Parotid perfusion in nasopharyngeal carcinoma patients in early-to-intermediate stage after low-dose intensity-modulated radiotherapy: Evaluated by fat-saturated dynamic contrast-enhanced magnetic resonance imaging

PurposeTo investigate parotid perfusion in early-to-intermediate stage after parotid-sparing radiation dose using fat-saturated DCE-MRI, and to verify whether the perfusion alteration was related to radiation dose and the PSV.Methods and MaterialsThirty-two parotid glands from 16 consecutive patients with pathologically proven nasopharyngeal carcinoma treated by IMRT were examined. The parotid glands received a radiation dose of 28.9 ± 3.9 Gy with a PSV of 43.1% ± 13.9%. Perfusion parameters were calculated using time-shifted Brix model from fat-saturated DCE-MRI data before (pre-RT) and in early-to-intermediate stage after (post-RT) IMRT. Paired t-test was used to evaluate perfusion changes, while Pearson's correlation test was used to examine perfusion dependency on radiation dose and PSV. For multiple comparisons Bonferroni correction was applied.ResultsSuccessful fat saturation was achieved in 29 of 32 parotid glands. Compared with pre-RT, the post-RT parotid glands showed significantly higher A, peak enhancement, and wash-in slope, plus a lower K_el, suggesting a mixed effect of increased vascular permeability and acinar loss. Linear regression showed that peak enhancement was positively associated with radiation dose in post-RT parotid glands. K_el and slope were negatively associated with PSV, while time-to-peak was positively associated with PSV significantly.ConclusionsOur results suggest that time-shifted Brix model is feasible for quantifying parotid perfusion using DCE-MRI. The perfusion alterations in early-to-intermediate stage after IMRT might be related to a mixed effect of increased vascular permeability and acinar loss with dose and PSV dependencies.     

Wavelength and power monitoring of DWDM systems using scanning F–P filter calibrated with a F–P laser

A novel technique to overcome the long-term drift and hysteresis of a scanning Fabry–Perot filter was developed and applied to wavelength and power monitoring of DWDM system. By using the comb peaks generated by a temperature-stabilized, near threshold-biased Fabry–Perot diode laser as wavelength reference for the scanning Fabry–Perot filter, wavelength and power measurement accuracy of better than ±10 pm and 0.2 dB, respectively, were achieved.     

Free-space Fresnel diffraction for the approximation of fractional Fourier transform

Fractional Fourier transformation of an object can be approximated by the object's free-space Fresnel diffraction pattern under some restricted conditions and plane wave illumination according to Hua's method. A better approximation is achieved under least-squared conditions developed in this paper. Simulation results verify that our theoretical development works for any fractional order a compared with the previous approach.     

Investigation of Heisenberg algebra for a modified anti-de Sitter and modified antiSnyder models

In this paper,we consider a possible modification of the de Sitter and anti-de Sitter space for the extended uncertainty principle.For the modified anti-de Sitter model we discuss the representation and wave functions of the momentum operator for a one-dimensional box problem.Also,we consider modified Snyder and anti-Snyder models for the generalized uncertainty principle.Then,we assume the Hamiltonian with different potential and solve the Heisenberg algebra for the modified(anti)-de Sitter and(anti)-Snyder models in both position and in the momentum space.     

Diffusion tensor parameters and principal eigenvector coherence: Relation to b-value intervals and field strength

Diffusion-weighted MRI images acquired at b-value greater than 1000 s mm^− 2 measure the diffusion of a restricted pool of water molecules. High b-value images are accompanied by a reduction in signal-to-noise ratio (SNR) due to the application of large diffusion gradients. By fitting the diffusion tensor model to data acquired at incremental b-value intervals, we determined the effect of SNR on tensor parameters in normal human brains, in vivo. In addition, we also investigated the impact of field strength on the diffusion tensor model. Data were acquired at 1.5 and 3 T, at b-values 0, 1000, 2000 and 3000 s mm^− 2 in twenty diffusion-sensitised directions. Fractional anisotropy (FA), mean diffusivity (MD) and principal eigenvector coherence (κ) were calculated from diffusion tensors fitted between datasets with b-values 0–1000, 0–2000, 0–3000, 1000–2000 and 2000–3000 s mm^− 2. Field strength and b-value effects on diffusion parameters were analysed in white and grey matter regions of interest. Decreases in FA, κ and MD were found with increasing b-value in white matter. Univariate analysis showed a significant increase in FA with increasing field strength in highly organised white matter. These results suggest there are significant differences in diffusion parameters at 1.5 and 3 T and that the optimal results, in terms of the highest values of FA in white matter, are obtained at 3 T with a maximum b = 1000 s mm^− 2.     

Defect of the five-thirds law using the Wiener-Hermite expansion

Application of the refined Wiener-Hermite expansion with moderate to high Reynolds numbers Re to homogeneous, isotropic turbulence is presented. The results show a defect to Kolmogorov's five-thirds law, increase in the absolute value of the exponent comparable with many theoretical predictions. Midrange spectra up to fluctuation Reynolds numbers of 10⁸ show little, if any, dependence of the defect on Re, as long as the initial spectra do not deviate too far from their equilibrium states. The renormalization scheme has also been proven to have no effect on the final shape of the spectrum.     

Novel Variable PDL Emulator Based on LiNbO3 Modulator

We propose and demonstrate a novel variable PDL emulator based on a LiNbO3 modulator. The proposed emulator could vary the PDL values simply by adjusting the bias voltage of modulator. The results show that the proposed PDL emulator could generate a wide range of PDL values (0 ～ 35 dB). The generated PDL value could be maintained within ± 0.02 dB for ＞70 minutes. The wavelength dependency was about 0.03 dB in the range of 1520nm ～ 1590 nm.     

Theranostic Iron@Gold Core–Shell Nanoparticles for Simultaneous Hyperthermia‐Chemotherapy upon Photo‐Stimulation

The challenges of nanoparticles, such as size‐dependent toxicity, nonbiocompatibility, or inability to undergo functionalization for drug conjugation, limit their biomedical application in more than one domain. Oval‐shaped iron@gold core–shell (oFe@Au) magnetic nanoparticles are engineered and their applications in magnetic resonance imaging (MRI), optical coherence tomography (OCT), and controlled drug release, are explored via photo stimulation‐generated hyperthermia. The oFe@Au nanoparticles have a size of 42.57 ± 5.99 nm and consist of 10.76 and 89.24 atomic % of Fe and Au, respectively. Upon photo‐stimulation for 10 and 15 minutes, the levels of cancer cell death induced by methotrexate‐conjugated oFe@Au nanoparticles are sixfold and fourfold higher, respectively, than oFe@Au nanoparticles alone. MRI and OCT confirm the application of these nanoparticles as a contrast agent. Finally, results of in vivo experiments reveal that the temperature is elevated by 13.2 °C, when oFe@Au nanoparticles are irradiated with a 167 mW cm^?2 808 nm laser, which results in a significant reduction in tumor volume and scab formation after 7 days, followed by complete disappearance after 14 days. The ability of these nanoparticles to generate heat upon photo‐stimulation also opens new doors for studying hyperthermia‐mediated controlled drug release for cancer therapy. Applications include biomedical engineering, cancer therapy, and theranostics fields.     

Efficient Krylov subspace methods for uncertainty quantification in large Bayesian linear inverse problems

Uncertainty quantification for linear inverse problems remains a challenging task, especially for problems with a very large number of unknown parameters (e.g., dynamic inverse problems) and for problems where computation of the square root and inverse of the prior covariance matrix are not feasible. This work exploits Krylov subspace methods to develop and analyze new techniques for large‐scale uncertainty quantification in inverse problems. In this work, we assume that generalized Golub‐Kahan‐based methods have been used to compute an estimate of the solution, and we describe efficient methods to explore the posterior distribution. In particular, we use the generalized Golub‐Kahan bidiagonalization to derive an approximation of the posterior covariance matrix, and we provide theoretical results that quantify the accuracy of the approximate posterior covariance matrix and of the resulting posterior distribution. Then, we describe efficient methods that use the approximation to compute measures of uncertainty, including the Kullback‐Liebler divergence. We present two methods that use the preconditioned Lanczos algorithm to efficiently generate samples from the posterior distribution. Numerical examples from dynamic photoacoustic tomography demonstrate the effectiveness of the described approaches.