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Magnetic resonance imaging (MRI) is the method of choice for noninvasive studies of micrometer-scale structures in biological tissues via their effects on the time- and frequency-dependent (restricted) and anisotropic self-diffusion of water. While new designs of time-dependent magnetic field gradient waveforms have enabled disambiguation between different aspects of translational motion that are convolved in traditional MRI methods relying on single pairs of field gradient pulses, data analysis for complex heterogeneous materials remains a challenge. Here, we propose and demonstrate nonparametric distributions of tensor-valued Lorentzian diffusion spectra, or "D(ω) distributions," as a general representation with sufficient flexibility to describe the MRI signal response from a wide range of model systems and biological tissues investigated with modulated gradient waveforms separating and correlating the effects of restricted and anisotropic diffusion. [ABSTRACT FROM AUTHOR]

Cyclic fluctuations in hypothalamic-pituitary-gonadal axis (HPG-axis) hormones exert powerful behavioral, structural, and functional effects through actions on the mammalian central nervous system. Yet, very little is known about how these fluctuations alter the structural nodes and information highways of the human brain. In a study of 30 naturally cycling women, we employed multidimensional diffusion and T1-weighted imaging during three estimated menstrual cycle phases (menses, ovulation, and mid-luteal) to investigate whether HPG-axis hormone concentrations co-fluctuate with alterations in white matter (WM) microstructure, cortical thickness (CT), and brain volume. Across the whole brain, 17β-estradiol and luteinizing hormone (LH) concentrations were directly proportional to diffusion anisotropy (μFA; 17β-estradiol: β1 = 0.145, highest density interval (HDI) = [0.211, 0.4]; LH: β1 = 0.111, HDI = [0.157, 0.364]), while follicle-stimulating hormone (FSH) was directly proportional to CT (β1 = 0 .162, HDI = [0.115, 0.678]). Within several individual regions, FSH and progesterone demonstrated opposing relationships with mean diffusivity (Diso) and CT. These regions mainly reside within the temporal and occipital lobes, with functional implications for the limbic and visual systems. Finally, progesterone was associated with increased tissue (β1 = 0.66, HDI = [0.607, 15.845]) and decreased cerebrospinal fluid (CSF; β1 = -0.749, HDI = [-11.604, -0.903]) volumes, with total brain volume remaining unchanged. These results are the first to report simultaneous brain-wide changes in human WM microstructure and CT coinciding with menstrual cycle-driven hormone rhythms. Effects were observed in both classically known HPG-axis receptor-dense regions (medial temporal lobe, prefrontal cortex) and in other regions located across frontal, occipital, temporal, and parietal lobes. Our results suggest that HPG-axis hormone fluctuations may have significant structural impacts across the entire brain.

Neurocognitive aging researchers are increasingly focused on the locus coeruleus, a neuromodulatory brainstem structure that degrades with age. With this rapid growth, the field will benefit from consensus regarding which magnetic resonance imaging (MRI) metrics of locus coeruleus structure are most sensitive to age and cognition. To address this need, the current study acquired magnetization transfer- and diffusion-weighted MRI images in younger and older adults who also completed a free recall memory task. Results revealed significantly larger differences between younger and older adults for maximum than average magnetization transfer-weighted contrast (MTC), axial than mean or radial single-tensor diffusivity (DTI), and free than restricted multi-compartment diffusion (NODDI) metrics in the locus coeruleus; with maximum MTC being the best predictor of age group. Age effects for all imaging modalities interacted with sex, with larger age group differences in males than females for MTC and NODDI metrics. Age group differences also varied across locus coeruleus subdivision for DTI and NODDI metrics, and across locus coeruleus hemispheres for MTC. Within older adults, however, there were no significant effects of age on MTC or DTI metrics, only an interaction between age and sex for free diffusion. Finally, independent of age and sex, higher restricted diffusion in the locus coeruleus was significantly related to better (lower) recall variability, but not mean recall. Whereas MTC has been widely used in the literature, our comparison between the average and maximum MTC metrics, inclusion of DTI and NODDI metrics, and breakdowns by locus coeruleus subdivision and hemisphere make important and novel contributions to our understanding of the aging of locus coeruleus structure.

The short association fibers or U-fibers travel in the superficial white matter (SWM) beneath the cortical layer. While the U-fibers play a crucial role in various brain disorders, there is a lack of effective tools to reconstruct their highly curved trajectory from diffusion MRI (dMRI). In this work, we propose a novel surface-based framework for the probabilistic tracking of fibers on the triangular mesh representation of the SWM. By deriving a closed-form solution to transform the spherical harmonics (SPHARM) coefficients of 3D fiber orientation distributions (FODs) to local coordinate systems on each triangle, we develop a novel approach to project the FODs onto the tangent space of the SWM. After that, we utilize parallel transport to realize the intrinsic propagation of streamlines on SWM following probabilistically sampled fiber directions. Our intrinsic and surface-based method eliminates the need to perform the necessary but challenging sharp turns in 3D compared with conventional volume-based tractography methods. Using data from the Human Connectome Project (HCP), we performed quantitative comparisons to demonstrate the proposed algorithm can more effectively reconstruct the U-fibers connecting the precentral and postcentral gyrus than previous methods. Quantitative validations were then performed on post-mortem MRIs to show the reconstructed U-fibers from our method more faithfully follow the SWM than volume-based tractography. Finally, we applied our algorithm to study the parietal U-fiber connectivity changes in autosomal dominant Alzheimers disease (ADAD) patients and successfully detected significant associations between U-fiber connectivity and disease severity.

BACKGROUND: Microvascular dysfunction is involved in the development of various cerebral disorders. It may contribute to these disorders by disrupting white matter tracts and altering brain connectivity, but evidence is scarce. We investigated the association between multiple biomarkers of microvascular function and whole-brain white matter connectivity. METHODS AND RESULTS: Cross-sectional data from The Maastricht Study, a Dutch population-based cohort (n=4326; age, 59.4±8.6 years; 49.7% women). Measures of microvascular function included urinary albumin excretion, central retinal arteriolar and venular calibers, composite scores of flicker light-induced retinal arteriolar and venular dilation, and plasma biomarkers of endothelial dysfunction (intercellular adhesion molecule-1, vascular cell adhesion molecule-1, E-selectin, and von Willebrand factor). White matter connectivity was calculated from 3T diffusion magnetic resonance imaging to quantify the number (average node degree) and organization (characteristic path length, global efficiency, clustering coefficient, and local efficiency) of white matter connections. A higher plasma biomarkers of endothelial dysfunction composite score was associated with a longer characteristic path length (β per SD, 0.066 [95% CI, 0.017-0.114]) after adjustment for sociodemographic, lifestyle, and cardiovascular factors but not with any of the other white matter connectivity measures. After multiple comparison correction, this association was nonsignificant. None of the other microvascular function measures were associated with any of the connectivity measures. CONCLUSIONS: These findings suggest that microvascular dysfunction as measured by indirect markers is not associated with whole-brain white matter connectivity.

Diffusion MRI (dMRI) can be used to probe microstructural properties of brain tissue and holds great promise as a means to non-invasively map Alzheimer's disease (AD) pathology. Few studies have evaluated multi-shell dMRI models such as neurite orientation dispersion and density imaging (NODDI) and mean apparent propagator (MAP)-MRI in cortical gray matter where many of the earliest histopathological changes occur in AD. Here, we investigated the relationship between CSF pTau181 and Aβ1-42 burden and regional cortical NODDI and MAP-MRI indices in 46 cognitively unimpaired individuals, 18 with mild cognitive impairment, and two with dementia (mean age: 71.8 ± 6.2 years) from the Alzheimer's Disease Neuroimaging Initiative. We compared findings to more conventional cortical thickness measures. Lower CSF Aβ1-42 and higher pTau181 were associated with cortical dMRI measures reflecting less hindered or restricted diffusion and greater diffusivity. Cortical dMRI measures, but not cortical thickness measures, were more widely associated with Aβ1-42 than pTau181 and better distinguished Aβ+ from Aβ- participants than pTau+ from pTau- participants. dMRI associations mediated the relationship between CSF markers and delayed logical memory performance, commonly impaired in early AD. dMRI metrics sensitive to early AD pathogenesis and microstructural damage may be better measures of subtle neurodegeneration in comparison to standard cortical thickness and help to elucidate mechanisms underlying cognitive decline.

BACKGROUND: Sensory processing dysfunction (SPD) is linked to altered white matter (WM) microstructure in school-age children. Sensory over-responsivity (SOR), a form of SPD, affects at least 2.5% of all children and has substantial deleterious impact on learning and mental health. However, SOR has not been well studied using microstructural imaging such as diffusion MRI (dMRI). Since SOR involves hypersensitivity to external stimuli, we test the hypothesis that children with SOR require compensatory neuroplasticity in the form of superior WM microstructural integrity to protect against internalizing behavior, leaving those with impaired WM microstructure vulnerable to somatization and depression. METHODS: Children ages 8-12 years old with neurodevelopmental concerns were assessed for SOR using a comprehensive structured clinical evaluation, the Sensory Processing 3 Dimensions Assessment, and underwent 3 Tesla MRI with multishell multiband dMRI. Tract-based spatial statistics was used to measure diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) metrics from global WM and nineteen selected WM tracts. Correlations of DTI and NODDI measures with measures of somatization and emotional disturbance from the Behavioral Assessment System for Children, 3rd edition (BASC-3), were computed in the SOR group and in matched children with neurodevelopmental concerns but not SOR. RESULTS: Global WM fractional anisotropy (FA) is negatively correlated with somatization and with emotional disturbance in the SOR group but not the non-SOR group. Also observed in children with SOR are positive correlations of radial diffusivity (RD) and free water fraction (FISO) with somatization and, in most cases, emotional disturbance. These effects are significant in boys with SOR, whereas the study is underpowered for girls. The most affected white matter are medial lemniscus and internal capsule sensory tracts, although effects of SOR are observed in many cerebral, cerebellar, and brainstem tracts. CONCLUSION: White matter microstructure is related to affective behavior in children with SOR.

BackgroundHigh b-value diffusion-weighted images (DWI) are used for detection of clinically significant prostate cancer (csPCa). This study qualitatively and quantitatively compares synthesized DWI (sDWI) to acquired (aDWI) for detection of csPCa.MethodsOne hundred fifty-one consecutive patients who underwent prostate MRI and biopsy were included in the study. Axial DWI with b = 0, 500, 1000, and 2000 s/mm2 using a 3T clinical scanner using a 32-channel phased-array body coil were acquired. We retrospectively synthesized DWI for b = 2000 s/mm2 via extrapolation based on mono-exponential decay, using b = 0 and b = 500 s/mm2 (sDWI500) and b = 0, b = 500 s/mm2, and b = 1000 s/mm2 (sDWI1000). Differences in signal intensity between sDWI and aDWI were evaluated within different regions of interest (prostate alone, prostate plus 5 mm, 30 mm and 70 mm margin and full field of view). The maximum DWI value within each ROI was evaluated for prediction of csPCa. Classification accuracy was compared to Restriction Spectrum Imaging restriction score (RSIrs), a previously validated biomarker based on multi-exponential DWI. Discrimination of csPCa was evaluated via area under the receiver operating characteristic curve (AUC).ResultsWithin the prostate, mean ± standard deviation of percent mean differences between sDWI and aDWI signal were -46 ± 35% for sDWI1000 and -67 ± 24% for sDWI500. AUC for aDWI, sDWI500, sDWI1000, and RSIrs within the prostate 0.62[95% confidence interval: 0.53, 0.71], 0.63[0.54, 0.72], 0.65[0.56, 0.73] and 0.78[0.71, 0.86], respectively.ConclusionsDWI is qualitatively comparable to aDWI within the prostate. However, hyperintense artifacts are introduced with sDWI in the surrounding pelvic tissue that interfere with quantitative cancer detection and might mask metastases. In the prostate, RSIrs yields superior quantitative csPCa detection than sDWI or aDWI.

Military veterans with posttraumatic stress disorder (PTSD) commonly experience posttraumatic guilt. Guilt over commission or omission evolves when responsibility is assumed for an unfortunate outcome (e.g., the death of a fellow combatant). Survivor guilt is a state of intense emotional distress experienced by the weight of knowing that one survived while others did not. This study of the Translational Research Center for TBI and Stress Disorders (TRACTS) analyzed structural and diffusion-weighted magnetic resonance imaging data from 132 male Iraq/Afghanistan veterans with PTSD. The Clinician-Administered PTSD Scale for DSM-IV (CAPS-IV) was employed to classify guilt. Thirty (22.7 %) veterans experienced guilt over acts of commission or omission, 34 (25.8 %) experienced survivor guilt, and 68 (51.5 %) had no posttraumatic guilt. White matter microstructure (fractional anisotropy, FA), cortical thickness, and cortical volume were compared between veterans with guilt over acts of commission or omission, veterans with survivor guilt, and veterans without guilt. Veterans with survivor guilt had significantly lower white matter FA compared to veterans who did not experience guilt (p <.001), affecting several regions of major white matter fiber bundles. There were no significant differences in white matter FA, cortical thickness, or volumes between veterans with guilt over acts of commission or omission and veterans without guilt (p >.050). This cross-sectional study with exclusively male veterans precludes inferences of causality between the studied variables and generalizability to the larger veteran population that includes women. Survivor guilt may be a particularly impactful form of posttraumatic guilt that requires specific treatment efforts targeting brain health. • Posttraumatic guilt is highly common among veterans with PTSD. • Survivor guilt is linked to altered white matter in veterans, potentially impacting moral cognition. • Lower FA in survivor guilt in key brain fiber tracts suggests impaired tissue organization. • Findings highlight the need for comprehensive assessment and intervention for veteran survivor guilt. [ABSTRACT FROM AUTHOR]

The zona incerta (ZI) is a subcortical structure primarily investigated in rodents that is implicated in various behaviors, ranging from motor control to survival-associated activities, partly due to its integration in multiple neural circuits. In the current study, we used diffusion magnetic resonance imaging tractography to segment the ZI and gain insight into its connectivity in various circuits in humans. We performed probabilistic tractography in 7T diffusion MRI on 178 participants from the Human Connectome Project to validate the ZI's anatomical subdivisions and their respective tracts. K-means clustering segmented the ZI based on each voxel's connectivity profile. We further characterized the connections of each ZI subregion using probabilistic tractography with each subregion as a seed. We identified 2 dominant clusters that delineated the whole ZI into rostral and caudal subregions. The caudal ZI primarily connected with motor regions, while the rostral ZI received a topographic distribution of projections from prefrontal areas, notably the anterior cingulate and medial prefrontal cortices. We generated a probabilistic ZI atlas that was registered to a patient-participant's magnetic resonance imaging scan for placement of stereoencephalographic leads for electrophysiology-guided deep brain stimulation to treat their obsessive-compulsive disorder. Rostral ZI stimulation improved the patient's core symptoms (mean improvement 21%). We present a tractography-based atlas of the rostral and caudal ZI subregions constructed using high-resolution diffusion magnetic resonance imaging from 178 healthy participants. Our work provides an anatomical foundation to explore the rostral ZI as a novel target for deep brain stimulation to treat refractory obsessive-compulsive disorder and other disorders associated with dysfunctional reward circuitry. [ABSTRACT FROM AUTHOR]

Stroke, the second leading cause of mortality globally, predominantly results from ischemic conditions. Immediate attention and diagnosis, related to the characterization of brain lesions, play a crucial role in patient prognosis. Standard stroke protocols include an initial evaluation from a non-contrast CT to discriminate between hemorrhage and ischemia. However, non-contrast CTs lack sensitivity in detecting subtle ischemic changes in this phase. Alternatively, diffusion-weighted MRI studies provide enhanced capabilities, yet are constrained by limited availability and higher costs. Hence, we idealize new approaches that integrate ADC stroke lesion findings into CT, to enhance the analysis and accelerate stroke patient management. This study details a public challenge where scientists applied top computational strategies to delineate stroke lesions on CT scans, utilizing paired ADC information. Also, it constitutes the first effort to build a paired dataset with NCCT and ADC studies of acute ischemic stroke patients. Submitted algorithms were validated with respect to the references of two expert radiologists. The best achieved Dice score was 0.2 over a test study with 36 patient studies. Despite all the teams employing specialized deep learning tools, results reveal limitations of computational approaches to support the segmentation of small lesions with heterogeneous density. [ABSTRACT FROM AUTHOR]

This study focuses on predicting the prognosis of acute ischemic stroke patients with focal neurologic symptoms using a combination of diffusion-weighted magnetic resonance imaging (DWI) and clinical information. The primary outcome is a poor functional outcome defined by a modified Rankin Scale (mRS) score of 3–6 after 3 months of stroke. Employing nnUnet for DWI lesion segmentation, the study utilizes both multi-task and multi-modality methodologies, integrating DWI and clinical data for prognosis prediction. Integrating the two modalities was shown to improve performance by 0.04 compared to using DWI only. The model achieves notable performance metrics, with a dice score of 0.7375 for lesion segmentation and an area under the curve of 0.8080 for mRS prediction. These results surpass existing scoring systems, showing a 0.16 improvement over the Totaled Health Risks in Vascular Events score. The study further employs grad-class activation maps to identify critical brain regions influencing mRS scores. Analysis of the feature map reveals the efficacy of the multi-tasking nnUnet in predicting poor outcomes, providing insights into the interplay between DWI and clinical data. In conclusion, the integrated approach demonstrates significant advancements in prognosis prediction for cerebral infarction patients, offering a superior alternative to current scoring systems. [ABSTRACT FROM AUTHOR]

Background: Neuronal intranuclear inclusion disease (NIID) is a rare neurodegenerative disease caused by the expansion of GGC repeats in the 5′-untranslated region (5′-UTR) of NOTCH2NLC. Although increasing evidence suggests that NIID affects various organs, its association with renal involvement remains unclear. We studied the genetic background of a family with NIID, in which four of five members presented with proteinuria as the initial manifestation. The renal pathology of three patients was diagnosed as focal segmental glomerulosclerosis (FSGS) at a previous hospital. These patients also presented with tremors, retinal degeneration, and episodic neurological events. Finally, one patient exhibited reversible bilateral thalamic high-intensity signal changes on diffusion-weighted imaging during episodic neurological events. Methods: Exome sequencing (ES) and nanopore long-read whole-genome sequencing (LR-WGS) were performed on the index case, followed by nanopore target sequencing using Cas9-mediated PCR-free enrichment and methylation analysis. Results: ES revealed no candidate variants; however, nanopore LR-WGS in the index case revealed expansion of short tandem repeats (STR) in NOTCH2NLC. Subsequent nanopore target sequencing using Cas9-mediated PCR-free enrichment showed STR expansion of NOTCH2NLC in an affected sibling and asymptomatic father. Methylation analysis using nanopore data revealed hypermethylation of the expanded allele in the asymptomatic father and partial hypermethylation in a mildly symptomatic sibling, whereas the expanded allele was hypomethylated in the index case. Conclusions: This investigation expands the clinical spectrum of NIID, suggesting that STR expansion of NOTCH2NLC is a cause of renal diseases, including FSGS. [ABSTRACT FROM AUTHOR]

The aim of this prospective, observational cohort study was to investigate and assess diverse neuroimaging biomarkers to predict patients' neurological recovery after coma. 32 patients (18–76 years, M = 44.8, SD = 17.7) with disorders of consciousness participated in the study. Multimodal neuroimaging data acquired during the patient's hospitalization were used to derive cortical glucose metabolism (18F-fluorodeoxyglucose positron emission tomography/computed tomography), and structural (diffusion-weighted imaging) and functional connectivity (resting-state functional MRI) indices. The recovery outcome was defined as a continuous composite score constructed from a multivariate neurobehavioral recovery assessment administered upon the discharge from the hospital. Fractional anisotropy-based white matter integrity in the anterior forebrain mesocircuit (r = 0.72, p <.001, 95% CI: 0.87, 0.45), and the functional connectivity between the antagonistic default mode and dorsal attention resting-state networks (r = − 0.74, p < 0.001, 95% CI: − 0.46, − 0.88) strongly correlated with the recovery outcome. The association between the posterior glucose metabolism and the recovery outcome was moderate (r = 0.38, p = 0.040, 95% CI: 0.66, 0.02). Structural (adjusted R2 = 0.84, p = 0.003) or functional connectivity biomarker (adjusted R2 = 0.85, p = 0.001), but not their combination, significantly improved the model fit to predict the recovery compared solely to bedside neurobehavioral evaluation (adjusted R2 = 0.75). The present study elucidates an important role of specific MRI-derived structural and functional connectivity biomarkers in diagnosis and prognosis of recovery after coma and has implications for clinical care of patients with severe brain injury. [ABSTRACT FROM AUTHOR]

Purpose: To compare performance of whole-body [68Ga]Ga-FAPI-04 and [18F]FDG PET imaging in the detection of Krukenberg tumors (KTs), primary site and extra-ovarian metastases of gastric signet-ring-cell carcinoma (GSRCC), and evaluate the value of [68Ga]Ga-FAPI-04 PET/MR imaging strategy and its potential impact on the management of KTs from GSRCC. Methods: Twelve patients with twenty-three KTs from GSRCC, who underwent both [68Ga]Ga-FAPI-04 pelvic PET/MR and whole-body [68Ga]Ga-FAPI-04 and [18F]FDG PET imaging were retrospectively analyzed. [68Ga]Ga-FAPI-04 and [18F]FDG uptakes were compared by using Wilcoxon signed-rank test or paired t test. McNemar's test was used to compare lesion detectability between two modalities. Two-tailed P<0.05 was considered statistically significant. Immunohistochemistry staining was utilized to analyze the fibroblast activation protein (FAP) expression in KTs. Results: A total of 12 patients with 23 KTs from GSRCC (8 synchronous and 4 metachronous) were evaluated. [68Ga]Ga-FAPI-04 was superior to [18F]FDG PET in detecting primary sites of GSRCC (100% [11/11] vs. 18.2% [2/11], p = 0.002), involved lymph nodes (90.9% [10/11] vs. 54.5% [6/11], p = 0.046) and peritoneal metastases (100% [12/12] vs. 41.7% [5/12], p = 0.008), with higher SUVmax and TBR (all p < 0.005). Both tracers had limited value in identifying KTs, with 100% false negative rate on [68Ga]Ga-FAPI-04 PET and a low detection rate of 8.7% on [18F]FDG PET. Fap immunohistochemistry showed negative or slight FAP expression in neoplastic signet ring cells and ovarian stroma. [68Ga]Ga-FAPI-04 PET/MR imaging strategy greatly improved the detection rate of Krukenberg tumors (87%, 20/23). After adding diffusion-weighted imaging (DWI), the detection rate was further improved (87.5% vs. 100%, p = 0.083). [68Ga]Ga-FAPI-04 PET/MR imaging strategy either upgraded TNM staging or changed treatment management in twelve patients. Conclusions: [68Ga]Ga-FAPI-04 PET outperformed [18F]FDG PET in detecting primary site and most extra-ovarian metastases of GSRCC, but both tracers had limited value in identifying Krukenberg tumors. Pelvis MRI should be applied to compensate the limitation of [68Ga]Ga-FAPI-04 PET imaging to identify Krukenberg tumours. The [68Ga]Ga-FAPI-04 PET/MR imaging strategy has the potential to impact treatment decisions for GSRCC patients with KTs. [ABSTRACT FROM AUTHOR]

This document is a collection of abstracts from the Journal of Neonatal - Perinatal Medicine. The abstracts cover various topics related to neonatal neurodevelopment and brain abnormalities in preterm infants. One study focuses on the use of MRI in predicting long-term outcomes in infants with Hypoxic Ischemic Encephalopathy. Another study explores the prediction of post-hemorrhagic ventricular dilatation in preterm infants with intraventricular hemorrhage. A third study examines the impact of cerebellar hemorrhage on the neurodevelopmental outcomes of extremely preterm infants. The fourth abstract compares the utility of early and late MRI in evaluating infants with Neonatal Encephalopathy. Additionally, there is a study investigating the impact of SARS-CoV-2 infection during pregnancy on neonatal neurological outcomes. Lastly, a study explores the hemodynamic responses associated with spontaneous neural activity in the early developing brain. These abstracts provide valuable insights into neonatal neurodevelopment and brain abnormalities in preterm infants. [Extracted from the article]

Behavioral differences between men and women have been studied extensively, as have differences in brain anatomy. However, most studies have focused on differences in gray matter, while white matter has been much less studied. We conducted a comprehensive study of 77 deep white matter tracts to analyze their volumetric and microstructural variability between men and women in the full Human Connectome Project (HCP) cohort of 1065 healthy individuals aged 22–35 years. We found a significant difference in total brain volume between men and women (+ 12.6% in men), consistent with the literature. 16 tracts showed significant volumetric differences between men and women, one of which stood out due to a larger effect size: the corpus callosum genu, which was larger in women (+ 7.3% in women, p = 5.76 × 10–19). In addition, we found several differences in microstructural parameters between men and women, both using standard Diffusion Tensor Imaging (DTI) parameters and more complex microstructural parameters from the Neurite Orientation Dispersion and Density Imaging (NODDI) model, with the tracts showing the greatest differences belonging to motor (cortico-spinal tracts, cortico-cerebellar tracts) or limbic (cingulum, fornix, thalamo-temporal radiations) systems. These microstructural differences may be related to known behavioral differences between the sexes in timed motor performance, aggressiveness/impulsivity, and social cognition. [ABSTRACT FROM AUTHOR]

Attention is a heterogeneous function theoretically divided into different systems. While functional magnetic resonance imaging (fMRI) has extensively characterized their functioning, the role of white matter in cognitive function has gained recent interest due to diffusion-weighted imaging advancements. However, most evidence relies on correlations between white matter properties and behavioral or cognitive measures. This study used a new method that combines the signal from distant voxels of fMRI images using the probability of structural connection given by high-resolution normative tractography. We analyzed three fMRI datasets with a visual perceptual task and three attentional manipulations: phasic alerting, spatial orienting, and executive attention. The phasic alerting network engaged temporal areas and their communication with frontal and parietal regions, with left hemisphere dominance. The orienting network involved bilateral fronto-parietal and midline regions communicating by association tracts and interhemispheric fibers. The executive attention network engaged a broad set of brain regions and white matter tracts connecting them, with a particular involvement of frontal areas and their connections with the rest of the brain. These results partially confirm and extend previous knowledge on the neural substrates of the attentional system, offering a more comprehensive understanding through the integration of structure and function. [ABSTRACT FROM AUTHOR]

Introduction MRI represents one of the clinical tools at the forefront of research efforts aimed at identifying diagnostic and prognostic biomarkers following traumatic brain injury (TBI). Both volumetric and diffusion MRI findings in mild TBI (mTBI) are mixed, making the findings difficult to interpret. As such, additional research is needed to continue to elucidate the relationship between the clinical features of mTBI and quantitative MRI measurements. Material and Methods Volumetric and diffusion imaging data in a sample of 976 veterans and service members from the Chronic Effects of Neurotrauma Consortium and now the Long-Term Impact of Military-Relevant Brain Injury Consortium observational study of the late effects of mTBI in combat with and without a history of mTBI were examined. A series of regression models with link functions appropriate for the model outcome were used to evaluate the relationships among imaging measures and clinical features of mTBI. Each model included acquisition site, participant sex, and age as covariates. Separate regression models were fit for each region of interest where said region was a predictor. Results After controlling for multiple comparisons, no significant main effect was noted for comparisons between veterans and service members with and without a history of mTBI. However, blast-related mTBI were associated with volumetric reductions of several subregions of the corpus callosum compared to non–blast-related mTBI. Several volumetric (i.e. hippocampal subfields, etc.) and diffusion (i.e. corona radiata, superior longitudinal fasciculus, etc.) MRI findings were noted to be associated with an increased number of repetitive mTBIs versus. Conclusions In deployment-related mTBI, significant findings in this cohort were only observed when considering mTBI sub-groups (blast mechanism and total number/dose). Simply comparing healthy controls and those with a positive mTBI history is likely an oversimplification that may lead to non-significant findings, even in consortium analyses. [ABSTRACT FROM AUTHOR]

To evaluate the diagnostic performance of diffusion-weighted imaging (DWI) in the 6-month interval post chemoradiation therapy (CRT) in determining persistent disease and whether persistent diffusion restriction on DWI at 6 months is associated with overall survival; and secondarily, to investigate the accuracy of pelvic lymph node assessment on T2-weighted imaging and DWI in the 6-month interval post CRT, in patients with squamous cell carcinoma of the anus. This retrospective study included patients with squamous cell carcinoma of the anus who underwent CRT followed by restaging rectal MRI from January 2010 to April 2020, with ≥1 year of follow-up after CRT. DW images were qualitatively evaluated by 2 junior and 2 senior abdominal radiologists to determine anal persistent disease. The reference standard for anal persistent disease was digital rectal examination/endoscopy and histopathology. Diagnostic performance was estimated using sensitivity, specificity, negative predictive value, and positive predictive value. Survival outcomes were evaluated via Kaplan-Meier analysis, and associations between survival outcomes and DWI status were tested for significance using the log-rank test. Additionally, DW and T2-weighted images were evaluated to determine lymph node status. Among 84 patients (mean age, 63 ± 10.2 years; 64/84 [76%] female), 14 of 84 (17%) had confirmed persistent disease. Interreader agreement on DWI between all 4 radiologists was moderate (Light's κ = 0.553). Overall, DWI had a sensitivity of 71.4%, specificity of 72.1%, positive predictive value of 34.5%, and negative predictive value of 92.5%. Patients with a negative DWI showed better survival than patients with a positive DWI (3-year overall survival of 92% vs 79% and 5-year overall survival of 87% vs 74%), although the difference did not reach statistical significance (P =.063). All patients with suspicious lymph nodes (14/14, 100%) showed negative pathology or decreased size during follow-up. At 6 months post CRT, DWI showed value in excluding anal persistent disease. Persistent diffusion restriction on DWI was not significantly associated with overall survival. Pelvic nodal assessment on DWI and T2-weighted imaging was limited in predicting persistent nodal metastases. [ABSTRACT FROM AUTHOR]

Background: Wernicke's encephalopathy (WE) is an acute neurological syndrome resulting from thiamine (vitamin B1) deficiency. It has been recognized increasingly in non-alcoholic patients, such as in the condition of malnutrition. Recent literature has shed light on uncommon symptoms and neuroimaging findings. Case report: We reported a case of a 44-year-old male who initially presented with bilateral hearing loss, and exhibited abnormality in the splenium of the corpus callosum on magnetic resonance imaging (MRI) diffusion-weighted imaging sequence. On the following day the patient developed new symptoms, including unstable walking, double vision and hallucination. The subsequent brain MRI demonstrated lesions involving periaqueductal grey matter and bilateral medial thalamus, indicating the diagnosis of WE. Empirical treatment with intravenous thiamine resulted in complete clinical and radiological resolution. Conclusion: To the best of our knowledge, the current case is the first report of WE in literature with uncommon but reversible manifestations. This case warns us to maintain a heightened level of suspicion for WE in malnourished patients with neurological deficits, despite the possibility of atypical presentations encompassing bilateral hearing disturbances and unusual neuroradiological results. Early diagnosis and timely administration of thiamine in WE are likely to lead to a favorable outcome and full recovery. [ABSTRACT FROM AUTHOR]

Objectives: Neuronal intranuclear inclusion disease (NIID) exhibited significant clinical heterogeneities. However, the clinical features, radiographic changes, and prognosis of patients with encephalitis-like NIID have yet to be systematically elucidated. Methods: Clinical data including medical history, physical examination, and laboratory examinations were collected and analyzed. Skin and sural nerve biopsies were conducted on the patient. Repeat-primed PCR (RP-PCR) and fluorescence amplicon length PCR (AL-PCR) were used to detect the expansion of CGG repeat. We also reviewed the clinical and genetic data of NIID patients with cortical enhancement. Results: A 54-year-old woman presented with encephalitis-like NIID, characterized by severe headache and agitative psychiatric symptoms. The brain MRI showed cortical swelling in the temporo-occipital lobes and significant enhancement of the cortical surface and dura, but without hyperintensities along the corticomedullary junction on diffusion-weighted image (DWI). A biopsy of the sural nerve revealed a demyelinating pathological change. The intranuclear inclusions were detected in nerve and skin tissues using the p62 antibody and electron microscopy. RP-PCR and AL-PCR unveiled the pathogenic expansion of CGG repeats in the NOTCH2NLC gene. A review of the literature indicated that nine out of the 16 patients with cortical lesions and linear enhancement exhibited encephalitis-like NIID. Conclusion: This study indicated that patients with encephalitis-like NIID typically exhibited headache and excitatory psychiatric symptoms, often accompanied by cortical edema and enhancement of posterior lobes, and responded well to glucocorticoid treatment. Furthermore, some patients may not exhibit hyperintensities along the corticomedullary junction on DWI, potentially leading to misdiagnosis. [ABSTRACT FROM AUTHOR]

Purpose: Complete androgen insensitivity syndrome (CAIS) and Mayer-Rokitansky-Küster-Hauser syndrome (MRKHS) share common clinical features such as female phenotype, vaginal hypoplasia, and primary amenorrhea. Magnetic resonance imaging (MRI) is performed to investigate the cause of primary amenorrhea. However, the MRI features are also similar in both disorders. They are ultimately diagnosed by chromosome testing, but there is a possibility of misdiagnosis if chromosome testing is not performed. This study aimed to identify MRI features that are useful for differentiating CAIS from MRKHS. Method: This multicenter retrospective study included 12 patients with CAIS and 19 patients with MRKHS. Three radiologists blindly evaluated the following features: (1) detection of vagina, (2) detection of nodular and cystic structures in the lateral pelvis; undescended testicles and paratesticular cysts in CAIS and rudimentary uteri and ovaries in MRKHS, (3) their location, (4) number of cysts in the cystic structures, and (5) signal intensity on diffusion-weighted images (DWI) and apparent diffusion coefficient (ADC) values of the nodular structures. Statistical comparisons were performed using Mann–Whitney U and Fisher's exact tests. Results: Compared with MRKHS, the CAIS group showed significantly detectable vagina, more ventrally located nodular and cystic structures, fewer cysts within the cystic structures, and nodular structures with higher signal intensity on DWI and lower ADC values. Conclusions: MRI features of detectable vagina, location of nodular and cystic structures, number of cysts within the cystic structures, signal intensity on DWI and ADC values of the nodular structures were useful in differentiating CAIS from MRKHS. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to assess the predictive efficacy of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in parametrial invasion (PMI) in cervical cancer patients. Methods: A total of 83 cervical cancer patients (32 PMI-positive and 51 PMI-negative) retrospectively underwent pretreatment IVIM-DWI and DCE-MRI scans. IVIM-DWI parameters included apparent diffusion coefficient (ADC), slow apparent diffusion coefficient (D), fast apparent diffusion coefficient (D*), and perfusion fraction (f). DCE-MRI parameters included volume transfer constant (Ktrans), flux rate constant (Kep), and fractional extravascular extracellular space volume (Ve). Logistic regression analyses were conducted to identify independent variables associated with PMI. Receiver operating characteristic curves were generated to assess the predictive performance of significant parameters. Results: Multivariable analysis revealed that the MRI parameters D (odds ratio [OR]: 7.05; 95% CI 1.78–27.88; P = 0.005), D* (OR 6.58; 95% CI 1.49–29.10; P = 0.01), f (OR 5.12; 95% CI 1.23–21.37; P = 0.03), Ktrans (OR 4.60; 95% CI 1.19–17.81; P = 0.03), and Kep (OR 4.90; 95% CI 1.25–19.18; P = 0.02) were independent predictors of PMI in cervical cancer patients. The combined parameter incorporating these parameters demonstrated the highest performance in predicting PMI, yielding an area under the curve of 0.906, sensitivity of 84.4%, and specificity of 86.3%. Conclusion: The proposed combined parameter exhibited favorable performance in identifying PMI in cervical cancer patients. [ABSTRACT FROM AUTHOR]

Accurately studying structural connectivity requires precise tract segmentation strategies. The U-Net network has been widely recognized for its exceptional capacity in image segmentation tasks and provides remarkable results in large tract segmentation when high-quality diffusion-weighted imaging (DWI) data are used. However, short tracts, which are associated with various neurological diseases, pose specific challenges, particularly when high-quality DWI data acquisition within clinical settings is concerned. Here, we aimed to evaluate the U-Net network ability to segment short tracts by using DWI data acquired in different experimental conditions. To this end, we conducted three types of training experiments involving 350 healthy subjects and 11 white matter tracts, including the anterior, posterior, and hippocampal commissure, fornix, and uncinated fasciculus. In the first experiment, the model was exclusively trained with high-quality data of the Human Connectome Project (HCP) dataset. The second experiment focused on images of healthy subjects acquired from a local hospital dataset, representing a typical clinical routine acquisition. In the third experiment, a hybrid training approach was employed, combining data of the HCP and local hospital datasets. Then, the best model was also tested in unseen DWIs of 10 epilepsy patients of the local hospital and 10 healthy subjects acquired on a scanner from another company. The outcomes of the third experiment demonstrated a notable enhancement in performance when contrasted with the preceding trials. Specifically, the short tracts within the local hospital dataset achieved Dice scores ranging between 0.60 and 0.65. Similar intervals were obtained with HCP data in the first experiment, and a substantial improvement compared to the scores between 0.37 and 0.50 obtained with the local hospital dataset at the same experiment. This improvement persisted when the method was applied to diverse scenarios, including different scanner acquisitions and epilepsy patients. These results indicate that combining datasets from different sources, coupled with resolution standardization strengthens the neural network ability to generalize predictions across a spectrum of datasets. Nevertheless, short tract segmentation performance is intricately linked to the training composition, to validation, and to testing data. Moreover, curved tracts have intricate structural nature, which adds complexities to their segmenting. Although the network training approach tested herein has provided promising results, caution must be taken when extrapolating its application to datasets acquired under distinct experimental conditions, even in the case of higher-quality data or analysis of long or short tracts. • To study structural connectivity, precise tract segmentation is crucial. • U-Net network is recognized for its exceptional capacity for image segmentation. • High-quality DWI data is a challenge for clinical image acquisitions. • Short tracts pose a greater challenge for neural networks to accurately predict. • Effectiveness of automatic segmentation on clinical images. [ABSTRACT FROM AUTHOR]

To assess whether diffusion-weighted imaging (DWI) with Compressed SENSE (CS) and deep learning (DL-CS-DWI) can improve image quality and lesion detection in patients at risk for hepatocellular carcinoma (HCC). This single-center prospective study enrolled consecutive at-risk participants who underwent 3.0 T gadoxetate disodium-enhanced MRI. Conventional DWI was acquired using parallel imaging (PI) with SENSE (PI-DWI). In CS-DWI and DL-CS-DWI, CS but not PI with SENSE was used to accelerate the scan with 2.5 as the acceleration factor. Qualitative and quantitative image quality were independently assessed by two masked reviewers, and were compared using the Wilcoxon signed-rank test. The detection rates of clinically-relevant (LR-4/5/M based on the Liver Imaging Reporting and Data System v2018) liver lesions for each DWI sequence were independently evaluated by another two masked reviewers against their consensus assessments based on all available non-DWI sequences, and were compared by the McNemar test. 67 participants (median age, 58.0 years; 56 males) with 197 clinically-relevant liver lesions were enrolled. Among the three DWI sequences, DL-CS-DWI showed the best qualitative and quantitative image qualities (p range, <0.001–0.039). For clinically-relevant liver lesions, the detection rates (91.4%–93.4%) of DL-CS-DWI showed no difference with CS-DWI (87.3%–89.8%, p = 0.230–0.231) but were superior to PI-DWI (82.7%–85.8%, p = 0.015–0.025). For lesions located in the hepatic dome, DL-CS-DWI demonstrated the highest detection rates (94.8%–97.4% vs 76.9%–79.5% vs 64.1%–69.2%, p = 0.002–0.045) among the three DWI sequences. In patients at high-risk for HCC, DL-CS-DWI improved image quality and detection for clinically-relevant liver lesions, especially for the hepatic dome. • DWI with CS and DL demonstrated superior image quality compared to CS-DWI and conventional DWI. • DL-CS-DWI improved detection rate for clinically-relevant liver lesions, especially in hepatic dome, compared to CS-DWI and conventional DWI. • Deep learning combined with compressive SENSE could improve the overall performance of liver DWI. [ABSTRACT FROM AUTHOR]

To explore the feasibility of ultra-high b-value diffusion-weighted imaging (ubDWI) in assessment of renal IRI. Thirty-five rabbits were randomized into a control group (n = 7) and a renal IRI group (n = 28). The rabbits in the renal IRI group underwent left renal artery clamping for 60 min. Rabbits underwent axial ubDWI before and at 1, 12, 24, and 48 h after IRI. Apparent diffusion coefficient (ADC st) were calculated from ubDWI with two b-values (b = 0, 1000 s/mm2). Triexponential fits were applied to calculate the pure diffusion coefficients (D), perfusion-related diffusion coefficient (D⁎), and ultra-high ADC (ADC uh). The interobserver reproducibility were evaluated. The repeated measurement analysis of variance and Spearman correlation analysis was used for statistical analysis. The ADC st , D, and ADC uh values showed good reproducibility. The ADC st , D, and D⁎ values of renal Cortex (CO) and outer medulla (OM) significantly decreased after IRI (all P < 0.05). The ADC uh values significantly increased from pre-IRI to 1 h after IRI (P < 0.05) and significantly declined at 24 h and 48 h after IRI (all P < 0.05). ADC uh was strongly positively correlated with AQP-1 in the renal CO and OM (ρ = 0.643, P < 0.001; ρ = 0.662, P < 0.001, respectively). ubDWI can be used to non-invasively evaluate early renal IRI, ADC uh may be adopted to reflect AQP-1 expression. [ABSTRACT FROM AUTHOR]

Diffusion-weighted imaging (DWI) holds promise for image-guided radiotherapy (MRgRT) in prostate cancer. However, challenges persist due to image distortion, artifacts, and apparent diffusion coefficient (ADC) reproducibility issues. This study aimed to assess DWI image quality and ADC reproducibility on both a 1.5 T MR-simulator and a 1.5 T MR-Linac, employing measurements from both an ACR MRI phantom and prostate cancer patients undergoing MRgRT. DW-MRI scans were conducted on 19 patients (mean age = 69 ± 8 years, with 23 MR-visible intra-prostatic lesions) and an ACR MRI phantom using a 1.5 T MR-simulator (b-values = 0, 800, 1400s/mm2) and a 1.5 T MR-Linac (b-values = 50, 500, 800 s/mm2). ADC homogeneity in the phantom was evaluated via 1D profile flatness (FL) in three directions. Image quality was assessed through qualitative 5-point Likert scale ratings and quantitative ADC and signal-to-noise ratio (SNR) measurements. Intra-observer reproducibility of image quality scores was evaluated using ICC(1, 2). Geometric distortion was measured by comparing landmark sizes on the ACR phantom against the ground truth. Mean ADC and reproducibility were assessed using Bland-Altman plots. Both MR-simulator and MR-Linac demonstrated high ADC homogeneity (FL > 87.5% - MR-simulator: 97.23 ± 0.62%, MR-Linac: 94.75 ± 0.62%, p < 0.05) in the phantom. Image quality scores revealed acceptable ratings (≥3) for capsule demarcation, image artifacts, and geometric distortion in patients. However, intra-prostatic lesions were barely discernible in b800 images for both MR-simulator (average score = 2.37 ± 1.33) and MR-Linac (average score = 2.16 ± 1.28). While MR-Linac DWI scans exhibited significantly more severe geometric distortion than MR-simulator scans (p < 0.01), most phantom measurements fell within the image in-plane resolution of 3 mm. Significant differences were noted in MR-simulator ADC (CTV: 1.20 ± 0.14 × 10−3 mm2/s (MR-simulator) vs 1.06 ± 0.10 × 10–3 mm2/s (MR-Linac); GTV: 1.05 ± 0.21 × 10−3 mm2/s vs 0.91 ± 0.16 × 10 mm2/s, all p < 0.05), with a small non-zero bias observed in the Bland-Altman analysis (CTV: 12.3%; GTV: 14.5%). The significantly larger MR-simulator ADC and the small non-zero bias hint at potential systematic differences in ADC values acquired from an MR-simulator and an MR-Linac, both at 1.5 T. Although acceptable ADC homogeneity was noted, caution is warranted in interpreting MR-Linac DWI images due to occasional severe artifacts. Further studies are essential to validate DWI and ADC as reliable imaging markers in prostate cancer MRgRT. [ABSTRACT FROM AUTHOR]

Diffusion MRI (dMRI) is inherently limited by SNR. Scanning at 7 T increases intrinsic SNR but 7 T MRI scans suffer from regions of signal dropout, especially in the temporal lobes and cerebellum. We applied dynamic parallel transmit (pTx) to allow whole-brain 7 T dMRI and compared with circularly polarized (CP) pulses in 6 subjects. Subject-specific 2-spoke dynamic pTx pulses were designed offline for 8 slabs covering the brain. We used vendor-provided B 0 and B 1 + mapping. Spokes positions were set using the Fourier difference approach, and RF coefficients optimized with a Jacobi-matrix high-flip-angle optimizer. Diffusion data were analyzed with FSL. Comparing whole-brain averages for pTx against CP scans: mean flip angle error improved by 15% for excitation (2-spoke-VERSE 15.7° vs CP 18.4°, P = 0.012) and improved by 14% for refocusing (2-spoke-VERSE 39.7° vs CP 46.2°, P = 0.008). Computed spin-echo signal standard deviation improved by 14% (2-spoke-VERSE 0.185 vs 0.214 CP, P = 0.025). Temporal SNR increased by 5.4% (2-spoke-VERSE 8.47 vs CP 8.04, P = 0.004) especially in the inferior temporal lobes. Diffusion fitting uncertainty decreased by 6.2% for first fibers (2-spoke VERSE 0.0655 vs CP 0.0703, P < 0.001) and 1.3% for second fibers (2-spoke VERSE 0.139 vs CP 0.141, P = 0.01). In conclusion, dynamic parallel transmit improves the uniformity of 7 T diffusion-weighted imaging. In future, less restrictive SAR limits for parallel transmit scans are expected to allow further improvements. • We implemented dynamic parallel transmit whole brain diffusion MRI. • Our protocols are based on the Human Connectome Project 7T study. • Parallel transmit improves uniformity of diffusion MRI, especially in temporal lobe. • Fiber fitting performance improves especially at the edges of the brain. • Forthcoming less restrictive SAR limits should further improve uniformity. [ABSTRACT FROM AUTHOR]

Objectives: To compare the performance of spectral CT and diffusion-weighted imaging (DWI) for predicting pathologic response after neoadjuvant chemotherapy (NAC) in locally advanced gastric cancer (LAGC). Materials and methods: This was a retrospective analysis drawn from a prospective dataset. Sixty-five patients who underwent baseline concurrent triple-phase enhanced spectral CT and DWI-MRI and standard NAC plus radical gastrectomy were enrolled, and those with poor images were excluded. The tumor regression grade (TRG) was the reference standard, and patients were classified as responders (TRG 0 + 1) or non-responders (TRG 2 + 3). Quantitative iodine concentration (IC), normalized IC (nIC), and apparent diffusion coefficient (ADC) were measured by placing a freehand region of interest manually on the maximal two-dimensional plane. Their differences between responders and non-responders were compared. The performances of significant parameters were evaluated by the receiver operating characteristic analysis. The correlations between parameters and TRG status were explored through Spearman correlation coefficient test. Kaplan–Meier survival analysis was adopted to analyze their relationship with patient survival. Results: nICDP and ADC were associated with the TRG and yielded comparable performances for predicting TRG categories, with area under the curve (AUC) of 0.674 and 0.673, respectively. Their combination achieved a significantly increased AUC of 0.770 (p ; 0.05) and was associated with patient disease-free survival, with hazard ratio of 2.508 (1.043–6.029). Conclusion: Spectral CT and DWI were equally useful imaging techniques for predicting pathologic response to NAC in LAGC. The combination of nICDP and ADC gained significant incremental benefits and was related to patient disease-free survival. Clinical relevance statement: Spectral CT and DWI-based quantitative measurements are effective markers for predicting the pathologic regression outcomes of locally advanced gastric cancer patients after neoadjuvant chemotherapy. Key Points: • The pathologic tumor regression grade, the standard criteria for treatment response after neoadjuvant chemotherapy in gastric cancer patients, is difficult to predict early. • The quantitative parameters of normalized iodine concentration at delay phase and apparent diffusion coefficients were correlated with pathologic response; their combination demonstrated incremental benefits and was associated with patient disease-free survival. • Spectral CT and DWI are equally useful imaging modalities for predicting tumor regression grade after neoadjuvant chemotherapy in patients with locally advanced gastric cancer. [ABSTRACT FROM AUTHOR]

Background: Increasing attention has been given to the peritumoral region. However, conflicting findings have been reported regarding the relationship between peritumoral region features on MRI and the prognosis of breast cancer. Purpose: To evaluate the relationship between peritumoral region features on MRI and prognosis of breast cancer. Materials and methods: A retrospective meta-analysis of observational studies comparing either qualitative or quantitative assessments of peritumoral MRI features on breast cancer with poor prognosis and control subjects was performed for studies published till October 2022. Pooled odds ratios (ORs) or standardized mean differences and 95% confidence intervals (CIs) were estimated by using random-effects models. The heterogeneity across the studies was measured using the statistic I2. Sensitivity analyses were conducted to test this association according to different study characteristics. Results: Twenty-four studies comprising 1853 breast cancers of poor prognosis and 2590 control participants were included in the analysis. Peritumoral edema was associated with non-luminal breast cancers (OR=3.56; 95%CI: 2.17, 5.83; p=.000), high expression of the Ki-67 index (OR=3.70; 95%CI: 2.41, 5.70; p =.000), high histological grade (OR=5.85; 95%CI: 3.89, 8.80; p=.000), lymph node metastasis (OR=2.83; 95%CI: 1.71, 4.67; p=.000), negative expression of HR (OR=3.15; 95%CI: 2.03, 4.88; p=.000), and lymphovascular invasion (OR=1.72; 95%CI: 1.28, 2.30; p=.000). The adjacent vessel sign was associated with greater odds of breast cancer with poor prognosis (OR=2.02; 95%CI: 1.68, 2.44; p=.000). Additionally, breast cancers with poor prognosis had higher peritumor-tumor ADC ratio (SMD=0.67; 95%CI: 0.54, 0.79; p=.000) and peritumoral ADCmean (SMD=0.29; 95%CI: 0.15, 0.42; p=.000). A peritumoral region of 2–20 mm away from the margin of the tumor is recommended. Conclusion: The presence of peritumoral edema and adjacent vessel signs, higher peritumor-tumor ADC ratio, and peritumoral ADCmean were significantly correlated with poor prognosis of breast cancer. Clinical relevance statement: MRI features of the peritumoral region can be used as a non-invasive index for the prognostic evaluation of invasive breast cancer. Key Points: • Peritumoral edema was positively associated with non-luminal breast cancer, high expression of the Ki-67 index, high histological grade, lymph node metastasis, negative expression of HR, and lymphovascular invasion. • The adjacent vessel sign was associated with greater odds of breast cancers with poor prognosis. • Breast cancers with poor prognosis had higher peritumor-tumor ADC ratio and peritumoral ADCmean. [ABSTRACT FROM AUTHOR]

The hypothalamus regulates homeostasis across the lifespan and is emerging as a regulator of aging. In murine models, aging-related changes in the hypothalamus, including microinflammation and gliosis, promote accelerated neurocognitive decline. We investigated relationships between hypothalamic microstructure and features of neurocognitive aging, including cortical thickness and cognition, in a cohort of community-dwelling older adults (age range 65–97 years, n=124). Hypothalamic microstructure was evaluated with two magnetic resonance imaging diffusion metrics: mean diffusivity (MD) and fractional anisotropy (FA), using a novel image processing pipeline. Hypothalamic MD was cross-sectionally positively associated with age and it was negatively associated with cortical thickness. Hypothalamic FA, independent of cortical thickness, was cross-sectionally positively associated with neurocognitive scores. An exploratory analysis of longitudinal neurocognitive performance suggested that lower hypothalamic FA may predict cognitive decline. No associations between hypothalamic MD, age, and cortical thickness were identified in a younger control cohort (age range 18–63 years, n=99). To our knowledge, this is the first study to demonstrate that hypothalamic microstructure is associated with features of neurocognitive aging in humans. • In animal models, aging-related changes in the hypothalamus drive brain aging. • The role of the hypothalamus in neurocognitive aging in humans is unknown. • We show that hypothalamic microstructure is altered with aging in older adults. • Hypothalamic microstructure is associated with cortical thickness and cognition. [ABSTRACT FROM AUTHOR]

Acknowledging the increasing use of whole-body magnetic resonance imaging (WB-MRI) in the oncological setting, we conducted a narrative review focusing on practical aspects of the examination and providing a synthesis of various acquisition protocols described in the literature. Firstly, we addressed the topic of patient preparation, emphasizing methods to enhance examination acceptance. This included strategies for reducing anxiety and patient distress, improving staff–patient interactions, and increasing overall patient comfort. Secondly, we analysed WB-MRI acquisition protocols recommended in existing imaging guidelines, such as MET-RADS-P, MY-RADS, and ONCO-RADS, and provided an overview of acquisition protocols reported in the literature regarding other expanding applications of WB-MRI in oncology, in patients with breast cancer, ovarian cancer, melanoma, colorectal and lung cancer, lymphoma, and cancers of unknown primary. Finally, we suggested possible acquisition parameters for whole-body images across MR systems from three different vendors. [ABSTRACT FROM AUTHOR]

Cerebrospinal fluid (CSF) plays a critical role in metabolic waste clearance from the brain, requiring its circulation throughout various brain pathways, including the ventricular system, subarachnoid spaces, para‐arterial spaces, interstitial spaces, and para‐venous spaces. The complexity of CSF circulation has posed a challenge in obtaining noninvasive measurements of CSF dynamics. The assessment of CSF dynamics throughout its various circulatory pathways is possible using diffusion magnetic resonance imaging (MRI) with optimized sensitivity to incoherent water movement across the brain. This review presents an overview of both established and emerging diffusion MRI techniques designed to measure CSF dynamics and their potential clinical applications. The discussion offers insights into the optimization of diffusion MRI acquisition parameters to enhance the sensitivity and specificity of diffusion metrics on underlying CSF dynamics. Lastly, we emphasize the importance of cautious interpretations of diffusion‐based imaging, especially when differentiating between tissue‐ and fluid‐related changes or elucidating structural versus functional alterations. [ABSTRACT FROM AUTHOR]

Background: Previous studies using emerging diffusion MRI techniques have revealed damage to the white matter (WM) microstructure in amyotrophic lateral sclerosis (ALS), particularly the influence of crossed fibers, but there is a lack of subgroup analyses. Purpose: To detect WM microstructural changes in ALS patients using fixel‐based analysis (FBA) and neurite orientation dispersion and density imaging (NODDI) MRI. Study Type: Prospective. Population: Thirty‐six ALS patients (aged 60.50 ± 9.5 years) and 25 healthy controls (HCs) (aged 58.90 ± 8.1 years). Field Strength/Sequence: 3 T; NODDI and FBA (b‐values = 0, 1000, and 2500 seconds/mm2). Assessment: Subgroups were performed according to progression rate and cognition, including fast and slow progression (FP/SP), ALS with and without cognitive impairment (ALS‐ci/ALS‐nci). Fiber density (FD), fiber‐bundle cross‐section (FC), combined fiber density and cross‐section (FDC), neurite density index (NDI), orientation dispersion index (ODI), isotropic volume fraction (ISO), and fractional anisotropy (FA) were calculated and their correlation with clinical variables examined. Statistical Testing: Chi‐square test, Mann–Whitney U test, two‐sample t test, partial correlation analysis, and false discovery rate (FDR) corrected. A P‐value <0.05 was considered significant. Results: ALS patients had lower FD and FDC values predominantly in the corticospinal tract (CST) and corpus callosum (CC) regions, as well as lower NDI value in the CC, radial crown, and internal capsule compared to HCs. Subgroup analysis based on progression rate and cognitive function showed significant differences in FBA results. The FC in the right CST region was significantly lower in the FP than SP, and the FD in the CC region was significantly lower in the ALS‐ci than ALS‐nci. Furthermore, a negative correlation was found between the mean FC value and the rate of progression in ALS patients (r = −0.408). Data Conclusion: FBA is a powerful tool for detecting complex cerebral WM microstructural damage for evaluating ALS cognition and disease progression. [ABSTRACT FROM AUTHOR]

Purpose: This work reports for the first time on the implementation and application of cardiac diffusion‐weighted MRI on a Connectom MR scanner with a maximum gradient strength of 300 mT/m. It evaluates the benefits of the increased gradient performance for the investigation of the myocardial microstructure. Methods: Cardiac diffusion‐weighted imaging (DWI) experiments were performed on 10 healthy volunteers using a spin‐echo sequence with up to second‐ and third‐order motion compensation (M2$$ {M}_2 $$ and M3$$ {M}_3 $$) and b=100, 450$$ b=100,450 $$, and 1000 s/mm2$$ \mathrm{s}/\mathrm{m}{\mathrm{m}}^2 $$ (twice the bmax$$ {b}_{\mathrm{max}} $$ commonly used on clinical scanners). Mean diffusivity (MD), fractional anisotropy (FA), helix angle (HA), and secondary eigenvector angle (E2A) were calculated for b = [100, 450] s/mm2$$ \mathrm{s}/\mathrm{m}{\mathrm{m}}^2 $$ and b = [100, 1000] s/mm2$$ \mathrm{s}/\mathrm{m}{\mathrm{m}}^2 $$ for both M2$$ {M}_2 $$ and M3$$ {M}_3 $$. Results: The MD values with M3$$ {M}_3 $$ are slightly higher than with M2$$ {M}_2 $$ with ΔMD=0.05±0.05[×10−3mm2/s](p=4e−5)$$ \Delta \mathrm{MD}=0.05\pm 0.05\kern0.3em \left[\times 1{0}^{-3}\kern0.3em {\mathrm{mm}}^2/\mathrm{s}\right]\kern0.3em \left(p=4e-5\right) $$ for bmax=450s/mm2$$ {b}_{\mathrm{max}}=450\kern0.3em \mathrm{s}/{\mathrm{mm}}^2 $$ and ΔMD=0.03±0.03[×10−3mm2/s](p=4e−4)$$ \Delta \mathrm{MD}=0.03\pm 0.03\kern0.3em \left[\times \kern0.3em 1{0}^{-3}\kern0.3em {\mathrm{mm}}^2/\mathrm{s}\right]\kern0.3em \left(p=4e-4\right) $$ for bmax=1000s/mm2$$ {b}_{\mathrm{max}}=1000\kern0.3em \mathrm{s}/{\mathrm{mm}}^2 $$. A reduction in MD is observed by increasing the bmax$$ {b}_{\mathrm{max}} $$ from 450 to 1000 s/mm2$$ \mathrm{s}/{\mathrm{mm}}^2 $$ (ΔMD=0.06±0.04[×10−3mm2/s](p=1.6e−9)$$ \Delta \mathrm{MD}=0.06\pm 0.04\kern0.3em \left[\times \kern0.3em 1{0}^{-3}\kern0.3em {\mathrm{mm}}^2/\mathrm{s}\right]\kern0.3em \left(p=1.6e-9\right) $$ for M2$$ {M}_2 $$ and ΔMD=0.08±0.05[×10−3mm2/s](p=1e−9)$$ \Delta \mathrm{MD}=0.08\pm 0.05\kern0.3em \left[\times \kern0.3em 1{0}^{-3}\kern0.3em {\mathrm{mm}}^2/\mathrm{s}\right]\kern0.3em \left(p=1e-9\right) $$ for M3$$ {M}_3 $$). The difference between FA, E2A, and HA was not significant in different schemes (p>0.05$$ p>0.05 $$). Conclusion: This work demonstrates cardiac DWI in vivo with higher b‐value and higher order of motion compensated diffusion gradient waveforms than is commonly used. Increasing the motion compensation order from M2$$ {M}_2 $$ to M3$$ {M}_3 $$ and the maximum b‐value from 450 to 1000 s/mm2$$ \mathrm{s}/{\mathrm{mm}}^2 $$ affected the MD values but FA and the angular metrics (HA and E2A) remained unchanged. Our work paves the way for cardiac DWI on the next‐generation MR scanners with high‐performance gradient systems. [ABSTRACT FROM AUTHOR]

Purpose: In contrast to peritumoral edema in metastases, GBM is histopathologically characterized by infiltrating tumor cells within the T2 signal alterations. We hypothesized that depending on the distance from the outline of the contrast-enhancing tumor we might reveal imaging evidence of gradual peritumoral infiltration in GBM and predominantly vasogenic edema around metastases. We thus investigated the gradual change of advanced diffusion metrics with the peritumoral zone in metastases and GBM. Methods: In 30 patients with GBM and 28 with brain metastases, peritumoral T2 hyperintensity was segmented in 33% partitions based on the total volume beginning at the enhancing tumor margin and divided into inner, middle and outer zones. Diffusion Tensor Imaging (DTI)-derived fractional anisotropy and mean diffusivity as well as Diffusion Microstructure Imaging (DMI)-based parameters Dax-intra, Dax-extra, V‑CSF and V-intra were employed to assess group-wise differences between inner and outer zones as well as within-group gradients between the inner and outer zones. Results: In metastases, fractional anisotropy and Dax-extra were significantly reduced in the inner zone compared to the outer zone (FA p = 0.01; Dax-extra p = 0.03). In GBM, we noted a reduced Dax-extra and significantly lower intraaxonal volume fraction (Dax-extra p = 0.008, V‑intra p = 0.006) accompanied by elevated axial intraaxonal diffusivity in the inner zone (p = 0.035). Between-group comparison of the outer to the inner zones revealed significantly higher gradients in metastases over GBM for FA (p = 0.04) as well as the axial diffusivity in the intra- (p = 0.02) and extraaxonal compartment (p < 0.001). Conclusion: Our findings provide evidence of gradual alterations within the peritumoral zone of brain tumors. These are compatible with predominant (vasogenic) edema formation in metastases, whereas our findings in GBM are in line with an axonal destructive component in the immediate peritumoral area and evidence of tumor cell infiltration with accentuation in the tumor's vicinity. [ABSTRACT FROM AUTHOR]

Objective: Tongue squamous cell carcinoma (TSCC) accounts for 43.4% of oral cancers in China and has a poor prognosis. This study aimed to explore whether radiomics features extracted from preoperative magnetic resonance imaging (MRI) could predict overall survival (OS) in patients with TSCC. Methods: The clinical imaging data of 232 patients with pathologically confirmed TSCC at Xiangyang No. 1 People's Hospital were retrospectively analyzed from February 2010 to October 2022. Based on 2–10 years of follow-up, patients were categorized into two groups: control (healthy survival, n = 148) and research (adverse events: recurrence or metastasis-related death, n = 84). A training and a test set were established using a 7:3 ratio and a time node. Radiomics features were extracted from axial T2-weighted imaging, contrast-enhanced T1-weighted imaging, and diffusion-weighted imaging (DWI) sequences. The corresponding radiomics scores were generated using the least absolute shrinkage and selection operator algorithm. Kaplan–Meier and multivariate Cox regression analyses were used to screen for independent factors affecting adverse events in patients with TSCC using clinical and pathological results. A novel nomogram was established to predict the probability of adverse events and OS in patients with TSCC. Results: The incidence of adverse events within 2–10 years after surgery was 36.21%. Kaplan–Meier analysis revealed that hot pot consumption, betel nut chewing, platelet–lymphocyte ratio, drug use, neutrophil–lymphocyte ratio, Radscore, and other factors impacted TSCC survival. Multivariate Cox regression analysis revealed that the clinical stage (P < 0.001), hot pot consumption (P < 0.001), Radscore 1 (P = 0.01), and Radscore 2 (P < 0.001) were independent factors affecting TSCC-OS. The same result was validated by the XGBoost algorithm. The nomogram based on the aforementioned factors exhibited good discrimination (C-index 0.86/0.81) and calibration (P > 0.05) in the training and test sets, accurately predicting the risk of adverse events and survival. Conclusion: The nomogram constructed using clinical data and MRI radiomics parameters may accurately predict TSCC-OS noninvasively, thereby assisting clinicians in promptly modifying treatment strategies to improve patient prognosis. [ABSTRACT FROM AUTHOR]

Diffusion-weighted imaging (DWI) is the primary method to investigate macro- and microstructure of neural white matter in vivo. DWI can be used to identify and characterize individual-specific white matter bundles, enabling precise analyses on hypothesis-driven connections in the brain and bridging the relationships between brain structure, function, and behavior. However, cortical endpoints of bundles may span larger areas than what a researcher is interested in, challenging presumptions that bundles are specifically tied to certain brain functions. Functional MRI (fMRI) can be integrated to further refine bundles such that they are restricted to functionally-defined cortical regions. Analyzing properties of these Functional Sub-Bundles (FSuB) increases precision and interpretability of results when studying neural connections supporting specific tasks. Several parameters of DWI and fMRI analyses, ranging from data acquisition to processing, can impact the efficacy of integrating functional and diffusion MRI. Here, we discuss the applications of the FSuB approach, suggest best practices for acquiring and processing neuroimaging data towards this end, and introduce the FSuB-Extractor, a flexible open-source software for creating FSuBs. We demonstrate our processing code and the FSuB-Extractor on an openly-available dataset, the Natural Scenes Dataset. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the efficacy of high b-value diffusion-weighted imaging (DWI) with a continuous-time random-walk (CTRW) diffusion model in determining the pathological grade and variant histology (VH) of bladder cancer (BCa). Methods: A total of 81 patients (median age, 70 years; range, 35-92 years; 18 females; 66 high grades; 30 with VH) with pathologically confirmed bladder urothelial carcinoma were retrospectively enrolled and underwent bladder MRI on a 3.0T MRI scanner. Multi-b-value DWI was performed using 11 b-values. Three CTRW model parameters were obtained: an anomalous diffusion coefficient (D) and two parameters reflecting temporal (a) and spatial (b) diffusion heterogeneity. The apparent diffusion coefficient (ADC) was calculated using b0 and b800. D, α, β, and ADC were statistically compared between high- and low-grade BCa, and between pure urothelial cancer (pUC) and VH. Comparisons were made using the Mann--Whitney U test between different pathological states. Receiver operating characteristic curve analysis was used to assess performance in differentiating the pathological states of BCa. Results: ADC, D, and a were significantly lower in high-grade BCa compared to low-grade, and in VH compared to pUC (p < 0.001), while b showed no significant differences (p > 0.05). The combination of D and a yielded the best performance for determining BCa grade and VH (area under the curves = 0.913, 0.811), significantly outperforming ADC (area under the curves = 0.823, 0.761). Conclusion: The CTRW model effectively discriminated pathological grades and variants in BCa, highlighting its potential as a noninvasive diagnostic tool. [ABSTRACT FROM AUTHOR]

Background: Although endometrial cancer (EC) is staged surgically, magnetic resonance imaging (MRI) plays a critical role in assessing and selecting the most appropriate treatment planning. We aimed to assess the diagnostic performance of quantitative analysis of diffusion-weighted imaging (DWI) in preoperative assessment of EC. Methods: Prospective analysis was done for sixty-eight patients with pathology-proven endometrial cancer who underwent MRI and DWI. Apparent diffusion coefficient (ADC) values were measured by two independent radiologists and compared with the postoperative pathological results. Results: There was excellent inter-observer reliability in measuring ADCmean values. There were statistically significant lower ADCmean values in patients with deep myometrial invasion (MI), cervical stromal invasion (CSI), type II EC, and lympho-vascular space involvement (LVSI) (AUC = 0.717, 0.816, 0.999, and 0.735 respectively) with optimal cut-off values of ≤ 0.84, ≤ 0.84, ≤ 0.78 and ≤ 0.82 mm2/s respectively. Also, there was a statistically significant negative correlation between ADC values and the updated 2023 FIGO stage and tumor grade (strong association), and the 2009 FIGO stage (medium association). Conclusions: The preoperative ADCmean values of EC were significantly correlated with main prognostic factors including depth of MI, CSI, EC type, grade, nodal involvement, and LVSI. [ABSTRACT FROM AUTHOR]

Introduction: This study evaluated changes in the white matter of the brain and psychological health variables, resulting from a neuroscience-based mindfulness intervention, the Training for Awareness, Resilience, and Action (TARA), in a population of healthy adolescents. Methods: A total of 100 healthy adolescents (57 female, age ranges 14-18years) were randomized into the 12-week TARA intervention or a waitlist-control group. All participants were imaged with diffusion MRI to quantify white matter connectivity between brain regions. Imaging occurred at baseline/randomization and after 12 weeks of baseline (pre- and post-intervention in the TARA group). We hypothesized that structural connectivity in the striatum and interoceptive networks would increase following the TARA intervention, and that, this increased connectivity would relate to psychological health metrics from the Strengths and Difficulties Questionnaire (SDQ) and the Insomnia Severity Index (ISI). The TARA intervention and all assessments, except for the MRIs, were fully remotely delivered using secure telehealth platforms and online electronic data capture systems. Results: The TARA intervention showed high consistency, tolerability, safety, recruitment, fidelity, adherence, and retention. After 12 weeks, the TARA group, but not controls, also demonstrated significantly improved sleep quality (p = 0.02), and changes in the right putamen node strength were related to this improved sleep quality (r=-0.42, p = 0.006). Similarly, the TARA group, but not controls, had significantly increased right insula node strength related to improved emotional well-being (r=-0.31, p = 0.04). Finally, we used the network-based statistics to identify a white matter interoception network that strengthened following TARA (p = 0.009). Discussion: These results suggest that the TARA mindfulness-based intervention in healthy adolescents is feasible and safe, and it may act to increase structural connectivity strength in interoceptive brain regions. Furthermore, these white matter changes are associated with improved adolescent sleep quality and emotional well-being. Our results suggest that TARA could be a promising fully remotely delivered intervention for improving psychological well-being in adolescents. As our findings suggest that TARA affects brain regions in healthy adolescents, which are also known to be altered during depression in adolescents, future studies will examine the effects of TARA on depressed adolescents. [ABSTRACT FROM AUTHOR]

Background: The diagnostic value of clinical rotator cuff (RC) tests is controversial, with only sparse evidence available about their anatomical specificity. We prospectively assessed regional RC muscle activation patterns by means of intravoxel incoherent motion (IVIM) diffusion-weighted magnetic resonance imaging (MRI) after the execution of common clinical RC tests. Methods: Ten healthy subjects (five males, five females) underwent three sessions of diffusion-weighted 3-T shoulder MRI before and after testing the supraspinatus (SSP, Jobe test, session 1), subscapularis (SSC, lift-off test, session 2, at least 1 week later), and infraspinatus muscle (ISP, external rotation test, session 3, another week later). IVIM parameters (perfusion fraction, f; pseudo-diffusion coefficient. D*; and their product, fD*) were measured in regions of interest placed in images of the SSP, SSC, ISP, and deltoid muscle. The Wilcoxon signed-rank test was used for group comparisons; p-values were adjusted using the Bonferroni correction. Results: After all tests, fD* was significantly increased in the respective target muscles (SSP, SSC, or ISP; p ≤ 0.001). After SSP testing, an additional significant increase of fD* was observed in the deltoid, the SSC, and the ISP muscle (p < 0.001). After the SSC and ISP tests, no significant concomitant increase of any parameter was observed in the other RC muscles. Conclusion: IVIM revealed varying activation patterns of RC muscles for different clinical RC tests. For SSP testing, coactivation of the deltoid and other RC muscles was observed, implying limited anatomical specificity, while the tests for the SSC and ISP specifically activated their respective target muscle. Relevance statement: Following clinical RC tests, IVIM MRI revealed that SSP testing led to shoulder muscle coactivation, while the SSC and ISP tests specifically activated the target muscles. Key Points: In this study, intravoxel incoherent motion MRI depicted muscle activation following clinical rotator cuff tests. After supraspinatus testing, coactivation of surrounding shoulder girdle muscles was observed. Subscapularis and infraspinatus tests exhibited isolated activation of their respective target muscles. [ABSTRACT FROM AUTHOR]

Acute brain infarction detected by diffusion-weighted magnetic resonance imaging (DW-MRI) is common after transcatheter aortic valve replacement (TAVR), but its clinical relevance is uncertain. The authors investigated the relationship between DW-MRI total lesion number (TLN), individual lesion volume (ILV), and total lesion volume (TLV) and clinical stroke outcomes after TAVR. Patient-level data were pooled from 4 prospective TAVR embolic protection studies, with consistent predischarge DW-MRI acquisition and core laboratory analysis. C-statistic was used to determine the best DW-MRI measure associated with clinical stroke. A total of 495 of 603 patients undergoing TAVR completed the predischarge DW-MRI. At 30 days, the rate of clinical ischemic stroke was 6.9%. Acute ischemic brain injury was seen in 85% of patients with 5.5 ± 7.3 discrete lesions per patient, mean ILV of 78.2 ± 257.1 mm3, and mean TLV of 555 ± 1,039 mm3. The C-statistic was 0.84 for TLV, 0.81 for number of lesions, and 0.82 for maximum ILV in predicting ischemic stroke. On the basis of the TLV cutpoint as defined by receiver operating characteristic (ROC), patients with a TLV >500 mm3 (vs TLV ≤500 mm3) had more ischemic stroke (18.2% vs 2.3%; P < 0.0001), more disabling strokes (8.8% vs 0.9%; P < 0.0001), and less complete stroke recovery (44% vs 62.5%; P = 0.001) at 30 days. Our study confirms that the number, size, and total volume of acute brain infarction defined by DW-MRI are each associated with clinical ischemic strokes, disabling strokes, and worse stroke recovery in patients undergoing TAVR and may have value as surrogate outcomes in stroke prevention trials. (A Prospective, Randomized Evaluation of the TriGuard™ HDH Embolic Deflection Device During TAVI [DEFLECT III]; NCT02070731) (A Study to Evaluate the Neuro-embolic Consequences of TAVR [NeuroTAVR]; NCT02073864) (The REFLECT Trial: Cerebral Protection to Reduce Cerebral Embolic Lesions After Transcatheter Aortic Valve Implantation [REFLECT I]; NCT02536196) (The REFLECT Trial: Cerebral Protection to Reduce Cerebral Embolic Lesions After Transcatheter Aortic Valve Implantation [REFLECT II]; NCT02536196) [ABSTRACT FROM AUTHOR]

Objectives: Seeking a noninvasive predictor for BRAF V600E mutation status of pleomorphic xanthoastrocytomas (PXAs) is essential for their prognoses and therapeutic use of BRAF inhibitors. We aimed to noninvasively diagnose BRAF V600E-mutated PXAs using MRI morphologic, DWI and clinical parameters. Methods: The clinical findings, anatomical MRI characteristics, and diffusion parameters of 36 pathologically confirmed PXAs were retrospectively analyzed, and BRAF V600E-mutated (n = 16) and wild-type (n = 20) groups were compared. A binary logistic-regression analysis was performed, and a ROC curve was calculated to determine the independent predictors of BRAF V600E mutation status, diagnostic accuracy, and optimal cut-off value. Results: A comparison of findings between groups showed that BRAF V600E-mutated PXAs were more frequent in children and young adults (≤ 35 years; P = 0.042) who often had histories of seizures (P = 0.004). Furthermore, BRAF V600E-mutated PXAs generally presented as solitary masses (P = 0.024), superficial locations with meningeal attachment (P < 0.001), predominantly cystic with mural nodules (P = 0.005), and had greater minimal ADC ratio (ADCratio) values of the tumor and peritumoral edema (P < 0.001). Binary logistic regression showed that age ≤ 35 years, solitary mass, superficial locations with meningeal attachment, and a greater minimal ADCratio of the tumor were independent predictors of BRAF V600E-mutated PXAs. The combination of all four independent predictors resulted in the highest sensitivity (100%) and specificity (90%), with AUC = 0.984. Conclusion: The BRAF V600E mutation status of PXAs could be noninvasively predicted using clinical and MRI characteristics. Critical relevance statement: The noninvasive diagnostic criteria for BRAF V600E-mutated PXAs could offer guidance for the administration of BRAF V600E mutation inhibitors in the future. Key points: 1. The relevant features of PXAs were analyzed according to BRAF V600E mutation status. 2. The BRAF V600E mutation status of PXAs can be accurately and noninvasively predicted. 3. The result can provide guidance for the administration of BRAF V600E mutation inhibitors. [ABSTRACT FROM AUTHOR]

Background: Mild encephalopathy wıth reversible splenial lesions (MERS) are a clinical–radiological diagnosis that can be diagnosed with radiological imaging and can be accompanied by impaired consciousness, aphasia, headache, and paralysis. MERS can be divided into two different types based on radiological findings; Involvement of the splenium is seen in type 1, and involvement of the splenium and deep white matter is seen in type 2. MERS Type 2 is very rare in adults. Here, we describe a patient diagnosed with MERS Type 2 and our therapeutic intervention. Case presentation: A 22-year-old woman presented with slurred speech, weakness in the extremities and headache that started 14 h ago. The patient had sore throat and fever of 37.6 °C for 2 days, and medical history or family history were unremarkable. Neurological examination revealed that she was conscious, cooperative, with no signs of meningeal irritation. Speech comprehension, naming, and repetition were preserved, motor examination revealed 5/5 left upper extremity strength, 4/5 right upper extremity strength, and 2/5 bilateral lower extremity strength. Diffusion-weighted magnetic resonance imaging (MRI-DWI) revealed bilateral deep white matter and splenium symmetrical diffusion restriction. Blood tests showed high C-reactive protein (CRP) and no leukocytosis. No cells were detected in the cerebrospinal fluid (CSF), protein was 151 mg/dl, glucose was within normal limits. The patient, who developed quadriparesis during follow-up, was started on pulse dose steroids. Neurological examination improved to patient's baseline at the 12th hour of treatment. In the 72nd hour control MRI-DWI, it was seen that the lesions had regressed. Culture/Polymerase chain reaction (PCR) for bacterial/viral infection agents came back negative. After steroids were given for 5 days, patient was discharged at her baseline. Conclusions: MERS is a rare diagnosis in adults and can be radiologically confused with acute toxic leukoencephalopathy. It can be distinguished clinically by the absence of prior infection, fever, and toxic agent exposure. Although there is no consensus in the literature regarding the treatment, the clinical picture improved rapidly after steroid in our case. Despite being rare, it should be considered in the differential diagnosis of patients with deep white matter lesions in adults. [ABSTRACT FROM AUTHOR]

Introduction: Traumatic brain injury (TBI) even in the mild form may result in long-lasting post-concussion symptoms. TBI is also a known risk to late-life neurodegeneration. Recent studies suggest that dysfunction in the glymphatic system, responsible for clearing protein waste from the brain, may play a pivotal role in the development of dementia following TBI. Given the diverse nature of TBI, longitudinal investigations are essential to comprehending the dynamic changes in the glymphatic system and its implications for recovery. Methods: In this prospective study, we evaluated two promising glymphatic imaging markers, namely the enlarged perivascular space (ePVS) burden and Diffusion Tensor Imaging-based ALPS index, in 44 patients with mTBI at two early post-injury time points: approximately 14 days (14Day) and 6-12 months (6-12Mon) post-injury, while also examining their associations with post-concussion symptoms. Additionally, 37 controls, comprising both orthopedic patients and healthy individuals, were included for comparative analysis. Results: Our key findings include: (1) White matter ePVS burden (WM-ePVS) and ALPS index exhibit significant correlations with age. (2) Elevated WM-ePVS burden in acute mTBI (14Day) is significantly linked to a higher number of post-concussion symptoms, particularly memory problems. (3) The increase in the ALPS index from acute (14Day) to the chronic (6-12Mon) phases in mTBI patients correlates with improvement in sleep measures. Furthermore, incorporating WM-ePVS burden and the ALPS index from acute phase enhances the prediction of chronic memory problems beyond socio-demographic and basic clinical information. Conclusion: ePVS burden and ALPS index offers distinct values in assessing glymphatic structure and activity. Early evaluation of glymphatic function could be crucial for understanding TBI recovery and developing targeted interventions to improve patient outcomes. [ABSTRACT FROM AUTHOR]

Introduction: Post-acute COVID syndrome (PACS) is a growing concern, given its impact on mental health and quality of life. However, its effects on cerebral white matter remain poorly understood, particularly in non-hospitalized cohorts. The goals of this cross-sectional, observational study were to examine (1) whether PACS was associated with distinct alterations in white matter microstructure, compared to symptom-matched non-COVID viral infection; and (2) whether microstructural alterations correlated with indices of post-COVID emotional health. Methods: Data were collected for 54 symptomatic individuals who tested positive for COVID-19 (mean age 41 ± 12 yrs., 36 female) and 14 controls who tested negative for COVID-19 (mean age 41 ± 14 yrs., 8 female), with both groups assessed an average of 4-5 months after COVID testing. Diffusion magnetic resonance imaging data were collected, and emotional health was assessed via the NIH emotion toolbox, with summary scores indexing social satisfaction, well-being and negative affect. Results: Despite similar symptoms, the COVID-19 group had reduced mean and axial diffusivity, along with increased mean kurtosis and neurite dispersion, in deep white matter. After adjusting for social satisfaction, higher levels of negative affect in the COVID-19 group were also correlated with increased mean kurtosis and reduced free water in white matter. Discussion: These results provide preliminary evidence that indices of white matter microstructure distinguish PACS from symptomatic non-COVID infection. Moreover, white matter effects seen in PACS correlate with the severity of emotional sequelae, providing novel insights into this highly prevalent disorder. [ABSTRACT FROM AUTHOR]

Background: Mild Cognitive Impairment (MCI) is a transitional stage from normal aging to dementia, characterized by noticeable changes in cognitive function that do not significantly impact daily life. Diffusion MRI (dMRI) plays a crucial role in understanding MCI by assessing white matter integrity and revealing early signs of axonal degeneration and myelin breakdown before cognitive symptoms appear. Methods: This study utilized the Alzheimer's Disease Neuroimaging Initiative (ADNI) database to compare white matter microstructure in individuals with MCI to cognitively normal (CN) individuals, employing advanced dMRI techniques such as diffusion kurtosis imaging (DKI), mean signal diffusion kurtosis imaging (MSDKI), and free water imaging (FWI). Results: Analyzing data from 55 CN subjects and 46 individuals with MCI, this study found significant differences in white matter integrity, particularly in free water levels and kurtosis values, suggesting neuroinflammatory responses and microstructural integrity disruption in MCI. Moreover, negative correlations between Mini-Mental State Examination (MMSE) scores and free water levels in the brain within the MCI group point to the potential of these measures as early biomarkers for cognitive impairment. Conclusion: In conclusion, this study demonstrates how a multimodal advanced diffusion imaging approach can uncover early microstructural changes in MCI, offering insights into the neurobiological mechanisms behind cognitive decline. [ABSTRACT FROM AUTHOR]

Platinum-based neoadjuvant chemotherapy (NACT) followed by radical hysterectomy has been proposed as an alternative treatment approach for cervical cancer (CC) in stage Ib2-IIb, who had a strong desire to be treated with surgery. Our study aims to develop a model based on multimodal MRI by using radiomics and deep learning to predict the treatment response in CC patients treated with neoadjuvant chemoradiotherapy (NACRT). From August 2009 to June 2013, CC patients in stage Ib2-IIb (FIGO 2008) who received NACRT at Fujian Cancer Hospital were enrolled in our study. Clinical information, contrast-enhanced T1-weighted imaging (CE-T1WI), and T2-weighted imaging (T2WI) data were respectively collected. Radiomic features and deep abstract features were extracted from the images using radiomics and deep learning models, respectively. Then, ElasticNet and SVM-RFE were employed for feature selection to construct four single-sequence feature sets. Early fusion of two multi-sequence feature sets and one hybrid feature set were performed, followed by classification prediction using four machine learning classifiers. Subsequently, the performance of the models in predicting the response to NACRT was evaluated by separating patients into training and validation sets. Additionally, overall survival (OS) and disease-free survival (DFS) were assessed using Kaplan-Meier survival curves. Among the four machine learning models, SVM exhibited the best predictive performance (AUC=0.86). Among the seven feature sets, the hybrid feature set achieved the highest values for AUC (0.86), ACC (0.75), Recall (0.75), Precision (0.81), and F1-score (0.75) in the validation set, outperforming other feature sets. Furthermore, the predicted outcomes of the model were closely associated with patient OS and DFS (p = 0.0044; p = 0.0039). A model based on MRI images with features from multiple sequences and different methods could precisely predict the response to NACRT in CC patients. This model could assist clinicians in devising personalized treatment plans and predicting patient survival outcomes. [ABSTRACT FROM AUTHOR]