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PURPOSE A new type of electronic dosimeter is presented, capable of discerning between the doses of gamma photons and neutrons in a mixed beam as found in Boron Neutron Capture Therapy (BNCT). We introduce a real-time dosimeter based on a thick gate Field Oxide Field Effect Transistor (FOXFET) covered with a neutron converter layer containing gadolinium. METHODS To sensitize the FOXFET dosimeter to neutron fluxes, a converter layer containing gadolinium oxide particles embedded in photoresines was deposited over the sensor surface. Mixed neutron-gamma field configurations with different neutron energy spectra were used to assess the FOXFET response, considering different thicknesses of the neutron converter layer. RESULTS The total gamma sensitivity of the devices resulted to be 43 mV/Gy. The responses of sensors with different converter layer thicknesses irradiated with different neutron spectra are simulated using GEANT4 code. The response to photons is not significantly modified with thin conversion layers when used in water medium. CONCLUSIONS A real-time dosimeter comprising a pair of FOXFET sensors-only one of them with a gadolinium neutron converter layer -allows the simultaneous measurement of gamma dose and neutron flux during BNCT irradiations. This article is protected by copyright. All rights reserved.

Medical physics 49(1), 714 - 726 (2022). doi:10.1002/mp.15343, Published by AAPM, College Park, Md.

Multi-parametric magnetic resonance imaging (mpMRI) has been playing an increasingly important role in the detection of prostate cancer (PCa). Various computer-aided detection algorithms were proposed for automated PCa detection by combining information in multiple mpMRI parameters. However, there are specific features of mpMRI, including between-voxel correlation within each prostate and heterogeneity across patients, that have not been fully explored but could potentially improve PCa detection if leveraged appropriately. This article proposes novel Bayesian approaches for voxel-wise PCa classification that accounts for spatial correlation and between-patient heterogeneity in the mpMRI data. Modeling the spatial correlation is challenging due to the extreme high dimensionality of the data, and we propose three scalable approaches based on Nearest Neighbor Gaussian Process (NNGP), reduced-rank approximation, and a conditional autoregressive (CAR) model that approximates a Gaussian Process with the Matern covariance, respectively. Our simulation study shows that properly modeling the spatial correlation and between-patient heterogeneity can substantially improve PCa classification. Application to in vivo data illustrates that classification is improved by all three spatial modeling approaches considered, while modeling the between-patient heterogeneity does not further improve our classifiers. Among the proposed models, the NNGP-based model is recommended given its high classification accuracy and computational efficiency.

Purpose In proton therapy, the potential of using high-dose rates in the cancer treatment is being explored. High-dose rates could improve efficiency and throughput in standard clinical practice, allow efficient utilization of motion mitigation techniques for moving targets, and potentially enhance normal tissue sparing due to the so-called FLASH effect. However, high-dose rates are difficult to reach when lower energy beams are applied in cyclotron-based proton therapy facilities, because they result in large beam sizes and divergences downstream of the degrader, incurring large losses from the cyclotron to the patient position (isocenter). In current facilities, the emittance after the degrader is reduced using circular collimators; however, this does not provide an optimal matching to the acceptance of the following beamline, causing a low transmission for these energies. We, therefore, propose to use a collimation system, asymmetric in both beam size and divergence, resulting in symmetric emittance in both beam transverse planes as required for a gantry system. This new emittance selection, together with a new optics design for the following beamline and gantry, allows a better matching to the beamline acceptance and an improvement of the transmission. Methods We implemented a custom method to design the collimator sizes and shape required to select high emittance, to be transported by the following beamline using new beam optics (designed with TRANSPORT) to maximize acceptance matching. For predicting the transmission in the new configuration (new collimators + optics), we used Monte Carlo simulations implemented in BDSIM, implementing a model of PSI Gantry 2 which we benchmarked against measurements taken in the current clinical scenario (circular collimators + clinical optics). Results From the BDSIM simulations, we found that the new collimator system and matching beam optics results in an overall transmission from the cyclotron to the isocenter for a 70 MeV beam of 0.72%. This is an improvement of almost a factor of 6 over the current clinical performance (0.13% transmission). The new optics satisfies clinical beam requirements at the isocenter. Conclusions We developed a new emittance collimation system for PSI's PROSCAN beamline which, by carefully selecting beam size and divergence asymmetrically, increases the beam transmission for low-energy beams in current state-of-the-art cyclotron-based proton therapy gantries. With these improvements, we could predict almost 1% transmission for low-energy beams at PSI's Gantry 2. Such a system could easily be implemented in facilities interested in increasing dose rates for efficient motion mitigation and FLASH experiments alike., Medical Physics, 48 (12), ISSN:0094-2405, ISSN:2473-4209, ISSN:1522-8541

On‐treatment EPID images are contaminated with patient‐generated scattered photons. If this component can be accurately estimated, its effect can be removed, and therefore a corresponding in vivo patient dose estimate will be more accurate. Our group previously developed a "tri‐hybrid" (TH) algorithm to provide fast but accurate estimates of patient‐generated photon scatter. The algorithm uses an analytical method to solve for singly‐scattered photon fluence, a modified Monte Carlo hybrid method to solve for multiply‐scattered photon fluence, and a pencil beam scatter kernel method to solve for electron interaction generated scattered photon fluence. However, for efficient clinical implementation, spatial and energy sampling must be optimized for speed while maintaining overall accuracy. In this work, the most significant sampling issues were examined, including spatial sampling settings for the patient voxel size, the number of Monte Carlo histories used in the modified hybrid MC method, scatter order sampling for the hybrid method, and also a range of energy spectrum sampling (i.e., energy bin sizes). The total predicted patient‐scattered photon fluence entering the EPID was compared with full MC simulation (EGSnrc) for validation. Three phantoms were tested with 6 and 18 MV beam energies, field sizes of 4 × 4, 10 × 10, and 20 × 20 cm2, and source‐to‐imager distance of 140 cm to develop a set of optimal sampling settings. With the recommended sampling, accuracy and precision of the total‐scattered energy fluence of the TH patient scatter prediction method are within 0.9% and 1.2%, respectively, for all test cases compared with full MC simulation results. For the mean energy spectrum across the imaging plane, comparison of TH with full MC simulation showed 95% overlap. This study has optimized sampling settings so that they have minimal impact on patient scatter prediction accuracy while maintaining maximum execution speed, a critical step for future clinical implementation.

© 2021 The Authors. Many biomedical applications require accurate non-rigid image registration that can cope with complex deformations. However, popular diffeomorphic Demons registration algorithms suffer from difficulties for complex and serious distortions since they only use image greyscale and gradient information. To address these difficulties, a new diffeomorphic Demons registration algorithm is proposed using hierarchical neighbourhood spectral features namely HNSF Log-Demons in this paper. In view of three important properties of hierarchical neighbourhood spectral features based on line graph such as rotation invariance, invariance of linear changes of brightness, and robustness to noise, the hierarchical neighbourhood spectral features of a reference image and a moving image is first extracted and these novel spectral features are incorporated into the energy function of the diffeomorphic registration framework to improve the capability of capturing complex distortions. Secondly, the Nystr ö o ̈ m approximation based on random singular value decomposition is employed to effectively enhance the computational efficiency of HNSF Log-Demons. Finally, the hybrid multi-resolution strategy based on wavelet decomposition in the registration process is utilised to further improve the registration accuracy and efficiency. Experimental results show that the proposed HNSF Log-Demons not only effectively ensures the generation of smooth and reversible deformation field, but also achieves better performance than state-of-the-art algorithms. National Natural Science Foundation of China. Grant Numbers: 61762058, 61861024, 61871259; Natural Science Foundation of Gansu Province of China. Grant Number: 20JR5RA404; Natural Science Basic Research Program of Shaanxi. Grant Number: 2021JC-47.

PURPOSE To demonstrate a novel 3D radial echo planar imaging (3D REPI) sequence for flexible, rapid, and motion-robust sampling in fMRI. METHODS The 3D REPI method expands on the recently described golden angle rotated EPI trajectory using radial batched internal navigator echoes (TURBINE) approach by exploiting the unused perpendicular direction in the EPI readout to form fast analogues of rotated stack of stars or spirals trajectories that cover all 3 dimensions of k-space. An iterative conjugate gradient algorithm with SENSE reconstruction and time-segmented non-uniform fast Fourier transform (FFT) was used for parallel imaging acceleration and to account for the effects of B0 inhomogeneity. The golden angle rotation allowed for sliding window reconstruction schemes to be applied in brain BOLD fMRI experiments. RESULTS Combined whole brain visual and motor fMRI experiments were successfully carried out on a clinical 3T scanner at 2 mm isotropic and 1 × 1 × 2 mm3 resolutions using the 3D REPI design. Improved sampling characteristics and image quality were observed for twisted trajectories at the expense of prolonged readout times and off-resonance effects. The ability to correct for rigid motion correction was also demonstrated. CONCLUSIONS 3D REPI presents a flexible approach for segmented volumetric fMRI with motion correction and high in-plane spatial resolutions. Improved BOLD fMRI brain activation maps were obtained using a sliding window reconstruction.

PURPOSE The aim of this work is the reconciliation of high spatial and temporal resolution for MRI. For this purpose, a novel sampling strategy for 3D encoding is proposed, which provides flexible k-space segmentation along with uniform sampling density and benign filtering effects related to signal decay. METHODS For time-critical MRI applications such as functional MRI (fMRI), 3D k-space is usually sampled by stacking together 2D trajectories such as echo planar imaging (EPI) or spiral readouts, where each shot covers one k-space plane. For very high temporal and medium to low spatial resolution, tilted hexagonal sampling (T-Hex) was recently proposed, which allows the acquisition of a larger k-space volume per excitation than can be covered with a planar readout. Here, T-Hex is described in a modified version where it instead acquires a smaller k-space volume per shot for use with medium temporal and high spatial resolution. RESULTS Mono-planar T-Hex sampling provides flexibility in the choice of speed, signal-to-noise ratio (SNR), and contrast for rapid MRI acquisitions. For use with a conventional gradient system, it offers the greatest benefit in a regime of high in-plane resolution

Purpose MR-guided radiotherapy has different requirements for the images than diagnostic radiology, thus requiring development of novel imaging sequences. MRI simulation is an excellent tool for optimizing these new sequences; however, currently available software does not provide all the necessary features. In this paper, we present a digital framework for testing MRI sequences that incorporates anatomical structure, respiratory motion, and realistic presentation of MR physics. Methods The extended Cardiac-Torso (XCAT) software was used to create T1 , T2 , and proton density maps that formed the anatomical structure of the phantom. Respiratory motion model was based on the XCAT deformation vector fields, modified to create a motion model driven by a respiration signal. MRI simulation was carried out with JEMRIS, an open source Bloch simulator. We developed an extension for JEMRIS, which calculates the motion of each spin independently, allowing for deformable motion. Results The performance of the framework was demonstrated through simulating the acquisition of a two-dimensional (2D) cine and demonstrating expected motion ghosts from T2 weighted spin echo acquisitions with different respiratory patterns. All simulations were consistent with behavior previously described in literature. Simulations with deformable motion were not more time consuming than with rigid motion. Conclusions We present a deformable four-dimensional (4D) digital phantom framework for MR sequence development. The framework incorporates anatomical structure, realistic breathing patterns, deformable motion, and Bloch simulation to achieve accurate simulation of MRI. This method is particularly relevant for testing novel imaging sequences for the purpose of MR-guided radiotherapy in lungs and abdomen.

In this article, a novel multiscale modeling method is proposed for transient computational fluid dynamics (CFD) simulations of the human airways. The developed method is the first attempt to incorporate spatial coupling and temporal coupling into transient human airway simulations, aiming to improve the flexibility and the efficiency of these simulations. In this method, domain decomposition was used to separate the complex airway model into different scaled domains. Each scaled domain could adopt a suitable mesh and timestep, as necessary: the coarse mesh and large timestep were employed in the macro regions to reduce the computational cost, while the fine mesh and small timestep were used in micro regions to maintain the simulation accuracy. The radial point interpolation method was used to couple data between the coarse mesh and the fine mesh. The continuous micro solution–intermittent temporal coupling method was applied to bridge different timesteps. The developed method was benchmarked using a well-studied four-generation symmetric airway model under realistic normal breath conditions. The accuracy and efficiency of the method were verified separately in the inhalation phase and the exhalation phase. Similar airflow behavior to previous studies was observed from the multiscale airway model. The developed multiscale method has the potential to improve the flexibility and efficiency of transient human airway simulations without sacrificing accuracy.

Physiological pulsations have been shown to affect the global blood oxygen level dependent (BOLD) signal in human brain. While these pulsations have previously been regarded as noise, recent studies show their potential as biomarkers of brain pathology. We used the extended 5 Hz spectral range of magnetic resonance encephalography (MREG) data to investigate spatial and frequency distributions of physiological BOLD signal sources. Amplitude spectra of the global image signals revealed cardiorespiratory envelope modulation (CREM) peaks, in addition to the previously known very low frequency (VLF) and cardiorespiratory pulsations. We then proceeded to extend the amplitude of low frequency fluctuations (ALFF) method to each of these pulsations. The respiratory pulsations were spatially dominating over most brain structures. The VLF pulsations overcame the respiratory pulsations in frontal and parietal gray matter, whereas cardiac and CREM pulsations had this effect in central cerebrospinal fluid (CSF) spaces and major blood vessels. A quasi‐periodic pattern (QPP) analysis showed that the CREM pulsations propagated as waves, with a spatiotemporal pattern differing from that of respiratory pulsations, indicating them to be distinct intracranial physiological phenomenon. In conclusion, the respiration has a dominant effect on the global BOLD signal and directly modulates cardiovascular brain pulsations., Extensive 5 Hz spectral resolution of fast fMRI revealed a new form of physiological brain contrast illustrating respiratory‐induced modulation of cardiovascular brain pulsations. Very low frequency (VLF), respiratory and cardiovascular pulses, their harmonics and the detected modulations were found to form the global BOLD signal. Propagating respiratory pulsations should be removed cautiously with voxel‐wise Fourier filtering as they compete globally with every other BOLD signal source. ​

PURPOSE Three 64-channel cardiac coils with different detector array configurations were designed and constructed to evaluate acceleration capabilities in simultaneous multislice (SMS) imaging for 3T cardiac MRI. METHODS Three 64-channel coil array configurations obtained from a simulation-guided design approach were constructed and systematically evaluated regarding their encoding capabilities for accelerated SMS cardiac acquisitions at 3T. Array configuration AUni-sized consists of uniformly distributed equally sized loops in an overlapped arrangement, BGapped uses a gapped array design with symmetrically distributed equally sized loops, and CDense has non-uniform loop density and size, where smaller elements were centered over the heart and larger elements were placed surrounding the target region. To isolate the anatomic variation from differences in the coil configurations, all three array coils were built with identical semi-adjustable housing segments. The arrays' performance was compared using bench-level measurements and imaging performance tests, including signal-to-noise ratio (SNR) maps, array element noise correlation, and SMS acceleration capabilities. Additionally, all cardiac array coils were evaluated on a healthy volunteer. RESULTS The array configuration CDense with the non-uniformly distributed loop density showed the best overall cardiac imaging performance in both SNR and SMS encoding power, when compared to the other constructed arrays. The diffusion weighted cardiac acquisitions on a healthy volunteer support the favorable accelerated SNR performance of this array configuration. CONCLUSION Our results indicate that optimized highly parallel cardiac arrays, such as the 64-channel coil with a non-uniform loop size and density improve highly accelerated SMS cardiac MRI in comparison to symmetrically distributed loop array designs.

We have developed physical and biological beam modeling for carbon scanning therapy at the Osaka Heavy Ion Therapy Center (Osaka HIMAK). Carbon beam scanning irradiation is based on continuous carbon beam scanning, which adopts hybrid energy changes using both accelerator energy changes and binary range shifters in the nozzles. The physical dose calculation is based on a triple Gaussian pencil‐beam algorithm, and we thus developed a beam modeling method using dose measurements and Monte Carlo simulation for the triple Gaussian. We exploited a biological model based on a conventional linear‐quadratic (LQ) model and the photon equivalent dose, without considering the dose dependency of the relative biological effectiveness (RBE), to fully comply with the carbon passive dose distribution using a ridge filter. We extended a passive ridge‐filter design method, in which carbon and helium LQ parameters are applied to carbon and fragment isotopes, respectively, to carbon scanning treatment. We then obtained radiation quality data, such as the linear energy transfer (LET) and LQ parameters, by Monte Carlo simulation. The physical dose was verified to agree with measurements to within ±2% for various patterns of volume irradiation. Furthermore, the RBE in the middle of a spread‐out Bragg peak (SOBP) reproduced that from passive dose distribution results to within ±1.5%. The developed carbon beam modeling and dose calculation program was successfully applied in clinical use at Osaka HIMAK.

The Tm -TSTOP and the variable dose methods were applied to alumina experimentally, and then all the steps of the methods were simulated numerically. The Tm -TSTOP experiments were performed between 70 and 300°C, and results showed that the glow curve of the used alumina had six distinct peaks between 40 and 400°C. The glow curves were analyzed using computerized glow curve fitting programs, the analytical equations were also fitted to the experimental data, and the trapping parameters of the peaks were measured. The samples were irradiated above the saturation level to ensure the complete filling of the electron traps and, therefore, the concentrations of traps were measured experimentally. Short-term anomalous fading behaviours of the peaks were investigated, and a new equation was proposed to compute the anomalous fading rate. In addition, the variable dose and Tm -TSTOP methods were simulated using the six trap-one recombination centre (6T1C) model and the experimental trapping parameters. Results showed that there was good harmony between numerical and experimental glow curves. After all the simulations were performed with acceptable accuracy, an estimate was made for the trapping coefficients (Ai = 1-6 ) that could not be measured directly from thermoluminescence experiments. Results showed that the trapping coefficients were affected by the applied dose.

The umami intensity of single flavor enhancer was detected by an electronic tongue and human sensory. The linear fit was performed to unravel the concentration–response values correlations of eight flavor enhancers. The electronic tongue response data were then analyzed using principal component analysis (PCA) and discriminant factor analysis (DFA) method. It was found that the umami response value of the electronic tongue and the flavor enhancer concentration showed a semi‐logarithmic function. Moreover, the PCA and DFA could successfully distinguish the variety and concentration of flavor enhancer. The umami intensities were also assessed by human sensory and showed consistency with those of electronic tongue tests. This implies the electronic tongue has a great potential as an alternative for biological tongue on sensing intensity of flavor enhancer., The umami response intensity of the electronic tongue was positively correlated with the concentration of all the umami substances and showed on a semi‐logarithmic function. The eight different flavor enhancers were successfully discriminated by PCA and DFA methods

Purpose To develop and evaluate a novel method for reconstruction of high-quality sodium MR images from noisy, limited k-space data. Theory and methods A novel reconstruction method was developed for reconstruction of high-quality sodium images from noisy, limited k-space data. This method is based on a novel image model that contains a motion-compensated generalized series model and a sparse model. The motion-compensated generalized series model enables effective use of anatomical information from a proton image for denoising and resolution enhancement of sodium data, whereas the sparse model enables high-resolution reconstruction of sodium-dependent novel features. The underlying model estimation problems were solved efficiently using convex optimization algorithms. Results The proposed method has been evaluated using both simulation and experimental data obtained from phantoms, healthy human volunteers, and tumor patients. Results showed a substantial improvement in spatial resolution and SNR over state-of-the-art reconstruction methods, including compressed sensing and anatomically constrained reconstruction methods. Quantitative tissue sodium concentration maps were obtained from both healthy volunteers and brain tumor patients. These tissue sodium concentration maps showed improved lesion fidelity and allowed accurate interrogation of small targets. Conclusion A new method has been developed to obtain high-resolution sodium images with good SNR at 3 T. The proposed method makes effective use of anatomical prior information for denoising, while using a sparse model synergistically to recover sodium-dependent novel features. Experimental results have been obtained to demonstrate the feasibility of achieving high-quality tissue sodium concentration maps and their potential for improved detection of spatially heterogeneous responses of tumor to treatment.

Purpose: To develop a general framework for Parallel Imaging (PI) with the use of Maxwell regularization for the estimation of the sensitivity maps (SMs) and constrained optimization for the parameter-free image reconstruction. Theory and Methods: Certain characteristics of both the SMs and the images are routinely used to regularize the otherwise ill-posed optimization-based joint reconstruction from highly accelerated PI data. In this paper we rely on a fundamental property of SMs--they are solutions of Maxwell equations-- we construct the subspace of all possible SM distributions supported in a given field-of-view, and we promote solutions of SMs that belong in this subspace. In addition, we propose a constrained optimization scheme for the image reconstruction, as a second step, once an accurate estimation of the SMs is available. The resulting method, dubbed Maxwell Parallel Imaging (MPI), works seamlessly for arbitrary sequences (both 2D and 3D) with any trajectory and minimal calibration signals. Results: The effectiveness of MPI is illustrated for a wide range of datasets with various undersampling schemes, including radial, variable-density Poisson-disc, and Cartesian, and is compared against the state-of-the-art PI methods. Finally, we include some numerical experiments that demonstrate the memory footprint reduction of the constructed Maxwell basis with the help of tensor decomposition, thus allowing the use of MPI for full 3D image reconstructions. Conclusions: The MPI framework provides a physics-inspired optimization method for the accurate and efficient image reconstruction from arbitrary accelerated scans.

PURPOSE: To investigate the feasibility of using the high Z(eff) storage phosphor material BaFBrI:Eu(2+) in conjunction with the low Z(eff) storage phosphor material KCl:Eu(2+) for simultaneous proton dose and linear energy transfer (LET) measurements by 1) measuring the fundamental optical and dosimetric properties of BaFBrI:Eu(2+), 2) evaluating its compatibility in being readout simultaneously with KCl:Eu(2+) dosimeters and 3) modeling and validating its LET dependence under elevated proton LET irradiation. METHODS: A commercial BaFBrI:Eu(2+) storage phosphor detector (Model ST-VI, Fujifilm) was characterized with energy dispersive x-ray analysis (EDS) to obtain its elemental composition. The dosimeters were irradiated using both a Mevion S250 proton therapy unit (at the center of a spread-out Bragg peak, SOBP) and a Varian Clinac iX linear accelerator with the latter being a low LET irradiation. The photostimulated luminescence (PSL) emission spectra, excitation spectra and luminescent lifetimes of the detector were measured post proton and photon irradiations. Dosimetric properties including dose linearity, dose rate dependence, radiation hardness, temporal and readout stabilities were studied using a laboratory optical reader after proton irradiations. In addition, its proton energy dependence was analytically modeled and experimentally validated by irradiating the detectors at various depths within the SOBP (Range: 15.0 g/cm(2), Modulation: 10.0 g/cm(2)). RESULTS: The active detector composition for the high Z(eff) storage phosphor detector was found to be BaFBr(0.85)I(0.15):Eu(2+). The BaFBr(0.85)I(0.15):Eu(2+) material’s excitation and emission spectra were in agreement under proton and photon irradiations, with peaks of 586 ± 1 nm and 400 ± 1 nm respectively with a full-width-at-half-maximum (FWHM) of 119 ± 3 nm and 30 ± 2 nm respectively. As dosimeter response under photon irradiation is generally believed to be free from LET effect, these results suggest LET independence of charge storage center types resulted from ionizing radiations. There is sufficient spectral overlaps with KCl:Eu(2+) dosimeters allowing both dosimeters to be readout under equivalent readout conditions, i.e. 594 nm stimulation and 420 nm detection wavelengths. Its PSL characteristic lifetime was found to be less than 5 microseconds which would make it suitable for fast 2D readout post irradiation. Its 420 nm emission band intensity was found to be linear up to 10 Gy absolute proton dose under the same irradiation conditions, dose rate independent, stable in time and under multiple readouts, and with high radiation hardness under cumulative proton dose histories up to 200 Gy as tested in this study. BaFBr(0.85)I(0.15):Eu(2+) showed significant proton energy- dependent dose under-response in regions of high LET which could be modeled by stopping power ratio calculations with an accuracy of 3% in low LET regions and a distance-to-agreement (DTA) of 1 mm in high LET regions (>5 keV/μm). CONCLUSION: We have proven the feasibility of dual-storage phosphor proton dosimetry for simultaneous proton dose and LET measurements. BaFBr(0.85)I(0.15):Eu(2+) has shown equally excellent dosimetry performance as its low Z(eff) complement KCl:Eu(2+) with distinctive LET dependence merely as a result of its higher Z(eff). These promising results pave the way for future studies involving simultaneous proton dose and LET measurements using this novel approach.

PURPOSE Both safety and accuracy are of vital importance for surgical operation procedures. An efficient way to avoid the singularity of the surgical robot concerning safety issues is to maximize its manipulability in robot-assisted surgery. The goal of this work was to validate a dynamic neural network optimization method for manipulability optimization control of a 7-degree of freedom (DoF) robot in a surgical operation. METHODS Three different paths, a circle, a sinusoid and a spiral were chosen to simulate typical surgical tasks. The dynamic neural network-based manipulability optimization control was implemented on a 7-DoF robot manipulator. During the surgical operation procedures, the manipulability of the robot manipulator and the accuracy of the surgical operation are recorded for performance validation. RESULTS By comparison, the dynamic neural network-based manipulability optimization control achieved optimized manipulability but with a loss of the accuracy of trajectory tracking (the global error was 1 mm compare to the 0.5 mm error of non-optimized method). CONCLUSIONS The method validated in this work achieved optimized manipulability with a loss of error. Future works should be introduced to improve the accuracy of the surgical operation.

Imaging of gases is a major challenge for any modality including MRI. NMR and MRI signals are directly proportional to the nuclear spin density and the degree of alignment of nuclear spins with applied static magnetic field, which is called nuclear spin polarization. The level of nuclear spin polarization is typically very low, i.e., one hundred thousandth of the potential maximum at 1.5 T and a physiologically relevant temperature. As a result, MRI typically focusses on imaging highly concentrated tissue water. Hyperpolarization methods transiently increases nuclear spin polarizations up to unity, yielding corresponding gains in MRI signal level of several orders of magnitude that enable the 3D imaging of dilute biomolecules including gases. Parahydrogen-induced polarization is a fast, highly scalable, and low-cost hyperpolarization technique. The focus of this Minireview is to highlight selected advances in the field of parahydrogen-induced polarization for the production of hyperpolarized compounds, which can be potentially employed as inhalable contrast agents.

Purpose To develop a reliable, consistent, and reproducible reference phantom for error quantification of phase-contrast MRI so it can be used for validation and quality control. Methods An air-driven rotation phantom consisting of a steadily rotating cylinder surrounded by a static ring both filled with agarose gel was developed. Rotational speed was measured and controlled in real time using an optical counter and a closed-loop controller. Consistency of the phantom was assessed by recording variations in rotational speed. The phantom was imaged with 2D phase-contrast MRI, and the velocity at each point was compared with analytically predicted velocity. Additionally, to examine reproducibility, the phantom was run with the same rotational speed on 2 different days and imaged using the same phase-contrast MRI protocol. Results The rotation phantom provided consistent rotational speed with 2 revolutions per minute SD from the set value for 20 min. Comparison between predicted and measured velocities demonstrated excellent agreement (intraclass correlation coefficient of 0.99). The RMS error in velocity components were less than 1% of maximum value. The scan-rescan experiment showed that the phantom can reproduce the same velocity distributions (intraclass correlation coefficient of 0.99) using the same rotational speed and MRI settings. Conclusion The developed rotation phantom provided well-defined and reproducible linear velocity distributions, which can be used for systematic and quantitative error analysis of phase-contrast MRI for a range of known velocities.

PURPOSE This work introduces a new lattice geometry library, egs_lattice, into the EGSnrc Monte Carlo code, which can be used for both modeling very large (previously unfeasible) quantities of geometries (e.g., cells or gold nanoparticles (GNPs)) and establishing recursive boundary conditions. The reliability of egs_lattice, as well as EGSnrc in general, is cross-validated and tested at short length scales and low energies. METHODS New Bravais, cubic, and hexagonal lattice geometries are defined in egs_lattice and their transport algorithms are described. Simulations of cells and GNP-containing cavities are implemented to compare to independent, published Geant4-DNA and PENELOPE results. Recursive boundary conditions, implemented through a cubic lattice, are used to perform electron Fano cavity tests. The Fano test is performed on three different-sized cells containing GNPs in the region around the nucleus for three source energies. RESULTS Lattices are successfully implemented in EGSnrc, and are used for validation. EGSnrc calculated the dose to cell cytoplasm and nucleus when irradiated by an internal electron source with a median difference of 0.6% compared to published Geant4-DNA results. EGSnrc calculated the ratio of dose to a microscopic cavity containing GNPs over dose to a cavity containing a homogeneous mixture of gold, and results generally agree (within 1%) with published PENELOPE results. The electron Fano cavity test is passed for all energies and cells considered, with sub-0.1% discrepancies between EGSnrc-calculated and expected values. Additionally, the recursive boundary conditions used for the Fano test provided a factor of over a million increase in efficiency in some cases. CONCLUSIONS The egs_lattice geometry library, currently available as a pull request on the EGSnrc GitHub "develop" branch, is now freely accessible as open-source code. Lattice geometry implementations cross-validated with independent simulations in other MC codes and verified with the electron Fano cavity test demonstrate not only the reliability of egs_lattice, but also, by extension, EGSnrc's ability to simulate transport in nanometer geometries and score in microscopic cavities.

PURPOSE The recently introduced robotic x-ray systems provide the flexibility to acquire cone-beam computed tomography (CBCT) data using customized, application-specific source-detector trajectories. We exploit this capability to mitigate the effects of x-ray scatter and noise in CBCT imaging of weight-bearing foot and cervical spine (C-spine) using scan orbits with a tilted rotation axis. METHODS We used an advanced CBCT simulator implementing accurate models of x-ray scatter, primary attenuation, and noise to investigate the effects of the orbital tilt angle in upright foot and C-spine imaging. The system model was parameterized using a laboratory version of a three-dimensional (3D) robotic x-ray system (Multitom RAX, Siemens Healthineers). We considered a generalized tilted axis scan configuration, where the detector remained parallel to patient's long body axis during the acquisition, but the elevation of source and detector was changing. A modified Feldkamp-Davis-Kress (FDK) algorithm was developed for reconstruction in this configuration, which departs from the FDK assumption of a detector that is perpendicular to the scan plane. The simulated foot scans involved source-detector distance (SDD) of 1386 mm, orbital tilt angles ranging 10° to 40°, and 400 views at 1 mAs/view and 0.5° increment; the C-spine scans involved -25° to -45° tilt angles, SDD of 1090 mm, and 202 views at 1.3 mAs and 1° increment The imaging performance was assessed by projection-domain measurements of the scatter-to-primary ratio (SPR) and by reconstruction-domain measurements of contrast, noise and generalized contrast-to-noise ratio (gCNR, accounting for both image noise and background nonuniformity) of the metatarsals (foot imaging) and cervical vertebrae (spine imaging). The effects of scatter correction were also compared for horizontal and tilted scans using an ideal Monte Carlo (MC)-based scatter correction and a frame-by-frame mean scatter correction. RESULTS The proposed modified FDK, involving projection resampling, mitigated streak artifacts caused by the misalignment between the filtering direction and the detector rows. For foot imaging (no grids), an optimized 20° tilted orbit reduced the maximum SPR from ~1.5 in a horizontal scan to

Pharyngeal bolus flow was simulated numerically using a finite element method. The bolus liquids were X-ray medium, glucose, and thickener solutions. For a low-viscosity bolus, the simulation showed a reasonable agreement of bolus velocity with X-ray measurements. The influence of bolus density on swallowing velocity was investigated numerically. Although a higher density resulted in a higher bolus velocity, the increase in velocity was modest. When the bolus viscosity was high, it was necessary to apply the slip boundary condition to obtain an agreement for bolus velocity between the simulation and X-ray measurements. The simulations also showed that the method of characteristic shear rate proposed by Zhu et al., Journal of Texture Studies, 2014, 45, 430-439 is effective for predicting the bolus velocity for shear-thinning fluids. In order to discuss the effect of saliva lubrication and the physical meaning of the characteristic shear rate, an immiscible two-layer flow of the core and wall layer was analyzed theoretically by analogy with mesopharyngeal bolus flow. The characteristic shear rate enabled us to correlate the macroscopic flow behavior and the viscosity of the core layer fluid. Lubrication due to the wall layer caused the apparent slip and enhanced the transfer of viscous core fluid. For viscous fluid that presented a large apparent slip in the two-layer model, the slip boundary condition was needed in the swallowing simulation. The numerical simulation and model flow analysis revealed the usefulness of characteristic shear rate and the importance of saliva-layer lubrication in swallowing.

Background and purpose Geometric distortions resulting from large pose changes reduce the accuracy of motion measurements and interfere with the ability to generate artifact-free information. Our goal is to develop an algorithm and pulse sequence to enable motion-compensated, geometric distortion compensated diffusion-weighted MRI, and to evaluate its efficacy in correcting for the field inhomogeneity and position changes, induced by large and frequent head motions. Methods Dual echo planar imaging (EPI) with a blip-reversed phase encoding distortion correction technique was evaluated in five volunteers in two separate experiments and compared with static field map distortion correction. In the first experiment, dual-echo EPI images were acquired in two head positions designed to induce a large field inhomogeneity change. A field map and a distortion-free structural image were acquired at each position to assess the ability of dual-echo EPI to generate reliable field maps and enable geometric distortion correction in both positions. In the second experiment, volunteers were asked to move to multiple random positions during a diffusion scan. Images were reconstructed using the dual-echo correction and a slice-to-volume registration (SVR) registration algorithm. The accuracy of SVR motion estimates was compared to externally measured ground truth motion parameters. Results Our results show that dual-echo EPI can produce slice-level field maps with comparable quality to field maps generated by the reference gold standard method. We also show that slice-level distortion correction improves the accuracy of SVR algorithms as slices acquired at different orientations have different levels of distortion, which can create errors in the registration process. Conclusions Dual-echo acquisitions with blip-reversed phase encoding can be used to generate slice-level distortion-free images, which is critical for motion-robust slice to volume registration. The distortion corrected images not only result in better motion estimates, but they also enable a more accurate final diffusion image reconstruction.

Self‐made milk knots in Xinjiang Kazakh ethnic group were used as material to establish the quality assessment system of flavor quality. The fuzzy analytic hierarchy process based on the optimal consistency matrix was used to evaluate the quality of the samples qualitatively and quantitatively. Its result is consistent with the cluster analysis of the SOM neural network. The results showed that the milk knot samples of Altay had differences with the milk knot samples of Yili. The comprehensive evaluation system is feasible and can evaluate the quality of milk knot samples by flavor characteristics. This can provide a reference for further research on the origin of differences between two types of milk knot samples., Self‐made milk knots in Xinjiang Kazakh ethnic group were used as material to establish the quality assessment system of flavor quality. The fuzzy analytic hierarchy process based on the optimal consistency matrix was used to evaluate the quality of the samples qualitatively and quantitatively. Its result is consistent with the cluster analysis of the SOM neural network.

The concept of broad sense agreement (BSA) has recently been proposed for studying the relationship between a continuous measurement and an ordinal measurement (Peng et al. [1]). They developed a non-parametric procedure for estimating the BSA index, which is only applicable to completely observed data. In this work, we consider the problem of evaluating BSA index when the continuous measurement is subject to censoring. We propose a nonparametric estimation method built upon a derivation of a new functional representation of the BSA index, which allows for accommodating censoring by plugging in the nonparametric survival function estimators. We establish the consistency and asymptotic normality for the proposed BSA estimator. We also investigate an alternative approach based on the strategy of multiple imputation, which is shown to have better empirical performance with small sample sizes than the plug-in method. Extensive simulation studies are conducted to evaluate our proposals. We illustrate our methods via an application to a Surgical Intensive Care Unit study.

To recover the neural activity from Magnetoencephalography (MEG) and Electroencephalography (EEG) measurements, we need to solve the inverse problem by utilizing the relation between dipole sources and the data generated by dipolar sources. In this study, we propose a new approach based on the implementation of a particle filter (PF) that uses minimum sampling variance resampling methodology to track the neural dipole sources of cerebral activity. We use this approach for the EEG data and demonstrate that it can naturally estimate the sources more precisely than the traditional systematic resampling scheme in PFs.

Purpose It has been shown, theoretically and in vivo, that using the Stejskal‐Tanner pulsed‐gradient, or linear tensor encoding (LTE), and in tissue exhibiting a “stick‐like” diffusion geometry, the direction‐averaged diffusion‐weighted MRI signal at high b‐values ( urn:x-wiley:07403194:media:mrm28191:mrm28191-math-0001) follows a power‐law, decaying as urn:x-wiley:07403194:media:mrm28191:mrm28191-math-0002. It has also been shown, theoretically, that for planar tensor encoding (PTE), the direction‐averaged diffusion‐weighted MRI signal decays as 1/b. We aimed to confirm this theoretical prediction in vivo. We then considered the direction‐averaged signal for arbitrary b‐tensor shapes and different tissue substrates to look for other conditions under which a power‐law exists. Methods We considered the signal decay for high b‐values for encoding geometries ranging from 2‐dimensional PTE, through isotropic or spherical tensor encoding to LTE. When a power‐law behavior was suggested, this was tested using in silico simulations and, when appropriate, in vivo using ultra‐strong (300 mT/m) gradients. Results Our in vivo results confirmed the predicted 1/b power law for PTE. Moreover, our analysis showed that using an axisymmetric b‐tensor a power‐law only exists under very specific conditions: (a) “stick‐like” tissue geometry and purely LTE or purely PTE waveforms; and (b) "pancake‐like" tissue geometry and a purely LTE waveform. Conclusions A complete analysis of the power‐law dependencies of the diffusion‐weighted signal at high b‐values has been performed. Only three specific forms of encoding result in a power‐law dependency, pure linear and pure PTE when the tissue geometry is “stick‐like” and pure LTE when the tissue geometry is "pancake‐like". The different exponents of these encodings could be used to provide independent validation of the presence of different tissue geometries in vivo.

The circular‐edge technique using a low‐contrast cylindrical object is commonly used to measure the modulation transfer functions (MTFs) in computed tomography (CT) images reconstructed with iterative reconstruction (IR) algorithms. This method generally entails averaging multiple images of the cylinder to reduce the image noise. We suspected that the cylinder edge shape depicted in the IR images might exhibit slight deformation with respect to the true shape because of the intrinsic nonlinearity of IR algorithms. Image averaging can reduce the image noise, but does not effectively improve the deformation of the edge shape; thereby causing errors in the MTF measurements. We address this issue and propose a method to correct the MTF. We scanned a phantom including cylindrical objects with a CT scanner (Ingenuity Elite, Philips Healthcare). We obtained cylinder images with iterative model reconstruction (IMR) algorithms. The images suggested that the depicted edge shape deforms and fluctuates depending on slice positions. Because of this deformation, image averaging can potentially cause additional blurring. We define the deformation function D that describes the additional blurring, and obtain D by analyzing multiple images. The MTF measured by the circular‐edge method (referred to as MTF') can be thought of as the multiplication of the true MTF by the Fourier transformation (FT) of D. We thus obtain the corrected MTF (MTFcorrected) by dividing MTF' by the FT of D. We validate our correction method by comparing the calculated images based on the convolution theorem using MTF' and MTFcorrected with the actual images obtained with the scanner. The calculated image using MTFcorrected is more similar to the actual image compared with the image calculated using MTF', particularly in edge regions. We describe a pitfall in MTF measurement using the circular‐edge technique with image averaging, and suggest a method to correct it.

PURPOSE To investigate for the first time the potentialities of obtaining microdosimetric measurements in scanned clinical carbon-ion beams using synthetic single crystal diamond detector and to verify the spectral conversion methods. METHODS Microdosimetric measurements were performed at different depths in a water phantom at the therapeutic scanned carbon-ion beam of the National Center of Oncological Hadrontherapy (CNAO) in Pavia, using waterproof encapsulated diamond microdosimeter developed at "Tor Vergata" University. A monoenergetic carbon-ion beam of 195 MeV/μ scanned over a square field of 2 × 2 cm2 was used. Experimental microdosimetric spectra were compared with those obtained with a propane-filled Tissue Equivalent Proportional Counters (TEPCs) microdosimeter in the same facility at the same conditions. To this purpose, the spectra in diamond were converted to the spectra that would have been collected with a propane-filled cylindrical sensitive volume by means of a novel analytic methodology, recently developed at MedAustron. RESULTS The microdosimetric spectra acquired by the diamond microdosimeter show different shapes in the 10 keV µm-1 ÷ 103 keV µm-1 lineal-energy range at different water depths. In spite of the high counting rate, no spectral distortion, due to pile-up events and polarization effects, were observed. The experimental spectra have a low detection threshold of about 6 keV µm-1 due to the electronic noise in the irradiation room. The comparison between the spectra converted to propane from diamond detector and the spectra collected directly with propane-filled TEPC shows a good agreement in the whole lineal-energy range. Furthermore this comparison confirms that diamond detector response is LET independent. The frequency- and dose-mean lineal energy values were also assessed for all spectra. The frequency-mean values obtained with diamond microdosimeter at different depths scales rather well with the absorbed dose values. CONCLUSIONS Microdosimetric characterization of a synthetic single crystal diamond detector in high-energy scanned carbon-ion beams was performed. The results of the present study showed that this detector is suitable for microdosimetry of clinical carbon ion beams. In addition, the good agreement between the converted diamond spectra and those obtained with TEPC provides the first experimental validation of the spectra conversion methodologies as valuable tools for the comparison of spectra collected with different detectors.

Purpose: Arterial Spin Labeling (ASL) is a quantitative, non-invasive alternative to perfusion imaging with contrast agents. Fixing values of certain model parameters in traditional ASL, which actually vary from region to region, may introduce bias in perfusion estimates. Adopting Magnetic Resonance Fingerprinting (MRF) for ASL is an alternative where these parameters are estimated alongside perfusion, but multiparametric estimation can degrade precision. We aim to improve the sensitivity of ASL-MRF signals to underlying parameters to counter this problem, and provide precise estimates. We also propose a regression based estimation framework for MRF-ASL. Methods: To improve the sensitivity of MRF-ASL signals to underlying parameters, we optimize ASL labeling durations using the Cramer-Rao Lower Bound (CRLB). This paper also proposes a neural network regression based estimation framework trained using noisy synthetic signals generated from our ASL signal model. Results: We test our methods in silico and in vivo, and compare with multiple post labeling delay (multi-PLD) ASL and unoptimized MRF-ASL. We present comparisons of estimated maps for six parameters accounted for in our signal model. Conclusions: The scan design process facilitates precise estimates of multiple hemodynamic parameters and tissue properties from a single scan, in regions of gray and white matter, as well as regions with anomalous perfusion activity in the brain. The regression based estimation approach provides perfusion estimates rapidly, and bypasses problems with quantization error. Keywords: Arterial Spin Labeling, Magnetic Resonance Fingerprinting, Optimization, Cramer-Rao Bound, Scan Design, Regression, Neural Networks, Deep Learning, Precision, Estimation, Brain Hemodynamics., Submitted to Magnetic Resonance in Medicine

Purpose To estimate relative biological effectiveness (RBE) ascribed to secondary fragments in a lateral distribution of carbon ion irradiation. The RBE was estimated with the microdosimetric kinetic (MK) model and measured linear energy transfer (LET) obtained with CR‐39 plastic detectors. Methods A water phantom was irradiated by a 12C pencil beam with energy of 380 MeV/u at the Gunma University Heavy Ion Medical Center (GHMC), and CR‐39 detectors were exposed to secondary fragments. Because CR‐39 was insensitive to low LET, we conducted Monte Carlo simulations with Geant4 to calculate low LET particles. The spectra of low LET particles were combined with experimental spectra to calculate RBE. To estimate accuracy of RBE, we calculated RBE by changing yield of low LET particles by ±10% and ±40%. Results At a small angle, maximum RBE by secondary fragments was 1.3 for 10% survival fractions. RBE values of fragments gradually decreased as the angle became larger. The shape of the LET spectra in the simulation reproduced the experimental spectra, but there was a discrepancy between the simulation and experiment for the relative yield of fragments. When the yield of low LET particles was changed by ±40%, the change of RBE was smaller than 10%. Conclusions RBE of 1.3 was expected for secondary fragments emitted at a small angle. Though, we observed a discrepancy in the relative yield of secondary fragments between simulation and experiment, precision of RBE was not so sensitive to the yield of low LET particles.

The conventional photoacoustic microscopy usually uses mechanical raster scanning to obtain three-dimensional information, and the imaging speed is limited. Meanwhile, the conventional photoacoustic microscopy can only be performed at one single scale due to fixed resolution, it cannot make full use of multiscale information for integrated imaging. Here, we proposed a multiscale photoacoustic microscopy based on single-pixel imaging. A sequence of sinusoidal fringes with varying spatial frequencies is used to obtain the Fourier coefficients in the case of a single ultrasonic transducer. By controlling the spatial frequency of fringe, the acquisition of Fourier coefficients can be controlled and multiscale imaging can be achieved. The feasibility of this method is verified by theory and simulation. The results show that the lateral resolution can be tuned from several microns to tens of microns without mechanical scanning. This method will expand the application of photoacoustic imaging in biomedical research.

Muscle fatigue during isometric contraction of biceps brachii is analysed using synchrosqueezed continuous wavelet transform with Morlet wavelet and singular value decomposition (SVD) features. The recorded surface electromyography signals are decomposed to time frequency matrix using Morlet wavelet and the characteristics are extracted using singular value features such as maximum singular value and zero crossing frequency. The percentage difference in feature values for each segment with the progression of fatigue is calculated. Results show that the recorded signals are complex, non‐stationary, multicomponent, and random in nature. Maximum singular value represents the non‐stationarity of a signal, with an increasing trend towards the fatigue condition. Zero crossing frequency represents the complexity or randomness in the signals and it decreases with the progression of fatigue. It is found that both the features are statistically significant with p

A theory is presented by which voltammograms, and dynamic electrochemical impedance spectroscopy (dEIS) measurements of redox processes of surface‐confined species can be analyzed. By the proposed procedure, from a set of voltammograms taken at varied scan‐rates, two scan‐rate independent, hysteresis‐free functions of potential can be calculated. One of them characterizes the redox kinetics, the other is the electrode charge associated with the redox equilibrium. The theory also comprises the analysis of the impedance spectra of the same system, which have been measured during dynamic conditions, i.e., during potental scans. Because of the formal analogy, the procedure is applicable also for voltammetry and dEIS of adsorption processes.

The development of hyperpolarization technologies enabled several yet exotic NMR applications at low and ultra‐low fields (ULF), where without hyperpolarization even the detection of a signal from analytes is a challenge. Herein, we present a method for the simultaneous excitation and observation of homo‐ and heteronuclear multiple quantum coherences (from zero up to the third‐order), which give an additional degree of freedom for ULF NMR experiments, where the chemical shift variation is negligible. The approach is based on heteronuclear correlated spectroscopy (COSY); its combination with a phase‐cycling scheme allows the selective observation of multiple quantum coherences of different orders. The nonequilibrium spin state and multiple spin orders are generated by signal amplification by reversible exchange (SABRE) and detected at ULF with a superconducting quantum interference device (SQUID)‐based NMR system., Ultra‐low field COrrelation SpectroscopY (ULF COSY): Hyperpolarized homo‐ and heteronuclear (1H‐19F) multiple quantum coherences (MQCs) from zero to the third order were observed at 91 μT by SQUID based NMR. MQCs were assigned by using density matrix simulations and measured here by a phase cycling modified ULF COSY sequence. The method allowed us to look deeper inside hyperpolarization processes at low magnetic fields.

Purpose: The gradient system transfer function (GSTF) characterizes the frequency transfer behavior of a dynamic gradient system and can be used to correct non‐Cartesian k‐space trajectories. This study analyzes the impact of the gradient coil temperature of a 3T scanner on the GSTF. Methods: GSTF self‐ and B\(_0\)‐cross‐terms were acquired for a 3T Siemens scanner (Siemens Healthcare, Erlangen, Germany) using a phantom‐based measurement technique. The GSTF terms were measured for various temperature states up to 45°C. The gradient coil temperatures were measured continuously utilizing 12 temperature sensors which are integrated by the vendor. Different modeling approaches were applied and compared. Results: The self‐terms depend linearly on temperature, whereas the B0‐cross‐term does not. Effects induced by thermal variation are negligible for the phase response. The self‐terms are best represented by a linear model including the three gradient coil sensors that showed the maximum temperature dependence for the three axes. The use of time derivatives of the temperature did not lead to an improvement of the model. The B\(_0\)‐cross‐terms can be modeled by a convolution model which considers coil‐specific heat transportation. Conclusion: The temperature dependency of the GSTF was analyzed for a 3T Siemens scanner. The self‐ and B0‐cross‐terms can be modeled using a linear and convolution modeling approach based on the three main temperature sensor elements.

PURPOSE: Patient body motion during a cardiac Positron Emission Tomography (PET) scan can severely degrade image quality. We propose and evaluate a novel method to detect, estimate, and correct body motion in cardiac PET. METHODS: Our method consists of three key components: motion detection, motion estimation, and motion-compensated image reconstruction. For motion detection, we first divide PET list-mode data into 1-second bins and compute the center of mass (COM) of the coincidences’ distribution in each bin. We then compute the covariance matrix within a 25-second sliding window over the COM signals inside the window. The sum of the eigenvalues of the covariance matrix is used to separate the list-mode data into “static” (i.e. body motion free) and “moving” (i.e. contaminated by body motion) frames. Each moving frame is further divided into a number of evenly-spaced sub-frames (referred to as “sub-moving” frames), in which motion is assumed to be negligible. For motion estimation, we first reconstruct the data in each static and sub-moving frame using a rapid back-projection technique. We then select the longest static frame as the reference frame and estimate elastic motion transformations to the reference frame from all other static and sub-moving frames using non-rigid registration. For motion-compensated image reconstruction, we reconstruct all the list-mode data into a single image volume in the reference frame by incorporating the estimated motion transformations in the PET system matrix. We evaluated the performance of our approach in both phantom and human studies. RESULTS: Visually, the motion-corrected (MC) PET images obtained by the proposed method have better quality and fewer motion artifacts than the images reconstructed without motion correction (NMC). Quantitative analysis indicates that MC yields higher myocardium to blood pool concentration ratios. MC also yields sharper myocardium than NMC. CONCLUSION: The proposed body motion correction method improves image quality of cardiac PET.

Understanding the functional dynamics of neural oscillations in the sensory thalamus is essential for elucidating the perception and modulation of neuropathic pain. Local field potentials were recorded from the sensory thalamus of twelve neuropathic pain patients. Single and combinational neural states were defined by the activity state of a single or paired oscillations. Relationships between the duration or occurrence rate of neural state and pre-operative pain level or pain relief induced by deep brain stimulation were evaluated. Results showed that the occurrence rate of the single neural state of low-beta oscillation was significantly correlated with pain relief. The duration and occurrence rate of combinational neural states of the paired low-beta with delta, theta, alpha, high-beta or low-gamma oscillations were more significantly correlated with pain relief than the single neural states. Moreover, these significant combinational neural states formed a local oscillatory network with low-beta oscillation as a key node. The results also showed correlations between measures of combinational neural states and subjective pain level as well. The duration of combinational neural states of paired alpha with delta or theta oscillations and the occurrence rate of neural states of the paired delta with low-beta or low-gamma oscillations were significantly correlated with pre-operative pain level. In conclusion, this study revealed that the integration of oscillations and the functional dynamics of neural states were differentially involved in modulation and perception of neuropathic pain. The functional dynamics could be biomarkers for developing neural state-dependent deep brain stimulation for neuropathic pain.

Purpose Respiration causes the deformation and sliding motion of the soft tissues, and affects the accuracy of the assessment of minimally invasive abdominal surgery. Nonrigid registration is used to eliminate the effects of respiration for the assessment. Because the soft tissues with high water content are volume preserving during deformation, incompressibility has to be considered when tracking soft tissues for nonrigid registration. The purpose of the study was to develop an incompressible nonrigid registration for tracking deformable soft tissues with sliding motion. Methods The nonrigid registration framework proposed in the present study includes two main steps: (a) The solution in the subspace of diffeomorphisms is searched and encoded to stationary velocity field in the log domain. (b) The divergence-free component and harmonic remainder are extracted by Fourier-based Helmholtz-Hodge decomposition (FHHD) and further integrated by an adaptive weight to simultaneously retain the incompressibility of deformation and compensate the sliding motion. The method was evaluated on 11 groups of synthetic datasets and five groups of clinical images. Registration accuracy is evaluated by using four quantitative measures, including mean surface distance (MSD), Hausdorff distance (HD), mean corresponding distance (MCD), and Dice similarity coefficient (DSC). Incompressibility is evaluated by using two quantitative measures, including relative volume change (RVC) and Jacobian determinant (J). Results Compared with three state-of-the-art nonrigid registration methods, the proposed method shows an advantage in handling the incompressible deformation of images with large sliding motion. The lowest (MSD, 0.631 mm), (HD, 6.000 mm), and (MCD, 3.555 mm) and the highest (DSC, 0.970) are obtained proving the high registration accuracy with sliding motion compensation of the proposed method. The (RVC, 0.006) and Jacobian determinant (J, 1.008 ± 0.070) are nearly close to 0 and 1, respectively, showing the strong incompressibility of the proposed method. The proposed method improves registration accuracy in nearly all cases, which maintains the incompressibility of tissue transformation while simultaneously compensating the sliding motion on clinical datasets. Conclusions The proposed method improves the registration accuracy of incompressible tissues when dealing with large sliding motion, and thus has the potential to improve current minimally invasive abdominal surgery.

Purpose: To demonstrate feasibility of transceive phase mapping with the PLANET method and its application for conductivity reconstruction in the brain. Methods: Accuracy and precision of transceive phase (ϕ±) estimation with PLANET, an ellipse fitting approach to phase-cycled balanced steady-state free precession (bSSFP) data, were assessed with simulations and measurements and compared to standard bSSFP. Measurements were conducted on a homogeneous phantom and in the brain of healthy volunteers at 3 tesla. Conductivity maps were reconstructed with Helmholtz-based electrical properties tomography. In measurements, PLANET was also compared to a reference technique for transceive phase mapping, i.e., spin echo. Results: Accuracy and precision of ϕ± estimated with PLANET depended on the chosen flip angle and TR. PLANET-based ϕ± was less sensitive to perturbations induced by off-resonance effects and partial volume (e.g., white matter + myelin) than bSSFP-based ϕ±. For flip angle = 25° and TR = 4.6 ms, PLANET showed an accuracy comparable to that of reference spin echo but a higher precision than bSSFP and spin echo (factor of 2 and 3, respectively). The acquisition time for PLANET was ~5 min; 2 min faster than spin echo and 8 times slower than bSSFP. However, PLANET simultaneously reconstructed T1, T2, B0 maps besides mapping ϕ±. In the phantom, PLANET-based conductivity matched the true value and had the smallest spread of the three methods. In vivo, PLANET-based conductivity was similar to spin echo-based conductivity. Conclusion: Provided that appropriate sequence parameters are used, PLANET delivers accurate and precise ϕ± maps, which can be used to reconstruct brain tissue conductivity while simultaneously recovering T1, T2, and B0 maps.

PURPOSE The purpose of this work is to analyze whether the Monte Carlo codes penh, fluka, and geant4/topas are suitable to calculate absorbed doses and fQ/fQ0 ratios in therapeutic high-energy photon and proton beams. METHODS We used penh, fluka, geant4/topas, and egsnrc to calculate the absorbed dose to water in a reference water cavity and the absorbed dose to air in two air cavities representative of a plane-parallel and a cylindrical ionization chamber in a 1.25 MeV photon beam and a 150 MeV proton beam - egsnrc was only used for the photon beam calculations. The physics and transport settings in each code were adjusted to simulate the particle transport as detailed as reasonably possible. From these absorbed doses, fQ0 factors, fQ factors, and fQ/fQ0 ratios (which are the basis of Monte Carlo calculated beam quality correction factors kQ,Q0 ) were calculated and compared between the codes. Additionally, we calculated the spectra of primary particles and secondary electrons in the reference water cavity, as well as the integrated depth-dose curve of 150 MeV protons in water. RESULTS The absorbed doses agreed within 1.4% or better between the individual codes for both the photon and proton simulations. The fQ0 and fQ factors agreed within 0.5% or better for the individual codes for both beam qualities. The resulting fQ/fQ0 ratios for 150 MeV protons agreed within 0.7% or better. For the 1.25 MeV photon beam, the spectra of photons and secondary electrons agreed almost perfectly. For the 150 MeV proton simulation, we observed differences in the spectra of secondary protons whereas the spectra of primary protons and low-energy delta electrons also agreed almost perfectly. The first 2 mm of the entrance channel of the 150 MeV proton Bragg curve agreed almost perfectly while for greater depths, the differences in the integrated dose were up to 1.5%. CONCLUSION penh, fluka, and geant4/topas are capable of calculating beam quality correction factors in proton beams. The differences in the fQ0 and fQ factors between the codes are 0.5% at maximum. The differences in the fQ/fQ0 ratios are 0.7% at maximum.

Purpose To investigate the feasibility of using an electromagnetic (EM) tracker to estimate rigid body head motion parameters, and using these measurements to retrospectively reduce motion artifacts. Theory and methods A clinically used MPRAGE sequence was modified to measure motion using the EM tracking system once per repetition time. A retrospective k-space based motion correction algorithm that corrects for phase ramps (translation in image domain) and rotation of 3D k-space (rotation in image domain) was developed, using the parameters recorded using an EM tracker. The accuracy of the EM tracker for the purpose of motion measurement and correction was tested in phantoms, volunteers, and pediatric patients. Results Position localization was accurate to the order of 200 microns compared with registration localization in a phantom study. The quality of reconstructed images was assessed by computing the root mean square error, the structural similarity metric and average edge strength. Image quality improved consistently when motion correction was applied in both volunteer scans with deliberate head motion and in pediatric patient scans. In patients, the average edge strength improved significantly with retrospective motion correction, compared with images with no correction applied. Conclusions EM tracking was effective in measuring head motion in the MRI scanner with high accuracy, and enabled retrospective reconstruction to improve image quality by reducing motion artifacts.

PURPOSE: To propose a highly-accelerated, high-resolution dynamic contrast-enhanced MRI (DCE-MRI) technique called GRASP-Pro (Golden-angle RAdial Sparse Parallel imaging with imProved performance) through a joint sparsity and self-calibrating explicit subspace-constraint with automated selection of contrast phases. METHODS: GRASP-Pro reconstruction enforces a combination of self-calibrating explicit low-rank subspace-constraint and temporal sparsity constraint. The temporal basis used to construct subspace is estimated from an intermediate reconstruction using the low-resolution portion of radial k-space, which eliminates the need for generating the basis using auxiliary data or a physical signal model. A convolutional neural network was trained to generate the contrast enhancement curve in the artery, from which clinically-relevant contrast phases are automatically selected for evaluation. The performance of GRASP-Pro was demonstrated for high spatiotemporal resolution DCE-MRI of the prostate and was compared against standard GRASP in terms of overall image quality, image sharpness, and residual streaks/noise level. RESULTS: Compared to GRASP, GRASP-Pro was able to reconstruct dynamic images with enhanced sharpness, less residual streaks/noise and finer delineation of the prostate without prolonging reconstruction time. The image quality improvement reaches statistical significance (P

Purpose Quantitative MRI applications, such as mapping the T1 time of tissue, puts high demands on the accuracy and precision of transmit field ( B 1 + ) estimation. A candidate approach to satisfy these requirements exploits the difference in phase induced by the Bloch-Siegert frequency shift (BSS) of 2 acquisitions with opposite off-resonance frequency radiofrequency pulses. Interleaving these radiofrequency pulses ensures robustness to motion and scanner drifts; however, here we demonstrate that doing so also introduces a bias in the B 1 + estimates. Theory and methods It is shown here by means of simulation and experiments that the amplitude of the error depends on MR pulse sequence parameters, such as repetition time and radiofrequency spoiling increment, but more problematically, on the intrinsic properties, T1 and T2 , of the investigated tissue. To solve these problems, a new approach to BSS-based B 1 + estimation that uses a multi-echo acquisition and a general linear model to estimate the correct BSS-induced phase is presented. Results In line with simulations, phantom and in vivo experiments confirmed that the general linear model-based method removed the dependency on tissue properties and pulse sequence settings. Conclusion The general linear model-based method is recommended as a more accurate approach to BSS-based B 1 + mapping.

We present a mathematical analysis of a reaction-diffusion model describing acid-mediated tumor invasion. The model describes the spatial distribution and temporal evolution of tumor cells, normal cells, and excess lactic acid concentration. The model assumes that tumor-induced alteration of microenvironmental pH provides a simple but complete mechanism for cancer invasion. We provide results on the existence and uniqueness of a solution considering Neumann and Dirichlet boundary conditions. We also provide numerical simulations to the solutions considering both boundary conditions.

Purpose To investigate the influence of magnetic fields on the microdosimetry of carbon-ion beams and the scaling effect of tissue equivalent proportional counter (TEPC) defined as the change of energy deposition in a TEPC from that in a microscopic scale region of interest due to the presence of a magnetic field in combination with the TEPC larger physical dimensions. Methods Geant4-based Monte Carlo simulations were conducted to calculate the microdosimetric quantities for carbon-ion beams with different initial energies (10-290 MeV/u) under magnetic fields of various strengths (0.5-3 T). The calculations were performed for a 1 μm spherical volume made of tissue, and for spherical TEPCs of 1 and 10 mm in diameter. Then, values of dose-averaged lineal energy (yD ) were acquired for the different scenarios to analyze the effect of magnetic fields on the microdosimetry of carbon-ion beams and the scaling effect of TEPC. Results The yD values and lineal energy spectra in the 1 μm spherical tissue volume for the scenarios without magnetic field and with magnetic fields of different strengths and directions remained nearly the same for the various energy carbon-ion beams. However, compared with those of the 1 μm spherical tissue volume, an increase of of yD values and an obvious shift of the lineal energy spectra for the TEPCs of 1 and 10 mm in diameter under magnetic fields were found. Conclusions The application of magnetic fields under 3 T has no significant influence on the microdosimetric results of carbon-ion beams. However, there is definitely a scaling effect when using TEPC for microdosimetric study, which alters the reading of TEPC in the presence of magnetic fields. Novel methods to correct the reading of TEPC or scaling effect-resistant microdosimetric measurement detectors are urgently needed to perform experimental microdosimetric studies under magnetic fields.

Nonrigid registration of medical images is especially critical in clinical treatment. Mutual information is a popular similarity measure for medical image registration; however, only the intensity statistical characteristics of the global consistency of image are considered in MI, and the spatial information is ignored. In this paper, a novel intensity‐based similarity measure combining normalized mutual information with spatial information for nonrigid medical image registration is proposed. The different parameters of Gaussian filtering are defined according to the regional variance, the adaptive Gaussian filtering is introduced into the local structure tensor. Then, the obtained adaptive local structure tensor is used to extract the spatial information and define the weighting function. Finally, normalized mutual information is distributed to each pixel, and the discrete normalized mutual information is multiplied with a weighting term to obtain a new measure. The novel measure fully considers the spatial information of the image neighborhood, gives the location of the strong spatial information a larger weight, and the registration of the strong gradient regions has a priority over the small gradient regions. The simulated brain image with single‐modality and multimodality are used for registration validation experiments. The results show that the new similarity measure improves the registration accuracy and robustness compared with the classical registration algorithm, reduces the risk of falling into local extremes during the registration process.

Purpose: Dual-head positron emission tomography (PET) scanners have increasingly attracted the attention of many researchers. However, with the compact geometry, the depth-of-interaction blurring will reduce the image resolution considerably. Monte Carlo (MC)-based system response matrix (SRM) is able to describe the physical process of PET imaging accurately and improve reconstruction quality significantly. The MC-based SRM is large and precomputed, which leads to a longer image reconstruction time with indexing and retrieving precomputed system matrix elements. In this study, we proposed a GPU acceleration algorithm to accelerate the iterative reconstruction. Methods: It has been demonstrated that the line-of-response (LOR)-based symmetry and the Graphics Processing Unit (GPU) technology can accelerate the reconstruction tremendously. LOR-based symmetry is suitable for the forward projection calculation, but not for the backprojection. In this study, we proposed a GPU acceleration algorithm that combined the LOR-based symmetry and voxel-based symmetry together, in which the LOR-based symmetry is responsible for the forward projection, and the voxel-based symmetry is used for the backprojection. Results: Simulation and real experiments verify the efficiency of the algorithm. Compared with the CPU-based calculation, the acceleration ratios of the forward projection and the backprojection operation are 130 and 110, respectively. The total acceleration ratio is 113x. In order to compare the acceleration effect of the different symmetries, we realized the reconstruction with the voxel-based symmetry and the LOR-based symmetry strategies. Compared with the LOR-based GPU reconstruction, the acceleration ratio is 3.5x. Compared with the voxel-based GPU reconstruction, the acceleration ratio is 12x. Conclusion: We have proposed a new acceleration algorithm for the dual-head PET system, in which both the forward and backprojection operations are accelerated by GPU. (c) 2019 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.