High-resolution Magnetic Resonance Imaging Research Articles

Internal carotid artery stenosis and occlusion based on machine learning: A comparative analysis of high-resolution MRI and CT angiography

ObjectiveTo explore the clinical application value of the imaging model of carotid artery stenosis occlusion based on machine learning. MethodsA comprehensive analysis was conducted on the medical records, MRI, and CT angiography images of 188 patients diagnosed with severe carotid artery stenosis. Specifically, the training cohort comprised 131 patients, including 107 males and 24 females, with an average age of 68 ± 8 years. A distinct verification group included 57 patients, 50 males, and 7 females, averaging 67 ± 8 years old. For the study, the volume of interest was manually outlined slice by slice, following the contour of the carotid plaque on cross-sectional images. The Radiomics package of Python software was used to extract image omics features. Feature screening was performed using intra - and inter-group correlation coefficients, redundancy analysis, minimum absolute contraction, and selection operator (LASSO) regression analysis. ResultsFour image omics features were selected based on the training set to construct the prediction model. Among the six machine learning models, the logistic regression model showed high and stable diagnostic efficiency, with an AUC of 0.872, sensitivity of 100.0%, and specificity of 66.2% in the training set. The AUC of the validation set was 0.867, the sensitivity was 83.3%, and the specificity was 78.8%. The calibration curve and DCA show that the logistic regression model has a reasonable degree of calibration and clinical application value. ConclusionPredictive MRI and CT angiography models based on machine learning have their respective application values in risk stratification of patients with severe asymptomatic carotid stenosis.

Functional locus coeruleus imaging to investigate an ageing noradrenergic system

The locus coeruleus (LC), our main source of norepinephrine (NE) in the brain, declines with age and is a potential epicentre of protein pathologies in neurodegenerative diseases (ND). In vivo measurements of LC integrity and function are potentially important biomarkers for healthy ageing and early ND onset. In the present study, high-resolution functional MRI (fMRI), a reversal reinforcement learning task, and dedicated post-processing approaches were used to visualise age differences in LC function (N = 50). Increased LC responses were observed during emotionally and task-related salient events, with subsequent accelerations and decelerations in reaction times, respectively, indicating context-specific adaptive engagement of the LC. Moreover, older adults exhibited increased LC activation compared to younger adults, indicating possible compensatory overactivation of a structurally declining LC in ageing. Our study shows that assessment of LC function is a promising biomarker of cognitive aging.

Risk factors for thrombotic events in systemic lupus erythematosus patients with antiphospholipid antibodies: insights from morphometric measurements of carotid arteries.

To identify the correlation between thrombosis and atherosclerosis in systemic lupus erythematosus (SLE) patients with antiphospholipid antibodies (aPLs) (SLE/aPLs) through high-resolution magnetic resonance imaging (HR-MRI) of the carotid artery. A single-center, cross-sectional study was conducted. We collected consecutive patients with SLE/aPLs and healthy controls who underwent carotid HR-MRI examinations. The morphometric characteristics of the common carotid artery (CCA), internal carotid artery (ICA), external carotid artery (ECA), and carotid bulb (Sinus) were measured, and the differences in morphometric parameters between different groups were analyzed. A total of 144 carotid arteries were analyzed. Compared with the control group, the wall area, wall thickness (WT and WTmax), and normalized wall index of CCA, ICA, ECA, and Sinus were increased in patients with SLE/aPLs, and the total vascular area (TVA) of CCA, ICA, and Sinus, and the bifurcation angle (BIFA) of ICA-ECA were also increased. A negative lupus anticoagulant (LAC) (with or without positive anticardiolipin antibody (aCL) or anti-β2glycoprotein antibody (aβ2GPI)) contributed to illustrating lower increased TVA and thickened vessel walls of CCA and ICA in SLE/aPLs patients without thrombotic events. Logistic regression analysis showed that WTmaxSinus and WTmaxGlobal were independent risk factors for thrombotic events in SLE/aPLs patients. The receiver operator characteristic curve showed that the cut-off value of WTmaxSinus was 2.855 mm, and WTmaxGlobal was 3.370 mm. HR-MRI ensures the complete and accurate measurement of carotid morphometric parameters. Compared with the control group, the carotid artery in patients with SLE/aPLs is mainly characterized by diffusely thickened vessel walls, and the patients with thrombotic events showed additional higher vascular area of CCA and ICA, and BIFA of ICA-ECA without significant change in lumen area. The carotid arteries of SLE/aPLs patients with thrombotic events exhibited significant vessel wall thickening in all segments except ECA compared to those without thrombotic events. LAC-negative and non-thrombotic events distinguish relatively early atherosclerosis in the carotid arteries in patients with SLE/aPLs. Patients with SLE/aPLs that possess circumscribed thickened carotid vessel walls (>3.370 mm), particularly thickened at the Sinus (>2.855 mm), may require management strategies for the risk of thrombotic events.

Cortex-to-caudate volume ratio as a predictor of cognitive decline in Alzheimer's disease and mild cognitive impairment

BackgroundBrain and cortical atrophy play crucial roles in supporting the clinical diagnosis of Alzheimer's disease (AD). This study hypothesized that the ratios of brain or cortical volume to subcortical gray matter structure volumes are potential imaging markers for cognitive alterations in AD dementia and amnestic mild cognitive impairment (aMCI). MethodsSeventy-seven subjects diagnosed with AD dementia or aMCI underwent baseline neuropsychological testing, 2-year follow-up cognitive assessments, and high-resolution T1-weighted MRI scans. Total brain/cortical volume and subcortical gray matter structure volumes were automatically segmented and measured. Univariate and multiple linear regression analyses were conducted to determine the associations between volumetric ratios and interval changes in cognitive scores. ResultsThe ratio of cortical volume to caudate volume showed the most significant association with changes in MoCA (B = 0.132, SE = 0.042, p = 0.002), MMSE (B = 0.140, SE = 0.040, p = 0.001), and CDR-SOB (B = −0.013, SE = 0.005, p = 0.007) scores over the 2-year follow-up period. These associations remained significant after adjusting for various covariates. Similar associations were observed for the ratios of cortical volume to putamen and globus pallidum volumes. ConclusionsThe cortex-to-caudate volume ratio is significantly associated with cognitive decline in AD dementia and aMCI. This ratio may serve as a useful biomarker for monitoring disease progression and predicting cognitive outcomes. Our findings highlight the importance of considering the relative atrophy of cortical and subcortical structures in understanding AD pathology.

Circadian functional changes of pain-processing brainstem nuclei and implications for cluster headache: A 7 Tesla imaging study.

Pain thresholds and primary headaches, including cluster headache attacks, have circadian rhythmicity. Thus, they might share a common neuronal mechanism. This study aimed to elucidate how the modulation of nociceptive input in the brainstem changes from noon to midnight. Insights into the mechanism of these fluctuations could allow for new hypotheses about the pathophysiology of cluster headache. This repeated measure observational study was conducted at the University Hospital Zurich from December 2019 to November 2022. Healthy adults between 18 and 85 years of age were eligible. All participants were examined at noon and midnight. We tested the pain threshold on both sides of the foreheads with quantitative sensory testing, assessed tiredness levels, and obtained high-field (7 Tesla) and high-resolution functional magnetic resonance imaging (MRI) at each visit. Functional connectivity was assessed at the two visits by performing a region-of-interest analysis. We defined nuclei in the brainstem implicated in processing nociceptive input as well as the thalamus and suprachiasmatic nucleus as the region-of-interest. Ten people were enrolled, and seven participants were included. First, we did not find statistically significant differences between noon and midnight of A-delta-mediated pain thresholds (median mechanical pain threshold at noon: left 9.2, right 9.2; at night: left 6.5, right 6.1). Second, after correction for a false discovery rate, we found changes in the mechanical pain sensitivity to have a statistically significant effect on changes in the functional connectivity between the left parabrachial nucleus and the suprachiasmatic nucleus (T = -40.79). The MRI data analysis suggested that brain stem nuclei and the hypothalamus modulate A-delta-mediated pain perception; however, these changes in pain perception did not lead to statistically significantly differing pain thresholds between noon and midnight. Hence, our findings shed doubt on our hypothesis that the physiologic circadian rhythmicity of pain thresholds could drive the circadian rhythmicity of cluster headache attacks.

Role of the vessel morphology on the lenticulostriate arteries hemodynamics during atrial fibrillation: A CFD-based multivariate regression analysis

Background and objectiveAtrial fibrillation (AF) is the most common cardiac arrhythmia, inducing accelerated and irregular beating. Beside well-known disabling symptoms - such as palpitations, reduced exercise tolerance, and chest discomfort - there is growing evidence that an alteration of deep cerebral hemodynamics due to AF increases the risk of vascular dementia and cognitive impairment, even in the absence of clinical strokes. The alteration of deep cerebral circulation in AF represents one of the least investigated among the possible mechanisms. Lenticulostriate arteries (LSAs) are small perforating arteries mainly departing from the middle cerebral artery (MCA) and susceptible to small vessel disease, which is one of the mechanisms of subcortical vascular dementia development. The purpose of this study is to investigate the impact of different LSAs morphologies on the cerebral hemodynamics during AF. MethodsBy combining a computational fluid dynamics (CFD) analysis of LSAs with 7T high-resolution magnetic resonance imaging (MRI), we performed different CFD-based multivariate regression analyses to detect which geometrical and morphological vessel features mostly affect AF hemodynamics in terms of wall shear stress. We exploited 17 cerebral 7T-MRI derived LSA vascular geometries extracted from 10 subjects and internal carotid artery data from validated 0D cardiovascular-cerebral modeling as inflow conditions. ResultsOur results revealed that few geometrical variables - namely the size of the MCA and the bifurcation angles between MCA and LSA - are able to satisfactorily predict the AF impact. In particular, the present study indicates that LSA morphologies exhibiting markedly obtuse LSA-MCA inlet angles and small MCA size downstream of the LSA-MCA bifurcation may be more prone to vascular damage induced by AF. ConclusionsThe present MRI-based computational study has been able for the first time to: (i) investigate the net impact of LSAs vascular morphologies on cerebral hemodynamics during AF events; (ii) detect which combination of morphological features worsens the hemodynamic response in the presence of AF. Awaiting necessary clinical confirmation, our analysis suggests that the local hemodynamics of LSAs is affected by their geometrical features and some LSA morphologies undergo greater hemodynamic alterations in the presence of AF.

Acute limbic system connectivity predicts chronic cognitive function in mild traumatic brain injury: An individualized differential structural covariance network study

Mild traumatic brain injury (mTBI) is a known risk factor for neurodegenerative diseases, yet the precise pathophysiological mechanisms remain poorly understand, often obscured by group-level analysis in non-invasive neuroimaging studies. Individual-based method is critical to exploring heterogeneity in mTBI. We recruited 80 mTBI patients and 40 matched healthy controls, obtaining high-resolution structural MRI for constructing Individual Differential Structural Covariance Networks (IDSCN). Comparisons were conducted at both the individual and group levels. Connectome-based Predictive Modeling (CPM) was applied to predict cognitive performance based on whole-brain connectivity. During the acute stage of mTBI, patients exhibited significant heterogeneity in the count and direction of altered edges, obscured by group-level analysis. In the chronic stage, the number of altered edges decreased and became more consistent, aligning with clinical observations of acute cognitive impairment and gradual improvement. Subgroup analysis based on loss of consciousness/post-traumatic amnesia revealed distinct patterns of alterations. The temporal lobe, particularly regions related to the limbic system, significantly predicted cognitive function from acute to chronic stage. The use of IDSCN and CPM has provided valuable individual-level insights, reconciling discrepancies from previous studies. Additionally, the limbic system may be an appropriate target for future intervention efforts.

Multi kernel cross sparse graph attention convolutional neural network for brain magnetic resonance imaging super-resolution

High-resolution Magnetic Resonance Imaging (MRI) is pivotal in both diagnosing and treating brain tumors, assisting physicians in diagnosis and treatment by displaying anatomical structures. Utilizing convolutional neural network-based super-resolution methods enables the efficient acquisition of high-resolution MRI images.However, Convolutional neural networks are limited by their kernel size, which restricts their ability to capture a wider field of view, potentially leading to feature omission and difficulties in establishing global and local feature relationships. To overcome these shortcomings, We have designed a novel network architecture that highlights three main modules: (i) Multiple Convolutional Feature (MCF)extraction module, which diversifies convolution operations for extracting image features, achieving comprehensive feature representation. (ii) Multiple Groupss of Cross-Iterative Feature(MGCIF) modules, promoting inter-channel feature interactions and emphasizing crucial features needed for subsequent learning. (iii) A Graph Neural Network Module based on a sparse attention mechanism, capable of connecting distant pixel features and identifying influential neighboring pixels for target pixel inpainting. To evaluate the accuracy of our proposed network, we conducted tests on four datasets, comprising two sets of brain tumor data and two sets of healthy head MRI data, all of which underwent varying degrees of degradation. We conducted experiments using nineteen super-resolution (SR) models. Our experiments were carried out on four datasets, and the results demonstrate that our method outperforms the current leading-edge methods. In the four datasets, our model showed improvements in Peak Signal-to-Noise Ratio (PSNR) scores compared to the second-place model,with increase of 1.16 %,1.08 %,0.19 % and 0.53 % for ×2,and 2.26 %,1.67 %,0.13 % and 0.45 % for × 4,respectively.

Structural Brain Alterations in Metabolic Syndrome: A Comprehensive MRI Volumetric Analysis of Subcortical and Associated Structures.

Objective: This study aims to elucidate the comprehensive effects of metabolic syndrome (MetS) on the structural integrity of subcortical brain regions and associated structures through high-resolution magnetic resonance imaging (MRI) volumetric analysis, thereby contributing to a deeper understanding of the neuroanatomical dimensions of MetS and its potential implications for cognitive functions and overall brain health. Methods: A cross-sectional design was implemented, involving 25 individuals diagnosed with MetS for at least one year and a healthy control group of 15 individuals at a tertiary hospital's family medicine clinic in Eastern Turkey. Participants underwent a high-resolution MRI scan using a 1.5T Siemens Aera scanner. The MRICloud platform was employed for comprehensive segmentation and quantitative analysis of various brain structures. Results: The study revealed significant volumetric reductions in all measured subcortical brain regions among individuals with MetS compared to the control group (all P < 0.05). Notable differences were observed in key structures such as the substantia nigra, corpus callosum, and thalamus. In subcortical structures, the largest volumetric differences were noted in the basal ganglia L (1322.4 mm³), while the most significant percentage differences were seen in the substantia nigra R (25.24%) and caudate nucleus L (21.02%). Conclusion: The findings from this study underscore the significant neuroanatomical changes associated with MetS, manifesting as volumetric reductions in critical subcortical brain areas. These alterations underscore the necessity for further research into the comprehensive influence of MetS on cognitive processes and the potential for early therapeutic interventions.

Clinical evaluation of 3D high-resolution isotropic knee MRI using Multi-Interleaved X-prepared TSE with inTUitive RElaxometry (MIXTURE) for simultaneous morphology and T2 mapping

PurposeQuantitative MRI techniques such as T2 mapping are useful in comprehensive evaluation of various pathologies of the knee joint yet require separate scans to conventional morphological measurements and long acquisition times. The recently introduced 3D MIXTURE (Multi-Interleaved X-prepared Turbo-Spin Echo with Intuitive Relaxometry) technique can obtain simultaneous morphologic and quantitative information of the knee joint. To compare MIXTURE with conventional methods and to identify differences in morphological and quantitative information. MethodsPhantom studies were conducted, and in vivo human scans were performed (20 patients) presented with knee arthralgia. MIXTURE is based on 3D TSE without and with T2 preparation modules in an interleaved manner for both morphology with PDW and fat suppressed T2W imaging as well as quantitative T2 mapping within one single scan. Image quality and lesion depiction were visually assessed and compared between MIXTURE and conventional 2D TSE by two experienced radiologists. Contrast-to-noise ratio was used to assess the adjacent tissue contrast in a quantitative way for both obtained PDW and fat suppressed T2W images. Quantitative T2 values were measured in phantom and from in vivo knee cartilage. ResultsThe overall diagnostic confidence and contrast-to-noise ratio were deemed comparable between MIXTURE and 2D TSE. While the chosen T2 preparation modules for MIXTURE rendered consistent T2 values comparing to the current standard, measured cartilage T2 values ranged from 26.1 to 50.7 ms, with significant difference between the lesion and normal areas (p < 0.05). ConclusionsMIXTURE can help to provide high-resolution information for both anatomical and pathological assessment.

A non-inferiority study of MRI versus CT for staging and image-defined risk factor assessment in the preoperative work-up of abdominopelvic neuroblastoma

BackgroundNeuroblastoma accounts for 15 % of cancer deaths in children. Complete surgical resection is associated with a higher overall survival rate but also a higher morbidity rate. An international group of experts has defined a nomenclature of image-defined risk factors (IDRFs) for the determination of operability and the anticipation of reasonably foreseeable complications of surgery. However, there is no consensus on the optimal imaging modality (CT or MRI) for the assessment of IDRFs. The objective of the present study was to determine the non-inferiority of MRI vs. CT in the preoperative assessment of abdominopelvic neuroblastoma. The secondary objective was to assess the contribution of gadolinium contrast enhancement. MethodsAll children diagnosed with abdominopelvic neuroblastoma and whose preoperative work-up included a contrast-enhanced CT or MRI scan of the abdomen and pelvis between January 2014 and January 2023 were included. To evaluate the IDRFs, all the images were reviewed in three steps: (i) non-contrast MRI scans, (ii) both non-contrast and contrast-enhanced MRI scans, and (iii) contrast-enhanced CT scans. ResultsTwenty-five patients were found to be eligible, and fifteen were included. The mean time interval between MRI and preoperative CT was 23 days. In all patients, the identified IDRFs were similar for all three imaging modalities. Fourteen patients underwent full resection of the tumour. The surgical reports were fully consistent with the IDRFs described on CT and/or MRI. ConclusionA high-resolution three-dimensional T2 MRI sequence agreed fully with contrast-enhanced CT for the detection of IDRFs. Contrast-enhanced MRI did not add value. However, surgeons will need time to adapt to this MRI-based approach and learn how to interpret the results with confidence.

Clinical High-Resolution Imaging of the Inner Ear by Using Magnetic Resonance Imaging (MRI) and Cone Beam Computed Tomography (CBCT).

Imaging of the delicate inner ear morphology has become more and more precise owing to the rapid progress in magnetic resonance imaging (MRI). However, in clinical practice, the interpretation of imaging findings is hampered by a limited knowledge of anatomical details which are frequently obscured by artifacts. Corresponding review articles are as rare in journals as they are in reference books. This shortness prompted us to perform a direct comparison of imaging with anatomical whole-mount sections as a reference. It was the intention of this paper to compare the microscopic anatomy of a human inner ear as shown on anatomical whole-mount sections with high-resolution MRI and cone beam computed tomography (CBCT). Both are available in clinical routine and depict the structures with maximum spatial resolution. It was also a goal of this work to clarify if structures that were observed on MRI in a regular manner correlate with factual inner ear anatomy or correspond with artifacts typical for imaging. A fresh human anatomical specimen was examined on a clinical 3-Tesla MRI scanner using a dedicated surface coil. The same specimen was then studied with CBCT. In each imaging modality, high-resolution 3D data sets which enabled multiplanar reformatting were created. In the second step, anatomical whole-mount sections of the specimen were cut and stained. This process enabled a direct comparison of imaging with anatomical conditions. Clinical MRI was able to depict the inner ear with remarkable anatomical precision. Strongly T2-weighted imaging protocols are exquisitely capable of showing the fluid-filled components of the inner ear. The macular organs, ampullar crests and cochlear aqueduct were clearly visible. Truncation artifacts are prone to be confused with the delicate membrane separating the endolymphatic from the perilymphatic compartment. However, it was not possible to directly depict this borderline. With the maximum resolution of magnetic resonance tomography, commonly used in everyday clinical practice, even the smallest details of the inner ear structures can be reliably displayed. However, it is important to distinguish between truncation artifacts and true anatomical structures. Therefore, this study can be useful as a reference for image analysis.

Synthesizing PET images from high-field and ultra-high-field MR images using joint diffusion attention model.

Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) stand as pivotal diagnostic tools for brain disorders, offering the potential for mutually enriching disease diagnostic perspectives. However, the costs associated with PET scans and the inherent radioactivity have limited the widespread application of PET. Furthermore, it is noteworthy to highlight the promising potential of high-field and ultra-high-field neuroimaging in cognitive neuroscience research and clinical practice. With the enhancement of MRI resolution, a related question arises: can high-resolution MRI improve the quality of PETimages? This study aims to enhance the quality of synthesized PET images by leveraging the superior resolution capabilities provided by high-field and ultra-high-fieldMRI. From a statistical perspective, the joint probability distribution is considered the most direct and fundamental approach for representing the correlation between PET and MRI. In this study, we proposed a novel model, the joint diffusion attention model, namely, the joint diffusion attention model (JDAM), which primarily focuses on learning information about the joint probability distribution. JDAM consists of two primary processes: the diffusion process and the sampling process. During the diffusion process, PET gradually transforms into a Gaussian noise distribution by adding Gaussian noise, while MRI remains fixed. The central objective of the diffusion process is to learn the gradient of the logarithm of the joint probability distribution between MRI and noise PET. The sampling process operates as a predictor-corrector. The predictor initiates a reverse diffusion process, and the corrector applies Langevindynamics. Experimental results from the publicly available Alzheimer's Disease Neuroimaging Initiative dataset highlight the effectiveness of the proposed model compared to state-of-the-art (SOTA) models such as Pix2pix and CycleGAN. Significantly, synthetic PET images guided by ultra-high-field MRI exhibit marked improvements in signal-to-noise characteristics when contrasted with those generated from high-field MRI data. These results have been endorsed by medical experts, who consider the PET images synthesized through JDAM to possess scientific merit. This endorsement is based on their symmetrical features and precise representation of regions displaying hypometabolism, a hallmark of Alzheimer'sdisease. This study establishes the feasibility of generating PET images from MRI. Synthesis of PET by JDAM significantly enhances image quality compared to SOTAmodels.

Integrative molecular and structural neuroimaging analyses of the interaction between depression and age of onset: A multimodal magnetic resonance imaging study

Depression is a neurodevelopmental disorder that exhibits progressive gray matter volume (GMV) atrophy. Research indicates that brain development is influential in depression-induced GMV alterations. However, the interaction between depression and age of onset is not well understood by the underlying molecular and neuropathological mechanisms. Thus, 152 first-episode depression individuals and matched 130 healthy controls (HCs) were recruited to undergo T1-weighted high-resolution magnetic resonance imaging for this study. By two-way ANOVA, age and diagnosis were used as factors when analyzing the interaction of GMV in the participants. Then, spatial correlations between neurotransmitter maps and factor-related volume maps are established. Results illustrate a pronounced antagonistic interaction between depression and age of onset in the right insula, superior temporal gyrus, anterior cingulate gyrus, and orbitofrontal gyrus. Depression-caused reductions in GMV are mainly distributed in thalamic-limbic-cortical regions, regardless of age. For the main effect of age, adults exhibit brain atrophy in frontal, cerebellum, parietal, and temporal lobe structures. Cross-modal correlations showed that GMV changes in the interactive regions were linked with the serotonergic system and dopaminergic systems. Summarily, our results reveal the interaction between depression and age of onset in neurobiological mechanisms, which provide hints for future treatment of different ages of depression.

23Na MRI: inter-reader reproducibility of normal fibroglandular sodium concentration measurements at 3 T

BackgroundTo study the reproducibility of 23Na magnetic resonance imaging (MRI) measurements from breast tissue in healthy volunteers.MethodsUsing a dual-tuned bilateral 23Na/1H breast coil at 3-T MRI, high-resolution 23Na MRI three-dimensional cones sequences were used to quantify total sodium concentration (TSC) and fluid-attenuated sodium concentration (FASC). B1-corrected TSC and FASC maps were created. Two readers manually measured mean, minimum and maximum TSC and mean FASC values using two sampling methods: large regions of interest (LROIs) and small regions of interest (SROIs) encompassing fibroglandular tissue (FGT) and the highest signal area at the level of the nipple, respectively. The reproducibility of the measurements and correlations between density, age and FGT apparent diffusion coefficient (ADC) values were evaluatedss.ResultsNine healthy volunteers were included. The inter-reader reproducibility of TSC and FASC using SROIs and LROIs was excellent (intraclass coefficient range 0.945−0.979, p < 0.001), except for the minimum TSC LROI measurements (p = 0.369). The mean/minimum LROI TSC and mean LROI FASC values were lower than the respective SROI values (p < 0.001); the maximum LROI TSC values were higher than the SROI TSC values (p = 0.009). TSC correlated inversely with age but not with FGT ADCs. The mean and maximum FGT TSC and FASC values were higher in dense breasts in comparison to non-dense breasts (p < 0.020).ConclusionsThe chosen sampling method and the selected descriptive value affect the measured TSC and FASC values, although the inter-reader reproducibility of the measurements is in general excellent.Relevance statement23Na MRI at 3 T allows the quantification of TSC and FASC sodium concentrations. The sodium measurements should be obtained consistently in a uniform manner.Key points• 23Na MRI allows the quantification of total and fluid-attenuated sodium concentrations (TSC/FASC).• Sampling method (large/small region of interest) affects the TSC and FASC values.• Dense breasts have higher TSC and FASC values than non-dense breasts.• The inter-reader reproducibility of TSC and FASC measurements was, in general, excellent.• The results suggest the importance of stratifying the sodium measurements protocol.Graphical

Optimizing timing for quantification of intracranial aneurysm enhancement: a multi-phase contrast-enhanced vessel wall MRI study.

Aneurysm wall enhancement (AWE) on high-resolution contrast-enhanced vessel wall MRI (VWMRI) is an emerging biomarker for intracranial aneurysms (IAs) stability. Quantification methods of AWE in the literature, however, are variable. We aimed to determine the optimal post-contrast timing to quantify AWE in both saccular and fusiform IAs. Consecutive patients with unruptured IAs were prospectively recruited. VWMRI was acquired on 1 pre-contrast and 4 consecutive post-contrast phases (each phase was 9 min). Signal intensity values of cerebrospinal fluid (CSF) and aneurysm wall on pre- and 4 post-contrast phases were measured to determine the aneurysm wall enhancement index (WEI). AWE was also qualitatively analyzed on post-contrast images using previous grading criteria. The dynamic changes of AWE grade and WEI were analyzed for both saccular and fusiform IAs. Thirty-four patients with 42 IAs (27 saccular IAs and 15 fusiform IAs) were included. The changes in AWE grade occurred in 8 (30%) saccular IAs and 6 (40%) in fusiform IAs during the 4 post-contrast phases. The WEI of fusiform IAs decreased 22.0% over time after contrast enhancement (p = 0.009), while the WEI of saccular IAs kept constant during the 4 post-contrast phases (p > 0.05). When performing quantitative analysis of AWE, acquiring post-contrast VWMRI immediately after contrast injection achieves the strongest AWE for fusiform IAs. While the AWE degree is stable for 36 min after contrast injection for saccular IAs. The standardization of imaging protocols and analysis methods for AWE will be helpful for imaging surveillance and further treatment decisions of patients with unruptured IAs. Imaging protocols and measurements of intracranial aneurysm wall enhancement are reported heterogeneously. Aneurysm wall enhancement for fusiform intracranial aneurysms (IAs) is strongest immediately post-contrast, and stable for 36 min for saccular IAs. Future multi-center studies should investigate aneurysm wall enhancement as an emerging marker of aneurysm growth and rupture.

11.7T Diffusion Magnetic Resonance Imaging and Tractography to Probe Human Brain Organoid Microstructure

BackgroundHuman brain organoids are 3-dimensional cellular models that mimic architectural features of a developing brain. Generated from human induced pluripotent stem cells, these organoids offer an unparalleled physiologically relevant in vitro system for disease modeling and drug screening. In the current study, we sought to establish a foundation for a magnetic resonance imaging (MRI)–based, label-free imaging system that offers high-resolution capabilities for deep tissue imaging of whole organoids. MethodsAn 11.7T Bruker/89 mm microimaging system was used to collect high-resolution multishell 3-dimensional diffusion images of 2 induced pluripotent stem cell–derived human hippocampal brain organoids. The MRI features identified in the study were interpreted on the basis of similarities with immunofluorescence microscopy. ResultsMRI microscopy at ≤40 μm isotropic resolution provided a 3-dimensional view of organoid microstructure. T2-weighted contrast showed a rosette-like internal structure and a protruding spherical structure that correlated with immunofluorescence staining for the choroid plexus. Diffusion tractography methods can be used to model tissue microstructural features and possibly map neuronal organization. This approach complements traditional immunohistochemistry imaging methods without the need for tissue clearing. ConclusionsThis proof-of-concept study shows, for the first time, the application of high-resolution diffusion MRI microscopy to image 2-mm diameter spherical human brain organoids. Application of ultrahigh-field MRI and diffusion tractography is a powerful modality for whole organoid imaging and has the potential to make a significant impact for probing microstructural changes in brain organoids used to model psychiatric disorders, neurodegenerative diseases, and viral infections of the human brain, as well as for assessing neurotoxicity in drug screening.

Comparison of detailed brain volume measurements in schizophrenia with healthy individuals

Aims: This study aims to provide insights into the preliminary and definitive diagnosis, treatment modalities, and elucidation of the underlying pathophysiological mechanisms of schizophrenia, alongside ongoing research efforts. Methods: This retrospective study examined a cohort of 31 patients (17 male, 14 female) diagnosed with schizophrenia according to the criteria specified in the Diagnostic and Statistical Manual of Mental Disorders (DSM V) at the Psychiatry Clinic of the University Hospital. The healthy control group, comprising 31 individuals (17 male, 14 female), was selected from archived records at the same hospital, with sociodemographic characteristics matching those of the patient group. High-resolution T1-weighted MRI images of the individuals were analyzed using the VolBrain AssemblyNet program. Results: It has been observed that the volumes of various brain structures, including white matter (WM), gray matter (GM), subcortical GM, cortical GM, WM+GM, IC, total cerebrum, right cerebrum, left cerebrum, cerebrum WM, cerebrum GM, are significantly reduced (p&lt;0.05) in patients diagnosed with schizophrenia compared to healthy controls. Additionally, volumes of cerebellar WM, GM, vermis, brainstem, accumbens, hippocampus, thalamus, ventral diencephalon (DC), amygdala, and basal forebrain were found to be decreased in schizophrenia patients compared to healthy controls. Conversely, volumes of the pallidum, caudate, putamen, inferior lateral ventricle, lateral ventricle, third ventricle, fourth ventricle, and CSF were observed to be increased. Conclusion: These findings underscore the widespread nature of neuroanatomical alterations in schizophrenia and highlight the importance of understanding these changes for elucidating the disorder's pathophysiology and developing targeted therapeutic interventions. Further research is warranted to explore the interplay of genetic, developmental, and environmental factors in schizophrenia.

Cross-Modality Reference and Feature Mutual-Projection for 3D Brain MRI Image Super-Resolution.

High-resolution (HR) magnetic resonance imaging (MRI) can reveal rich anatomical structures for clinical diagnoses. However, due to hardware and signal-to-noise ratio limitations, MRI images are often collected with low resolution (LR) which is not conducive to diagnosing and analyzing clinical diseases. Recently, deep learning super-resolution (SR) methods have demonstrated great potential in enhancing the resolution of MRI images; however, most of them did not take the cross-modality and internal priors of MR seriously, which hinders the SR performance. In this paper, we propose a cross-modality reference and feature mutual-projection (CRFM) method to enhance the spatial resolution of brain MRI images. Specifically, we feed the gradients of HR MRI images from referenced imaging modality into the SR network to transform true clear textures to LR feature maps. Meanwhile, we design a plug-in feature mutual-projection (FMP) method to capture the cross-scale dependency and cross-modality similarity details of MRI images. Finally, we fuse all feature maps with parallel attentions to produce and refine the HR features adaptively. Extensive experiments on MRI images in the image domain and k-space show that our CRFM method outperforms existing state-of-the-art MRI SR methods.

Correlation between chest DW-MRI and 18F-FDG PET/CT in newly diagnosed non-small cell lung cancer (NSCLC)

BackgroundPET/CT is currently the gold standard for lung cancer staging, and it is also used to identify distant and nodal metastases. High-resolution MRI can also be used to diagnose and provide morphological details about lung cancer. Standardized uptake value ‘SUV’ calculated from PET/CT gives information about tumor behavior where the SUV reflects metabolic tumor activity. Apparent diffusion coefficient ‘ADC’ calculated from DW-MRI is a quantitative imaging marker aiming to assess tumor cellularity which reflects tumor behavior. The study aimed to correlate ADC assessed by DW-MRI and metabolic activity determined by SUV max in PET/CT in local and nodal staging of newly diagnosed NSCLC.ResultsOur study involved twenty-one patients who were pathologically proven to be NSCLC, 19 males (90.5%) and 2 females (9.5%), with a median age of 61 years (ranging from 37 to 84 years). Among all NSCLC primary mass lesions, we observed a statistically significant inverse correlation between SUV max achieved from PET/CT and ADC max, ADC mean, and ADC min calculated from DW-MR (r = − 0.509 and p = 0.019, r = − 0.472 and p = 0.031 and r = − 0.434 and p = 0.049 for correlation between SUV max of PET/CT and ADC max, ADC mean and ADC min of DW-MR, respectively). Additionally, we observed another statistically significant inverse correlation between SUV max achieved from PET/CT and ADC max, ADC mean, and ADC min calculated from DW-MR in NSCLC mediastinal lymph nodes (r = − 0.699 and p = 0.011, r = − 0.58 and p = 0.048 and r = − 0.629 and p = 0.028 for correlation between SUV max of PET/CT and ADC max, ADC mean and ADC min of DW-MR, respectively).ConclusionsADC values calculated from DW-MRI might act as a new prognostic tool owing to its significant inverse correlation with SUV max achieved from PET/CT in NSCLC primary mass lesions as well as mediastinal lymph nodes.