Generalized inhomogeneity-resilient relaxation along a fictitious field (girRAFF) for improved robustness in rotating frame relaxometry at 3T

PURPOSE

To optimize Relaxation along a Fictitious Field (RAFF) pulses for rotating frame relaxometry with improved robustness in the presence ofB 0 $$ {\mathrm{B}}_0 $$ andB 1 + $$ {\mathrm{B}}_1^{+} $$ field inhomogeneities.

METHODS

The resilience of RAFF pulses againstB 0 $$ {\mathrm{B}}_0 $$ andB 1 + $$ {\mathrm{B}}_1^{+} $$ inhomogeneities was studied using Bloch simulations. A parameterized extension of the RAFF formulation was introduced and used to derive a generalized inhomogeneity-resilient RAFF (girRAFF) pulse. RAFF and girRAFF preparation efficiency, defined as the ratio of the longitudinal magnetization before and after the preparation (M z ( T p ) / M 0 $$ {M}_z\left({T}_p\right)/{M}_0 $$ ), were simulated and validated in phantom experiments.T RAFF $$ {T}_{\mathrm{RAFF}} $$ andT girRAFF $$ {T}_{\mathrm{girRAFF}} $$ parametric maps were acquired at 3T in phantom, the calf muscle, and the knee cartilage of healthy subjects. The relaxation time maps were analyzed for resilience against artificially induced field inhomogeneities and assessed in terms of in vivo reproducibility.

RESULTS

Optimized girRAFF preparations yielded improved preparation efficiency (0.95/0.91 simulations/phantom) with respect to RAFF (0.36/0.67 simulations/phantom).T girRAFF $$ {T}_{\mathrm{girRAFF}} $$ preparations showed in phantom/calf 6.0/4.8 times higher resilience toB 0 $$ {\mathrm{B}}_0 $$ inhomogeneities than RAFF, and a 4.7/5.3 improved resilience toB 1 + $$ {\mathrm{B}}_1^{+} $$ inhomogeneities. In the knee cartilage,T girRAFF $$ {T}_{\mathrm{girRAFF}} $$ (53± $$ \pm $$ 14 ms) was higher thanT RAFF $$ {T}_{\mathrm{RAFF}} $$ (42± $$ \pm $$ 11 ms). Moreover, girRAFF preparations yielded 7.6/4.9 times improved reproducibility acrossB 0 $$ {\mathrm{B}}_0 $$ /B 1 + $$ {\mathrm{B}}_1^{+} $$ inhomogeneity conditions, 1.9 times better reproducibility across subjects and 1.2 times across slices compared with RAFF. Dixon-based fat suppression led to a further 15-fold improvement in the robustness of girRAFF to inhomogeneities.

CONCLUSIONS

RAFF pulses display residual sensitivity to off-resonance and pronounced sensitivity toB 1 + $$ {\mathrm{B}}_1^{+} $$ inhomogeneities. Optimized girRAFF pulses provide increased robustness and may be an appealing alternative for applications where resilience against field inhomogeneities is required.

Feasibility of interleaved multislice averaged magnetization inversion-recovery acquisitions of the spinal cord

PURPOSE

To establish an interleaved multislice variant of the averaged magnetization inversion-recovery acquisitions (AMIRA) approach for 2D spinal cord imaging with increased acquisition efficiency compared with the conventional 2D single-slice approach(es), and to determine essential prerequisites for a working interleaved multislice AMIRA approach in practice.

METHODS

The general AMIRA concept is based on an inversion recovery-prepared, segmented, and time-limited cine balanced SSFP sequence, generating images of different contrast. For AMIRA imaging of multiple, independent slices in a 2D interleaved fashion, a slice loop within the acquisition loops was programmed. The former non-selective inversions were replaced with slice-selective inversions with user-definable slice thickness.

RESULTS

The thickness of the slice-selective inversion in 2D interleaved multislice AMIRA should be doubled compared with the manufacturer's standard setting to avoid an increased sensitivity to flow and pulsation effects particularly in the CSF. However, this solution also limits its practical applicability, as slices located at directly adjacent vertebrae cannot be imaged together. Successful interleaved two-slice AMIRA imaging for a "reference" in vivo protocol with 0.50 × 0.50 mm2 in-plane resolution and 8-mm slice thickness is demonstrated, therefore halving its acquisition time per slice from 3 min down to 1.5 min.

CONCLUSION

The investigated 2D interleaved two-slice AMIRA variant facilitates spinal cord imaging that maintains similar contrast and the same resolution as the conventional 2D single-slice AMIRA approach, but does so with a halved acquisition time.

Brain activity during working memory in patients with autoimmune Addison's disease

Autoimmune Addison's disease (AAD) is treated with daily oral hormone replacements for cortisol and aldosterone. The current treatment is sub-optimal, and frequently results in supra- and infra-physiological cortisol levels that might negatively affect the brain and cognitive functioning. It is currently unclear if the brains of these patients need to be better protected. The present study investigates brain function during working memory in young adults with AAD compared to healthy controls. All participants (56 AAD (33 females), 62 controls (39 females), 19-43 years), underwent MRI brain scanning while performing a visuo-spatial and verbal working memory task. No main group differences in accuracy, reaction time or brain activity during the tasks were found. These findings suggest that patients perform equal to controls, and achieve similar levels of brain activity during working memory. However, variations in the patient population may have confounded this outcome. Controlled studies on larger cohorts are therefore needed to confirm these findings and test if having AAD affects the brain on the long term.

Characteristic brain functional activation and connectivity during actual and imaginary right-handed grasp

We used 34-channel functional near infrared spectroscopy to investigate and compare changes in oxyhemoglobin concentration of brain networks in bilateral prefrontal cortex, sensorimotor cortex, and occipital lobe of 22 right-handed healthy adults during executive right-handed grasp (motor execution task) and imagined right-handed grasp (motor imagery task). Then calculated lateral index and functional contribution degree, and measured functional connectivity strength between the regions of interest. In the motor executive block task, there was a significant increase in oxyhemoglobin concentration in regions of interest except for right occipital lobe (P<0.05), while in the motor imagery task, all left regions of interest's oxyhemoglobin concentration increased significantly (P<0.05). Except the prefrontal cortex in motor executive task, the left side of the brain was dominant. Left sensorimotor cortex played a major role in these two tasks, followed by right sensorimotor cortex. Among all functional contribution degree, left sensorimotor cortex, right sensorimotor cortex and left occipital lobe ranked top three during these tasks. In continuous acquisition tasks, functional connectivity on during motor imagery task was stronger than that during motor executive task. Brain functions during two tasks of right-hand grasping movement were partially consistent. However, the excitability of brain during motor imagery was lower, and it was more dependent on the participation of left prefrontal cortex, and its synchronous activity of the whole brain was stronger. The trend of functional contribution degree was basically consistent with oxyhemoglobin concentration and lateral index, and can be used as a novel index to evaluate brain function. [ChiCTR2200063792 (2022-09-16)].

Computer-assisted analysis of routine EEG to identify hidden biomarkers of epilepsy: A systematic review

Background

Computational analysis of routine electroencephalogram (rEEG) could improve the accuracy of epilepsy diagnosis. We aim to systematically assess the diagnostic performances of computed biomarkers for epilepsy in individuals undergoing rEEG.

Methods

We searched MEDLINE, EMBASE, EBM reviews, IEEE Explore and the grey literature for studies published between January 1961 and December 2022. We included studies reporting a computational method to diagnose epilepsy based on rEEG without relying on the identification of interictal epileptiform discharges or seizures. Diagnosis of epilepsy as per a treating physician was the reference standard. We assessed the risk of bias using an adapted QUADAS-2 tool.

Results

We screened 10 166 studies, and 37 were included. The sample size ranged from 8 to 192 (mean=54). The computed biomarkers were based on linear (43%), non-linear (27%), connectivity (38%), and convolutional neural networks (10%) models. The risk of bias was high or unclear in all studies, more commonly from spectrum effect and data leakage. Diagnostic accuracy ranged between 64% and 100%. We observed high methodological heterogeneity, preventing pooling of accuracy measures.

Conclusion

The current literature provides insufficient evidence to reliably assess the diagnostic yield of computational analysis of rEEG.

Significance

We provide guidelines regarding patient selection, reference standard, algorithms, and performance validation.

B1-MRF: Large dynamic range MRF-based absolute B 1 + mapping in the human body at 7T

PURPOSE

This study aims to map the transmit magnetic field (B 1 + $$ {B}_1^{+} $$ ) in the human body at 7T using MR fingerprinting (MRF), with a focus on achieving high accuracy and precision across a large dynamic range, particularly at low flip angles (FAs).

METHODS

A FLASH-based MRF sequence (B1-MRF) with highB 1 + $$ {B}_1^{+} $$ sensitivity was developed. Phantom and in vivo abdominal imaging were performed at 7T, and the results were compared with established reference methods, including a slow but precise preparation-based method (PEX), saturated TurboFLASH (satTFL), actual flip angle imaging (AFI) and Bloch-Siegert shift (BSS).

RESULTS

The MRF signal curve was highly sensitive toB 1 + $$ {B}_1^{+} $$ , while T1 sensitivity was comparatively low. The phantom experiment showed good agreement ofB 1 + $$ {B}_1^{+} $$ to PEX for a T1 range of 204-1691 ms evaluated at FAs from 0° to 70°. Compared to the references, a dynamic range increase larger than a factor of two was determined experimentally. In vivo liver scans showed a strong correlation between B1-MRF, satTFL, and RPE-AFI in a low body mass index (BMI) subject (18.1 kg/m2). However, in larger BMI subjects (≥25.5 kg/m2), inconsistencies were observed in lowB 1 + $$ {B}_1^{+} $$ regions for satTFL and RPE-AFI, while B1-MRF still provided consistent results in these regions.

CONCLUSION

B1-MRF provides accurate and preciseB 1 + $$ {B}_1^{+} $$ maps over a wide range of FAs, surpassing the capabilities of existing methods in the FA range < 60°. Its enhanced sensitivity at low FAs is advantageous for various applications requiring preciseB 1 + $$ {B}_1^{+} $$ estimates, potentially advancing the frontiers of ultra-high field (UHF) body imaging at 7T and beyond.

Distortion-free water-fat separated diffusion-weighted imaging using spatiotemporal joint reconstruction

PURPOSE

Diffusion-weighted imaging (DWI) suffers from geometric distortion and chemical shift artifacts due to the commonly used Echo Planar Imaging (EPI) trajectory. Even with fat suppression in DWI, severe B0 and B1 variations can result in residual fat, which becomes both a source of image artifacts and a confounding factor in diffusion-weighted contrast in distinguishing benign and malignant tissues. This work presents a method for acquiring distortion-free diffusion-weighted images using spatiotemporal acquisition and joint reconstruction. Water-fat separation is performed by chemical-shift encoding.

METHODS

Spatiotemporal acquisition is employed to obtain distortion-free images at a series of echo times. Chemical-shift encoding is used for water-fat separation. Reconstruction and separation are performed jointly in the spat-spectral domain. To address the shot-to-shot motion-induced phase in DWI, an Fast Spin Echo (FSE)-based phase navigator is incorporated into the sequence to obtain distortion-free phase information. The proposed method was validated in phantoms and in vivo for the brain, head and neck, and breast.

RESULTS

The proposed method enables the acquisition of distortion-free diffusion-weighted images in the presence of B0 field inhomogenieties commonly observed in the body. Water and fat components are separated with no obvious spectral leakage artifacts. The estimated Apparent Diffusion Coefficient (ADC) is comparable to that of multishot DW-EPI.

CONCLUSION

Distortion-free, water-fat separated diffusion-weighted images in body can be obtained through the utilization of spatiotemporal acquisition and joint reconstruction methods.

Alteration of fractional anisotropy in preterm-born individuals: a systematic review and meta-analysis

BACKGROUD

Neurological disorders are common in preterm (PT) born individuals. Diffusion tensor imaging (DTI) studies using tract-based spatial statistics (TBSS) effectively detect microstructural white matter (WM) abnormalities in the brain. We conducted this systematic review to integrate the findings of TBSS studies to determine the most consistent WM alterations in PT born individuals.

METHODS

PubMed, Embase, Web of Science and Science Direct were searched. DTI studies using TBSS in PT born individuals were screened up to October 2022. The systematic review included studies reporting alterations in FA values for the entire brain in a stereotactic space, with three coordinates (x, y, z), according to the seed-based d mapping method.

RESULTS

The search strategy identified seventeen studies that fulfilled our inclusion criteria, with a total of 911 PT-born individuals and 563 matched controls were analysed. Of the seventeen studies, eight were dedicated to 650 adults, five to 411 children and four to 413 infants. Ten studies recruited 812 individuals born very prematurely (GA <29 weeks), six studies recruited 386 moderately premature individuals (GA = 29-32 weeks) and one study recruited 276 individuals born late prematurely (GA >32 weeks). This meta-analysis of six studies including 388 individuals highlighted four brain regions in which fractional anisotropy (FA) was lower in PT group than in people born at term. The quantitative meta-analysis found that the most robust WM alterations were located in the corpus callosum (CC), the bilateral thalamus and the left superior longitudinal fasciculus (SLF) II. Significant changes in FA reflect WM abnormalities in PT born individuals from infant to young adulthood.

CONCLUSIONS

Significant changes in FA reflect WM abnormalities in individuals born PT from infancy to young adulthood. The abnormal development of the CC, bilateral thalamus and left SLF may play a vital role in the neurodevelopment of PT individuals.

Automated algorithm for medical data structuring, and segmentation using artificial intelligence within secured environment for dataset creation

Objective

Routinely collected electronic health records using artificial intelligence (AI)-based systems bring out enormous benefits for patients, healthcare centers, and its industries. Artificial intelligence models can be used to structure a wide variety of unstructured data.

Methods

We present a semi-automatic workflow for medical dataset management, including data structuring, research extraction, AI-ground truth creation, and updates. The algorithm creates directories based on keywords in new file names.

Results

Our work focuses on organizing computed tomography (CT), magnetic resonance (MR) images, patient clinical data, and segmented annotations. In addition, an AI model is used to generate different initial labels that can be edited manually to create ground truth labels. The manually verified ground truth labels are later included in the structured dataset using an automated algorithm for future research.

Conclusion

This is a workflow with an AI model trained on local hospital medical data with output based/adapted to the users and their preferences. The automated algorithms and AI model could be implemented inside a secondary secure environment in the hospital to produce inferences.

Electromagnetic field enhanced flow state: Insights from electrophysiological measures, self-reported experiences, and gameplay

The intersection of neuroscience and technology hinges on the development of wearable devices and electrodes that can augment brain networks to improve cognitive capabilities such as learning and concentration. The capacity to enhance networks associated with these functions above baseline capabilities, holds the potential to benefit numerous individuals. The purpose of this study was to determine if electromagnetic field exposure modeled from physiological data would increase instances of flow in participants playing a computer game. The flow state refers to a subjective state of optimal performance experienced by individuals during a variety of tasks. For this study, participants (n = 39, 18-65 years, nfemale = 20) played the arcade game Snake for two ten-minute periods (each with a ten-minute rest period immediately following). For one of the trials, an electromagnetic field was applied bilaterally to the temporal lobes, with the other serving as the control. Brain activity was measured using quantitative electroencephalography, flow experience was measured using the Flow Short Scale and game play scores were also recorded. Results showed deceased beta 1 (12-16 Hz) activity in the left cuneus [t = 4.650, p < 0.01] and left precuneus [t = 4.603, p < 0.01], left posterior cingulate [t = 4.521, p < 0.05], insula [t = 4.234, p < 0.05], and parahippocampal gyrus [t = 4.113, p < 0.05] for trials when the field was active, compared to controls during rest periods. Results from the Flow Short Scale showed a statistically significant difference in mean "concentration ease" scores across electromagnetic field conditions, irrespective of difficulty [t = 2.131, p < 0.05]. In the EMF exposure trials, there was no discernible experience effect; participants with prior experience in the game Snake did not exhibit significantly better performance compared to those without prior experience. This anticipated effect was observed in control conditions. The comparable performance observed between novices and experienced players in the EMF condition indicate a noteworthy learning curve for novices. In all, these results provide evidence supporting the ability of EMF patterned from amygdaloid firing (6-20 Hz) to elicit neurological correlates of flow in brain regions previously reported in the literature, facilitate concentration, and subtly improve game scores. The possibility for wearable devices to support learning, concentration, and focus are discussed.

MPGAN: Multi Pareto Generative Adversarial Network for the denoising and quantitative analysis of low-dose PET images of human brain

Positron emission tomography (PET) imaging is widely used in medical imaging for analyzing neurological disorders and related brain diseases. Usually, full-dose imaging for PET ensures image quality but raises concerns about potential health risks of radiation exposure. The contradiction between reducing radiation exposure and maintaining diagnostic performance can be effectively addressed by reconstructing low-dose PET (L-PET) images to the same high-quality as full-dose (F-PET). This paper introduces the Multi Pareto Generative Adversarial Network (MPGAN) to achieve 3D end-to-end denoising for the L-PET images of human brain. MPGAN consists of two key modules: the diffused multi-round cascade generator (GDmc) and the dynamic Pareto-efficient discriminator (DPed), both of which play a zero-sum game for n(n∈1,2,3) rounds to ensure the quality of synthesized F-PET images. The Pareto-efficient dynamic discrimination process is introduced in DPed to adaptively adjust the weights of sub-discriminators for improved discrimination output. We validated the performance of MPGAN using three datasets, including two independent datasets and one mixed dataset, and compared it with 12 recent competing models. Experimental results indicate that the proposed MPGAN provides an effective solution for 3D end-to-end denoising of L-PET images of the human brain, which meets clinical standards and achieves state-of-the-art performance on commonly used metrics.

Water phase transition and signal nulling in 3D dual-echo adiabatic inversion-recovery UTE (IR-UTE) imaging of myelin

PURPOSE

The semisolid myelin sheath has very fast transverse relaxation and is invisible to conventional MRI sequences. UTE sequences can detect signal from myelin. The major challenge is the concurrent detection of various water components.

METHODS

The inversion recovery (IR)-based UTE (IR-UTE) sequence employs an adiabatic inversion pulse to invert and suppress water magnetizations. TI plays a key role in water suppression, with negative water magnetizations (negative phase) before the null point and positive water magnetizations (positive phase) after the null point. A series of dual-echo IR-UTE images were acquired with different TIs to detect water phase transition. The effects of TR in phase transition and water suppression were also investigated using a relatively long TR of 500 ms and a short TR of 106 ms. The water phase transition in dual-echo IR-UTE imaging of myelin was investigated in five ex vivo and five in vivo human brains.

RESULTS

An apparent phase transition was observed in the second echo at the water signal null point, where the myelin signal was selectively detected by the UTE data acquisition at the optimal TI. The water phase transition point varied significantly across the brain when the long TR of 500 ms was used, whereas the convergence of TIs was observed when the short TR of 106 ms was used.

CONCLUSION

The results suggest that the IR-UTE sequence with a short TR allows uniform inversion and nulling of water magnetizations, thereby providing volumetric imaging of myelin.

The impact of insomnia on brain networks topology in depressed patients: A resting-state fMRI study

OBJECTIVE

Depression and insomnia frequently co-occur, but the neural mechanisms between patients with varying degrees of these conditions are not fully understood. The specific topological features and connectivity patterns of this co-morbidity have not been extensively studied. This study aimed to investigate the topological characteristics of topological characteristics and functional connectivity of brain networks in depressed patients with insomnia.

METHODS

Resting-state functional magnetic resonance imaging data from 32 depressed patients with a high level of insomnia (D-HI), 35 depressed patients with a low level of insomnia (D-LI), and 81 healthy controls (HC) were used to investigate alterations in brain topological organization functional networks. Nodal and global properties were analyzed using graph-theoretic techniques, and network-based statistical analysis was employed to identify changes in brain network functional connectivity.

RESULTS

Compared to the HC group, both the D-HI and D-LI groups showed an increase in the global efficiency (Eglob) values, local efficiency (Eloc) was decreased in the D-HI group, and Lambda and shortest path length (Lp) values were decreased in the D-LI group. At the nodal level, the right parietal nodal clustering coefficient (NCp) values were reduced in D-HI and D-LI groups compared to those in HC. The functional connectivity of brain networks in patients with D-HI mainly involves default mode network (DMN)-cingulo-opercular network (CON), DMN-visual network (VN), DMN-sensorimotor network (SMN), and DMN-cerebellar network (CN), while that in patients with D-LI mainly involves SMN-CON, SMN-SMN, SMN-VN, and SMN-CN. The values of the connection between the midinsula and postoccipital gyrus was negatively correlated with scores for early awakening in D-HI.

CONCLUSION

These findings may contribute to our understanding of the underlying neuropsychological mechanisms in depressed patients with insomnia.

Cerebral white matter burden is linked to cognitive function in patients undergoing hemodialysis

INTRODUCTION

Chronic kidney disease is related to neurodegeneration and structural changes in the brain which might lead to cognitive decline. The Fazekas scale used for assessing white matter hyperintensities (WMHs) was associated with poor cognitive performance. Therefore, this study investigated the associations between the mini-mental status examination (MMSE), Montreal cognitive assessment (MoCA), cognitive abilities screening instrument (CASI), and Fazekas scale in patients under hemodialysis (HD).

METHODS

The periventricular (PV) WMHs and deep WMHs (DWMHs) in brain magnetic resonance images of 59 patients under dialysis were graded using the Fazekas scale. Three cognition function tests were also performed, then multivariable ordinal regression and logistic regression were used to identify the associations between cognitive performance and the Fazekas scale.

RESULTS

There were inverse associations between the three cognitive function tests across the Fazekas scale of PVWMHs (p = .037, .006, and .008 for MMSE, MoCA, and CASI, respectively), but the associations were attenuated in the DWMHs group. In CASI, significant differences were identified in short-term memory, mental manipulation, abstract thinking, language, spatial construction, and name fluency in the PVWMHs group. However, DWMHs were only significantly correlated with abstract thinking and short-term memory.

CONCLUSION

An inverse correlation existed between the Fazekas scale, predominantly in PVWMHs, and cognition in patients undergoing HD. The PVWMHs were associated with cognitive performance assessed by MMSE, MoCA, and CASI, as well as with subdomains of CASI such as memory, language and name fluency in patients undergoing HD.

Brain-Derived neurotrophic factor and inflammatory biomarkers are unaffected by acute and chronic intermittent hypoxic-hyperoxic exposure in geriatric patients: a randomized controlled trial

BACKGROUND

Animal and human studies have shown that exposure to hypoxia can increase brain-derived neurotrophic factor (BDNF) protein transcription and reduce systematic inflammatory cytokine response. Therefore, the aim of this study was to investigate the acute and chronic effects of intermittent hypoxic-hyperoxic exposure (IHHE) prior to aerobic exercise on BDNF, interleukin-6 (IL-6), and C-reactive protein (CRP) blood levels in geriatric patients.

PATIENTS AND METHODS

Twenty-five geriatric patients (83.1 ± 5.0 yrs, 71.1 ± 10.0 kg, 1.8 ± 0.9 m) participated in a placebo-controlled, single-blinded trial and were randomly assigned to either an intervention (IG) or control group (CG) performing an aerobic cycling training (17 sessions, 20 min·session-1, 3 sessions·week-1). Prior to aerobic cycling exercise, the IG was additionally exposed to IHHE for 30 min, whereas the CG received continuous normoxic air. Blood samples were taken immediately before (pre-exercise) and 10 min (post-exercise) after the first session as well as 48 h (post-training) after the last session to determine serum (BDNFS) and plasma BDNF (BDNFP), IL-6, and CRP levels. Intervention effects were analyzed using a 2 x 2 analysis of covariance with repeated measures. Results were interpreted based on effect sizes with a medium effect considered as meaningful (ηp2 ≥ 0.06, d ≥ 0.5).

RESULTS

CRP was moderately higher (d = 0.51) in the CG compared to the IG at baseline. IHHE had no acute effect on BDNFS (ηp2 = 0.01), BDNFP (ηp2 < 0.01), BDNF serum/plasma-ratio (ηp2 < 0.01), IL-6 (ηp2 < 0.01), or CRP (ηp2 = 0.04). After the 6-week intervention, an interaction was found for BDNF serum/plasma-ratio (ηp2 = 0.06) but not for BDNFS (ηp2 = 0.04), BDNFP (ηp2 < 0.01), IL-6 (ηp2 < 0.01), or CRP (ηp2 < 0.01). BDNF serum/plasma-ratio increased from pre-exercise to post-training (d = 0.67) in the CG compared to the IG (d = 0.51). A main effect of time was found for BDNFP (ηp2 = 0.09) but not for BDNFS (ηp2 = 0.02). Within-group post-hoc analyses revealed a training-related reduction in BDNFP in the IG and CG by 46.1% (d = 0.73) and 24.7% (d = 0.57), respectively.

CONCLUSION

The addition of 30 min IHHE prior to 20 min aerobic cycling seems not to be effective to increase BDNFS and BDNFP or to reduce IL-6 and CRP levels in geriatric patients after a 6-week intervention.The study was retrospectively registered at drks.de (DRKS-ID: DRKS00025130).

Eye-tracking measurement of attention bias to social threat among youth: A replication and extension study

Attentional bias to social threat cues has been linked to heightened anxiety and irritability in youth. Yet, inconsistent methodology has limited replication and led to mixed findings. The current study aims to 1) replicate and extend two previous pediatric studies demonstrating a relationship between negative affectivity and attentional bias to social threat and 2) examine the test-retest reliability of an eye-tracking paradigm among a subsample of youth. Attention allocation to negative versus non-negative emotional faces was measured using a free-viewing eye-tracking task among youth (N=185 total, 60% female, M age=13.10 years, SD age=2.77) with three face-pair conditions: happy-angry, neutral-disgust, sad-happy. Replicating procedures of two previous studies, linear mixed-effects models compared attention bias between children with anxiety disorders and healthy controls. Bifactor analysis was used to parse shared versus unique facets of general negative affectivity (i.e., anxiety, irritability), which were then examined in relation to attention bias. Test-retest reliability of the bias-index was estimated among a subsample of youth (N=36). No significant differences in attention allocation or bias emerged between anxiety and healthy control groups. While general negative affectivity across the sample was not associated with attention bias, there was a positive relationship for anxiety and irritability on duration of attention allocation toward negative faces. Test-retest reliability for attention bias was moderate (r=0.50, p<.01). While anxiety-related findings from the two previous studies were not replicated, the relationship between attention bias and facets of negative affect suggests a potential target for treatment. Evidence for test-retest reliability encourages future use of the eye-tracking task for researchers.

Different baseline functional patterns of the frontal cortex in amyotrophic lateral sclerosis patients with Corticospinal tract hyperintensity

Nearly half of the amyotrophic lateral sclerosis (ALS) patients showed hyperintensity of the corticospinal tract (CST+), yet whether brain functional pattern differs between CST+and CST- patients remains obscure. In the current study, 19 ALS CST+, 41 ALS CST- patients and 37 healthy controls (HC) underwent resting state fMRI scans. We estimated local activity and connectivity patterns via the Amplitude of Low Frequency Fluctuations (ALFF) and the Network-Based Statistic (NBS) approaches respectively. The ALS CST+patients did not differ from the CST- patients in amyotrophic lateral sclerosis functional rating scale revised (ALSFRS-R) score and disease duration. ALFF of the superior frontal gyrus (SFG) and the inferior frontal gyrus pars opercularis (OIFG) were highest in the HC and lowest in the ALS CST- patients, resulting in significant group differences (PFWE<0.05). NBS analysis revealed a frontal network consisting of connections between SFG, OIFG, orbital frontal gyrus, middle cingulate cortex and the basal ganglia, which exhibited HC>ALS CST+ > ALS CST- group differences (PFWE=0.037) as well. The ALFF of the OIFG was significantly correlated with ALSFRS-R (R=0.34, P=0.028) and mean connectivity of the frontal network was trend-wise significantly correlated with disease duration (R=-0.31, P=0.052) in the ALS CST- patients. However, these correlations were insignificant in ALS CST+patients (P values > 0.8). In conclusion, The ALS CST+patients exhibited different patterns of baseline functional activity and connectivity in the frontal cortex which may indicate a functional compensatory effect.

Cortical morphological alterations in cognitively normal Parkinson's disease with severe hyposmia

Olfactory dysfunction is a common non-motor symptom of Parkinson's disease(PD) and may hold valuable insights into the disease's underlying pathophysiology. This study aimed to investigate cortical morphometry alterations in PD patients with severe hyposmia(PD-SH) and mild hyposmia(PD-MH) using surface-based morphometry(SBM) methods. Participants included 36 PD-SH patients, 38 PD-MH patients, and 40 healthy controls(HCs). SBM analysis revealed distinct patterns of cortical alterations in PD-SH and PD-MH patients. PD-MH patients exhibited reduced cortical thickness in the right supramarginal gyrus, while PD-SH patients showed widespread cortical thinning in regions including the bilateral pericalcarine cortex, bilateral lingual gyrus, left inferior parietal cortex, left lateral occipital cortex, right pars triangularis, right cuneus, and right superior parietal cortex. Moreover, PD-SH patients displayed reduced cortical thickness in the right precuneus compared to PD-MH patients. Fractal dimension analysis indicated increased cortical complexity in PD-MH patients' right superior temporal cortex and right supramarginal gyrus, as well as decreased complexity in the bilateral postcentral cortex, left superior parietal cortex, and right precentral cortex. Similarly, cortical gyrification index and cortical sulcal depth exhibited heterogeneous patterns of changes in PD-SH and PD-MH patients compared to HCs. These findings underscore the multifaceted nature of olfactory impairment in PD, with distinct patterns of cortical morphometry alterations associated with different degrees of hyposmia. The observed discrepancies in brain regions showing alterations reflect the complexity of PD's pathophysiology. These insights contribute to a deeper understanding of olfactory dysfunction in PD and provide potential avenues for early diagnosis and targeted interventions.

Accelerating multipool CEST MRI of Parkinson's disease using deep learning-based Z-spectral compressed sensing

PURPOSE

To develop a deep learning-based approach to reduce the scan time of multipool CEST MRI for Parkinson's disease (PD) while maintaining sufficient prediction accuracy.

METHOD

A deep learning approach based on a modified one-dimensional U-Net, termed Z-spectral compressed sensing (CS), was proposed to recover dense Z-spectra from sparse ones. The neural network was trained using simulated Z-spectra generated by the Bloch equation with various parameter settings. Its feasibility and effectiveness were validated through numerical simulations and in vivo rat brain experiments, compared with commonly used linear, pchip, and Lorentzian interpolation methods. The proposed method was applied to detect metabolism-related changes in the 6-hydroxydopamine PD model with multipool CEST MRI, including APT, CEST@2 ppm, nuclear Overhauser enhancement, direct saturation, and magnetization transfer, and the prediction performance was evaluated by area under the curve.

RESULTS

The numerical simulations and in vivo rat-brain experiments demonstrated that the proposed method could yield superior fidelity in retrieving dense Z-spectra compared with existing methods. Significant differences were observed in APT, CEST@2 ppm, nuclear Overhauser enhancement, and direct saturation between the striatum regions of wild-type and PD models, whereas magnetization transfer exhibited no significant difference. Receiver operating characteristic analysis demonstrated that multipool CEST achieved better predictive performance compared with individual pools. Combined with Z-spectral CS, the scan time of multipool CEST MRI can be reduced to 33% without distinctly compromising prediction accuracy.

CONCLUSION

The integration of Z-spectral CS with multipool CEST MRI can enhance the prediction accuracy of PD and maintain the scan time within a reasonable range.

Convergence and divergence in neurostructural signatures of unipolar and bipolar depressions: Insights from surface-based morphometry and prospective follow-up

BACKGROUND

Bipolar disorder (BD) is often misidentified as unipolar depression (UD) during its early stages, typically until the onset of the first manic episode. This study aimed to explore both shared and unique neurostructural changes in patients who transitioned from UD to BD during follow-up, as compared to those with UD.

METHODS

This study utilized high-resolution structural magnetic resonance imaging (MRI) to collect brain data from individuals initially diagnosed with UD. During the average 3-year follow-up, 24 of the UD patients converted to BD (cBD). For comparison, the study included 48 demographically matched UD patients who did not convert and 48 healthy controls. The MRI data underwent preprocessing using FreeSurfer, followed by surface-based morphometry (SBM) analysis to identify cortical thickness (CT), surface area (SA), and cortical volume (CV) among groups.

RESULTS

The SBM analysis identified shared neurostructural characteristics between the cBD and UD groups, specifically thinner CT in the right precentral cortex compared to controls. Unique to the cBD group, there was a greater SA in the right inferior parietal cortex compared to the UD group. Furthermore, no significant correlations were observed between cortical morphological measures and cognitive performance and clinical features in the cBD and UD groups.

LIMITATIONS

The sample size is relatively small.

CONCLUSIONS

Our findings suggest that while cBD and UD exhibit some common alterations in cortical macrostructure, numerous distinct differences are also present. These differences offer valuable insights into the neuropathological underpinnings that distinguish these two conditions.

Training individuals with schizophrenia to gain volitional control of the theory of mind network with real-time fMRI: A pilot study

Individuals diagnosed with schizophrenia spectrum disorders (SSDs) often demonstrate alterations in the Theory of Mind Network (ToM-N). Here, in this proof-of-concept, single-arm pilot study, we investigate whether participants with an SSD (N = 7) were able to learn to volitionally control regions of the ToM-N (dorso/middle/ventromedial prefrontal cortex [D/M/VMPFC], left temporoparietal junction [LTPJ], precuneus [PC], right superior temporal sulcus [RSTS], and right temporoparietal junction [RTPJ]) using real-time fMRI neurofeedback (rtfMRI-NF). Region-of-interest analyses demonstrate that after neurofeedback training, participants were able to gain volitional control in the following ToM-N brain regions during the transfer task, where no active feedback was given: right temporoparietal junction, precuneus, and dorso/ventromedial prefrontal cortex (neurofeedback effect Fs > 6.17, ps < .05). These findings suggest that trained volitional control over the ToM-N is tentatively feasible with rtfMRI neurofeedback in SSD, although findings need to be replicated with more robust designs that include a control group and larger samples.

Pixel-wise annotation for clear and contaminated regions segmentation in wireless capsule endoscopy images: A multicentre database

Wireless capsule endoscopy (WCE) is capable of non-invasively visualizing the small intestine, the most complicated segment of the gastrointestinal tract, to detect different types of abnormalities. However, its main drawback is reviewing the vast number of captured images (more than 50,000 frames). The recorded images are only sometimes clear, and different contaminating agents, such as turbid materials and air bubbles, degrade the visualization quality of the WCE images. This condition could cause serious problems such as reducing mucosal view visualization, prolonging recorded video reviewing time, and increasing the risks of missing pathology. On the other hand, accurately quantifying the amount of turbid fluids and bubbles can indicate potential motility malfunction. To assist in developing computer vision-based techniques, we have constructed the first multicentre publicly available clear and contaminated annotated dataset by precisely segmenting 17,593 capsule endoscopy images from three different databases. In contrast to the existing datasets, our dataset has been annotated at the pixel level, discriminating the clear and contaminated regions and subsequently differentiating bubbles and turbid fluids from normal tissue. To create the dataset, we first selected all of the images (2906 frames) in the reduced mucosal view class covering different levels of contamination and randomly selected 12,237 images from the normal class of the copyright-free CC BY 4.0 licensed small bowel capsule endoscopy (SBCE) images from the Kvasir capsule endoscopy database. To mitigate the possible available bias in the mentioned dataset and to increase the sample size, the number of 2077 and 373 images have been stochastically chosen from the SEE-AI project and CECleanliness datasets respectively for the subsequent annotation. Randomly selected images have been annotated with the aid of ImageJ and ITK-SNAP software under the supervision of an expert SBCE reader with extensive experience in gastroenterology and endoscopy. For each image, two binary and tri-colour ground truth (GT) masks have been created in which each pixel has been indexed into two classes (clear and contaminated) and three classes (bubble, turbid fluids, and normal), respectively. To the best of the author's knowledge, there is no implemented clear and contaminated region segmentation on the capsule endoscopy reading software. Curated multicentre dataset can be utilized to implement applicable segmentation algorithms for identification of clear and contaminated regions and discrimination bubbles, as well as turbid fluids from normal tissue in the small intestine. Since the annotated images belong to three different sources, they provide a diverse representation of the clear and contaminated patterns in the WCE images. This diversity is valuable for training the models that are more robust to variations in data characteristics and can generalize well across different subjects and settings. The inclusion of images from three different centres allows for robust cross-validation opportunities, where computer vision-based models can be trained on one centre's annotated images and evaluated on others.

Phase stabilization with motion compensated diffusion weighted imaging

PURPOSE

Diffusion encoding gradient waveforms can impart intra-voxel and inter-voxel dephasing owing to bulk motion, limiting achievable signal-to-noise and complicating multishot acquisitions. In this study, we characterize improvements in phase consistency via gradient moment nulling of diffusion encoding waveforms.

METHODS

Healthy volunteers received neuro (N = 10 $$ N=10 $$ ) and cardiac (N = 10 $$ N=10 $$ ) MRI. Three gradient moment nulling levels were evaluated: compensation for position (M 0 $$ {M}_0 $$ ), position + velocity (M 1 $$ {M}_1 $$ ), and position + velocity + acceleration (M 1 + M 2 $$ {M}_1+{M}_2 $$ ). Three experiments were completed: (Exp-1) Fixed Trigger Delay Neuro DWI; (Exp-2) Mixed Trigger Delay Neuro DWI; and (Exp-3) Fixed Trigger Delay Cardiac DWI. Significant differences (p < 0 . 05 $$ p<0.05 $$ ) of the temporal phase SD between repeated acquisitions and the spatial phase gradient across a given image were assessed.

RESULTS

M 0 $$ {M}_0 $$ moment nulling was a reference for all measures. In Exp-1, temporal phase SD forG z $$ {G}_z $$ diffusion encoding was significantly reduced withM 1 $$ {M}_1 $$ (35% of t-tests) andM 1 + M 2 $$ {M}_1+{M}_2 $$ (68% of t-tests). The spatial phase gradient was reduced in 23% of t-tests forM 1 $$ {M}_1 $$ and 2% of cases forM 1 + M 2 $$ {M}_1+{M}_2 $$ . In Exp-2, temporal phase SD significantly decreased withM 1 + M 2 $$ {M}_1+{M}_2 $$ gradient moment nulling only forG z $$ {G}_z $$ (83% of t-tests), but spatial phase gradient significantly decreased with onlyM 1 $$ {M}_1 $$ (50% of t-tests). In Exp-3,M 1 + M 2 $$ {M}_1+{M}_2 $$ gradient moment nulling significantly reduced temporal phase SD and spatial phase gradients (100% of t-tests), resulting in less signal attenuation and more accurate ADCs.

CONCLUSION

We characterized gradient moment nulling phase consistency for DWI. Using M1 for neuroimaging and M1 + M2 for cardiac imaging minimized temporal phase SDs and spatial phase gradients.

Neural correlates of anhedonia in young adults with subthreshold depression: A graph theory approach for cortical-subcortical structural covariance

BACKGROUND

Anhedonia is an enduring symptom of subthreshold depression (StD) and predict later onset of major depressive disorder (MDD). Brain structural covariance describes the inter-regional distribution of morphological changes compared to healthy controls (HC) and reflects brain maturation and disease progression. We investigated neural correlates of anhedonia from the structural covariance.

METHODS

T1-weighted brain magnetic resonance images were acquired from 79 young adults (26 StD, 30 MDD, and 23 HC). Intra-individual structural covariance networks of 68 cortical surface area (CSAs), 68 cortical thicknesses (CTs), and 14 subcortical volumes were constructed. Group-level hubs and principal edges were defined using the global and regional graph metrics, compared between groups, and examined for the association with anhedonia severity.

RESULTS

Global network metrics were comparable among the StD, MDD, and HC. StD exhibited lower centralities of left pallidal volume than HC. StD showed higher centralities than HC in the CSAs of right rostral anterior cingulate cortex (ACC) and pars triangularis, and in the CT of left pars orbitalis. Less anhedonia was associated with higher centralities of left pallidum and right amygdala, higher edge betweenness centralities in the structural covariance (EBSC) of left postcentral gyrus-parahippocampal gyrus and LIPL-right amygdala. More anhedonia was associated with higher centralities of left inferior parietal lobule (LIPL), left postcentral gyrus, left caudal ACC, and higher EBSC of LIPL-left postcentral gyrus, LIPL-right lateral occipital gyrus, and left caudal ACC-parahippocampal gyrus.

LIMITATIONS

This study has a cross-sectional design.

CONCLUSIONS

Structural covariance of brain morphologies within the salience and limbic networks, and among the salience-limbic-default mode-somatomotor-visual networks, are possible neural correlates of anhedonia in depression.

Promoting mental health in higher education: towards a model of well-being factors in emerging adulthood

PURPOSE

This study aims to contribute to the development of a theoretical model that is useful for enhancing well-being/positive mental health with pedagogical resources that enable the acquisition of skills and knowledge, particularly during Emerging Adulthood.

METHODS

This paper enquires into the role of well-being promotion in higher education following the dual-factor model of mental health difficulties and wellbeing. The study narratively reviews the main well-being models and presents a compared theoretical synthesis examining the dimensions that promote or facilitate the presence of well-being using a promotion approach.

RESULTS

The study identifies 14 dimensions involved in wellbeing-emotional, psychological and social factors-that can be potentially improved through learning processes. Drawing on empirical and theoretical studies on emerging adult population, a factorial model is proposed. Preliminary factor interactions are examined paying close attention to the cognitive processes that explain or affect their relationship with well-being, the possible correlations between them and particularities of emerging adults.

CONCLUSION

Wellbeing factors can be particularly targeted by educational promotion, as they can be developed through learning processes. An integrative model that provides a broad perspective can assist in pedagogical design and defining educational goals for these learning processes involved in wellbeing promotion.

Epileptic brain network mechanisms and neuroimaging techniques for the brain network

Epilepsy can be defined as a dysfunction of the brain network, and each type of epilepsy involves different brain-network changes that are implicated differently in the control and propagation of interictal or ictal discharges. Gaining more detailed information on brain network alterations can help us to further understand the mechanisms of epilepsy and pave the way for brain network-based precise therapeutic approaches in clinical practice. An increasing number of advanced neuroimaging techniques and electrophysiological techniques such as diffusion tensor imaging-based fiber tractography, diffusion kurtosis imaging-based fiber tractography, fiber ball imaging-based tractography, electroencephalography, functional magnetic resonance imaging, magnetoencephalography, positron emission tomography, molecular imaging, and functional ultrasound imaging have been extensively used to delineate epileptic networks. In this review, we summarize the relevant neuroimaging and neuroelectrophysiological techniques for assessing structural and functional brain networks in patients with epilepsy, and extensively analyze the imaging mechanisms, advantages, limitations, and clinical application ranges of each technique. A greater focus on emerging advanced technologies, new data analysis software, a combination of multiple techniques, and the construction of personalized virtual epilepsy models can provide a theoretical basis to better understand the brain network mechanisms of epilepsy and make surgical decisions.

JOSA: Joint surface-based registration and atlas construction of brain geometry and function

Surface-based cortical registration is an important topic in medical image analysis and facilitates many downstream applications. Current approaches for cortical registration are mainly driven by geometric features, such as sulcal depth and curvature, and often assume that registration of folding patterns leads to alignment of brain function. However, functional variability of anatomically corresponding areas across subjects has been widely reported, particularly in higher-order cognitive areas. In this work, we present JOSA, a novel cortical registration framework that jointly models the mismatch between geometry and function while simultaneously learning an unbiased population-specific atlas. Using a semi-supervised training strategy, JOSA achieves superior registration performance in both geometry and function to the state-of-the-art methods but without requiring functional data at inference. This learning framework can be extended to any auxiliary data to guide spherical registration that is available during training but is difficult or impossible to obtain during inference, such as parcellations, architectonic identity, transcriptomic information, and molecular profiles. By recognizing the mismatch between geometry and function, JOSA provides new insights into the future development of registration methods using joint analysis of brain structure and function.

Associations between PTSD and temporal discounting: The role of future thinking

BACKGROUND AND OBJECTIVES

Despite documented alterations in future thinking in posttraumatic stress disorder (PTSD), our understanding of how individuals with PTSD make future-oriented decisions is limited. We tested the hypothesis that increased discounting in association with PTSD reflects failure to spontaneously envision future rewarding situations.

METHODS

Thirty-seven trauma exposed war-zone veterans completed a standard temporal discounting task as well as a temporal discounting task accompanied by episodic future thinking cues.

RESULTS

Severity of PTSD symptoms was associated with preference for sooner, smaller rewards in the standard task. Consistent with our hypothesis, when participants engaged in future thinking, greater PTSD symptom severity was no longer associated with steeper discounting. Moreover, difficulty anticipating future events, as measured contemporaneously in a separate task (Verfaellie et al., 2024), mediated the relationship between PTSD symptom severity and degree of discounting in the standard task. Among PTSD symptom clusters, the severity of avoidance and negative alterations in cognition and mood was related to steeper discounting. Measures of depression and alcohol use were not associated with discounting.

LIMITATIONS

The sample included mostly male, predominantly White veterans who experienced primarily combat-related trauma.

CONCLUSIONS

PTSD-associated alterations in temporal discounting reflect failure to spontaneously imagine future positive events. Two common correlates of PTSD, depression and alcohol use, could not account for the observed associations between PTSD and future-oriented decisions.

Uncertainties Regarding Cerebral Palsy Diagnosis: Opportunities to Clarify the Consensus Definition

Background and Objectives

We have established that physicians, including neurologists, variably diagnose cerebral palsy (CP) when using the most recent CP definition from 2006. We also know that child neurologists and neurodevelopmentalists view themselves to be optimally suited to diagnose CP based on their training backgrounds. Therefore, to reduce variability in CP diagnosis, our objective was to elucidate uncertainties child neurologists and neurodevelopmentalists may have regarding practical application of the 2006 definition.

Methods

We conducted a cross-sectional survey of child neurologists and neurodevelopmentalists built into a discussion seminar at the 2022 Child Neurology Society (CNS) Annual Meeting, the largest professional meeting of these specialists in North America. Seminar attendees were provided the 2006 definition and asked whether they had any uncertainties about the practical application of the definition across 4 hypothetical clinical vignettes. A group of national and international CP leaders then processed these data through iterative discussions to develop recommendations for clarifying the 2006 definition.

Results

The seminar was attended by 50% of all conference attendees claiming CME (202/401). Of the 164 closing survey respondents, 145 (88%) expressed uncertainty regarding the clinical application of the 2006 definition. These uncertainties focused on 1) age, both regarding the minimum and maximum ages of brain disturbance or motor symptom onset (67/164, 41%), and 2) interpretation of the term "nonprogressive" (48/164, 29%). Almost all respondents (157/164, 96%) felt that we should revise the 2006 consensus definition of CP.

Discussion

To address the most common CP diagnostic uncertainties we identified, we collectively propose 4 points of clarification to the 2006 definition: 1) motor symptoms/signs should be present by 2 years old; 2) CP can and should be diagnosed as early as possible; 3) the clinical motor disability phenotype should be nonprogressive through 5 years old; and 4) a CP diagnosis should be re-evaluated if motor disability is progressive or absent by 5 years old. We anticipate that clarifying the 2006 definition of CP in this manner could address the uncertainties we identified among child neurologists and neurodevelopmentalists and reduce the diagnostic variability that currently exists.

Transcranial ultrafast ultrasound Doppler imaging: A phantom study

Ultrafast ultrasound Doppler imaging facilitates the assessment of cerebral hemodynamics with high spatio-temporal resolution. However, the significant acoustic impedance mismatch between the skull and soft tissue results in phase aberrations, which can compromise the quality of transcranial imaging and introduce biases in velocity and direction quantification of blood flow. This paper proposed an aberration correction method that combines deep learning-based skull sound speed modelling with ray theory to realize transcranial plane-wave imaging and ultrafast Doppler imaging. The method was validated through phantom experiments using a linear array with a center frequency of 6.25 MHz, 128 elements, and a pitch of 0.3 mm. The results demonstrated an improvement in the imaging quality of intracranial targets when using the proposed method. After aberration correction, the average locating deviation decreased from 1.40 mm to 0.27 mm in the axial direction, from 0.50 mm to 0.20 mm in the lateral direction, and the average full-width-at-half-maximum (FWHM) decreased from 1.37 mm to 0.97 mm for point scatterers. For circular inclusions, the average contrast-to-noise ratio (CNR) improved from 8.1 dB to 11.0 dB, and the average eccentricity decreased from 0.36 to 0.26. Furthermore, the proposed method was applied to transcranial ultrafast Doppler flow imaging. The results showed a significant improvement in accuracy and quality for blood Doppler flow imaging. The results in the absence of the skull were considered as the reference, and the average normalized root-mean-square errors of the axial velocity component on the five selected axial profiles were reduced from 17.67% to 8.02% after the correction.

Improved visualization of intracranial distal arteries with multiple 2D slice dynamic ASL-MRA and super-resolution convolutional neural network

PURPOSE

To develop a novel framework to improve the visualization of distal arteries in arterial spin labeling (ASL) dynamic MRA.

METHODS

The attenuation of ASL blood signal due to the repetitive application of excitation RF pulses was minimized by splitting the acquisition volume into multiple thin 2D (M2D) slices, thereby reducing the exposure of the arterial blood magnetization to RF pulses while it flows within the brain. To improve the degraded vessel visualization in the slice direction due to the limited minimum achievable 2D slice thickness, a super-resolution (SR) convolutional neural network (CNN) was trained by using 3D time-of-flight (TOF)-MRA images from a large public dataset. And then, we applied domain transfer from 3D TOF-MRA to M2D ASL-MRA, while avoiding acquiring a large number of ASL-MRA data required for CNN training.

RESULTS

Compared to the conventional 3D ASL-MRA, far more distal arteries were visualized with higher signal intensity by using M2D ASL-MRA. In general, however, the vessel visualization with a conventional interpolation was prone to be blurry and unclear due to the limited spatial resolution in the slice direction, particularly in small vessels. Application of CNN-based SR transferred from 3D TOF-MRA to M2D ASL-MRA successfully addressed such a limitation and achieved clearer visualization of small vessels than conventional interpolation.

CONCLUSION

This study demonstrated that the proposed framework provides improved visualization of distal arteries in later dynamic phases, which will particularly benefit the application of this approach in patients with cerebrovascular disease who have slow blood flow.

Time-division multiplexing (TDM) sequence removes bias in T2 estimation and relaxation-diffusion measurements

PURPOSE

To compare the performance of multi-echo (ME) and time-division multiplexing (TDM) sequences for accelerated relaxation-diffusion MRI (rdMRI) acquisition and to examine their reliability in estimating accurate rdMRI microstructure measures.

METHOD

The ME, TDM, and the reference single-echo (SE) sequences with six TEs were implemented using Pulseq with single-band (SB) and multi-band 2 (MB2) acceleration factors. On a diffusion phantom, the image intensities of the three sequences were compared, and the differences were quantified using the normalized RMS error (NRMSE). Shinnar-Le Roux (SLR) pulses were implemented for the SB-ME and SB-SE sequences to investigate the impact of slice profiles on ME sequences. For the in-vivo brain scan, besides the image intensity comparison and T2-estimates, different methods were used to assess sequence-related effects on microstructure estimation, including the relaxation diffusion imaging moment (REDIM) and the maximum-entropy relaxation diffusion distribution (MaxEnt-RDD).

RESULTS

TDM performance was similar to the gold standard SE acquisition, whereas ME showed greater biases (3-4× larger NRMSEs for phantom, 2× for in-vivo). T2 values obtained from TDM closely matched SE, whereas ME sequences underestimated the T2 relaxation time. TDM provided similar diffusion and relaxation parameters as SE using REDIM, whereas SB-ME exhibited a 60% larger bias in the  map and on average 3.5× larger bias in the covariance between relaxation-diffusion coefficients.

CONCLUSION

Our analysis demonstrates that TDM provides a more accurate estimation of relaxation-diffusion measurements while accelerating the acquisitions by a factor of 2 to 3.

Unraveling contributions to the Z-spectrum signal at 3.5 ppm of human brain tumors

PURPOSE

To evaluate the influence of the confounding factors, direct water saturation (DWS), and magnetization transfer contrast (MTC) effects on measured Z-spectra and amide proton transfer (APT) contrast in brain tumors.

METHODS

High-grade glioma patients were scanned using an RF saturation-encoded 3D MR fingerprinting (MRF) sequence at 3 T. For MRF reconstruction, a recurrent neural network was designed to learn free water and semisolid macromolecule parameter mappings of the underlying multiple tissue properties from saturation-transfer MRF signals. The DWS spectra and MTC spectra were synthesized by solving Bloch-McConnell equations and evaluated in brain tumors.

RESULTS

The dominant contribution to the saturation effect at 3.5 ppm was from DWS and MTC effects, but 25%-33% of the saturated signal in the gadolinium-enhancing tumor (13%-20% for normal tissue) was due to the APT effect. The APT# signal of the gadolinium-enhancing tumor was significantly higher than that of the normal-appearing white matter (10.1% vs. 8.3% at 1 μT and 11.2% vs. 7.8% at 1.5 μT).

CONCLUSION

The RF saturation-encoded MRF allowed us to separate contributions to the saturation signal at 3.5 ppm in the Z-spectrum. Although free water and semisolid MTC are the main contributors, significant APT contrast between tumor and normal tissues was observed.

Dopaminergic system and neurons: Role in multiple neurological diseases

The dopaminergic system is a complex and powerful neurotransmitter system in the brain. It plays an important regulatory role in motivation, reward, cognition, and motor control. In recent decades, research in the field of the dopaminergic system and neurons has increased exponentially and is gradually becoming a point of intervention in the study and understanding of a wide range of neurological diseases related to human health. Studies have shown that the dopaminergic system and neurons are involved in the development of many neurological diseases (including, but not limited to Parkinson's disease, schizophrenia, depression, attention deficit hyperactivity disorder, etc.) and that dopaminergic neurons either have too much stress or too weak function in the dopaminergic system can lead to disease. Therefore, targeting dopaminergic neurons is considered key to treating these diseases. This article provides a comprehensive review of the dopaminergic system and neurons in terms of brain region distribution, physiological function and subtypes of dopaminergic neurons, as well as the role of the dopaminergic system and neurons in a variety of diseases.

Jointly constrained group sparse connectivity representation improves early diagnosis of Alzheimer's disease on routinely acquired T1-weighted imaging-based brain network

Background

Radiomics-based morphological brain networks (radMBN) constructed from routinely acquired structural MRI (sMRI) data have gained attention in Alzheimer's disease (AD). However, the radMBN suffers from limited characterization of AD because sMRI only characterizes anatomical changes and is not a direct measure of neuronal pathology or brain activity.

Purpose

To establish a group sparse representation of the radMBN under a joint constraint of group-level white matter fiber connectivity and individual-level sMRI regional similarity (JCGS-radMBN).

Methods

Two publicly available datasets were adopted, including 120 subjects from ADNI with both T1-weighted image (T1WI) and diffusion MRI (dMRI) for JCGS-radMBN construction, 818 subjects from ADNI and 200 subjects solely with T1WI from AIBL for validation in early AD diagnosis. Specifically, the JCGS-radMBN was conducted by jointly estimating non-zero connections among subjects, with the regularization term constrained by group-level white matter fiber connectivity and individual-level sMRI regional similarity. Then, a triplet graph convolutional network was adopted for early AD diagnosis. The discriminative brain connections were identified using a two-sample t-test, and the neurobiological interpretation was validated by correlating the discriminative brain connections with cognitive scores.

Results

The JCGS-radMBN exhibited superior classification performance over five brain network construction methods. For the typical NC vs. AD classification, the JCGS-radMBN increased by 1-30% in accuracy over the alternatives on ADNI and AIBL. The discriminative brain connections exhibited a strong connectivity to hippocampus, parahippocampal gyrus, and basal ganglia, and had significant correlation with MMSE scores.

Conclusion

The proposed JCGS-radMBN facilitated the AD characterization of brain network established on routinely acquired imaging modality of sMRI.

Supplementary Information

The online version of this article (10.1007/s13755-023-00269-0) contains supplementary material, which is available to authorized users.

Metadata-conditioned generative models to synthesize anatomically-plausible 3D brain MRIs

Recent advances in generative models have paved the way for enhanced generation of natural and medical images, including synthetic brain MRIs. However, the mainstay of current AI research focuses on optimizing synthetic MRIs with respect to visual quality (such as signal-to-noise ratio) while lacking insights into their relevance to neuroscience. To generate high-quality T1-weighted MRIs relevant for neuroscience discovery, we present a two-stage Diffusion Probabilistic Model (called BrainSynth) to synthesize high-resolution MRIs conditionally-dependent on metadata (such as age and sex). We then propose a novel procedure to assess the quality of BrainSynth according to how well its synthetic MRIs capture macrostructural properties of brain regions and how accurately they encode the effects of age and sex. Results indicate that more than half of the brain regions in our synthetic MRIs are anatomically plausible, i.e., the effect size between real and synthetic MRIs is small relative to biological factors such as age and sex. Moreover, the anatomical plausibility varies across cortical regions according to their geometric complexity. As is, the MRIs generated by BrainSynth significantly improve the training of a predictive model to identify accelerated aging effects in an independent study. These results indicate that our model accurately capture the brain's anatomical information and thus could enrich the data of underrepresented samples in a study. The code of BrainSynth will be released as part of the MONAI project at https://github.com/Project-MONAI/GenerativeModels.

Modern methods of neuroanatomical and neurophysiological research

Our article explores a variety of modern research techniques employed in neuroanatomy and neurophysiology. We highlight the use of computer technologies, image analysis methods, and innovative approaches that expand our understanding of anatomical structures. The techniques we discuss include fractal analysis, the Pickworth method, scanning microscopy, and advanced computer image processing systems. Fractal analysis, in particular, offers a unique perspective on brain structures and functions and is a key tool in neuroanatomical research. We also focus on its application in neuroanatomical studies, particularly in cases of Alzheimer's disease and epilepsy. These modern research methods not only enhance our knowledge but also have significant clinical potential. Their use in diagnosing neurological diseases like Alzheimer's and epilepsy promises faster and more accurate diagnoses. We emphasize the combination of multiple methods for improved quality of anatomical structure imaging.

Oligodendrocyte-specific expression of PSG8-AS1 suggests a role in myelination with prognostic value in oligodendroglioma

The segmentally duplicated Pregnancy-specific glycoprotein (PSG) locus on chromosome 19q13 may be one of the most rapidly evolving in the human genome. It comprises ten coding genes (PSG1-9, 11) and one predominantly non-coding gene (PSG10) that are expressed in the placenta and gut, in addition to several poorly characterized long non-coding RNAs. We report that long non-coding RNA PSG8-AS1 has an oligodendrocyte-specific expression pattern and is co-expressed with genes encoding key myelin constituents. PSG8-AS1 exhibits two peaks of expression during human brain development coinciding with the most active periods of oligodendrogenesis and myelination. PSG8-AS1 orthologs were found in the genomes of several primates but significant expression was found only in the human, suggesting a recent evolutionary origin of its proposed role in myelination. Additionally, because co-deletion of chromosomes 1p/19q is a genomic marker of oligodendroglioma, expression of PSG8-AS1 was examined in these tumors. PSG8-AS1 may be a promising diagnostic biomarker for glioma, with prognostic value in oligodendroglioma.

Dissociation of focal and large-scale inhibitory functions in the older adults: A multimodal MRI study

BACKGROUND

The decline of inhibitory in cognitive aging is linked to reduced cognitive and mental capacities in older adults. However, this decline often shows inconsistent clinical presentations, suggesting varied impacts on different inhibition-related tasks. Inhibitory control, a multifaceted construct, involves various types of inhibition. Understanding these components is crucial for comprehending how aging affects inhibitory functions. Our research investigates the influences of aging on large-scale and focal-scale inhibitory and examines the relationship with brain markers.

METHODS

We examined the impact of aging on inhibitory in 18 younger (20-35 years) and 17 older adults (65-85 years) using focal and large-scale inhibition tasks. The Gabor task assessed focal-scale inhibition, while the Stop Signal Task (SST) evaluated large-scale inhibition. Participants underwent neuropsychological assessments and MRI scans, including magnetic resonance spectroscopy (MRS) and structural and resting fMRI.

RESULTS

Older adults exhibited a marked decline in inhibitory function, with slower SST responses indicating compromised large-scale inhibition. Conversely, the Gabor task showed no significant age-related changes. MRS findings revealed decreased levels of GABA, glutamate, glutamine, and NAA in the pre-SMA, correlating with observed large-scale inhibition in older adults. Additionally, pre-SMA seed-based functional connectivity analysis showed reduced brain network connections in older adults, potentially contributing to inhibitory control deficits.

CONCLUSIONS

Our study elucidates the differential effects of aging on inhibitory functions. While large-scale inhibition is more vulnerable to aging, focal-scale inhibition is relatively preserved. These findings highlight the importance of targeted cognitive interventions and underscore the necessity of a multifaceted approach in aging research.

Inflammation-related abnormal dynamic brain activity correlates with cognitive impairment in first-episode, drug-naïve major depressive disorder

BACKGROUND

Cognitive impairment is common in major depressive disorder (MDD) and potentially linked to inflammation-induced alterations in brain function. However, the relationship between inflammation, dynamic brain activity, and cognitive impairment in MDD remains unclear.

METHODS

Fifty-seven first-episode, drug-naïve MDD patients and sixty healthy controls underwent fMRI scanning. Dynamic amplitude of low-frequency fluctuations (dALFF) and dynamic functional connectivity (dFC) were measured using the sliding window method. Plasma IL - 6 levels and cognitive function were assessed using enzyme-linked immunosorbent assay (ELISA) and the Repeated Battery for Assessment of Neuropsychological Status (RBANS), respectively.

RESULTS

MDD patients exhibited decreased dALFF in the bilateral inferior temporal gyrus (ITG), right inferior frontal gyrus, opercular part (IFGoperc), and bilateral middle occipital gyrus (MOG). Regions of dALFF associated with IL-6 included right ITG (r = -0.400/p = 0.003), left ITG (r = -0.381/p = 0.004), right IFGoperc (r = -0.342/p = 0.011), and right MOG (r = -0.327/p = 0.016). Furthermore, IL-6-related abnormal dALFF (including right ITG: r = 0.309/p = 0.023, left ITG: r = 0.276/p = 0.044) was associated with attention impairment. These associations were absent entirely in MDD patients without suicidal ideation. Additionally, IL-6 levels were correlated with dFC of specific brain regions.

LIMITATIONS

Small sample size and cross-sectional study design.

CONCLUSIONS

Inflammation-related dALFF was associated with attention impairment in MDD patients, with variations observed among MDD subgroups. These findings contribute to the understanding of the intricate relationship between inflammation, dynamic brain activity and cognitive impairments in MDD.

Functional benefits of continuous vs. categorical listening strategies on the neural encoding and perception of noise-degraded speech

Acoustic information in speech changes continuously, yet listeners form discrete perceptual categories to ease the demands of perception. Being a more continuous/gradient as opposed to a more discrete/categorical listener may be further advantageous for understanding speech in noise by increasing perceptual flexibility and resolving ambiguity. The degree to which a listener's responses to a continuum of speech sounds are categorical versus continuous can be quantified using visual analog scaling (VAS) during speech labeling tasks. Here, we recorded event-related brain potentials (ERPs) to vowels along an acoustic-phonetic continuum (/u/ to /a/) while listeners categorized phonemes in both clean and noise conditions. Behavior was assessed using standard two alternative forced choice (2AFC) and VAS paradigms to evaluate categorization under task structures that promote discrete vs. continuous hearing, respectively. Behaviorally, identification curves were steeper under 2AFC vs. VAS categorization but were relatively immune to noise, suggesting robust access to abstract, phonetic categories even under signal degradation. Behavioral slopes were correlated with listeners' QuickSIN scores; shallower slopes corresponded with better speech in noise performance, suggesting a perceptual advantage to noise degraded speech comprehension conferred by a more gradient listening strategy. At the neural level, P2 amplitudes and latencies of the ERPs were modulated by task and noise; VAS responses were larger and showed greater noise-related latency delays than 2AFC responses. More gradient responders had smaller shifts in ERP latency with noise, suggesting their neural encoding of speech was more resilient to noise degradation. Interestingly, source-resolved ERPs showed that more gradient listening was also correlated with stronger neural responses in left superior temporal gyrus. Our results demonstrate that listening strategy modulates the categorical organization of speech and behavioral success, with more continuous/gradient listening being advantageous to sentential speech in noise perception.

Physics-guided self-supervised learning for retrospective T1 and T2 mapping from conventional weighted brain MRI: Technical developments and initial validation in glioblastoma

PURPOSE

To develop a self-supervised learning method to retrospectively estimate T1 and T2 values from clinical weighted MRI.

METHODS

A self-supervised learning approach was constructed to estimate T1, T2, and proton density maps from conventional T1- and T2-weighted images. MR physics models were employed to regenerate the weighted images from the network outputs, and the network was optimized based on loss calculated between the synthesized and input weighted images, alongside additional constraints based on prior information. The method was evaluated on healthy volunteer data, with conventional mapping as references. The reproducibility was examined on two 3.0T scanners. Performance in tumor characterization was inspected by applying the method to a public glioblastoma dataset.

RESULTS

For T1 and T2 estimation from three weighted images (T1 MPRAGE, T1 gradient echo sequences, and T2 turbo spin echo), the deep learning method achieved global voxel-wise error ≤9% in brain parenchyma and regional error ≤12.2% in six types of brain tissues. The regional measurements obtained from two scanners showed mean differences ≤2.4% and correlation coefficients >0.98, demonstrating excellent reproducibility. In the 50 glioblastoma patients, the retrospective quantification results were in line with literature reports from prospective methods, and the T2 values were found to be higher in tumor regions, with sensitivity of 0.90 and specificity of 0.92 in a voxel-wise classification task between normal and abnormal regions.

CONCLUSION

The self-supervised learning method is promising for retrospective T1 and T2 quantification from clinical MR images, with the potential to improve the availability of quantitative MRI and facilitate brain tumor characterization.

Exercise training and chronic kidney disease: characterization and bibliometrics of citation classics of clinical intervention trials

BACKGROUND

Exercise research targeting chronic kidney disease (CKD) has been conducted for more than 30 years, and the benefits of exercise for CKD patients have been progressively demonstrated. This study analyzes citation classics on clinical intervention trials on exercise training and CKD to describe the research landscape and hotspots through bibliometric analysis.

METHODS

To identify clinical trials of exercise training interventions for CKD with more than 100 citations from the Web of Science Core Collection database. Extracted bibliometric information, participant information, and study characteristics of the included articles. The total citations, annual average citations, publication of year, author keywords, and study-related data were bibliometric analyzed and described using Excel 2019 and VOSviewer software.

RESULTS

A total of 30 citation classics were included, with a total citation frequency of 102 to 279 (mean ± standard deviation: 148.4 ± 49.4). The American Journal of Kidney Diseases (n = 7) published the most (n = 7) classic citations in the field of CKD exercise research, and the Journal of the American Society of Nephrology was the most cited. The hotspot of research around CKD and exercise training interventions focused on population (hemodialysis and end-stage renal disease), exercise type (resistance training, yoga, and leg-cycling), and outcomes (cardiovascular indices, physical performance, psychological status, kidney function, physical activity). Reported dropout rates ranged from 0.0% to 47.4%.

CONCLUSION

A bibliometric analysis of citation classics on exercise training and CKD highlights the potential benefits of exercise as a non-pharmacological therapy for patients with CKD, as well as developments and hotspots in the field.

Visual effects on tactile stimulation and its perception: A pilot study using near-infrared spectroscopy

In rubber hand illusion, visual information affects tactile information, whereas in the mirror box illusion, visual information has the opposite effect. However, its underlying mechanisms are not fully understood. As one of the reasons, non-invasive neuroimaging techniques, such as functional magnetic resonance, positron emission tomography, and electroencephalography, often fail to detect complex and fragile responses in the sensory-motor cortex. Using near-infrared spectroscopy (NIRS), we examined neural activity during tactile tracing on a sine-shaped acrylic board to investigate the effects of (1) visual information and (2) the spatial frequency of the sine shape on brain activity. We used spatial frequencies of 2-3 and 20-30 Hz as low- and high-tactile stimuli, respectively. Two types of experiments, with and without an acrylic board, were conducted. Participants performed the tracing tasks with their index finger at 1 Hz of temporal frequency of a 200 mm length of the acrylic board as main tasks and only space moving without touching as a control task. We show effect of visual information on neural activation, including not only activation intensity but also activation patterns.•Testing of mutual effects of vision and haptics.•Testing of sensory-motor paradox using NIRS.•A high NIRS sensitivity to stimulus-induced hemodynamic change.

Glymphatic system: a gateway for neuroinflammation

The glymphatic system is a relatively recently identified fluid exchange and transport system in the brain. Accumulating evidence indicates that glymphatic function is impaired not only in central nervous system disorders but also in systemic diseases. Systemic diseases can trigger the inflammatory responses in the central nervous system, occasionally leading to sustained inflammation and functional disturbance of the central nervous system. This review summarizes the current knowledge on the association between glymphatic dysfunction and central nervous system inflammation. In addition, we discuss the hypothesis that disease conditions initially associated with peripheral inflammation overwhelm the performance of the glymphatic system, thereby triggering central nervous system dysfunction, chronic neuroinflammation, and neurodegeneration. Future research investigating the role of the glymphatic system in neuroinflammation may offer innovative therapeutic approaches for central nervous system disorders.

The unique face of comorbid anxiety and depression: Increased frontal, insula and cingulate cortex response during Pavlovian fear-conditioning

BACKGROUND

Dysregulation of fear processing through altered sensitivity to threat is thought to contribute to the development of anxiety disorders and major depressive disorder (MDD). However, fewer studies have examined fear processing in MDD than in anxiety disorders. The current study used propensity matching to examine the hypothesis that comorbid MDD and anxiety (AnxMDD) shows greater neural correlates of fear processing than MDD, suggesting that the co-occurrence of AnxMDD is exemplified by exaggerated defense related processes.

METHODS

195 individuals with MDD (N = 65) or AnxMDD (N = 130) were recruited from the community and completed multi-level assessments, including a Pavlovian fear learning task during functional imaging. Visual images paired with threat (conditioned stimuli: CS+) were compared to stimuli not paired with threat (CS-).

RESULTS

MDD and AnxMDD showed significantly different patterns of activation for CS+ vs CS- in the dorsal anterior insula/inferior frontal gyrus (partial eta squared; ηp2 = 0.02), dorsolateral prefrontal cortex (ηp2 = 0.01) and dorsal anterior/mid cingulate cortex (ηp2 = 0.01). These differences were driven by greater activation to the CS+ in AnxMDD versus MDD.

LIMITATIONS

Limitations include the cross-sectional design, a scream US rather than shock and half the number of MDD as AnxMDD participants.

CONCLUSIONS

AnxMDD showed a pattern of increased activation in regions identified with fear processing. Effects were consistently driven by threat, further suggesting fear signaling as the emergent target process. Differences emerged in regions associated with salience processing, attentional orienting/conflict, self-relevant processing and executive functioning in comorbid anxiety and depression, thereby highlighting potential treatment targets for this prevalent and treatment resistant group.

Anhedonia is associated with higher functional connectivity between the nucleus accumbens and paraventricular nucleus of thalamus

BACKGROUND

Anhedonia stands as a life-threatening transdiagnostic feature of many mental illnesses, most notably major depression and involves neural circuits for processing reward information. The paraventricular nucleus of the thalamus (PVT) is associated with reward-seeking behavior, however, links between the PVT circuit and anhedonia have not been investigated in humans.

METHODS

In a sample of adults with and without psychiatric symptoms (n = 75, 18-41 years, 55 female), we generated an anhedonia factor score for each participant using a latent factor analysis, utilizing data from depression and anxiety assessments. Functional connectivity between the PVT and the nucleus accumbens (NAc) was calculated from high-resolution (1.5 mm) resting state fMRI.

RESULTS

Anhedonia factor scores showed a positive relationship with functional connectivity between the PVT and the NAc, principally in males and in those with psychiatric symptoms. In males, connectivity between other midline thalamic nuclei and the NAc did not show these relationships, suggesting that this link may be specific to PVT.

LIMITATIONS

This cohort was originally recruited to study depression and not anhedonia per se. The distribution of male and female participants in our cohort was not equal. Partial acquisition in high-resolution fMRI scans restricted regions of interest outside of the thalamus and reward networks.

CONCLUSIONS

We report evidence that anhedonia is associated with enhanced functional connectivity between the PVT and the NAc, regions that are relevant to reward processing. These results offer clues as to the potential prevention and prevention and treatment of anhedonia.

Improved gradient echo magnitude- and phase-based mapping of T 2 $$ {\mathrm{T}}_2 $$ using multiple RF spoiling increments at 3T and 7T

PURPOSE

The transverse relaxation time T  2 $$ {}_2 $$ holds significant relevance in clinical applications and research studies. Conventional T  2 $$ {}_2 $$ mapping approaches rely on spin-echo sequences, which require lengthy acquisition times and involve high radiofrequency (RF) power deposition. An alternative gradient echo (GRE) phase-based T  2 $$ {}_2 $$ mapping method, utilizing steady-state acquisitions at one small RF spoil phase increment, was recently demonstrated. Here, a modified magnitude- and phase-based T  2 $$ {}_2 $$ mapping approach is proposed, which improvesT 2 $$ {\mathrm{T}}_2 $$ estimations by simultaneous fitting ofT 1 $$ {\mathrm{T}}_1 $$ and signal amplitude (A ∝ P D $$ A\propto PD $$ ) at three or more RF spoiling phase increments, instead of assuming a fixedT 1 $$ {\mathrm{T}}_1 $$ value.

METHODS

The feasibility of the magnitude-phase-based method was assessed by simulations, in phantom and in vivo experiments using skipped-CAIPI three-dimensional-echo-planar imaging (3D-EPI) for rapid GRE imaging.T 2 $$ {\mathrm{T}}_2 $$ ,T 1 $$ {\mathrm{T}}_1 $$ and PD estimations obtained by our method were compared toT 2 $$ {\mathrm{T}}_2 $$ of the phase-based method andT 1 $$ {\mathrm{T}}_1 $$ and PD of spoiled GRE-based multi-parameter mapping using a multi-echo version of the same sequence.

RESULTS

The agreement of the proposedT 2 $$ {\mathrm{T}}_2 $$ with ground truth and referenceT 2 $$ {\mathrm{T}}_2 $$ values was higher than that of phase-basedT 2 $$ {\mathrm{T}}_2 $$ in simulations and in phantom data. While phase-basedT 2 $$ {\mathrm{T}}_2 $$ overestimation increases with actualT 2 $$ {\mathrm{T}}_2 $$ andT 1 $$ {\mathrm{T}}_1 $$ , the proposed method is accurate over a large range of physiologically meaningfulT 2 $$ {\mathrm{T}}_2 $$ andT 1 $$ {\mathrm{T}}_1 $$ values. At the same time, precision is improved. In vivo results were in line with these observations.

CONCLUSION

Accurate magnitude-phase-based T  2 $$ {}_2 $$ mapping is feasible in less than 5 min scan time for 1 mm nominal isotropic whole-head coverage at 3T and 7T.

Integrated approach to reducing polypharmacy in older people: exploring the role of oxidative stress and antioxidant potential therapy

Increased life expectancy, attributed to improved access to healthcare and drug development, has led to an increase in multimorbidity, a key contributor to polypharmacy. Polypharmacy is characterised by its association with a variety of adverse events in the older persons. The mechanisms involved in the development of age-related chronic diseases are largely unknown; however, altered redox homeostasis due to ageing is one of the main theories. In this context, the present review explores the development and interaction between different age-related diseases, mainly linked by oxidative stress. In addition, drug interactions in the treatment of various diseases are described, emphasising that the holistic management of older people and their pathologies should prevail over the individual treatment of each condition.

Contralateral renal change in a unilateral ureteral obstruction rat model using intravoxel incoherent motion diffusion-weighted imaging

OBJECTIVES

Most functional magnetic resonance research has primarily examined alterations in the affected kidney, often neglecting the contralateral kidney. Our study aims to investigate whether imaging parameters accurately depict changes in both the renal cortex and medulla in a unilateral ureteral obstruction rat model, thereby showcasing the utility of intravoxel incoherent motion (IVIM) in evaluating contralateral renal changes.

METHODS

Six rats underwent MR scans and were subsequently sacrificed for baseline histological examination. Following the induction of left ureteral obstruction, 48 rats were scanned, and the histopathological examinations were conducted on days 3, 7, 10, 14, 21, 28, 35, and 42. The apparent diffusion coefficient (ADC), pure molecular diffusion (D), pseudodiffusion (D*), and perfusion fraction (f) values were measured using IVIM.

RESULTS

On the 10th day of obstruction, both cortical and medullary ADC values differed significantly between the UUO10 group and the sham group (p < 0.01). The cortical D values showed statistically significant differences between UUO3 group and sham group (p < 0.01) but not among UUO groups at other time point. Additionally, the cortical and medullary f values were statistically significant between the UUO21 group and the sham group (p < 0.01). Especially, the cortical f values exhibited significant differences between the UUO21 group and the UUO groups with shorter obstruction time (at time point of 3, 7, 10, 14 day) (p < 0.01).

CONCLUSIONS

Significant hemodynamic alterations were observed in the contralateral kidney following renal obstruction. IVIM accurately captures changes in the unobstructed kidney. Particularly, the cortical f value exhibits the highest potential for assessing contralateral renal modifications.