Deep Learning Method for Rapid Simultaneous Multistructure Temporal Bone Segmentation.

OBJECTIVE: To develop and validate a deep learning algorithm for the automated segmentation of key temporal bone structures from clinical computed tomography (CT) data sets. STUDY DESIGN: Cross-sectional study. SETTING: A total of 325 CT scans from a clinical database. METHOD: A state-of-the-art deep learning (DL) algorithm (SwinUNETR) was used to train a prediction model for rapid segmentation of 9 key temporal bone structures in a data set of 325 clinical CTs. The data set was manually annotated by a specialist to serve as the ground truth. The data set was randomly split into training (n = 260) and testing (n = 65) sets. The model's performance was objectively assessed through external validation on the test set using metrics including Dice, Balanced accuracy, Hausdorff distances, and processing time. RESULTS: The model achieved an average Dice coefficient of 0.87 for all structures, an average balanced accuracy of 0.94, an average Hausdorff distance of 0.79 mm, and an average processing time of 9.1 seconds per CT. CONCLUSION: The present DL model for the automated simultaneous segmentation of multiple structures within the temporal bone from CTs achieved high accuracy according to currently commonly employed objective analysis. The results demonstrate the potential of the method to improve preoperative evaluation and intraoperative guidance in otologic surgery.

Nanozyme colorimetric sensing of L-cysteine and copper ions based on PtCo nanoparticles@multi-walled carbon nanotubes.

In this work, PtCo bimetallic nanoparticles supported on multi-walled carbon nanotubes (PtCo@MWCNTs) nanohybrid was prepared simply and used for the first time as a novel nanozyme in the colorimetric sensing of L-cysteine (L-Cys) and Cu2+. Due to its strong enzyme-like catalytic activity, the prepared PtCo@MWCNTs nanohybrid can catalyze the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) to form ox-TMB without H2O2. Interestingly, the oxidase-like active of PtCo@MWCNTs was effectively suppressed by L-Cys, which could reduce ox-TMB to colorless TMB and lead to a pronounced blue fading, and the absorbance at 652 nm gradually decreased with increasing L-Cys concentration. On the other hand, the nanozyme activity of PtCo@MWCNTs can be recovered due to the complexation between L-Cys and Cu2+. Therefore, a colorimetric method based on PtCo@MWCNTs nanozyme was established to detect L-Cys and Cu2+. The results show that the assay platform has simple, rapid, sensitive performance and good selectivity. The detection limits for L-Cys and Cu2+ are 0.041 µM and 0.056 µM, respectively, coupled with the linearities of 0.01 ~ 60.0 µM and 0.05 ~ 80.0 µM. The successful first application of PtCo bimetal-based nanozyme in colorimetric sensing herein opens a new direction for nanozyme and colorimetric analysis, showing great potential applications.

Automated Radiomic Analysis of Vestibular Schwannomas and Inner Ears Using Contrast-Enhanced T1-Weighted and T2-Weighted Magnetic Resonance Imaging Sequences and Artificial Intelligence.

OBJECTIVE: To objectively evaluate vestibular schwannomas (VSs) and their spatial relationships with the ipsilateral inner ear (IE) in magnetic resonance imaging (MRI) using deep learning. STUDY DESIGN: Cross-sectional study. PATIENTS: A total of 490 adults with VS, high-resolution MRI scans, and no previous neurotologic surgery. INTERVENTIONS: MRI studies of VS patients were split into training (390 patients) and test (100 patients) sets. A three-dimensional convolutional neural network model was trained to segment VS and IE structures using contrast-enhanced T1-weighted and T2-weighted sequences, respectively. Manual segmentations were used as ground truths. Model performance was evaluated on the test set and on an external set of 100 VS patients from a public data set (Vestibular-Schwannoma-SEG). MAIN OUTCOME MEASURES: Dice score, relative volume error, average symmetric surface distance, 95th-percentile Hausdorff distance, and centroid locations. RESULTS: Dice scores for VS and IE volume segmentations were 0.91 and 0.90, respectively. On the public data set, the model segmented VS tumors with a Dice score of 0.89 ± 0.06 (mean ± standard deviation), relative volume error of 9.8 ± 9.6%, average symmetric surface distance of 0.31 ± 0.22 mm, and 95th-percentile Hausdorff distance of 1.26 ± 0.76 mm. Predicted VS segmentations overlapped with ground truth segmentations in all test subjects. Mean errors of predicted VS volume, VS centroid location, and IE centroid location were 0.05 cm 3 , 0.52 mm, and 0.85 mm, respectively. CONCLUSIONS: A deep learning system can segment VS and IE structures in high-resolution MRI scans with excellent accuracy. This technology offers promise to improve the clinical workflow for assessing VS radiomics and enhance the management of VS patients.

Improving Transcranial Acoustic Targeting: The Limits of CT-Based Velocity Estimates and the Role of MR.

Transcranial magnetic resonance-guided focused ultrasound (tcMRgFUS) enables the noninvasive treatment of the deep brain. This capacity relies on the ability to focus acoustic energy through the in-tact skull, a feat that requires accurate estimates of the acoustic velocity in individual patient skulls. In current practice, these estimates are generated using a pretreatment computed tomography (CT) scan and then registered to a magnetic resonance (MR) dataset on the day of the treatment. Treatment safety and efficacy can be improved by eliminating the need to register the CT data to the MR images and by improving the accuracy of acoustic velocity measurements. In this study, we examine the capacity of MR to supplement or replace CT as a means of estimating velocity in the skull. We find that MR can predict velocity with less but comparable accuracy to CT. We then use micro-CT imaging to better understand the limitations of Hounsfield unit (HU)-based estimates of velocity, demonstrating that the macrostructure of pores in the skull contributes to the acoustic velocity of the bone. We find evidence that detailed T2 measurements provide information about pore macrostructure similar to the information obtained with micro-CT, offering a potential clinical mechanism for improving patient-specific estimates of acoustic velocity in the human skull.

Distortion-Free Diffusion Imaging Using Self-Navigated Cartesian Echo-Planar Time Resolved Acquisition and Joint Magnitude and Phase Constrained Reconstruction.

Echo-planar time resolved imaging (EPTI) is an effective approach for acquiring high-quality distortion-free images with a multi-shot EPI (ms-EPI) readout. As with traditional ms-EPI acquisitions, inter-shot phase variations present a main challenge when incorporating EPTI into a diffusion-prepared pulse sequence. The aim of this study is to develop a self-navigated Cartesian EPTI-based (scEPTI) acquisition together with a magnitude and phase constrained reconstruction for distortion-free diffusion imaging. A self-navigated Cartesian EPTI-based diffusion-prepared pulse sequence is designed. The different phase components in EPTI diffusion signal are analyzed and an approach to synthesize a fully phase-matched navigator for the inter-shot phase correction is demonstrated. Lastly, EPTI contains richer magnitude and phase information than conventional ms-EPI, such as the magnitude and phase correlations along the temporal dimension. The potential of these magnitude and phase correlations to enhance the reconstruction is explored. The reconstruction results with and without phase matching and with and without phase or magnitude constraints are compared. Compared with reconstruction without phase matching, the proposed phase matching method can improve the accuracy of inter-shot phase correction and reduce signal corruption in the final diffusion images. Magnitude constraints further improve image quality by suppressing the background noise and thereby increasing SNR, while phase constraints can mitigate possible image blurring from adding magnitude constraints. The high-quality distortion-free diffusion images and simultaneous diffusion-relaxometry imaging capacity provided by the proposed EPTI design represent a highly valuable tool for both clinical and neuroscientific assessments of tissue microstructure.

Study on Delamination Between Polymer Materials and Metals in IC Packaging Process.

The electronic package interconnects electronic signals from one area to another and package delamination is a serious problem in the configuration of materials. This study focused on decreasing the delamination of the low-profile fine pitch ball grid array (LFBGA) and plastic ball grid array (PBGA) packages in terms of polymer thermal issue, metal bonding and bonding mechanisms. PBGA and LFBGA are a very common type of packaging processes in the electronics industry. The present study dealt first with delamination of the LFBGA packaging, through characterization and determination of physical and chemical properties such as surface roughness, surface energy, and contact angle. The relationship between surface roughness and delamination was verified through various roughness bonding experiments. In addition, the surface energy was determined by measuring the contact angle after cleaning the metal surface of Cu, Ni and Cr with Ar + O2 gas, and, this gas plasma treatment was applied to enhance the adhesive properties. The compositions of the surface were analyzed through an X-ray photoelectron spectroscopy (XPS). Also, the delamination issue between the corner of the heat sink cap and the epoxy resin was observed for delamination of the LFBGA packaging. Further, this study analyzed the PBGA packaging process through the finite element analysis simulation software ANSYS. To improve the heat sink cap delamination issue of the PBGA, a new chamfer design of the corner seat was streamlined to decrease the stress value and delamination. Besides, the simulation results demonstrated that the stress value reduced after increasing the shoulder length. The results implicate that the stress value is inversely proportional to the shoulder width and the chamfer radius. This study demonstrated that the optimization in design was able reduce the delamination phenomena in configuration material.

Functional magnetic resonance electrical impedance tomography (fMREIT) sensitivity analysis using an active bidomain finite-element model of neural tissue.

PURPOSE: A direct method of imaging neural activity was simulated to determine typical signal sizes. METHODS: An active bidomain finite-element model was used to estimate approximate perturbations in MR phase data as a result of neural tissue activity, and when an external MR electrical impedance tomography imaging current was added to the region containing neural current sources. RESULTS: Modeling-predicted, activity-related conductivity changes should produce measurable differential phase signals in practical MR electrical impedance tomography experiments conducted at moderate resolution at noise levels typical of high field systems. The primary dependence of MR electrical impedance tomography phase contrast on membrane conductivity changes, and not source strength, was demonstrated. CONCLUSION: Because the injected imaging current may also affect the level of activity in the tissue of interest, this technique can be used synergistically with neuromodulation techniques such as deep brain stimulation, to examine mechanisms of action.

Evaluation of magnetohydrodynamic effects in magnetic resonance electrical impedance tomography at ultra-high magnetic fields.

PURPOSE: Artifacts observed in experimental magnetic resonance electrical impedance tomography images were hypothesized to be because of magnetohydrodynamic (MHD) effects. THEORY AND METHODS: Simulations of MREIT acquisition in the presence of MHD and electrical current flow were performed to confirm findings. Laminar flow and (electrostatic) electrical conduction equations were bidirectionally coupled via Lorentz force equations, and finite element simulations were performed to predict flow velocity as a function of time. Gradient sequences used in spin-echo and gradient echo acquisitions were used to calculate overall effects on MR phase images for different electrical current application or phase-encoding directions. RESULTS: Calculated and experimental phase images agreed relatively well, both qualitatively and quantitatively, with some exceptions. Refocusing pulses in spin echo sequences did not appear to affect experimental phase images. CONCLUSION: MHD effects were confirmed as the cause of observed experimental phase changes in MREIT images obtained at high fields. These findings may have implications for quantitative measurement of viscosity using MRI techniques. Methods developed here may be also important in studies of safety and in vivo artifacts observed in high field MRI systems.

The effect of potassium chloride on Aplysia Californica abdominal ganglion activity.

OBJECTIVE: Spontaneous activity in the abdominal ganglion of Aplysia can be used as a convenient bioelectricity source in tests of novel MRI-based functional imaging methods, such as functional Magnetic Resonance Electrical Impedance Tomography (fMREIT). In these tests, it is necessary to find a consistent treatment that modulates neural activity, so that these results can be compared with control data. Effects of MREIT imaging currents combined with treatment were also of interest. APPROACH: Potassium chloride (KCl) was employed as a rhythm modulator. In a series of experiments, effects of adding different volumes of KCl solution were tested and compared with experiments on control groups that had artificial sea water administered. In all cases, neuronal activity was measured with micro electrode arrays. MAIN RESULTS: It was possible to reversibly stop spontaneous activity in ganglia by increasing the extracellular potassium chloride concentration to 89 mM. There was no effect on experimental outcomes when current was administered to the sample chamber between recordings. SIGNIFICANCE: KCl can be used as a reversible neural modulator for testing neural detection methods.

Direct detection of neural activity in vitro using magnetic resonance electrical impedance tomography (MREIT).

We describe a sequence of experiments performed in vitro to verify the existence of a new magnetic resonance imaging contrast - Magnetic Resonance Electrical Impedance Tomography (MREIT) -sensitive to changes in active membrane conductivity. We compared standard deviations in MREIT phase data from spontaneously active Aplysia abdominal ganglia in an artificial seawater background solution (ASW) with those found after treatment with an excitotoxic solution (KCl). We found significant increases in MREIT treatment cases, compared to control ganglia subject to extra ASW. This distinction was not found in phase images from the same ganglia using no imaging current. Further, significance and effect size depended on the amplitude of MREIT imaging current used. We conclude that our observations were linked to changes in cell conductivity caused by activity. Functional MREIT may have promise as a more direct method of functional neuroimaging than existing methods that image correlates of blood flow such as BOLD fMRI.

External current application in a bidomain model of active neural tissue.

The formal treatment of tissue as two coupled continua is referred to as a bidomain model. Bidomain models have recently been used to describe the properties of neural tissue and nerve fiber bundles [1, 2]. By adapting the Hodgkin Huxley equations in COMSOL Multiphysics, we have investigated the propagation of an action potential through neural tissue by external current stimulation.

Temperature- and frequency-dependent dielectric properties of biological tissues within the temperature and frequency ranges typically used for magnetic resonance imaging-guided focused ultrasound surgery.

PURPOSE: This study aimed to obtain the temperature- and frequency-dependent dielectric properties of tissues subjected to magnetic resonance (MR) scanning for MR imaging-guided focused ultrasound surgery (MRgFUS). These variables are necessary to calculate radio frequency electromagnetic fields distribution and specific radio frequency energy absorption rate (SAR) in the healthy tissues surrounding the target tumours, and their variation may affect the efficacy of advanced RF pulses. MATERIALS AND METHODS: The dielectric properties of porcine uterus, liver, kidney, urinary bladder, skeletal muscle, and fat were determined using an open-ended coaxial probe method. The temperature range was set from 36 °C to 60 °C; and the frequencies were set at 42.58 (1 T), 64 (1.5 T), 128 (3 T), 170 (4 T), 298 (7 T), 400 (9 T), and 468 MHz (11 T). RESULTS: Within the temperature and frequency ranges, the dielectric constants were listed as follows: uterus 49.6-121.64, liver 44.81-127.68, kidney 37.3-169.26, bladder 42.43-125.95, muscle 58.62-171.7, and fat 9.2327-20.2295. The following conductivities were obtained at the same temperature and frequency ranges: uterus 0.5506-1.4419, liver 0.5174-0.9709, kidney 0.8061-1.3625, bladder 0.6766-1.1817, muscle 0.8983-1.3083, and fat 0.1552-0.2316. CONCLUSIONS: The obtained data are consistent with the temperature and frequency ranges typically used in MRgFUS and thus can be used as reference to calculate radio frequency electromagnetic fields and SAR distribution inside the healthy tissues subjected to MR scanning for MRgFUS.