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Propagation of statistical uncertainties in covariant density functional theory: Ground state observables and single-particle properties

Statistical errors in ground state observables and single-particle properties of spherical even-even nuclei and their propagation to the limits of nuclear landscape have been investigated in covariant density functional theory (CDFT) for the first time. Here, we consider only covariant energy density functionals with non-linear density dependency. Statistical errors for binding energies and neutron skins significantly increase on approaching two-neutron drip line. On the contrary, such a trend does not exist for statistical errors in charge radii and two-neutron separation energies. The absolute and relative energies of the single-particle states in the vicinity of the Fermi level are characterized by low statistical errors ($\sigma(e_i)\sim 0.1$ MeV). Statistical errors in the predictions of spin-orbit splittings are rather small. Statistical errors in physical observables are substantially smaller than related systematic uncertainties. As a result, at the present level of the development of theory, theoretical uncertainties at nuclear limits are dominated by systematic ones. Statistical errors in the description of physical observables related to the ground state and single-particle degrees of freedom are typically substantially lower in CDFT as compared with Skyrme density functional theory. The correlations between the model parameters are studied in detail. The parametric correlations are especially pronounced for the $g_2$ and $g_3$ parameters which are responsible for the density dependence of the model. The accounting of this fact potentially allows to reduce the number of free parameters of non-linear meson coupling model from six to five.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

THE APOKASC CATALOG: AN ASTEROSEISMIC AND SPECTROSCOPIC JOINT SURVEY OF TARGETS IN THE KEPLER FIELDS

We present the first APOKASC catalog of spectroscopic and asteroseismic properties of 1916 red giants observed in the Kepler fields. The spectroscopic parameters provided from the Apache Point Observatory Galactic Evolution Experiment project are complemented with asteroseismic surface gravities, masses, radii, and mean densities determined by members of the Kepler Asteroseismology Science Consortium. We assess both random and systematic sources of error and include a discussion of sample selection for giants in the Kepler fields. Total uncertainties in the main catalog properties are of the order of 80 K in T {sub eff}, 0.06 dex in [M/H], 0.014 dex in log g, and 12% and 5% in mass and radius, respectively; these reflect a combination of systematic and random errors. Asteroseismic surface gravities are substantially more precise and accurate than spectroscopic ones, and we find good agreement between their mean values and the calibrated spectroscopic surface gravities. There are, however, systematic underlying trends with T {sub eff} and log g. Our effective temperature scale is between 0 and 200 K cooler than that expected from the infrared flux method, depending on the adopted extinction map, which provides evidence for a lower value on average than that inferred for the Kepler Input Catalog (KIC). We find a reasonable correspondence between the photometric KIC and spectroscopic APOKASC metallicity scales, with increased dispersion in KIC metallicities as the absolute metal abundance decreases, and offsets in T {sub eff} and log g consistent with those derived in the literature. We present mean fitting relations between APOKASC and KIC observables and discuss future prospects, strengths, and limitations of the catalog data.

79 ASTRONOMY AND ASTROPHYSICS↗

Analysis of Prostate Patient Setup and Tracking Data: Potential Intervention Strategies

Purpose: To evaluate the setup, interfraction, and intrafraction organ motion error distributions and simulate intrafraction intervention strategies for prostate radiotherapy. Methods and Materials: A total of 17 patients underwent treatment setup and were monitored using the Calypso system during radiotherapy. On average, the prostate tracking measurements were performed for 8 min/fraction for 28 fractions for each patient. For both patient couch shift data and intrafraction organ motion data, the systematic and random errors were obtained from the patient population. The planning target volume margins were calculated using the van Herk formula. Two intervention strategies were simulated using the tracking data: the deviation threshold and period. The related planning target volume margins, time costs, and prostate position 'fluctuation' were presented. Results: The required treatment margin for the left-right, superoinferior, and anteroposterior axes was 8.4, 10.8, and 14.7 mm for skin mark-only setup and 1.3, 2.3, and 2.8 mm using the on-line setup correction, respectively. Prostate motion significantly correlated among the superoinferior and anteroposterior directions. Of the 17 patients, 14 had prostate motion within 5 mm of the initial setup position for {>=}91.6% of the total tracking time. The treatment margin decreased to 1.1, 1.8, and 2.3 mm with a 3-mm threshold correction and to 0.5, 1.0, and 1.5 mm with an every-2-min correction in the left-right, superoinferior, and anteroposterior directions, respectively. The periodic corrections significantly increase the treatment time and increased the number of instances when the setup correction was made during transient excursions. Conclusions: The residual systematic and random error due to intrafraction prostate motion is small after on-line setup correction. Threshold-based and time-based intervention strategies both reduced the planning target volume margins. The time-based strategies increased the treatment time and the in-fraction position fluctuation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

A review of setup error in supine breast radiotherapy using cone-beam computed tomography

Setup error in breast radiotherapy (RT) measured with 3-dimensional cone-beam computed tomography (CBCT) is becoming more common. The purpose of this study is to review the literature relating to the magnitude of setup error in breast RT measured with CBCT. The different methods of image registration between CBCT and planning computed tomography (CT) scan were also explored. A literature search, not limited by date, was conducted using Medline and Google Scholar with the following key words: breast cancer, RT, setup error, and CBCT. This review includes studies that reported on systematic and random errors, and the methods used when registering CBCT scans with planning CT scan. A total of 11 relevant studies were identified for inclusion in this review. The average magnitude of error is generally less than 5 mm across a number of studies reviewed. The common registration methods used when registering CBCT scans with planning CT scan are based on bony anatomy, soft tissue, and surgical clips. No clear relationships between the setup errors detected and methods of registration were observed from this review. Further studies are needed to assess the benefit of CBCT over electronic portal image, as CBCT remains unproven to be of wide benefit in breast RT.

61 RADIATION PROTECTION AND DOSIMETRY↗

DISSECTING THE STELLAR-MASS-SFR CORRELATION IN z = 1 STAR-FORMING DISK GALAXIES

Using a mass-limited sample of 24 {mu}m detected, star-forming galaxies at 0.5 < z < 1.3, we study the mass-star formation rate (SFR) correlation and its tightness. The correlation is well defined ({sigma} = 0.28 dex) for disk galaxies (n{sub Sersic} < 1.5), while more bulge-dominated objects often have lower specific SFRs (sSFRs). For disk galaxies, a much tighter correlation ({sigma} = 0.19 dex) is obtained if the rest-frame H-band luminosity is used instead of stellar mass derived from multi-color photometry. The sSFR correlates strongly with rest-frame optical colors (hence luminosity-weighted stellar age) and also with clumpiness (which likely reflects the molecular gas fraction). This implies that most of the observed scatter is real, despite its low level, and not dominated by random measurement errors. After correcting for these differential effects a remarkably small dispersion remains ({sigma} = 0.14 dex), suggesting that measurement errors in mass or SFR are {approx}< 0.10 dex, excluding systematic uncertainties. Measurement errors in stellar masses, the thickening of the correlation due to real sSFR variations, and varying completeness with stellar mass, can spuriously bias the derived slope to lower values due to the finite range over which observables (mass and SFR) are available. When accounting for these effects, the intrinsic slope for the main sequence for disk galaxies gets closer to unity.

79 ASTRONOMY AND ASTROPHYSICS↗

TU-H-CAMPUS-JeP3-01: Towards Robust Adaptive Radiation Therapy Strategies

Purpose: To set up a framework combining robust treatment planning with adaptive reoptimization in order to maintain high treatment quality, to respond to interfractional variations and to identify those patients who will benefit the most from an adaptive fractionation schedule. Methods: We propose adaptive strategies based on stochastic minimax optimization for a series of simulated treatments on a one-dimensional patient phantom. The plan should be able to handle anticipated systematic and random errors and is applied during the first fractions. Information on the individual geometric variations is gathered at each fraction. At scheduled fractions, the impact of the measured errors on the delivered dose distribution is evaluated. For a patient that receives a dose that does not satisfy specified plan quality criteria, the plan is reoptimized based on these individual measurements using one of three different adaptive strategies. The reoptimized plan is then applied during future fractions until a new scheduled adaptation becomes necessary. In the first adaptive strategy the measured systematic and random error scenarios and their assigned probabilities are updated to guide the robust reoptimization. The focus of the second strategy lies on variation of the fraction of the worst scenarios taken into account during robust reoptimization. In the third strategy the uncertainty margins around the target are recalculated with the measured errors. Results: By studying the effect of the three adaptive strategies combined with various adaptation schedules on the same patient population, the group which benefits from adaptation is identified together with the most suitable strategy and schedule. Preliminary computational results indicate when and how best to adapt for the three different strategies. Conclusion: A workflow is presented that provides robust adaptation of the treatment plan throughout the course of treatment and useful measures to identify patients in need for an adaptive treatment strategy.

60 APPLIED LIFE SCIENCES↗

SYSTEMATIC EFFECTS IN POLARIZING FOURIER TRANSFORM SPECTROMETERS FOR COSMIC MICROWAVE BACKGROUND OBSERVATIONS

The detection of the primordial B-mode polarization signal of the cosmic microwave background (CMB) would provide evidence for inflation. Yet as has become increasingly clear, the detection of a such a faint signal requires an instrument with both wide frequency coverage to reject foregrounds and excellent control over instrumental systematic effects. Using a polarizing Fourier transform spectrometer (FTS) for CMB observations meets both of these requirements. In this work, we present an analysis of instrumental systematic effects in polarizing FTSs, using the Primordial Inflation Explorer (PIXIE) as a worked example. We analytically solve for the most important systematic effects inherent to the FTS—emissive optical components, misaligned optical components, sampling and phase errors, and spin synchronous effects—and demonstrate that residual systematic error terms after corrections will all be at the sub-nK level, well below the predicted 100 nK B-mode signal.

79 ASTRONOMY AND ASTROPHYSICS↗

SU-E-T-114: Analysis of MLC Errors On Gamma Pass Rates for Patient-Specific and Conventional Phantoms

Purpose: To evaluate whether a 3D patient-specific phantom is better able to detect known MLC errors in a clinically delivered treatment plan than conventional phantoms. 3D printing may make fabrication of such phantoms feasible. Methods: Two types of MLC errors were introduced into a clinically delivered, non-coplanar IMRT, partial brain treatment plan. First, uniformly distributed random errors of up to 3mm, 2mm, and 1mm were introduced into the MLC positions for each field. Second, systematic MLC-bank position errors of 5mm, 3.5mm, and 2mm due to simulated effects of gantry and MLC sag were introduced. The original plan was recalculated with these errors on the original CT dataset as well as cylindrical and planar IMRT QA phantoms. The original dataset was considered to be a perfect 3D patient-specific phantom. The phantoms were considered to be ideal 3D dosimetry systems with no resolution limitations. Results: Passing rates for Gamma Index (3%/3mm and no dose threshold) were calculated on the 3D phantom, cylindrical phantom, and both on a composite and field-by-field basis for the planar phantom. Pass rates for 5mm systematic and 3mm random error were 86.0%, 89.6%, 98% and 98.3% respectively. For 3.5mm systematic and 2mm random error the pass rates were 94.7%, 96.2%, 99.2% and 99.2% respectively. For 2mm systematic error with 1mm random error the pass rates were 99.9%, 100%, 100% and 100% respectively. Conclusion: A 3D phantom with the patient anatomy is able to discern errors, both severe and subtle, that are not seen using conventional phantoms. Therefore, 3D phantoms may be beneficial for commissioning new treatment machines and modalities, patient-specific QA and end-to-end testing.

60 APPLIED LIFE SCIENCES↗

TU-G-BRD-08: In-Vivo EPID Dosimetry: Quantifying the Detectability of Four Classes of Errors

Purpose: EPID dosimetry is an emerging method for treatment verification and QA. Given that the in-vivo EPID technique is in clinical use at some centers, we investigate the sensitivity and specificity for detecting different classes of errors. We assess the impact of these errors using dose volume histogram endpoints. Though data exist for EPID dosimetry performed pre-treatment, this is the first study quantifying its effectiveness when used during patient treatment (in-vivo). Methods: We analyzed 17 patients; EPID images of the exit dose were acquired and used to reconstruct the planar dose at isocenter. This dose was compared to the TPS dose using a 3%/3mm gamma criteria. To simulate errors, modifications were made to treatment plans using four possible classes of error: 1) patient misalignment, 2) changes in patient body habitus, 3) machine output changes and 4) MLC misalignments. Each error was applied with varying magnitudes. To assess the detectability of the error, the area under a ROC curve (AUC) was analyzed. The AUC was compared to changes in D99 of the PTV introduced by the simulated error. Results: For systematic changes in the MLC leaves, changes in the machine output and patient habitus, the AUC varied from 0.78–0.97 scaling with the magnitude of the error. The optimal gamma threshold as determined by the ROC curve varied between 84–92%. There was little diagnostic power in detecting random MLC leaf errors and patient shifts (AUC 0.52–0.74). Some errors with weak detectability had large changes in D99. Conclusion: These data demonstrate the ability of EPID-based in-vivo dosimetry in detecting variations in patient habitus and errors related to machine parameters such as systematic MLC misalignments and machine output changes. There was no correlation found between the detectability of the error using the gamma pass rate, ROC analysis and the impact on the dose volume histogram. Funded by grant R18HS022244 from AHRQ.

60 APPLIED LIFE SCIENCES↗

Cluster Mass Calibration at High Redshift: HST Weak Lensing Analysis of 13 Distant Galaxy Clusters from the South Pole Telescope Sunyaev-Zel’dovich Survey

We present an HST/Advanced Camera for Surveys (ACS) weak gravitational lensing analysis of 13 massive high-redshift (z(median) = 0.88) galaxy clusters discovered in the South Pole Telescope (SPT) Sunyaev-Zel'dovich Survey. This study is part of a larger campaign that aims to robustly calibrate mass-observable scaling relations over a wide range in redshift to enable improved cosmological constraints from the SPT cluster sample. We introduce new strategies to ensure that systematics in the lensing analysis do not degrade constraints on cluster scaling relations significantly. First, we efficiently remove cluster members from the source sample by selecting very blue galaxies in V - I colour. Our estimate of the source redshift distribution is based on Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) data, where we carefully mimic the source selection criteria of the cluster fields. We apply a statistical correction for systematic photometric redshift errors as derived from Hubble Ultra Deep Field data and verified through spatial cross-correlations. We account for the impact of lensing magnification on the source redshift distribution, finding that this is particularly relevant for shallower surveys. Finally, we account for biases in the mass modelling caused by miscentring and uncertainties in the concentration-mass relation using simulations. In combination with temperature estimates from Chandra we constrain the normalization of the mass-temperature scaling relation ln (E(z) M-500c/10(14)M(circle dot)) = A + 1.5ln (kT/7.2 keV) to A = 1.81(-0.14)(+0.24)(stat.)+/- 0.09(sys.), consistent with self-similar redshift evolution when compared to lower redshift samples. Additionally, the lensing data constrain the average concentration of the clusters to c(200c) = 5.6(-1.8)(+3.7).

cosmology: observations↗

Evaluating the Uncertainty of Terrestrial Water Budget Components Over High Mountain Asia

This study explores the uncertainties in terrestrial water budget estimation over High Mountain Asia (HMA) using a suite of uncoupled land surface model (LSM) simulations. The uncertainty in the water balance components of precipitation (P), evapotranspiration (ET), runoff (R), and terrestrial water storage (TWS) is significantly impacted by the uncertainty in the driving meteorology, with precipitation being the most important boundary condition. Ten gridded precipitation datasets along with a mix of model-, satellite-, and gauge-based products, are evaluated first to assess their suitability for LSM simulations over HMA. The datasets are evaluated by quantifying the systematic and random errors of these products as well as the temporal consistency of their trends. Though the broader spatial patterns of precipitation are generally well captured by the datasets, they differ significantly in their means and trends. In general, precipitation datasets that incorporate information from gauges are found to have higher accuracy with low Root Mean Square Errors and high correlation coefficient values. An ensemble of LSM simulations with selected subset of precipitation products is then used to produce the mean annual fluxes and their uncertainty over HMA in P, ET, and R to be 2.11 ± 0.45, 1.26 ± 0.11, and 0.85 ± 0.36 mm per day, respectively. The mean annual estimates of the surface mass (water) balance components from this model ensemble are comparable to global estimates from prior studies. However, the uncertainty/spread of P, ET, and R is significantly larger than the corresponding estimates from global studies. A comparison of ET, snow cover fraction, and changes in TWS estimates against remote sensing-based references confirms the significant role of the input meteorology in influencing the water budget characterization over HMA and points to the need for improving meteorological inputs.

Yoon, Yeosang↗

Forces from Stochastic Density Functional Theory under Nonorthogonal Atom-Centered Basis Sets

We develop a formalism for calculating forces on the nuclei within the linear-scaling stochastic density functional theory (sDFT) in a nonorthogonal atom-centered basis set representation (Fabian et al. Wiley Interdiscip. Rev.: Comput. Mol. Sci. 2019, 9, e1412, 10.1002/wcms.1412) and apply it to the Tryptophan Zipper 2 (Trp-zip2) peptide solvated in water. We use an embedded-fragment approach to reduce the statistical errors (fluctuation and systematic bias), where the entire peptide is the main fragment and the remaining 425 water molecules are grouped into small fragments. We analyze the magnitude of the statistical errors in the forces and find that the systematic bias is of the order of 0.065 eV/Å (~1.2 × 10 -3 E h / a 0 ) when 120 stochastic orbitals are used, independently of system size. This magnitude of bias is sufficiently small to ensure that the bond lengths estimated by stochastic DFT (within a Langevin molecular dynamics simulation) will deviate by less than 1% from those predicted by a deterministic calculation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Weak-lensing mass calibration of redMaPPer galaxy clusters in Dark Energy Survey Science Verification data

We use weak-lensing shear measurements to determine the mean mass of optically selected galaxy clusters in Dark Energy Survey Science Verification data. In a blinded analysis, we split the sample of more than 8,000 redMaPPer clusters into 15 subsets, spanning ranges in the richness parameter $5 \leq \lambda \leq 180$ and redshift $0.2 \leq z \leq 0.8$, and fit the averaged mass density contrast profiles with a model that accounts for seven distinct sources of systematic uncertainty: shear measurement and photometric redshift errors; cluster-member contamination; miscentering; deviations from the NFW halo profile; halo triaxiality; and line-of-sight projections. We combine the inferred cluster masses to estimate the joint scaling relation between mass, richness and redshift, $\mathcal{M}(\lambda,z) \varpropto M_0 \lambda^{F} (1+z)^{G}$. We find $M_0 \equiv \langle M_{200\mathrm{m}}\,|\,\lambda=30,z=0.5\rangle=\left[ 2.35 \pm 0.22\ \rm{(stat)} \pm 0.12\ \rm{(sys)} \right] \cdot 10^{14}\ M_\odot$, with $F = 1.12\,\pm\,0.20\ \rm{(stat)}\, \pm\, 0.06\ \rm{(sys)}$ and $G = 0.18\,\pm\, 0.75\ \rm{(stat)}\, \pm\, 0.24\ \rm{(sys)}$. The amplitude of the mass-richness relation is in excellent agreement with the weak-lensing calibration of redMaPPer clusters in SDSS by Simet et al. (2016) and with the Saro et al. (2015) calibration based on abundance matching of SPT-detected clusters. Our results extend the redshift range over which the mass-richness relation of redMaPPer clusters has been calibrated with weak lensing from $z\leq 0.3$ to $z\leq0.8$. Calibration uncertainties of shear measurements and photometric redshift estimates dominate our systematic error budget and require substantial improvements for forthcoming studies.

79 ASTRONOMY AND ASTROPHYSICS↗

Effective field theory approach to heavy quark fragmentation

Using an approach based on Soft Collinear Effective Theory (SCET) and Heavy Quark Effective Theory (HQET) we determine the b-quark fragmentation function from electron-positron annihilation data at the Z-boson peak at next-to-next-to leading order with next-to-next-to leading log resummation of DGLAP logarithms, and next-to-next-to-next-to leading log resummation of endpoint logarithms. This analysis improves, by one order, the previous extraction of the b-quark fragmentation function. We find that while the addition of the next order in the calculation does not much shift the extracted form of the fragmentation function, it does reduce theoretical errors indicating that the expansion is converging. Using an approach based on effective field theory allows us to systematically control theoretical errors. Furthermore, while the fits of theory to data are generally good, the fits seem to be hinting that higher order correction from HQET may be needed to explain the b-quark fragmentation function at smaller values of momentum fraction.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

CfA4: LIGHT CURVES FOR 94 TYPE Ia SUPERNOVAE

We present multi-band optical photometry of 94 spectroscopically confirmed Type Ia supernovae (SNe Ia) in the redshift range 0.0055-0.073, obtained between 2006 and 2011. There are a total of 5522 light-curve points. We show that our natural-system SN photometry has a precision of {approx}< 0.03 mag in BVr'i', {approx}< 0.06 mag in u', and {approx}< 0.07 mag in U for points brighter than 17.5 mag and estimate that it has a systematic uncertainty of 0.014, 0.010, 0.012, 0.014, 0.046, and 0.073 mag in BVr'i'u'U, respectively. Comparisons of our standard-system photometry with published SN Ia light curves and comparison stars reveal mean agreement across samples in the range of {approx}0.00-0.03 mag. We discuss the recent measurements of our telescope-plus-detector throughput by direct monochromatic illumination by Cramer et al. This technique measures the whole optical path through the telescope, auxiliary optics, filters, and detector under the same conditions used to make SN measurements. Extremely well characterized natural-system passbands (both in wavelength and over time) are crucial for the next generation of SN Ia photometry to reach the 0.01 mag accuracy level. The current sample of low-z SNe Ia is now sufficiently large to remove most of the statistical sampling error from the dark-energy error budget. But pursuing the dark-energy systematic errors by determining highly accurate detector passbands, combining optical and near-infrared (NIR) photometry and spectra, using the nearby sample to illuminate the population properties of SNe Ia, and measuring the local departures from the Hubble flow will benefit from larger, carefully measured nearby samples.

79 ASTRONOMY AND ASTROPHYSICS↗

The intrinsic quasar luminosity function: Accounting for accretion disk anisotropy

Quasar luminosity functions are a fundamental probe of the growth and evolution of supermassive black holes. Measuring the intrinsic luminosity function is difficult in practice, due to a multitude of observational and systematic effects. As sample sizes increase and measurement errors drop, characterizing the systematic effects is becoming more important. It is well known that the continuum emission from the accretion disk of quasars is anisotropic—in part due to its disk-like structure—but current luminosity function calculations effectively assume isotropy over the range of unobscured lines of sight. Here, we provide the first steps in characterizing the effect of random quasar orientations and simple models of anisotropy on observed luminosity functions. We find that the effect of orientation is not insignificant and exceeds other potential corrections such as those from gravitational lensing of foreground structures. We argue that current observational constraints may overestimate the intrinsic luminosity function by as much as a factor of ∼2 on the bright end. This has implications for models of quasars and their role in the universe, such as quasars' contribution to cosmological backgrounds.

79 ASTRONOMY AND ASTROPHYSICS↗

TH-B-BRC-00: How to Identify and Resolve Potential Clinical Errors Before They Impact Patients Treatment: Lessons Learned

Radiation treatment consists of a chain of events influenced by the quality of machine operation, beam data commissioning, machine calibration, patient specific data, simulation, treatment planning, imaging and treatment delivery. There is always a chance that the clinical medical physicist may make or fail to detect an error in one of the events that may impact on the patient’s treatment. In the clinical scenario, errors may be systematic and, without peer review, may have a low detectability because they are not part of routine QA procedures. During treatment, there might be errors on machine that needs attention. External reviews of some of the treatment delivery components by independent reviewers, like IROC, can detect errors, but may not be timely. The goal of this session is to help junior clinical physicists identify potential errors as well as the approach of quality assurance to perform a root cause analysis to find and eliminate an error and to continually monitor for errors. A compilation of potential errors will be presented by examples of the thought process required to spot the error and determine the root cause. Examples may include unusual machine operation, erratic electrometer reading, consistent lower electron output, variation in photon output, body parts inadvertently left in beam, unusual treatment plan, poor normalization, hot spots etc. Awareness of the possibility and detection of error in any link of the treatment process chain will help improve the safe and accurate delivery of radiation to patients. Four experts will discuss how to identify errors in four areas of clinical treatment. D. Followill, NIH grant CA 180803.

60 APPLIED LIFE SCIENCES↗

TH-B-BRC-01: How to Identify and Resolve Potential Clinical Errors

Radiation treatment consists of a chain of events influenced by the quality of machine operation, beam data commissioning, machine calibration, patient specific data, simulation, treatment planning, imaging and treatment delivery. There is always a chance that the clinical medical physicist may make or fail to detect an error in one of the events that may impact on the patient’s treatment. In the clinical scenario, errors may be systematic and, without peer review, may have a low detectability because they are not part of routine QA procedures. During treatment, there might be errors on machine that needs attention. External reviews of some of the treatment delivery components by independent reviewers, like IROC, can detect errors, but may not be timely. The goal of this session is to help junior clinical physicists identify potential errors as well as the approach of quality assurance to perform a root cause analysis to find and eliminate an error and to continually monitor for errors. A compilation of potential errors will be presented by examples of the thought process required to spot the error and determine the root cause. Examples may include unusual machine operation, erratic electrometer reading, consistent lower electron output, variation in photon output, body parts inadvertently left in beam, unusual treatment plan, poor normalization, hot spots etc. Awareness of the possibility and detection of error in any link of the treatment process chain will help improve the safe and accurate delivery of radiation to patients. Four experts will discuss how to identify errors in four areas of clinical treatment. D. Followill, NIH grant CA 180803.

60 APPLIED LIFE SCIENCES↗