Shu, Yunhong

Introduction: Understanding mid-term test-retest reliability and within-subject variability is important for interpreting changes observed in longitudinal and intervention studies. The reliability of resting-state functional magnetic resonance imaging (rs-fMRI) is known to vary across measures and brain regions. However, how reliability differs across functional networks and connectivity- and amplitude-based measures, and whether multi-echo acquisition and processing modify these patterns, remain incompletely characterized. Methods: Twenty-two healthy volunteers underwent two rs-fMRI sessions 15.7 ± 4.0 days apart on a Compact 3T scanner. Multi-echo, middle-echo, and independently acquired single-echo datasets were compared, with multi-echo independent component analysis additionally evaluated as a denoising approach. Functional connectivity (FC) and three amplitude-based measures were evaluated using the Schaefer 400 parcellation. Reliability was systematically assessed using intraclass correlation coefficient (ICC), within-subject standard deviation (wSD), and systematic bias at edge or regional, and network levels. Results: Acquisition-dependent differences in reliability were generally modest. Multi-echo acquisition and processing increased functional connectivity strength and the magnitude of amplitude-based measures and improved inferior cortical coverage, but these enhancements did not consistently translate into substantially higher ICC or lower wSD. In contrast, reliability showed clear network-dependent differences. FC reliability varied markedly across network pairs and was not explained by connectivity strength alone; pairs involving the default mode and control networks generally showed more favorable profiles than several somatomotor and visual network pairs. Fractional amplitude of low-frequency fluctuations (fALFF) also showed network-dependent reliability, with the most favorable regional reproducibility observed in the default mode and control networks and lower reproducibility in the somatomotor and visual networks. Conclusion: These findings provide practical mid-term reliability benchmarks for rs-fMRI on a Compact 3T scanner and show that measurement stability varies more clearly across measures and functional networks than across acquisition approaches.

Abstract White matter bundles play a crucial role in cognitive functions by rapidly transmitting information between brain regions. Inter-areal conduction guides the integration of information and conduction velocity is a fundamental parameter in theories and models of brain function. However, distributions of conduction velocity remain difficult to characterize in vivo in humans. In this work, we integrated diffusion magnetic resonance imaging (dMRI) tractography with intracranial electrical stimulation during clinical stereo-electroencephalography (sEEG) monitoring in 17 subjects to measure conduction velocity within four major white matter bundles. Our findings reveal that human brain conduction is characterized by high variability both within and between bundles, reflecting a predominance of slow connections alongside rare high-speed connections. Because conduction velocity in myelinated fibers follows an approximately linear relationship with axon diameter, we derive underlying axon diameter distributions and show that these estimates are comparable to previous post-mortem studies. These findings demonstrate a heavily skewed distribution of human neural conduction velocities and show that structural heterogeneity shapes the timing and integration of information in large-scale networks.

ABSTRACT Unexpected RF noise artifact “followed” a patient with an implanted spinal cord stimulator to multiple MR systems. Subsequent testing and clinical scanning showed no artifact, implying that the artifact originated from the implanted device. MR exams ( n = 173) performed over a two‐year period in patients ( n = 122) who had implanted spinal cord stimulators from the same manufacturer were reviewed for artifacts and device models. RF noise artifacts were observed in ~50% of exams in patients with a specific model of spinal cord stimulator, but only ~1%–8% of exams in other models from the same manufacturer. We hope that by describing this artifact, health care professionals can avoid service costs and scheduling delays.

Abstract Hypoxia constrains cerebral oxygen availability and challenges brain function and stability. Although hypoxia-responsive functional connectivity (HR-FC) reorganizes rapidly with declining arterial oxygen partial pressure, its relationship to local neurovascular activity remains unclear. We examined time-resolved amplitude of low-frequency fluctuations (ALFF) in blood-oxygenation-level dependent (BOLD) fMRI during graded acute hypoxia in healthy adults, performing a continuous cognitive test (Go/No-go task) with concurrent physiological monitoring. Dynamic ALFF and functional connectivity were estimated using a sliding-window approach and analyzed across large-scale brain networks defined by Schaefer’s 17-network parcellation. Severe hypoxia elicited temporally dissociated responses across modalities. Functional connectivity increased monotonically, whereas ALFF exhibited pronounced nonlinear modulation, including phase-dependent divergence across networks. During hypoxic decompensation, the default mode network (DefaultA) showed marked ALFF suppression, whereas a ventral secondary somatosensory-dominant network (SomMotB) exhibited preferential preservation despite similar engagement in HR-FC. Together, these findings indicate that network-level ALFF captures a distinct yet complementary layer of functional dynamics, with a temporal profile distinct from functional connectivity. Spontaneous BOLD dynamics during acute hypoxia reflect structured network-level modulation rather than a uniform suppression attributable solely to reduced oxygen availability. These findings support a conceptual framework of cerebral oxygen budgeting , in which metabolic constraints reshape functional dynamics across brain networks.

Abstract Background Respiration has traditionally been considered a source of artifact in functional MRI (fMRI) due to chest motion. However, the respiratory cycle also induces changes in local oxygen concentration, resulting in fluctuations in the fMRI signal. These breathing‐triggered signals (BTS) may reflect underlying oxygen metabolism. This preliminary study developed a method to extract BTS from resting‐state BOLD fMRI and examined differences between healthy and mild cognitive impairment (MCI) groups. Method MRI scans were conducted under IRB approval on a compact 3T MRI system. Participants included two groups of 18 healthy volunteers (42.6±16.0 years) and 12 MCI patients (70.9±7.3 years). Each MRI scan included T 1 ‐weighted anatomy imaging and multi‐echo resting‐state fMRI acquisitions. The preprocessing pipeline was implemented by AFNI and FreeSurfer. Figure 1 illustrates the workflow for extracting and averaging fMRI data based on respiratory or cardiac cycle windows. As depicted in Figure 2(c,d), the mean fMRI signals corresponding to the breathing or cardiac cycles were modeled using a low‐order Fourier series to assess their amplitudes. A linear mixed‐effects model was employed to examine the effects of group and breathing cycle period, using MATLAB's ‘fitlme’ function with the formula: BTS ∼ Period + Group. Result As shown in Figure 2(e,f), breathing‐triggered BOLD signals were prominent, while cardiac‐driven BOLD signals were rarely observed. Figure 2(g) shows that global BTSs in the healthy group exhibited a linear relationship with the breathing cycle period, persisting even after artifact correction (RETROICOR for respiration and cardiac cycles and RVT). Figure 3 highlights significant regional differences between groups, particularly in the hippocampus and thalamus ( p < 0.05, uncorrected), where BTS amplitudes were greater in the MCI group. Potentially, the detected BTS could provide some insights into the coupling between respiration and cerebral oxygen metabolism and potentially serve as an imaging biomarker to assess brain health. However, due to the limited number of samples, these findings should be interpreted with caution, and further analysis is needed. Conclusion This preliminary study suggests that breathing‐triggered signals in resting‐state BOLD fMRI have the potential to serve as a noninvasive biomarker for early detection and monitoring of neurodegenerative conditions such as MCI.

Abstract Background Flow‐related ghost artifact from a 3D Magnetization Prepared Rapid Gradient Echo (MPRAGE) sequence results from unsaturated magnetization of incoming arterial flow. This is especially common on MR scanners equipped with smaller radiofrequency (RF) transmit coils. A high‐performance compact 3T (C3T) scanner features a smaller RF‐transmit coil (inner diameter 37 cm, length 40 cm), leading to a rapid fall‐off of the B1 field below the neck. This configuration results in more intense flow‐related ghost artifacts, especially in younger patients. Purpose The C3T scanner's smaller RF‐transmit coil provides RF field coverage over the brain region, causing bright in‐flow arterial signals and flow‐related artifacts in the conventional 3D‐MPRAGE scans. The purpose of this study is to suppress these artifacts by adding a RF saturation band (RFSB) pulses to the 3D‐MPRAGE sequence. Methods The RFSB was added to the 3D‐MPRAGE sequence as a preparation pulse option. To test the effectiveness, 37 subjects were scanned on the C3T under an IRB‐approved protocol using 3D‐MPRAGE with and without RFSB. Ten of those subjects underwent repeated scans with and without RFSB to evaluate test‐retest reliability. A consensus evaluation by two neuroradiologists was performed on all data to compare signal to noise ratio, image contrast, presence of artifacts, and diagnostic confidence. Quantitative analysis included calculating test‐retest differences by image subtraction and evaluating the variance in flow‐artifact‐induced image intensity between the scans with and without RFSB. Additionally, one subject was scanned on a whole‐body 3T scanner using a transmit/receive (T/R) head coil to demonstrate the method's applicability across different MRI platforms as a proof of concept. Results The Wilcoxon signed‐rank test of the neuroradiologist evaluations showed a significant reduction in artifacts and an improvement in diagnostic confidence in the posterior fossa region with and without RFSB ( p < 0.0001). Test–retest analysis showed that adding RFSB significantly reduced image intensity variability in the cerebellum, even among subjects without visible flow artifacts. The normalized difference decreased from 8.71% to 6.41% ( p = 0.0059), suggesting improved image reliability in regions prone to flow‐related artifacts. Additionally, similar findings were observed in scans on a whole‐body 3T with a T/R head coil, demonstrating the broader applicability of this method. Conclusion Incorporating RFSB into 3D‐MPRAGE scans effectively reduces flow‐related ghost artifact on the C3T scanner, improving image quality and diagnostic confidence. These findings suggest that the proposed method could be widely implemented across MRI systems utilizing a smaller RF‐transmit coil.

Recent advancements in compact MRI scanners, portable low-field-strength MRI systems, and high-performance gradient inserts address the challenges of conventional MRI for brain imaging, providing more accessible and versatile technology.

Abstract Electrical stimulation is increasingly used to modulate brain networks for clinical purposes. The basic unit of neurostimulation, a single electrical pulse, can travel through white matter to influence connected neuronal populations. However, the mechanisms by which it influences connected populations is not well understood: stimulation may excite, inhibit, or add noise to neuronal population activity. In this study, we investigated how single pulses modulate the neuronal processing of images in a well-controlled visual paradigm. In two human subjects implanted with iEEG electrodes for clinical purposes, single pulses were delivered to electrodes in white matter tracts connected to measurement electrodes in visual cortex. Images appeared on-screen at 0, 100, or 200 ms after each pulse. Using finite impulse response modeling, we decomposed the broadband and evoked potential responses into separate components induced by electrical stimulation and by visual processing. Single pulses induced transient broadband increases followed by suppression, but they did not modulate the visual broadband responses (i.e., stimulation response was additive to visual response). In contrast, single pulses elicited prominent brain stimulation evoked potentials and they modulated the visual evoked potentials. Specifically, visual evoked potentials were larger when stimulation occurred closer to visual onset. This indicates that a single electrical pulse can increase the strength or synchrony of visual inputs. Overall, these findings suggest that the effects of electrical stimulation in the visual system are two-fold: stimulation induces additive effects on broadband power, possibly by adding noise, and it interacts with synchronous visual inputs to amplify them.

AbstractPurposeTo study implant lead tip heating because of the RF power deposition by developing mathematical models and comparing them with measurements acquired at 1.5 T and 3 T, especially to predict resonant length.Theory and MethodsA simple exponential model and an adapted transmission line model for the electric field transfer function were developed. A set of wavenumbers, including that calculated from insulated antenna theory (King wavenumber) and that of the embedding medium were considered. Experiments on insulated, capped wires of varying lengths were performed to determine maximum temperature rise under RF exposure. The results are compared with model predictions from analytical expressions derived under the assumption of a constant electric field, and with those numerically calculated from spatially varying, simulated electric fields from body coil transmission. Simple expressions for the resonant length bounded between one‐quarter and one‐half wavelength are developed based on the roots of transcendental equations.ResultsThe King wavenumber for both models more closely matched the experimental data with a maximum root mean square error of 9.81°C at 1.5 T and 5.71°C at 3 T compared to other wavenumbers with a maximum root mean square error of 27.52°C at 1.5 T and 22.01°C for 3 T. Resonant length was more accurately predicted compared to values solely based on the embedding medium.ConclusionAnalytical expressions were developed for implanted lead heating and resonant lengths under specific assumptions. The value of the wavenumber has a strong effect on the model predictions. Our work could be used to better manage implanted device lead tip heating.