Biomedical subjects

M Vicic

Publications and source records attributed to M Vicic.

3 recordsLinked to original sources

PubMed2006

Dose response explorer: an integrated open-source tool for exploring and modelling radiotherapy dose-volume outcome relationships.

Radiotherapy treatment outcome models are a complicated function of treatment, clinical and biological factors. Our objective is to provide clinicians and scientists with an accurate, flexible and user-friendly software tool to explore radiotherapy outcomes data and build statistical tumour control or normal tissue complications models. The software tool, called the dose response explorer system (DREES), is based on Matlab, and uses a named-field structure array data type. DREES/Matlab in combination with another open-source tool (CERR) provides an environment for analysing treatment outcomes. DREES provides many radiotherapy outcome modelling features, including (1) fitting of analytical normal tissue complication probability (NTCP) and tumour control probability (TCP) models, (2) combined modelling of multiple dose-volume variables (e.g., mean dose, max dose, etc) and clinical factors (age, gender, stage, etc) using multi-term regression modelling, (3) manual or automated selection of logistic or actuarial model variables using bootstrap statistical resampling, (4) estimation of uncertainty in model parameters, (5) performance assessment of univariate and multivariate analyses using Spearman's rank correlation and chi-square statistics, boxplots, nomograms, Kaplan-Meier survival plots, and receiver operating characteristics curves, and (6) graphical capabilities to visualize NTCP or TCP prediction versus selected variable models using various plots. DREES provides clinical researchers with a tool customized for radiotherapy outcome modelling. DREES is freely distributed. We expect to continue developing DREES based on user feedback.

Computer Simulation↗

PubMed2005

A comparison of Monte Carlo dose calculation denoising techniques.

Recent studies have demonstrated that Monte Carlo (MC) denoising techniques can reduce MC radiotherapy dose computation time significantly by preferentially eliminating statistical fluctuations ('noise') through smoothing. In this study, we compare new and previously published approaches to MC denoising, including 3D wavelet threshold denoising with sub-band adaptive thresholding, content adaptive mean-median-hybrid (CAMH) filtering, locally adaptive Savitzky-Golay curve-fitting (LASG), anisotropic diffusion (AD) and an iterative reduction of noise (IRON) method formulated as an optimization problem. Several challenging phantom and computed-tomography-based MC dose distributions with varying levels of noise formed the test set. Denoising effectiveness was measured in three ways: by improvements in the mean-square-error (MSE) with respect to a reference (low noise) dose distribution; by the maximum difference from the reference distribution and by the 'Van Dyk' pass/fail criteria of either adequate agreement with the reference image in low-gradient regions (within 2% in our case) or, in high-gradient regions, a distance-to-agreement-within-2% of less than 2 mm. Results varied significantly based on the dose test case: greater reductions in MSE were observed for the relatively smoother phantom-based dose distribution (up to a factor of 16 for the LASG algorithm); smaller reductions were seen for an intensity modulated radiation therapy (IMRT) head and neck case (typically, factors of 2-4). Although several algorithms reduced statistical noise for all test geometries, the LASG method had the best MSE reduction for three of the four test geometries, and performed the best for the Van Dyk criteria. However, the wavelet thresholding method performed better for the head and neck IMRT geometry and also decreased the maximum error more effectively than LASG. In almost all cases, the evaluated methods provided acceleration of MC results towards statistically more accurate results.

Algorithms↗

PubMed2003

Dependence of radiochromic film optical density post-exposure kinetics on dose and dose fractionation.

Radiochromic film (RCF) has been shown to be a precise and accurate secondary planar dosimeter for acute exposure radiation fields. However, its application to low dose-rate brachytherapy has been questioned because of possible dose-rate effects. To address this concern, we have measured the optical density (OD) of Model 55-2 RCF as a function of time (interval between the completion of irradiation and densitometry using a 633 nm laser scanner) following exposure (from less than 1 hour to 90 days) for single and split doses from 1 Gy to 100 Gy. Our work demonstrates that film darkening as a function of post-irradiation time depends significantly on total dose, with films exposed to lower doses developing faster than films given higher doses. At 1 Gy, the OD 90 days after exposure is 200% larger than that measured 1 h after exposure compared to a 20% increase over 90 days for doses larger than 20 Gy. An empirical model with time-independent, fast and slow growth terms was used to fit single exposure data. The dependence of the resulting best-fit parameters on dose was investigated. Splitting the dose into two fractions (20 Gy followed by doses of 1-80 Gy 24 h later) results in modest post-irradiation time-dependent changes in the total optical density (at most 15% at small doses), which dissipates within 20 hours following the second exposure. This experimental finding is consistent with the predictions of a simple cumulative dose superposition model. Overall, both experimental and empirical modeling suggest that dose-rate effects may be relatively small despite the strong dependence of film darkening kinetics on total dose. However, more experimental evaluation of radiochromic film response dependence on dose rate and dose-time-fractionation patterns is needed.

Brachytherapy↗