the proposed high level MSN method and radiomics textural features on the MDD and BD clinical studies.

Evaluation of Glutathione T2 in the Human Brain Using J-Difference MRS at 3 T: Multicenter Multivendor Study.

The need to quantify brain glutathione (GSH) accurately by J-difference spectroscopy has stimulated assessment of the TE effects on GSH edited signals at the popular field strength 3 T. We performed multiple-TE J-difference MRS at two sites to evaluate the GSH T2 relaxation and TE dependence of the GSH signal resolution. Two 10-ms spectrally selective Gaussian editing RF pulses were implemented in 3 T MEGA-PRESS sequences at two sites having different vendors. The sequences were optimized, with numerical and phantom analyses, for editing of the GSH 2.95 ppm resonance. The timings of the editing pulses within the sequences were tailored for high-amplitude GSH signal production for a TE range of 58-160 ms. Invivo human brain data were collected at five TEs (58, 70, 88, 116, and 150 ms) from five subjects at each site. Following LCModel analysis of difference and edit-off spectra independently between the sites, metabolite T2 values were estimated with mono-exponential regression of the signal estimates. Simulations and phantom data indicated that the MEGA-edited GSH peak amplitude was progressively larger with increasing TE up to 125-140 ms and the maximum amplitude was 2- to 2.5-fold greater than the amplitude at TE of 58 ms. For invivo data, the edited GSH peak was the largest at TE of 88 ms among the five TEs. Brain GSH T2 was measured as 88 ± 11 ms from 10 subjects, with no significant difference between the sites. The LCModel-returned correlation coefficient between GSH and co-edited N-acetylaspartate (NAA) multiplet was significantly smaller at short TEs than at long TEs. Our data suggest that MEGA-edited GSH signal undergoes extensive attenuation with increasing TE due to the fast T2 relaxation, and the edited GSH signal can be well resolved at short TEs with small interferences from adjacent co-edited NAA multiplet.

A foundation model with weak experiential guidance in detecting muscle invasive bladder cancer on MRI.

Preoperative detection of muscle-invasive bladder cancer (MIBC) remains a great challenge in practice. We aimed to develop and validate a deep Vesical Imaging Network (ViNet) model for the detection of MIBC using high-resolution T2-weighted MR imaging (hrT2WI) in a multicenter cohort. ViNet was designed using a modified 3D ResNet, in which, the encoder layers were pretrained using a self-supervised foundation model on over 40,000 cross-modal imaging datasets for transfer learning, and the classification modules were weakly supervised by an experiential knowledge-domain mask indicated by a nnUNet segmentation model. Optimal ViNet model was trained in derivation data (cohort 1, n=312) and validated in multicenter data (cohort 2, n=79; cohort 3, n=44; cohort 4, n=56) across a multi-ablation-test for model selection. In internal validation, ViNet using hrT2WI outperformed all ablation-test models (odds ratio [OR], 7.41 versus 1.85-2.70; all P<0.05). In external validation, the performance of ViNet using hrT2WI versus ablation-test models was heterogeneous (OR, 1.31-3.89 versus 0.89-9.75; P=0.03-0.15). In addition, clinical benefit of ViNet was evaluated between six readers using the Vesical Imaging-Reporting and Data System (VI-RADS) versus ViNet-adjusted VI-RADS. As a result, ViNet-adjusted VI-RADS upgraded 62.9% (17/27) of MIBC missed in VI-RADS score 2, while downgraded 84.1% (69/84), 62.5% (35/56) and 67.9% (19/28) of non-muscle-invasive bladder cancer (NMIBC) overestimated in VI-RADS score 3-5. We concluded that ViNet presents a promising alternative for diagnosing MIBC using hrT2WI instead of conventional multiparametric MRI.

In vivo imaging markers of glymphatic dysfunction in amyotrophic lateral sclerosis: Analysis of ALPS index and choroid plexus volume.

The glymphatic system, essential for brain waste clearance, has been implicated in neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS). Emerging imaging markers, such as the analysis along the perivascular space (ALPS) index and choroid plexus volume (CPV), may provide insights into glymphatic function, but their relevance to ALS remains unclear. To assess glymphatic dysfunction in ALS patients using the ALPS index and CPV. In this prospective single-center study, we analyzed 51 ALS patients and 51 age- and sex-matched healthy controls (HC). The ALPS index was calculated using diffusion tensor imaging, and 3D T1-weighted MRI was used for automated estimation of CPV and its fraction (CPV/total intracranial volume). Diagnostic performance was assessed using area under the receiver operating curve (AUC). Correlations between imaging markers and clinical parameters were also examined. ALS patients had a significantly lower ALPS index (ALS: 1.45±0.15; HC: 1.55±0.16; p=0.002) and higher CPV fraction (ALS: 0.12±0.04%; HC: 0.10±0.02%; p<0.001). The ALPS index and CPV fraction had AUCs of 0.70 and 0.72, respectively. A significant inverse correlation was observed between the ALPS index and CPV fraction (r=-0.31, p=0.002). Both markers correlated with aging but not with clinical disability or progression rate. This study identifies glymphatic dysfunction in ALS, as evidenced by changes in the ALPS index and CPV. Larger studies are warranted to validate these findings and assess their potential as biomarkers for ALS.

The value of hippocampal sub-region imaging features for the diagnosis and severity grading of ASD in children

BackgroundHippocampal structural changes in Autism Spectrum Disorder (ASD) are inconsistent. This study investigates hippocampal subregion changes in ASD patients to reveal intrinsic hippocampal anomalies. MethodsA retrospective study from Hainan Children’s Hospital database (2020–2023) included ASD patients and matched controls. We classified ASD participants based on severity, dividing all subjects into four groups: normal, mild, moderate, and severe. High-resolution T1-weighted MRI images were analyzed for hippocampal subregion segmentation and volume calculations using Freesurfer. Texture features were extracted via the Gray-Level Co-occurrence Matrix. The Receiver Operating Characteristic curve was used to evaluate seven random forest predictive models constructed from volume, subregion, and texture features, as well as their combinations following feature selection. ResultsThe study included 114 ASD patients (98 boys, 2–8 years; 16 girls, 2–6 years; 17 mild, 57 moderate, 40 severe) and 111 healthy controls (HCs). No significant differences in volumes were found between ASD patients and HCs (adjusted P-value >0.05). The seven random forest models showed that single volume and texture features performed poorly for ASD classification; however, integrating various feature types improved AUC values. Further selection of texture, subregion, and volume features enhanced AUC performance across normal and varying severity categories, demonstrating the potential value of specific subregions and integrated features in ASD diagnosis. ConclusionRandom forest models revealed that hippocampal volume, texture features, and subregion characteristics are crucial for diagnosing and assessing the severity of ASD. Integrating selected texture and subregion features optimized diagnostic efficacy, while combining texture, subregion, and volume features further improved severity grading effectiveness.

Quantitative assessment of thalamic damage and serum neurofilament light chain in relapsing-remitting multiple sclerosis

BackgroundThe study assessed group differences in the thalamus microstructural parameters among healthy individuals and relapsing-remitting multiple sclerosis (RRMS) patients and examined the relationship between quantitative MRI (qMRI) parameters and neurological scores, T2 lesion load, and serum neurofilament light chain (sNfL) levels. MethodsA total of 30 patients with RRMS and 26 age- and sex-matched healthy controls were recruited in this study. The qMRI images were obtained from these individuals. T2 lesion load, thalamic volume, and parameters of thalamic subnuclei were estimated. The neurological functions of participants were assessed using a battery of tests. sNfL concentrations were measured using the single molecule array (SIMOA) technique. ResultsT2 relaxometry in the whole thalamus and its subnuclei were increased, and showed an apparent correlation with T2 lesion load and the severity of MS (EDSS, MSSS, 9HPT, T25FW, SDMT). T1 variability was prolonged in most thalamic subnuclei, and it was correlated with the severity of MS (EDSS, 9HPT, SDMT). Thalamic volumetric parameters of MS patients were smaller than those of healthy controls (p < 0.001) and showed an apparent correlation with MS severity. Surprisingly, sNfL levels showed no correlation with T2 relaxometry, T1 variability, or thalamic volumetric parameters. ConclusionQuantitative synthetic MRI, especially, the metric T2 relaxation times provides a surrogate parameter for assessing underlying thalamic and subnuclei damage in the RRMS group. Integrating structural and quantitative MRI allows a better assessment of the neurodegeneration in the normal-appearing thalamus of RRMS.

Simultaneous Concentration and T2 Mapping of Brain Metabolites by Fast Multi-Echo Spectroscopic Imaging.

The purpose of this study was to produce metabolite-specific T2 and concentration maps in a clinically compatible time frame. A multi-TE 2D MR spectroscopic imaging (MRSI) experiment (multi-echo single-shot MRSI [MESS-MRSI]) deployed truncated and partially sampled multi-echo trains from single scans and was combined with simultaneous multiparametric model fitting. It was tested invivo for the brain in five healthy subjects. Cramér-Rao lower bounds (CRLB) were used as the measure of performance. The novel method was compared with (1) traditional multi-echo multi-shot (MEMS) MRSI and, as proof of concept, with (2) a truncated version of MEMS, which mimics the MESS acquisition (MESS-mocked) on the original fully sampled MEMS dataset. MESS-MRSI simultaneously yields concentration and T2 maps with a nominal voxel size of ~2 cm3 with a 16 × 16 FOV matrix in 7 min scan time. The estimated values not only align well with the equivalent mocked experiment but are also in good agreement with the traditional threefold longer MEMS acquisition. The MESS-MRSI scheme extends former findings for single-voxel MESS, with improvements in CRLB ranging from 17% to 45% for concentrations and 10% to 23% for T2s when compared to traditional MEMS. This finding suggests that concentrations and T2 times can be reliably estimated in a multi-echo spectroscopic imaging exam by trading off spectral resolution (for some of the acquired TEs) with a significant reduction in scan time, as long as (1) an appropriate bidimensional frequency-TE model is deployed and (2) one TE is sampled in full. Thus, high spectral resolution information can be injected to the partially sampled TEs during fitting by prior knowledge from the one fully sampled TE. Tissue-type and regional distributions of 16 metabolite concentrations align well with the literature, and T2 distributions for five major metabolites are described by region and tissue. The novel MRSI acquisition strategy, based on partially sampled single-shot multi-echo trains twinned to multiparametric fitting, is optimally suited to provide simultaneous 2D concentration and T2 maps in clinic-compatible scan times. MESS principles allow embedding advanced MRSI techniques to further improve speed, coverage, or resolution. Preliminary findings from a cohort of five subjects reveal correlations between T2 relaxation times and the relative fraction of gray/white matter, suggesting tissue-type-dependent microstructural changes.

3D-printed radiopaque episcleral plaques with radioactive collimating cavities for enhanced dose delivery in brachytherapy.

Episcleral plaque brachytherapy (EPBT) is a well-established treatment. However, the lateral dose to healthy tissues, such as the sclera, retina, and optic nerve is often problematic and results in side effects. This study proposes an innovative approach based on the 3D-printing of radiopaque polymer plaques featuring cylindrical radioactive cavities (CRC) with a potential collimating effect on radiation delivery to tumors. A CAD model based on the COMS protocol was created and 3D-printed using radiopaque PEEK polymer. Cylindrical cavities (1 mm depth/diameter) were evenly spaced on the plaque's inner surface. Two radioactive layouts (RL1: uniform loading; RL2: radial gradient loading) were designed. µCT imaging was used to assess the geometric accuracy of the 3D-printed CRC EPs, and dose distribution was evaluated for the two (2) radioactive layouts using MAGIC-pf gel dosimetry and T2-weighted MRI. The resulting dose profiles were compared with those generated by both COMS and SEP plaques. Radiopaque CRC EPs showed higher central axis dose deposition while minimizing lateral overexposure compared to COMS and SEP plaques, while also providing robust back-shielding. Dose profiles from RL1 CRC EPs (uniform layout) extended deeper into the eye, whereas RL2 CRC EPs (with gradient) exhibited a more rapid dose fall-off, producing a concentrated, spherical dose distribution. 3D-printed radiopaque EPs with radioactivity encapsulated in cylindrical cavities demonstrated the ability to achieve more forward-projected dose profiles in EPBT. This fabrication design and a modulated radioactivity distribution across the EP surface would enable more precise and deeper dose delivery while reducing radiation exposure to lateral healthy tissues.

Peripheral Neuropathy in Systemic Sclerosis with Proximal Nerve Involvement: Diagnostic Challenges and Response to Corticosteroid Therapy.

Peripheral neuropathy is a complication in systemic sclerosis that is occasionally encountered in clinical settings. The mechanisms underlying this condition remain unclear and treatment strategies have not yet been established, making management challenging. Here, we report a case of peripheral neuropathy associated with systemic sclerosis that was successfully treated with corticosteroid therapy despite the absence of conventional inflammatory findings on histopathology or blood tests. A 44-year-old Japanese man diagnosed with systemic sclerosis presented with gradually worsening paresthesia and gait disorder. A nerve conduction study and histological examination of a biopsy sample from the left sural nerve, where the nerve conduction study indicated abnormalities, revealed findings consistent with peripheral neuropathy associated with systemic sclerosis. The results of blood tests or cerebrospinal fluid analysis did not indicate significant inflammatory findings, aside from a slight elevation in protein levels in the cerebrospinal fluid. Similarly, the histological analysis of the nerve biopsy showed no signs of inflammation. T2-weighted magnetic resonance imaging of the lumbar region revealed hyperintensity at the nerve roots, suggesting inflammation at the nerve roots. Based on these findings, we initiated corticosteroid therapy, which led to an improvement in both the patient's symptoms and results in the nerve conduction study. This case provides new insights into the pathogenesis of peripheral neuropathy associated with systemic sclerosis and highlights that the potential benefits of immunosuppressive therapy should not be overlooked, even in the absence of conventional inflammatory signs.

UK Biobank MRI Data Can Power the Development of Generalizable Brain Clocks: A Study of Standard ML/DL Methodologies and Performance Analysis on External Databases.

In this study, we present a comprehensive pipeline to train and compare a broad spectrum of machine learning and deep learning brain clocks, integrating diverse preprocessing strategies and correction terms. Our analysis also includes established methodologies which have shown success in prior UK Biobank-related studies. For our analysis we used T1-weighted MRI scans and processed de novo all images via FastSurfer, transforming them into a conformed space for deep learning and extracting image-derived phenotypes for our machine learning approaches. We rigorously evaluated these approaches both as robust age predictors for healthy individuals and as potential biomarkers for various neurodegenerative conditions, leveraging data from the UK Biobank, ADNI, and NACC datasets. To this end we designed a statistical framework to assess age prediction performance, the robustness of the prediction across cohort variability (database, machine type and ethnicity) and its potential as a biomarker for neurodegenerative conditions. Results demonstrate that highly accurate brain age models, typically utilising penalised linear machine learning models adjusted with Zhang's methodology, with mean absolute errors under 1 year in external validation, can be achieved while maintaining consistent prediction performance across different age brackets and subgroups (e.g., ethnicity and MRI machine/manufacturer). Additionally, these models show strong potential as biomarkers for neurodegenerative conditions, such as dementia, where brain age prediction achieved an AUROC of up to 0.90 in distinguishing healthy individuals from those with dementia.

Normative measurements of the frontal nerve by magnetic resonance imaging in an Australia cohort

PurposeTo report the normative dimensions of the frontal nerve (FN) on fat-suppressed suppressed gadolinium (fs-gad) enhanced magnetic resonance imaging (MRI).MethodA retrospective cohort study of patients who underwent coronal fs-gad T1-weighted MRI. Orbits were excluded if there was unilateral or bilateral pathology of the FN or optic nerve sheath (ONS), incomplete MRI sequences, poor image quality or indiscernible FN on radiological assessment. The maximum diameter of the FN and ONS was measured.ResultsThe mean age of participants was 58 ± 16 years and 50% were females (n = 42). The mean normative measurements (mean ± standard deviation) on coronal T1-weighted imaging: optic nerve sheath, 5.08 ± 0.67mm. On coronal fs-gad T1-weighted imaging: frontal nerve, 0.74 ± 0.18mm. No significant differences were found between male or female participants in both the frontal nerve (p = 0.913) or optic nerve sheath (p = 0.646). There was no significant correlation between age and mean diameter of the frontal nerve (r = 0.14, p = 0.067) or optic nerve sheath (r = 0.075, p = 0.336). Additionally, no significant difference was identified between the mean diameter of the frontal nerve (p = 0.075) and optic nerve sheath (p = 0.120) across age groups. The mean frontal nerve to optic nerve sheath ratio was 0.15 ± 0.04.ConclusionNormative dimensions of the FN may provide quantitative cut-offs that can aid the diagnosis of FN enlargement seen in instances such as IgG4-related ophthalmic disease (IgG4-ROD) and neoplastic perineural spread.

Deep Learning-Based Precontrast CT Parcellation for MRI-Free Brain Amyloid PET Quantification.

This study aimed to develop a deep learning (DL) model for brain region parcellation using CT data from PET/CT scans to enable accurate amyloid quantification in 18F-FBB PET/CT without relying on high-resolution MRI. A retrospective dataset of PET/CT and T1-weighted MRI pairs from 226 individuals (157 with mild cognitive impairment or dementia and 69 healthy controls) was used. The dataset was split into training/validation (60%) and test (40%) sets. Utilizing auto-generated segmentation labels, 3 UNets were independently trained for multiplanar brain parcellation on CT and subsequently ensembled. Amyloid load was measured across 46 volumes of interest (VOIs), derived from the Desikan-Killiany-Tourville atlas. Dice similarity coefficient between the proposed CT-based DL model and MRI-based (FreeSurfer) method was calculated, with SUVR comparison using linear regression analysis and intraclass correlation coefficient. Global SUVRs were also compared within groups with clinical dementia ratings (CDRs) of 0, 0.5, and 1. The DL-based CT parcellation achieved mean Dice similarity coefficients of 0.80 for all 46 VOIs, 0.72 for 16 cortical and limbic VOIs, and 0.83 for 30 subcortical VOIs. For regional and global SUVR comparisons, the linear regression yielded a slope, y-intercept, and R2 of 1 ± 0.027, 0 ± 0.040, and ≧0.976, respectively (P < 0.001), and the intraclass correlation coefficient was ≧0.988 (P < 0.001). For global SUVRs in each CDR group, these values were 1 ± 0.020, 0 ± 0.026, ≧0.993, and ≧0.996, respectively (P < 0.001). Both MRI-based and CT-based global SUVR showed a consistent increase as the CDR score increased. The DL-based CT parcellation agrees strongly with MRI-based methods for amyloid PET quantification.

Impact of Five Soy Proteins on Lean Chicken Breast Systems with Varying Moisture Contents: Cooking Loss, Texture, Microstructure, and T2 NMR

With increasing global meat consumption, meat–plant hybrid products have gained interest as a sustainable alternative. Soy proteins have been used in small quantities (2–3%) as meat extenders, yet limited data exist on their use at higher levels. Here, five commercial soy proteins (four isolates: SPI-A to -D; one concentrate: SPC) were used for meat replacement in lean meat batters with 0/40/80% added water. Cooking loss, texture, light micrographs, and T2 relaxation were analyzed. At 33% and 66% meat replacement, soy protein treatments maintained comparable or reduced cooking loss; SPI-D and SPC were the least and most effective, respectively. Complete replacement eliminated cooking loss in 0% and 40% water systems but failed to form self-supporting gels in the 80% system. At 33% replacement, SPI-A to -C generally increased hardness, whereas increasing the replacement level further to 66% decreased it. In the 0% and 80% systems, SPI-A treatments exhibited hardness comparable to controls, SPI-D treatments drastically reduced hardness, and SPC treatments maintained greater hardness than the controls even at 66% replacement. Micrographs offered potential explanations for these macroscopic measurements. NMR T2 data indicated that soy proteins restricted water mobility both pre- and post-cooking. Specifically, in the 40% and 80% systems, the T22 peaks (expelled liquid) of the hybrid samples containing 33% SPI-A were ~350 ms and 760 ms, compared to ~570 ms and 1170 ms for the meat controls, respectively. In conclusion, most soy proteins (except SPI-D) enhanced water binding, with SPI-A showing optimal texture and SPC showing promise as a more economical alternative.

Highly specific amyloid and tau PET ligands for ATN classification in suspected Alzheimer's disease patients.

This study aims to accurately classify ATN profiles using highly specific amyloid and tau PET ligands and MRI in patients with cognitive impairment and suspected Alzheimer's disease (AD). It also aims to explore the relationship between quantified amyloid and tau deposition and cognitive function. Twenty-seven patients (15 women and 12 men; age range: 64-81years) were included in this study. Amyloid and tau PET scans were performed using 18F-NAV4694 and 18F-MK6240, respectively. For each patient, amyloid and tau PET images were visually assessed and classified as either amyloid-positive or amyloid-negative, and as 18F-MK6240 Braak stage 0 (tau-negative) or Braak stages I-VI (tau-positive). Voxel-based morphometry of three-dimensional T1-weighted MRI was used to evaluate neurodegeneration. Amyloid and tau depositions were quantified using the Centiloid scale and standardized uptake value ratio (SUVR), respectively. Global cognitive function was assessed with the Mini-Mental State Examination (MMSE). Patients were categorized into seven ATN profiles. Six patients (22%) exhibited a normal AD biomarker profile, 15 patients (56%) fell within the Alzheimer's continuum, and 14 patients (52%) were diagnosed with AD. Additionally, six patients (22%) displayed non-AD pathological changes. Positive and negative findings of amyloid and tau PET were concordant in 24 patients (89%). Among the 14 patients diagnosed with AD, the Centiloid scale for amyloid deposition did not show a significant negative correlation with MMSE scores (r = 0.269, p = 0.451). In contrast, the SUVR for tau deposition in the neocortex exhibited a significant negative correlation (r = -0.689, p = 0.014), while tau deposition in the mesial temporal region did not show a significant correlation (r = 0.158, p = 0.763). Highly specific amyloid and tau PET scans, along with MRI, can be utilized to accurately classify ATN profiles in patients with cognitive impairment and suspected AD. The discordance in amyloid and tau PET findings in three patients allowed for a more precise AD diagnosis. Furthermore, tau PET imaging provided insight into the propagation of tau deposition in the neocortex beyond the mesial temporal region, which is associated with cognitive decline.

Ide Copy Number Variant Does Not Influence Stroke Severity in 2 C57BL/6J Mouse Models nor in Humans: An Exploratory Study.

Contrary to the common belief, the most commonly used laboratory C57BL/6J mouse inbred strain presents a distinctive genetic and phenotypic variability, and for several traits, the genotype-phenotype link remains still unknown. Recently, we characterized the most important stroke survival factor such as brain collateral plasticity in 2 brain ischemia C57BL/6J mouse models (bilateral common carotid artery stenosis and middle cerebral artery occlusion) and observed a Mendelian-like fashion of inheritance of the posterior communicating artery (PcomA) patency. Interestingly, a copy number variant (CNV) spanning Ide locus was reported to segregate in an analogous Mendelian-like pattern in the C57BL/6J colonies of the Jackson Laboratory. Given IDE critical role in vascular plasticity, we hypothesized Ide CNV may have explained PcomA variability in C57BL/6J inbred mice. We applied a combination of techniques (T2-weighted magnetic resonance imaging, time-of-flight angiography, cerebral blood flow imaging, and histology) to characterize the collaterome in 77 C57BL/6J bilateral common carotid artery stenosis, middle cerebral artery occlusion, naive, and sham mice and performed on these Taqman genotyping, exome sequencing, and RNA sequencing. We then investigated the hypothesis that IDE structural variants (CNVs, gain/loss of function mutations) may have influenced the cerebrovascular phenotype in a large cohort of 454 040 cases and controls (UK Biobank, Genomics England). We detected an Ide CNV in a bilateral common carotid artery stenosis mouse with 2 patent PcomAs (minor allele frequency, 1.3%), not segregating with the PcomA patency phenotype. In addition, 2 heterozygous IDE CNVs, resulting in loss of function were found in 1 patient with hereditary ataxia, a patient with hereditary congenital heart disease, and 2 healthy individuals (minor allele frequency 9×10-6). Moreover, we report 4 IDE loss of function point mutations (p.Leu5X, p.Met394ValfsX29, p.Pro14SerfsX26, p.Leu889X, minor allele frequency 0.02%) present also in controls or inherited from healthy parents. Ide CNV and loss of function variants are rare, do not crucially influence PcomA variability in C57BL/6J inbred mice, and do not cause a vascular phenotype in humans.

A multi-cohort study of longitudinal and cross-sectional Alzheimer's disease biomarkers in cognitively unimpaired older adults.

The generalizability of neuroimaging and cognitive biomarkers in their sensitivity to detect preclinical Alzheimer's disease (AD) and power to predict progression in large, multisite cohorts remains unclear. Longitudinal demographics, T1-weighted magnetic resonance imaging (MRI), and cognitive scores of 3036 cognitively unimpaired (CU) older adults (amyloid beta [Aβ]-negative/positive [A-/A+]: 1270/1558) were included. Cross-sectional and longitudinal cognition and medial temporal lobe (MTL) structural measures were extracted. Cross-sectional MTL tau burden (T) was computed from tau positron emission tomography (N=1095). We found cross-sectional tau and longitudinal structural biomarkers best separated A+ CU from A- CU. A-T+ CU had significantly faster neurodegeneration rate compared to A-T- CU. MTL tau was significantly correlated with MRI and cognitive biomarkers regardless of Aβ status. MTL tau, MRI, and cognition provided complementary information about disease progression. This large multisite study replicates prior findings in CU older adults, supporting the utility of neuroimaging and cognitive biomarkers in preclinical AD clinical trials and normal aging studies. We investigated neuroimaging and cognitive biomarkers in 3036 cognitively unimpaired (CU) participants. Medial temporal lobe (MTL) tau and longitudinal MTL atrophy best separate amyloid beta positive (A+) CU from amyloid beta negative (A-) CU. A- tau positive (T+) CU had a significantly faster neurodegeneration rate compared to A-T- CU. MTL tau correlated with structural magnetic resonance imaging (MRI) and cognition regardless of amyloid beta status. Combined baseline MTL tau, MRI, and cognition best predict Alzheimer's disease progression.