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Purpose: Pre‐calculation of accurate dose deposition kernels for treatment planning of spot‐based radiotherapies, such as Gamma Knife (GK) and Gamma Pod (GP), can be very time‐consuming and may require large data storage with an enormous number of possible spots. We proposed a novel kernel decomposition (KD) model to address accurate and fast (real‐time) dose calculation with reduced data storage requirements for spot‐based treatment planning. The application of the KD model was demonstrated for clinical GK and GP radiotherapy platforms. Methods: The dose deposition kernel at each spot (shot position) is modeled as the product of a shift‐invariant kernel based on a reference kernel and spatially variant scale factor. The reference kernel, one for each collimator, is defined at the center of the commissioning phantom for GK and at the center of the treatment target for GP and calculated using the Monte Carlo (MC) method. The spatially variant scale factor is defined as the ratio of the mean tissue maximum ratio (TMR) at the candidate shot position to that at the reference kernel position, and the mean TMR map is calculated within the entire volume through parallel beam ray tracing on the density image followed by averaging over all source directions. The proposed KD dose calculations were compared with the MC method and with the GK and GP treatment planning system (TPS) computations for various shot positions and collimator sizes utilizing a phantom and 14 and 12 clinical plans for GK and GP, respectively. Results: For the phantom study, the KD Gamma index (3%/1 mm) passing rates were greater than 99% (median 100%) relative to the MC doses, except for the shots close to the boundary. The passing rates dropped below 90% for 8 mm (16 mm) shots positioned within ∼1 cm (∼2 cm) of the boundary. For the clinical GK plans, the KD Gamma passing rates were greater than 99% (median 100%) compared to the MC and greater than 92% (median 99%) compared to the TPS. For the clinical GP plans, the KD Gamma passing rates were greater than 95% (median 98%) compared to the MC and greater than 91% (median 97%) compared to the TPS. The scale factors were calculated in sub‐seconds with GPU implementation and only need to be calculated once before treatment plan optimization. The calculation of the dose kernel was also within sub‐seconds without requiring beam‐by‐beam calculation commonly done in the TPS. Conclusion: The proposed model can provide an accurate dose and enables real‐time dose and derivative calculations by kernel shifting and scaling without pre‐calculating or requiring large data storage for GK and GP dose deposition kernels during treatment planning. This model could be useful for spot‐based radiotherapy treatment planning by allowing an efficient global fine search for optimal spots. [ABSTRACT FROM AUTHOR]

Purpose: The flattening filter (FF) has traditionally been used to flatten beams or create uniform fields in conformal and intensity‐modulated radiation therapy (IMRT) but reduces the dose rate. Many studies have confirmed improvement in delivery efficiency by removing the FF, also known as flattening filter free (FFF), especially for small field stereotactic body radiation therapy (SBRT); but it is unclear if large treatment fields still favor the FFF beam. We propose a novel, unified approach to quantify delivery efficiency of the FFF and flattened beams. Methods: We modeled the FF effect by inverse conical filters and systematically studied delivery efficiency (beam‐on time, BOT) by varying the filter thickness, including the FF and FFF mode. We formulated the BOT of different beams for any arbitrary fluence map in linear programming to solve the optimal inverse conical filter that minimizes the BOT. One‐dimensional optimal filters of minimum BOT were also derived in closed form for conical fluence to gain insight for arbitrary clinical fluence maps. We evaluated the BOT of the FFF beam and flattened beam for conformal treatment fields of various dimensions ranging from 5 cm × 5 cm to 25 cm × 25 cm. We also analyzed the BOT for 698 clinical IMRT prostate fluence maps of field size 10 cm × 10 cm, 17 head‐and‐neck fluence maps of field size 15 cm × 15 cm, and additional realistic test data from 90° rotation and up to 40 cm × 40 cm enlargement of these clinical fluence maps, which were all initially generated with flattened beams. Results: The FFF beam minimized the BOT for A field size less than 20 cm in single leaf pair cases and for conformal fields of dimension less than 20 cm × 20 cm. The FFF beam also minimized the BOT for all tested prostate and head‐and‐neck cases. The median BOT ratios of the FFF beam to the flattened beam were 0.56 and 0.61 for prostate and head‐and‐neck cases, respectively. The FFF beam minimized the BOT for field size up to 30 cm × 30 cm and had similar BOTs to those of the flattened beam for field size greater than 30 cm × 30 cm in those clinically realistic test data. Conclusion: The filter modeling and BOT calculation enable us to quantify delivery efficiency of the FFF beam and flattened beam in a unified approach. The FFF beam minimized the BOT both theoretically and in simulations for all clinically relevant field sizes and fluence maps in IMRT. The results for conformal fields imply that the FFF beam requires less BOT than the flattened beam for volumetric modulated arc therapy (VMAT) treatments. The delivery efficiency consideration favors the FFF beam in intensity‐modulated treatments and may eventually lead to removal of the FF in all future linear accelerator head designs. [ABSTRACT FROM AUTHOR]