Detection Of Signal Changes Research Articles

We Are on the Clock

See related article, pages 250–255. Time plays a major role in acute stroke treatment. Millions of neurons are lost each minute in acute ischemic stroke,1 and the efficacy of intravenous thrombolysis is related to time from symptom onset with earlier treatment being more effective.2,3 Moreover, knowledge of the time of symptom onset is a prerequisite for treatment with intravenous thrombolysis. This information, however, is lacking in a large proportion of patients with acute stroke. In 14% to 27% of patients, stroke symptoms occur during sleep,4–6 and this large group of patients is a priori excluded from the only specific and effective treatment available for acute stroke. This dissatisfying situation has raised interest in imaging surrogate markers of lesion age, which might help identify patients presenting within a time window making them eligible for thrombolytic treatment.6 In this issue of Stroke, Ebinger et al report on a study on the relation between the visibility of acute ischemic lesions in fluid-attenuated inversion recovery (FLAIR) MRI and lesion age.7 Stroke MRI lends itself to be used as a surrogate marker of lesion age with signal changes in different MRI sequences taking a different course during the first hours of ischemia. Although diffusion-weighted imaging (DWI) allows for the detection of signal changes resulting from cytotoxic edema within minutes, the T2 relaxation time increases continuously during the first hours of stroke.8 This …

The longitudinal changes of BOLD response and cerebral hemodynamics from acute to subacute stroke. A fMRI and TCD study

BackgroundBy mapping the dynamics of brain reorganization, functional magnetic resonance imaging MRI (fMRI) has allowed for significant progress in understanding cerebral plasticity phenomena after a stroke. However, cerebro-vascular diseases can affect blood oxygen level dependent (BOLD) signal. Cerebral autoregulation is a primary function of cerebral hemodynamics, which allows to maintain a relatively constant blood flow despite changes in arterial blood pressure and perfusion pressure. Cerebral autoregulation is reported to become less effective in the early phases post-stroke.This study investigated whether any impairment of cerebral hemodynamics that occurs during the acute and the subacute phases of ischemic stroke is related to changes in BOLD response.We enrolled six aphasic patients affected by acute stroke. All patients underwent a Transcranial Doppler to assess cerebral autoregulation (Mx index) and fMRI to evaluate the amplitude and the peak latency (time to peak-TTP) of BOLD response in the acute (i.e., within four days of stroke occurrence) and the subacute (i.e., between five and twelve days after stroke onset) stroke phases.ResultsAs patients advanced from the acute to subacute stroke phase, the affected hemisphere presented a BOLD TTP increase (p = 0.04) and a deterioration of cerebral autoregulation (Mx index increase, p = 0.046). A similar but not significant trend was observed also in the unaffected hemisphere. When the two hemispheres were grouped together, BOLD TTP delay was significantly related to worsening cerebral autoregulation (Mx index increase) (Spearman's rho = 0.734; p = 0.01).ConclusionsThe hemodynamic response function subtending BOLD signal may present a delay in peak latency that arises as patients advance from the acute to the subacute stroke phase. This delay is related to the deterioration of cerebral hemodynamics. These findings suggest that remodeling the fMRI hemodynamic response function in the different phases of stroke may optimize the detection of BOLD signal changes.

DNA hybridization detection in a microfluidic channel using two fluorescently labelled nucleic acid probes

A conceptually new technique for fast DNA detection has been developed. Here, we report a fast and sensitive online fluorescence resonance energy transfer (FRET) detection technique for label-free target DNA. This method is based on changes in the FRET signal resulting from the sequence-specific hybridization between two fluorescently labelled nucleic acid probes and target DNA in a PDMS microfluidic channel. Confocal laser-induced microscopy has been used for the detection of fluorescence signal changes. In the present study, DNA hybridizations could be detected without PCR amplification because the sensitivity of confocal laser-induced fluorescence detection is very high. Two probe DNA oligomers (5′-CTGAT TAGAG AGAGAA-TAMRA-3′ and 5′-TET-ATGTC TGAGC TGCAGG-3′) and target DNA (3′-GACTA ATCTC TCTCT TACAG GCACT ACAGA CTCGA CGTCC-5′) were introduced into the channel by a microsyringe pump, and they were efficiently mixed by passing through the alligator teeth-shaped PDMS microfluidic channel. Here, the nucleic acid probes were terminally labelled with the fluorescent dyes, tetrafluororescein (TET) and tetramethyl-6-carboxyrhodamine (TAMRA), respectively. According to our confocal fluorescence measurements, the limit of detection of the target DNA is estimated to be 1.0 × 10 −6 to 1.0 × 10 −7 M. Our result demonstrates that this analytical technique is a promising diagnostic tool that can be applied to the real-time analysis of DNA targets in the solution phase.

Theoretical optimization of multi-echo fMRI data acquisition

Simulations are used to optimize multi-echo fMRI data acquisition for detection of BOLD signal changes in this study. Optimal sequence design (echo times and sampling period (receiver bandwidth)) and the variation in sensitivity between tissues with different baseline T*2 are investigated, taking into account the effects of physiological noise and non-exponential signal decay. In the case of a single echo, for normally distributed, uncorrelated noise, the results indicate that the sampling period should be made as long as possible (so as to produce an acceptable level of image distortion), up to a maximum sampling period of 3T*2, (i.e. optimum TE = 1.5T*2). Combining the signal from multiple echoes using weighted summation improves the contrast-to-noise ratio (CNR), at a reduced optimum echo interval. If the BOLD effect causes a constant change in relaxation rate, ΔR*2, independent of the tissue R*2, then a multi-echo acquisition causes considerable variation in sensitivity to BOLD signal changes with tissue T*2, so that if the sequence is optimized for a target tissue T*2 it will be more sensitive to BOLD signal changes in tissues with shorter T*2 values. Fitting for ΔR*2 reduces the CNR, and when using this approach, the shortest echo time interval should be used, down to a limit of about 0.3T*2, and as many echoes as possible within the constraints of TR or hardware limitations should be collected. It is also shown that the optimal sequence will remain optimum or close to optimum irrespective of whether there are physiological noise contributions.

How long to scan? The relationship between fMRI temporal signal to noise ratio and necessary scan duration

Recent advances in MRI receiver and coil technologies have significantly improved image signal-to-noise ratios (SNR) and thus temporal SNR (TSNR). These gains in SNR and TSNR have allowed the detection of fMRI signal changes at higher spatial resolution and therefore have increased the potential to localize small brain structures such as cortical layers and columns. The majority of current fMRI processing strategies employ multi-subject averaging and therefore require spatial smoothing and normalization, effectively negating these gains in spatial resolution higher than about 10 mm 3. Reliable detection of activation in single subjects at high resolution is becoming a more common desire among fMRI researchers who are interested in comparing individuals rather than populations. Since TSNR decreases with voxel volume, detection of activation at higher resolutions requires longer scan durations. The relationship between TSNR, voxel volume and detectability is highly non-linear. In this study, the relationship between TSNR and the necessary fMRI scan duration required to obtain significant results at varying P values is determined both experimentally and theoretically. The results demonstrate that, with a TSNR of 50, detection of activation of above 2% requires at most 350 scan volumes (when steps are taken to remove the influence of physiological noise from the data). Importantly, these results also demonstrate that, for activation magnitude on the order of 1%, the scan duration required is more sensitive to the TSNR level than at 2%. This study showed that with voxel volumes of ∼ 10 mm 3 at 3 T, and a corresponding TSNR of ∼ 50, the required number of time points that guarantees detection of signal changes of 1% is about 860, but if TSNR increases by only 20%, the time for detection decreases by more than 30%. More than just being an exercise in numbers, these results imply that imaging of columnar resolution (effect size = 1% and assuming a TR of 1 s) at 3 T will require either 10 min for a TSNR of 60 or 40 min for a TSNR of 30. The implication is that at these resolutions, TSNR is likely to be critical for determining success or failure of an experiment.

Mapping the MRI voxel volume in which thermal noise matches physiological noise—Implications for fMRI

This work addresses the choice of the imaging voxel volume in blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI). Noise of physiological origin that is present in the voxel time course is a prohibitive factor in the detection of small activation-induced BOLD signal changes. If the physiological noise contribution dominates over the temporal fluctuation contribution in the imaging voxel, further increases in the voxel signal-to-noise ratio (SNR) will have diminished corresponding increases in temporal signal-to-noise (TSNR), resulting in reduced corresponding increases in the ability to detect activation induced signal changes. On the other hand, if the thermal and system noise dominate (suggesting a relatively low SNR) further decreases in SNR can prohibit detection of activation-induced signal changes. Here we have proposed and called the “suggested” voxel volume for fMRI the volume where thermal plus system-related and physiological noise variances are equal. Based on this condition we have created maps of fMRI suggested voxel volume from our experimental data at 3T, since this value will spatially vary depending on the contribution of physiologic noise in each voxel. Based on our fast EPI segmentation technique we have found that for gray matter (GM), white matter (WM), and cerebral spinal fluid (CSF) brain compartments the mean suggested cubical voxel volume is: (1.8 mm) 3, (2.1 mm) 3 and (1.4 mm) 3, respectively. Serendipitously, (1.8 mm) 3 cubical voxel volume for GM approximately matches the cortical thickness, thus optimizing BOLD contrast by minimizing partial volume averaging. The introduced suggested fMRI voxel volume can be a useful parameter for choice of imaging volume for functional studies.

EEG‐fMRI using z‐shimming in patients with temporal lobe epilepsy

To use z-shimming, a technique that reduces signal loss due to susceptibility artifacts that can result in reduced or absent activation in electroencephalography (EEG) functional MRI (fMRI) sessions in patients with temporal lobe epilepsy (TLE), to determine whether it would result in an increased ability to detect significant regions of blood oxygenation level-dependent (BOLD) signal change. Eight patients with TL EEG spikes underwent an EEG-fMRI scanning session using z-shimming. The signal intensities in the z-shimmed images were compared with those in the standard images. BOLD activation maps were created from the two sets of images using the timings of the spikes observed on the EEG. The mean signal increase in the TLs as a result of z-shimming was 45.9%+/-4.5%. The percentage of TL voxels above a brain intensity threshold rose from 66.1%+/-7.6% to 77.6%+/-5.7%. This appreciable increase in signal did not lead to any significant differences in the statistical maps created with the two sets of functional images. The results suggest that loss of signal is not the limiting factor for the detection of spike-related BOLD signal changes in patients with TLE activity.

An adaptive filter for suppression of cardiac and respiratory noise in MRI time series data

The quality of MRI time series data, which allows the study of dynamic processes, is often affected by confounding sources of signal fluctuation, including the cardiac and respiratory cycle. An adaptive filter is described, reducing these signal fluctuations as long as they are repetitive and their timing is known. The filter, applied in image domain, does not require temporal oversampling of the artifact-related fluctuations. Performance is demonstrated for suppression of cardiac and respiratory artifacts in 10-minute brain scans on 6 normal volunteers. Experimental parameters resemble a typical fMRI experiment (17 slices; 1700 ms TR). A second dataset was acquired at a rate well above the Nyquist frequency for both cardiac and respiratory cycle (single slice; 100 ms TR), allowing identification of artifacts specific to the cardiac and respiratory cycles, aiding assessment of filtering performance. Results show significant reduction in temporal standard deviation (SDt) in all subjects. For all 6 datasets with 1700 ms TR combined, the filtering method resulted in an average reduction in SDt of 9.2% in 2046 voxels substantially affected by respiratory artifacts, and 12.5% for the 864 voxels containing substantial cardiac artifacts. The maximal SDt reduction achieved was 52.7% for respiratory and 55.3% for cardiac filtering. Performance was found to be at least equivalent to the previously published RETROICOR method. Furthermore, the interaction between the filter and fMRI activity detection was investigated using Monte Carlo simulations, demonstrating that filtering algorithms introduce a systematic error in the detected BOLD-related signal change if applied sequentially. It is demonstrated that this can be overcome by combining physiological artifact filtering and detection of BOLD-related signal changes simultaneously. Visual fMRI data from 6 volunteers were analyzed with and without the filter proposed here. Inclusion of the cardio-respiratory regressors in the design matrix yielded a 4.6% t-score increase and 4.0% increase in the number of significantly activated voxels.

MRI Features After Radiofrequency Ablation of Osteoid Osteoma with Cooled Probes and Impedance-Control Energy Delivery

The purposes of our study were to determine the temporal changes in MR signal in bone after radiofrequency ablation of osteoid osteoma and the size of the zone of marrow signal change produced by the radiofrequency technique and to compare the size of the zone with published data for radiofrequency ablation with manual-control protocols. Radiofrequency ablation was performed in 10 patients with a clinical and radiologic diagnosis of osteoid osteoma. A cooled radiofrequency probe was inserted in the nidus. Twelve minutes of radiofrequency energy was applied from a 200-W radiofrequency generator in an impedance-control setting. MRI with multiplanar turbo spin-echo T1-weighted and STIR sequences was performed at 1, 7, and 28 days after the procedure in seven patients. The three remaining patients had follow-up imaging at 28 days only. The images were reviewed by two radiologists who categorized the imaging features and measured the marrow zone of signal alteration when visible. The size of the zone of marrow signal change produced by the radiofrequency technique was compared with published data for radiofrequency ablation with manual-control protocols. A 1-mm band of homogeneous altered marrow signal distributed symmetrically parallel to the entire probe tract was seen earliest, at 1 day, in the femoral neck lesion treated with the 2-cm probe. The band was low signal on the T1 sequence and high signal on the STIR sequence, and the diameter of the zone was 27 mm. By 7 days, five of the seven treated bones showed a band of marrow signal alteration. By 28 days, all 10 treated bones had a band of marrow signal alteration. The interband distance at 90 degrees to the probe measured on STIR images at 28 days was a mean of 20.9 mm (confidence interval, 16.1-25.7 mm [p < 0.05]; range +/- measurement error, 10.5-35 +/- 1.64 mm) with a 1-cm probe and 30.5 mm (measurement error, +/- 0.78 mm) on T1 images without contrast material when a 2-cm exposed-tip probe was used. Higher-output generators with impedance-control software and internally cooled radiofrequency probes with longer exposed tips produce larger zones of marrow signal change than expected with manual-control protocols. MRI allows detection of temporal marrow signal change after radiofrequency ablation. The marrow signal change with a high-energy delivery protocol is larger than manual-control protocols.

Detection of deoxygenation-related signal change in acute ischemic stroke patients by T2*-weighted magnetic resonance imaging.

Acute decreases in the MR T2*-weighted signal have been reported in experimental models of middle cerebral artery occlusion. This has been attributed to blood deoxygenation in association with an increased brain oxygen extraction fraction. The aim of this study was to detect this signal by susceptibility-weighted MR imaging in acute ischemic stroke patients. Dynamic susceptibility contrast-enhanced MR (DSC-MR) imaging was performed within 4 hours of stroke onset in 6 patients with unilateral cerebral artery occlusion (middle cerebral artery, n=5; internal carotid artery, n=1). Cerebral blood volume was estimated on a pixel-by-pixel basis. DSC-MR images taken before arrival of the contrast medium were examined visually to identify hypointense areas. Bilateral regions of interest were set in the middle cerebral artery territory for comparison of the mean signal intensity. A semilogarithmic plot of signal intensity versus cerebral blood volume for every pixel in the region of interest was also analyzed. The side on which the hypointense area was seen was significantly correlated with the side of arterial occlusion. The mean signal intensity was significantly smaller on the affected side than on the contralateral side. The semilogarithmic plot of signal intensity versus cerebral blood volume indicated greater deoxyhemoglobin concentrations for the ipsilateral than for the contralateral region of interest. DSC-MR images allow detection of hypointensity in the affected cerebral hemisphere in acute ischemic stroke patients. Such hypointensity may indicate increased oxygen extraction fraction (misery perfusion) and may provide information valuable to patient care.

Detection versus Estimation in Event-Related fMRI: Choosing the Optimal Stimulus Timing

With the advent of event-related paradigms in functional MRI, there has been interest in finding the optimal stimulus timing, especially when the interstimulus interval is varied during the imaging run. Previous works have proposed stimulus timings to optimize either the estimation of the impulse response function (IRF) or the detection of signal changes. The purpose of this paper is to clarify that estimation and detection are fundamentally different goals and to determine the optimal stimulus timing and distribution with respect to both the accuracy of estimating the IRF and the power of detection assuming a particular hemodynamic model. Simulated stimulus distributions are varied systematically, from traditional blocked designs to rapidly varying event related designs. These simulations indicate that estimation of the hemodynamic impulse response function is optimized when stimuli are frequently alternated between task and control states, with shorter interstimulus intervals and stimulus durations, whereas the detection of activated areas is optimized by blocked designs. The stimulus timing for a given experiment should therefore be generated with the required detectability and estimation accuracy.

A new approach to measure single-event related brain activity using real-time fMRI: feasibility of sensory, motor, and higher cognitive tasks.

Real-time fMRI is a rapidly emerging methodology that enables monitoring changes in brain activity during an ongoing experiment. In this article we demonstrate the feasibility of performing single-event sensory, motor, and higher cognitive tasks in real-time on a clinical whole-body scanner. This approach requires sensitivity optimized fMRI methods: Using statistical parametric mapping we quantified the spatial extent of BOLD contrast signal changes as a function of voxel size and demonstrate that sacrificing spatial resolution and readout bandwidth improves the detection of signal changes in real time. Further increases in BOLD contrast sensitivity were obtained by using real-time multi-echo EPI. Real-time image analysis was performed using our previously described Functional Imaging in REal time (FIRE) software package, which features real-time motion compensation, sliding window correlation analysis, and automatic reference vector optimization. This new fMRI methodology was validated using single-block design paradigms of standard visual, motor, and auditory tasks. Further, we demonstrate the sensitivity of this method for online detection of higher cognitive functions during a language task using single-block design paradigms. Finally, we used single-event fMRI to characterize the variability of the hemodynamic impulse response in primary and supplementary motor cortex in consecutive trials using single movements. Real-time fMRI can improve reliability of clinical and research studies and offers new opportunities for studying higher cognitive functions.

The detection and significance of subtle changes in mixed-signal brain lesions by serial MRI scan matching and spatial normalization

The purpose of this work is to detect and assess the significance of subtle signal changes in mixed-signal lesions based on serial MRI scan matching. Pairs of serially acquired T1-weighted volume MR images from 20 normal controls and seven patients with epilepsy were matched and difference images obtained. The precision and consistency of the registration were evaluated. The Gaussian noise level in the difference images was determined automatically. A structured difference filter was then used to segment structured (changed) voxels from the Gaussian noise. In the controls, the structured difference images were normalized into Talairach space, resulting in a structured noise map. The significance of changes in patients was assessed by spatial normalization and comparison with the structured noise map. The precision and consistency of the co-registration were ≤0.06 mm with a registration success rate of 100%. The Gaussian noise level in the difference images was in the range 3.0–6.9. In the controls, an average of 1.6% of the brain voxels were classified as structured. Since-based registration resulted in a reduction of < 1 % in the amount of structure compared to linear interpolation. The structured noise map in controls showed high noise density in areas affected by image artefacts. We show examples of significant changes found in lesions which had been reported as unchanged on visual inspection. A novel quantitative approach has been presented for the detection and quantification of subtle signal changes in lesions. This method is of potential clinical value in the non-invasive characterization of signal change and biological behaviour of neoplastic lesions.