Errors In Dose Estimates Research Articles

Abstract PR001: Radiation dose estimates via live, optical imaging are highly dependent upon patient skin tone

Abstract Introduction: New medical technologies must be tested across diverse populations to ensure efficacy for all patients. In the last decade, a novel technique for imaging in vivo radiation dose was developed to mitigate clinical radiotherapy (RT) incidents. Named Cherenkov imaging (CI), this technology captures the inherent light emission from ionizing radiation interacting with tissue during RT and allows for spatial verification of dose across a patient surface compared to their plan. Recent efforts have been made to use CI to quantitatively assess the true dose delivered across a patient’s surface in real-time, but many patient-specific factors prevent developing a direct Cherenkov-to-dose calibration until addressed. Melanin, a known absorber of light including Cherenkov wavelengths, is the most influential. Early phantom studies showed a near 45% change in emission across a range of skin tones for the same dose. Up until now, further investigation into this effect has been limited to phantoms due to a low number of in vivo CI studies and predominantly Caucasian catchment area demographics. We present a first detailed analysis of imaging patients with a wider range of skin tones and quantifying the effect that it has on dose estimation errors. Methods: A multi-institutional partnership was developed to expand patient demographics and increase diverse skin tone representation. All CI was completed with time-gated iCMOS cameras that capture the low light emission from tissue during RT. Cherenkov images were normalized by absolute planned dose and bulk tissue heterogeneities to minimize non-linear effects outside of skin tone. Patients were initially categorized by ethnicity and their skin tones were quantified by analysis of calibrated color photography. Average Cherenkov light intensity per dose was compared across various skin tones towards developing a calibration system for quantifying dose from the corrected signals. Results: In vivo Cherenkov images exhibit a nearly 220% decrease in signal across a range of skin tones, from White to Black/African American patients, greatly affecting the Cherenkov-to-dose calibration. However, a linear correlation exists between quantitative skin luminosity and dose-normalized Cherenkov emission. Thus, quantifying skin luminosity provides a method to normalize out the effect of skin tone and minimize the in vivo dose estimation errors across diverse patient demographics. Conclusion: This study addresses the critically important issue of developing optical tools that are appropriately calibrated for all skin tones. In vivo CI must be calibrated by skin tone for dosimetric assessments. We have shown that it is not only feasible to image dark skin patients, but possible to quantify the effect that a range of skin tones has on CI for a given dose. Using this information, we can develop a skin tone normalization algorithm to minimize dose estimation errors. Future work will focus on expanding our patient dataset to even darker skin tones through active recruitment efforts in the participating clinics. Citation Format: Savannah Decker, Jacqueline Andreozzi, Diego Hernandez, Daniel Alexander, Vihan Wickramasinghe, Ibrahim Oraiqat, Erli Chen, Iman Washington, Rongxiao Zhang, Lesley Jarvis, Petr Bruza, David Gladstone, Brian Pogue. Radiation dose estimates via live, optical imaging are highly dependent upon patient skin tone [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr PR001.

Comparison of voxel S-value methods for personalized voxel-based dosimetry of 177 Lu-DOTATATE.

Voxel-based dosimetry is potentially accurate than organ-based dosimetry because it considers the anatomical variations in each individual and the heterogeneous radioactivity distribution in each organ. Here, voxel-based dosimetry for 177 Lu-DOTATATE therapy was performed using single and multiple voxel S-value (VSV) methods and compared with Monte Carlo simulations. To verify these methods, we adopted sequential 177 Lu-DOTATATE single-photon emission computed tomography and X-ray computed tomography (SPECT/CT) dataset acquired from Sunway Medical Centre using the major vendor's SPECT/CT scanner (Siemens Symbia Intevo). The administered activity of 177 Lu-DOTATATE was 7.99±0.36GBq. SPECT/CT images were acquired 0.5, 4, 24, and 48h after injection in Sunway Medical Centre. For the multiple VSV method, VSV kernels of 177 Lu in media with various densities were generated by Geant4 Application for Emission Tomography (GATE) simulation first. The second step involved the convolution of the time-integrated activity map with each kernel to produce medium-specific dose maps. Third, each medium-specific dose map was masked using binary medium masks, which were generated from CT-based density maps. Finally, all masked dose maps were summed to generate the final dose map. VSV methods with four different VSV sets (1, 4, 10, and 20 VSVs) were compared. Voxel-wise density correction for the single VSV method was also performed. The absorbed doses in the kidneys, bone marrow, and tumors were analyzed, and the relative errors between the VSV and Monte Carlo simulation approaches were estimated. Organ-based dosimetry using Organ Level INternal Dose Assessment/EXponential Modeling (OLINDA/EXM) was also compared. The accuracy of the multiple VSV approach increased with the number of dose kernels. The average dose estimation errors of a single VSV with density correction and 20 VSVs were less than 6% in most cases, although organ-based dosimetry using OLINDA/EXM yielded an error of up to 123%. The advantages of the single VSV method with density correction and the 20 VSVs over organ-based dosimetry were most evident in bone marrow and bone-metastatic tumors with heterogeneous medium properties. The single VSV method with density correction and multiple VSV method with 20 dose kernels enabled fast and accurate radiation dose estimation. Accordingly, voxel-based dosimetry methods can be useful for managing administration activity and for investigating tumor dose responses to further increase the therapeutic efficacy of 177 Lu-DOTATATE.

Dosimetric accuracy of a cross-calibration coefficient for plane-parallel ionization chamber obtained in low-energy electron beams using various cylindrical dosimeters

Abstract Introduction: The accuracy of the cross-calibration procedure depends on ionization chamber type, both used as reference one and under consideration. Also, the beam energy and phantom medium could influence the precision of cross calibration coefficient, resulting in a systematic error in dose estimation and thus could influence the linac beam output checking. This will result in a systematic mismatch between dose calculated in treatment planning system and delivered to the patient. Material and methods: The usage of FC65-G, CC13 and CC01 thimble reference chambers as well as 6, 9, and 15 MeV electron beams has been analyzed. A plane-parallel PPC05 chamber was calibrated since scarce literature data are available for this dosimeter type. The influence of measurement medium and an effective point of measurement (EPOM) on obtained results are also presented. Results: Dose reconstruction precision of ~0.1% for PPC05 chamber could be obtained when cross-calibration is based on a thimble CC13 chamber. Nd,w,Qcross obtained in beam ≥ 9MeV gives 0.1 – 0.5% precision of dose reconstruction. Without beam quality correction, 15 MeV Nd,w,Qcross is 10% lower than Co-60 Nd,w,0. Various EPOM shifts resulted in up to 0.6% discrepancies in Nd,w,Qcross values. Conclusions: Ionization chamber with small active volume and tissue-equivalent materials supplies more accurate cross-calibration coefficients in the range of 6 – 15 MeV electron beams. In the case of 6 and 9 MeV beams, the exact position of an effective point of measurement is of minor importance. In-water cross-calibration coefficient can be used in a solid medium without loss of dose accuracy.

Quantitative investigation of dose accumulation errors from intra-fraction motion in MRgRT for prostate cancer

Accurate spatial dose delivery in radiotherapy is frequently complicated due to changes in the patient’s internal anatomy during and in-between therapy segments. The recent introduction of hybrid MRI radiotherapy systems allows unequaled soft-tissue visualization during radiation delivery and can be used for dose reconstruction to quantify the impact of motion. To this end, knowledge of anatomical deformations obtained from continuous monitoring during treatment has to be combined with information on the spatio-temporal dose delivery to perform motion-compensated dose accumulation (MCDA). Here, the influence of the choice of deformable image registration algorithm, dose warping strategy, and magnetic resonance image resolution and signal-to-noise-ratio on the resulting MCDA is investigated. For a quantitative investigation, four 4D MRI-datasets representing typical patient observed motion patterns are generated using finite element modeling and serve as a gold standard. Energy delivery is simulated intra-fractionally in the deformed image space and, subsequently, MCDA-processed. Finally, the results are substantiated by comparing MCDA strategies on clinically acquired patient data. It is shown that MCDA is needed for correct quantitative dose reconstruction. For prostate treatments, using the energy per mass transfer dose warping strategy has the largest influence on decreasing dose estimation errors.

Patient-Informed Organ Dose Estimation in Clinical CT: Implementation and Effective Dose Assessment in 1048 Clinical Patients.

OBJECTIVE. The purpose of this study is to comprehensively implement a patient-informed organ dose monitoring framework for clinical CT and compare the effective dose (ED) according to the patient-informed organ dose with ED according to the dose-length product (DLP) in 1048 patients. MATERIALS AND METHODS. Organ doses for a given examination are computed by matching the topogram to a computational phantom from a library of anthropomorphic phantoms and scaling the fixed tube current dose coefficients by the examination volume CT dose index (CTDIvol) and the tube-current modulation using a previously validated convolution-based technique. In this study, the library was expanded to 58 adult, 56 pediatric, five pregnant, and 12 International Commission on Radiological Protection (ICRP) reference models, and the technique was extended to include multiple protocols, a bias correction, and uncertainty estimates. The method was implemented in a clinical monitoring system to estimate organ dose and organ dose-based ED for 647 abdomen-pelvis and 401 chest examinations, which were compared with DLP-based ED using a t test. RESULTS. For the majority of the organs, the maximum errors in organ dose estimation were 18% and 8%, averaged across all protocols, without and with bias correction, respectively. For the patient examinations, DLP-based ED was significantly different from organ dose-based ED by as much as 190.9% and 234.7% for chest and abdomen-pelvis scans, respectively (mean, 9.0% and 24.3%). The differences were statistically significant (p < .001) and exhibited overestimation for larger-sized patients and underestimation for smaller-sized patients. CONCLUSION. A patient-informed organ dose estimation framework was comprehensively implemented applicable to clinical imaging of adult, pediatric, and pregnant patients. Compared with organ dose-based ED, DLP-based ED may overestimate effective dose for larger-sized patients and underestimate it for smaller-sized patients.

Specific absorbed fractions and radionuclide S-values for tumors of varying size and composition

Accurate estimates of tumor absorbed dose are essential for the evaluation of treatment efficacy in radiopharmaceutical cancer therapy. Although tumor dosimetry via the MIRD schema has been previously investigated, prior studies have been limited to the consideration of soft-tissue tumors. In the present study, specific absorbed fractions (SAFs) for monoenergetic photons, electrons, and alpha particles in tumors of varying compositions were computed using Monte Carlo simulations in MCNPX after which self-irradiation S-values for 22 radionuclides (along with 14 additional alpha-emitter progeny) were generated for tumors of both varying size and tissue composition. The tumors were modeled as spheres with radii ranging from 0.10 cm to 6.0 cm and with compositions varying from 100% soft tissue (ST) to 100% mineral bone (MB). The energies of the photons and electrons were varied on a logarithm energy grid from 10 keV to 10 MeV. The energies of alpha particles were varied along a linear energy grid from 0.5 MeV to 12 MeV. In all cases, a homogenous activity distribution was assumed throughout the tumor volume. Furthermore, to assess the effect of tumor shape, several ellipsoidal tumors of different compositions were modeled and absorbed fractions were computed for monoenergetic electrons and photons. S-values were then generated using detailed decay data from the 2008 MIRD Monograph on Radionuclide Data and Decay Schemes. Our study results demonstrate that a soft-tissue model yields relative errors of 25% and 71% in the absorbed fraction assigned to uniform sources of 1.5 MeV electrons and 100 keV photons, respectively, localized within a 1 cm diameter tumor of MB. The data further show that absorbed fractions for moderate ellipsoids can be well approximated by a spherical shape of equal mass within a relative error of < 8%. S-values for 22 radionuclides (and their daughter progeny) were computed with results demonstrating how relative errors in SAFs could propagate to relative errors in tumor dose estimates as high as 86%. A comprehensive data set of radionuclide S-values by tumor size and tissue composition is provided for application of the MIRD schema for tumor dosimetry in radiopharmaceutical therapy.

Lifetime Mortality Risk from Cancer and Circulatory Disease Predicted from the Japanese Atomic Bomb Survivor Life Span Study Data Taking Account of Dose Measurement Error.

Dosimetric measurement error is known to potentially bias the magnitude of the dose response, and can also affect the shape of dose response. In this report, generalized relative and absolute rate models are fitted to the latest Japanese atomic bomb survivor solid cancer, leukemia and circulatory disease mortality data (followed from 1950 through 2003), with the latest (DS02R1) dosimetry, using Bayesian techniques to adjust for errors in dose estimates and assessing other model uncertainties. Linear-quadratic models are fitted and used to assess lifetime mortality risks for contemporary UK, USA, French, Russian, Japanese and Chinese populations. For a test dose of 0.1 Gy absorbed dose weighted by neutron relative biological effectiveness, solid cancer, leukemia and circulatory disease mortality risks for a UK population using a generalized linear-quadratic relative rate model were estimated to be 3.88% Gy-1 [95% Bayesian credible interval (BCI): 1.17, 6.97], 0.35% Gy-1 (95% BCI: -0.03, 0.78) and 2.24% Gy-1 (95% BCI: -0.17, 13.76), respectively. Using a generalized absolute rate linear-quadratic model at 0.1 Gy, the lifetime risks for these three end points were estimated to be 3.56% Gy-1 (95% BCI: 0.54, 6.78), 0.41% Gy-1 (95% BCI: 0.01, 0.86) and 1.56% Gy-1 (95% BCI: -1.10, 7.21), respectively. There was substantial evidence of curvature for solid cancer (in particular, the group of solid cancers excluding lung, breast and stomach cancers) and leukemia, so that for solid cancer and leukemia, estimates of excess risk per unit dose were nearly doubled by increasing the dose from 0.01 to 1.0 Gy, with most of the increase occurring in the interval from 0.1 to 1.0 Gy. For circulatory disease, the dose-response curvature was inverse, so that risk per unit dose was nearly halved by going from 0.01 t o 1.0 Gy weighted absorbed dose, although there were substantial uncertainties. In general, there were higher radiation risks for females compared to males. This was true for solid cancer and circulatory disease overall, as well as for lung, breast, stomach and the group of other solid cancers, and was the case whether relative or absolute rate projection models were employed; however, for leukemia this pattern was reversed. Risk estimates varied somewhat between populations, with lower cancer risks in aggregate for China and Russia, but higher circulatory disease risks for Russia, particularly using the relative rate model. There was more pronounced variation for certain cancer sites and certain types of projection models, so that breast cancer risk was markedly lower in China and Japan using a relative rate model, but the opposite was the case for stomach cancer. There was less variation between countries using the absolute rate models for stomach cancer and breast cancer, but this was not the case for lung cancer and the group of other solid cancers, or for circulatory disease.

Strengths and Weaknesses of Dosimetry Used in Studies of Low-Dose Radiation Exposure and Cancer.

A monograph systematically evaluating recent evidence on the dose-response relationship between low-dose ionizing radiation exposure and cancer risk required a critical appraisal of dosimetry methods in 26 potentially informative studies. The relevant literature included studies published in 2006-2017. Studies comprised case-control and cohort designs examining populations predominantly exposed to sparsely ionizing radiation, mostly from external sources, resulting in average doses of no more than 100 mGy. At least two dosimetrists reviewed each study and appraised the strengths and weaknesses of the dosimetry systems used, including assessment of sources and effects of dose estimation error. An overarching concern was whether dose error might cause the spurious appearance of a dose-response where none was present. The review included 8 environmental, 4 medical, and 14 occupational studies that varied in properties relative to evaluation criteria. Treatment of dose estimation error also varied among studies, although few conducted a comprehensive evaluation. Six studies appeared to have known or suspected biases in dose estimates. The potential for these biases to cause a spurious dose-response association was constrained to three case-control studies that relied extensively on information gathered in interviews conducted after case ascertainment. The potential for spurious dose-response associations from dose information appeared limited to case-control studies vulnerable to recall errors that may be differential by case status. Otherwise, risk estimates appeared reasonably free of a substantial bias from dose estimation error. Future studies would benefit from a comprehensive evaluation of dose estimation errors, including methods accounting for their potential effects on dose-response associations.

Factors affecting accuracy of S values and determination of time-integrated activity in clinical Lu-177 dosimetry.

In any radiotherapy, the absorbed dose needs to be estimated based on two factors, the time-integrated activity of the administered radiopharmaceutical and the patient-specific dose kernel. In this study, we consider the uncertainty with which such absorbed dose estimation can be achieved in a clinical environment. To calculate the total error of dose estimation we considered the following aspects: The error resulting from computing the time-integrated activity, the difference between the S-value and the patient specific full Monte Carlo simulation, the error from segmenting the volume-of-interest (kidney) and the intrinsic error of the activimeter. The total relative error in dose estimation can amount to 25.0% and is composed of the error of the time-integrated activity 17.1%, the error of the S-value 16.7%, the segmentation error 5.4% and the activimeter accuracy 5.0%. Errors from estimating the time-integrated activity and approximations applied to dose kernel computations contribute about equally and represent the dominant contributions far exceeding the contributions from VOI segmentation and activimeter accuracy.

MPS dose reconstruction for internal emitters: some site-specific issues and approaches

Background As part of the Million Person Study (MPS), dose reconstructions for internal emitters have been performed for several U.S. facilities where large quantities of radionuclides were handled. The main challenges and dominant sources of potential error in retrospective dose estimates for internally exposed workers have been found to vary from site to site. This article discusses some important issues encountered in dose reconstructions performed for selected MPS sites and the approaches used to address those issues. The focus is on some foundational components of retrospective dose assessments that have received little attention in the literature. Methods The discussion is built around illustrative exposure data and dose reconstructions for workers at selected facilities addressed in the MPS. Related findings at some non-MPS sites are also discussed. Results Each of the following items has been found to be a major source of potential error in reconstructed tissue doses for some MPS sites: identification of all dosimetrically important internal emitters; the time pattern of intake; the mode(s) of intake; reliability of bioassay measurements; application of surrogate (coworker) information in lieu of, or in conjunction with, worker-specific monitoring data; the chemical and physical forms of inhaled radionuclides; and the relation of air monitoring data to actual intake. Conclusions (1) Much of the dose reconstruction effort for internal emitters should be devoted to development of best feasible exposure scenarios. (2) Coworker data should be used to assign exposure scenarios or dose estimates to workers with missing exposure data only if there is compelling evidence of similar coworker exposure. (3) Bioassay data for some radionuclides and periods of operation at MPS sites are of questionable reliability due to sizable uncertainties associated with contamination, recovery, or background issues. (4) Dose estimates derived solely from air monitoring data should be treated as highly uncertain values in the absence of site-specific information demonstrating that the data are reasonably predictive of intake. (5) For intakes known or assumed to be via inhalation, the uncertainty in lung dose typically is much greater than the uncertainty in dose to systemic tissues, when dose estimates are based on urinary excretion data. (6) The lung dose estimate often can be improved through development of site-specific respiratory absorption parameter values. (7) There is generally insufficient site-specific information to justify development of site-specific systemic models.

RADIATION DOSE ESTIMATION BY COMPLETELY AUTOMATED INTERPRETATION OF THE DICENTRIC CHROMOSOME ASSAY.

Accuracy of the automated dicentric chromosome (DC) assay relies on metaphase image selection. This study validates a software framework to find the best image selection models that mitigate inter-sample variability. Evaluation methods to determine model quality include the Poisson goodness-of-fit of DC distributions for each sample, residuals after calibration curve fitting and leave-one-out dose estimation errors. The process iteratively searches a pool of selection model candidates by modifying statistical and filter cut-offs to rank the best candidates according to their respective evaluation scores. Evaluation scores minimize the sum of squared errors relative to the actual radiation dose of the calibration samples. For one laboratory, the minimum score for the curve fit residual method was 0.0475 Gy2, compared to 1.1975 Gy2 without image selection. Application of optimal selection models using samples of unknown exposure produced estimated doses within 0.5 Gy of physical dose. Model optimization standardizes image selection among samples and provides relief from manual DC scoring, improving accuracy and consistency of dose estimation.

Effects of incomplete residential histories on studies of environmental exposure with application to childhood leukaemia and background radiation

When evaluating environmental exposures, residential exposures are often most relevant. In most countries, it is impossible to establish full residential histories. In recent publications, childhood leukaemia and background radiation have been studied with and without full residential histories. This paper investigates the consequences of lacking such full data.Data from a nationwide Finnish Case-Control study of Childhood Leukaemia and gamma rays were analysed. This included 1093 children diagnosed with leukaemia in Finland in 1990–2011. Each case was matched by gender and year of birth to three controls. Full residential histories were available. The dose estimates were based on outdoor background radiation measurements. The indoor dose rates were obtained with a dwelling type specific conversion coefficient and the individual time-weighted mean red bone marrow dose rates were calculated using age-specific indoor occupancy and the age and gender of the child. Radiation from Chernobyl fallout was included and a 2-year latency period assumed.The median separation between successive dwellings was 3.4 km and median difference in red bone marrow dose 2.9 nSv/h. The Pearson correlation between the indoor red bone marrow dose rates of successive dwellings was 0.62 (95% CI 0.60, 0.64). The odds ratio for a 10 nSv/h increase in dose rate with full residential histories was 1.01 (95% CI 0.97, 1.05). Similar odds ratios were calculated with dose rates based on only the first dwelling (1.02, 95% CI 0.99, 1.05) and only the last dwelling (1.00, 95% CI 0.98, 1.03) and for subjects who had lived only in a single dwelling (1.05, 95% CI 0.98, 1.10).Knowledge of full residential histories would always be the option of choice. However, due to the strong correlation between exposure estimates in successive dwellings and the uncertainty about the most relevant exposure period, estimation of overall exposure level from a single address is also informative. Error in dose estimation is likely to cause some degree of classical measurement error resulting in bias towards the null.

Accurate cytogenetic biodosimetry through automated dicentric chromosome curation and metaphase cell selection.

Accurate digital image analysis of abnormal microscopic structures relies on high quality images and on minimizing the rates of false positive (FP) and negative objects in images. Cytogenetic biodosimetry detects dicentric chromosomes (DCs) that arise from exposure to ionizing radiation, and determines radiation dose received based on DC frequency. Improvements in automated DC recognition increase the accuracy of dose estimates by reclassifying FP DCs as monocentric chromosomes or chromosome fragments. We also present image segmentation methods to rank high quality digital metaphase images and eliminate suboptimal metaphase cells. A set of chromosome morphology segmentation methods selectively filtered out FP DCs arising primarily from sister chromatid separation, chromosome fragmentation, and cellular debris. This reduced FPs by an average of 55% and was highly specific to these abnormal structures (≥97.7%) in three samples. Additional filters selectively removed images with incomplete, highly overlapped, or missing metaphase cells, or with poor overall chromosome morphologies that increased FP rates. Image selection is optimized and FP DCs are minimized by combining multiple feature based segmentation filters and a novel image sorting procedure based on the known distribution of chromosome lengths. Applying the same image segmentation filtering procedures to both calibration and test samples reduced the average dose estimation error from 0.4 Gy to <0.2 Gy, obviating the need to first manually review these images. This reliable and scalable solution enables batch processing for multiple samples of unknown dose, and meets current requirements for triage radiation biodosimetry of high quality metaphase cell preparations.

Body Size-Specific Organ and Effective Doses of Chest CT Screening Examinations of the National Lung Screening Trial.

We calculated body size-specific organ and effective doses for 23,734 participants in the National Lung Screening Trial (NLST) using a CT dose calculator. We collected participant-specific technical parameters of 23,734 participants who underwent CT in the clinical trial. For each participant, we calculated two sets of organ doses using two methods. First, we computed body size-specific organ and effective doses using the National Cancer Institute CT (NCICT) dosimetry program, which is based on dose coefficients derived from a library of body size-dependent adult male and female computational phantoms. We then recalculated organ and effective doses using dose coefficients from reference size phantoms for all examinations to investigate potential errors caused by the lack of body size consideration in the dose calculations. The underweight participants (body mass index [BMI; weight in kilograms divided by the square of height in meters] < 18.5) received 1.3-fold greater lung dose (median, 4.93 mGy) than the obese participants (BMI > 30) (3.90 mGy). Thyroid doses were approximately 1.3- to 1.6-fold greater than the lung doses (6.3-6.5 mGy). The reference phantom-based dose calculation underestimates the body size-specific lung dose by up to 50% for the underweight participants and overestimates that value by up to 200% for the overweight participants. The median effective dose ranges from 2.01 mSv in obese participants to 2.80 mSv in underweight participants. Body size-specific organ and effective doses were computed for 23,734 NLST participants who underwent low-dose CT screening. The use of reference size phantoms can lead to significant errors in organ dose estimates when body size is not considered in the dose assessment.

Radiation treatment of patients with cardiac pacemaker: Wedge type effect estimation

Introduction An increasing number of pacemaker patients are receiving radiotherapy in various sites in our department. The need hence arises to accurately determine the radiation burden of pacemaker devices for radiotherapy patients, given the limited tolerance of such devices reported by manufacturers and select the best treatment parameters during the design of their treatment plan. Purpose This study aims to investigate the dependence of pacemaker dose on the type of wedge filter implemented in the radiotherapy machine, comparing the effect of dynamic wedges of various angles to the effect of the universal motorized wedge. Materials and methods In this study two different linear accelerators were used. All measurements were performed with 6 MV photon beams, at a range of distances from the field centre, for wedged and open beams. Dose was measured for dynamic wedges 15°, 30°, 45° and 60° and corresponding motorized wedge angles, for various wedge orientations. Moreover, the above estimated doses were compared with the data from two different treatment planning systems. Results The effect of the wedge filter can elevate the pacemaker dose significantly compared to that of an open field. Comparing the wedge designs measured in this study, the use of a dynamic wedge decreases the pacemaker burden. The pacemaker estimated dose from treatment planning systems diverged from the measured values. Conclusion This study provides data about the pacemaker exposure for different wedge systems. Furthermore, the treatment planning system’s dose estimation errors can not be neglected.

Quantification of residual dose estimation error on log file-based patient dose calculation

PurposeThe log file-based patient dose estimation includes a residual dose estimation error caused by leaf miscalibration, which cannot be reflected on the estimated dose. The purpose of this study is to determine this residual dose estimation error. Methods and materialsModified log files for seven head-and-neck and prostate volumetric modulated arc therapy (VMAT) plans simulating leaf miscalibration were generated by shifting both leaf banks (systematic leaf gap errors: ±2.0, ±1.0, and ±0.5mm in opposite directions and systematic leaf shifts: ±1.0mm in the same direction) using MATLAB-based (MathWorks, Natick, MA) in-house software. The generated modified and non-modified log files were imported back into the treatment planning system and recalculated. Subsequently, the generalized equivalent uniform dose (gEUD) was quantified for the definition of the planning target volume (PTV) and organs at risks. ResultsFor MLC leaves calibrated within ±0.5mm, the quantified residual dose estimation errors that obtained from the slope of the linear regression of gEUD changes between non- and modified log file doses per leaf gap are in head-and-neck plans 1.32±0.27% and 0.82±0.17Gy for PTV and spinal cord, respectively, and in prostate plans 1.22±0.36%, 0.95±0.14Gy, and 0.45±0.08Gy for PTV, rectum, and bladder, respectively. ConclusionsIn this work, we determine the residual dose estimation errors for VMAT delivery using the log file-based patient dose calculation according to the MLC calibration accuracy.

Bayesian dose-response analysis for epidemiological studies with complex uncertainty in dose estimation.

Most conventional risk analysis methods rely on a single best estimate of exposure per person, which does not allow for adjustment for exposure-related uncertainty. Here, we propose a Bayesian model averaging method to properly quantify the relationship between radiation dose and disease outcomes by accounting for shared and unshared uncertainty in estimated dose. Our Bayesian risk analysis method utilizes multiple realizations of sets (vectors) of doses generated by a two-dimensional Monte Carlo simulation method that properly separates shared and unshared errors in dose estimation. The exposure model used in this work is taken from a study of the risk of thyroid nodules among a cohort of 2376 subjects who were exposed to fallout from nuclear testing in Kazakhstan. We assessed the performance of our method through an extensive series of simulations and comparisons against conventional regression risk analysis methods. When the estimated doses contain relatively small amounts of uncertainty, the Bayesian method using multiple a priori plausible draws of dose vectors gave similar results to the conventional regression-based methods of dose-response analysis. However, when large and complex mixtures of shared and unshared uncertainties are present, the Bayesian method using multiple dose vectors had significantly lower relative bias than conventional regression-based risk analysis methods and better coverage, that is, a markedly increased capability to include the true risk coefficient within the 95% credible interval of the Bayesian-based risk estimate. An evaluation of the dose-response using our method is presented for an epidemiological study of thyroid disease following radiation exposure.

TU‐G‐BRD‐09: Evaluation of Patient DVH‐Based QA Metrics for Prostate VMAT: Correlation Between Accuracy of Estimated 3D Patient Dose and MLC Position Error

Purpose:The purpose of this study was to evaluate the accuracy of patient DVH‐based QA metrics and test the hypothesis: measurement‐guided 3D dose reconstruction (MGDR) captures the induced dose error.Methods:We used 3DVH software with an ArcCHECK to estimate 3D patient dose by MGDR. Two different calculating modes of MGDR were used: “Normal Sensitivity” and “High Sensitivity”. Ten prostate cancer patients treated with hypo‐fractionated VMAT (67.6 Gy/26 Fr) were studied. For the baseline plan, we induced MLC errors (−0.75, −0.5, −0.25, 0.25, 0.5 and 0.75 mm for each single bank), generated by in‐house software. We compared the 3D patient dose estimated by 3DVH and that calculated by the treatment planning system. We evaluated the correlation between dose estimation error and MLC position error.Results:Slopes of linear fit to dose estimation error versus MLC position error for mean dose and D95 to the PTV were 1.76 and 1.40% mm‐1, respectively, for “Normal Sensitivity” and −0.53 and −0.88% mm‐1, respectively, for “High Sensitivity”, showing better accuracy for “High Sensitivity” than “Normal Sensitivity”. On the other hand, the slopes for mean dose to the rectum and bladder and V55 to the rectum and bladder were −1.00, −0.55, −3.53 and −1.85% mm‐1, respectively, for “Normal Sensitivity” and −2.89, −2.39, −6.24 and −4.11% mm‐1, respectively, for “High Sensitivity”, showing significant better accuracy for “Normal Sensitivity” than “High Sensitivity”.Conclusion:Our results showed that 3DVH had some residual error for both sensitivities, indicating the MGDR could capture a part of the induced error but not all of the induced error.Furthermore, we found that “Normal Sensitivity” might have better accuracy for the DVH metric for PTV and that “High Sensitivity” might have better accuracy for DVH metrics for the rectum and bladder. We must be willing to tolerate this residual error in clinical care.

Shared dosimetry error in epidemiological dose-response analyses.

Radiation dose reconstruction systems for large-scale epidemiological studies are sophisticated both in providing estimates of dose and in representing dosimetry uncertainty. For example, a computer program was used by the Hanford Thyroid Disease Study to provide 100 realizations of possible dose to study participants. The variation in realizations reflected the range of possible dose for each cohort member consistent with the data on dose determinates in the cohort. Another example is the Mayak Worker Dosimetry System 2013 which estimates both external and internal exposures and provides multiple realizations of "possible" dose history to workers given dose determinants. This paper takes up the problem of dealing with complex dosimetry systems that provide multiple realizations of dose in an epidemiologic analysis. In this paper we derive expected scores and the information matrix for a model used widely in radiation epidemiology, namely the linear excess relative risk (ERR) model that allows for a linear dose response (risk in relation to radiation) and distinguishes between modifiers of background rates and of the excess risk due to exposure. We show that treating the mean dose for each individual (calculated by averaging over the realizations) as if it was true dose (ignoring both shared and unshared dosimetry errors) gives asymptotically unbiased estimates (i.e. the score has expectation zero) and valid tests of the null hypothesis that the ERR slope β is zero. Although the score is unbiased the information matrix (and hence the standard errors of the estimate of β) is biased for β≠0 when ignoring errors in dose estimates, and we show how to adjust the information matrix to remove this bias, using the multiple realizations of dose. The use of these methods in the context of several studies including, the Mayak Worker Cohort, and the U.S. Atomic Veterans Study, is discussed.

The Influence of Early Measurements Onto the Estimated Kidney Dose in [(177)Lu][DOTA(0),Tyr(3)]Octreotate Peptide Receptor Radiotherapy of Neuroendocrine Tumors.

Multiple measurements have been required to estimate the radiation dose to the kidneys resulting from [(177)Lu]DOTATATE therapy for neuroendocrine tumors. The aim of this study was to investigate the influence of early time-point measurement in the renal dose calculation. Anterior/posterior whole-body planar scintigraphy images were acquired at approx. 1, 24, 48, and 72 h after administration of [(177)Lu]DOTATATE. Furthermore, we acquired planar 1-bed dynamic recordings in 12 frames (5 min each) during the first hour. We assessed kidney exposure with a three-phase model consisting of a linear increase to the maximum within the initial minutes p.i., followed a bi-exponential decline. This three-phase-model served as reference for evaluating accuracy of dose estimates in 105 kidneys calculated by conventional mono-exponential fitting of the final three and four whole-body images. Mean effective half-life times for the reference model were 25.8 ± 12.0 min and 63.9 ± 17.6 h, predicting a mean renal dose of 5.7 ± 2.1 Gy. The effective half-life time was 46.3 ± 15.4 h for the last four and 63.3 ± 17.0 h for the last three data points. The mean start of the first whole-body measurement was 1.2 ± 0.1 h p.i. The ratio of fast to slow phases was 28.1 ± 23.9% at this time point, which caused a mean absolute percentage dose deviation of 12.4% for four data points, compared to 3.1% for three data points. At a mean time of 2.4 h p.i. (max 5.1 h), the ratio of fast to slow phase declined below 5%. Kinetic analysis of renal uptake using dynamic planar scans from the first hour after injection revealed a fast and a slow washout phase. Although the fast phase did not contribute substantially to the estimated renal dose, it could influence planar measurements performed within the first hours. We found that the presence of two clearance phases can hamper accurate dose estimation based on a single-phase model, resulting in approximately 12.4% dose underestimation, thus potentially resulting in overtreatment. In the absence of dynamic initial recordings, the first dosimetry measurements should therefore be obtained later than 3-5 h after [(177)Lu]DOTATATE injection. Omitting the early whole-body image reduced the dose estimation error to 3.1%.