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Background Purpose Methods Results Conclusions Four‐dimensional computed tomography (4DCT) is an es sential tool in radiation therapy. However, the 4D acquisition process may cause motion artifacts which can obscure anatomy and distort functional measurements from CT scans.We describe a deep learning algorithm to identify the location of artifacts within 4DCT images. Our method is flexible enough to handle different types of artifacts, including duplication, misalignment, truncation, and interpolation.We trained and validated a U‐net convolutional neural network artifact detection model on more than 23 000 coronal slices extracted from 98 4DCT scans. The receiver operating characteristic (ROC) curve and precision‐recall curve were used to evaluate the model's performance at identifying artifacts compared to a manually identified ground truth. The model was adjusted so that the sensitivity in identifying artifacts was equivalent to that of a human observer, as measured by computing the average ratio of artifact volume to lung volume in a given scan.The model achieved a sensitivity, specificity, and precision of 0.78, 0.99, and 0.58, respectively. The ROC area‐under‐the‐curve (AUC) was 0.99 and the precision‐recall AUC was 0.73. Our model sensitivity is 8% higher than previously reported state‐of‐the‐art artifact detection methods.The model developed in this study is versatile, designed to handle duplication, misalignment, truncation, and interpolation artifacts within a single image, unlike earlier models that were designed for a single artifact type. [ABSTRACT FROM AUTHOR]

Purpose: To assess the practicality of employing a commercial knowledge‐based planning tool (RapidPlan) to generate adapted intact prostate and prostate bed volumetric modulated arc therapy (VMAT) plans on iterative cone‐beam computed tomography (iCBCT) datasets. Methods and materials: Intact prostate and prostate bed RapidPlan models were trained utilizing planning data from 50 and 44 clinical cases, respectively. To ensure that refined models were capable of producing adequate clinical plans with a single optimization, models were tested with 50 clinical planning CT datasets by comparing dose‐volume histogram (DVH) and plan quality metric (PQM) values between clinical and RapidPlan‐generated plans. The RapidPlan tool was then used to retrospectively generate adapted VMAT plans on daily iCBCT images for 20 intact prostate and 15 prostate bed cases. As before, DVH and PQM metrics were utilized to dosimetrically compare scheduled (iCBCT Verify) and adapted (iCBCT RapidPlan) plans. Timing data was collected to further evaluate the feasibility of integrating this approach within an online adaptive radiotherapy workflow. Results: Model testing results confirmed the models were capable of producing VMAT plans within a single optimization that were overall improved upon or dosimetrically comparable to original clinical plans. Direct application of RapidPlan on iCBCT datasets produced satisfactory intact prostate and prostate bed plans with generally improved target volume coverage/conformality and rectal sparing relative to iCBCT Verify plans as indicated by DVH values, though bladder metrics were marginally increased on average. Average PQM values for iCBCT RapidPlans were significantly improved compared to iCBCT Verify plans. The average time required [in mm:ss] to generate adapted plans was 06:09 ± 02:06 (intact) and 07:12 ± 01:04 (bed). Conclusion: This study demonstrated the feasibility of leveraging RapidPlan to expeditiously generate adapted VMAT intact prostate and prostate bed plans on iCBCT datasets. In general, adapted plans were dosimetrically improved relative to scheduled plans, emphasizing the practicality of the proposed approach. [ABSTRACT FROM AUTHOR]

Australian biodiversity is facing an extinction crisis; yet, government spending on conservation is wholly inadequate. The involvement of local communities in fundraising, direct actions, and habitat restoration is becoming vital in the fate of threatened species. Here, we review the research outputs and impact generated from 22 years of conservation‐driven collaboration between researchers and a local community focused on saving the endangered Mary River turtle (Elusor macrurus). The study found that this collaboration generated a significant body of research that advanced the ecological knowledge of the species and ensured the findings were being applied towards the conservation of the turtle, locally and nationally. While the national listing status of E. macrurus as endangered has not changed over the past 22 years, the knowledge gained about the turtle's biology and its use to better advise development and water resources in the catchment suggests that the species' future is brighter than when it was first discovered in 1994. This review demonstrates the potential of local communities in driving and supporting conservation initiatives and provides a blueprint for scientific endeavours that inform adaptive community conservation programmes for threatened species. [ABSTRACT FROM AUTHOR]

Background: Biomarkers estimating local lung ventilation have been derived from computed tomography (CT) imaging using various image acquisition and post‐processing techniques. CT‐ventilation biomarkers have potential clinical use in functional avoidance radiation therapy (RT), in which RT treatment plans are optimized to reduce dose delivered to highly ventilated lung. Widespread clinical implementation of CT‐ventilation biomarkers necessitates understanding of biomarker repeatability. Performing imaging within a highly controlled experimental design enables quantification of error associated with remaining variables. Purpose: To characterize CT‐ventilation biomarker repeatability and dependence on image acquisition and post‐processing methodology in anesthetized and mechanically ventilated pigs. Methods: Five mechanically ventilated Wisconsin Miniature Swine (WMS) received multiple consecutive four‐dimensional CT (4DCT) and maximum inhale and exhale breath‐hold CT (BH‐CT) scans on five dates to generate CT‐ventilation biomarkers. Breathing maneuvers were controlled with an average tidal volume difference <200 cc. As surrogates for ventilation, multiple local expansion ratios (LERs) were calculated from the acquired CT scans using Jacobian‐based post‐processing techniques. LER2$LER_2$ measured local expansion between an image pair using either inhale and exhale BH‐CT images or two 4DCT breathing phase images. LERN$LER_N$ measured the maximum local expansion across the 4DCT breathing phase images. Breathing maneuver consistency, intra‐ and interday biomarker repeatability, image acquisition and post‐processing technique dependence were quantitatively analyzed. Results: Biomarkers showed strong agreement with voxel‐wise Spearman correlation ρ>0.9$\rho > 0.9$ for intraday repeatability and ρ>0.8$\rho > 0.8$ for all other comparisons, including between image acquisition techniques. Intra‐ and interday repeatability were significantly different (p < 0.01). LER2 and LERN post‐processing did not significantly affect intraday repeatability. Conclusions: 4DCT and BH‐CT ventilation biomarkers derived from consecutive scans show strong agreement in controlled experiments with nonhuman subjects. [ABSTRACT FROM AUTHOR]

Background: Functional lung avoidance radiation therapy (RT) is a technique being investigated to preferentially avoid specific regions of the lung that are predicted to be more susceptible to radiation‐induced damage. Reducing the dose delivered to high functioning regions may reduce the occurrence radiation‐induced lung injuries (RILIs) and toxicities. However, in order to develop effective lung function‐sparing plans, accurate predictions of post‐RT ventilation change are needed to determine which regions of the lung should be spared. Purpose: To predict pulmonary ventilation change following RT for nonsmall cell lung cancer using machine learning. Methods: A conditional generative adversarial network (cGAN) was developed with data from 82 human subjects enrolled in a randomized clinical trial approved by the institution's IRB to predict post‐RT pulmonary ventilation change. The inputs to the network were the pre‐RT pulmonary ventilation map and radiation dose distribution. The loss function was a combination of the binary cross‐entropy loss and an asymmetrical structural similarity index measure (aSSIM) function designed to increase penalization of under‐prediction of ventilation damage. Network performance was evaluated against a previously developed polynomial regression model using a paired sample t‐test for comparison. Evaluation was performed using eight‐fold cross‐validation. Results: From the eight‐fold cross‐validation, we found that relative to the polynomial model, the cGAN model significantly improved predicting regions of ventilation damage following radiotherapy based on true positive rate (TPR), 0.14±0.15 to 0.72±0.21, and Dice similarity coefficient (DSC), 0.19±0.16 to 0.46±0.14, but significantly declined in true negative rate, 0.97±0.05 to 0.62±0.21, and accuracy, 0.79±0.08 to 0.65±0.14. Additionally, the average true positive volume increased from 104±119 cc in the POLY model to 565±332 cc in the cGAN model, and the average false negative volume decreased from 654±361 cc in the POLY model to 193±163 cc in the cGAN model. Conclusions: The proposed cGAN model demonstrated significant improvement in TPR and DSC. The higher sensitivity of the cGAN model can improve the clinical utility of functional lung avoidance RT by identifying larger volumes of functional lung that can be spared and thus decrease the probability of the patient developing RILIs. [ABSTRACT FROM AUTHOR]

The main aims of this work were to assess phylogenetic relationships of the trentepohlialean photobionts in tropical, mainly sterile, lichens collected in Bolivia, to examine their genetic diversity, host specificity, and the impact of habitat factors on the occurrence of Trentepohliales. Based on rbcL marker analysis, we constructed a phylogenetic tree with eight major clades of Trentepohliales, of which seven free‐living species are intermingled with lichenized ones. Our analyses show that the studied photobionts are scattered across the phylogenetic tree and algae from temperate and tropical regions do not form monophyletic groups, except within one clade that seems to be restricted to the tropics. There is no significant occurrence pattern of lichenized Trentepohliaceae on a specific substratum, except Cephaleuros spp. and Phycopeltis spp., which are restricted to leaves, while some clades with lichenized algae may be specialized to tree bark and wood. Moreover, we found two patterns of associations: first, closely related algae can associate with distantly related mycobionts; second, some other trentepohlioid algae associate with selected lineages of fungi (e.g., Arthoniaceae or Graphidaceae). We also found that some lineages of photobionts are even more selective and associate exclusively with one species (e.g., Dichosporidium nigrocinctum, Diorygma antillarum) or closely related lichen‐forming fungi (Herpothallon spp.). Concluding, we found that occurrence of some trentepohlialean photobionts may correlate with the particular type of the mycobiont. [ABSTRACT FROM AUTHOR]

Until recently, the reptile fauna of Christmas Island in the Indian Ocean comprised five endemic species (two skinks, two geckos, and one snake) and one native, non‐endemic skink. Four of these species were common and widespread until at least 1979, but by 2012 had disappeared from the wild. During the years of decline, little research was undertaken to examine why the species were disappearing. Here, we use a retrospective expert elicitation to rank potential factors that contributed to the loss of Christmas Island's reptiles and to assess the likelihood of re‐establishing populations of two species now listed as Extinct in the Wild. We additionally considered why one endemic lizard, the Christmas Island giant gecko (Cyrtodactylus sadleiri), and three introduced lizards remain common. Experts considered that the introduced common wolf snake (Lycodon capucinus) was the most likely cause of decline, as its temporal and spatial spread across the island closely matched patterns of lizard disappearances. An Asian co‐occurrence in recent evolutionary timeframes of the common wolf snake with the Christmas Island giant gecko and three introduced reptiles was the most marked point of difference between the extant and lost lizard species. The demise in less than 20 years of 80% of Christmas Island's native lizard assemblage highlights the vulnerability of island fauna to invading species. [ABSTRACT FROM AUTHOR]

Purpose: To create a dose‐response model that predicts lung ventilation change following radiation therapy, and examine the effects of out‐of‐phase ventilation. Methods: The dose‐response model was built using 27 human subjects who underwent radiation therapy (RT) from an IRB‐approved trial. For each four‐dimensional computed tomography, two ventilation maps were created by calculating the N‐phase local expansion ratio (LERN) using most or all breathing phases and the 2‐phase LER (LER2) using only the end inspiration and end expiration breathing phases. A polynomial regression model was created using the LERN ventilation maps pre‐RT and post‐RT and dose distributions for each subject, and crossvalidated with a leave‐one‐out method. Further validation of the model was performed using 15 additional human subjects using common statistical operating characteristics and gamma pass rates. Results: For voxels receiving 20 Gy or greater, there was a significant increase from 52% to 59% (P = 0.03) in the gamma pass rates of the LERN model predicted post‐RT Jacobian maps to the actual post‐RT Jacobian maps, relative to the LER2 model. Additionally, accuracy significantly increased (P = 0.03) from 68% to 75% using the LERN model, relative to the LER2 model. Conclusions: The LERN model was significantly more accurate than the LER2 model at predicting post‐RT ventilation maps. More accurate post‐RT ventilation maps will aid in producing a higher quality functional avoidance treatment plan, allowing for potentially better normal tissue sparing. [ABSTRACT FROM AUTHOR]

Purpose: Deep tissue abscesses remain a serious cause of morbidity, mortality, and hospital stay despite development of percutaneous drainage and increasing use of perioperative antibiotics. The goal of this study was to examine the feasibility of methylene blue (MB) mediated photodynamic therapy (PDT) for treatment of infected abscesses with intracavity MB delivery, using computed tomography (CT) imaging data from a representative abscess patient population and Monte Carlo simulation of light delivery. Methods: This retrospective study included all adult subjects that received percutaneous abscess drainage between 1 January 2014 and 31 December 2014 at our institution whose abscess was confirmed by abdominal CT imaging less than 1 week preprocedure (n = 358). Of these, 40 subjects were further analyzed with Monte Carlo simulation. Abscess volumes were segmented from CT images, and imported into the Monte Carlo simulation space. Monte Carlo simulations were performed with a single fiber placement for each abscess, with the optical power at which a fluence rate of either 4 or 20 mW/cm2 was achieved for 95% of the abscess wall recorded. Subjects for which a fluence rate of 4 mW/cm2 was attainable in 95% of the abscess wall with a maximum input optical power of 2000 mW were considered eligible for MB‐PDT. Results: 42.5% of subjects would have been eligible for MB‐PDT, with 17.5% attaining the higher threshold of 20 mW/cm2 in 95% of the abscess wall, given a 1% Intralipid concentration within the abscess cavity and the assumed abscess wall optical properties. The mean optical power necessary was 680 ± 580 mW for the 4 mW/cm2 threshold, and 1100 ± 600 mW for the 20 mW/cm2 threshold. Abscess surface area and threshold optical power were correlated (Spearman ρ = 0.73, P = 0.001), with larger abscesses requiring higher optical power. Of the subjects who were not eligible for MB‐PDT, abscess volumes (150 ± 120 vs 62 ± 41 cm3, P = 0.0049) and surface areas (320 ± 200 vs 140 ± 70 cm2, P = 0.0015) tended to be larger than for those who were eligible. There were no significant differences in eligibility, optical power required, or abscess volume or surface area based on abscess location. For all eligible subjects, at the optical power necessary to achieve 4 mW/cm2 in 95% of the abscess wall, 2.5 ± 3.7% (0%–13.2%) of the wall experienced a fluence rate greater than or equal to 400 mW/cm2. At the 20 mW/cm2 threshold, 8.8 ± 11.4% (0%–31.1%) of the wall surpassed this 400 mW/cm2 level. If subjects with greater than 5% of the wall exceeding 400 mW/cm2 are treated as ineligible, overall eligibility becomes 32.5% for the 4 mW/cm2 threshold and 10.0% for the 20 mW/cm2 threshold. Conclusions: Assuming that the subjects analyzed were representative of the overall patient population, over 150 patients that received percutaneous abscess drainage during the study period would have been eligible for MB‐PDT at the time of drainage, with smaller abscesses being more amenable for treatment. This technique could potentially reduce abscess recurrence, duration of drainage catheter placement, and reliance on systemic antibiotics. These results motivate a future Phase 2 clinical trial following successful completion of the ongoing safety study. [ABSTRACT FROM AUTHOR]

Acarospora rhabarbarina Hue, published as a replacement name for the later homonym Lecanora bella Nyl., is an illegitimate superfluous name because Nylander had previously published his own replacement name, L. xanthophana (≡ A. xanthophana (Nyl.) Jatta). Furthermore, Hue, Magnusson and other later authors misapplied the name A. xanthophana to a common South American taxon, which is described here as A. congregata, the epithet referring to the usual arrangement of the apothecia in groups in large areoles. Lecanora ochrophana Nyl., a synonym of A. xanthophana, is lectotypified. The question of conservation of names, including an explanation as to why it is not proposed in this case, is discussed. [ABSTRACT FROM AUTHOR]

This article presents the results of experimental and theoretical studies of the vO&bond;H and vO&bond;D band shapes in the polarized infrared spectra of 3-thiophenic acid crystals measured at room temperature and at 77 K. The line shapes are studied theoretically within the framework of the anharmonic coupling theory, Davydov coupling, Fermi resonance, direct and indirect damping, as well as the selection rule breaking mechanism for forbidden transitions. The adiabatic approximation allowing to separate the high-frequency motion from the slow one of the H-bond bridge is performed for each separate H-bond bridge of the dimer and a strong nonadiabatic correction is introduced via the resonant exchange between the fast-mode excited states of the two moieties. The spectral density is obtained within the linear response theory by Fourier transform of the damped autocorrelation functions. The approach correctly fits the experimental line shape of the hydrogenated compound and predicts satisfactorily the evolution in the line shapes with temperature and the change in the line shape with isotopic substitution. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010 [ABSTRACT FROM AUTHOR]