BENCHMARKING AND IMPLEMENTATION OF A NEW INDEPENDENT MONTE CARLO DOSE CALCULATION QUALITY ASSURANCE AUDIT TOOL FOR CLINICAL TRIALS

Introduction Commercial treatment planning systems employ a variety of dose calculation algorithms to plan and predict the dose distributions a patient receives during external beam radiation therapy. Traditionally, the Radiological Physics Center has relied on measurements to assure that institutions participating in the National Cancer Institute sponsored clinical trials administer radiation in doses that are clinically comparable to those of other participating institutions. To complement the effort of the RPC, an independent dose calculation tool needs to be developed that will enable a generic method to determine patient dose distributions in three dimensions and to perform retrospective analysis of radiation delivered to patients who enrolled in past clinical trials. Methods A multi-source model representing output for Varian 6 MV and 10 MV photon beams was developed and evaluated. The Monte Carlo algorithm, know as the Dose Planning Method (DPM), was used to perform the dose calculations. The dose calculations were compared to measurements made in a water phantom and in anthropomorphic phantoms. Intensity modulated radiation therapy and stereotactic body radiation therapy techniques were used with the anthropomorphic phantoms. Finally, past patient treatment plans were selected and recalculated using DPM and contrasted against a commercial dose calculation algorithm. Results The multi-source model was validated for the Varian 6 MV and 10 MV photon beams. The benchmark evaluations demonstrated the ability of the model to accurately calculate dose for the Varian 6 MV and the Varian 10 MV source models. The patient calculations proved that the model was reproducible in determining dose under similar conditions described by the benchmark tests. Conclusions The dose calculation tool that relied on a multi-source model approach and used the DPM code to calculate dose was developed, validated, and benchmarked for the Varian 6 MV and 10 MV photon beams. Several patient dose distributions were contrasted against a commercial algorithm to provide a proof of principal to use as an application in monitoring clinical trial activity.

A 3-D CT assisted Monte Carlo evaluation of intracavitary brachytherapy implants

Intracavitary brachytherapy (ICB) combined with external beam irradiation for treatment of cervical cancer is highly successful in achieving local control. The M.D. Anderson Cancer Center employs Fletcher Suit Delclos (FSD) applicators. FSD applicators contain shields to limit dose to critical structures. Dosimetric evaluation of ICB implants is limited to assessing dose at reference points. These points serve as surrogates for treatment intensity and critical structure dose. Several studies have mentioned that the ICRU38 reference points inadequately characterize the dose distribution. Also, the ovoid shields are rarely considered in dosimetry. ^ The goal of this dissertation was to ascertain the influence of the ovoid shields on patient dose distributions. Monte Carlo dosimetry (MCD) was applied to patient computed tomography(CT) scans. These data were analyzed to determine the effect of the shields on dose to standard reference points and the bladder and rectum. The hypothesis of this work is that the ICRU38 bladder and rectal points computed conventionally are not clinically acceptable surrogates for the maximum dose points as determined by MCD. ^ MCD was applied to the tandem and ovoids. The FSD ovoids and tandem were modeled in a single input file that allowed dose to be calculated for any patient. Dose difference surface histograms(DDSH) were computed for the bladder and rectum. Reference point doses were compared between shielded and unshielded ovoids, and a commercial treatment planning system. ^ The results of this work showed the tandem tip screw caused a 33% reduction in dose. The ovoid shields reduced the dose by a maximum of 48.9%. DDSHs revealed on average 5% of the bladder surface area was spared 53 cGy and 5% of the rectal surface area was spared 195 cGy. The ovoid shields on average reduced the dose by 18% for the bladder point and 25% for the rectal point. The Student's t-test revealed the ICRU38 bladder and rectal points do not predict the maximum dose for these organs. ^ It is concluded that modeling the tandem and ovoid internal structures is necessary for accurate dose calculations, the bladder shielding segments may not be necessary, and that the ICRU38 bladder point is irrelevant. ^

Verification of intensity modulated stereotactic radiotherapy using Monte Carlo calculations and EPID dosimetry

The purpose of this work was to develop a comprehensive IMSRT QA procedure that examined, using EPID dosimetry and Monte Carlo (MC) calculations, each step in the treatment planning and delivery process. These steps included verification of the field shaping, treatment planning system (RTPS) dose calculations, and patient dose delivery. Verification of each step in the treatment process is assumed to result in correct dose delivery to the patient. ^ The accelerator MC model was verified against commissioning data for field sizes from 0.8 × 0.8 cm 2 to 10 × 10 cm 2. Depth doses were within 2% local percent difference (LPD) in low gradient regions and 1 mm distance to agreement (DTA) in high gradient regions. Lateral profiles were within 2% LPD in low gradient regions and 1 mm DTA in high gradient regions. Calculated output factors were within 1% of measurement for field sizes ≥1 × 1 cm2. ^ The measured and calculated pretreatment EPID dose patterns were compared using criteria of 5% LPD, 1 mm DTA, or 2% of central axis pixel value with ≥95% of compared points required to pass for successful verification. Pretreatment field verification resulted in 97% percent of the points passing. ^ The RTPS and Monte Carlo phantom dose calculations were compared using 5% LPD, 2 mm DTA, or 2% of the maximum dose with ≥95% of compared points required passing for successful verification. RTPS calculation verification resulted in 97% percent of the points passing. ^ The measured and calculated EPID exit dose patterns were compared using criteria of 5% LPD, 1 mm DTA, or 2% of central axis pixel value with ≥95% of compared points required to pass for successful verification. Exit dose verification resulted in 97% percent of the points passing. ^ Each of the processes above verified an individual step in the treatment planning and delivery process. The combination of these verification steps ensures accurate treatment delivery to the patient. This work shows that Monte Carlo calculations and EPID dosimetry can be used to quantitatively verify IMSRT treatments resulting in improved patient care and, potentially, improved clinical outcome. ^

Monte Carlo and analytical dose calculations for ocular proton therapy

Uveal melanoma is a rare but life-threatening form of ocular cancer. Contemporary treatment techniques include proton therapy, which enables conservation of the eye and its useful vision. Dose to the proximal structures is widely believed to play a role in treatment side effects, therefore, reliable dose estimates are required for properly evaluating the therapeutic value and complication risk of treatment plans. Unfortunately, current simplistic dose calculation algorithms can result in errors of up to 30% in the proximal region. In addition, they lack predictive methods for absolute dose per monitor unit (D/MU) values. ^ To facilitate more accurate dose predictions, a Monte Carlo model of an ocular proton nozzle was created and benchmarked against measured dose profiles to within ±3% or ±0.5 mm and D/MU values to within ±3%. The benchmarked Monte Carlo model was used to develop and validate a new broad beam dose algorithm that included the influence of edgescattered protons on the cross-field intensity profile, the effect of energy straggling in the distal portion of poly-energetic beams, and the proton fluence loss as a function of residual range. Generally, the analytical algorithm predicted relative dose distributions that were within ±3% or ±0.5 mm and absolute D/MU values that were within ±3% of Monte Carlo calculations. Slightly larger dose differences were observed at depths less than 7 mm, an effect attributed to the dose contributions of edge-scattered protons. Additional comparisons of Monte Carlo and broad beam dose predictions were made in a detailed eye model developed in this work, with generally similar findings. ^ Monte Carlo was shown to be an excellent predictor of the measured dose profiles and D/MU values and a valuable tool for developing and validating a broad beam dose algorithm for ocular proton therapy. The more detailed physics modeling by the Monte Carlo and broad beam dose algorithms represent an improvement in the accuracy of relative dose predictions over current techniques, and they provide absolute dose predictions. It is anticipated these improvements can be used to develop treatment strategies that reduce the incidence or severity of treatment complications by sparing normal tissue. ^

Lobe specific Ca2+-calmodulin nano-domain in neuronal spines: a single molecule level analysis.

Calmodulin (CaM) is a ubiquitous Ca(2+) buffer and second messenger that affects cellular function as diverse as cardiac excitability, synaptic plasticity, and gene transcription. In CA1 pyramidal neurons, CaM regulates two opposing Ca(2+)-dependent processes that underlie memory formation: long-term potentiation (LTP) and long-term depression (LTD). Induction of LTP and LTD require activation of Ca(2+)-CaM-dependent enzymes: Ca(2+)/CaM-dependent kinase II (CaMKII) and calcineurin, respectively. Yet, it remains unclear as to how Ca(2+) and CaM produce these two opposing effects, LTP and LTD. CaM binds 4 Ca(2+) ions: two in its N-terminal lobe and two in its C-terminal lobe. Experimental studies have shown that the N- and C-terminal lobes of CaM have different binding kinetics toward Ca(2+) and its downstream targets. This may suggest that each lobe of CaM differentially responds to Ca(2+) signal patterns. Here, we use a novel event-driven particle-based Monte Carlo simulation and statistical point pattern analysis to explore the spatial and temporal dynamics of lobe-specific Ca(2+)-CaM interaction at the single molecule level. We show that the N-lobe of CaM, but not the C-lobe, exhibits a nano-scale domain of activation that is highly sensitive to the location of Ca(2+) channels, and to the microscopic injection rate of Ca(2+) ions. We also demonstrate that Ca(2+) saturation takes place via two different pathways depending on the Ca(2+) injection rate, one dominated by the N-terminal lobe, and the other one by the C-terminal lobe. Taken together, these results suggest that the two lobes of CaM function as distinct Ca(2+) sensors that can differentially transduce Ca(2+) influx to downstream targets. We discuss a possible role of the N-terminal lobe-specific Ca(2+)-CaM nano-domain in CaMKII activation required for the induction of synaptic plasticity.

A Bayesian approach to estimating the regression coefficients of a multinomial logit model

A Bayesian approach to estimation of the regression coefficients of a multinominal logit model with ordinal scale response categories is presented. A Monte Carlo method is used to construct the posterior distribution of the link function. The link function is treated as an arbitrary scalar function. Then the Gauss-Markov theorem is used to determine a function of the link which produces a random vector of coefficients. The posterior distribution of the random vector of coefficients is used to estimate the regression coefficients. The method described is referred to as a Bayesian generalized least square (BGLS) analysis. Two cases involving multinominal logit models are described. Case I involves a cumulative logit model and Case II involves a proportional-odds model. All inferences about the coefficients for both cases are described in terms of the posterior distribution of the regression coefficients. The results from the BGLS method are compared to maximum likelihood estimates of the regression coefficients. The BGLS method avoids the nonlinear problems encountered when estimating the regression coefficients of a generalized linear model. The method is not complex or computationally intensive. The BGLS method offers several advantages over Bayesian approaches. ^

Slope estimation in a parametric measurement error model: A simulation study

In regression analysis, covariate measurement error occurs in many applications. The error-prone covariates are often referred to as latent variables. In this proposed study, we extended the study of Chan et al. (2008) on recovering latent slope in a simple regression model to that in a multiple regression model. We presented an approach that applied the Monte Carlo method in the Bayesian framework to the parametric regression model with the measurement error in an explanatory variable. The proposed estimator applied the conditional expectation of latent slope given the observed outcome and surrogate variables in the multiple regression models. A simulation study was presented showing that the method produces estimator that is efficient in the multiple regression model, especially when the measurement error variance of surrogate variable is large.^