Group inference of default‐mode networks from functional magnetic resonance imaging data: comparison of random‐ and mixed‐effects group statistics

Default‐mode network (DMN) activity measured with functional magnetic resonance imaging (fMRI) represents dominant intrinsic neuronal activations of the human brain during rest as opposed to task periods. Previous studies have demonstrated the utility of DMNs in identifying characteristic traits such as hyperactivation and hypoactivation from group‐level fMRI data. However, these group‐level spatial patterns (SPs) were mostly based on random‐effect (RFX) statistics determined using only the intersubject variability. To reduce the potentially significant level of variability in group‐level SPs in RFX due to intrasubject variability, we were motivated to adopt a mixed‐effects (MFX) statistics that is using both intrasubject and intersubject variability. Publicly available group fMRI database during resting state was analyzed using a temporal concatenation‐based group independent component (IC) analysis, and DMN‐related ICs at the group‐level were automatically selected. The individual‐level SPs of these DMN‐related ICs were subsequently estimated using a dual‐regression approach. Using these individual‐level SPs, we evaluated the reproducibility and potential variability of the DMNs from the RFX and MFX statistics using performance measures including (1) neuronal activation levels, (2) percentages of overlap, (3) Pearson's spatial correlation coefficients, and (4) the distances between center‐of‐clusters. The resulting SPs from the MFX‐based group inference showed a significantly greater level of reproducibility than those from the RFX‐based group inference as tested in a bootstrapping framework Family‐wise error (FWE)‐corrected p < 10^?10, one‐way analysis of variance (ANOVA)). The reported findings may provide a valuable supplemental option for investigating the neuropsychiatric group‐ or condition‐dependent characteristic traits implicated in DMNs. © 2012 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 22, 121–131, 2012     

AIE Nanoparticles with High Stimulated Emission Depletion Efficiency and Photobleaching Resistance for Long‐Term Super‐Resolution Bioimaging

Stimulated emission depletion (STED) nanoscopy is a typical super‐resolution imaging technique that has become a powerful tool for visualizing intracellular structures on the nanometer scale. Aggregation‐induced emission (AIE) luminogens are ideal fluorescent agents for bioimaging. Herein, long‐term super‐resolution fluorescence imaging of cancer cells, based on STED nanoscopy assisted by AIE nanoparticles (NPs) is realized. 2,3‐Bis(4‐(phenyl(4‐(1,2,2‐triphenylvinyl)phenyl)amino)phenyl) fumaronitrile (TTF), a typical AIE luminogen, is doped into colloidal mesoporous silica to form fluorescent NPs. TTF@SiO₂ NPs bear three significant features, which are all essential for STED nanoscopy. First, their STED efficiency can reach more than 60%. Second, they are highly resistant to photobleaching, even under long‐term and high‐power STED light irradiation. Third, they have a large Stokes' shift of ≈150 nm, which is beneficial for restraining the fluorescence background induced by the STED light irradiation. STED nanoscopy imaging of TTF@SiO₂‐NPs‐stained HeLa cells is performed, exhibiting a high lateral spatial resolution of 30 nm. More importantly, long‐term (more than half an hour) super‐resolution cell imaging is achieved with low fluorescence loss. Considering that AIE luminogens are widely used for organelle targeting, cellular mapping, and tracing, AIE‐NPs‐based STED nanoscopy holds great potential for many basic biomedical studies that require super‐resolution and long‐term imaging.     

Iterative adaptive spatial filtering for noise‐suppression in functional magnetic resonance imaging time‐series

We present an iterative scheme for adaptive smoothing of functional magnetic resonance images. We propose a novel similarity measure to estimate the weights of the smoothing filter based on the functional similarity of the voxels under the smoothing kernel with the voxel under consideration as well as their similarity with a reference time‐course representing the expected BOLD response. We demonstrate the performance of the proposed method by applying the method to preprocess both simulated and real fMRI data. The method improves the functional SNR of the data while preserving the shapes of the functionally active region and its performance is not compromised when structured noise is the dominant noise source. © 2011 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 21, 260‐270, 2011;     

Real‐time ballistocardiographic artifact reduction using the k‐teager energy operator detector and multi‐channel referenced adaptive noise cancelling

The simultaneous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) recording technique has recently received considerable attention and has been used in many studies on cognition and neurological disease. EEG‐fMRI simultaneous recording has the advantage of enabling the monitoring of brain activity with both high temporal resolution and high spatial resolution in real time. The successful removal of the ballistocardiographic (BCG) artifact from the EEG signal recorded during an MRI is an important prerequisite for real‐time EEG‐fMRI joint analysis. We have developed a new framework dedicated to BCG artifact removal in real‐time. This framework includes a new real‐time R‐peak detection method combining a k‐Teager energy operator, a thresholding detector, and a correlation detector, as well as a real‐time BCG artifact reduction procedure combining average artifact template subtraction and a new multi‐channel referenced adaptive noise cancelling method. Our results demonstrate that this new framework is efficient in the real‐time removal of the BCG artifact. The multi‐channel adaptive noise cancellation (mANC) method performs better than the traditional ANC method in eliminating the BCG residual artifact. In addition, the computational speed of the mANC method fulfills the requirements of real‐time EEG‐fMRI analysis. © 2016 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 26, 209–215, 2016     

Single‐Cell Detection of mRNA Expression Using Nanofountain‐Probe Electroporated Molecular Beacons

New techniques for single‐cell analysis enable new discoveries in gene expression and systems biology. Time‐dependent measurements on individual cells are necessary, yet the common single‐cell analysis techniques used today require lysing the cell, suspending the cell, or long incubation times for transfection, thereby interfering with the ability to track an individual cell over time. Here a method for detecting mRNA expression in live single cells using molecular beacons that are transfected into single cells by means of nanofountain probe electroporation (NFP‐E) is presented. Molecular beacons are oligonucleotides that emit fluorescence upon binding to an mRNA target, rendering them useful for spatial and temporal studies of live cells. The NFP‐E is used to transfect a DNA‐based beacon that detects glyceraldehyde 3‐phosphate dehydrogenase and an RNA‐based beacon that detects a sequence cloned in the green fluorescence protein mRNA. It is shown that imaging analysis of transfection and mRNA detection can be performed within seconds after electroporation and without disturbing adhered cells. In addition, it is shown that time‐dependent detection of mRNA expression is feasible by transfecting the same single cell at different time points. This technique will be particularly useful for studies of cell differentiation, where several measurements of mRNA expression are required over time.     

Extended finite element method coupled with face‐based strain smoothing technique for three‐dimensional fracture problems

In this work, the extended finite element method (XFEM) is for the first time coupled with face‐based strain‐smoothing technique to solve three‐dimensional fracture problems. This proposed method, which is called face‐based smoothed XFEM here, is expected to combine both the advantages of XFEM and strain‐smoothing technique. In XFEM, arbitrary crack geometry can be modeled and crack advance can be simulated without remeshing. Strain‐smoothing technique can eliminate the integration of singular term over the volume around the crack front, thanks to the transformation of volume integration into area integration. Special smoothing scheme is implemented in the crack front smoothing domain. Three examples are presented to test the accuracy, efficiency, and convergence rate of the face‐based smoothed XFEM. From the results, it is clear that smoothing technique can improve the performance of XFEM for three‐dimensional fracture problems. Copyright © 2015 John Wiley & Sons, Ltd.     

Image‐guided navigation of single‐element focused ultrasound transducer

The spatial specificity and controllability of focused ultrasound (FUS), in addition to its ability to modify the excitability of neural tissue, allows for the selective and reversible neuromodulation of the brain function, with great potential in neurotherapeutics. Intraoperative magnetic resonance imaging (MRI) guidance has limitations due to its complicated examination logistics, such as fixation through skull screws to mount the stereotactic frame, simultaneous sonication in the MRI environment, and restrictions in choosing MR‐compatible materials. To overcome these limitations, an image‐guidance system based on optical tracking and preoperative imaging data is developed, separating the imaging acquisition for guidance and sonication procedure for treatment. Techniques to define the local coordinates of the focal point of sonication are presented. First, mechanical calibration detects the concentric rotational motion of a rigid‐body optical tracker, attached to a straight rod mimicking the sonication path, pivoted at the virtual FUS focus. The spatial error presented in the mechanical calibration was compensated further by MRI‐based calibration, which estimates the spatial offset between the navigated focal point and the ground‐truth location of the sonication focus obtained from a temperature‐sensitive MR sequence. MRI‐based calibration offered a significant decrease in spatial errors (1.9 ± 0.8 mm; 57% reduction) compared to the mechanical calibration method alone (4.4 ± 0.9 mm). Using the presented method, pulse‐mode FUS was applied to the motor area of the rat brain, and successfully stimulated the motor cortex. The presented techniques can be readily adapted for the transcranial application of FUS to intact human brain. © 2012 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 22, 177–184, 2012     

Variations in BOLD response latency estimated from event‐related fMRI at 3T: Comparisons between gradient‐echo and Spin‐echo

Functional magnetic resonance imaging (fMRI) commonly uses gradient‐recalled echo (GRE) signals to detect regional hemodynamic variations originating from neural activities. While the spatial localization of activation shows promising applications, indexing temporal response remains a poor mechanism for detecting the timing of neural activity. Particularly, the hemodynamic response may fail to resolve sub‐second temporal differences between brain regions because of its signal origin or noise in data, or both. This study aimed at evaluating the performance of latency estimation using different fMRI techniques, with two event‐related experiments at 3T. Experiment I evaluated latency variations within the visual cortex and their relationship with contrast‐to‐noise ratios (CNRs) for GRE, spin echo (SE), and diffusion‐weighted SE (DWSE). Experiment II used delayed visual stimuli between two hemifields (delay time = 0, 250, and 500 ms, respectively) to assess the temporal resolving power of three protocols: GRE_TR1000, GRE_TR500, and SE_TR1000. The results of experiment I showed the earliest latency with DWSE, followed by SE, and then GRE. Latency variations decreased as CNR increased. However, similar variations were found between GRE and SE, when the latter had lower CNR. In experiment II, measured stimulus delays from all conditions were significantly correlated with preset stimulus delays. Inter‐subject variation in the measured delay was found to be greatest with GRE_TR1000, followed by GRE_TR500, and the least with SE_TR1000. Conclusively, blood oxygenation level‐dependent responses obtained from GRE exhibit greater CNR but no compromised latency variations in the visual cortex. SE is potentially capable of improving the performance of latency estimation, especially for group analysis. © 2013 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 23, 215–221, 2013     

Real‐Time and High‐Resolution Bioimaging with Bright Aggregation‐Induced Emission Dots in Short‐Wave Infrared Region

Fluorescence imaging in the spectral region beyond the conventional near‐infrared biological window (700–900 nm) can theoretically afford high resolution and deep tissue penetration. Although some efforts have been devoted to developing a short‐wave infrared (SWIR; 900–1700 nm) imaging modality in the past decade, long‐wavelength biomedical imaging is still suboptimal owing to the unsatisfactory materials properties of SWIR fluorophores. Taking advantage of organic dots based on an aggregation‐induced emission luminogen (AIEgen), herein microscopic vasculature imaging of brain and tumor is reported in living mice in the SWIR spectral region. The long‐wavelength emission of AIE dots with certain brightness facilitates resolving brain capillaries with high spatial resolution (≈3 µm) and deep penetration (800 µm). Owning to the deep penetration depth and real‐time imaging capability, in vivo SWIR microscopic angiography exhibits superior resolution in monitoring blood–brain barrier damage in mouse brain, and visualizing enhanced permeability and retention effect in tumor sites. Furthermore, the AIE dots show good biocompatibility, and no noticeable abnormalities, inflammations or lesions are observed in the main organs of the mice. This work will inspire new insights on development of advanced SWIR techniques for biomedical imaging.     

Optical Imaging Approaches to Monitor Static and Dynamic Cell‐on‐Chip Platforms: A Tutorial Review

Miniaturized laboratories on chip platforms play an important role in handling life sciences studies. The platforms may contain static or dynamic biological cells. Examples are a fixed medium of an organ‐on‐a‐chip and individual cells moving in a microfluidic channel, respectively. Due to feasibility of control or investigation and ethical implications of live targets, both static and dynamic cell‐on‐chip platforms promise various applications in biology. To extract necessary information from the experiments, the demand for direct monitoring is rapidly increasing. Among different microscopy methods, optical imaging is a straightforward choice. Considering light interaction with biological agents, imaging signals may be generated as a result of scattering or emission effects from a sample. Thus, optical imaging techniques could be categorized into scattering‐based and emission‐based techniques. In this review, various optical imaging approaches used in monitoring static and dynamic platforms are introduced along with their optical systems, advantages, challenges, and applications. This review may help biologists to find a suitable imaging technique for different cell‐on‐chip studies and might also be useful for the people who are going to develop optical imaging systems in life sciences studies.     

Model‐based reconstruction for T1 mapping using single‐shot inversion‐recovery radial FLASH

Quantitative parameter mapping in MRI is typically performed as a two‐step procedure where serial imaging is followed by pixelwise model fitting. In contrast, model‐based reconstructions directly reconstruct parameter maps from raw data without explicit image reconstruction. Here, we propose a method that determines T1 maps directly from multi‐channel raw data as obtained by a single‐shot inversion‐recovery radial FLASH acquisition with a Golden Angle view order. Joint reconstruction of a T1, spin‐density and flip‐angle map is formulated as a nonlinear inverse problem and solved by the iteratively regularized Gauss‐Newton method. Coil sensitivity profiles are determined from the same data in a preparatory step of the reconstruction. Validations included numerical simulations, in vitro MRI studies of an experimental T1 phantom, and in vivo studies of brain and abdomen of healthy subjects at a field strength of 3 T. The results obtained for a numerical and experimental phantom demonstrated excellent accuracy and precision of model‐based T1 mapping. In vivo studies allowed for high‐resolution T1 mapping of human brain (0.5–0.75 mm in‐plane, 4 mm section thickness) and liver (1.0 mm, 5 mm section) within 3.6–5 s. In conclusion, the proposed method for model‐based T1 mapping may become an alternative to two‐step techniques, which rely on model fitting after serial image reconstruction. More extensive clinical trials now require accelerated computation and online implementation of the algorithm. © 2016 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 26, 254–263, 2016     

Microfluidic Platforms for Yeast‐Based Aging Studies

The budding yeast Saccharomyces cerevisiae has been a powerful model for the study of aging and has enabled significant contributions to our understanding of basic mechanisms of aging in eukaryotic cells. However, the laborious low‐throughput nature of conventional methods of performing aging assays limits the pace of discoveries in this field. Some of the technical challenges of conventional aging assay methods can be overcome by use of microfluidic systems coupled to time‐lapse microscopy. One of the major advantages is the ability of a microfluidic system to perform long‐term cell culture under well‐defined environmental conditions while tracking individual yeast. Here, recent advancements in microfluidic platforms for various yeast‐based studies including replicative lifespan assay, long‐term culture and imaging, gene expression, and cell signaling are discussed. In addition, emerging problems and limitations of current microfluidic approaches are examined and perspectives on the future development of this dynamic field are presented.     

Gadolinium Metallofullerene‐Based Activatable Contrast Agent for Tumor Signal Amplification and Monitoring of Drug Release

Activatable imaging probes are promising to achieve increased signal‐to‐noise ratio for accurate tumor diagnosis and treatment monitoring. Magnetic resonance imaging (MRI) is a noninvasive imaging technique with excellent anatomic spatial resolution and unlimited tissue penetration depth. However, most of the activatable MRI contrast agents suffer from metal ion‐associated potential long‐term toxicity, which may limit their bioapplications and clinical translation. Herein, an activatable MRI agent with efficient MRI performance and high safety is developed for drug (doxorubicin) loading and tumor signal amplification. The agent is based on pH‐responsive polymer and gadolinium metallofullerene (GMF). This GMF‐based contrast agent shows high relaxivity and low risk of gadolinium ion release. At physiological pH, both GMF and drug molecules are encapsulated into the hydrophobic core of nanoparticles formed by the pH‐responsive polymer and shielded from the aqueous environment, resulting in relatively low longitudinal relativity and slow drug release. However, in acidic tumor microenvironment, the hydrophobic‐to‐hydrophilic conversion of the pH‐responsive polymer leads to amplified MR signal and rapid drug release simultaneously. These results suggest that the prepared activatable MRI contrast agent holds great promise for tumor detection and monitoring of drug release.     

Magneto‐Plasmonic Au‐Fe Alloy Nanoparticles Designed for Multimodal SERS‐MRI‐CT Imaging

Diagnostic approaches based on multimodal imaging are needed for accurate selection of the therapeutic regimens in several diseases, although the dose of administered contrast drugs must be reduced to minimize side effects. Therefore, large efforts are deployed in the development of multimodal contrast agents (MCAs) that permit the complementary visualization of the same diseased area with different sensitivity and different spatial resolution by applying multiple diagnostic techniques. Ideally, MCAs should also allow imaging of diseased tissues with high spatial resolution during surgical interventions. Here a new system based on multifunctional Au‐Fe alloy nanoparticles designed to satisfy the main requirements of an ideal MCA is reported and their biocompatibility and imaging capability are described. The MCAs show easy and versatile surface conjugation with thiolated molecules, magnetic resonance imaging (MRI) and computed X‐ray tomography (CT) signals for anatomical and physiological information (i.e., diagnostic and prognostic imaging), large Raman signals amplified by surface enhanced Raman scattering (SERS) for high sensitivity and high resolution intrasurgical imaging, biocompatibility, exploitability for in vivo use and capability of selective accumulation in tumors by enhanced permeability and retention effect. Taken together, these results show that Au‐Fe nanoalloys are excellent candidates as multimodal MRI‐CT‐SERS imaging agents.     

Dopant‐Free Small‐Molecule Hole‐Transporting Material for Inverted Perovskite Solar Cells with Efficiency Exceeding 21%

Hole‐transporting materials (HTMs) play a critical role in realizing efficient and stable perovskite solar cells (PVSCs). Considering their capability of enabling PVSCs with good device reproducibility and long‐term stability, high‐performance dopant‐free small‐molecule HTMs (SM‐HTMs) are greatly desired. However, such dopant‐free SM‐HTMs are highly elusive, limiting the current record efficiencies of inverted PVSCs to around 19%. Here, two novel donor–acceptor‐type SM‐HTMs (MPA‐BTI and MPA‐BTTI) are devised, which synergistically integrate several design principles for high‐performance HTMs, and exhibit comparable optoelectronic properties but distinct molecular configuration and film properties. Consequently, the dopant‐free MPA‐BTTI‐based inverted PVSCs achieve a remarkable efficiency of 21.17% with negligible hysteresis and superior thermal stability and long‐term stability under illumination, which breaks the long‐time standing bottleneck in the development of dopant‐free SM‐HTMs for highly efficient inverted PVSCs. Such a breakthrough is attributed to the well‐aligned energy levels, appropriate hole mobility, and most importantly, the excellent film morphology of the MPA‐BTTI. The results underscore the effectiveness of the design tactics, providing a new avenue for developing high‐performance dopant‐free SM‐HTMs in PVSCs.     

Direct strain tensor approximation for full‐field strain measurement methods

Full‐field strain measurement techniques are based on computing the spatial derivatives of numerical or functional approximations of the underlying displacement fields extracted from digital imaging methods. These methods implicitly assume that the medium satisfies the strain compatibility conditions, which are only true in the case of a continuum body that remains continuum throughout its deformation history. In the present work, we introduce a method that can be used to calculate the strain components directly from typical digital imaging data, without the need of the continuum hypothesis and the need for displacement field differentiation. Thus, it enables the measurement of strain fields from imaged surfaces that may or may not contain discontinuities. Numerical comparisons are performed on the basis synthetic data produced from an analytical solution for an elastically orthotropic open‐hole domain in tension. For performance comparison purposes, the mean absolute error distributions are calculated for the cases of both the traditional meshless random grid method, and the direct strain method introduced herein. It is established that the more refined representation of strain provided by our present approach is more accurate everywhere in the domain, but most importantly, near its boundaries. Published 2013. This article is a US Government work and is in the public domain in the USA.     

Re‐evaluation of re‐hospitalization and rehabilitation in renal research

Introduction: The use of administrative data to capture 30‐day readmission rates in end‐stage renal disease is challenging since Medicare combines claims from acute care, inpatient rehabilitation (IRF), and long‐term care hospital stays into a single “Inpatient” file. For data prior to 2012, the United States Renal Data System does not contain the variables necessary to easily identify different facility types, making it likely that prior studies have inaccurately estimated 30‐day readmission rates. Methods: For this report, we developed two methods (a “simple method” and a “rehabilitation‐adjusted method”) to identify acute care, IRF, and long‐term care hospital stays from United States Renal Data System claims data, and compared them to methods used in previously published reports. Findings: We found that prior methods overestimated 30‐day readmission rates by up to 12.3% and overestimated average 30‐day readmission costs by up to 11%. In contrast, the simple and rehabilitation‐adjusted methods overestimated 30‐day readmission rates by 0.1% and average 30‐day readmission costs by 1.8%. The rehabilitation‐adjusted method also accurately identified 96.8% of IRF stays. Discussion: Prior research has likely provided inaccurate estimates of 30‐day readmissions in patients undergoing dialysis. In the absence of data on specific facility types particularly when using data prior to 2012, future researchers could employ our method to more accurately characterize 30‐day readmission rates and associated outcomes in patients with end‐stage renal disease.     

Wavelet‐based adaptive vector quantization for still‐image coding

Wavelet transform coding (WTC) with vector quantization (VQ) has been shown to be efficient in the application of image compression. An adaptive vector quantization coding scheme with the Gold‐Washing dynamic codebook‐refining mechanism in the wavelet domain, called symmetric wavelet transform‐based adaptive vector quantization (SWT‐GW‐AVQ), is proposed for still‐image coding in this article. The experimental results show that the GW codebook‐refining mechanism working in the wavelet domain rather than the spatial domain is very efficient, and the SWT‐GW‐AVQ coding scheme may improve the peak signal‐to‐noise ratio (PSNR) of the reconstructed images with a lower encoding time. © 2002 Wiley Periodicals, Inc. Int J Imaging Syst Technol 12, 166–174, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.10024     

Low‐Saturation‐Intensity,High‐Photostability,and High‐Resolution STED Nanoscopy Assisted by CsPbBr3 Quantum Dots

Stimulated emission depletion (STED) nanoscopy is one of the most promising super‐resolution imaging techniques for microstructure imaging. Commercial CdSe@ZnS quantum dots are used as STED probes and ≈50 nm lateral resolution is obtained. Compared with other quantum dots, perovskite CsPbBr₃ nanoparticles (NPs) possess higher photoluminescence quantum yield and larger absorption cross‐section, making them a more effective probe for STED nanoscopy. In this study, CsPbBr₃ NPs are used as probes for STED nanoscopy imaging. The fluorescence intensity of the CsPbBr₃ sample is hardly weakened at all after 200 min irradiation with a 39.8 mW depletion laser, indicating excellent photobleaching resistance of the CsPbBr₃ NPs. The saturation intensity of the CsPbBr₃ NPs is extremely low and estimated to be only 0.4 mW (0.126 MW cm^?2). Finally, an ultrahigh lateral resolution of 20.6 nm is obtained for a single nanoparticle under 27.5 mW STED laser irradiation in CsPbBr₃‐based STED nanoscopy imaging, which is a tenfold improvement compared with confocal microscopy. Because of its high fluorescence stability and ultrahigh resolution under lower depletion power, CsPbBr₃‐assisted STED nanoscopy has great potential to investigate microstructures that require super‐resolution and long‐term imaging.     

Regularization in parallel magnetic resonance imaging

SPIRiT (iterative self‐consistent parallel imaging reconstruction) can be solved efficiently for data acquired on arbitrary k‐space trajectories, and its sparsity regularized variant L1‐SPIRiT accelerates reconstruction. In this paper, we propose a regularized SPIRiT reconstruction based on steerable pyramid decomposition. The directionally filter banks lead to a better separation of signal and noise compared to a discrete wavelet transform (DWT). In vivo datasets and eight‐channel Shepp‐Logan phantom studies demonstrate efficient reconstructions. We compared our work with five state‐of‐the‐art parallel imaging techniques; our method yields better reconstruction results.