A phased array ultrasound system with a robotic arm for neuromodulation.

BACKGROUND: Ultrasonic neuromodulation (UNMOD) provides a non-invasive brain stimulation. However, the high-resolution region-specificity of UNMOD with a single element transducer combined with a mechanical positioning system could have limits due to the intrinsic positioning error from mechanical systems. OBJECTIVE/HYPOTHESIS: A phased array system could lead to highly selective neuromodulation with electronic control. METHODS: A specialized phased-array system with a robotic arm is implemented for a rhesus monkey model. Various primary motor cortex areas related to tail, hand, and mouth were stimulated with a 200 µm step size. The ultrasonic parameters were ISPTA of 840 mW/cm2, pulse repetition frequency of 100 Hz, and a 5% duty factor at 600 kHz. The induced movement were recorded and analyzed. RESULTS: Separate digits, mouth, and tongue motions were successfully induced by electronically controlling the focus. The identical body part movement could be induced when the focus was moved back to the identical primary motor cortex with electronic control. Accordingly, the reproducibility of UNMOD could be partially validated with rhesus monkey model. CONCLUSION: A phased-array system appears to have a potential for the non-invasive and region-selective neuromodulation method.

Sonophoresis with ultrasound-responsive liquid-core nuclei for transdermal drug delivery.

BACKGROUND: Sonophoresis can increase the delivery efficiency of various drugs into the skin. A recent advance in sonophoresis is the use of ultrasound-responsive liquid-core nuclei (URLN) to increase the probability of cavitation. In this study, we developed a URLN and ultrasound device, and demonstrated its effectiveness through in vitro and clinical tests. MATERIALS AND METHODS: Three types of experiments were designed to evaluate the efficiency of sonophoresis with URLN. First, a Franz diffusion cell with cosmetic ingredients was used to analyze quantitatively the amount of drug delivered to the porcine skin. Second, after the application of sonophoresis with URLN, the porcine skin surface was examined using scanning electron microscopy (SEM) to see the changes in morphology. Finally, a clinical test was performed to verify the utility of sonophoresis with URLN. RESULTS: The results indicate that sonophoresis with URLN can increase the amount of compound delivered by approximately 11.9-fold over 6 h for niacinamide and by 7.33-fold over 6 h for adenosine. In addition, we observed approximately 20-30 µm sized pores on porcine skin in SEM images. In clinical testing, the application of sonophoresis with cosmetics containing URLN for 3 min improved the efficiency of transdermal drug delivery by 1.9-fold, the depth of absorption by 2.0-fold, and the speed of absorption by 2.0-fold at 30 min after application. CONCLUSION: We expect that sonophoresis with specialized URLN in transdermal drug delivery could be used widely for various skin-related applications.

Multi-Focus Image Fusion Using Focal Area Extraction in a Large Quantity of Microscopic Images.

The non-invasive examination of conjunctival goblet cells using a microscope is a novel procedure for the diagnosis of ocular surface diseases. However, it is difficult to generate an all-in-focus image due to the curvature of the eyes and the limited focal depth of the microscope. The microscope acquires multiple images with the axial translation of focus, and the image stack must be processed. Thus, we propose a multi-focus image fusion method to generate an all-in-focus image from multiple microscopic images. First, a bandpass filter is applied to the source images and the focus areas are extracted using Laplacian transformation and thresholding with a morphological operation. Next, a self-adjusting guided filter is applied for the natural connections between local focus images. A window-size-updating method is adopted in the guided filter to reduce the number of parameters. This paper presents a novel algorithm that can operate for a large quantity of images (10 or more) and obtain an all-in-focus image. To quantitatively evaluate the proposed method, two different types of evaluation metrics are used: "full-reference" and "no-reference". The experimental results demonstrate that this algorithm is robust to noise and capable of preserving local focus information through focal area extraction. Additionally, the proposed method outperforms state-of-the-art approaches in terms of both visual effects and image quality assessments.

Development of 64Cu-loaded Perfluoropentane Nanodroplet: A Potential Tumor Theragnostic Nano-carrier and Dual-Modality PET-Ultrasound Imaging Agents.

The purpose of this study was to develop and preliminarily evaluate phospholipid-shelled nanodroplets (NDs) encapsulating perfluoropentane (PFP) and radioactive 64Cu as a hybrid positron emission tomography (PET)-ultrasound (US) probe. PFP NDs were fabricated by mixing liquid-phase PFP with a phospholipid solution. The 64Cu was encapsulated into the NDs in a size-controlled manner by exploiting the hydrophobicity of 64Cu-diacetyl-bis(N4-methylthiosemicarbazone) (64Cu-ATSM) using a vial mixer and an extruder. The fabricated 64Cu-loaded PFP NDs (64Cu-PFP NDs) were evaluated using in vitro/in vivo PET-computed tomography (PET-CT), US imaging and transmission electron microscopy. In the in vitro PET images, the 64Cu-PFP NDs were observed as a hot spot in the lower section of the test tube. In the acquired US images, the mean region of interest brightness values of 64Cu-PFP NDs were revealed by their strong echo image. In a tumor-bearing mouse animal model, tumor uptake of the 64Cu-PFP NDs was low, that is, approximately 65%, compared with that of only free 64Cu, as determined by PET-delayed imaging analysis. The dual-function concept of the NDs is expected to contribute to the prognosis and effectiveness of therapy by fusing the science and technology of nuclear medicine and US.

Transdermal Drug Delivery using a Specialized Cavitation Seed for Ultrasound.

GOAL: The Sonophoresis, which utilizes ultrasound for transdermal drug delivery (TDD), can improve the efficiency of drug delivery for a variety of drugs predominantly due to caviation effect. In order to increase the efficacy of sonophoresis, we propose an alternative cavitation seed specialized for sonophoresis, which can be concentrated on the skin surface by gravity adapting perfluorohexane as core. METHODS: An in vitro and in vivo experiments were conducted to assess the effect of the specialized cavitation seed. High performance liquid chromatography was used for in vitro experiments on porcine skin with ferulic acid and an optical imaging system was used for in vivo experiments on rat model with fluorescein isothiocyanate-dextran (FD, 150 kDa), respecitively. RESULTS: The amount of ferulic acid delivered by sonophoresis with the proposed cavitation seed was approximately 1,700 times greater than the amount delivered by diffusion. FD could be delivered to a depth of 500 »m under the skin, and the average total flux in the region of interest was increased 6.4-fold for the group using sonophoresis with the cavitation seed compared to the group using diffusion. CONCLUSION: Conclusively, sonophoresis with the proposed cavitation seed demonstrated significant improvement in TDD and the possibility of macromolecule delivery into the skin. SIGNIFICANCE: This approach has potential to be a main TDD method for variety of applications including medicine and cosmetics.

Sonophoresis Using Ultrasound Contrast Agents: Dependence on Concentration.

Sonophoresis can increase skin permeability to various drugs in transdermal drug delivery. Cavitation is recognized as the predominant mechanism of sonophoresis. Recently, a new logical approach to enhance the efficiency of transdermal drug delivery was tried. It is to utilize the engineered microbubble and its resonant frequency for increase of cavitation activity. Actively-induced cavitation with low-intensity ultrasound (less than ~1 MPa) causes disordering of the lipid bilayers and the formation of aqueous channels by stable cavitation which indicates a continuous oscillation of bubbles. Furthermore, the mutual interactions of microbubble determined by concentration of added bubble are also thought to be an important factor for activity of stable cavitation, even in different characteristics of drug. In the present study, we addressed the dependence of ultrasound contrast agent concentration using two types of drug on the efficiency of transdermal drug delivery. Two types of experiment were designed to quantitatively evaluate the efficiency of transdermal drug delivery according to ultrasound contrast agent concentration. First, an experiment of optical clearing using a tissue optical clearing agent was designed to assess the efficiency of sonophoresis with ultrasound contrast agents. Second, a Franz diffusion cell with ferulic acid was used to quantitatively determine the amount of drug delivered to the skin sample by sonophoresis with ultrasound contrast agents. The maximum enhancement ratio of sonophoresis with a concentration of 1:1,000 was approximately 3.1 times greater than that in the ultrasound group without ultrasound contrast agent and approximately 7.5 times greater than that in the control group. These results support our hypothesis that sonophoresis becomes more effective in transdermal drug delivery due to the presence of engineered bubbles, and that the efficiency of transdermal drug delivery using sonophoresis with microbubbles depends on the concentration of microbubbles in case stable cavitation is predominant.

Functional brain networks associated with eating behaviors in obesity.

Obesity causes critical health problems including diabetes and hypertension that affect billions of people worldwide. Obesity and eating behaviors are believed to be closely linked but their relationship through brain networks has not been fully explored. We identified functional brain networks associated with obesity and examined how the networks were related to eating behaviors. Resting state functional magnetic resonance imaging (MRI) scans were obtained for 82 participants. Data were from an equal number of people of healthy weight (HW) and non-healthy weight (non-HW). Connectivity matrices were computed with spatial maps derived using a group independent component analysis approach. Brain networks and associated connectivity parameters with significant group-wise differences were identified and correlated with scores on a three-factor eating questionnaire (TFEQ) describing restraint, disinhibition, and hunger eating behaviors. Frontoparietal and cerebellum networks showed group-wise differences between HW and non-HW groups. Frontoparietal network showed a high correlation with TFEQ disinhibition scores. Both frontoparietal and cerebellum networks showed a high correlation with body mass index (BMI) scores. Brain networks with significant group-wise differences between HW and non-HW groups were identified. Parts of the identified networks showed a high correlation with eating behavior scores.

Connectivity Analysis and Feature Classification in Attention Deficit Hyperactivity Disorder Sub-Types: A Task Functional Magnetic Resonance Imaging Study.

Attention deficit hyperactivity disorder (ADHD) is a pervasive neuropsychiatric disorder. Patients with different ADHD subtypes show different behaviors under different stimuli and thus might require differential approaches to treatment. This study explores connectivity differences between ADHD subtypes and attempts to classify these subtypes based on neuroimaging features. A total of 34 patients (13 ADHD-IA and 21 ADHD-C subtypes) underwent functional magnetic resonance imaging (fMRI) with six task paradigms. Connectivity differences between ADHD subtypes were assessed for the whole brain in each task paradigm. Connectivity measures of the identified regions were used as features for the support vector machine classifier to distinguish between ADHD subtypes. The effectiveness of connectivity measures of the regions were tested by predicting ADHD-related Diagnostic and Statistical Manual of Mental Disorders (DSM) scores. Significant connectivity differences between ADHD subtypes were identified mainly in the frontal, cingulate, and parietal cortices and partially in the temporal, occipital cortices and cerebellum. Classifier accuracy for distinguishing between ADHD subtypes was 91.18 % for both gambling punishment and emotion task paradigms. Linear prediction under the two task paradigms showed significant correlation with DSM hyperactive/impulsive score. Our study identified important brain regions from connectivity analysis based on an fMRI paradigm using gambling punishment and emotion task paradigms. The regions and associated connectivity measures could serve as features to distinguish between ADHD subtypes.

Parametric response mapping of dynamic CT for predicting intrahepatic recurrence of hepatocellular carcinoma after conventional transcatheter arterial chemoembolization.

OBJECTIVES: The aim of our study was to determine the diagnostic value of a novel image analysis method called parametric response mapping (PRM) for prediction of intrahepatic recurrence of hepatocellular carcinoma (HCC) treated with conventional transcatheter arterial chemoembolization (TACE). METHODS: This retrospective study was approved by the IRB. We recruited 55 HCC patients who achieved complete remission (CR) after TACE and received longitudinal multiphasic liver computed tomography (CT). The patients fell into two groups: the recurrent tumour group (n = 29) and the non-recurrent tumour group (n = 26). We applied the PRM analysis to see if this technique could distinguish between the two groups. The results of the PRM analysis were incorporated into a prediction algorithm. We retrospectively removed data from the last time point and attempted to predict the response to therapy of the removed data. RESULTS: The PRM analysis was able to distinguish between the non-recurrent and recurrent groups successfully. The prediction algorithm detected response to therapy with an area under the curve (AUC) of 0.76, while the manual approach had AUC 0.64. CONCLUSIONS: Adopting PRM analysis can potentially distinguish between recurrent and non-recurrent HCCs and allow for prediction of response to therapy after TACE. KEY POINTS: Parametric response mapping (PRM) could help assess patients with recurrent HCCs after TACE. Parametric response mapping could direct patients to individualized therapy. Longitudinal CT images were analyzed with advanced image analysis method.

Structural and Functional Brain Connectivity of People with Obesity and Prediction of Body Mass Index Using Connectivity.

Obesity is a medical condition affecting billions of people. Various neuroimaging methods including magnetic resonance imaging (MRI) have been used to obtain information about obesity. We adopted a multi-modal approach combining diffusion tensor imaging (DTI) and resting state functional MRI (rs-fMRI) to incorporate complementary information and thus better investigate the brains of non-healthy weight subjects. The objective of this study was to explore multi-modal neuroimaging and use it to predict a practical clinical score, body mass index (BMI). Connectivity analysis was applied to DTI and rs-fMRI. Significant regions and associated imaging features were identified based on group-wise differences between healthy weight and non-healthy weight subjects. Six DTI-driven connections and 10 rs-fMRI-driven connectivities were identified. DTI-driven connections better reflected group-wise differences than did rs-fMRI-driven connectivity. We predicted BMI values using multi-modal imaging features in a partial least-square regression framework (percent error 15.0%). Our study identified brain regions and imaging features that can adequately explain BMI. We identified potentially good imaging biomarker candidates for obesity-related diseases.

Sound packing DNA: packing open circular DNA with low-intensity ultrasound.

Supercoiling DNA (folding DNA into a more compact molecule) from open circular forms requires significant bending energy. The double helix is coiled into a higher order helix form; thus it occupies a smaller footprint. Compact packing of DNA is essential to improve the efficiency of gene delivery, which has broad implications in biology and pharmaceutical research. Here we show that low-intensity pulsed ultrasound can pack open circular DNA into supercoil form. Plasmid DNA subjected to 5.4 mW/cm(2) intensity ultrasound showed significant (p-values <0.001) supercoiling compared to DNA without exposure to ultrasound. Radiation force induced from ultrasound and dragging force from the fluid are believed to be the main factors that cause supercoiling. This study provides the first evidence to show that low-intensity ultrasound can directly alter DNA topology. We anticipate our results to be a starting point for improved non-viral gene delivery.

Connectivity analysis of normal and mild cognitive impairment patients based on FDG and PiB-PET images.

Connectivity analysis allows researchers to explore interregional correlations, and thus is well suited for analysis of complex networks such as the brain. We applied whole brain connectivity analysis to assess the progression of Alzheimer's disease (AD). To detect early AD progression, we focused on distinguishing between normal control (NC) subjects and subjects with mild cognitive impairment (MCI). Fludeoxyglucose (FDG) and Pittsburgh compound B (PiB)-positron emission tomography (PET) were acquired for 75 participants. A graph network was implemented using correlation matrices. Correlation matrices of FDG and PiB-PET were combined into one matrix using a novel method. Group-wise differences between NC and MCI patients were assessed using clustering coefficients, characteristic path lengths, and betweenness centrality using various correlation matrices. Using connectivity analysis, this study identified important regions differentially affected by AD progression.

Real-Time Analysis of Cellular Response to Small-Molecule Drugs within a Microfluidic Dielectrophoresis Device.

Quantitative detection of the biological properties of living cells is essential for a wide range of purposes, from the understanding of cellular characteristics to the development of novel drugs in nanomedicine. Here, we demonstrate that analysis of cell biological properties within a microfluidic dielectrophoresis device enables quantitative detection of cellular biological properties and simultaneously allows large-scale measurement in a noise-robust and probeless manner. Applying this technique, the static and dynamic biological responses of live B16F10 melanoma cells to the small-molecule drugs such as N-ethylmaleimide (NEM) and [(dihydronindenyl)oxy]alkanoic acid (DIOA) were quantitatively and statistically examined by investigating changes in movement of the cells. Measurement was achieved using subtle variations in dielectrophoresis (DEP) properties of the cells, which were attributed to activation or deactivation of K(+)/Cl(-) cotransporter channels on the cell membrane by the small-molecule drugs, in a microfluidic device. On the basis of quantitative analysis data, we also provide the first report of the shift of the complex permittivity of a cell induced by the small-molecule drugs. In addition, we demonstrate interesting quantifiable parameters including the drug effectiveness coefficient, antagonistic interaction coefficient, kinetic rate, and full width at half-maximum, which corresponded to changes in biological properties of B16F10 cells over time when NEM and DIOA were introduced alone or in combination. Those demonstrated parameters represent very useful tools for evaluating the effect of small-molecule drugs on the biological properties of cells.

Differences in early and late mild cognitive impairment tractography using a diffusion tensor MRI.

Diffusion tensor MRI tractography is an imaging tool that can provide information of in-vivo neuronal fiber tracts to assess progress for Alzheimer's disease (AD). In an effort to detect early AD progression, we focused on distinguishing subgroups within mild cognitive impairment (MCI): early MCI and late MCI. Tractography was applied not only to white matter regions but also neighboring gray matter regions known to be affected by AD. Nerve fibers touching the hippocampus, thalamus, and amygdala in both hemispheres were extracted to quantify limbic system fiber connectivity. Two fiber extraction algorithms, fiber assignment by continuous tracking and the Runge Kutta approach, were applied to an AD imaging database. We computed the number of fibers touching regions of interest as the imaging feature. The imaging feature could distinguish between the MCI subgroups. It was also significantly correlated with a known genetic marker for AD, the apolipoprotein E epsilon 4 allele. The number of fibers might be a useful imaging biomarker to complement conventional region of interest-based biomarkers for AD research.

Improved explanation of human intelligence using cortical features with second order moments and regression.

BACKGROUND: Cortical features derived from magnetic resonance imaging (MRI) provide important information to account for human intelligence. Cortical thickness, surface area, sulcal depth, and mean curvature were considered to explain human intelligence. One region of interest (ROI) of a cortical structure consisting of thousands of vertices contained thousands of measurements, and typically, one mean value (first order moment), was used to represent a chosen ROI, which led to a potentially significant loss of information. METHODS: We proposed a technological improvement to account for human intelligence in which a second moment (variance) in addition to the mean value was adopted to represent a chosen ROI, so that the loss of information would be less severe. Two computed moments for the chosen ROIs were analyzed with partial least squares regression (PLSR). Cortical features for 78 adults were measured and analyzed in conjunction with the full-scale intelligence quotient (FSIQ). RESULTS: Our results showed that 45% of the variance of the FSIQ could be explained using the combination of four cortical features using two moments per chosen ROI. Our results showed improvement over using a mean value for each ROI, which explained 37% of the variance of FSIQ using the same set of cortical measurements. DISCUSSION: Our results suggest that using additional second order moments is potentially better than using mean values of chosen ROIs for regression analysis to account for human intelligence.

Parametric response mapping of dynamic CT as an imaging biomarker to distinguish viability of hepatocellular carcinoma treated with transcatheter arterial chemoembolization.

PURPOSE: Accurate assessment of viability of hepatocellular carcinoma (HCC) after transcatheter arterial chemoembolization (TACE) is important for therapy planning. The purpose of this study is to determine the diagnostic value of a novel image analysis method called parametric response mapping (PRM) in predicting viability of tumor in HCC treated with TACE for dynamic CT images. METHODS: 35 patients who had 35 iodized-oil defect areas (IODAs) in HCCs treated with TACE were included in our study. These patients were divided into two groups, one group with viable tumors (n = 22) and the other group with non-viable tumors (n = 13) in the IODA. All patients were followed up using triple-phase dynamic CT after the treatment. We compared (a) manual analysis, (b) using PRM results, and (c) using PRM results with automatic classifier to distinguish between two tumor groups based on dynamic CT images from two longitudinal exams. Two radiologists performed the manual analysis. The PRM approach was implemented using prototype software. We adopted an off-the-shelf k nearest neighbor (kNN) classifier and leave-one-out cross-validation for the third approach. The area under the curve (AUC) values were compared for three approaches. RESULTS: Manual analysis yielded AUC of 0.74, using PRM results yielded AUC of 0.84, and using PRM results with an automatic classifier yielded AUC of 0.87. CONCLUSIONS: We improved upon the standard manual analysis approach by adopting a novel image analysis method of PRM combined with an automatic classifier.