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Purpose and Background: Conventional early breast cancer treatment consists of a lumpectomy followed by whole breast radiation therapy. Accelerated partial breast irradiation (APBI) is an investigational approach to post-lumpectomy radiation for early breast cancer. The purpose of this study is to compare four external beam APBI techniques, including tomotherapy, with conventional whole breast irradiation for their radiation conformity index, dose homogeneity index, and dose to organs at risk., Methods and Materials: Small-field tangents, three-dimensional conformal radiation therapy, intensity-modulated radiation therapy and helical tomotherapy were compared for each of 15 patients (7 right, 8 left). One radiation conformity and two dose homogeneity indices were used to evaluate the dose to the target. The mean dose to organs at risk was also evaluated., Results: All proposed APBI techniques improved the conformity index significantly over whole breast tangents while maintaining dose homogeneity and without a significant increase in dose to organs at risk., Conclusion: The four-field IMRT plan produced the best dosimetric results; however this technique would require appropriate respiratory motion management. An alternative would be to use a four-field conformal technique that is less sensitive to the effects of respiratory motion.

Abstract: Background and purpose: Multi-leaf collimator (MLC) positional errors occur during intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) deliveries. The impact of such errors has been evaluated for IMRT but not VMAT. The purpose of this work is to understand how random and systematic VMAT MLC positional errors affect the patient dose distribution. Materials and methods: Eight head and neck single arc (360°) VMAT treatment plans were created. Random and two types of systematic MLC errors were simulated for error magnitudes of 0.25, 0.5, 1, 2 and 5mm. The two types of systematic MLC errors were: (1) MLC banks are shifted in the same direction (left or right) and (2) MLC banks are shifted in opposing directions resulting in smaller or larger field shapes. The MLC errors were simulated, for all control points, on both banks of active MLC leaves only. Results: There is a linear correlation of MLC errors with gEUD for all error types. The gEUD dose sensitivities with MLC error for the PTV70 were −0.2, −0.9, −2.8 and 1.9Gy/mm for random, systematic shift, systematic close and systematic open MLC errors, respectively. The sensitivity of VMAT plans to MLC positional errors was similar to those of IMRT plans with less than 50 segments but much less than those created for a step and shoot with more than 50 segments or sliding-window delivery technique. To maintain the PTV70 to within 2% would require that MLC open/close errors be within 0.6mm. Conclusions: Radiation therapy centers should have adequate quality assurance programs in place to assess open/close MLC errors (i.e. leaf gap errors) as they tend to be more impactful than random or systematic MLC shift errors. [Copyright &y& Elsevier]

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. [ABSTRACT FROM AUTHOR]

A common method in generating intensity modulated radiation therapy (IMRT) plans consists of a three step process: an optimized fluence intensity map (IM) for each beam is generated via inverse planning, this IM is then segmented into discrete levels, and finally, the segmented map is translated into a set of MLC apertures via a leaf sequencing algorithm. To date, limited work has been done on this approach as it pertains to intensity modulated arc therapy (IMAT), specifically in regards to the latter two steps. There are two determining factors that separate IMAT segmentation and leaf sequencing from their IMRT equivalents: (1) the intrinsic 3D nature of the intensity maps (standard 2D maps plus the angular component), and (2) that the dynamic multileaf collimator (MLC) constraints be met using a minimum number of arcs. In this work, we illustrate a technique to create an IMAT plan that replicates Tomotherapy deliveries by applying IMAT specific segmentation and leaf-sequencing algorithms to Tomotherapy output sinograms. We propose and compare two alternative segmentation techniques, a clustering method, and a bottom-up segmentation method (BUS). We also introduce a novel IMAT leaf-sequencing algorithm that explicitly takes leaf movement constraints into consideration. These algorithms were tested with 51 angular projections of the output leaf-open sinograms generated on the Hi-ART II treatment planning system (Tomotherapy Inc.). We present two geometric phantoms and 2 clinical scenarios as sample test cases. In each case 12 IMAT plans were created, ranging from 2 to 7 intensity levels. Half were generated using the BUS segmentation and half with the clustering method. We report on the number of arcs produced as well as differences between Tomotherapy output sinograms and segmented IMAT intensity maps. For each case one plan for each segmentation method is chosen for full Monte Carlo dose calculation (NumeriX LLC) and dose volume histograms (DVH) are calculated. In all cases, the BUS method outperformed the clustering, method. We recommend using the BUS algorithm and discuss potential improvements to the clustering algorithms. [ABSTRACT FROM AUTHOR]