Deep learning-based quantification of brain atrophy using 2D T1-weighted MRI for Alzheimer's disease classification.

Background: Determining brain atrophy is crucial for the diagnosis of neurodegenerative diseases. Despite detailed brain atrophy assessments using three-dimensional (3D) T1-weighted magnetic resonance imaging, their practical utility is limited by cost and time. This study introduces deep learning algorithms for quantifying brain atrophy using a more accessible two-dimensional (2D) T1, aiming to achieve cost-effective differentiation of dementia of the Alzheimer's type (DAT) from cognitively unimpaired (CU), while maintaining or exceeding the performance obtained with T1-3D individuals and to accurately predict AD-specific atrophy similarity and atrophic changes [W-scores and Brain Age Index (BAI)]. Methods: Involving 924 participants (478 CU and 446 DAT), our deep learning models were trained on cerebrospinal fluid (CSF) volumes from 2D T1 images and compared with 3D T1 images. The performance of the models in differentiating DAT from CU was assessed using receiver operating characteristic analysis. Pearson's correlation analyses were used to evaluate the relations between 3D T1 and 2D T1 measurements of cortical thickness and CSF volumes, AD-specific atrophy similarity, W-scores, and BAIs. Results: Our deep learning models demonstrated strong correlations between 2D and 3D T1-derived CSF volumes, with correlation coefficients r ranging from 0.805 to 0.971. The algorithms based on 2D T1 accurately distinguished DAT from CU with high accuracy (area under the curve values of 0.873), which were comparable to those of algorithms based on 3D T1. Algorithms based on 2D T1 image-derived CSF volumes showed high correlations in AD-specific atrophy similarity (r = 0.915), W-scores for brain atrophy (0.732 ≤ r ≤ 0.976), and BAIs (r = 0.821) compared with those based on 3D T1 images. Conclusion: Deep learning-based analysis of 2D T1 images is a feasible and accurate alternative for assessing brain atrophy, offering diagnostic precision comparable to that of 3D T1 imaging. This approach offers the advantage of the availability of T1-2D imaging, as well as reduced time and cost, while maintaining diagnostic precision comparable to T1-3D.

A Characteristic Magnetic Resonance Imaging Finding to Identify Morton Neuroma: The Slug Sign.

Background: Morton neuroma is a common cause of forefoot pain and sensory disturbances, but it is difficult to identify on magnetic resonance imaging (MRI). The aim of this study was to verify the usefulness of a characteristic MRI finding (slug sign) for identifying Morton neuroma and to clarify the relationship between excised neuroma characteristics and preoperative MRI findings. Methods: Twenty-two web spaces were retrospectively assessed from the second and third intermetatarsal spaces of 11 feet of 10 patients (7 women and 3 men, aged average 59.5 years) who underwent surgical excision of Morton neuroma between 2017 and 2022. Asymptomatic web spaces were used as control. Neuromas with 2 branches of the plantar digital nerves on axial T1-weighted MRI (MRI-T1WI) were considered the slug sign. We investigated the preoperative presence of the slug sign in Morton neuroma and asymptomatic control web spaces. We also investigated the relationship between the maximum transverse diameter of the excised specimen and that estimated on coronal MRI-T1WI. Results: A total of 15 Morton neuromas were excised and assessed. The slug signs were present in 10 intermetatarsal spaces in 15 web spaces with Morton neuroma whereas the sign was found in 1 intermetatarsal space in 7 asymptomatic web spaces. The sensitivity and specificity for the slug sign to diagnose Morton neuroma was 66.7% and 85.7%, respectively. The positive and negative predictive values were 90.9% and 54.5%, respectively. The mean maximum transverse diameter of excised neuromas was 4.7 mm. The mean maximum transverse diameter of neuromas on coronal MRI-T1WI was 3.4 mm. A significant positive correlation was found between the maximum transverse diameters of excised specimens and diameters estimated on coronal MRI-T1WI (r = 0.799, P < .001). Conclusion: The slug sign may be a useful indicator of Morton neuroma on MRI to confirm nerve involvement after bifurcation. Level of Evidence: Level IV, retrospective series.

Diagnosis for autism spectrum disorder children using T1-based gray matter and arterial spin labeling-based cerebral blood flow network metrics.

Introduction: Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by impairments in motor skills, communication, emotional expression, and social interaction. Accurate diagnosis of ASD remains challenging due to the reliance on subjective behavioral observations and assessment scales, lacking objective diagnostic indicators. Methods: In this study, we introduced a novel approach for diagnosing ASD, leveraging T1-based gray matter and ASL-based cerebral blood flow network metrics. Thirty preschool-aged patients with ASD and twenty-two typically developing (TD) individuals were enrolled. Brain network features, including gray matter and cerebral blood flow metrics, were extracted from both T1-weighted magnetic resonance imaging (MRI) and ASL images. Feature selection was performed using statistical t-tests and Minimum Redundancy Maximum Relevance (mRMR). A machine learning model based on random vector functional link network was constructed for diagnosis. Results: The proposed approach demonstrated a classification accuracy of 84.91% in distinguishing ASD from TD. Key discriminating network features were identified in the inferior frontal gyrus and superior occipital gyrus, regions critical for social and executive functions in ASD patients. Discussion: Our study presents an objective and effective approach to the clinical diagnosis of ASD, overcoming the limitations of subjective behavioral observations. The identified brain network features provide insights into the neurobiological mechanisms underlying ASD, potentially leading to more targeted interventions.

A Facile NMR Method for Pre-MRI Evaluation of Trigger-Responsive T1 Contrast Enhancement.

There is a growing interest in developing paramagnetic nanoparticles as responsive magnetic resonance imaging (MRI) contrast agents, which feature switchable T1 image contrast of water protons upon biochemical cues for better discerning diseases. However, performing an MRI is pragmatically limited by its cost and availability. Hence, a facile, routine method for measuring the T1 contrast is highly desired in early-stage development. This work presents a single-point inversion recovery (IR) nuclear magnetic resonance (NMR) method that can rapidly evaluate T1 contrast change by employing a single, optimized IR pulse sequence that minimizes water signal for "off-state" nanoparticles and allows for sensitively measuring the signal change with "switch-on" T1 contrast. Using peptide-induced liposomal gadopentetic acid (Gd3+ -DTPA) release and redox-sensitive manganese oxide (MnO2 ) nanoparticles as a demonstration of generality, this method successfully evaluates the T1 shortening of water protons caused by liposomal Gd3+ -DTPA release and Mn2+ formation from MnO2 reduction. Furthermore, the NMR measurement is highly correlated to T1 -weighted MRI scans, suggesting its feasibility to predict the MRI results at the same field strength. This NMR method can be a low-cost, time-saving alternative for pre-MRI evaluation for a diversity of responsive T1 contrast systems.

Linking sarcopenia, brain structure and cognitive performance: a large-scale UK Biobank study.

Sarcopenia refers to age-related loss of muscle mass and function and is related to impaired somatic and brain health, including cognitive decline and Alzheimer's disease. However, the relationships between sarcopenia, brain structure and cognition are poorly understood. Here, we investigate the associations between sarcopenic traits, brain structure and cognitive performance. We included 33 709 UK Biobank participants (54.2% female; age range 44-82 years) with structural and diffusion magnetic resonance imaging, thigh muscle fat infiltration (n = 30 561) from whole-body magnetic resonance imaging (muscle quality indicator) and general cognitive performance as indicated by the first principal component of a principal component analysis across multiple cognitive tests (n = 22 530). Of these, 1703 participants qualified for probable sarcopenia based on low handgrip strength, and we assigned the remaining 32 006 participants to the non-sarcopenia group. We used multiple linear regression to test how sarcopenic traits (probable sarcopenia versus non-sarcopenia and percentage of thigh muscle fat infiltration) relate to cognitive performance and brain structure (cortical thickness and area, white matter fractional anisotropy and deep and lower brain volumes). Next, we used structural equation modelling to test whether brain structure mediated the association between sarcopenic and cognitive traits. We adjusted all statistical analyses for confounders. We show that sarcopenic traits (probable sarcopenia versus non-sarcopenia and muscle fat infiltration) are significantly associated with lower cognitive performance and various brain magnetic resonance imaging measures. In probable sarcopenia, for the included brain regions, we observed widespread significant lower white matter fractional anisotropy (77.1% of tracts), predominantly lower regional brain volumes (61.3% of volumes) and thinner cortical thickness (37.9% of parcellations), with |r| effect sizes in (0.02, 0.06) and P-values in (0.0002, 4.2e-29). In contrast, we observed significant associations between higher muscle fat infiltration and widespread thinner cortical thickness (76.5% of parcellations), lower white matter fractional anisotropy (62.5% of tracts) and predominantly lower brain volumes (35.5% of volumes), with |r| effect sizes in (0.02, 0.07) and P-values in (0.0002, 1.9e-31). The regions showing the most significant effect sizes across the cortex, white matter and volumes were of the sensorimotor system. Structural equation modelling analysis revealed that sensorimotor brain regions mediate the link between sarcopenic and cognitive traits [probable sarcopenia: P-values in (0.0001, 1.0e-11); muscle fat infiltration: P-values in (7.7e-05, 1.7e-12)]. Our findings show significant associations between sarcopenic traits, brain structure and cognitive performance in a middle-aged and older adult population. Mediation analyses suggest that regional brain structure mediates the association between sarcopenic and cognitive traits, with potential implications for dementia development and prevention.

T1-weighted MRI of targeting atherosclerotic plaque based on CD40 expression on engulfed USPIO's cell surface.

Atherosclerosis is a chronic inflammatory disease characterized by the accumulation of cholesterol within the arterial wall. Its progression can be monitored via magnetic resonance imaging (MRI). Ultrasmall Superparamagnetic Particles of Iron Oxide (USPIO) (<5 nm) have been employed as T1 contrast agents for MRI applications. In this study, we synthesized USPIO with an average surface carboxylation of approximately 5.28 nm and a zeta potential of -47.8 mV. These particles were phagocytosed by mouse aortic endothelial cells (USPIO-MAECs) and endothelial progenitor cells (USPIO-EPCs), suggesting that they can be utilized as potential contrast agent and delivery vehicle for the early detection of atherosclerosis. However, the mechanism by which this contrast agent is delivered to the plaque remains undetermined. Our results demonstrated that with increasing USPIO concentration during 10-100 µg ml-1, consistent change appeared in signal enhancement on T1-weighted MRI. Similarly, T1-weighted MRI of MAECs and EPCs treated with these concentrations exhibited a regular change in signal enhancement. Prussian blue staining of USPIO revealed substantial absorption into MAECs and EPCs after treatment with 50 µg ml-1USPIO for 24 h. The iron content in USPIO-EPCs was much higher (5 pg Fe/cell) than in USPIO-MAECs (0.8 pg Fe/cell). In order to substantiate our hypothesis that CD40 protein on the cell surface facilitates migration towards inflammatory cells, we utilized AuNPs-PEI (gold nanoparticles-polyethylenimine) carrying siRNACD40to knockout CD40 expression in MAECs. It has been documented that gold nanoparticle-oligonucleotide complexes could be employed as intracellular gene regulation agents for the control of protein level in cells. Our results confirmed that macrophages are more likely to bind to MAECs treated with AuNPs-PEI-siRNANC(control) for 72 h than to MAECs treated with AuNPs-PEI-siRNACD40(reduced CD40 expression), thus confirming CD40 targeting at the cellular level. When USPIO-MAECs and MAECs (control) were delivered to mice (high-fat-fed) via tail vein injection respectively, we observed a higher iron accumulation in plaques on blood vessels in high-fat-fed mice treated with USPIO-MAECs. We also demonstrated that USPIO-EPCs, when delivered to high-fat-fed mice via tail vein injection, could indeed label plaques by generating higher T1-weighted MRI signals 72 h post injection compared to controls (PBS, USPIO and EPCs alone). In conclusion, we synthesized a USPIO suitable for T1-weighted MRI. Our results have confirmed separately at the cellular and tissue andin vivolevel, that USPIO-MAECs or USPIO-EPCs are more accessible to atherosclerotic plaques in a mouse model. Furthermore, the high expression of CD40 on the cell surface is a key factor for targeting and USPIO-EPCs may have potential therapeutic effects.

Diabetic striatopathy: an updated overview of current knowledge and future perspectives.

PURPOSE: Diabetic striatopathy (DS) is a rare complication of poorly controlled diabetes mellitus (DM), characterized by hyperglycemia associated with chorea/ballism and characteristic reversible basal ganglia abnormalities on computed tomography (CT) and/or magnetic resonance imaging (MRI). We propose a narrative review of the literature on this topic, currently unknown to most, and about which physicians should be aware. We intend to summarize, critically review, and take to mean the evidence on this disorder, describing its typical features. METHODS: We searched Pubmed for English-language sources using the following keywords in the title and the abstract: diabetic striatopathy, hyperglycemic non-ketotic hemichorea/hemiballism, chorea/hemichorea associated with non-ketotic hyperglycemia, diabetic hemiballism/hemichorea, chorea, hyperglycemia, and basal ganglia syndrome. We collected scientific articles, including case reports, reviews, systematic reviews, and meta-analyses from the years 1975 to 2023. We eliminated duplicate, non-English language or non-related articles. RESULTS: Older Asian women are more frequently affected. Suddenly or insidiously hemichorea/hemiballism, mainly in the limbs, and high blood glucose with elevated HbA1c in the absence of ketone bodies have been observed. Furthermore, CT striatal hyperdensity and T1-weighted MRI hyperintensity have been observed. DS is often a treatable disease following proper hydration and insulin administration. Histopathological findings are variable, and no comprehensive hypothesis explains the atypical cases reported. CONCLUSION: DS is a rare neurological manifestation of DM. If adequately treated, although treatment guidelines are lacking, the prognosis is good and life-threatening complications may occur occasionally. During chorea/hemiballism, we recommend blood glucose and HbA1c evaluation. Further studies are needed to understand the pathogenesis.

Nanodiamond-Enhanced Magnetic Resonance Imaging.

Nanodiamonds (ND) hold great potential for diverse applications due to their biocompatibility, non-toxicity, and versatile functionalization. Direct visualization of ND by means of non-invasive imaging techniques will open new venues for labeling and tracking, offering unprecedented and unambiguous detection of labeled cells or nanodiamond-based drug carrier systems. The structural defects in diamonds, such as vacancies, can have paramagnetic properties and potentially act as contrast agents in magnetic resonance imaging (MRI). The smallest nanoscale diamond particles, detonation ND, are reported to effectively reduce longitudinal relaxation time T1 and provide signal enhancement in MRI. Using in vivo, chicken embryos, direct visualization of ND is demonstrated as a bright signal with high contrast to noise ratio. At 24 h following intravascular application marked signal enhancement is noticed in the liver and the kidneys, suggesting uptake by the phagocytic cells of the reticuloendothelial system (RES), and in vivo labeling of these cells. This is confirmed by visualization of nanodiamond-labeled macrophages as positive (bright) signal, in vitro. Macrophage cell labeling is not associated with significant increase in pro-inflammatory cytokines or marked cytotoxicity. These results indicate nanodiamond as a novel gadolinium-free contrast-enhancing agent with potential for cell labeling and tracking and over periods of time.

Occult neurohypophyseal germinoma discovered during the course of long-term diabetes insipidus: illustrative case.

BACKGROUND: The authors report a case of occult neurohypophyseal germinoma detected in a patient with long-term diabetes insipidus. Central diabetes insipidus is the initial symptom in 95% of cases of neurohypophyseal germinoma. In occult neurohypophyseal germinomas, no abnormalities are seen on magnetic resonance imaging (MRI) at the onset of symptoms. It can take several months or even years for these changes to be detected on MRI. OBSERVATIONS: A 20-year-old male was diagnosed with central diabetes insipidus at the age of 17 years, and gonadal and adrenal corticosteroid insufficiency was noted at the age of 19 years. Head MRI showed an enlarged and enhanced pituitary stalk. He was referred to our department for a suspected neoplastic lesion. Endoscopic transsphenoidal biopsy indicated a pure germinoma. He was treated with chemotherapy and radiotherapy and then was discharged. LESSONS: In this case, new imaging findings appeared 19 months after the onset of diabetes insipidus, and the pathological diagnosis was made after almost 24 months. Because the patient had a history of growth hormone deficiency and had a positive test result for diabetes insipidus, occult neurohypophyseal germinoma was suspected, and periodic contrast-enhanced MRI monitoring was deemed essential.

Caspase-3-Triggered Intracellular Gadolinium Nanoparticle Formation for T1-Weighted Magnetic Resonance Imaging of Apoptosis In Vivo.

Apoptosis, with a hallmark of upregulated protease Caspase-3, has been frequently imaged with various probes to reveal the therapeutic efficiencies of different drugs. However, activatable molecular probes with programmable self-assembling behaviors that enable enhanced T1-weighted magnetic resonance imaging (MRI) of apoptosis remain scarce. Herein, taking advantage of a CBT-Cys click reaction, we rationally designed a Caspase-3-activatable self-assembling probe Ac-Asp-Glu-Val-Asp-Cys(StBu)-Lys(DOTA(Gd))-CBT (DEVDCS-Gd-CBT) for apoptosis imaging in vivo. After Caspase-3 cleavage in apoptotic cells, DEVDCS-Gd-CBT underwent CBT-Cys click reaction to form a cyclic dimer, which self-assembled into Gd nanoparticles. With this probe, enhanced T1-weighted MR images of apoptosis were achieved at low magnetic fields in vitro, in cis-dichlorodiamineplatinum-induced apoptotic cells and in tail-amputation-simulated apoptotic zebrafish. We anticipate that the smart probe DEVDCS-Gd-CBT could be applied for T1-weighted MRI of apoptosis-related diseases in the clinic in the future.

Quality assessment, variability and reproducibility of anatomical measurements derived from T1-weighted brain imaging: The RIN-Neuroimaging Network case study.

Initiatives for the collection of harmonized MRI datasets are growing continuously, opening questions on the reliability of results obtained in multi-site contexts. Here we present the assessment of the brain anatomical variability of MRI-derived measurements obtained from T1-weighted images, acquired according to the Standard Operating Procedures, promoted by the RIN-Neuroimaging Network. A multicentric dataset composed of 77 brain T1w acquisitions of young healthy volunteers (mean age = 29.7 ± 5.0 years), collected in 15 sites with MRI scanners of three different vendors, was considered. Parallelly, a dataset of 7 "traveling" subjects, each undergoing three acquisitions with scanners from different vendors, was also used. Intra-site, intra-vendor, and inter-site variabilities were evaluated in terms of the percentage standard deviation of volumetric and cortical thickness measures. Image quality metrics such as contrast-to-noise and signal-to-noise ratio in gray and white matter were also assessed for all sites and vendors. The results showed a measured global variability that ranges from 11% to 19% for subcortical volumes and from 3% to 10% for cortical thicknesses. Univariate distributions of the normalized volumes of subcortical regions, as well as the distributions of the thickness of cortical parcels appeared to be significantly different among sites in 8 subcortical (out of 17) and 21 cortical (out of 68) regions of i nterest in the multicentric study. The Bland-Altman analysis on "traveling" brain measurements did not detect systematic scanner biases even though a multivariate classification approach was able to classify the scanner vendor from brain measures with an accuracy of 0.60 ± 0.14 (chance level 0.33).

High-stability spherical lanthanide nanoclusters for magnetic resonance imaging.

High-nuclear lanthanide clusters have shown great potential for the administration of high-dose mononuclear gadolinium chelates in magnetic resonance imaging (MRI). The development of high-nuclear lanthanide clusters with excellent solubility and high stability in water or solution has been challenging and is very important for expanding the performance of MRI. We used N-methylbenzimidazole-2-methanol (HL) and LnCl3·6H2O to synthesize two spherical lanthanide clusters, Ln32 (Ln = Ho, Ho32; and Ln = Gd, Gd32), which are highly stable in solution. The 24 ligands L- are all distributed on the periphery of Ln32 and tightly wrap the cluster core, ensuring that the cluster is stable. Notably, Ho32 can remain highly stable when bombarded with different ion source energies in HRESI-MS or immersed in an aqueous solution of different pH values for 24 h. The possible formation mechanism of Ho32 was proposed to be Ho(III), (L)- and H2O → Ho3(L)3/Ho3(L)4 → Ho4(L)4/Ho4(L)5 → Ho6(L)6/Ho6(L)7 → Ho16(L)19 → Ho28(L)15 → Ho32(L)24/Ho32(L)21/Ho32(L)23. To the best of our knowledge, this is the first study of the assembly mechanism of spherical high-nuclear lanthanide clusters. Spherical cluster Gd32, a form of highly aggregated Gd(III), exhibits a high longitudinal relaxation rate (1 T, r1 = 265.87 mM-1·s-1). More notably, compared with the clinically used commercial material Gd-DTPA, Gd32 has a clearer and higher-contrast T1-weighted MRI effect in mice bearing 4T1 tumors. This is the first time that high-nuclear lanthanide clusters with high water stability have been utilized for MRI. High-nuclear Gd clusters containing highly aggregated Gd(III) at the molecular level have higher imaging contrast than traditional Gd chelates; thus, using large doses of traditional gadolinium contrast agents can be avoided.

Convolutional-recurrent neural networks approximate diffusion tractography from T1-weighted MRI and associated anatomical context.

Diffusion MRI (dMRI) streamline tractography is the gold-standard for in vivo estimation of white matter (WM) pathways in the brain. However, the high angular resolution dMRI acquisitions capable of fitting the microstructural models needed for tractography are often time-consuming and not routinely collected clinically, restricting the scope of tractography analyses. To address this limitation, we build on recent advances in deep learning which have demonstrated that streamline propagation can be learned from dMRI directly without traditional model fitting. Specifically, we propose learning the streamline propagator from T1w MRI to facilitate arbitrary tractography analyses when dMRI is unavailable. To do so, we present a novel convolutional-recurrent neural network (CoRNN) trained in a teacher-student framework that leverages T1w MRI, associated anatomical context, and streamline memory from data acquired for the Human Connectome Project. We characterize our approach under two common tractography paradigms, WM bundle analysis and structural connectomics, and find approximately a 5-15% difference between measures computed from streamlines generated with our approach and those generated using traditional dMRI tractography. When placed in the literature, these results suggest that the accuracy of WM measures computed from T1w MRI with our method is on the level of scan-rescan dMRI variability and raise an important question: is tractography truly a microstructural phenomenon, or has dMRI merely facilitated its discovery and implementation?

Reliability of spinal cord measures based on synthetic T1-weighted MRI derived from multiparametric mapping (MPM).

Short MRI acquisition time, high signal-to-noise ratio, and high reliability are crucial for image quality when scanning healthy volunteers and patients. Cross-sectional cervical cord area (CSA) has been suggested as a marker of neurodegeneration and potential outcome measure in clinical trials and is conventionally measured on T1-weigthed 3D Magnetization Prepared Rapid Acquisition Gradient-Echo (MPRAGE) images. This study aims to reduce the acquisition time for the comprehensive assessment of the spinal cord, which is typically based on MPRAGE for morphometry and multi-parameter mapping (MPM) for microstructure. The MPRAGE is replaced by a synthetic T1-w MRI (synT1-w) estimated from the MPM, in order to measure CSA. SynT1-w images were reconstructed using the MPRAGE signal equation based on quantitative maps of proton density (PD), longitudinal (R1) and effective transverse (R2*) relaxation rates. The reliability of CSA measurements from synT1-w images was determined within a multi-center test-retest study format and validated against acquired MPRAGE scans by assessing the agreement between both methods. The response to pathological changes was tested by longitudinally measuring spinal cord atrophy following spinal cord injury (SCI) for synT1-w and MPRAGE using linear mixed effect models. CSA measurements based on the synT1-w MRI showed high intra-site (Coefficient of variation [CoV]: 1.43% to 2.71%) and inter-site repeatability (CoV: 2.90% to 5.76%), and only a minor deviation of -1.65 mm2 compared to MPRAGE. Crucially, by assessing atrophy rates and by comparing SCI patients with healthy controls longitudinally, differences between synT1-w and MPRAGE were negligible. These results demonstrate that reliable estimates of CSA can be obtained from synT1-w images, thereby reducing scan time significantly.

The preparation of MnO2/BSA/CdTe quantum dots complex for ratiometric fluorescence/ T1-weighted MRI detection of H2O2.

Hydrogen peroxide, as the second messenger in cells, plays an essential regulatory role in cell proliferation, differentiation and migration. How to effectively identify H2O2 signals, and detect H2O2 in circulating tumor cells, are essential for the early diagnosis of tumors. Herein a fluorescence and T1-weighted MR dual-mode imaging material, named MnBQ, has been successfully prepared and characterized. Based on the chemical redox reaction between MnBQ and H2O2, a fluorescence/T1-weighted MRI dual-mode sensor has been developed for quantitative analysis of H2O2, of which the lowest limit detection obtained from fluorescence and MRI could reach 2.841 µmol/L and 43.85 µmol/L, respectively. This imaging sensor has dual advantages of high sensitivity and high spatial resolution, which could be a good candidate for monitoring of H2O2 in vivo.

Multi-atlas thalamic nuclei segmentation on standard T1-weighed MRI with application to normal aging.

Specific thalamic nuclei are implicated in healthy aging and age-related neurodegenerative diseases. However, few methods are available for robust automated segmentation of thalamic nuclei. The threefold aims of this study were to validate the use of a modified thalamic nuclei segmentation method on standard T1 MRI data, to apply this method to quantify age-related volume declines, and to test functional meaningfulness by predicting performance on motor testing. A modified version of THalamus Optimized Multi-Atlas Segmentation (THOMAS) generated 22 unilateral thalamic nuclei. For validation, we compared nuclear volumes obtained from THOMAS parcellation of white-matter-nulled (WMn) MRI data to T1 MRI data in 45 participants. To examine the effects of age/sex on thalamic nuclear volumes, T1 MRI available from a second data set of 121 men and 117 women, ages 20-86 years, were segmented using THOMAS. To test for functional ramifications, composite regions and constituent nuclei were correlated with Grooved Pegboard test scores. THOMAS on standard T1 data showed significant quantitative agreement with THOMAS from WMn data, especially for larger nuclei. Sex differences revealing larger volumes in men than women were accounted for by adjustment with supratentorial intracranial volume (sICV). Significant sICV-adjusted correlations between age and thalamic nuclear volumes were detected in 20 of the 22 unilateral nuclei and whole thalamus. Composite Posterior and Ventral regions and Ventral Anterior/Pulvinar nuclei correlated selectively with higher scores from the eye-hand coordination task. These results support the use of THOMAS for standard T1-weighted data as adequately robust for thalamic nuclear parcellation.

Standard deviations of MR signal intensities show a consistent trend during imaging follow-ups for glioblastoma patients when corrected for non-biological heterogeneity due to hardware and software variation.

INTRODUCTION: Glioblastoma multiforme (GBM) has a poor prognosis in spite of advanced MRI guided treatments today. Routine MRI using conventional T1 or advanced permeability based MRI of GBM often does not adequately represent changing tumor phases or overall survival. In this work, region of interest (ROI) based tissue MR standard deviation (SD) is demonstrated as an important MRI variable that could be a potential biomarker of GBM heterogeneity and radioresistance. MATERIALS AND METHODS: MRI characterization is often qualitative and lacks reproducibility. Using standardized MRI phantoms we have normalized retrospective records of 12 radioresistant GBM patients that underwent radiation therapy (RT) with concomitant and adjuvant temozolomide (TMZ) chemotherapy followed by serial MR imaging with gadolinium contrast. RESULTS AND DISCUSSION: We have identified key variables like hardware, software and protocol variation and have standardized those using test phantoms at five MR systems. We suggest GBM growth during the treatment period can be linked to normalized MRI signal and its fluctuations from session to session and from magnet to magnet by using an ROI derived standard deviation that corresponds to heterogeneity of the tumor MRI signal and changes in magnetic susceptibility. The time period observed in our patient group for peak standard deviations is approximately halfway through the tumor course and may correspond to a growth of more aggressive MES subtype of cells. To model the GBM heterogeneity we performed in vitro T1 weighted inversion recovery MRI experiments at 3 T for porous media of silicate particles in 1% aq solution of Gadavist and linked SD with particle size and local gadolinium volume within porous media. Such in vitro models mimic the increased SD in radioresistant GBM and as a novel contribution suggest that finer texture with high surface area might arise approximately halfway through the overall survival duration in GBM. CONCLUSION: Standard deviation as a measure of magnetic susceptibility may be collectively linked to the changes in texture, cell fractions (biological) and trapped contrast media (vascular as well as artifactual consequences) and should be evaluated as a potential biomarker of GBM aggressiveness than the overall MRI signal intensity from a GBM.

Functional connectivity and structural changes of thalamic subregions in episodic migraine.

BACKGROUND: The thalamus plays a crucial role in transmitting nociceptive information to various cortical regions involving migraine-related allodynia and photophobia. Abnormal structural and functional alterations related to the thalamus have been well established. However, it is unknown whether the brain structure and function of the thalamic subregions are differentially affected in this disorder. In this study, we aimed to clarify this issue by comparing the structure and function of 16 thalamic subregions between patients with episodic migraine (EM) and healthy controls (HCs). METHODS: Twenty-seven patients with EM and 30 sex-, age- and education-matched HCs underwent resting-state functional and structural magnetic resonance imaging scans. Functional connectivity (rsFC), grey matter volume (GMV), and diffusion tensor imaging (DTI) parameters of each subregion of the thalamus were calculated and compared between the two groups. Furthermore, correlation analyses between neuroimaging changes and clinical features were performed in this study. RESULTS: First, compared with HCs, patients with EM exhibited decreased rsFC between the anterior-medial-posterior subregions of the thalamus and brain regions mainly involved in the medial system of the pain processing pathway and default mode network (DMN). Second, for the whole thalamus and each of its subregions, there were no significant differences in GMV between patients with EM and HCs (P > 0.05, Bonferroni corrected). Third, there was no significant difference in DTI parameters between the two groups (P > 0.05). Finally, decreased rsFC was closely related to scores on the Hamilton Rating Scale for Anxiety (HAMA) and Big Five Inventory (BFI) scales. CONCLUSION: Selective functional hypoconnectivity in the thalamic subregions provides neuroimaging evidence supporting the important role of thalamocortical pathway dysfunction in episodic migraine, specifically, that it may modulate emotion and different personality traits in migraine patients.

The pancreas-to-muscle signal intensity ratio on T1-weighted MRI as a predictive biomarker for postoperative pancreatic fistula after distal pancreatectomy: a single-center retrospective study.

BACKGROUND: Postoperative pancreatic fistula (POPF) is one of the serious complications of pancreatic surgery. When POPF occurs and becomes severe, it causes secondary complications and a longer treatment period. We previously reported a correlation between pancreatic fibrosis and magnetic resonance imaging (MRI) findings, and MRI may have the potential to predict POPF. This study aimed to assess the predictive ability of the pancreas-to-muscle signal intensity ratio on T1-weighted MRI (SIR on T1-w MRI) for POPF after distal pancreatectomy (DP). METHODS: This single-institution retrospective study comprised 117 patients who underwent DP. It was conducted between 2010 and 2021 at the Gifu University Hospital. We statistically analyzed pre-, intra-, and postoperative factors to assess the correlation with POPF. RESULTS: According to the definition and grading of the International Study Group of Pancreatic Fistula (ISGPF), 29 (24.8%) of the 117 patients had POPF grades B and C. In the univariate analysis, POPF was significantly associated with the pancreas-to-muscle SIR on T1-w MRI, the drainage fluid amylase concentration (D-Amy) levels on postoperative day (POD) 1 and 3, white blood cell count on POD 1 and 3, C-reactive protein level on POD 3, and heart rate on POD 3. In multivariate analysis, only the pancreas-to-muscle SIR on T1-w MRI (>1.37; odds ratio [OR] 23.25; 95% confidence interval [CI] 3.93-454.03; p < 0.01) and D-Amy level on POD 3 (>737 U/l; OR 3.91; 95% CI 1.02-16.36; p = 0.046) were identified as independent predictive factors. CONCLUSIONS: The pancreas-to-muscle SIR on T1-w MRI and postoperative D-Amy levels were able to predict the development of POPF after DP. The pancreas-to-muscle SIR on T1-w MRI may be a potential objective biomarker reflecting pancreatic status.

Early Predictive Factors for Postoperative Pancreatic Fistula After Distal Pancreatectomy for Pancreatic Cancer.

BACKGROUND/AIM: Postoperative pancreatic fistula (POPF) is the most serious complication of distal pancreatectomy (DP). When POPF occurs and becomes severe, it causes secondary complications and leads to a longer treatment period. This study aimed to identify early predictive factors of POPF after DP for pancreatic cancer (PC). PATIENTS AND METHODS: This retrospective, single-institution study comprised of 55 patients with PC who underwent DP between 2010 and 2021 at the Gifu University Hospital. We statistically analyzed pre-, intra-, and post-operative factors to identify early predictive factors for POPF. RESULTS: According to the definition and grading of the International Study Group of Pancreatic Fistula (ISGPF), 12 (21.8%) of 55 patients had POPF grades B and C. In the univariate analysis, POPF was significantly associated with the pancreas-to-muscle signal intensity ratio on T 1 -weighted magnetic resonance imaging (SIR on T 1 -w MRI), the drainage fluid amylase (D-Amy) levels on postoperative day 3 (POD3), C-reactive protein (CRP) on POD3, and heart rate on POD3. In multivariate analysis, pancreas-to-muscle SIR on T 1 -w MRI [>1.37; odds ratio (OR)=17.08; 95% confidence interval (CI)=1.64-598.16; p=0.02], D-Amy levels on POD3 (>1,200 U/l; OR=20.00; 95% CI=1.73-563.83; p=0.02) and heart rate on POD3 (>100 bpm; OR=15.33; 95% CI=1.53-258.45; p=0.02) were identified as independent early predictive factors. CONCLUSION: Preoperative pancreas-to-muscle SIR on T 1 -w MRI and postoperative D-Amy levels and heart rate significantly correlated with POPF after DP for PC. Postoperative management based on these predictive factors may improve the postoperative course.