Monte Carlo dose verification for intensity-modulated arc therapy

Intensity-modulated arc therapy (IMAT), a technique which combines beam rotation and dynamic multileaf collimation, has been implemented in our clinic. Dosimetric errors can be created by the inability of the planning system to accurately account for the effects of tissue inhomogeneities and physical characteristics of the multileaf collimator (MLC). The objective of this study is to explore the use of Monte Carlo (MC) simulation for IMAT dose verification. The BEAM/DOSXYZ Monte Carlo system was implemented to perform dose verification for the IMAT treatment. The implementation includes the simulation of the linac head/MLC (Elekta SL20), the conversion of patient CT images and beam arrangement for 3D dose calculation, the calculation of gantry rotation and leaf motion by a series of static beams and the development of software to automate the entire MC process. The MC calculations were verified by measurements for conventional beam settings. The agreement was within 2%. The IMAT dose distributions generated by a commercial forward planning system (RenderPlan. Elekta) were compared with those calculated by the MC package. For the cases studied, discrepancies of over 10% were found between the MC and the RenderPlan dose calculations. These discrepancies were due in part to the inaccurate dose calculation of the RenderPlan system. The computation time for the IMAT MC calculation was in the range of 20-80 min on 15 Pentium-Ill computers. The MC method was also useful in verifying the beam apertures used in the IMAT treatments.     

Analysing collimator structure effects in head-scatter calculations for IMRT class fields using scatter raytracing

The frequent blocking of the irradiated volume in intensity modulated radiation therapy (IMRT) makes the head-scatter fraction of the incident photon fluence more significant than that in conventional therapy with open fields. On the other hand. certain collimator configurations block scatter photons directed to a given observation point while allowing primary photons to be transmitted. The 'anomalous blocking' makes the primary field a poor indicator of the scatter fluence. Since large MU-to-cGy ratios in IMRT can magnify head-scatter uncertainties, it becomes necessary to accurately model both the effective scatter source and the collimator structure that limits the scatter reaching the irradiated volume. First we obtain a dual-source model, using a Taylor series expansion to derive the effective scatter source distribution from the data measured for the Elekta SL20 linac equipped with a multi-leaf collimator (MLC). Then, using a raytracing algorithm, we calculate the transmission of scatter rays from the effective scatter source plane to points in the patient plane. The method can account for the anomalous blocking of scatter by the MLC leaves and the backup diaphragms. For a variety of collimator settings tested, the calculations agree with measurements to an accuracy of 0.002psi10 x 10, where psi10 x 10 is the total (primary + scatter) photon fluence of an open 10 x 10 cm2 field for the same MU delivered. Although the significance of collimator structure in IMRT depends strongly on fields shapes employed for the delivery, potential cumulative errors on the order of a few per cent can be avoided in fluence calculations if the proposed method is used.     

Using a photon phase-space source for convolution/superposition dose calculations in radiation therapy

For a given linac design, the dosimetric characteristics of a photon beam are determined uniquely by the energy and radial distributions of the electron beam striking the x-ray target. However, in the usual commissioning of a beam from measured data, a large number of variables can be independently tuned, making it difficult to derive a unique and self-consistent beam model. For example, the measured dosimetric penumbra in water may be attributed in various proportions to the lateral secondary electron range, the focal spot size and the transmission through the tips of a non-divergent collimator; the head-scatter component in the tails of the transverse profiles may not be easy to resolve from phantom scatter and head leakage; and the head-scatter tails corresponding to a certain extra-focal source model may not agree self-consistently with in-air output factors measured on the central axis. To reduce the number of adjustable variables in beam modelling, we replace the focal and extra-focal sources with a single phase-space plane scored just above the highest adjustable collimator in a EGS/BEAM simulation of the linac. The phase-space plane is then used as photon source in a stochastic convolution/superposition dose engine. A photon sampled from the uncollimated phase-space plane is first propagated through an arbitrary collimator arrangement and then interacted in the simulation phantom. Energy deposition kernel rays are then randomly issued from the interaction points and dose is deposited along these rays. The electrons in the phase-space file are used to account for electron contamination. 6 MV and 18 MV photon beams from an Elekta SL linac are used as representative examples. Except for small corrections for monitor backscatter and collimator forward scatter for large field sizes (<0.5% with <20 x 20 cm2 field size), we found that the use of a single phase-space photon source provides accurate and self-consistent results for both relative and absolute dose calculations.     

Microbial contamination of hospital bed handsets

BACKGROUND: Hospital bed handsets, including nurse call equipment and television controls, have been found to contain biologic material and may be contaminated with microbes. OBJECTIVE: The aim of this study was to assess the microbial contamination of hospital bed handsets. METHODS: Hospital bed handsets were removed from 115 randomly chosen rooms in a suburban hospital. The handsets were transported to the laboratory in a sterile fashion and opened using a sterile technique, and cultures were obtained from both the anterior and posterior surfaces of the units. RESULTS: The cultures of 12 units (10.4%) revealed no microorganisms. One hundred three units (89.6%) had cultures that grew microorganisms. Of the handsets that were found to contain microorganisms, 48 units (46.6%) had only 1 microorganism, and 55 units (53.4%) had multiple organisms, including 33 units (32.0%) with 2 microorganisms, 21 units (20.4%) with 3 microorganisms, and 1 unit (1.0%) with 4 microorganisms. The microorganisms identified included 90 isolates (87.4%) of coagulase-negative staphylococcus, 51 isolates (49.5%) of bacillus species, 13 isolates (12.6%) of fungal species, 8 isolates (7.8%) of nonhemolytic streptococcus species, 7 isolates (6.8%) of alpha-hemolytic streptococcus species, 1 isolate (1.0%) of Staphylococcus aureus, and 1 isolate (1.0%) of methicillin-resistant Staphylococcus aureus. CONCLUSION: Hospital bed handsets were found to have a high incidence of contamination with bacteria and fungus and were found to contain organisms that are known to be the etiologic agents in nosocomial infections. Because of the frequency and duration of contact between hospital patients and hospital bed handsets, existing infection control measures should be studied that could reduce the level of contamination of such handsets or that could isolate the handsets from the patient.