A Two-Step Framework for Multi-Material Decomposition of Dual Energy Computed Tomography from Projection Domain.

Background And Purpose: Dual-energy computed tomography (DECT) utilizes separate X-ray energy spectra to improve multi-material decomposition (MMD) for various diagnostic applications. However accurate decomposing more than two types of material remains challenging using conventional methods. Deep learning (DL) methods have shown promise to improve the MMD performance, but typical approaches of conducing DL-MMD in the image domain fail to fully utilize projection information or are under computationally inefficient iterative setup.

Ultrastructure of the ejaculatory duct of Terrobittacus implicatus (Mecoptera: Bittacidae).

The unique mating behavior of Bittacidae has been extensively studied, yet the mechanisms underlying internal sperm transport and temporary storage before mating remain enigmatic. Herein, we aim to elucidate these mechanisms by investigating the fine structure of the ejaculatory duct, which serves for sperm transport and temporary storage. The ultrastructure of the ejaculatory duct of Terrobittacus implicatus (Mecoptera: Bittacidae) was examined by light and transmission electron microscopy for the first time in this study.

Prediction of Residual Compressive Strength after Impact Based on Acoustic Emission Characteristic Parameters.

This study proposes a prediction method for residual compressive strength after impact based on the extreme gradient boosting model, focusing on composite laminates as the studied material system. Acoustic emission tests were conducted under controlled temperature and humidity conditions to collect characteristic parameters, establishing a mapping relationship between these parameters and residual compressive strength under small sample conditions. The model accurately predicted the residual compressive strength of the laminates after impact, with the coefficient of determination and root mean square error for the test set being 0.

Analytical HDR prostate brachytherapy planning with automatic catheter and isotope selection.

Background: High dose rate (HDR) brachytherapy is commonly used to treat prostate cancer. Existing HDR planning systems solve the dwell time problem for predetermined catheters and a single energy source.

Purpose: Additional degrees of freedom can be obtained by relaxing the catheters' pre-designation and introducing more source types, and may have a dosimetric benefit, particularly in improving conformality to spare the urethra.

Deep Transfer Learning Approach for Localization of Damage Area in Composite Laminates Using Acoustic Emission Signal.

Intelligent composite structures with self-aware functions are preferable for future aircrafts. The real-time location of damaged areas of composites is a key step. In this study, deep transfer learning was used to achieve the real-time location of damaged areas.

Ultrastructure of Ejaculatory Ducts of and (Mecoptera: Panorpidae).

The ultrastructure of the ejaculatory duct was investigated in the scorpionflies (Chou 1981) and (Hua & Cai, 2009) (Mecoptera: Panorpidae) using light and transmission electron microscopy. The ejaculatory ducts of both species comprise a median duct and an accessory sac. The median duct consists of a basal lamina, a mono-layered epithelium, a subcuticular cavity, and an inner cuticle.

Tomographic detection of photon pairs produced from high-energy X-rays for the monitoring of radiotherapy dosing.

Measuring the radiation dose reaching a patient's body is difficult. Here we report a technique for the tomographic reconstruction of the location of photon pairs originating from the annihilation of positron-electron pairs produced by high-energy X-rays travelling through tissue. We used Monte Carlo simulations on pre-recorded data from tissue-mimicking phantoms and from a patient with a brain tumour to show the feasibility of this imaging modality, which we named 'pair-production tomography', for the monitoring of radiotherapy dosing.

An efficient rectangular optimization method for sparse orthogonal collimator based small animal irradiation.

Intensity-modulated radiotherapy (IMRT) is widely used in clinical radiotherapy, treating varying malignancies with conformal doses. As the test field for clinical translation, preclinical small animal experiments need to mimic the human radiotherapy condition, including IMRT. However, small animal IMRT is a systematic challenge due to the lack of corresponding hardware and software for miniaturized targets.

Reformulated McNamara RBE-weighted beam orientation optimization for intensity modulated proton therapy.

Purpose: Empirical relative biological effectiveness (RBE) models have been used to estimate the biological dose in proton therapy but do not adequately capture the factors influencing RBE values for treatment planning. We reformulate the McNamara RBE model such that it can be added as a linear biological dose fidelity term within our previously developed sensitivity-regularized and heterogeneity-weighted beam orientation optimization (SHBOO) framework.

Methods: Based on our SHBOO framework, we formulated the biological optimization problem to minimize total McNamara RBE dose to OARs.

ROAD: ROtational direct Aperture optimization with a Decoupled ring-collimator for FLASH radiotherapy.

Ultra-high dose rate in radiotherapy (FLASH) has been shown to increase the therapeutic index with markedly reduced normal tissue toxicity and the same or better tumor cell killing. The challenge to achieve FLASH using x-rays, besides developing a high output linac, is to intensity-modulate the high-dose-rate x-rays so that the biological gain is not offset by the lack of physical dose conformity. In this study, we develop the ROtational direct Aperture optimization with a Decoupled ring-collimator (ROAD) to achieve simultaneous ultrafast delivery and complex dose modulation.

DeepMC: a deep learning method for efficient Monte Carlo beamlet dose calculation by predictive denoising in magnetic resonance-guided radiotherapy.

Emerging magnetic resonance (MR) guided radiotherapy affords significantly improved anatomy visualization and, subsequently, more effective personalized treatment. The new therapy paradigm imposes significant demands on radiation dose calculation quality and speed, creating an unmet need for the acceleration of Monte Carlo (MC) dose calculation. Existing deep learning approaches to denoise the final plan MC dose fail to achieve the accuracy and speed requirements of large-scale beamlet dose calculation in the presence of a strong magnetic field for online adaptive radiotherapy planning.

Identification and expression profiles of candidate chemosensory receptors in (Lepidoptera: Zygaenidae).

Insect olfaction and vision play important roles in survival and reproduction. Diurnal butterflies mainly rely on visual cues whereas nocturnal moths rely on olfactory signals to locate external resources. Cramer (Lepidoptera: Zygaenidae) is an important pest of the landscape tree in China and other Southeast Asian regions.

A novel energy layer optimization framework for spot-scanning proton arc therapy.

Purpose: Spot-scanning proton arc therapy (SPAT) is an emerging modality to improve plan conformality and delivery efficiency. A greedy and heuristic method is proposed in the existing SPAT algorithm to select energy layers and sequence energy switching with gantry rotation, which does not promise optimality in either dosimetry or efficiency. We aim to develop a method to solve the energy layer switching and dosimetry optimization problems in an integrated framework for SPAT.

Image-domain multimaterial decomposition for dual-energy computed tomography with nonconvex sparsity regularization.

Dual-energy computed tomography (CT) has the potential to decompose tissues into different materials. However, the classic direct inversion (DI) method for multimaterial decomposition (MMD) cannot accurately separate more than two basis materials due to the ill-posed problem and amplified image noise. We propose an integrated MMD method that addresses the piecewise smoothness and intrinsic sparsity property of the decomposition image.

Noise Suppression in Image-Domain Multi-Material Decomposition for Dual-Energy CT.

Objective: Dual-energy CT (DECT) strengthens the material characterization and quantification due to its capability of material discrimination. The image-domain multi-material decomposition (MMD) via matrix inversion suffers from serious degradation of the signal-to-noise ratios (SNRs) of the decomposed images, and thus the clinical application of DECT is limited. In this paper, we propose a noise suppression algorithm based on the noise propagation for image-domain MMD.

Single-arc VMAT optimization for dual-layer MLC.

Dual-layer multi-leaf collimator (DLMLC) has recently attracted renewed interest due to its good balance among resolution, low leakage, and high fabricability. However, existing progressive sampling based volumetric modulated arc therapy (VMAT) algorithm is ineffective for DLMLC, requiring more arcs to achieve dosimetry comparable to VMAT plans with higher resolution single-layer MLC (SLMLC). In this study, we develop a novel single-arc VMAT optimization framework to take advantage of the unique DLMLC characteristics fully.

Ultrastructure of the vasa deferentia of Terrobittacus implicatus and Cerapanorpa nanwutaina (Insecta: Mecoptera).

The fine structures of vasa deferentia and postvesicular vasa deferentia were investigated in the hangingfly Terrobittacus implicatus (Cai et al. 2006) and the scorpionfly Cerapanorpa nanwutaina (Chou 1981) using light and transmission electron microscopy, and schematic diagrams were drawn accordingly. The vasa deferentia of both species comprise muscular layers, a basal lamina, and a mono-layered epithelium, but the postvesicular vasa deferentia contain muscular layers, a basal lamina, a single-layered epithelium, a subcuticular cavity, and an inner cuticle respectively.

A novel optimization framework for VMAT with dynamic gantry couch rotation.

Existing volumetric modulated arc therapy (VMAT) optimization using coplanar arcs is highly efficient but usually dosimetrically inferior to intensity modulated radiation therapy (IMRT) with optimized non-coplanar beams. To achieve both dosimetric quality and delivery efficiency, we proposed in this study, a novel integrated optimization method for non-coplanar VMAT (4πVMAT). 4πVMAT with direct aperture optimization (DAO) was achieved by utilizing a least square dose fidelity objective, along with an anisotropic total variation term for regularizing the fluence smoothness, a single segment term for imposing simple apertures, and a group sparsity term for selecting beam angles.

Technical Note: Iterative megavoltage CT (MVCT) reconstruction using block-matching 3D-transform (BM3D) regularization.

Purpose: Megavoltage CT (MVCT) images are noisier than kilovoltage CT (KVCT) due to low detector efficiency to high-energy x rays. Conventional denoising methods compromise edge resolution and low-contrast object visibility. In this work, we incorporated block-matching 3D-transform shrinkage (BM3D) transformation into MVCT iterative reconstruction as nonlocal patch-wise regularization.

VMAT optimization with dynamic collimator rotation.

Purpose: Although collimator rotation is an optimization variable that can be exploited for dosimetric advantages, existing Volumetric Modulated Arc Therapy (VMAT) optimization uses a fixed collimator angle in each arc and only rotates the collimator between arcs. In this study, we develop a novel integrated optimization method for VMAT, accounting for dynamic collimator angles during the arc motion.

Methods: Direct Aperture Optimization (DAO) for Dynamic Collimator in VMAT (DC-VMAT) was achieved by adding to the existing dose fidelity objective an anisotropic total variation term for regulating the fluence smoothness, a binary variable for forming simple apertures, and a group sparsity term for controlling collimator rotation.

Ultrastructure and function of the seminal vesicle of Bittacidae (Insecta: Mecoptera).

The fine structure of the seminal vesicle and reproductive accessory glands was investigated in Bittacidae of Mecoptera using light and transmission electron microscopy. The male reproductive system of Bittacidae mainly consists of a pair of testes, a pair of vasa deferentia, and an ejaculatory sac. The vas deferens is greatly expanded for its middle and medio-posterior parts to form a well-developed seminal vesicle.

Shading correction assisted iterative cone-beam CT reconstruction.

Recent advances in total variation (TV) technology enable accurate CT image reconstruction from highly under-sampled and noisy projection data. The standard iterative reconstruction algorithms, which work well in conventional CT imaging, fail to perform as expected in cone beam CT (CBCT) applications, wherein the non-ideal physics issues, including scatter and beam hardening, are more severe. These physics issues result in large areas of shading artifacts and cause deterioration to the piecewise constant property assumed in reconstructed images.

Ultrastructure of male accessory glands in the scorpionfly Sinopanorpa tincta (Navás, 1931) (Mecoptera: Panorpidae).

The ultrastructure of male reproductive accessory glands was investigated in the scorpionfly Sinopanorpa tincta (Navás, 1931) (Mecoptera: Panorpidae) using light and transmission electron microscopy. The male accessory glands comprise one pair of mesodermal glands (mesadenia) and six pairs of ectodermal glands (ectadenia). The former opens into the vasa deferentia and the latter into the ejaculatory sac.