Investigation of a Novel Decision Support Metric for Head and Neck Adaptive Radiation Therapy Using a Real-Time In Vivo Portal Dosimetry System.

In adaptive radiation therapy of head and neck cancer, any significant anatomical changes observed are used to adapt the treatment plan to maintain target coverage without elevating the risk of xerostomia. However, the additional resources required for adaptive radiation therapy pose a challenge for broad-based implementation. It is hypothesized that a change in transit fluence is associated with volumetric change in the vicinity of the target and therefore can be used as a decision support metric for adaptive radiation therapy. This was evaluated by comparing the fluence with volumetric changes in 12 patients. Transit fluence was measured by an in vivo portal dosimetry system. Weekly cone beam computed tomography was used to determine volume change in the rectangular region of interest from condyloid process to C6. The integrated transit fluence through the region of interest on the day of the cone beam computed tomography scan was calculated with the first treatment as the baseline. The correlation between fluence change and volume change was determined. A logistic regression model was also used to associate the 5% region of interest volume reduction replanning trigger point and the fluence change. The model was assessed by a chi-square test. The area under the receiver-operating characteristic curve was also determined. A total of 46 pairs of measurements were obtained. The correlation between fluence and volumetric changes was found to be -0.776 (P value <.001). The negative correlation is attributed to the increase in the photon fluence transport resulting from the volume reduction. The chi-square of the logistic regression was found to be 17.4 (P value <.001). The area under the receiver-operating characteristic curve was found to be 0.88. Results indicate the change in transit fluence, which can be measured without consuming clinical resources or requiring additional time in the treatment room, can be used as a decision support metric for adaptive therapy.

Bilinear models for inter- and intra-patient variation of the prostate.

We propose bilinear models for capturing and effectively decoupling the expected shape variations of an organ both across the patient population and within a specific patient. Bilinear models have been successfully introduced in other areas of computer vision, but they have rarely been used in medical imaging applications. Our particular interest is in modeling the shape variation of the prostate for potential use in radiation therapy treatment planning. Using a dataset of 204 prostate shapes contoured from CT imagery of 12 different patients, we build bilinear models and show that they can fit both training and testing shapes accurately. We also show how the bilinear model can adapt to a new patient using only a few example shapes, producing a patient-specific model that also reflects expected content variation learnt from a broader population. Finally, we evaluate the training and testing projection error, adaptation performance and image segmentation accuracy of the bilinear model compared to linear principal component analysis and hierarchical point distribution models with the same number of parameters.

A monte carlo approach to electron contamination sources in the Saturne-25 and -41.

The various components of the accelerator treatment head act as sources of contaminating electrons. The presence of contamination electrons increases the surface dose, which deteriorates the skin-sparing effect. The present study examines the sources of this 'contamination', the influence on the surface dose and the shape of the build-up curve. The Monte Carlo simulation of two linear accelerators, Saturne-25 and -41, allowed us to study the influence of electron contamination in various therapeutic energies and in different geometries. The Saturne-25 and -41 cover a wide range of therapeutic energies with nominal energies 12/23 MV and 6/15 MV, respectively. The analysis of the results shows that at a source-to-surface distance of 100 cm and a wide opening of the collimators, the main sources of contaminating electrons are the flattening filter and the air below it. The contribution of the secondary contamination electrons on the surface dose is 16% for 6 MV and 12 MV, 6% for 15 MV and 17% for 23 MV. The energy spectra of electrons coming from the flattening filter and the air below it are completely different. The air produces electrons of low energies. The mean energies of these spectra vary from 1 MeV to 2 MeV depending on the nominal energy of the photon beam. The secondary electrons generated by the flattening filter produce a wide energy spectrum with mean energies of the same order of the bremsstrahlung spectrum. The flattening filter absorbs the secondary electrons generated in the target, the primary collimator and the air inside the head.

Simulation with EGS4 code of external beam of radiotherapy apparatus with workstation and PC gives similar results?

This article presents a comparison between two implementations of an EGS4 Monte Carlo simulation of a radiation therapy machine. The first implementation was run on a high performance RISC workstation, and the second was run on an inexpensive PC. The simulation was performed using the MCRAD user code. The photon energy spectra, as measured at a plane transverse to the beam direction and containing the isocenter, were compared. The photons were also binned radially in order to compare the variation of the spectra with radius. With 500,000 photons recorded in each of the two simulations, the running times were 48 h and 116 h for the workstation and the PC, respectively. No significant statistical differences between the two implementations were found.

A Monte Carlo model of photon beams used in radiation therapy.

A generic Monte Carlo model of a photon therapy machine is described. The model, known as McRad, is based on EGS4 and has been in use since 1991. Its primary function has been the characterization of the incident photon fluence for use by dose calculation algorithms. The accuracy of McRad is examined by comparing the dose distributions in a water phantom generated using only the Monte Carlo data with measured dose distributions for two machines in our clinic; a 6 MV Varian Clinac 600C and the 15 MV beam from a Clinac 2100C. The Monte Carlo generated dose distributions are computed using a dose calculation algorithm based on the use of differential pencil beam kernels. It was found that the match to measured data could be improved if the model is tuned by adjusting the energy of the electron beam incident on the target. The beam profiles were found to be more sensitive indicators of the electron beam energy than the depth dose curves. Beyond the depths reached by contaminant electrons, the computed and measured depth dose curves agree to better than 1%. The comparison of beam profiles indicate that in regions up to within 1 cm of the field edge, the measured and computed doses generally agree to within 2%-3%.

Analysis of the photon beam treatment planning data for a scanning beam machine.

The characteristics of photon beams from the Scanditronix MM50 radiation therapy machine that are necessary for treatment planning are described. The MM50 uses a scanning beam instead of a conventional flattening filter to achieve flat dose distributions. At each beam energy, a scan pattern is chosen, depending on the field size; the small scan pattern (S) is used for field sizes up to 10 x 10 cm, the medium scan pattern (M) is used for field sizes up to 20 x 20 cm, and the large scan pattern (L) is used for the larger field sizes. The dose distributions of the beams associated with the 10 MV S, M, and L scan patterns, the 25 MV S, M, and L patterns, and the 50 MV S and M patterns are described. The data reported includes central axis data, beam profiles, and output factors. In addition to the measured data, our dose calculation model requires a pencil beam kernel for each beam. The kernel is constructed using the average photon energy spectrum, which is generated using a Monte Carlo simulation of the MM50. The simulation, based on EGS4, is also used to generate the radial variation of fluence and energy fluence, which is required by a new dose calculation model that does not require the measurement of beam profiles. The Monte Carlo generated data; the photon energy spectrum, the fluence, and the energy fluence are presented.