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. This study presents a novel analytical approach to solving the corresponding HDR planning problem. METHODS: The catheter and dual-energy source selection problem was formulated as a constrained optimization problem with a non-convex group sparsity regularization. The optimization problem was solved using the fast-iterative shrinkage-thresholding algorithm (FISTA). Two isotopes were considered. The dose rates for the HDR 4140 Ytterbium (Yb-169) source and the Elekta Iridium (Ir-192) HDR Flexisource were modeled according to the TG-43U1 formalism and benchmarked accordingly. Twenty-two retrospective HDR prostate brachytherapy patients treated with Ir-192 were considered. An Ir-192 only (IRO), Yb-169 only (YBO), and dual-source (DS) plan with optimized catheter location was created for each patient with N catheters, where N is the number of catheters used in the clinically delivered plans. The DS plans jointly optimized Yb-169 and Ir-192 dwell times. All plans and the clinical plans were normalized to deliver a 15 Gy prescription (Rx) dose to 95% of the clinical treatment volume (CTV) and evaluated for the CTV D90%, V150%, and V200%, urethra D0.1cc and D1cc, bladder V75%, and rectum V75%. Dose-volume histograms (DVHs) were generated for each structure. RESULTS: The DS plans ubiquitously selected Ir-192 as the only treatment source. IRO outperformed YBO in organ at risk (OARs) OAR sparing, reducing the urethra D0.1cc and D1cc by 0.98% ( p = 2.22 ∗ 10 - 9 $p\ = \ 2.22*{10^{ - 9}}$ ) and 1.09% ( p = 1.22 ∗ 10 - 10 $p\ = \ 1.22*{10^{ - 10}}$ ) of the Rx dose, respectively, and reducing the bladder and rectum V75% by 0.09 ( p = 0.0023 $p\ = \ 0.0023$ ) and 0.13 cubic centimeters (cc) ( p = 0.033 $p\ = \ 0.033$ ), respectively. The YBO plans delivered a more homogenous dose to the CTV, with a smaller V150% and V200% by 3.20 ( p = 4.67 ∗ 10 - 10 $p\ = \ 4.67*{10^{ - 10}}$ ) and 1.91 cc ( p = 5.79 ∗ 10 - 10 $p\ = \ 5.79*{10^{ - 10}}$ ), respectively, and a lower CTV D90% by 0.49% ( p = 0.0056 $p\ = \ 0.0056$ ) of the prescription dose. The IRO plans reduce the urethral D1cc by 2.82% ( p = 1.38 ∗ 10 - 4 $p\ = \ 1.38*{10^{ - 4}}$ ) of the Rx dose compared to the clinical plans, at the cost of increased bladder and rectal V75% by 0.57 ( p = 0.0022 $p\ = \ 0.0022$ ) and 0.21 cc ( p = 0.019 $p\ = \ 0.019$ ), respectively, and increased CTV V150% by a mean of 1.46 cc ( p = 0.010 $p\ = \ 0.010$ ) and CTV D90% by an average of 1.40% of the Rx dose ( p = 8.80 ∗ 10 - 8 $p\ = \ 8.80*{10^{ - 8}}$ ). While these differences are statistically significant, the clinical differences between the plans are minimal. CONCLUSIONS: The proposed analytical HDR planning algorithm integrates catheter and isotope selection with dwell time optimization for varying clinical goals, including urethra sparing. The planning method can guide HDR implants and identify promising isotopes for specific HDR clinical goals, such as target conformality or OAR sparing.

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. The sensor network obtained acoustic emission signals from different damaged areas of the aluminum alloy plate. The acoustic emission time-domain signal is transformed into the input image by continuous wavelet transform. The convolutional neural network-based model automatically localized the damaged area by extracting features from the input image. A small amount of composite acoustic emission data was used to fine-tune some network parameters of the basic model through transfer learning. This enabled the model to classify the damaged area of composites. The accuracy of the transfer learning model trained with 900 samples is 96.38%, which is comparable to the accuracy of the model trained directly with 1800 samples; the training time of the former is only 17.68% of that of the latter. The proposed method can be easily adapted to new composite structures using transfer learning and a small dataset, providing a new idea for structural health monitoring.

Phylogenetic implications based on an ultrastructural study with emphasis on the tracheal system of the compound eyes of three species of nymphalid butterflies.

Compound eyes are the prominent visual organs of insects and can provide valuable information for the reconstruction of insect phylogeny. Although the largest butterfly family (Nymphalidae) has been well defined, the infrafamilial phylogenetic relationships remain controversial hitherto. In the present study the ultrastructure of the compound eyes of three nymphalids Neptis beroe, Childrena zenobia, and Palaeonympha opalina was investigated using light and transmission electron microscopy in an attempt to seek potentially important phylogenetic characters. The compound eyes of the nymphalids share a tracheal system in a "1-4-8" branching pattern. The eight tracheal subbranches exhibit distinct distribution patterns along the basal retinula cell as follows: the tracheal subbranches of Palaeonympha opaline are close to the rhabdom in the distance from the distalmost part of the basal retinula cell to the rhabdom end, while those of N. beroe and C. zenobia are on the periphery of the retinula along almost the whole basal retinula cell and become close to the rhabdom just at the proximal end of the basal retinula cell. The tracheal structure of the three nymphalids is discussed for their potential phylogenetic implications.

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. We simulated three image-reconstruction methods, one applicable to a pencil X-ray beam scanning through a region of interest, and two applicable to the excitation of tissue volumes via broad beams (with temporal resolution sufficient to identify coincident photon pairs via filtered back projection, or with higher temporal resolution sufficient for the estimation of a photon's time-of-flight). In addition to the monitoring of radiotherapy dosing, we show that image contrast resulting from pair-production tomography is highly proportional to the material's atomic number. The technique may thus also allow for element mapping and for soft-tissue differentiation.

Ultrastructure of Ejaculatory Ducts of Cerapanorpa nanwutaina and Furcatopanorpa longihypovalva (Mecoptera: Panorpidae).

The ultrastructure of the ejaculatory duct was investigated in the scorpionflies Cerapanorpa nanwutaina (Chou 1981) and Furcatopanorpa longihypovalva (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. The accessory sac contains a single layer of epithelium and a basal lamina. A muscular layer is present in the accessory sac of C. nanwutaina and in the median duct of F. longihypovalva. The epithelia in the median duct and the accessory sac are well developed, their cells containing numerous cisterns of rough endoplasmic reticulum, mitochondria, and microvilli. The secretions of the median duct are first extruded into the subcuticular cavity and then into the lumen through an inner cuticle, while the secretions of the accessory sac are discharged directly into the lumen. The ejaculatory duct of F. longihypovalva is longer and has thicker epithelium with more cell organelles and secretions than that of C. nanwutaina.

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

Objective.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.Approach.The sparse orthogonal collimators (SOC) based on the direct rectangular aperture optimization (RAO) substantially simplified the hardware for miniaturization. This study investigates and evaluates a significantly improved RAO algorithm for complex mouse irradiation using SOC. Because the Kronecker product representation of the rectangular aperture is the main limitation of the computational performance, we reformulated matrix multiplication in the data fidelity term using multiplication with small matrices instead of the Kronecker product of the dose loading matrices. Solving the optimization problem was further accelerated using the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA).Main results.Four mouse cases, including a liver, a brain tumor, a concave U-target, and a complex total marrow irradiation (TMI) case, were included in this study with manually delineated targets and OARs. Seven coplanar-field SOC IMRT (sIMRT) plans were compared with idealistic fluence map based IMRT (iIMRT) plans. For the first three cases with simpler and smaller targets, the differences between sIMRT plans and iIMRT plans in the planning target volumes (PTV) statistics are within 1%. For the TMI case, the sIMRT plans are superior in reducing hot spots (also termedDmax) of PTV, kidneys, lungs, heart, and bowel by 20.5%, 31.5%, 24.67%, 20.13%, and 17.78%, respectively. On average, in four cases in this study, the sIMRT plan conformity is comparable to that of the iIMRT's with lightly increased R50 and Integral Dose by 2.23% and 2.78%.Significance.The significantly improved sIMRT optimization method allows fast plan creation in under 1 min for smaller targets and makes complex TMI planning feasible while achieving comparable dosimetry to idealistic IMRT with fluence map optimization.

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. We solve this problem using two optimization algorithms: FISTA (McNam-FISTA) and Chambolle-Pock (McNam-CP). We compare their performances with a physical dose optimizer assuming RBE = 1.1 in all structures (PHYS-FISTA) and an LET-weighted dose model (LET-FISTA). Three head and neck patients were planned with the four techniques and compared on dosimetry and robustness. RESULTS: Compared to Phys-FISTA, McNam-CP was able to match CTV [HI, Dmax, D95%, D98%] by [0.00, 0.05%, 1.4%, 0.8%]. McNam-FISTA and McNam-CP were able to significantly improve overall OAR [Dmean, Dmax] by an average of [36.1%,26.4%] and [29.6%, 20.3%], respectively. Regarding CTV robustness, worst [Dmax, V95%, D95%, D98%] improvement of [-6.6%, 6.2%, 6.0%, 4.8%] was reported for McNam-FISTA and [2.7%, 2.7%, 5.3%, -4.3%] for McNam-CP under combinations of range and setup uncertainties. For OARs, worst [Dmax, Dmean] were improved by McNam-FISTA and McNam-CP by an average of [25.0%, 19.2%] and [29.5%, 36.5%], respectively. McNam-FISTA considerably improved dosimetry and CTV robustness compared to LET-FISTA, which achieved better worst-case OAR doses. CONCLUSION: The four optimization techniques deliver comparable biological doses for the head and neck cases. Besides modest CTV coverage and robustness improvement, OAR biological dose and robustness were substantially improved with both McNam-FISTA and McNam-CP, showing potential benefit for directly incorporating McNamara RBE in proton treatment planning.

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. The ROAD design includes a fast-rotating slip-ring linac and a decoupled collimator-ring with 75 pre-shaped multi-leaf-collimator (MLC) modules. The ring-source rotates at 1 rotation per second (rps) clockwise while the ring-collimator is either static or rotating at 1 rps counterclockwise, achieving 75 (ROAD-75) or 150 (ROAD-150) equal-angular beams for one full arc. The Direct Aperture Optimization (DAO) for ROAD was formulated to include a least-square dose fidelity, an anisotropic total variation term, and a single segment term. The FLASH dose (FD) and FLASH biological equivalent dose (FBED) were computed voxelwise, with the latter using a spatiotemporal model accounting for radiolytic oxygen depletion. ROAD was compared with clinical volumetric modulated arc therapy (VMAT) on a brain, a lung, a prostate, and a head and neck cancer patient. The mean dose rate of ROAD-75 and ROAD-150 are 76.2 Gy s-1 and 112 Gy s-1 respectively to deliver 25 Gy single-fraction dose in 1 s. With improved PTV homogeneity, ROAD-150 reduced (max, mean) OAR physical dose by (4.8 Gy, 6.3 Gy). The average R50 and integral dose of (VMAT, ROAD-75, ROAD-150) are (4.8, 3.2, 3.2) and (89, 57, 56) Gy×Liter, respectively. The FD and FBED showed model dependent FLASH effects. The novel ROAD design achieves ultrafast dose delivery and improves physical dosimetry compared with clinical VMAT, providing a potentially viable engineering solution for x-ray FLASH radiotherapy.

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. Our deep learning dose calculation method, DeepMC, addresses these needs by predicting low-noise dose from extremely noisy (but fast) MC-simulated dose and anatomical inputs, thus enabling significant acceleration. DeepMC simultaneously reduces MC sampling noise and predicts corrupted dose buildup at tissue-air material interfaces resulting from MR-field induced electron return effects. Here we demonstrate our model's ability to accelerate dose calculation for daily treatment planning by a factor of 38 over traditional low-noise MC simulation with clinically meaningful accuracy in deliverable dose and treatment delivery parameters. As a post-processing approach, DeepMC provides compounded acceleration of large-scale dose calculation when used alongside established MC acceleration techniques in variance reduction and graphics processing unit-based MC simulation.

Identification and expression profiles of candidate chemosensory receptors in Histia rhodope (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. Histia rhodope Cramer (Lepidoptera: Zygaenidae) is an important pest of the landscape tree Bischofia polycarpa in China and other Southeast Asian regions. As a diurnal moth, H. rhodope represents a suitable model for studying the evolutionary shift from olfactory to visual communication. However, only a few chemosensory soluble proteins have been characterized and information on H. rhodope chemoreceptor genes is currently lacking. In this study, we identified 45 odorant receptors (ORs), nine ionotropic receptors (IRs), eight gustatory receptors (GRs) and two sensory neuron membrane proteins (SNMPs) from our previously acquired H. rhodope antennal transcriptomic data. The number of chemoreceptors of H. rhodope was less compared with that found in many nocturnal moths. Some specific chemoreceptors such as OR co-receptor (ORco), ionotropic receptors co-receptor, CO2 receptors, sugar receptors and bitter receptors were predicted by phylogenetic analysis. Notably, two candidate pheromone receptors (PRs) were identified within a novel PR lineage. qRT-PCR results showed that almost all tested genes (22/24) were predominantly expressed in antennae, indicating that they may be important in olfactory function. Among these antennae-enriched genes, six ORs, five IRs and two GRs displayed female-biased expression, while two ORs displayed male-biased expression. Additionally, HrhoIR75q.2 and HrhoGR67 were more highly expressed in heads and legs. This study enriches the olfactory gene inventory of H. rhodope and provides the foundation for further research of the chemoreception mechanism in diurnal moths.

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. METHODS: In an integrated approach, energy layer optimization for spot-scanning proton arc therapy (ELO-SPAT) is formulated with a dose fidelity term, a group sparsity regularization, a log barrier regularization, and an energy sequencing (ES) penalty. The combination of L2,1/2-norm group sparsity regularization and log barrier function allows one energy layer being selected per control point. The ES regularization term sorts the delivery sequence from high energy to low energy to reduce the total energy layer switching time (ELST) and subsequently the total delivery time. Within the ES penalty, the gradient of layer weights between adjacent beams is first calculated along beam direction and then along energy direction. The gradients indicate energy switch patterns between two adjacent beams. The time-wise costly energy switch-up is more heavily penalized in the ES term. This ELO-SPAT method was tested on one frontal base-of-skull (BOS) patient, one chordoma (CHDM) patient with a simultaneous integrated boost, one bilateral head-and-neck (H&N) patient, and one lung (LNG) patient. We compared ELO-SPAT with intensity-modulated proton therapy (IMPT) using discrete beams and SPArc by Ding et al. For the two arc algorithms, both the plans with and without energy sequencing were created and compared. RESULTS: Energy layer optimization for spot-scanning proton arc therapy reduced the runtime of optimization by 84% on average compared with the greedy SPArc method. In both the ELO-SPAT plans with and without ES, one energy layer per control point was selected. Without ES regularization, the energy sequence was arbitrary, with around 40-60 switch-up for the tested cases. After adding ES regularization, the number of energy switch-up was reduced to less than 20. Compared with the energy sequenced SPArc plans, the ELO-SPAT plans with ES led to 24% less total ELST for synchrotron plans and 14% less for cyclotron plans. Both the ELO-SPAT and SPArc plans achieved better sparing compared with the IMPT plans for most Organs-at-risks (OARs), with or without ES. Without ES, the ELO-SPAT plans achieved further improvement of the OARs compared with the SPArc plans, with an averaged reduction of OAR [Dmean, Dmax] by [1.57, 3.34] GyRBE. Adding the ES regularization degraded the plan quality, but the ELO-SPAT plans still had comparable or slightly better sparing than the SPArc plans with ES, with an averaged reduction of OAR [Dmean, Dmax] by [1.42, 2.34] GyRBE. CONCLUSION: We developed a computationally efficient spot-scanning proton arc optimization method, which solved energy layer selection and sequencing in an integrated framework, generating plans with good dosimetry and high delivery efficiency.

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. METHODS: The noise in the decomposed images only distributes in two perpendicular directions and is suppressed by estimating the center of mass of the same-material pixel group vertically along the principal axis where the noise disturbance is minimal. The proposed method is evaluated using the line-pair and contrast-rod slices of the Catphan©600 phantom and one patient data set. We compared the proposed method with the direct inversion and the block-matching and three-dimensional (BM3D) filtration methods. RESULTS: The results of Catphan©600 phantom and the patient show that the proposed method successfully suppresses the noise of the basis material images by one order of magnitude and preserves the spatial resolution of the decomposed images. Compared with the BM3D filtration method, the proposed method maintains the texture distribution of the decomposed images at the same SNR and the accuracy of the electron density measurement. CONCLUSION: The algorithm achieves effective noise suppression compared with the BM3D filtration while maintaining the spatial distribution of the decomposed material images. It is, thus, attractive for advanced clinical applications using DECT.

Many-isocenter optimization for robotic radiotherapy.

Despite significant dosimetric gains, clinical implementation of the 4π non-coplanar radiotherapy on the widely available C-arm gantry system is hindered by limited clearance, and the need to perform complex coordinated gantry and couch motion. A robotic radiotherapy platform would be conducive to such treatment but a new conflict between field size and MLC modulation resolution needs to be managed for versatile applications. This study investigates the dosimetry and delivery efficiency of purposefully creating many isocenters to achieve simultaneously high MLC modulation resolution and large tumor coverage. An integrated optimization framework was proposed for simultaneous beam orientation optimization (BOO), isocenter selection, and fluence map optimization (FMO). The framework includes a least-square dose fidelity objective, a total variation term for regularizing the fluence smoothness, and a group sparsity term for beam selection. A minimal number of isocenters were identified for efficient target coverage. Colliding beams excluded, high-resolution small-field 4π intensity-modulated radiotherapy (IMRT) treatment plans with 50 cm source-to-isocenter distance (SID-50) on 10 Head and Neck (H&N) cancer patients were compared with low-resolution large-field plans with 100 cm SID (SID-100). With the same or better target coverage, the average reduction of [Dmean, Dmax] of 20-beam SID-50 plans from 20-beam SID-100 plans were [2.09 Gy, 1.19 Gy] for organs at risk (OARs) overall, [3.05 Gy, 0.04 Gy] for parotid gland, [3.62 Gy, 5.19 Gy] for larynx, and [3.27 Gy, 1.10 Gy] for mandible. R50 and integral dose were reduced by 5.3% and 9.6%, respectively. Wilcoxon signed-rank test showed significant difference (p  < 0.05) in planning target volume (PTV) homogeneity, PTV Dmax, R50, Integral dose, and OAR Dmean and Dmax. The estimated delivery time of 20-beam [SID-50, SID-100] plans were [19, 18] min and [14, 9] min, assuming 5 fractions and 30 fractions, respectively. With clinically acceptable delivery efficiency, many-isocenter optimization is dosimetrically desirable for treating large targets with high modulation resolution on the robotic platform.

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. The proposed MMD was formulated as an optimization problem including a quadratic data fidelity term, an isotropic total variation term that encourages image smoothness, and a nonconvex penalty function that promotes decomposition image sparseness. The mass and volume conservation rule was formulated as the probability simplex constraint. An accelerated primal-dual splitting approach with line search was applied to solve the optimization problem. The proposed method with different penalty functions was compared against DI on a digital phantom, a Catphan® 600 phantom, a quantitative imaging phantom, and a pelvis patient. The proposed framework distinctly separated the CT image up to 12 basis materials plus air with high decomposition accuracy. The cross talks between two different materials are substantially reduced, as shown by the decreased nondiagonal elements of the normalized cross correlation (NCC) matrix. The mean square error of the measured electron densities was reduced by 72.6%. Across all datasets, the proposed method improved the average volume fraction accuracy from 61.2% to 99.9% and increased the diagonality of the NCC matrix from 0.73 to 0.96. Compared with DI, the proposed MMD framework improved decomposition accuracy and material separation.

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. Direct aperture optimization (DAO) for single-arc DLMLC VMAT was formulated as a least square dose fidelity objective, along with an anisotropic total variation term to regulate the fluence smoothness and a single segment term for forming simple apertures. The DAO was solved through alternating optimization approach. The DLMLC deliverability constraint and the MLC leaf speed constraint were formulated as the optimization constraints and solved using a graph optimization algorithm. Feasibility of the proposed framework was tested on a brain, a lung, and a prostate cancer patient. The framework was further adapted for a simultaneous integrated boost (SIB) case. The single-arc DLMLC-10 mm (leaf width) plan was compared against single-arc SLMLC VMAT plans including SLMLC-5mm, SLMLC-10mm, and SLMLC with 10 mm leaf width and 5 mm leaf step size (SLMLC-10mm-5mm). Compared with the SLMLC-10mm plan and the SLMLC-10mm-5mm plan, with the same target coverage, the DLMLC-10 mm plan reduced R50 by 30.7% and 10.0%, the average max OAR dose by 5.79% and 3.7% of the prescription dose, and the average mean OAR dose by 4.18% and 2.1% of the prescription dose, respectively. The plan quality is comparable to that of the SLMLC-5mm plan. The novel single-arc VMAT optimization framework for DLMLC utilizes two MLC layers to improve the effective modulation resolution and afford more sophisticated modulation. Consequently, DLMLC VMAT achieves superior dosimetry to SLMLC VMAT with the same leaf width.

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. The vas deferens releases secretions into the lumen directly, probably by means of merocrine production. On the contrary, the cells of the postvesicular vas deferens correspond to class I glandular cells, discharging secretions into the subcuticular cavity first, and then into the lumen through an inner cuticle. The epithelium in both structures of Bittacidae is well developed and contains more microvilli, organelles, and more types of secretions than in Panorpidae. In Panorpidae, the spine of the postvesicular vas deferens may serve as a barricade for the reflow of the sperm and to protect the extraordinarily long structure from being collapsed or injured.

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. Continuous gantry/couch angle trajectories were selected using the Dijkstra's algorithm, where the edge and node costs were determined based on the maximal gantry rotation speed and the estimated fluence map at the current iteration, respectively. The couch-gantry-patient collision space was calculated based on actual machine geometry and a human subject 3D surface. Beams leading to collision are excluded from the DAO and beam trajectory selection (BTS). An alternating optimization strategy was implemented to solve the integrated DAO and BTS problem. The feasibility of 4πVMAT using one full-arc or two full-arcs was tested on nine patients with brain, lung, or prostate cancer. The plan was compared against a coplanar VMAT (2πVMAT) plan using one additional arc and collimator rotation. Compared to 2πVMAT, 4πVMAT reduced the average maximum and mean organs-at-risk dose by 9.63% and 3.08% of the prescription dose with the same target coverage. R50 was reduced by 23.0%. Maximum doses to the dose limiting organs, such as the brainstem, the major vessels, and the proximal bronchus, were reduced by 8.1 Gy (64.8%), 16.3 Gy (41.5%), and 19.83 Gy (55.5%), respectively. The novel 4πVMAT approach affords efficient delivery of non-coplanar arc trajectories that lead to dosimetric improvements compared with coplanar VMAT using more arcs.

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. METHODS: The iterative reconstruction was achieved by adding to the existing least square data fidelity objective a regularization term, formulated as the L1 norm of the BM3D transformed image. A Fast Iterative Shrinkage-Thresholding Algorithm (FISTA) was adopted to accelerate CT reconstruction. The proposed method was compared against total variation (TV) regularization, BM3D postprocess method, and filtered back projection (FBP). RESULTS: In the Catphan phantom study, BM3D regularization better enhances low-contrast objects compared with TV regularization and BM3D postprocess method at the same noise level. The spatial resolution using BM3D regularization is 2.79 and 2.55 times higher than that using the TV regularization at 50% of the modulation transfer function (MTF) magnitude, for the fully sampled reconstruction and down-sampled reconstruction, respectively. The BM3D regularization images show better bony details and low-contrast soft tissues, on the head and neck (H&N) and prostate patient images. CONCLUSIONS: The proposed iterative BM3D regularization CT reconstruction method takes advantage of both the BM3D denoising capability and iterative reconstruction data fidelity consistency. This novel approach is superior to TV regularized iterative reconstruction or BM3D postprocess for improving noisy MVCT image quality.

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. The optimal collimator angle for each beam angle was selected using the Dijkstra's algorithm, where the node costs depend on the estimated fluence map at the current iteration and the edge costs account for the mechanical constraints of multi-leaf collimator (MLC). An alternating optimization strategy was implemented to solve the DAO and collimator angle selection (CAS). Feasibility of DC-VMAT using one full-arc with dynamic collimator rotation was tested on a phantom with two small spherical targets, a brain, a lung and a prostate cancer patient. The plan was compared against a static collimator VMAT (SC-VMAT) plan using three full arcs with 60 degrees of collimator angle separation in patient studies. RESULTS: With the same target coverage, DC-VMAT achieved 20.3% reduction of R50 in the phantom study, and reduced the average max and mean OAR dose by 4.49% and 2.53% of the prescription dose in patient studies, as compared with SC-VMAT. The collimator rotation co-ordinated with the gantry rotation in DC-VMAT plans for deliverability. There were 13 beam angles in the single-arc DC-VMAT plan in patient studies that requires slower gantry rotation to accommodate multiple collimator angles. CONCLUSIONS: The novel DC-VMAT approach utilizes the dynamic collimator rotation during arc delivery. In doing so, DC-VMAT affords more sophisticated intensity modulation, alleviating the limitation previously imposed by the square beamlet from the MLC leaf thickness and achieves higher effective modulation resolution. Consequently, DC-VMAT with a single arc manages to achieve superior dosimetry than SC-VMAT with three full arcs.

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. The seminal vesicle is composed of layers of developed muscles and a mono-layered epithelium surrounding the small central lumen. The epithelium is rich in rough endoplasmic reticulum and mitochondria, and secretes vesicles and granules into the central lumen by merocrine mechanisms. A pair of elongate mesodermal accessory glands opens into the lateral side of the seminal vesicles. The accessory glands are similar to the seminal vesicle in structure, also consisting of layers of muscle fibres and a mono-layered elongated epithelium, the cells of which contain numerous cisterns of rough endoplasmic reticulum and mitochondria, and a few Golgi complexes. The epithelial cells of accessory glands extrude secretions via apocrine and merocrine processes. The seminal vesicles mainly serve the function of secretion rather than temporarily storing spermatozoa. The sperm instead are temporarily stored in the epididymis, the greatly coiled distal portion of the vas deferens.