Machine learning-based estimation of patient body weight from radiation dose metrics in computed tomography.

PURPOSE: Currently, precise patient body weight (BW) at the time of diagnostic imaging cannot always be used for radiation dose management. Various methods have been explored to address this issue, including the application of deep learning to medical imaging and BW estimation using scan parameters. This study develops and evaluates machine learning-based BW prediction models using 11 features related to radiation dose obtained from computed tomography (CT) scans. METHODS: A dataset was obtained from 3996 patients who underwent positron emission tomography CT scans, and training and test sets were established. Dose metrics and descriptive data were automatically calculated from the CT images or obtained from Digital Imaging and Communications in Medicine metadata. Seven machine-learning models and three simple regression models were employed to predict BW using features such as effective diameter (ED), water equivalent diameter (WED), and mean milliampere-seconds. The mean absolute error (MAE) and correlation coefficient between the estimated BW and the actual BW obtained from each BW prediction model were calculated. RESULTS: Our results found that the highest accuracy was obtained using a light gradient-boosting machine model, which had an MAE of 1.99 kg and a strong positive correlation between estimated and actual BW (ρ = 0.972). The model demonstrated significant predictive power, with 73% of patients falling within a ±5% error range. WED emerged as the most relevant dose metric for BW estimation, followed by ED and sex. CONCLUSIONS: The proposed machine-learning approach is superior to existing methods, with high accuracy and applicability to radiation dose management. The model's reliance on universal dose metrics that are accessible through radiation dose management software enhances its practicality. In conclusion, this study presents a robust approach for BW estimation based on CT imaging that can potentially improve radiation dose management practices in clinical settings.

Maximal Analgesic Effect Attained by the Use of Objective Neurophysiological Measurements With Closed-Loop Spinal Cord Stimulation.

OBJECTIVES: Spinal cord stimulation (SCS) has been challenged by the lack of neurophysiologic data to guide therapy optimization. Current SCS programming by trial-and-error results in suboptimal and variable therapeutic effects. A novel system with a physiologic closed-loop feedback mechanism using evoked-compound action potentials enables the optimization of physiologic neural dose by consistently and accurately activating spinal cord fibers. We aimed to identify neurophysiologic dose metrics and their ranges that resulted in clinically meaningful treatment responses. MATERIALS AND METHODS: Subjects from 3 clinical studies (n = 180) with baseline back and leg pain ≥60 mm visual analog scale and physical function in the severe to crippled category were included. Maximal analgesic effect (MAE) was operationally defined as the greatest percent reduction in pain intensity or as the greatest cumulative responder score (minimal clinically important differences [MCIDs]) obtained within the first 3 months of SCS implant. The physiologic metrics that produced the MAE were analyzed. RESULTS: We showed that a neural dose regimen with a high neural dose accuracy of 2.8µV and dose ratio of 1.4 resulted in a profound clinical benefit to chronic pain patients (MAE of 79 ± 1% for pain reduction and 12.5 ± 0.4 MCIDs). No differences were observed for MAE or neurophysiological dose metrics between the trial phase and post-implant MAE visit. CONCLUSION: For the first time, an evidence-based neural dose regimen is available for a neurostimulation intervention as a starting point to enable optimization of clinical benefit, monitoring of adherence, and management of the therapy.

Translating dosimetry of Dibenzo[def,p]chrysene (DBC) and metabolites across dose and species using physiologically based pharmacokinetic (PBPK) modeling.

Dibenzo[def,p]chrysene (DBC) is an environmental polycyclic aromatic hydrocarbon (PAH) that causes tumors in mice and has been classified as a probable human carcinogen by the International Agency for Research on Cancer. Animal toxicity studies often utilize higher doses than are found in relevant human exposures. Additionally, like many PAHs, DBC requires metabolic bioactivation to form the ultimate toxicant, and species differences in DBC and DBC metabolite metabolism have been observed. To understand the implications of dose and species differences, a physiologically based pharmacokinetic model (PBPK) for DBC and major metabolites was developed in mice and humans. Metabolism parameters used in the model were obtained from experimental in vitro metabolism assays using mice and human hepatic microsomes. PBPK model simulations were evaluated against mice dosed with 15 mg/kg DBC by oral gavage and human volunteers orally microdosed with 29 ng of DBC. DBC and its primary metabolite DBC-11,12-diol were measured in blood of mice and humans, while in urine, the majority of DBC metabolites were obeserved as conjugated DBC-11,12-diol, conjugated DBC tetrols, and unconjugated DBC tetrols. The PBPK model was able to predict the time course concentrations of DBC, DBC-11,12-diol, and other DBC metabolites in blood and urine of human volunteers and mice with reasonable accuracy. Agreement between model simulations and measured pharmacokinetic data in mice and human studies demonstrate the success and versatility of our model for interspecies extrapolation and applicability for different doses. Furthermore, our simulations show that internal dose metrics used for risk assessment do not necessarily scale allometrically, and that PBPK modeling provides a reliable approach to appropriately account for interspecies differences in metabolism and physiology.

The Use of Nanomaterial In Vivo Organ Burden Data for In Vitro Dose Setting.

Effects of nanomaterials are usually observed at higher concentrations in vitro compared to animal studies. This is pointing to differences between in vivo situations and generally less complex in vitro models. These differences concern toxicodynamics and the internal exposure (at the target cells of the in vitro and in vivo test system). The latter can be minimized by appropriate in vivo to in vitro dose extrapolations (IVIVE). An IVIVE six-step procedure is proposed here: 1) determine in vivo exposure; 2) identify in vivo organ burden at lowest observed adverse effect concentration; 3) extrapolate in vivo organ burden to in vitro effective dose; 4) extrapolate in vitro effective dose to nominal concentration; 5) set dose ranges to establish dose-response relationships; and 6) consider uncertainties and specificities of in vitro test system. Assessing the results of in vitro studies needs careful consideration of discrepancies between in vitro and in vivo models: apart from different endpoints (usually cellular responses in vitro and adverse effects on organs or organisms in vivo), nanomaterials can also have a different potency in relatively simple in vitro models and the more complex corresponding organ in vivo. IVIVE can, nonetheless, reduce the differences in exposures.

Translating nanoparticle dosimetry from conventional in vitro systems to occupational inhalation exposures.

As encouraged by Toxicity Testing in the 21st Century, researchers increasingly apply high-throughput in vitro approaches to identify and characterize nanoparticle hazards, including conventional aqueous cell culture systems to assess respiratory hazards. Translating nanoparticle dose from conventional toxicity testing systems to relevant human exposures remains a major challenge for assessing occupational risk of nanoparticle exposures. Here, we explored existing computational tools and data available to translate nanoparticle dose metrics from cellular test systems to inhalation exposures of silver nanoparticles in humans. We used the Multiple-Path Particle Dosimetry (MPPD) Model to predict nanoparticle deposition of humans exposed to 20 and 110 nm silver nanoparticles at 0.9 µg/m3 over an 8 h period, the proposed National Institute of Occupational Safety and Health (NIOSH) recommended exposure limit (REL). MPPD predicts 8.1 and 3.7 µg of silver deposited in an 8 h period for 20 and 110 nm nanoparticles, respectively, with 20 nm particles displaying nearly 11-fold higher total surface area deposited. Peak deposited nanoparticle concentrations occurred more proximal in the pulmonary tract compared to mass deposition patterns (generation 4 vs. generations 20-21, respectively) due to regional differences in lung lining fluid volumes. Assuming 0.4% nanoparticle dissolution by mass measured in previous studies predicted peak concentrations of silver ions in cells of 1.06 and 0.89 µg/mL for 20 and 110 nm particles, respectively. Both predicted concentrations are below the measured toxic threshold of 1.7 µg/mL of silver ions in cells from in vitro assessments. Assuming 4% dissolution by mass predicted 10-fold higher silver concentrations in tissues, peaking at 10.6 and 8.9 µg/mL, for 20 and 110 nm nanoparticles respectively, exceeding the observed in vitro toxic threshold and highlighting the importance and sensitivity of dissolution rates. Overall, this approach offers a framework for extrapolating nanotoxicity results from in vitro cell culture systems to human exposures. Aligning appropriate dose metrics from in vitro and in vivo hazard characterizations and human pulmonary doses from occupational exposures are critical components for successful nanoparticle risk assessment and worker protection providing guidance for designing future in vitro studies aimed at relevant human exposures.

Total dose defines the incidence of percutaneous IgE/IgG1 mediated immediate-type hypersensitivity caused by papain.

Assessment of human health risk requires an understanding of antigen dose metrics associated with toxicity. Whereas assessment of the human health risk for delayed-type hypersensitivity is understood, the metrics remain unclear for percutaneous immediate-type hypersensitivity (ITH) mediated by IgE/IgG1. In this work, we aimed to investigate the dose metric for percutaneous ITH mediated by IgE/IgG1 responses. Papain, which causes ITH via percutaneous sensitization in humans, was used to sensitize guinea pigs and mice. The total dose per animal or dose per unit area was adjusted to understand the drivers of sensitization. Passive cutaneous anaphylaxis (PCA) and enzyme-linked immunosorbent assay (ELISA) for papain-specific IgG1 enabled quantification of the response in guinea pigs. In mice, the number of antigen-bearing B cells in the draining lymph nodes (DLN) was calculated using flow cytometry papain-specific IgG1 and IgE levels were quantified by ELISA. PCA positive test rates and the amounts of antigen-specific antibody corresponded with total dose per animal, not dose per unit area. Furthermore, the number of B cells taking up antigen within DLN also correlated with total dose. These findings indicate that the total antigen dose is the important metric for percutaneous IgE/IgG1-mediated ITH.

Size-specific dose estimates (SSDEs) for computed tomography and influencing factors on it: a systematic review.

The actual dose received during a computed tomography (CT) examination depends on both the patient size and the radiation output of the scanner. To represent the actual patient morphometry, a new radiation dose metric named size-specific dose estimates (SSDEs) was developed by the American Association of Physicists in Medicine in 2011. The purpose of this article is to review the SSDE concept and the factors influencing it. Moreover, the appropriate methodology of SSDE determination and the application of SSDE as a diagnostic reference-level quantity is critically analyzed based on the data available in the literature. It is expected that this review could potentially increase awareness among CT users of the effective utilization of SSDE as a tool to aid in the optimization of radiation dose in CT.

Application of the ICRP respiratory tract model to estimate pulmonary retention of industrially sampled indium-containing dusts.

Inhalation of indium-containing dusts is associated with the development of indium lung disease. Workers may be exposed to several different chemical forms of indium; however, their lung dosimetry is not fully understood. We characterized the physicochemical properties and measured the lung dissolution kinetics of eight indium-containing dusts. Indium dissolution rates in artificial lung fluids spanned two orders of magnitude. We used the International Commission on Radiological Protection (ICRP) human respiratory model (HRTM) to estimate pulmonary indium deposition, retention and biokinetic clearance to blood. For a two-year (median workforce tenure at facility) exposure to respirable-sized particles of the indium materials, modeled indium clearance (>99.99% removed) from the alveolar-interstitial compartment was slow for all dusts; salts would clear in 4 years, sintered indium-tin oxide (ITO) would clear in 9 years, and indium oxide would require 48 years. For this scenario, the ICRP HRTM predicted that indium translocated to blood would be present in that compartment for 3.5-18 years after cessation of exposure, depending on the chemical form. For a 40-year exposure (working lifetime), clearance from the alveolar-interstitial compartment would require 5, 10 and 60 years for indium salts, sintered ITO and indium oxide, respectively and indium would be present in blood for 5-53 years after exposure. Consideration of differences in chemical forms of indium, dissolution rates, alveolar clearance and residence time in blood should be included in exposure assessment and epidemiological studies that rely on measures of total indium in air or blood to derive risk estimates.

Dosimetric Comparison of Ultra-Hypofractionated and Conventionally Fractionated Radiation Therapy Boosts for Patients with High-Risk Prostate Cancer.

Recent comparison of an ultra-hypofractionated radiotherapy (UF-RT) boost to a conventionally fractionated (CF-RT) option showed similar toxicity and disease control outcomes. An analysis of the treatment plans for these patients is needed for evaluating calculated doses for different organs, treatment beam-on time, and requirements for human and financial resources. Eighty-six plans for UF-RT and 93 plans for CF-RT schemes were evaluated. The biologically equivalent dose, EQD2, summed for the first phase and the boost, was calculated for dose-volume parameters for organs at risk (OARs), as well as for the PTV1. ArcCHECK measurements for the boost plans were used for a comparison of planned and delivered doses. Monitor units and beam-on times were recorded by the Eclipse treatment planning system. Statistical analysis was performed with a significance level of 0.05. Dosimetric parameter values for OARs were well within tolerance for both groups. EQD2 for the PTV1 was on average 84 Gy for UF-RT patients and 76 Gy for CF-RT patients. Gamma passing rate for planned/delivered doses comparison was above 98% for both groups with 3 mm/3% distance to agreement/dose difference criteria. Total monitor units per fraction were 647 ± 94 and 2034 ± 570 for CF-RT and UF-RT, respectively. The total delivery time for boost radiation for the patients in the UF-RT arm was, on average, four times less than the total time for a conventional regimen with statistically equal clinical outcomes for the two arms in this study.

Assessing modes of action, measures of tissue dose and human relevance of rodent toxicity endpoints with octamethylcyclotetrasiloxane (D4).

Octamethylcyclotetrasiloxane (D4), a highly lipophilic, volatile compound with low water solubility, is metabolized to lower molecular weight, linear silanols. Toxicity has been documented in several tissues in animals following mixed vapor/aerosol exposures by inhalation at near saturating vapor concentrations or with gavage dosing in vegetable oil vehicles. These results, together with more mechanism-based studies and detailed pharmacokinetic information, were used to assess likely modes of action (MOAs) and the tissue dose measures of D4 and metabolites that would serve as key events leading to these biological responses. This MOA analysis indicates that pulmonary effects arise from direct epithelial contact with mixed vapor/aerosol atmospheres of D4; liver hypertrophy and hepatocyte proliferation arise from adaptive, rodent-specific actions of D4 with nuclear receptor signaling pathways; and, nephropathy results from a combination of chronic progresive nephropathy and silanol metabolites binding with alpha-2u globulin (a male rat specific protein). At this time, the MOAs of other liver effects - pigment accumulation and bile duct hyperplasia (BDH) preferentially observed in Sprague-Dawley (SD) rats- are not known. Hypothalamic actions of D4 delaying the rat mid-cycle gonadotrophin releasing hormone (GnRH) surge that result in reproductive effects and subsequent vaginal/uterine/ovarian tissue responses, including small increases in incidence of benign endometrial adenomas, are associated with prolongation of endogenous estrogen exposures due to delays in ovulation. Human reproduction is not controlled by a mid-cycle GnRH surge. Since the rodent-specific reproductive and the vaginal/uterine/ovarian tissue responses are not relevant for risk assessments in human populations, D4 should neither be classified as a CMR (i.e., carcinogenic, mutagenic, or toxic for reproduction) substance nor be regarded as an endocrine disruptor. Bile duct hyperplasia (BDH) and pigment accumulation in liver seen in SD rats are endpoints that could serve to define a Benchmark Dose (BMD) or No-Observed-Effect-Level (NOEL) for D4 although their human relevance remains uncertain.

Next generation risk assessment (NGRA): Bridging in vitro points-of-departure to human safety assessment using physiologically-based kinetic (PBK) modelling - A case study of doxorubicin with dose metrics considerations.

Using the chemical doxorubicin (DOX), the objective of the present study was to evaluate the impact of dose metrics selection in the new approach method of integrating physiologically-based kinetic (PBK) modelling and relevant human cell-based assays to inform a priori the point of departure for human health risk. We reviewed the literature on the clinical consequences of DOX treatment to identify dosing scenarios with no or mild cardiotoxicity observed. Key concentrations of DOX that induced cardiomyocyte toxicity in vitro were derived from studies of our own and others. A human population-based PBK model of DOX was developed and verified against pharmacokinetic data. The model was then used to predict plasma and extracellular and intracellular heart concentrations of DOX under selected clinical settings and compared with in vitro outcomes, based on several dose metrics: Cmax (maximum concentration) or AUC (area under concentration-time curve) in free or total form of DOX. We found when using in vitro assays to predict cardiotoxicity for DOX, AUC is a better indicator. Our study illustrates that when appropriate dose metrics are used, it is possible to combine PBK modelling with in vitro-derived toxicity information to define margins of safety and predict low-risk human exposure levels.

What is plan quality in radiotherapy? The importance of evaluating dose metrics, complexity, and robustness of treatment plans.

Plan evaluation is a key step in the radiotherapy treatment workflow. Central to this step is the assessment of treatment plan quality. Hence, it is important to agree on what we mean by plan quality and to be fully aware of which parameters it depends on. We understand plan quality in radiotherapy as the clinical suitability of the delivered dose distribution that can be realistically expected from a treatment plan. Plan quality is commonly assessed by evaluating the dose distribution calculated by the treatment planning system (TPS). Evaluating the 3D dose distribution is not easy, however; it is hard to fully evaluate its spatial characteristics and we still lack the knowledge for personalising the prediction of the clinical outcome based on individual patient characteristics. This advocates for standardisation and systematic collection of clinical data and outcomes after radiotherapy. Additionally, the calculated dose distribution is not exactly the dose delivered to the patient due to uncertainties in the dose calculation and the treatment delivery, including variations in the patient set-up and anatomy. Consequently, plan quality also depends on the robustness and complexity of the treatment plan. We believe that future work and consensus on the best metrics for quality indices are required. Better tools are needed in TPSs for the evaluation of dose distributions, for the robust evaluation and optimisation of treatment plans, and for controlling and reporting plan complexity. Implementation of such tools and a better understanding of these concepts will facilitate the handling of these characteristics in clinical practice and be helpful to increase the overall quality of treatment plans in radiotherapy.

A physiologically-based pharmacokinetic model of oseltamivir phosphate and its carboxylate metabolite for rats and humans.

Oseltamivir phosphate (OP, Tamiflu®) is a widely used prodrug for the treatment of influenza viral infections. Orally administered OP is rapidly hydrolyzed by the carboxylesterases in animals to oseltamivir carboxylate (OC), a potent influenza virus neuraminidase inhibitor. The goals of this study were to develop and validate a physiologically-based pharmacokinetic (PBPK) model of OP/OC in rats and humans, and to predict the internal tissue doses for OP and OC in humans after receiving OP orally. To this end, a PBPK model of OP/OC was first developed in the rat, which was then scaled up to humans by replacing the physiological and biochemical parameters with human-specific values. The proposed PBPK model consisted of an OP and an OC sub-models each containing nine first-order, flow-limited tissue/organ compartments. OP metabolism to OC was assumed to carry out mainly by hepatic carboxylesterases although extra-hepatic metabolism also occurred especially in the plasma. The PBPK model was developed and validated by experimental data from our laboratories and from the literature. The proposed PBPK model accurately predicted the pharmacokinetic behavior of OP and OC in humans and rats after receiving a single or multiple doses of OP orally or an OC dose i.v. The PBPK model was used to predict the internal tissue doses of OP and OC in a hypothetical human after receiving the recommended dose of 75 mg/kg OP b.i.d. for 6 days. Steady-state OC concentrations in the plasma and major organs such as the lung and the brain were higher than the minimum in vitro IC50 reported for H1N1 influenza virus neuraminidase, confirming OP is an effective, anti-viral agent. OP side-effects in the gastrointestinal tract and brain of humans were explainable by the tissue doses found in these organs. The PBPK model provides a quantitative tool to evaluate the relationship between an externally applied dose of OP and the internal tissue doses in humans. As such the model can be used to adjust the dose regimens for adult patients in disease states e.g., renal failure and liver damage.

Radiation dose metrics in multidetector computed tomography examinations: A multicentre retrospective study from seven tertiary care hospitals in Kerala, South India.

BACKGROUND: Presently, computed tomography (CT) is the most important source of medical radiation exposure. CT radiation doses vary considerably across institutions depending on the protocol and make of equipment. India does not yet have national or region-specific CT diagnostic reference levels. AIM: To evaluate radiation doses of consecutive multidetector CT (MDCT) examinations based on anatomic region, performed in 1 month, collected simultaneously from seven tertiary care hospitals in Kerala. SETTINGS AND DESIGN: Descriptive study. MATERIALS AND METHODS: We collected the CT radiation dose data of examinations from the seven collaborating tertiary care hospitals in Kerala, performed with MDCT scanners of five different makes. The data included anatomic region, number of phases, CT dose index (CTDIvol), dose-length product (DLP), and effective dose (ED) of each examinations and patient demographic data. STATISTICAL ANALYSIS: We calculated the 25th, 50th, and 75th percentiles of the CTDIvol, DLP, and ED according to anatomic region. We made descriptive comparisons of these results with corresponding data from other countries. RESULTS: Of 3553 patients, head was the most frequently performed examination (60%), followed by abdomen (19%). For single-phase head examinations, 75th percentile of CTDIvol was 68.1 mGy, DLP 1120 mGy-cm, and ED 2.1 mSv. The 75th percentiles of CTDIvol, DLP, and ED for single-phase abdomen examinations were 10.6, 509.3, and 7.7, and multiphase examinations were 14.6, 2666.9, and 40.8; single-phase chest examinations were 23.4, 916.7, and 13.38, and multiphase examinations were 19.9, 1737.6, and 25.36; single-phase neck were 24.9, 733.6, and 3.814, and multiphase neck were 24.9, 2076, and 10.79, respectively. CONCLUSION: This summary CT radiation dose data of most frequently performed anatomical regions could provide a starting point for institutional analysis of CT radiation doses, which in turn leads to meaningful optimization of CT.

Modeling of Body Weight Metrics for Effective and Cost-Efficient Conventional Factor VIII Dosing in Hemophilia A Prophylaxis.

The total body weight-based dosing strategy currently used in the prophylactic treatment of hemophilia A may not be appropriate for all populations. The assumptions that guide weight-based dosing are not valid in overweight and obese populations, resulting in overdosing and ineffective resource utilization. We explored different weight metrics including lean body weight, ideal body weight, and adjusted body weight to determine an alternative dosing strategy that is both safe and resource-efficient in normal and overweight/obese adult patients. Using a validated population pharmacokinetic model, we simulated a variety of dosing regimens using different doses, weight metrics, and frequencies; we also investigated the implications of assuming various levels of endogenous factor production. Ideal body weight performed the best across all of the regimens explored, maintaining safety while moderating resource consumption for overweight and obese patients.

Identification of the appropriate dose metric for pulmonary inflammation of silver nanoparticles in an inhalation toxicity study.

A number of studies have shown that induction of pulmonary toxicity by nanoparticles of the same chemical composition depends on particle size, which is likely in part due to differences in lung deposition. Particle size mostly determines whether nanoparticles reach the alveoli, and where they might induce toxicity. For the risk assessment of nanomaterials, there is need for a suitable dose metric that accounts for differences in effects between different sized nanoparticles of the same chemical composition. The aim of the present study is to determine the most suitable dose metric to describe the effects of silver nanoparticles after short-term inhalation. Rats were exposed to different concentrations (ranging from 41 to 1105 µg silver/m(3) air) of 18, 34, 60 and 160 nm silver particles for four consecutive days and sacrificed at 24 h and 7 days after exposure. We observed a concentration-dependent increase in pulmonary toxicity parameters like cell counts and pro-inflammatory cytokines in the bronchoalveolar lavage fluid. All results were analysed using the measured exposure concentrations in air, the measured internal dose in the lung and the estimated alveolar dose. In addition, we analysed the results based on mass, particle number and particle surface area. Our study indicates that using the particle surface area as a dose metric in the alveoli, the dose-response effects of the different silver particle sizes overlap for most pulmonary toxicity parameters. We conclude that the alveolar dose expressed as particle surface area is the most suitable dose metric to describe the toxicity of silver nanoparticles after inhalation.

Simple in vitro models can predict pulmonary toxicity of silver nanoparticles.

To study the effects of nanomaterials after inhalation, a large number of in vitro lung models have been reported in literature. Although the in vitro models contribute to the reduction of animal studies, insufficient data exists to determine the predictive value of these in vitro models for the in vivo situation. The aim of this study was to determine the correlation between in vitro and in vivo data by comparing the dose metrics of silver nanoparticles in an in vitro lung model of increasing complexity to our previously published in vivo inhalation study. In vivo, the previously published study showed that the alveolar dose expressed as particle surface area is the most suitable dose metric to describe the toxicity of silver nanoparticles after inhalation. The results of the present study show that particle surface area is a suitable dose metric to describe the effects of silver nanoparticles when using a simple monolayer of lung epithelial cells. The dose metric shifted from particle surface area to particle mass when adding an increasing number of macrophages. In addition, a co-culture of endothelial cells, epithelial cells and macrophages on a Transwell® insert correlated less well to the in vivo results compared to the epithelial monolayer. We conclude that for studying the acute pulmonary toxicity of nanoparticles simple in vitro models using an epithelial monolayer better predict the in vivo response compared to complex co-culture models.

Normal tissue complication probability (NTCP) modelling using spatial dose metrics and machine learning methods for severe acute oral mucositis resulting from head and neck radiotherapy.

BACKGROUND AND PURPOSE: Severe acute mucositis commonly results from head and neck (chemo)radiotherapy. A predictive model of mucositis could guide clinical decision-making and inform treatment planning. We aimed to generate such a model using spatial dose metrics and machine learning. MATERIALS AND METHODS: Predictive models of severe acute mucositis were generated using radiotherapy dose (dose-volume and spatial dose metrics) and clinical data. Penalised logistic regression, support vector classification and random forest classification (RFC) models were generated and compared. Internal validation was performed (with 100-iteration cross-validation), using multiple metrics, including area under the receiver operating characteristic curve (AUC) and calibration slope, to assess performance. Associations between covariates and severe mucositis were explored using the models. RESULTS: The dose-volume-based models (standard) performed equally to those incorporating spatial information. Discrimination was similar between models, but the RFCstandard had the best calibration. The mean AUC and calibration slope for this model were 0.71 (s.d.=0.09) and 3.9 (s.d.=2.2), respectively. The volumes of oral cavity receiving intermediate and high doses were associated with severe mucositis. CONCLUSIONS: The RFCstandard model performance is modest-to-good, but should be improved, and requires external validation. Reducing the volumes of oral cavity receiving intermediate and high doses may reduce mucositis incidence.

A practical approach to determine dose metrics for nanomaterials.

Traditionally, administered mass is used to describe doses of conventional chemical substances in toxicity studies. For deriving toxic doses of nanomaterials, mass and chemical composition alone may not adequately describe the dose, because particles with the same chemical composition can have completely different toxic mass doses depending on properties such as particle size. Other dose metrics such as particle number, volume, or surface area have been suggested, but consensus is lacking. The discussion regarding the most adequate dose metric for nanomaterials clearly needs a systematic, unbiased approach to determine the most appropriate dose metric for nanomaterials. In the present study, the authors propose such an approach and apply it to results from in vitro and in vivo experiments with silver and silica nanomaterials. The proposed approach is shown to provide a convenient tool to systematically investigate and interpret dose metrics of nanomaterials. Recommendations for study designs aimed at investigating dose metrics are provided.

Radiation dose metrics in CT: assessing dose using the National Quality Forum CT patient safety measure.

PURPOSE: The National Quality Forum (NQF) is a nonprofit consensus organization that recently endorsed a measure focused on CT radiation doses. To comply, facilities must summarize the doses from consecutive scans within age and anatomic area strata and report the data in the medical record. Our purpose was to assess the time needed to assemble the data and to demonstrate how review of such data permits a facility to understand doses. METHODS AND MATERIALS: To assemble the data we used for analysis, we used the dose monitoring software eXposure to automatically export dose metrics from consecutive scans in 2010 and 2012. For a subset of 50 exams, we also collected dose metrics manually, copying data directly from the PACS into an excel spreadsheet. RESULTS: Manual data collection for 50 scans required 2 hours and 15 minutes. eXposure compiled the data in under an hour. All dose metrics demonstrated a 30% to 50% reduction between 2010 and 2012. There was also a significant decline and a reduction in the variability of the doses over time. CONCLUSION: The NQF measure facilitates an institution's capacity to assess the doses they are using for CT as part of routine practice. The necessary data can be collected within a reasonable amount of time either with automatic software or manually. The collection and review of these data will allow facilities to compare their radiation dose distributions with national distributions and allow assessment of temporal trends in the doses they are using.