Dosimetric impacts of beam-hardening filter removal for the CyberKnife system

PurposeEquipment refurbishment was performed to remove the beam-hardening filter (BHF) from the CyberKnife system (CK). This study aimed to confirm the change in the beam characteristics between the conventional CK (present-BHF CK) and CK after the BHF was removed (absent-BHF CK) and evaluate the impact of BHF removal on the beam quality correction factors k_Q.MethodsThe experimental measurements of the beam characteristics of the present- and absent-BHF CKs were compared. The CKs were modeled using Monte Carlo simulations (MCs). The energy fluence spectra were calculated using MCs. Finally, k_Q were estimated by combining the MC results and analytic calculations based on the TRS-398 and TRS-483 approaches.ResultsAll gamma values for percent depth doses and beam profiles between each CK were less than 0.5 following the 3%/1 mm criteria. The percentage differences for tissue-phantom ratios at depths of 20 and 10 cm and percentage depth doses at 10 cm between each CK were −1.20% and −0.97%, respectively. The MC results demonstrated that the photon energy fluence spectrum of the absent-BHF CK was softer than that of the present-BHF CK. The k_Q values for the absent-BHF CK were in agreement within 0.02% with those for the present-BHF CK.ConclusionsThe photon energy fluence spectrum was softened by the removal of BHF. However, no remarkable impact was observed for the measured beam characteristics and k_Q. Therefore, the previous findings of the k_Q values for the present-BHF CK can be directly used for the absent-BHF CK.     

Rapid photogrammetry of morphological traits of free-ranging moths

1. Photogrammetric studies of free-ranging animals are limited to mammals and birds. Recent advances in insect photogrammetry, including 3D imaging, are entirely associated with museum specimens.
2. We present a rapid, simple, accurate, and inexpensive morphometric method targeting thousands of free-ranging insects attracted to light screens using images taken without collecting a specimen or even constraining the individual in any manner. A reference grid printed on the screen is used to calibrate the images for shape and size without prior knowledge of the camera-subject configuration. The method requires only inexpensive, off-the-shelf, consumer equipment, and freely available programming (R statistical language) and image processing (ImageMagick) tools.
3. We demonstrate the efficacy of the method using a dataset of 3675 images of free-ranging hawkmoths (Lepidoptera:Sphingidae) imaged in natural repose on a screen. We show that this method introduces no bias and has a high degree of correspondence with traditional morphometry using collected specimens. We also propose error metrics, which quantify the calibration quality and identify images with poor data.
4. Although this method is particularly suited for the hyperdiverse moth community, which dominates the dynamics of many terrestrial ecosystems, it can be used for other phototropic taxa identifiable on an image to (morpho)-species. It will help in accumulating reliable trait data from hundreds of thousands of individual insects without any expenditure on specimen collection. It is particularly suited for studies which require multi-epoch, multi-locate sampling like investigations into ecosystem stability, climate change, and community assembly.

     

Bunching up the background betters bias in species distribution models

Sets of presence records used to model species’ distributions typically consist of observations collected opportunistically rather than systematically. As a result, sampling probability is geographically uneven, which may confound the model's characterization of the species’ distribution. Modelers frequently address sampling bias by manipulating training data: either subsampling presence data or creating a similar spatial bias in non‐presence background data. We tested a new method, which we call ‘background thickening’, in the latter category. Background thickening entails concentrating background locations around presence locations in proportion to presence location density. We compared background thickening to two established sampling bias correction methods – target group background selection and presence thinning – using simulated data and data from a case study. In the case study, background thickening and presence thinning performed similarly well, both producing better model discrimination than target group background selection, and better model calibration than models without correction. In the simulation, background thickening performed better than presence thinning when the number of simulated presence locations was low, and vice versa. We discuss drawbacks to target group background selection, why background thickening and presence thinning are conservative but robust sampling bias correction methods, and why background thickening is better than presence thinning for small sample sizes. Particularly, background thickening is advantageous for treating sampling bias when data are scarce because it avoids discarding presence records.     

A simple and efficient dispersion correction to the Hartree–Fock theory

One of the most challenging problems in computational chemistry and in drug discovery is the accurate prediction of the binding energy between a ligand and a protein receptor. It is well known that the binding energy calculated with the Hartree–Fock molecular orbital theory (HF) lacks the dispersion interaction energy that significantly affects the accuracy of the total binding energy of a large molecular system. We propose a simple and efficient dispersion energy correction to the HF theory (HF-D_tq). The performance of HF-D_tq was compared with those of several recently proposed dispersion corrected density functional theory methods (DFT-Ds) as to the binding energies of 68 small non-covalent complexes. The overall performance of HF-D_tq was found to be nearly equivalent to that of more sophisticated B3LYP-D₃. HF-D_tq will thus be a useful and powerful method for accurately predicting the binding energy between a ligand and a protein, albeit it is a simple correction procedure based on HF.     

How do species dominating in succession differ from others?

Abstract. Data on succession were collected from 15 seres starting on bare ground in man-made habitats (i.e. sites disturbed by various mining activities, bulldozed sites, ruderal urban sites, the exposed bottom of a destroyed water reservoir, and abandoned fields), all in the western part of the Czech Republic, Central Europe. The period for which the data on succession were available ranged from 12 to 60 yr. 56 species reaching dominance in some period of succession were selected (the criterion being: at least 25 % cover in at least one year in any sere); they were compared for biological and ecological traits with other species participating in the seres (167 species with at least 1 % cover in at least one year in any sere), and with the Central European flora as a whole. Significant differences between the species dominating in succession and others were found for the following traits: life form, life strategy, pollination mode, and ability of lateral spread. Dominant species differed from the regional flora in distribution of life strategies, pollination mode and immigration status. The results suggest that an ‘ideal successional dominant’ is a tall, wind-pollinated plant, often a geophyte capable of intensive lateral spread, requiring high nutrient supply and sufficient site moisture. The set of traits contributing to achieving dominance by a species in human-made habitats includes both features occurring independently of phylogenies (life strategy, pollination mode, plant height, moisture demands) and those which dominant species probably share due to their common ancestors (nutrient demands, capability of extensive lateral spread).     

Evaluation of a cycle-generative adversarial network-based cone-beam CT to synthetic CT conversion algorithm for adaptive radiation therapy

PurposeImage-guided radiation therapy could benefit from implementing adaptive radiation therapy (ART) techniques. A cycle-generative adversarial network (cycle-GAN)-based cone-beam computed tomography (CBCT)-to-synthetic CT (sCT) conversion algorithm was evaluated regarding image quality, image segmentation and dosimetric accuracy for head and neck (H&N), thoracic and pelvic body regions.MethodsUsing a cycle-GAN, three body site-specific models were priorly trained with independent paired CT and CBCT datasets of a kV imaging system (XVI, Elekta). sCT were generated based on first-fraction CBCT for 15 patients of each body region. Mean errors (ME) and mean absolute errors (MAE) were analyzed for the sCT. On the sCT, manually delineated structures were compared to deformed structures from the planning CT (pCT) and evaluated with standard segmentation metrics. Treatment plans were recalculated on sCT. A comparison of clinically relevant dose-volume parameters (D₉₈, D₅₀ and D₂ of the target volume) and 3D-gamma (3%/3mm) analysis were performed.ResultsThe mean ME and MAE were 1.4, 29.6, 5.4 Hounsfield units (HU) and 77.2, 94.2, 41.8 HU for H&N, thoracic and pelvic region, respectively. Dice similarity coefficients varied between 66.7 ± 8.3% (seminal vesicles) and 94.9 ± 2.0% (lungs). Maximum mean surface distances were 6.3 mm (heart), followed by 3.5 mm (brainstem). The mean dosimetric differences of the target volumes did not exceed 1.7%. Mean 3D gamma pass rates greater than 97.8% were achieved in all cases.ConclusionsThe presented method generates sCT images with a quality close to pCT and yielded clinically acceptable dosimetric deviations. Thus, an important prerequisite towards clinical implementation of CBCT-based ART is fulfilled.