Signal intensity ratio of draining vein on silent MR angiography as an indicator of high-flow arteriovenous shunt in brain arteriovenous malformation.

OBJECTIVES: To evaluate whether the signal intensity ratio (rSI) of the draining vein on silent MR angiography is correlated with arteriovenous (A-V) transit time on digital subtraction angiography (DSA), thereby identifying high-flow A-V shunt in brain arteriovenous malformation (BAVM), and to analyze whether the rSI and the characteristic of draining veins on silent MRA are associated with hemorrhage presentation. METHODS: Eighty-one draining veins of 46 participants with BAVM (mean age 33.2 ± 16.9 years) who underwent silent MRA and DSA were evaluated retrospectively. The correlation between the rSI of the draining vein on silent MRA and A-V transit time on DSA was examined. The AUC-ROC was obtained to evaluate the performance of the rSI in determining the presence of high-flow A-V shunt. The characteristics of draining veins with the maximum rSI (rSImax) were further compared between the hemorrhagic and non-hemorrhagic untreated BAVM. RESULTS: The rSI of each draining vein on silent MRA was significantly correlated with A-V transit time from DSA (r = -0.81, p < .001). The AUC-ROC was 0.89 for using the rSI to determine the presence of high-flow A-V shunt. A cut-off rSI value of 1.09 yielded a sensitivity of 82.4% and a specificity of 82.8%. The draining vein with rSImax and no ectasia was significantly more observed in the hemorrhagic group (p = 0.045). CONCLUSIONS: The rSI of the draining vein on silent MRA is significantly correlated with A-V transit time on DSA, and it can be used as an indicator of high-flow A-V shunt in BAVM. KEY POINTS: • The signal intensity ratio (rSI) of the draining vein on silent MRA significantly correlated with arteriovenous (A-V) transit time of brain arteriovenous malformation (BAVM) on digital subtraction angiography (DSA). • The area under the receiver operating characteristic curve (AUC) was 0.89 for using the rSI of draining veins to determine high-flow A-V shunt. • Draining veins with maximum rSI and no ectasia were significantly more observed in the hemorrhagic group of BAVM (p = 0.045).

Low-frequency fluctuation in continuous real-time feedback of finger force: a new paradigm for sustained attention.

OBJECTIVE: Behavioral studies have suggested a low-frequency (0.05 Hz) fluctuation of sustained attention on the basis of the intra-individual variability of reaction-time. Conventional task designs for functional magnetic resonance imaging (fMRI) studies are not appropriate for frequency analysis. The present study aimed to propose a new paradigm, real-time finger force feedback (RT-FFF), to study the brain mechanisms of sustained attention and neurofeedback. METHODS: We compared the low-frequency fluctuations in both behavioral and fMRI data from 38 healthy adults (19 males; mean age, 22.3 years). Two fMRI sessions, in RT-FFF and sham finger force feedback (S-FFF) states, were acquired (TR 2 s, Siemens Trio 3-Tesla scanner, 8 min each, counter-balanced). Behavioral data of finger force were obtained simultaneously at a sampling rate of 250 Hz. RESULTS: Frequency analysis of the behavioral data showed lower amplitude in the low-frequency band (0.004-0.104 Hz) but higher amplitude in the high-frequency band (27.02-125 Hz) in the RT-FFF than the S-FFF states. The mean finger force was not significantly different between the two states. fMRI data analysis showed higher fractional amplitude of low-frequency fluctuation (fALFF) in the S-FFF than in the RT-FFF state in the visual cortex, but higher fALFF in RT-FFF than S-FFF in the middle frontal gyrus, the superior frontal gyrus, and the default mode network. CONCLUSION: The behavioral results suggest that the proposed paradigm may provide a new approach to studies of sustained attention. The fMRI results suggest that a distributed network including visual, motor, attentional, and default mode networks may be involved in sustained attention and/or real-time feedback. This paradigm may be helpful for future studies on deficits of attention, such as attention deficit hyperactivity disorder and mild traumatic brain injury.

Granger causality analysis implementation on MATLAB: a graphic user interface toolkit for fMRI data processing.

A lot of functional magnetic resonance imaging (fMRI) studies have indicated that Granger causality analysis (GCA) is a suitable method to reveal causal effect among brain regions. Based on another MATLAB GUI toolkit, Resting State fMRI Data Analysis Toolkit (REST), we implemented GCA on MATLAB as a graphical user interface (GUI) toolkit. This toolkit, namely REST-GCA, could output both the residual-based F and the signed-path coefficient. REST-GCA also intergrates a programme that could transform the distribution of residual-based F to approximately normal distribution and then permit parametric statistical inference at group level. Using REST-GCA, we tested the causal effect of the right frontal-insular cortex (rFIC) onto each voxel in the whole brain, and vice versa, each voxel in the whole brain on the rFIC, in a voxel-wise way in a resting-state fMRI dataset from 30 healthy college students. Using Jarque-Bera goodness-of-fit test and the Lilliefors goodness-of-fit test, we found that the transformation from F to F' and the further standardization from F' to Z score substantially improved the normality. The results of one sample t-tests on Z score showed bi-directional positive causal effect between rFIC and the dorsal anterior cingulate cortex (dACC). One sample t-tests on the signed-path coefficients showed positive causal effect from rFIC to dACC but negative from dACC to rFIC. All these results indicate that REST-GCA may be useful toolkit for caudal analysis of fMRI data.