Interview: challenges faced by the modern bioanalytical laboratory.

Timothy Sangster (Charles River Laboratories) and Mike Oliver (Thermo Fisher Scientific) speak to Thomas Payne at Bioanalysis in September 2012 about the challenges faced by the modern bioanalytical laboratory. Timothy Sangster has been with Charles River Laboratories since September 2009. Having worked for Quintiles, Pharmacia, Astrazeneca and Huntingdon Life Sciences, he has gained experience over 17 years in both CRO and pharmaceutical environments, and also in both Europe and the USA. Specific areas of interest over the past years have been microchromatography, sample preparation and matrix effects, to name a few. Mike Oliver has held the position of Global Product Manager for sample preparation at Thermo Fisher Scientific since 2010, being responsible for the development and introduction of new innovative technologies such as SOLA™ to the market place. Prior to this role, Mike has worked for two leading MS vendors over a 9­year period, being responsible for biotechnology sales within the UK and providing application solutions for proteomic and metabolic workflows based on high-resolution LC-MS platforms, respectively. Mike holds a PhD in MS and Biochemistry from the MS Research Unit, University of Wales, Swansea, UK.

Experimental measurements and Monte Carlo simulations for dosimetric evaluations of intrafraction motion for gated and ungated intensity modulated arc therapy deliveries.

Respiratory gated radiation therapy allows for a smaller margin expansion for the planning target volume (PTV) to account for respiratory induced motion and is emerging as a common method to treat lung and liver tumors. We investigated the dosimetric effect of free motion and gated delivery for intensity modulated arc therapy (IMAT) with experimental measurements and Monte Carlo simulations. The impact of PTV margin and duty cycle for gated delivery is studied with Monte Carlo simulations. A motion phantom is used for this study. Two sets of contours were drawn on the mid-inspiration CT scan of this motion phantom. For each set of contours, an IMAT plan to be delivered with constant dose rate was created. The plans were generated on a CT scan of the phantom in the static condition with 3 mm PTV margin and applied to the motion phantom under four conditions: static, full superior-inferior (SI) motion (A = 1 cm, T = 4 s) and gating conditions (25% and 50% duty cycles) with full SI motion. A 6 by 15 cm piece of radiographic film was placed in the sagittal plane of the phantom and then irradiated under all measurement conditions. Film calibration was performed with a step-wedge method to convert optical density to dose. Gated IMAT delivery was first validated in 2D by comparing static film with that from gating and full motion. A previously verified simulation tool for IMRT that takes the log files from the multileaf collimator (MLC) controller and the gating system were adapted to simulate the delivered IMAT treatment for full 3D dosimetric analysis. The IMAT simulations were validated against the 2D film measurements. The resultant IMAT simulations were evaluated with dose criteria, dose-volume histograms and 3D gamma analysis. We validated gated IMAT deliveries when we compared the static film with the one from gating using 25% duty cycle using 2D gamma analysis. Within experimental and setup uncertainties, film measurements agreed with their corresponding simulated plans using 2D gamma analysis. Finally, when planning with margins designed for gating with 25% duty cycle and applying 50% or no gating during treatment, the dose differences in D(min,) D(99%) and D(95%) of the clinical target volume can be up to 27 cGy, 20 cGy and 18 cGy, respectively, for a plan with 200 cGy prescription dose. We have experimentally delivered gated IMAT with constant dose rate to a motion phantom and assessed their accuracies with film dosimetry and Monte Carlo simulations. Film dosimetry demonstrated that 25% gating and static plans are within 2%, 2 mm. The Monte Carlo simulation method was employed to generate dose delivered in 3D to a motion phantom, and the dosimetric results were reported. Since our film measurements agreed well with Monte Carlo simulations, we can reliably use this simulation tool to further study the dosimetric effects of target motion and effectiveness of gating for IMAT deliveries.

Incorporating geometric ray tracing to generate initial conditions for intensity modulated arc therapy optimization.

PURPOSE AND BACKGROUND: Intensity modulated arc therapy (IMAT) is a rotational variant of Intensity modulated radiation therapy (IMRT) that is achieved by allowing the multileaf collimator (MLC) positions to vary as the gantry rotates around the patient. This work describes a method to generate an IMAT plan through the use of a fast ray tracing technique based on dosimetric and geometric information for setting initial MLC leaf positions prior to final IMAT optimization. METHODS AND MATERIALS: Three steps were used to generate an IMAT plan. The first step was to generate arcs based on anatomical contours. The second step was to generate ray importance factor (RIF) maps by ray tracing the dose distribution inside the planning target volume (PTV) to modify the MLC leaf positions of the anatomical arcs to reduce the maximum dose inside the PTV. The RIF maps were also segmented to create a new set of arcs to improve the dose to low dose voxels within the PTV. In the third step, the MLC leaf positions from all arcs were put through a leaf position optimization (LPO) algorithm and brought into a fast Monte Carlo dose calculation engine for a final dose calculation. The method was applied to two phantom cases, a clinical prostate case and the Radiological Physics Center (RPC)'s head and neck phantom. The authors assessed the plan improvements achieved by each step and compared plans with and without using RIF. They also compared the IMAT plan with an IMRT plan for the RPC phantom. RESULTS: All plans that incorporated RIF and LPO had lower objective function values than those that incorporated LPO only. The objective function value was reduced by about 15% after the generation of RIF arcs and 52% after generation of RIF arcs and leaf position optimization. The IMAT plan for the RPC phantom had similar dose coverage for PTV1 and PTV2 (the same dose volume histogram curves), however, slightly lower dose to the normal tissues compared to a six-field IMRT plan. CONCLUSION: The use of a ray importance factor can generate initial IMAT arcs efficiently for further MLC leaf position optimization to obtain more favorable IMAT plan.

Commissioning a fast Monte Carlo dose calculation algorithm for lung cancer treatment planning.

A commercial Monte Carlo simulation package, NXEGS 1.12 (NumeriX LLC, New York, NY), was commissioned for photon-beam dose calculations. The same sets of measured data from 6-MV and 18-MV beams were used to commission NXEGS and Pinnacle 6.2b (Philips Medical Systems, Andover, MA). Accuracy and efficiency were compared against the collapsed cone convolution algorithm implemented in Pinnacle 6.2b, together with BEAM simulation (BEAMnrc 2001: National Research Council of Canada, Ottawa, ON). We investigated a number of options in NXEGS: the accuracy of fast Monte Carlo, the re-implementation of EGS4, post-processing technique (dose de-noising algorithm), and dose calculation time. Dose distributions were calculated with NXEGS, Pinnacle, and BEAM in water, lung-slab, and air-cylinder phantoms and in a lung patient plan. We compared the dose distributions calculated by NXEGS, Pinnacle, and BEAM. In a selected region of interest (7725 voxels) in the lung phantom, all but 1 voxel had a gamma (3% and 3 mm thresholds) of 1 or less for the dose difference between the NXEGS re-implementation of EGS4 and BEAM, and 99% of the voxels had a gamma of 1 or less for the dose difference between NXEGS fast Monte Carlo and BEAM. Fast Monte Carlo with post-processing was up to 100 times faster than the NXEGS re-implementation of EGS4, while maintaining +/- 2% statistical uncertainty. With air inhomogeneities larger than 1 cm, post-processing preserves the dose perturbations from the air cylinder. When 3 or more beams were used, fast Monte Carlo with post-processing was comparable to or faster than Pinnacle 6.2b collapsed cone convolution.

Monte Carlo dose calculation of segmental IMRT delivery to a moving phantom using dynamic MLC and gating log files.

Respiratory gating is emerging as a tool to limit the effect of motion for liver and lung tumors. In order to study the impact of target motion and gated intensity modulated radiation therapy (IMRT) delivery, a computer program was developed to simulate segmental IMRT delivery to a moving phantom. Two distinct plans were delivered to a rigid-motion phantom with a film insert in place under four conditions: static, sinusoidal motion, gated sinusoidal motion with a duty cycle of 25% and gated sinusoidal motion with duty cycle of 50% under motion conditions of a typical patient (A = 1 cm, T = 4 s). The MLC controller log files and gating log files were retained to perform a retrospective Monte Carlo dose calculation of the plans. Comparison of the 2D planar dose distributions between simulation and measurement demonstrated that our technique had at least 94% of the points passing gamma criteria of 3% for dose difference and 3 mm as the distance to agreement. This note demonstrates that the use of dynamic multi-leaf collimator and respiratory monitoring system log files together with a fast Monte Carlo dose calculation algorithm is an accurate and efficient way to study the dosimetric effect of motion for gated or non-gated IMRT delivery on a rigidly-moving body.