Mercury (Hg) concentration in fish commercialized in the São Luís fish market (MA) and potential exposure of consumers.

Fish consumption is the main path of human exposure to Hg and may represent a risk to public health, even with low Hg concentrations in fish, if consumption rates are high. This study quantifies, for the first time, the Hg concentrations in nine most commercialized species in the São Luís (MA) fish market, where fish consumption is high, and estimates human exposure. Average Hg concentrations were highest in carnivorous species, yellow hake (Cynoscion acoupa) (0.296 mg kg-1), the Atlantic croaker (Micropogonias undulatus) (0.263 mg kg-1), whereas lowest concentrations were recorded in iliophagous Mullets (Mugil curema) (0.021 mg kg-1) and the Shorthead drum Larimus breviceps (0.025 mg kg-1). Significant correlations were observed between Hg concentrations and fish length in two species: the Coco-Sea catfish (Bagre bagre) and the Atlantic bumper (Chloroscombrus crysurus), but not in the other species, since they presented relatively uniform size of individuals and/or a small number of samples. Risk coefficients, despite the relatively low Hg concentrations, suggest that consumers should limit their consumption of Yellow hake and Atlantic croaker, as they can present some risk to human health (EDI > RfD and THQ > 1), depending on the frequency of their consumption and the consumer's body weight.

Thermoluminescent dosimeters (TLD-100) for absorbed dose measurements in alpha-emitting radionuclides.

Early works that used thermoluminescent dosimeters (TLDs) to measure absorbed dose from alpha particles reported relatively high variation (10%) between TLDs, which is undesirable for modern dosimetry applications. This work outlines a method to increase precision for absorbed dose measured using TLDs with alpha-emitting radionuclides by applying an alpha-specific chip factor (CF) that individually characterizes the TLD sensitivity to alpha particles. Variation between TLDs was reduced from 21.8% to 6.7% for the standard TLD chips and 7.9% to 3.3% for the thin TLD chips. It has been demonstrated by this work that TLD-100 can be calibrated to precisely measure the absorbed dose to water from alpha-emitting radionuclides.

Robotic-Assisted Total Knee Arthroplasty in Obese Patients.

Background: Robotic-assisted systems have gained popularity in total knee arthroplasty (TKA). The purpose of this study was to evaluate operative characteristics and radiographic outcomes of obese patients undergoing robotic-assisted TKA. Methods: A retrospective review of consecutive cases performed by a single surgeon was performed from January 1, 2016, to January 31, 2022. Adult patients with body mass index ≥35 kg/m2 who underwent primary TKA using a computed tomography-assisted robotic system were compared to patients who underwent primary TKA using conventional instrumentation. Demographics, preoperative and postoperative radiographic measurements, and intraoperative outcomes were compared between cohorts. In total, 119 patients were identified, 60 in the robotic-assisted cohort and 59 in the conventional instrumentation cohort. Results: Age, body mass index, and estimated blood loss were not significantly different between the cohorts. The robotic-assisted cohort experienced longer tourniquet times (93.3 vs 75.5 minutes, P < .001). Preoperative hip-knee-ankle angle (HKA) was similar between the robotic-assisted and conventional cohorts (8.4° ± 4.9° vs 9.3° ± 5.3°, P = .335). Postoperative HKA was 2.0° ± 1.4° in the robotic-assisted group and 3.1° ± 3.23° in the conventional group (P = .040). The proportion of patients with postoperative HKA > 3° of varus or valgus was 9 of 60 (15.0%) in the robotic-assisted cohort compared to 18 of 59 (30.5%) using conventional instrumentation (P = .043). Conclusions: Obese patients treated with robotic-assisted TKA had postoperative alignment closer to neutral and fewer postoperative radiographic outliers than patients treated with conventional instrumentation. The results of this study support use of robotic-assisted technologies in TKA, particularly in obese patients.

Optimizing the enzymatic production of biolubricants by the Taguchi method: Esterification of the free fatty acids from castor oil with 2-ethyl-1-hexanol catalyzed by Eversa Transform 2.0.

The solvent-free esterification of the free fatty acids (FFAs) obtained by the hydrolysis of castor oil (a non-edible vegetable oil) with 2-ethyl-1-hexanol (a branched fatty alcohol) was catalyzed by different free lipases. Eversa Transform 2.0 (ETL) features surpassed most commercial lipases. Some process parameters were optimized by the Taguchi method (L16'). As a result, a conversion over 95% of the FFAs of castor oil into esters with lubricants properties was achieved under optimized reaction conditions (15 wt% of biocatalyst content, 1:4 molar ratio (FFAs/alcohol), 30 °C, 180 rpm, 96 h). The substrates molar ratio had the highest influence on the dependent variable (conversion at 24 h). FFAs/2-ethyl-1-hexanol esters were characterized regarding the physicochemical and tribological properties. Interestingly, the modification of the FFAs with 2-ethyl-1-hexanol by ETL increased the oxidative stability of the FFAs feedstock from 0.18 h to 16.83 h. The biolubricants presented a lower friction coefficient than the reference commercial mineral lubricant (0.052 ± 0.07 against 0.078 ± 0.04). Under these conditions, ETL catalyzed the oligomerization of ricinoleic acid (a hydroxyl fatty acid) into estolides, reaching a conversion of 25.15% of the initial FFAs (for the first time).

Integrative genotyping of cancer and immune phenotypes by long-read sequencing.

Single-cell transcriptomics has become the definitive method for classifying cell types and states, and can be augmented with genotype information to improve cell lineage identification. Due to constraints of short-read sequencing, current methods to detect natural genetic barcodes often require cumbersome primer panels and early commitment to targets. Here we devise a flexible long-read sequencing workflow and analysis pipeline, termed nanoranger, that starts from intermediate single-cell cDNA libraries to detect cell lineage-defining features, including single-nucleotide variants, fusion genes, isoforms, sequences of chimeric antigen and TCRs. Through systematic analysis of these classes of natural 'barcodes', we define the optimal targets for nanoranger, namely those loci close to the 5' end of highly expressed genes with transcript lengths shorter than 4 kB. As proof-of-concept, we apply nanoranger to longitudinal tracking of subclones of acute myeloid leukemia (AML) and describe the heterogeneous isoform landscape of thousands of marrow-infiltrating immune cells. We propose that enhanced cellular genotyping using nanoranger can improve the tracking of single-cell tumor and immune cell co-evolution.

Non-contact scintillator imaging dosimetry for total body irradiation in radiotherapy.

Objective.The goal of this work was to assess the potential use of non-contact scintillator imaging dosimetry for tracking delivery in total body irradiation (TBI).Approach. Studies were conducted to measure the time-gated light signals caused by radiation exposure to scintillators that were placed on tissue. The purpose was to assess efficacy in conditions common for TBI, such as the large source to surface distance (SSD) commonly used, the reduced dose rate, the inclusion of a plexiglass spoiler, angle of incidence and effects of peripheral patient support structures. Dose validation work was performed on phantoms that mimicked human tissue optical properties and body geometry. For this work, 1.5 cm diameter scintillating disks were developed and affixed to phantoms under various conditions. A time-gated camera synchronized to the linac pulses was used for imaging. Scintillation intensity was quantified in post processing and the values verified with simultaneous thermolumiescent dosimeter (TLD) measurements. Mean scintillation values in each region were compared to TLD measurements to produce dose response curves, and scatter effects from the spoiler and patient bed were quantified.Main results.The dose determined by scintillators placed in TBI conditions agreed with TLD dose determinations to within 2.7%, and did so repeatedly within 1.0% standard deviation variance. A linear fit between scintillator signal and TLD dose was achieved with anR2= 0.996 across several body sites. Scatter from the patient bed resulted in a maximum increase of 19% in dose.Significance.This work suggests that non-contact scintillator imaging dosimetry could be used to verify dose in real time to patients undergoing TBI at the prescribed long SSD and low dose rate. It also has shown that patient transport stretchers can significantly influence surface dose by increasing scatter.

Preclinical Models of Anal Cancer Combined-Modality Therapy.

INTRODUCTION: There have been no significant changes in anal cancer treatment options in 4 decades. In this study, we highlight two preclinical models designed to assess anal cancer treatments. MATERIALS AND METHODS: Transgenic K14E6/E7 mice were treated with 7, 12-dimethylbenz(a)anthracene until anal tumors developed. Mice were treated with localized radiation in addition to chemotherapy (combined-modality therapy [CMT]) and compared to no treatment control (NTC). K14E6/E7 mouse anal spheroids with and without Pik3ca mutations were isolated and treated with vehicle, LY3023414 (LY3) (a drug previously shown to be effective in cancer prevention), CMT, or CMT + LY3. RESULTS: In the in vivo model, there was a significant increase in survival in the CMT group compared to the NTC group (P = 0.0392). In the ex vivo model, there was a significant decrease in the mean diameter of CMT and CMT + LY3-treated spheroids compared to vehicle (P ≤ 0.0001). For LY3 alone compared to vehicle, there was a statistically significant decrease in spheroid size in the K14E6/E7 group without mutation (P = 0.0004). CONCLUSIONS: We have provided proof of concept for two preclinical anal cancer treatment models that allow for the future testing of novel therapies for anal cancer.

Leucine Supplementation Exacerbates Morbidity in Male but Not Female Mice with Colorectal Cancer-Induced Cachexia.

Cancer cachexia (CC) is a multifactorial wasting syndrome characterized by a significant loss in lean and/or fat mass and represents a leading cause of mortality in cancer patients. Nutraceutical treatments have been proposed as a potential treatment strategy to mitigate cachexia-induced muscle wasting. However, contradictory findings warrant further investigation. The purpose of this study was to determine the effects of leucine supplementation on skeletal muscle in male and female ApcMin/+ mice (APC). APC mice and their wild-type (WT) littermates were given normal drinking water or 1.5% leucine-supplemented water (n = 4-10/group/sex). We measured the gene expression of regulators of inflammation, protein balance, and myogenesis. Leucine treatment lowered survival rates, body mass, and muscle mass in males, while in females, it had no effect on body or muscle mass. Leucine treatment altered inflammatory gene expression by lowering Il1b 87% in the APC group and decreasing Tnfa 92% in both WT and APC males, while it had no effect in females (p < 0.05). Leucine had no effect on regulators of protein balance and myogenesis in either sex. We demonstrated that leucine exacerbates moribundity in males and is not sufficient for mitigating muscle or fat loss during CC in either sex in the ApcMin/+ mouse.

Integration and dosimetric validation of a dynamic collimation system for pencil beam scanning proton therapy.

Objective.To integrate a Dynamic Collimation System (DCS) into a pencil beam scanning (PBS) proton therapy system and validate its dosimetric impact.Approach.Uncollimated and collimated treatment fields were developed for clinically relevant targets using an in-house treatment plan optimizer and an experimentally validated Monte Carlo model of the DCS and IBA dedicated nozzle (DN) system. The dose reduction induced by the DCS was quantified by calculating the mean dose in 10- and 30-mm two-dimensional rinds surrounding the target. A select number of plans were then used to experimentally validate the mechanical integration of the DCS and beam scanning controller system through measurements with the MatriXX-PT ionization chamber array and EBT3 film. Absolute doses were verified at the central axis at various depths using the IBA MatriXX-PT and PPC05 ionization chamber.Main results.Simulations demonstrated a maximum mean dose reduction of 12% for the 10 mm rind region and 45% for the 30 mm rind region when utilizing the DCS. Excellent agreement was observed between Monte Carlo simulations, EBT3 film, and MatriXX-PT measurements, with gamma pass rates exceeding 94.9% for all tested plans at the 3%/2 mm criterion. Absolute central axis doses showed an average verification difference of 1.4% between Monte Carlo and MatriXX-PT/PPC05 measurements.Significance.We have successfully dosimetrically validated the delivery of dynamically collimated proton therapy for clinically relevant delivery patterns and dose distributions with the DCS. Monte Carlo simulations were employed to assess dose reductions and treatment planning considerations associated with the DCS.

Standardization and Visualization of the Surgical Time-Out.

INTRODUCTION: The time-out (TO) can prevent adverse events but is subject to TO engagement. We hypothesize transforming the TO to an auditable, active process will improve compliance and engagement. METHODS: The passive nature of the current TO was identified as a potential safety issue on staff patient safety culture surveys. Subsequently, the Time Out Engagement and Standardization quality improvement initiative was developed and included a whiteboard checklist to be used in the operating room. As a baseline, 11 TOs were audited concerning engagement and content. Key stakeholders were engaged to determine potential interventions. A TO consisting of 15 elements using a TO whiteboard checklist with role-specific objectives was developed. Plan, Do, Study, Act cycles commenced. After implementation, 17 TOs were audited based on engagement and content. RESULTS: Before intervention, engagement varied with nurse participating in 100% compared with anesthesia provider or surgeon participating in 18%. No TO included all 15 elements and only 13% of elements included in all TOs. After implementation of Time Out Engagement and Standardization, anesthesia and surgeon who participated increased to 100% and 76.5%, respectively (P < 0.0001, P = 0.006). The 15 standardized elements of the TO were discussed in 90% of cases. Overall, preintervention 88 elements (57.1%) were completed across all TOs, while postintervention 243 elements (98.8%) were completed (P < 0.001). CONCLUSIONS: We identified a need for increased engagement of the TO based on staff concerns, which were verified through auditing. Implementation of a team-driven intervention and 3 rapid Plan, Do, Study, Act cycles led to measurable improvement of the surgical TO.

Improving physician documentation for malnutrition: A sustainable quality improvement initiative.

This study compares documentation and reimbursement rates before and after provider education in nutritional status documentation. Our study aimed to evaluate accurate documentation of nutrition status between registered dietitian nutritionists and licensed independent practitioners before and after the implementation of a dietitian-led Nutrition-Focused Physical Exam intervention at an academic medical center in the southeastern US. ICD-10 codes identified patients from 10/1/2016-1/31/2018 with malnutrition. The percentage of patients with an appropriate diagnosis of malnutrition and reimbursement outcomes attributed to malnutrition documentation were calculated up to 24 months post-intervention. 528 patients were analyzed. Pre-intervention, 8.64% of patients had accurate documentation compared to 46.3% post-intervention. Post-intervention, 68 encounters coded for malnutrition resulted in an estimated $571,281 of additional reimbursement, sustained at 6, 12, 18, and 24 months. A multidisciplinary intervention improved physician documentation accuracy of malnutrition status and increased reimbursement rates.

Simultaneous photon counting and charge integrating for pulse pile-up correction in paralyzable photon counting detectors.

Objective.In photon counting detectors (PCDs), electric pulses induced by two or more x-ray photons can pile up and result in count losses when their temporal separation is less than the detector dead time. The correction of pulse pile-up-induced count loss is particularly difficult for paralyzable PCDs since a given value of recorded counts can correspond to two different values of true photon interactions. In contrast, charge (energy) integrating detectors work by integrating collected electric charge induced by x-rays over time and do not suffer from pile-up losses. This work introduces an inexpensive readout circuit element to the circuits of PCDs to simultaneously collect time-integrated charge to correct pile-up-induced count losses.Approach.Prototype electronics were constructed to collect time-integrated charges simultaneously with photon counts. A splitter was used to feed the electric signal in parallel to both a digital counter and a charge integrator. After recording PCD counts and integrating collected charge, a lookup table can be generated to map raw counts in the total- and high-energy bins and total charge to estimate pile-up-free true counts. Proof-of-concept imaging experiments were performed with a CdTe-based PCD array to test this method.Main results.The proposed electronics successfully recorded photon counts and time-integrated charge simultaneously, and whereas photon counts exhibited paralyzable pulse pile-up, time-integrated charge using the same electric signal as the counts measurement was linear with x-ray flux. With the proposed correction, paralyzable PCD counts became linear with input flux for both total- and high-energy bins. At high flux levels, uncorrected post-log measurements of PMMA objects severely overestimated radiological path lengths for both energy bins. After the proposed correction, the non-monotonic measurements again became linear with flux and accurately represented the true radiological path lengths. No impact on the spatial resolution was observed after the proposed correction in images of a line-pair test pattern.Significance.Time-integrated charge can be used to correct for pulse pile-up in paralyzable PCDs where analytical solutions may be difficult to use, and integrated charge can be collected simultaneously with counts using inexpensive electronics.

PETRA: A pencil beam trimming algorithm for analytical proton therapy dose calculations with the dynamic collimation system.

BACKGROUND: The Dynamic Collimation System (DCS) has been shown to produce superior treatment plans to uncollimated pencil beam scanning (PBS) proton therapy using an in-house treatment planning system (TPS) designed for research. Clinical implementation of the DCS requires the development and benchmarking of a rigorous dose calculation algorithm that accounts for pencil beam trimming, performs monitor unit calculations to produce deliverable plans at all beam energies, and is ideally implemented with a commercially available TPS. PURPOSE: To present an analytical Pencil bEam TRimming Algorithm (PETRA) for the DCS, with and without its range shifter, implemented in the Astroid TPS (.decimal, Sanford, Florida, USA). MATERIALS: PETRA was derived by generalizing an existing pencil beam dose calculation model to account for the DCS-specific effects of lateral penumbra blurring due to the nickel trimmers in two different planes, integral depth dose variation due to the trimming process, and the presence and absence of the range shifter. Tuning parameters were introduced to enable agreement between PETRA and a measurement-validated Dynamic Collimation Monte Carlo (DCMC) model of the Miami Cancer Institute's IBA Proteus Plus system equipped with the DCS. Trimmer position, spot position, beam energy, and the presence or absence of a range shifter were all used as variables for the characterization of the model. The model was calibrated for pencil beam monitor unit calculations using procedures specified by International Atomic Energy Agency Technical Report Series 398 (IAEA TRS-398). RESULTS: The integral depth dose curves (IDDs) for energies between 70 MeV and 160 MeV among all simulated trimmer combinations, with and without the ranger shifter, agreed between PETRA and DCMC at the 1%/1 mm 1-D gamma criteria for 99.99% of points. For lateral dose profiles, the median 2-D gamma pass rate for all profiles at 1.5%/1.5 mm was 99.99% at the water phantom surface, plateau, and Bragg peak depths without the range shifter and at the surface and Bragg peak depths with the range shifter. The minimum 1.5%/1.5 mm gamma pass rates for the 2-D profiles at the water phantom surface without and with the range shifter were 98.02% and 97.91%, respectively, and, at the Bragg peak, the minimum pass rates were 97.80% and 97.5%, respectively. CONCLUSION: The PETRA model for DCS dose calculations was successfully defined and benchmarked for use in a commercially available TPS.

Procedure-Based Telehealth Utilization in General Surgery.

The authors hypothesize that standardized telehealth (TH) scheduling processes will improve TH utilization without increasing adverse events. Fifty visits preimplementation and 67 visits postimplementation were audited from June 2021 to January 2022. Both leadership and frontline stakeholders were engaged to identify current workflows and potential interventions targeting outpatient elective procedures. Process mapping outlined current TH scheduling workflows. Outcomes related to TH completion, cost, and TH scheduling were collected after implementation. Preimplementation TH scheduling rate was 32%. The intervention required TH postoperative appointments to be scheduled in clinic at the time of surgery scheduling with TH being the default postsurgical appointment for a standardized list of eligible procedures. Following implementation, 95% of patients undergoing eligible procedures had TH follow-up. This provided improved access to surgical follow-up care, by reducing travel needs to the Veterans Affairs facility. Secondarily, this intervention increased clinic appointment availability and resulted in possible increased revenue for billable visits. Standardizing TH scheduling based on the procedure improves the utilization of TH resulting in improved clinic efficiency and increased revenue, without increasing adverse events.

Development of skeletal muscle fibrosis in a rodent model of cancer cachexia.

Cachexia is characterized by losses in lean body mass and its progression results in worsened quality of life and exacerbated outcomes in cancer patients. However, the role and impact of fibrosis during the early stages and development of cachexia in under-investigated. The purpose of this study was to determine if fibrosis occurs during cachexia development, and to evaluate this in both sexes. Female and male C57BL6/J mice were injected with phosphate-buffered saline or Lewis Lung Carcinoma (LLC) at 8-week of age, and tumors were allowed to develop for 1, 2, 3, or 4 weeks. 3wk and 4wk female tumor-bearing mice displayed a dichotomy in tumor growth and were reassigned to high tumor (HT) and low tumor (LT) groups. In vitro analyses were also performed on cocultured C2C12 and 3T3 cells exposed to LLC conditioned media. Immunohistochemistry and quantitative polymerase chain reaction (qPCR) analysis were used to investigate fibrosis and fibrosis-related signaling in skeletal muscle. Collagen deposition in skeletal muscle was increased in the 1wk, LT, and HT groups in female mice. However, collagen deposition was only increased in the 4wk group in male mice. In general, female mice displayed earlier alterations in extracellular matrix (ECM)-related genes beginning at 1wk post-LLC injection. Whereas this was not seen in males. While overall tumor burden is tightly correlated to cachexia development in both sexes, fibrotic development is not. Male mice did not exhibit early-stage alterations in ECM-related genes contrary to what was noted in female mice.

An illustration of model agnostic explainability methods applied to environmental data.

Historically, two primary criticisms statisticians have of machine learning and deep neural models is their lack of uncertainty quantification and the inability to do inference (i.e., to explain what inputs are important). Explainable AI has developed in the last few years as a sub-discipline of computer science and machine learning to mitigate these concerns (as well as concerns of fairness and transparency in deep modeling). In this article, our focus is on explaining which inputs are important in models for predicting environmental data. In particular, we focus on three general methods for explainability that are model agnostic and thus applicable across a breadth of models without internal explainability: "feature shuffling", "interpretable local surrogates", and "occlusion analysis". We describe particular implementations of each of these and illustrate their use with a variety of models, all applied to the problem of long-lead forecasting monthly soil moisture in the North American corn belt given sea surface temperature anomalies in the Pacific Ocean.

Next-generation RNA sequencing elucidates transcriptomic signatures of pathophysiologic nerve regeneration.

The cellular and molecular underpinnings of Wallerian degeneration have been robustly explored in laboratory models of successful nerve regeneration. In contrast, there is limited interrogation of failed regeneration, which is the challenge facing clinical practice. Specifically, we lack insight on the pathophysiologic mechanisms that lead to the formation of neuromas-in-continuity (NIC). To address this knowledge gap, we have developed and validated a novel basic science model of rapid-stretch nerve injury, which provides a biofidelic injury with NIC development and incomplete neurologic recovery. In this study, we applied next-generation RNA sequencing to elucidate the temporal transcriptional landscape of pathophysiologic nerve regeneration. To corroborate genetic analysis, nerves were subject to immunofluorescent staining for transcripts representative of the prominent biological pathways identified. Pathophysiologic nerve regeneration produces substantially altered genetic profiles both temporally and in the mature neuroma microenvironment, in contrast to the coordinated genetic signatures of Wallerian degeneration and successful regeneration. To our knowledge, this study presents as the first transcriptional study of NIC pathophysiology and has identified cellular death, fibrosis, neurodegeneration, metabolism, and unresolved inflammatory signatures that diverge from pathways elaborated by traditional models of successful nerve regeneration.

Artificial intelligence evaluation of focused assessment with sonography in trauma.

BACKGROUND: The focused assessment with sonography in trauma (FAST) is a widely used imaging modality to identify the location of life-threatening hemorrhage in a hemodynamically unstable trauma patient. This study evaluates the role of artificial intelligence in interpretation of the FAST examination abdominal views, as it pertains to adequacy of the view and accuracy of fluid survey positivity. METHODS: Focused assessment with sonography for trauma examination images from 2015 to 2022, from trauma activations, were acquired from a quaternary care level 1 trauma center with more than 3,500 adult trauma evaluations, annually. Images pertaining to the right upper quadrant and left upper quadrant views were obtained and read by a surgeon or radiologist. Positivity was defined as fluid present in the hepatorenal or splenorenal fossa, while adequacy was defined by the presence of both the liver and kidney or the spleen and kidney for the right upper quadrant or left upper quadrant views, respectively. Four convolutional neural network architecture models (DenseNet121, InceptionV3, ResNet50, Vgg11bn) were evaluated. RESULTS: A total of 6,608 images, representing 109 cases were included for analysis within the "adequate" and "positive" data sets. The models relayed 88.7% accuracy, 83.3% sensitivity, and 93.6% specificity for the adequate test cohort, while the positive cohort conferred 98.0% accuracy, 89.6% sensitivity, and 100.0% specificity against similar models. Augmentation improved the accuracy and sensitivity of the positive models to 95.1% accurate and 94.0% sensitive. DenseNet121 demonstrated the best accuracy across tasks. CONCLUSION: Artificial intelligence can detect positivity and adequacy of FAST examinations with 94% and 97% accuracy, aiding in the standardization of care delivery with minimal expert clinician input. Artificial intelligence is a feasible modality to improve patient care imaging interpretation accuracy and should be pursued as a point-of-care clinical decision-making tool. LEVEL OF EVIDENCE: Diagnostic Test/Criteria; Level III.

A dependent Bayesian Dirichlet process model for source apportionment of particle number size distribution.

The relationship between particle exposure and health risks has been well established in recent years. Particulate matter (PM) is made up of different components coming from several sources, which might have different level of toxicity. Hence, identifying these sources is an important task in order to implement effective policies to improve air quality and population health. The problem of identifying sources of particulate pollution has already been studied in the literature. However, current methods require an a priori specification of the number of sources and do not include information on covariates in the source allocations. Here, we propose a novel Bayesian nonparametric approach to overcome these limitations. In particular, we model source contribution using a Dirichlet process as a prior for source profiles, which allows us to estimate the number of components that contribute to particle concentration rather than fixing this number beforehand. To better characterize them we also include meteorological variables (wind speed and direction) as covariates within the allocation process via a flexible Gaussian kernel. We apply the model to apportion particle number size distribution measured near London Gatwick Airport (UK) in 2019. When analyzing this data, we are able to identify the most common PM sources, as well as new sources that have not been identified with the commonly used methods.

IMRT QA result prediction via MLC transmission decomposition.

BACKGROUND: Quality assurance measurement of IMRT/VMAT treatment plans is resource intensive, and other more efficient methods to achieve the same confidence are desirable. PURPOSE: We aimed to analyze treatment plans in the context of the treatment planning systems that created them, in order to predict which ones will fail a standard quality assurance measurement. To do so, we sought to create a tool external to the treatment planning system that could analyze a set of MLC positions and provide information that could be used to calculate various evaluation metrics. METHODS: The tool was created in Python to read in DICOM plan files and determine the beam fluence fraction incident on each of seven different zones, each classified based on the RayStation MLC model. The fractions, termed grid point fractions, were validated by analyzing simple test plans. The average grid point fractions, over all control points for 46 plans were then computed. These values were then compared with gamma analysis pass percentages and median dose differences to determine if any significant correlations existed. RESULTS: Significant correlation was found between the grid point fraction metrics and median dose differences, but not with gamma analysis pass percentages. Correlations were positive or negative, suggesting differing model parameter value sensitivities, as well as potential insight into the treatment planning system dose model. CONCLUSIONS: By decomposing MLC control points into different transmission zones, it is possible to create a metric that predicts whether the analyzed plan will pass a quality assurance measurement from a dose calculation accuracy standpoint. The tool and metrics developed in this work have potential applications in comparing clinical beam models or identifying their weak points. Implementing the tool within a treatment planning system would also provide more potential plan optimization parameters.