To-noise Ratio Research Articles

Myo-inositol and total NAA in the hippocampus are linked to CSF tau pathology in cognitively normal older adults.

Understanding relationships between in vivo neurometabolic changes and Alzheimer's disease (AD) pathology in the hippocampus, a region vulnerable to early changes in AD, will support early diagnosis. Two studies using 1 H-MRS examined concentrations of myo-inositol (MI), total creatine (tCr) and total NAA (tNAA) in the hippocampus. The first study compared hippocampal metabolite concentrations in healthy young and older adults and the second study assessed relationships between hippocampal metabolites and cerebrospinal fluid (CSF) measurements of Aβ42, phosphotau 181 (pTau181), and total tau (t-Tau) while adjusting for demographic covariates and spectral characteristics (linewidth, signal- to-noise ratio) in a separate group of older adults ranging from cognitively normal (CN) to AD-dementia. Hippocampal MI, but not tCr or tNAA, was increased in cognitively normal older versus young adults. Within the second older adult group, MI and tNAA, but not tCr, were linked to increases in CSF pTau181 and t-Tau, but not Aβ42. Tau deposition in cognitively normal individuals is associated with biochemical changes related to glial reactivity and neural integrity in the hippocampus.

A Robust Dual Watermarking using Grey Wolf Optimization, Selective Encryption and Fast Flexible De-Noising Convolution Neural Network

Digital data interchange in IoT systems has flourished with the advancement of industrial internet technologies. Particularly, more and more digital images created by intelligent and industrial equipment are sent there are security concerns related to the website, server, and cloud. To accomplish this issue, in this article a secure watermarking approach is suggested in this research to effectively improve security, invisibility, and resilience at the same time. The adequate coefficient for information embedding is first determined using an assortment of transform domain techniques Discrete-Wavelet-Transform (DWT), Heisenberg- decomposition (HD), and Tensor-singular-value-decomposition (T-SVD). Using the grey wolf optimization (GWO) approach, we estimated the appropriate embedding factors to provide a reasonable compromise between robustness and invisibility. To enable the suggested approach to offer an additional level of security, a selective encryption technique is used on the watermark image. Moreover, FFDNet—a quick and adaptable de-noising convolutional-neural–network is working to increase the robustness-of-the suggested algorithm. The results demonstrate that the recommended watermarking method generates exceptional imperceptibility, resilience, and security against standard attacks. Additionally, the comparison demonstrates that the suggested algorithm performs better than alternative strategies. The following metrics were reached: 51.6966 dB, 0.9944, 0.9961, and 0.2849 for the peak-signal- to-noise ratio (PSNR), Structural-Similarity-Index (SSIM), number of changing pixels per second (NPCR), and unified-averaged-changed-intensity (UACI) average scores.

Evaluating Impact of Different Parameters in Additive Manufacturing for Complex Situations

Additive manufacturing (AM) has emerged as an effective method for fabricating parts with internal complex features. However, optimizing process parameters to achieve desired mechanical properties for such complex geometries remains a challenge. This research aims to systematically evaluate the influence of AM process parameters on the tensile strength of PLA plus specimens containing a rectangular channel integrated inside the gauge section. A Taguchi L9 orthogonal design of experiments was formulated with four control factors - printing temperature, layer height, wall line count and infill percentage. Tensile testing specimen of standard ASTM D638-Type I containing a rectangular channel of 1.5x5x50mm was printed on an FDM machine. Tensile testing determined the ultimate tensile strength and percentage of elongation as the response. Signal- to-noise ratio analysis revealed optimized levels as 210°C, 0.20mm, 3 wall lines and 100% infill. Tensile testing of specimens printed at these conditions yielded average UTS of 34.58 MPa. Adopting Taguchi methodology, this study aims to improve understanding of interplay between key AM parameters and mechanical properties for PLA plus specimens with complex internal geometry. Optimized settings aid quality fabrication of functionally graded parts with intricate designs using this sustainable FDM material. Statistical design of experiments serves as an efficient evaluation approach. Key Words: Additive Manufacturing, Fused Deposition Modelling, PLA, Tensile Test Specimen

Enhanced Efficiency in Coefficient of Friction Evaluation through Automated Data Processing

In this work, an approach towards automated extraction and evaluation of static and kinematic coefficients of friction is presented. By replacing manual evaluation with an automated process, this approach yields promising results, simplifies data handling, and saves significant time. The methodology shows potential for application to a wide range of experimental data and provides advanced processing capabilities using the extracted and mathematically evaluated data points. However, for data with high signal- to-noise ratios, automatic detection still requires further optimization to improve accuracy.

Optimization of acquisition parameters for cortical inhomogeneous magnetization transfer (ihMT) imaging using a rapid gradient echo readout.

Imaging biomarkers with increased myelin specificity are needed to better understand the complex progression of neurological disorders. Inhomogeneous magnetization transfer (ihMT) imaging is an emergent technique that has a high degree of specificity for myelin content but suffers from low signal to-noise ratio (SNR). This study used simulations to determine optimal sequence parameters for ihMT imaging for use in high-resolution cortical mapping. MT-weighted cortical image intensity and ihMT SNR were simulated using modified Bloch equations for a range of sequence parameters. The acquisition time was limited to 4.5 min/volume. A custom MT-weighted RAGE sequence with center-out k-space encoding was used to enhance SNR at 3 T. Pulsed MT imaging was studied over a range of saturation parameters, and the impact of the turbo factor on the effective ihMT resolution was investigated. 1 mm isotropic ihMTsat maps were generated in 25 healthy adults. Greater SNR was observed for larger number of bursts consisting of 6-8 saturation pulses each, combined with a high readout turbo factor. However, that protocol suffered from a point spread function that was more than twice the nominal resolution. For high-resolution cortical imaging, we selected a protocol with a higher effective resolution at the cost of a lower SNR. We present the first group-average ihMTsat whole-brain map at 1 mm isotropic resolution. This study presents the impact of saturation and excitation parameters on ihMTsat SNR and resolution. We demonstrate the feasibility of high-resolution cortical myelin imaging using ihMTsat in less than 20 min.

Low-complexity IRS beamforming based on sphere decoding and tabu search

The real-time reconfiguration of intelligent reflecting surface (IRS) is one of the crucial, yet challenging tasks required to exploit the benefits of IRS. In this paper, we study an IRS-aided multiple-input single-output (MISO) wireless network, where a coarsely quantized (few resolution bits) IRS is reconfigured to help the point-to-point communication between a multi-antenna access point (AP) and a single-antenna user. Specifically, the transmit precoders at the AP and the reflecting discrete phase shifters at the IRS are jointly optimized to maximize the signal- to-noise ratio (SNR) at the user. The optimization is studied in two practical wireless propagation environments. First, we consider an environment where the direct AP-user link is in deep fade, which enables the relaxation of the optimization problem such that it can be optimally solved by the proposed sphere-decoder (SD) algorithm. Second, a normal propagation environment for all links is considered, wherein we propose the tabu search (TS) algorithm to solve the joint active and passive beamforming problem with low complexity. The proposed TS algorithm is shown to work well, even in deep-fade AP-user link scenarios. The presented numerical results confirm the validity of our analysis and demonstrate the effectiveness of the proposed schemes over the benchmark schemes on different system setups and propagation environments.

Multi-Head Attention-Based Spectrum Sensing for Cognitive Radio

Spectrum sensing is one of the key tasks of cognitive radio to monitor the activity of the primary user. The sensing accuracy of the secondary user is dependent on the signal-to-noise ratio of the primary user signal. A novel Multi-head Attention-based spectrum sensing for Cognitive Radio is proposed through this work to increase the detection probability of the primary user at a low signal- to-noise ratio condition. A radio machine learning dataset with a variety of digital modulation schemes and varying signal-to-noise ratios served as a training source for the proposed model. Further, the performance metrics were evaluated to assess the performance of the proposed model. The experimental results indicate that the proposed model is optimized in terms of the amount of training time required which also has an increase of 27.6% in the probability of detection of the primary user under a low signal-to-noise ratio when compared to other related works that use deep learning.

Acquisition Time and Probabilities of Detection and False Alarm in Direct Sequence Code Division Multiple Access Systems

Multiple access interference (MAI) is one of the most important issues to consider in the design, implementation and operation of 5G systems using code division multiple access (CDMA) technique based on spread spectrum that offers a more flexible solution, compared to other techniques. Especially, it permits a much higher user bit rate, due to the bandwidth allocated to the emitted signal; thus, allowing very attractive multimedia services. In this paper, we develop the expressions of the detection probability, false alarm probability and the average acquisition time - in a direct sequence CDMA (DS-CDMA) transmission system - using a serial search and taking into consideration MAI. The evolution of these parameters according to the signal- to-noise ratio (SNR) and the decision threshold leads to study performances of the system in terms of detection and average acquisition time. The obtained results reveal that the acquisition time decreases when the SNR increases. Additionally, it is found that the probability of detection increases when the threshold decreases, and increasing SNR it reaches a constant value for an SNR/chip around 0 dB for all thresholds.

АНАЛІЗ ЗАСТОСОВНОСТІ МЕТОДУ ДВОЧАСТОТНОЇ ІНТЕРФЕРОМЕТРІЇ ДЛЯ ВИМІРЮВАННЯ КУТА МІСЦЯ ЦІЛЕЙ У ДВОКООРДИНАТНИХ РЛС

Subject and Purpose. The study deals with the dual-frequency radio interferometry technique, which is based on the employment of two fairly close frequencies with the aim to remove ambiguity of the radar target elevation estimation using 2D-radar and eliminate 2 pm-uncertainty of the signal phase difference measurement. Analysis of random noise action on the accuracy of the elevation angle estimation by the dual-frequency radio interferometry and assessment of practical applicability of the method make up the purpose of the paper. Methods and Methodology. The noise action on the elevation angle measurement accuracy is examined through a series of an- alytical calculations with the use of statistical analysis methods. The noise in each receiving channel is modeled in terms of additive, statistically independent stationary Gaussian processes with zero mean values and equal variances. The calculation results are checked via computer simulations with statistics estimations for 106 random noise realizations. Results. A correct condition has been developed for the sector width where the target elevation angle is unambiguously estimated depending on the space separation of the antennas (baselines) and the frequency ratio. Expressions for elevation angle estimation errors have been obtained, showing that the error is mainly contributed by the faults in the determination of the ambiguity interval number. A probability of the correct determination of the ambiguity interval number has been derived depending on the signal- to-noise ratio and the frequency difference, indicating that almost one hundred per cent probability of the correct determination of the ambiguity interval number is only achieved when the signal-to-noise ratio exceeds 30 dB. A comparative analysis has been performed between the methods of dual-frequency interferometry and conventional phase-difference direction finding in the case of close X-band frequencies and the same sectors of survey. Conclusions. The dual-frequency radio interferometry technique with close frequencies has been shown to outperform the stand- ard phase-difference direction-finding method only when the signal-to-noise ratio is sufficiently high (over 30 dB). In principle, the accuracy of the technique seems possible to improve by taking significantly different frequencies selected with regard to the scale negotiation condition. However, it should be mentioned that the implementation of the relevant algorithm in practice is much more complicated than the conventional scheme with a single frequency and several antenna baselines.

Sensitivity analysis of thermoacoustic oscillation in cryogenics system based on response surface method

In the practical application of cryogenic systems, the presence of thermoacoustic oscillation can cause a series of adverse consequences such as pressure fluctua-tions, thermal leakage, structural damage, and so on. To ensure stable operation of the system, variable cross-section control pipe fittings are introduced, and re-sponse surface analysis method is used to optimize the parameter design of the control pipe fittings. A series of simulations have been conducted and the response surface method is introduced to conduct variance analysis on the simulation re-sults, and obtain the regression model of the system pressure ratio, then analyze the interaction between parameters. The analysis of variance shows that the cor-relation coefficient and adjustment coefficient are both close to 1.0, the signal to noise ratio is high, and the fitting degree of the regression model is good. The prediction error of the regression model for the pressure ratio is within ?10, and the distribution of the residual meets the random normal distribution, which can predict the system performance within the parameter design range. The interaction between pipe diameter and length has no significant impact on the oscillation state, so in design, priority should be given to the impact of location and pipe diameter. This work will provide the basis for determining the optimal control structure size of oscillation-free piping system.

Reversible data hiding scheme using deep learning and visual cryptography for medical image communication

Due to a growth in information sharing and the use of multiple digital technologies, human lifestyles have been delivered into the virtual world. This digital world has seen the use of images in special fields increase dramatically, especially in healthcare. Healthcare services can be delivered remotely through telemedicine, a well-known method of providing quality healthcare for people worldwide. There is the risk of illegal exploitation of medical data when telemedicine applications involve exposing data over open networks. In particular, medical experts should exercise more caution when sharing a patient’s private information. In the proposed model, reversible data concealment is combined with visual cryptography to provide a secure method of exchanging medical images. A cover image is divided into nonoverlapping secret shares using Hadamard matrix. Secret digital imaging communication in medicine (DICOM) image is encoded by a deep learning model and embedded into secret shares for secure medical image sharing. Finally, the DICOM image is fully reversibly extracted with the cover image. In this case, a visual cryptographic design is used to secure the embedded secret shares. Furthermore, the metrics, such as mean squared error, peak-signal–to-noise ratio, and normalized correlations, are evaluated in the suggested scheme and are compared with various research outcomes to determine the performance of the nominated model.

Optimizing the Measurement of 0.5-kHz Cubic Distortion Product Otoacoustic Emission.

The measurement of low-frequency cubic distortion product otoacoustic emission, for example, 0.5-kHz cubic distortion product otoacoustic emission, is often severely affected by background noise, and currently 0.5-kHz cubic distortion product otoacoustic emission is not commonly applicable in clinical setting. The fundamental part of current study was the optimization of recording technology to reduce noise interference with the measurement of 0.5-kHz cubic distortion product otoacoustic emission and to establish the response patterns of cubic distortion product otoacoustic emission across speech frequencies from 0.5 to 8kHz in the presence of normal hearing and noise-induced hearing loss. After a series of optimization, a clinically applicable technology of measuring 0.5-kHz cubic distortion product otoacoustic emission was successfully completed via animal model. Cubic distortion product otoacoustic emission was recorded in 6 guinea pigs across speech frequencies from 0.5 to 8kHz before and after exposure to white bandnoise between 0.5 and 2 kHz. After noise exposure, significant reduction in the signal-to-noise ratio of cubic distortion product otoacoustic emission was found at 0.5 and 2 kHz, indicating our recording technology was sensitive and accurate. Other interesting finding was the reduction in cubic distortion product otoacoustic emiss ion-s ignal -to-n oise ratio at 4 and 6 kHz although the reduction was not statistically significant probably because of short exposure time. The result implied that the damaging effect induced by low-frequency noise exposure might spread upward to high-frequency region. Our recording technology was stable and reliable and had the great potentiality to be used in clinical setting.

Automatic detection and classification of baleen and toothed whale calls via machine learning approaches over instantaneous wide areas in the Gulf of Maine received on a coherent hydrophone array

Large acoustic data sets are typically generated from ocean observations with a 160-element coherent hydrophone array and correspondingly larger volumes of acoustic detection events stem from coherent array processing. Beamforming enhances detection signal to-noise ratio, significantly improving detection ranges, as well as providing signal bearing. Here, we develop and train algorithms for the automatic detection and classification of baleen and toothed whale calls present in multiple beamformed spectrograms spanning 360 degree azimuths generated via the passive ocean acoustic waveguide remote sensing technique in the following six categories for the Gulf of Maine: Fin, Sei, Minke, Humpback, unidentified baleen whale downsweep chirps, and general toothed whale encompassing echolocation clicks and whistles below 4 kHz. The classifiers include random forest, support vector machine (SVM), and decision tree applied to hand-engineered features, as well as Convolutional Neural Network (CNN)-based model on the per-channel energy normalization transform (PCEN) applied directly to beamformed spectrogram imagery. Total accuracy of 95% and average F1-score of 85% are achieved using random forest classifier. The processing flow, including beamforming, PCEN extraction and call classification, run in real-time making the methods suitable for real-world applications, such as marine mammal monitoring and mitigation in ocean hydrocarbon prospecting and wind farm installations.

Minimally Equicorrelated MIMO Modelling for NLOS MM Wave Performance Improvement

The 5G physical layer has evolved rapidly. With transmissions at 28, 38, and 72 GHz, millimeter (MM) wave communications are at the core of it. Such links provide improved data rates to an increased number of users availing around 20 GHz of free spectrum. Directional arrays in multiple-input multiple-output (MIMO) setups facilitate beamsteered transmissions. Maximal ratio combining (MRC) receivers aid MM wave signaling and link metrics are analyzed in terms of antenna correlations. The system model is evaluated assuming a short range, non-line-of-sight (NLOS) MM wave user under independently correlated, Rayleigh conditions. This paper showcases analytical closed form expressions for received signal, output signal- to-noise ratio (SNR), line-of-sight (LOS), probability density function (PDF), and NLOS average capacity of the proposed MM wave link. The derivations exhibit capacity alterations with transceiver correlations. MM wave correlation matrices have unique dependency on steering vectors or corresponding transmission angles. This does not apply to millimeter wave.

A Novel Image Super-Resolution Reconstruction Framework Using the AI Technique of Dual Generator Generative Adversarial Network (GAN)

Image superresolution (SR) is the process of enlarging and enhancing a low-resolution image. Image superresolution helps in industrial image enhancement, classification, detection, pattern recognition, surveillance, satellite imaging, medical diagnosis, image analytics, etc. It is of utmost importance to keep the features of the low-resolution image intact while enlarging and enhancing it. In this research paper, a framework is proposed that works in three phases and generates superresolution images while keeping low-resolution image features intact and reducing image blurring and artifacts. In the first phase, image enlargement is done, which enlarges the low-resolution image to the 2x/4x scale using two standard algorithms. The second phase enhances the image using an AI-empowered Generative adversarial network (GAN). We have used a GAN with dual generators and named it EffN-GAN (EfficientNet-GAN). Fusion is done in the last phase, wherein the final improved image is generated by fusing the enlarged image and GAN output image. The fusion phase helps in reducing the artifacts. We have used the DIV2K dataset to train the GAN and further tested the results on the images of Set5, Set14, B100, Urban100, Manga109 datasets with ground truth of size 224x224x3. The obtained results were compared with the state-of-the-art superresolution approach based on important image quality parameters, namely, Peak signal-to--to-noise ratio (PSNR), Structural similarity index (SSIM), Visual information fidelity (VIF) image quality parameters. The results show that the proposed framework for generating super-resolution images from 2x/4x resolution downgraded images improves the aforementioned mentioned image quality parameters significantly.

Abstract 2454: Imaging pancreatic ductal adenocarcinoma using a zinc-sensitive MRI contrast agent: A novel method to detect early-stage PDAC lesions

Abstract Background: Zinc content and its flux from the exocrine pancreas are both novel candidates for molecular imaging of pancreatic ductal adenocarcinoma (PDAC) due to the markedly dysregulated homeostasis in PDAC lesions. Here, we introduce the use of a Gd-based zinc probe (GdL) to monitor stimulated exocrine function in the healthy and PDAC bearing mouse pancreas by MRI. Methods: Male adult mice were implanted with syngeneic PDAC cells into the pancreas and allowed to form PDAC for 1 and 2 weeks. Healthy mice were used as controls. Mice were fasted overnight and imaged in a 4.7 T scanner. Two 2D T1-weighted gradient echo scans were obtained as baseline (TE/TR = 2.9/125 ms, Avg = 4). Mice then received either 1) 0.07mmol/kg GdL (i.v.) plus 10 ug/kg caerulein (i.p.), 2) 0.07mmol/kg GdL (i.v.) plus Saline (i.p.), or 3) 0.01 mmol/kg Gd-DOTA (i.v.). Immediately following injections, serial 2D T1-weighted gradient echo scans were obtained for 25 minutes. PDAC mice receiving saline were considered as negative controls. Change in contrast to-noise ratio (CNR) of tumor and pancreas was quantified and reported as a function of time. Tumor and pancreas tissue were then fixed, and histological analysis was done to characterize the expression of zinc transporters in healthy pancreas and PDAC tissues. Results: Secretagogue-stimulated zinc secretion (SSZS) MRI of the exocrine pancreas relies on evoking zinc release from intracellular stores from acinar and ductal cells. After i.p. injection of the secretagogue caerulein in fasted healthy animals, we observed only a small enhancement in the pancreas. However, both groups of animals carrying orthotopically implanted PDAC cells (1-wk and 2-wks) responded in hyper-secretory fashion. Negative controls (saline group) did not show significant pancreatic or tumor enhancement. Importantly, the effect of caerulein in PDAC animals and the increase in overall pancreatic enhancement were only found in PDAC tumor bearing animals. Dysregulation of zinc trafficking was confirmed by immunohistochemistry staining for the zinc import transporters ZIP3 and ZIP4. These transporters were upregulated only in PDAC-bearing pancreas and the positive staining was concentrated mostly in the tumor parenchyma and gradually dissipated in the surrounding pancreatic tissue. Conclusions: Zinc flux is markedly upregulated in PDAC. By stimulating the natural zinc secretion from exocrine pancreatic cells using an exogenous secretagogue, caerulein, we can non-invasively monitor early malignant transformations in pancreatic parenchyma and tumor cells by MRI with a Gd-based zinc sensitive probe. Citation Format: Mozhdeh Sojoodi, Ian Ramsay, Eric Gale, Stephen C. Barrett, Motaz Qadan, Peter Caravan, Kenneth K. Tanabe, Veronica Clavijo Jordan. Imaging pancreatic ductal adenocarcinoma using a zinc-sensitive MRI contrast agent: A novel method to detect early-stage PDAC lesions [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2454.

Image reconstruction based on a single-pixel camera and left optimization

Subject of study. A set of schemes that can make the single-pixel camera use the prior information of the image to improve the image reconstruction effect is proposed. Method. After the measurement data of the single-pixel camera is processed by standardization or left optimization, the energy and direction information of the signal can be reflected by the processed data. According to the energy and direction information characteristics of the reconstructed image by orthogonal matching pursuit, the use of total variation minimization algorithms in a specific area can improve the image reconstruction effect. Main Results. Based on the [0,1] random matrix and the [0,1] circulant matrix, the measurement data of the single-pixel camera cannot effectively reflect the energy and direction information of the signal. After the measurement data of a single-pixel camera are processed by standardization, the energy information of the signal can be more clearly reflected. Although the direction information is also reflected, it is not very obvious. After the measurement data of the single-pixel camera are processed by left optimization, both the energy and direction information of the signal can be well reflected. Therefore, the energy and direction information of the measurement data of the single-pixel camera after left optimization can be used as criteria for evaluating the quality of the signal reconstruction. Experimental results show that based on such criteria, using orthogonal matching pursuit and total variation minimization algorithms in different columns of the measurement data can greatly improve the image reconstruction. Even if the measurement data contains noise, the signal- to-noise ratio can be improved by more than 16 dB. Practical significance. In real compressed sensing engineering applications, the measurement data and measurement matrix are the only known factors. Because the real image is unknown, the quality of the reconstruction can only be evaluated based on long-term work experience or logical reasoning on the basis of the results of simulation experiments. Based on the energy and direction information of the measurement data of the single-pixel camera after left optimization, the result of image reconstruction can be evaluated objectively.

Convolutional Neural Network-Based Radar Antenna Scanning Period Recognition

The antenna scanning period (ASP) of radar is a crucial parameter in electronic warfare (EW) which is used in many applications, such as radar work pattern recognition and emitter recognition. For antennas of radars and EW systems, which perform scanning circularly, the method based on threshold measurement is invalid. To overcome this shortcoming, this study proposes a method using the convolutional neural network (CNN) to recognize the ASP of radar under the condition that antennas of the radar and EW system both scan circularly. A system model is constructed, and factors affecting the received signal power are analyzed. A CNN model for rapid and accurate ASP radar classification is developed. A large number of received signal time–power images of three separate ASPs are used for the training and testing of the developed model under different experimental conditions. Numerical experiment results and performance comparison demonstrate high classification accuracy and effectiveness of the proposed method in the condition that antennas of radar and EW system are circular scan, where the average recognition accuracy for radar ASP is at least 90% when the signal to-noise ratio (SNR) is not less than 30 dB, which is significantly higher than the recognition accuracy of NAC and AFT methods based on adaptive threshold detection.

Utility of 3D Double Inversion Recovery Sequence in Paediatric Epilepsy and its Comparison to 3D Fluid Attenuation Inversion Recovery Sequence and T1 Inversion Recovery Sequence : A Cross-sectional Study

Introduction: Epilepsy is a disease with predisposition to generate epileptic seizures, associated with neurobiological, cognitive, psychological, and social consequences. Nearly 30% of children undergoing medical treatment for epilepsy become refractive to the treatment. For those children, the ability to find the epileptogenic area is higher with Magnetic Resonance Imaging (MRI) of the brain. The traditional 2D spin-echo sequences used in epilepsy protocol for adults cannot be used alone in paediatric structural neuroimaging. Additional sequences are needed to identify epileptogenic areas due to differences in myelination. Here, present study compared the role of three volumetric sequences 3D-Fluid Attenuated Inversion Recovery (FLAIR) , 3D-T1 weighted Inversion Recovery (T1-IR) and 3D-Double Inversion Recovery (DIR) for paediatric epilepsy as part of structural neuroimaging. Aim: To assess the utility of 3D-DIR in paediatric epilepsy disorders and localisation of epileptogenic foci in brain, congenital malformations of brain and compare its findings with 3D-FLAIR and 3D-T1-IR. Materials and Methods: The present study was a cross-sectional study of children diagnosed with paediatric epilepsy, who were evaluated with MRI brain at Stanley Medical College, Chennai, Tamil Nadu, India, between April 2020 to April 2021 with three sequences, 3D-DIR, 3D-T1-IR and 3D-FLAIR. Lesions of atleast 3 mm in diameter were identified as foci of high signal intensity and counted in each of the three sequences separately and classified according to their location. Then, average signal intensities of the lesions were calculated manually on each of sequences using Region of Interest (ROI) analysis which had a mean size of 3 mm2 . Then the Signal-to-Noise Ratio (SNR), Contrast to-Noise Ratio (CNR), Contrast Ratio (CR), and Asymmetry Signal Ratio (ASR) were calculated. Results: Evaluation was done on 51 paediatric epilepsy patients and showed the total number of lesions detected (208 lesions) and measured contrast parameters (CR, CNR and ASR) which were found to be significantly higher in 3D-DIR, showed higher detection of the intracortical and white matter lesions than 3DFLAIR and 3D-T1-IR. SNR was higher in 3D-FLAIR. Conclusion: Present study concluded that the greatest value of the DIR sequence has a higher ability in detecting epileptogenic foci and congenital malformations of the lesions in comparison with FLAIR and T1-IR.

Characterization of Resting State Default Mode Network in Individuals with HbSS and HbSC, and Healthy Controls Using 7-Tesla Human MRI

Sickle cell disease (SCD) is complicated by accelerated brain aging and cerebrovascular complications leading to structural brain damage and altered resting state functional connectivity (RS-FC). Investigation of the Default Mode Network (DMN), the most studied of the RS-FC networks, by functional MRI may provide insight into the neurological and neuropsychiatric complications of SCD. Prior studies have largely focused on the HbSS genotype of SCD as opposed to the HbSC genotype, which accounts for 30% of the total SCD cases in the US. Both genotypes are expected to impact brain disease, but in different manner.The aim of this study was to characterize the DMN in patients with HbSC, HbSS and healthy race and age-matched controls using state of the art 7-Tesla (7T) magnetic resonance imaging (MRI) with high contrast- and signal- to-noise ratios. On the day of the MRI scanning, participants were administered the brief pain inventory questionnaire (BPI), the digit symbol substitution test of cognitive function, and underwent basic blood work. Controls (n= 43, 53% female, mean age = 36+/-12 years), patients with HbSS (n=19, 63% female, mean age= 36+/-12) and HbSC (n=16 (50% female, mean age=36+/-13) were scanned using a 7T Siemens Magnetom scanner with the Tic Tac Toe radiofrequency coil system (Ibrahim et al., 2013). We obtained whole brain structural T1-weighted images and blood oxygenations level dependent resting state functional MRI (RS-fMRI). During the RS-fMRI, participants were instructed to keep their eyes open, look at a fixation cross, and lie without motion in the scanner. To identify significant differences in RS-FC between the groups, we conducted voxel-wise nonparametric analysis of variance. In the cortical areas with significant clusters, we ran ad-hoc t-tests (controls vs. HbSS, HbSC vs. HbSS, 1000 permutations, uncorrected cluster forming threshold = p < 0.001, family-wise error (FWE) rate=0.05) and we added age and sex as confounders. Then, we correlated RS-FC and the following variables: age, hemoglobin, BPI total, and DSST score.We found a significant difference between the three groups in the DMN (Fig 1) (p=0.0002). The ad-hoc t-tests showed that in the DMN, the RS-FC for the medial prefrontal cortex (mPFC) was significantly higher for the controls when compared to patients with HbSS (p=0.002). RS-FC for the mPFC was also significantly higher in patients with HbSC as compared to HbSS (p=0.001). There was a non-significant trend towards lower RS-FC in patients with HbSC as compared to controls. We also found weak non-significant negative correlation, (r= -0.24, p=0.1315), a strong significant negative correlation (r=-0.5, p=0.04) and very strong significant negative correlation (r=-0.8, p=0.001) between age and RS-FC in the mPFC for controls, HbSC, and HbSS patients, respectively. (Fig 2). We did not find any significant correlation between the RS-FC in the three groups and Hb levels, BPI total, and DSST score.In this work and for the first time, using 7T human MRI we identified altered RS-FC between SCD genotypes and between controls and patients with HbSS. It is notable that the RS-FC for HbSC patients was intermediate between that of the other two groups. Our results imply the RS-FC levels might be susceptible to disease genotype and not necessarily Hb levels, cognition and pain. The finding of a stronger correlation between age and FC in patients with SCD as compared to controls corroborates the notion that accelerated brain aging is operant in SCD. [Display omitted] DisclosuresNovelli: Novartis Pharmaceuticals: Consultancy.