Patient-specific Monte Carlo dose calculations for (103)Pd breast brachytherapy

Impact on the estimated dose of different tissue assignment strategies during partial breast irradiations with INTRABEAM

PURPOSE

Partial breast irradiations with electronic brachytherapy or kilovoltage intraoperative radiotherapy devices such as Axxent or INTRABEAM are becoming more common every day. Breast is mainly composed of glandular and adipose tissues, which are not always clearly disentangled in planning breast CTs. In these cases, breast tissues are replaced with an average soft tissue, or even water. However, at kilovoltage energies, this may lead to large differences in the delivered dose, due to the dominance of photoelectric effect. Therefore, the aim of this work was to study the effect on the dose prescribed in breast with the INTRABEAM device using different soft tissue assignment strategies that would replace the adipose and glandular tissues that constitute the breast in cases where these tissues cannot be adequately distinguished in a CT scan.

METHODS AND MATERIALS

Dose was computed with a Monte Carlo code in five patients with a 3 cm diameter INTRABEAM spherical applicator. Tissues within the breast were assigned following six different strategies: one based on the TG-43 recommendations, representing the whole breast as water of unity density, another one also water-based but with CT derived density, and the other four also based on CT-derived densities, using a single tissue resulting from different mixes of glandular and adipose tissues. These were compared against the reference dose computed in an accurately segmented CT, following TG-186 recommendations. Relative differences and dose ratios between the reference and the other tissue assignment strategies were obtained in three regions of interest inside the breast.

RESULTS AND CONCLUSIONS

Dose planning in water-based tissues was found inaccurate for breast treatment with INTRABEAM, as it would incur in up to 30% under-prescription of dose. If accurate soft tissue assignments in the breast cannot be safely done, a single-tissue composition of 80% adipose and 20% glandular tissue, or even a 100% adipose tissue, would be recommended to avoid dose under-prescription.

Dosimetric investigation of 103Pd permanent breast seed implant brachytherapy based on Monte Carlo calculations

PURPOSE

Permanent breast seed implant using ¹⁰³Pd is emerging as an effective adjuvant radiation technique for early stage breast cancer. However, clinical dose evaluations follow the water-based TG-43 approach with its considerable approximations. Toward clinical adoption of advanced TG-186 model-based dose evaluations, this study presents a comprehensive investigation for permanent breast seed implant considering both target and normal tissue doses.

METHODS AND MATERIALS

Dose calculations are performed with the free open-source Monte Carlo (MC) code, egs_brachy, using two types of virtual patient models: TG43sim (simulated TG-43 conditions) and MCref (heterogeneous tissue modeling from patient CT, seeds at implant angle) for 35 patients. The sensitivity of dose metrics to seed orientation and tissue segmentation are assessed.

RESULTS

In the target volume, D₉₀ is 14.1 ± 5.8% lower with MCref than with TG43sim, on average. Conversely, normal tissue doses are generally higher with MCref than with TG43sim, for example, by 22 ± 13% for skin D_1cm2, 82 ± 7% for ribs D_max, and 71 ± 23% for heart D_1cm3. Discrepancies between MCref and TG43sim doses vary over the patient cohort, as well as with the tissue and metric considered. Skin doses are particularly sensitive to seed orientation, with average difference of 4% (maximum 28%) in D_1cm2 for seeds modeled vertically (egs_brachy default) compared with those aligned with implant angle.

CONCLUSIONS

TG-43 dose evaluations generally underestimate doses to critical normal organs/tissues while overestimating target doses. There is considerable variation in MCref and TG43sim on a patient-by-patient basis, motivating clinical adoption of patient-specific MC dose calculations. The MCref framework presented herein provides a consistent modeling approach for clinical implementation of advanced TG-186 dose calculations.

A novel and fast methodology to calculate doses in LDR brachytherapy

We present the concept of a new methodology for faster simulation of the doses in brachytherapy with permanent implants, based on the knowledge of the seeds arrangement, adding previously simulated doses in an equivalent medium in terms of the atomic composition of the organ in question. To perform the doses calculations we use Monte Carlo simulations. We simulated a cylindrical I-125 seed and compared our results against published data. Our proposal is to have the doses simulated previously in different arrangement of seed-absorbents, and then, considering the spacial positions of the seeds after the implants, these doses can be directly added, obtaining a very fast computation of the total dose. Two phantoms of prostates with permanent implant seeds in 2D and 3D arrangements were simulated. The results of the proposed methodology were compared with two complete Monte Carlo simulations in 2D and 3D designs. Differences in doses were analysed, obtaining statistical discrepancies of less than 1% and reducing the simulation time by more than 4 orders of magnitude. With the proposed methodology, it is possible to perform rapid dose calculations in brachytherapy, using laptop or desktop computers.

Investigating energy deposition in glandular tissues for mammography using multiscale Monte Carlo simulations

PURPOSE

To investigate energy deposition in glandular tissues of the breast on macro- and microscopic length scales in the context of mammography.

METHODS

Multiscale mammography models of breasts are developed, which include segmented, voxelized macroscopic tissue structure as well as nine regions of interest (ROIs) embedded throughout the breast tissue containing explicitly-modelled cells. Using a 30 kVp Mo/Mo spectrum, Monte Carlo (MC) techniques are used to calculate dose to ∼mm voxels containing glandular and/or adipose tissues, as well as energy deposition on cellular length scales. ROIs consist of at least 1000 mammary epithelial cells and ∼200 adipocytes; specific energy (energy imparted per unit mass; stochastic analogue of the absorbed dose) is calculated within mammary epithelial cell nuclei.

RESULTS

Macroscopic dose distributions within segmented breast tissue demonstrate considerable variation in energy deposition depending on depth and tissue structure. Doses to voxels containing glandular tissue vary between ∼0.1 and ∼4 times the mean glandular dose (MGD, averaged over the entire breast). Considering microscopic length scales, mean specific energies for mammary epithelial cell nuclei are ∼30% higher than the corresponding glandular voxel dose. Additionally, due to the stochastic nature of radiation, there is considerable variation in energy deposition throughout a cell population within a ROI: for a typical glandular voxel dose of 4 mGy, the standard deviation of the specific energy for mammary epithelial cell nuclei is 85% relative to the mean. Thus, for a glandular voxel dose of 4 mGy at the centre of the breast, corresponding mammary epithelial cell nuclei will receive specific energies up to ∼9 mGy (considering the upper end of the 1σ standard deviation of the specific energy), while a ROI located 2 cm closer to the radiation source will receive specific energies up to ∼40 mGy. Energy deposition within mammary epithelial cell nuclei is sensitive to cell model details including cellular elemental compositions and nucleus size, underlining the importance of realistic cellular models.

CONCLUSIONS

There is considerable variation in energy deposition on both macro- and microscopic length scales for mammography, with glandular voxel doses and corresponding cell nuclei specific energies many times higher than the MGD in parts of the breast. These results should be considered for radiation-induced cancer risk evaluation in mammography which has traditionally focused on a single metric such as the MGD.

The influence of tissue composition uncertainty on dose distributions in brachytherapy

BACKGROUND AND PURPOSE

Model-based dose calculation algorithms (MBDCAs) have evolved from serving as a research tool into clinical practice in brachytherapy. This study investigates primary sources of tissue elemental compositions used as input to MBDCAs and the impact of their variability on MBDCA-based dosimetry.

MATERIALS AND METHODS

Relevant studies were retrieved through PubMed. Minimum dose delivered to 90% of the target (D₉₀), minimum dose delivered to the hottest specified volume for organs at risk (OAR) and mass energy-absorption coefficients (μ_en/ρ) generated by using EGSnrc "g" user-code were compared to assess the impact of compositional variability.

RESULTS

Elemental composition for hydrogen, carbon, oxygen and nitrogen are derived from the gross contents of fats, proteins and carbohydrates for any given tissue, the compositions of which are taken from literature dating back to 1940-1950. Heavier elements are derived from studies performed in the 1950-1960. Variability in elemental composition impacts greatly D₉₀ for target tissues and doses to OAR for brachytherapy with low energy sources and less for ¹⁹²Ir-based brachytherapy. Discrepancies in μ_en/ρ are also indicative of dose differences.

CONCLUSIONS

Updated elemental compositions are needed to optimize MBDCA-based dosimetry. Until then, tissue compositions based on gross simplifications in early studies will dominate the uncertainties in tissue heterogeneity.