Due to limitations and uncertainties in dose calculation algorithms, different algorithms can predict different dose distributions and dose‐volume histograms for the same treatment. This can be a problem when estimating the normal tissue complication probability (NTCP) for patient‐specific dose distributions. Published NTCP model parameters are often derived for a different dose calculation algorithm than the one used to calculate the actual dose distribution. The use of algorithm‐specific NTCP model parameters can prevent errors caused by differences in dose calculation algorithms. The objective of this work was to determine how to change the NTCP model parameters for lung complications derived for a simple correction‐based pencil beam dose calculation algorithm, in order to make them valid for three other common dose calculation algorithms. NTCP was calculated with the relative seriality (RS) and Lyman‐Kutcher‐Burman (LKB) models. The four dose calculation algorithms used were the pencil beam (PB) and collapsed cone (CC) algorithms employed by Oncentra, and the pencil beam convolution (PBC) and anisotropic analytical algorithm (AAA) employed by Eclipse. Original model parameters for lung complications were taken from four published studies on different grades of pneumonitis, and new algorithm‐specific NTCP model parameters were determined. The difference between original and new model parameters was presented in relation to the reported model parameter uncertainties. Three different types of treatments were considered in the study: tangential and locoregional breast cancer treatment and lung cancer treatment. Changing the algorithm without the derivation of new model parameters caused changes in the NTCP value of up to 10 percentage points for the cases studied. Furthermore, the error introduced could be of the same magnitude as the confidence intervals of the calculated NTCP values. The new NTCP model parameters were tabulated as the algorithm was varied from PB to PBC, AAA, or CC. Moving from the PB to the PBC algorithm did not require new model parameters; however, moving from PB to AAA or CC did require a change in the NTCP model parameters, with CC requiring the largest change. It was shown that the new model parameters for a given algorithm are different for the different treatment types.PACS numbers: 87.53.‐j, 87.53.Kn, 87.55.‐x, 87.55.dh, 87.55.kd

Background and purpose: To investigate the impact of the clinical implementation of a deterministic particle transport method on the lung dose evaluation for radiotherapy of breast cancer focusing on dosimetric effects of the lung density. Material and methods: Fourteen patients with left sided breast cancer having both deep inspiration breath hold (DIBH) and free breathing CT scans were studied. Lung density variations for 157 patients treated under DIBH were quantified and the cases with the lowest lung densities for breast and for loco regional treatment added to the study. Dose calculations were performed with the class-b type algorithm AAA and the deterministic algorithm Acuros XB. Monte Carlo method was utilized as reference. Differences in the dose distributions were evaluated by comparing DVH parameters. Results: Lung density variations between 0.08 and 0.3 g/cm 3 and between 0.02 and 0.25 g/cm 3 were found for loco-regional and tangential breast treatments under DIBH, respectively. Lung DVH parameters for patients with medium and high lung density obtained by the different algorithms agreed within 3%. Larger differences were observed for low lung density cases where the correction based algorithm underestimated V 10Gy and overestimated V 40Gy by up to 5%. The least affected parameter, V 20Gy , deviated by less than 2% for all cases and densities. Conclusions: Dosimetric constrains for lung based on V 20Gy required minimum changes due to implementation of the new algorithm regardless of breathing technique or type of treatment. Evaluation criteria utilizing V 10Gy or V 40Gy needed reconsideration, especially for treatments under DIBH involving low lung density.

Locoregional treatment of breast cancer involves adjacent, half blocked fields matched at isocenter. The objective of this work is to study the dosimetric effects of the uncertainties in jaw positioning for such a case, and how a treatment planning protocol including adjacent field overlap of 1 mm affects the dose distribution. A representative treatment plan, involving 6 and 15 photon beams, for a patient treated at our hospital is chosen. Monte Carlo method (EGSnrc/BEAMnrc) is used to simulate the treatment. Uncertainties in jaw positioning of ±1 mm are addressed, which implies extremes in reality of 2 mm field gap/overlap when planning adjacent fields without overlap and 1 mm gap or 3 mm overlap for a planning protocol with 1 mm overlap. Dosimetric parameters for PTV, lung and body are analyzed. Treatment planning protocol with 1 mm overlap of the adjacent fields does not considerably counteract possible underdosage of the target in the case studied. PTV‐normalV95% is for example reduced from 95% for perfectly aligned fields to 90% and 91% for 2 mm and 1 mm gap, respectively. However, the risk of overdosage in PTV and in healthy soft tissue is increased when following the protocol with 1 mm overlap. A 3 mm overlap compared to 2 mm overlap results in an increase in maximum dose to PTV, PTV‐normalD2%, from 113% to 121%. V120% for ‘Body‐PTV’ is also increased from 5 cm3 to 14 cm3. A treatment planning protocol with 1 mm overlap does not considerably improve the coverage of PTV in the case of erroneous jaw positions causing gap between fields, but increases the overdosage in PTV and doses to healthy tissue, in the case of overlapping fields, for the case investigated.PACS numbers: 87.55.D‐, 87.55.dk, 87.55.Gh, 87.55.K‐, 87.56.J‐

The objective of this work is to apply a Monte Carlo (MC) accelerator model, validated by experimental data at isocentre distances, to a large-field total body irradiation (TBI) technique and to develop a strategy for individual patient treatment on the basis of MC dose distributions. Calculations are carried out using BEAMnrc/DOSXYZnrc code packages for a 15 MV Varian accelerator. Acceptable agreement is obtained between MC data and measurements in a large water phantom behind a spoiler at source-skin distances (SSD) = 460 cm as well as in a CIRS® thorax phantom. Dose distributions in patients are studied when simulating bilateral beam delivery at a distance of 480 cm to the patient central sagittal plane. A procedure for individual improvement of the dose uniformity is suggested including the design of compensators in a conventional treatment planning system (TPS) and a subsequent update of the dose distribution. It is demonstrated that the dose uniformity for the simple TBI technique can be considerably improved. The optimization strategy developed is straightforward and suitable for clinics where the TPS available is deficient to calculate 3D dose distributions at extended SSD.

In this work the dosimetric performance of CMOS active pixel sensors for the measurement of small photon beams is presented. The detector used consisted of an array of 520  × 520 pixels on a 25 µm pitch. Dosimetric parameters measured with this sensor were compared with data collected with an ionization chamber, a film detector and GEANT4 Monte Carlo simulations. The sensor performance for beam profiles measurements was evaluated for field sizes of 0.5  × 0.5 cm(2). The high spatial resolution achieved with this sensor allowed the accurate measurement of profiles, beam penumbrae and field size under lateral electronic disequilibrium. Field size and penumbrae agreed within 5.4% and 2.2% respectively with film measurements. Agreements with ionization chambers better than 1.0% were obtained when measuring tissue-phantom ratios. Output factor measurements were in good agreement with ionization chamber and Monte Carlo simulation. The data obtained from this imaging sensor can be easily analyzed to extract dosimetric information. The results presented in this work are promising for the development and implementation of CMOS active pixel sensors for dosimetry applications.

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