Array Position Research Articles

Scala Tympani Volume Influences Initial 6-Month Hearing Preservation With Lateral Wall Electrode Arrays.

To examine the effects of scala tympani (ST) volume, cochlear duct length (CDL), and angular insertion depth (AID) on low-frequency hearing preservation for cochlear implant (CI) recipients of lateral wall electrode arrays. A retrospective review identified 45 adult CI recipients of 24-, 28-, or 31.5-mm lateral wall electrode arrays with preoperative unaided hearing thresholds ≤45 decibel hearing level (dB HL) at 250 Hz. All patients underwent preoperative and postoperative computed tomography to evaluate cochlear morphology and electrode array position. A linear mixed effects model evaluated effects of ST volume, CDL, AID, preoperative low-frequency pure-tone average (LFPTA; 125, 250, and 500 Hz), age at surgery, and biological sex on the postoperative change in LFPTA at activation and 6 months post-activation. There were significant main effects of ST volume (p = 0.044), age (p = 0.028), and biological sex (p = 0.003), indicating better low-frequency hearing preservation for CI recipients with larger ST volumes, younger age at surgery, and female biological sex. Although CDL positively correlated with ST volume (r = 0.74, p < 0.001), there was no significant main effect of CDL (p = 0.367). A broad range in AID of the most apical electrode contact was observed (301.4°-681.8°); however, there was no significant main effect of AID on low-frequency hearing preservation (p = 0.700). During the initial 6 months following implantation, intrinsic factors such as cochlear morphology may have a greater impact on low-frequency hearing preservation than apical positioning of a flexible lateral wall electrode array when using soft surgical techniques. 3 Laryngoscope, 2024.

TMOD-09. NEWLY DESIGNED TUMOR TREATING FIELDS (TTFIELDS) ARRAYS FOR THE MOUSE HEAD DEMONSTRATE EFFICACY FOR TREATMENT OF GLIOBLASTOMA

Abstract Tumor Treating Fields (TTFields) therapy is a cancer treatment modality based on continuous, non-invasive delivery of electric fields. TTFields therapy is approved for treatment of glioblastoma (GBM), delivered to the patient’s brain by two array pairs placed on the scalp. Further research in animals to expand the knowledge regarding TTFields treatment of GBM is limited, as this is mainly performed in mouse models and arrays for application of TTFields to the mouse head are lacking. The small dimensions and specific geometries of the mouse head make the development of such arrays challenging. The aim of this study was to design arrays that will allow efficient and stable delivery of TTFields to the mouse head. To overcome the small head size, we developed a layout with two arrays situated on the head of the mouse, each divided into two smaller disks, and positioned opposite two arrays on the torso. We identified a thin and transparent adhesive tape (facilitating correct array positioning) with good tackiness and easy removal (without leaving residual adhesive on the skin). The arrays met the minimum treatment requirements: current ≥ 50 mA, usage ≥ 75%, field intensity ≥ 1 V/cm RMS. We then conducted an efficacy study with the new arrays, using GL-261 GBM cells intracranially injected into C57BL/6 mice. Treatment with sham-heat (control) or TTFields was initiated 11 days following tumor inoculation and maintained continuously for 12 days. Efficacy was measured via magnetic resonance imaging (MRI) of tumor volume, showing a decrease of 31% at treatment end in TTFields-treated mice versus the control. Overall, the new arrays are flexible, strongly adherent, deliver TTFields at a sufficient intensity, and showed efficacy for treating GBM in mice.

Study and Analysis of the Thunder Source Location Error Based on Acoustic Ray-Tracing

Error analysis and estimation of thunder source location results is a prerequisite for obtaining accurate location results of thunder sources, which is of great significance for a deeper understanding of the physical process of lightning channel discharges. Most of the thunder source location algorithms are based on the simplified model of the straight-line propagation of acoustic waves to determine the location of the thunder source; however, the acoustic wave is affected by the inhomogeneity of the atmosphere medium in the propagation process and its acoustic ray will be bent. Temperature and humidity are the main factors affecting the vertical distribution of the velocity of sound in the atmosphere, therefore, it is necessary to study the changes in location errors under the models of uniform vertical distribution of temperature only and uniform vertical distribution of humidity only. This paper focuses on the theory of acoustic ray-tracing in neglecting the presence of the wind and the acoustic attenuation and the theoretical derivation of the location error of thunder source inversion for the three models is carried out by using MATLAB R2019b programming. Then, simulation analysis and comparative study on the variation law of thunder source location error with the height of the source, ground temperature, ground humidity, and array position under the three models are carried out. The results of the study show that the maximum location error can be obtained from the straight-line propagation model, the location error obtained from the model of uniform vertical distribution of temperature only is the second, and the location error obtained from the model of uniform vertical distribution of humidity only is the least and can be negligible compared to the first two models. In the trend of error variation, the variation of location error with temperature and humidity is relatively flat in the first two models; however, the variation of location error with the height of the thunder source is more drastic, which can be more than 80%. The location error obtained from the array inversion closer to the thunder source increases linearly with the height of the thunder source, the location error obtained from the more distant array inversion shows a fast-decreasing trend at the height of the thunder source from 500 to 3500 m, and a flat trend above 3500 m. The location error varies relatively smoothly with the height of the thunder source, the ground temperature, and the ground humidity in the model of uniform vertical distribution of humidity only. In addition, the position of the array also has an important effect on lightning location. The further the horizontal distance from the source, the greater the location error will be obtained in the first two models, and when the thunder source is at a low height and detected at a long distance, the location error will be very large, so relevant data should be modified in actual observation.

High-Precision Bi-Directional Beam-Pointing Measurement Method Based on Space Solar Power Station System.

In the process of wireless energy transmission from a Space Solar Power Station (SSPS) to a satellite, the efficiency of energy transmission is closely related to the accuracy of beam control. The existing methods commonly ignore the impact of array position, structural deviation of the transmitting antenna, and modulation errors, which leads to the deviation error in actual energy transmission beams and the reduction of energy transmission efficiency. This paper innovatively proposes a high-precision bi-directional beam-pointing measurement method, which provides a technical basis for advancing the beam-pointing control accuracy from the perspective of improving the beam-pointing measurement accuracy. The method consists of (1) the interferometer goniometry method to realize high-precision guiding beam pointing measurement; and (2) the power field reconstruction method to realize offset angle measurement of the energy-transmitting beam. Simulation results demonstrate that under dynamic conditions, the guiding beam-pointing measurement accuracy of this method reaches 0.05°, which is better than the traditional 0.1° measurement accuracy based on the guiding beam. The measurement accuracy of the offset distance of the energy center is better than 0.11 m, and the measurement accuracy of the offset angle is better than 0.012°.

A robust myoelectric pattern recognition framework based on individual motor unit activities against electrode array shifts

Background and objectiveElectrode shift is always one of the critical factors to compromise the performance of myoelectric pattern recognition (MPR) based on surface electromyogram (SEMG). However, current studies focused on the global features of SEMG signals to mitigate this issue but it is just an oversimplified description of the human movements without incorporating microscopic neural drive information. The objective of this work is to develop a novel method for calibrating the electrode array shifts toward achieving robust MPR, leveraging individual motor unit (MU) activities obtained through advanced SEMG decomposition. MethodsAll of the MUs from decomposition of SEMG data recorded at the original electrode array position were first initialized to train a neural network for pattern recognition. A part of decomposed MUs could be tracked and paired with MUs obtained at the original position based on spatial distribution of their MUAP waveforms, so as to determine the shift vector (describing both the orientation and distance of the shift) implicated consistently by these multiple MU pairs. Given the known shift vector, the features of the after-shift decomposed MUs were corrected accordingly and then fed into the network to finalize the MPR task. The performance of the proposed method was evaluated with data recorded by a 16 × 8 electrode array placed over the finger extensor muscles of 8 subjects performing 10 finger movement patterns. ResultsThe proposed method achieved a shift detection accuracy of 100 % and a pattern recognition accuracy approximating to 100 %, significantly outperforming the conventional methods with lower shift detection accuracies and lower pattern recognition accuracies (p < 0.05). ConclusionsOur method demonstrated the feasibility of using decomposed MUAP waveforms’ spatial distributions to calibrate electrode shift. This study provides a new tool to enhance the robustness of myoelectric control systems via microscopic neural drive information at an individual MU level.

Position estimation of acoustic elements based on improved delay estimation algorithm

Array signal processing is extensively utilized in the field of underwater acoustics (UWA). The majority of existing array signal processing algorithms require precise array position information to optimize their functionality. However, the intricate nature of the UWA environment introduces challenges such as the influence of water flow, which may result in deviations from the predetermined array positions. Consequently, this can amplify errors in array processing algorithms. Therefore, a high-precision array positioning method is needed to estimate the actual position of the array. The effectiveness of current array localization algorithms employing delay differential matching depends significantly on the accuracy of delay estimation and the formulation of the ambiguity function. In response to these crucial factors, this paper presents an algorithm for estimating array element positions that leverages an improved approach to delay estimation. Firstly, we propose the ρ-PHAT algorithm enhanced by the artificial fish swarm algorithm (AFSA-PHAT), significantly improving delay estimation accuracy, particularly in low signal-to-noise ratio (SNR) conditions. Compared to the traditional ρ-PHAT algorithm, this approach achieves a 3 dB increase in precision and a reduction in the root-mean-square error (RMSE). Additionally, a novel method is introduced for constructing the ambiguity function, which focuses on minimizing the acoustic complexity to encompass only direct and surface-reflected sounds. This improvement makes it particularly suitable for hydrophone arrays deployed near the sea surface. Computer simulations and experimental results validate that the algorithm, incorporating the aforementioned improvements, achieves enhanced accuracy in position estimation, reduced RMSE, and increased robustness.

The numerical reconstruction methods for characterizing defects by full matrix data using an ultrasonic array

Abstract This study introduces ultrasonic imaging and inversion methods for the quantitative characterization of crack defects. The Total Focusing Method (TFM) is a high-precision ultrasonic imaging method, but it may produce length errors when used for large-angle defect detection. An SV transverse wave TFM method is introduced, significantly reducing length errors in a 60° crack to 8.31%. However, the ultrasonic image method is influenced by factors like array position, limiting its practicality. To overcome this limitation, the study proposes an inversion method using the subarray scattering coefficient matrix, which is more stable and less sensitive to array positioning. Comparative analysis with finite element simulations and experiments indicates optimal array positions associated with different methods. At these positions, both methods yield angular characterization errors for the 60° crack of less than 1%, validating the proposed techniques for non-destructive testing applications.

Sparse TFM imaging of different-scale phased array based on the DWSO algorithm

ABSTRACT Using sparse matrix for total focusing method (TFM) imaging can improve computational efficiency in non-destructive testing (NDT). In sparse matrix design, binary particle swarm optimisation (BPSO) and genetic algorithm (GA) often fall into local optimal solution, and the computational efficiency decreases significantly with the expansion of array scale. In this paper, a discrete war strategy optimisation (DWSO) is proposed to realise sparse array ultrasonic imaging. This method uses equidistant scatter mapping to real-number encode the array position and limit the search range. Then, the fitness function is constructed with low side lobe peak and narrow main lobe width to obtain the optimal array element distribution. Experiments on standard test block demonstrate the DWSO algorithm has a narrower main lobe width and lower side lobe peaks than BPSO and GA. The imaging time of the sparse array constructed by this algorithm is reduced by more than 65% compared with the full array. As array scale grows, the running time variation of the proposed method is reduced by 73.2% and 77.3% compared with GA and BPSO, which has good adaptability and provides theoretical support for real-time defect detection.

Stability discussion of metal carbonates in aqueous solution: Reactive force field and density functional theory

The nucleation and precipitation of metal carbonates occupy a crucial position in a wide array of industrial processes, environmental occurrences, and geological formations. Understanding the fundamental mechanisms underlying these processes is paramount for optimizing industrial applications and mitigating environmental impacts. In this study, we embark on an investigation utilizing reactive force field molecular-dynamics simulations to delve deeply into the nucleation and precipitation process of metal carbonates. These simulations provide profound insights into the mechanisms and kinetics governing the process across diverse conditions. Additionally, through density functional theory calculations, we scrutinize the energetic and dynamical stability of highly hydrated amorphous carbonates and hydrate crystals. Our revelations offer illuminating perspectives on the intricate interplay of factors shaping nucleation and precipitation processes, serving as a foundation for future inquiries in this research field.

Intra-Cochlear Electrode Position Impacts the Preservation of Residual Hearing in an Animal Model of Cochlear Implant Surgery.

Preservation of residual hearing after cochlear implantation remains challenging. There are several approaches to preserve residual hearing, but the configuration of the implant electrode array seems to play a major role. Lateral wall electrode arrays are seemingly more favorable in this context. To date, there are no experimental data available which correlate the spatial electrode position in the scala tympani with the extent of hearing preservation. Based on micro-computed tomography (µCT) imaging data, this study analyses the exact position of a pure silicone electrode array inserted into the cochlea of four guinea pigs. Array position data were correlated with the extent of hearing loss after implantation, measured using auditory brainstem measurements in the frequency range of the area occupied by the electrode array area as well as apical to the array. The use of pure silicone arrays without electrodes resulted in artifact-free, high-resolution µCT images that allowed precise determination of the arrays' positions within the scala tympani. The electrode arrays' locations ranged from peri-modiolar to an anti-modiolar. These revealed a correlation of a lower postoperative hearing loss with a higher spatial proximity to the lateral wall. This correlation was found in the low-frequency range only. A significant correlation between the inter-individual differences in the diameter of the scala tympani and the postoperative hearing loss could not be observed. This study demonstrates the importance of the intra-cochlear electrode array's position for the preservation of residual hearing. The advantage of such an electrode array's position approximated to the lateral wall suggests, at least for this type of electrode array applied in the guinea pig, it would be advantageous in the preservation of residual hearing for the apical part of the cochlea, beyond the area occupied by the electrode array.

A geometric solution to microphone array position calibration and its confidence interval analysis

Wireless acoustic sensor networks (WASNs) comprised of spatially distributed acoustic nodes have been increasingly popular in many areas such as speech enhancement, blind source separation, and audio surveillance, where node position information is generally required to implement relevant processing algorithms. In this article, we focus on the node position calibration only using direction-of-arrival (DOA) information with each node consisting of a microphone array. State-of-the-art techniques translate the position calibration into optimization of DOA-based cost functions, and have shown notable success. However, a compromise between position calibration accuracy and computational load still exists. Furthermore, none of the existing studies can offer a quantitative evaluation of calibration performance before the optimization procedure is finished. To address these problems, a geometric solution to array node position calibration is proposed using DOA measurements. For a given array node, DOAs of three sources are first utilized to construct cylinder, plane, and cone equations. Next, the two-dimensional projection of intersections among these equations is calculated using Sylvesterresultantmatrix. Finally, a closed-form solution of node position in three-dimensional space is established. Moreover, explicit mathematical derivation of the confidence interval analysis on the calibration results under given node angle estimation error condition is presented, indicating that the proposed method can provide predictable performance with corresponding probabilities. The Cramér-Rao bound (CRB) is further investigated. Simulation results reveal that as compared with existing methods our approach achieves comparable calibration accuracy with much less computational burden. Real-world experiments also verify its effectiveness.

A Novel Positional Calibration Method for an Underwater Acoustic Beacon Array Based on the Equivalent Virtual Long Baseline Positioning Model

The performance of long baseline (LBL) positioning systems is significantly impacted by the distribution and positional calibration accuracy of underwater acoustic beacon arrays. In previous calibration methods for beacon arrays based on autonomous underwater vehicle (AUV) platforms, the slant range information of each beacon was processed independently, and each beacon was calibrated one at a time. This approach not only decreases the calibration efficiency but also leaves the positional calibration accuracy of each beacon highly susceptible to the navigation trajectory of the AUV. To overcome these limitations, an equivalent virtual LBL (EVLBL) positioning model is introduced in this paper. This model operates by adjusting the positions of each beacon according to the dead reckoning increments computed during the AUV’s reception of positioning signals, effectively forming a virtual beacon array. Consequently, the AUV is capable of mitigating LBL positioning errors that arise from its motion by simultaneously receiving positioning signals from all beacons. Additionally, an overall calibration method for beacon arrays based on particle swarm optimization (PSO) is proposed. In this approach, the minimization of the deviation between the EVLBL trajectory and the dead reckoning trajectory is set as the optimization objective, and the coordinates of each beacon are iteratively optimized. The simulation results demonstrate that the proposed EVLBL-based PSO algorithm (EVPSO) significantly enhanced the calibration efficiency and positional accuracy of the beacon array. Compared with conventional methods, the estimation error of the beacon positions was reduced from 6.40 m to within 1.00 m. After compensating for the beacon array positions, the positioning error of the LBL system decreased from approximately 5.00 m (with conventional methods) to around 1.00 m (with EVPSO), demonstrating the effectiveness of the proposed approach.

An efficient position optimization method based on improved genetic algorithm and machine learning for sparse array

Sparse array antennas are significant in communication and radar systems due to the advantages of high resolution, low complexity, and immunity to interference. In this letter, a novel array synthesis method based on an improved genetic algorithm (IGA) is proposed to optimize the antenna position in the sparse array. Different from the traditional generic methods with high computational complexity, a method combined with Gaussian process regression (GPR) prediction is proposed to optimize the antenna position with low computational complexity. The proposed method can minimize the peak sidelobe level (PSLL) during the beam scanning procedures. Moreover, the minimum antenna spacing constraint is also considered to ensure a physically achievable solution. Simulation results show that the proposed method can achieve a lower PSLL with fewer iterations and provide a global optimization solution for large array synthesis compared with existing methods. Furthermore, a prototype of the sparse array principle optimized by IGA is designed. Measurement results indicate that the optimized sparse array has good synthesis performance in high frequency.

High fidelity ultrasonic measurements for defect detection and characterisation

Repeatable measurements with detachable transducers such as phased arrays have much potential for enhancing the sensitivity of nondestructive evaluation (NDE), as baseline subtraction can be employed. This paper aims to develop post-processing methods to overcome the variation between inspections which leads to poor subtraction performance. In this paper, ultrasonic immersion inspections are performed on a brass sample and a steel sample with a corroded backwall. Reference measurements are taken, and then small defects are machined to simulate defect growth in industrial applications. Defect types include two 1 mm diameter flat bottom holes (FBH) extending from 15 mm to 17 mm in the brass sample and two 2 mm diameter holes drilled to 1 mm depth from the corroded surface of the steel sample to represent the growth of localised pits. Although FMC/TFM is used in this paper, the defects have similar response amplitudes to the structural noise, and they cannot be detected or characterised directly from the images by the conventional 6 dB drop method. This paper demonstrates the utilisation of ultrasonic measurements, together with cross-correlation, to obtain inspection variables which include array position and couplant wave velocity. By knowing the variations between inspection conditions, compensation is made in post-processing to improve image repeatability, and hence the performance of baseline subtraction. The SNR is improved by approximately 10–25 dB depending on how great the actual variations are. It is shown that these previously undetectable defects can be seen and accurately sized after conducting baseline subtraction with compensation.

Transfer alignment method based on installation deviation angle estimation for array POS

Transfer alignment of array Position and Orientation System (POS) is the key technology to provide motion information for airborne earth observation high-precision imaging. Because the large deviation angle between main Inertial Measurement Unit (IMU) and slave IMU is difficult to accurately measure by existing methods, the transfer alignment accuracy will be seriously affected. Aiming at this issue, a transfer alignment method based on installation deviation angle estimation for array POS is proposed. This method includes two steps: pre-estimation and improved transfer alignment. First, two deviation angles are calculated by angular velocity and acceleration using quaternion optimization method respectively. The higher-precision deviation angle is fused by two deviation angles using their respective weights, which are calculated by Signal to Noise Ratios (SNRs). Second, the result of pre-estimation is used in transfer alignment. Residual errors of deviation angle are considered as state variables and be compensated online. Compared with the existing methods, the velocity, position and attitude errors calculated by this method are reduced by 15.4%, 31.7% and 66.5% respectively. The proposed method significantly reduces the adverse effect of installation deviation angle on measurement accuracy of array POS.

Treatment Planning and Aberration Correction Algorithm for HIFU Ablation of Renal Tumors.

High-intensity focused ultrasound (HIFU) applications for thermal or mechanical ablation of renal tumors often encounter challenges due to significant beam aberration and refraction caused by oblique beam incidence, inhomogeneous tissue layers, and presence of gas and bones within the beam. These losses can be significantly mitigated through sonication geometry planning, patient positioning, and aberration correction using multielement phased arrays. Here, a sonication planning algorithm is introduced, which uses the simulations to select the optimal transducer position and evaluate the effect of aberrations and acoustic field quality at the target region after aberration correction. Optimization of transducer positioning is implemented using a graphical user interface (GUI) to visualize a segmented 3-D computed tomography (CT)-based acoustic model of the body and to select sonication geometry through a combination of manual and automated approaches. An HIFU array (1.5 MHz, 256 elements) and three renal cell carcinoma (RCC) cases with different tumor locations and patient body habitus were considered. After array positioning, the correction of aberrations was performed using a combination of backpropagation from the focus with an ordinary least squares (OLS) optimization of phases at the array elements. The forward propagation was simulated using a combination of the Rayleigh integral and k-space pseudospectral method (k-Wave toolbox). After correction, simulated HIFU fields showed tight focusing and up to threefold higher maximum pressure within the target region. The addition of OLS optimization to the aberration correction method yielded up to 30% higher maximum pressure compared to the conventional backpropagation and up to 250% higher maximum pressure compared to the ray-tracing method, particularly in strongly distorted cases.

Uncovering Vulnerable Phases in Cochlear Implant Electrode Array Insertion: Insights from an In Vitro Model.

The aim of this study is to improve our understanding of the mechanics involved in the insertion of lateral wall cochlear implant electrode arrays. A series of 30 insertion experiments were conducted by three experienced surgeons. The experiments were carried out in a previously validated artificial temporal bone model according to established soft surgery guidelines. The use of an in vitro setup enabled us to comprehensively evaluate relevant parameters, such as insertion force, intracochlear pressure, and exact electrode array position in a controlled and repeatable environment. Our findings reveal that strong intracochlear pressure transients are more frequently caused during the second half of the insertion, and that regrasping the electrode array is a significant factor in this phenomenon. For choosing an optimal insertion speed, we show that it is crucial to balance slow movement to limit intracochlear stress with short duration to limit tremor-induced pressure spikes, challenging the common assumption that a slower insertion is inherently better. Furthermore, we found that intracochlear stress is affected by the order of execution of postinsertion steps, namely sealing the round window and posterior tympanotomy with autologous tissue and routing of the excess cable into the mastoid cavity. Finally, surgeons' subjective estimates of physical parameters such as speed, smoothness, and resistance did not correlate with objectively assessed measures, highlighting that a thorough understanding of intracochlear mechanics is essential for an atraumatic implantation. The results presented in this article allow us to formulate evidence-based surgical recommendations that may ultimately help to improve surgical outcome and hearing preservation in cochlear implant patients.

A New Sparse Bayesian Learning-Based Direction of Arrival Estimation Method with Array Position Errors

In practical applications, the hydrophone array has element position errors, which seriously degrade the performance of the direction of arrival estimation. We propose a direction of arrival (DOA) estimation method based on sparse Bayesian learning using existing array position errors to solve this problem. The array position error and angle grid error parameters are introduced, and the prior distribution of these two errors is determined. The joint probability density distribution function is established by means of a sparse Bayesian learning model. At the same time, the unknown parameters are optimized and iterated using the expectation maximum algorithm and the corresponding parameters are solved to obtain the spatial spectrum. The results of the simulation and the lake experiments show that the proposed method effectively overcomes the problem of array element position errors and has strong robustness. It shows a good performance in terms of its estimation accuracy, meaning that the resolution ability can be greatly improved in the case of a low signal-to-noise ratio or small number of snapshots.

Fastener hole inspection using 2D phased array

Fastener hole cracks, resulting from stress concentration around the hole, are potential sources of failure in mechanical structures. Traditionally, inspection involves manually moving a single ultrasonic probe around the hole or using an eddy current probe to move through the hole. However, single ultrasonic probe inspection is time-consuming and needs skilful operators. Eddy current inspection requires the removal of the fastener in advance and does not allow easy crack sizing and visualization. This paper proposes a novel approach that combines a 2D phased array with a coupling block to enable complete fastener hole inspection from a single array position. A single full matrix capture (FMC) data set is collected, from which 3D volumetric images are formed. To obtain clear images of the geometry and potential defects, half-skip and multi-skip total focusing method imaging algorithms are investigated together with transmitter–receiver pairs selection methods to detect different target features. Experimental results demonstrate that the proposed inspection approach can eliminate dead zone problems and capture all target information from a single inspection position. These methods show great potential in enhancing the efficiency and reliability of fastener hole inspections.

Tumor-treating fields dosimetry in glioblastoma: Insights into treatment planning, optimization, and dose-response relationships.

Tumor-treating fields (TTFields) are currently a Category 1A treatment recommendation by the US National Comprehensive Cancer Center for patients with newly diagnosed glioblastoma. Although the mechanism of action of TTFields has been partly elucidated, tangible and standardized metrics are lacking to assess antitumor dose and effects of the treatment. This paper outlines and evaluates the current standards and methodologies in the estimation of the TTFields distribution and dose measurement in the brain and highlights the most important principles governing TTFields dosimetry. The focus is on clinical utility to facilitate a practical understanding of these principles and how they can be used to guide treatment. The current evidence for a correlation between TTFields dose, tumor growth, and clinical outcome will be presented and discussed. Furthermore, we will provide perspectives and updated insights into the planning and optimization of TTFields therapy for glioblastoma by reviewing how the dose and thermal effects of TTFields are affected by factors such as tumor location and morphology, peritumoral edema, electrode array position, treatment duration (compliance), array "edge effect," electrical duty cycle, and skull-remodeling surgery. Finally, perspectives are provided on how to optimize the efficacy of future TTFields therapy.