Quantification of the skin sparing effect achievable with high-energy photon beams when carbon fiber tables are used

A clinical trial to compare a 3D-printed bolus with a conventional bolus with the aim of reducing cardiopulmonary exposure in postmastectomy patients with volumetric modulated arc therapy

BACKGROUND

We compared the dosimetry, application, and acute toxicity of a 3D-printed and a conventional bolus for postmastectomy radiotherapy (PMRT) with volumetric modulated arc therapy (VMAT). Materials and Methods Eligible patients (n = 75) with PMRT breast cancer were randomly selected to receive VMAT with a conventional bolus or a 3D-printed bolus. The primary endpoint was a 10% decrease in the mean heart dose to left-sided breast cancer patients. The secondary endpoint was a 5% decrease in the mean ipsilateral lung dose to all patients. A comparative analysis was carried out of the dosimetry, normal tissue complication probability (NTCP), acute skin toxicity, and radiation pneumonitis.

RESULTS

Compared to a conventional bolus, the mean heart dose in left-sided breast cancer was reduced by an average of 0.8 Gy (5.5 ± 1.3 Gy vs. 4.7 ± 0.8 Gy, p = 0.035) and the mean dose to the ipsilateral lung was also reduced by an average of 0.8 Gy (12.4 ± 1.0 Gy vs. 11.6 ± 0.8 Gy, p < 0.001). The values for V_50Gy of the PTV of the chest wall for the 3D-printed and conventional boluses were 95.4 ± 0.6% and 94.8 ± 0.8% (p = 0.026) and the values for the CI of the entire PTV were 0.83 ± 0.02 and 0.80 ± 0.03 (p < 0.001), respectively. The NTCP for the 3D-printed bolus was also reduced to an average of 0.14% (0.32 ± 0.19% vs. 0.18 ± 0.11%, p = 0.017) for the heart and 0.45% (3.70 ± 0.67% vs. 3.25 ± 0.18%, p < 0.001) for the ipsilateral lung. Grade 2 and Grade 1 radiation pneumonitis were 0.0% versus 7.5% and 14.3% versus 20.0%, respectively (p = 0.184).

CONCLUSIONS

The 3D-printed bolus may reduce cardiopulmonary exposure in postmastectomy patients with volumetric modulated arc therapy.

Integral dose based inverse optimization objective function promises lower toxicity in head-and-neck

PURPOSE

The voxels in a CT data sets contain density information. Besides its use in dose calculation density has no other application in modern radiotherapy treatment planning. This work introduces the use of density information by integral dose minimization in radiotherapy treatment planning for head-and-neck squamous cell carcinoma (HNSCC).

MATERIALS AND METHODS

Eighteen HNSCC cases were studied. For each case two intensity modulated radiotherapy (IMRT) plans were created: one based on dose-volume (DV) optimization, and one based on integral dose minimization (Energy hereafter) inverse optimization. The target objective functions in both optimization schemes were specified in terms of minimum, maximum, and uniform doses, while the organs at risk (OAR) objectives were specified in terms of DV- and Energy-objectives respectively. Commonly used dosimetric measures were applied to assess the performance of Energy-based optimization. In addition, generalized equivalent uniform doses (gEUDs) were evaluated. Statistical analyses were performed to estimate the performance of this novel inverse optimization paradigm.

RESULTS

Energy-based inverse optimization resulted in lower OAR doses for equivalent target doses and isodose coverage. The statistical tests showed dose reduction to the OARs with Energy-based optimization ranging from ∼2% to ∼15%.

CONCLUSIONS

Integral dose minimization based inverse optimization for HNSCC promises lower doses to nearby OARs. For comparable therapeutic effect the incorporation of density information into the optimization cost function allows reduction in the normal tissue doses and possibly in the risk and the severity of treatment related toxicities.

Automated inverse optimization facilitates lower doses to normal tissue in pancreatic stereotactic body radiotherapy

Purpose

Inverse planning is trial-and-error iterative process. This work introduces a fully automated inverse optimization approach, where the treatment plan is closely tailored to the unique patient anatomy. The auto-optimization is applied to pancreatic stereotactic body radiotherapy (SBRT).

Materials and methods

The automation is based on stepwise reduction of dose-volume histograms (DVHs). Five uniformly spaced points, from 1% to 70% of the organ at risk (OAR) volumes, are used. Doses to those DVH points are iteratively decreased through multiple optimization runs. With each optimization run the doses to the OARs are decreased, while the dose homogeneity over the target is increased. The iterative process is terminated when a pre-specified dose heterogeneity over the target is reached. Twelve pancreatic cases were retrospectively studied. Doses to the target, maximum doses to duodenum, bowel, stomach, and spinal cord were evaluated. In addition, mean doses to liver and kidneys were tallied. The auto-optimized plans were compared to the actual treatment plans, which are based on national protocols.

Results

The prescription dose to 95% of the planning target volume (PTV) is the same for the treatment and the auto-optimized plans. The average difference for maximum doses to duodenum, bowel, stomach, and spinal cord are -4.6 Gy, -1.8 Gy, -1.6 Gy, and -2.4 Gy respectively. The negative sign indicates lower doses with the auto-optimization. The average differences in the mean doses to liver and kidneys are -0.6 Gy, and -1.1 Gy to -1.5 Gy respectively.

Conclusions

Automated inverse optimization holds great potential for personalization and tailoring of radiotherapy to particular patient anatomies. It can be utilized for normal tissue sparing or for an isotoxic dose escalation.

Integral Dose-Based Inverse Optimization May Reduce Side Effects in Radiotherapy of Prostate Carcinoma

PURPOSE

The purpose of this work is to apply a novel inverse optimization approach, based on utilization of quantitative imaging information in the optimization function, to prostate carcinoma.

MATERIALS AND METHODS

This new inverse optimization algorithm relies upon quantitative information derived from computed tomography (CT) imaging studies. The Hounsfield numbers of the CT voxels are converted to physical density, which in turn is used to calculate voxel mass and the corresponding integral dose, by summation over the product of dose and mass in each dose voxel. This integral dose is used for plan optimization through its global minimization. The optimization results are compared to the optimization results derived from most commonly used dose-volume-based inverse optimization, where objective functions are formed as summation over all dose voxels of the squared differences between voxel doses and user specified doses. The data from 25 prostate plans were optimized with dose-volume histogram (DVH) and integral dose (energy) minimization objective functions. The results obtained with the energy- and DVH-based optimization schemes were studied through commonly used dosimetric indices (DIs). Statistical equivalence tests were further performed to establish population-based significance results.

RESULTS

Both DVH- and energy-based plans for each case were normalized so that 95% of the planning target volume receives the prescription dose. The average differences for the rectum and bladder DIs ranged from 1.6 to 25%, where the energy-based quantities were lower. For both femoral heads, the energy-based optimization-derived doses were lower on average by 32%. The statistical tests demonstrated that the significant differences in the tallied dose indices range from 2.7% to more than 50% for rectum, bladder, and femoral heads.

CONCLUSION

For majority of the clinically relevant dosimetric quantities, energy-based inverse optimization performs better than the standard of care DVH-based optimization in prostate carcinoma. The population averaged statistically significant differences range from ~3 to ~50%. Therefore, this newly proposed optimization approach, incorporating explicitly quantitative imaging information in the inverse optimization function, holds potential for further reduction of complication rates in prostate cancer.

A Patient-Specific Polylactic Acid Bolus Made by a 3D Printer for Breast Cancer Radiation Therapy

Purpose

The aim of this study was to assess the feasibility and advantages of a patient-specific breast bolus made using a 3D printer technique.

Methods

We used the anthropomorphic female phantom with breast attachments, which volumes are 200, 300, 400, 500 and 650 cc. We simulated the treatment for a right breast patient using parallel opposed tangential fields. Treatment plans were used to investigate the effect of unwanted air gaps under bolus on the dose distribution of the whole breast. The commercial Super-Flex bolus and 3D-printed polylactic acid (PLA) bolus were applied to investigate the skin dose of the breast with the MOSFET measurement. Two boluses of 3 and 5 mm thicknesses were selected.

Results

There was a good agreement between the dose distribution for a virtual bolus generated by the TPS and PLA bolus. The difference in dose distribution between the virtual bolus and Super-Flex bolus was significant within the bolus and breast due to unwanted air gaps. The average differences between calculated and measured doses in a 200 and 300 cc with PLA bolus were not significant, which were -0.7% and -0.6% for 3mm, and -1.1% and -1.1% for 5 mm, respectively. With the Super-Flex bolus, however, significant dose differences were observed (-5.1% and -3.2% for 3mm, and -6.3% and -4.2% for 5 mm).

Conclusion

The 3D-printed solid bolus can reduce the uncertainty of the daily setup and help to overcome the dose discrepancy by unwanted air gaps in the breast cancer radiation therapy.

New approach in lung cancer radiotherapy offers better normal tissue sparing

PURPOSE

Medical images are more than pictures. They contain additional quantitative information which can be interrogated, quantified, and utilized. Besides anatomical information computed tomography (CT) imaging data provide electron density information. Radiotherapy use of this density information is limited to its application only in dose calculations. The direct product of dose, density, and volume forms a quantity called integral dose. The integral dose delivered to a volume of interest is the total energy deposited in that volume. Here it is hypothesized that minimization of the integral dose is advantageous in radiotherapy planning. The purpose of this work is to study the incorporation of quantitative imaging information in radiotherapy inverse optimization through total energy minimization (Energy hereafter).

DESIGN

Twenty lung patient plans were studied. For each patient density was quantified on voxel-by-voxel basis through image gray value-to-density conversion curves. Energy-based objective function was used for inverse radiotherapy plan optimization. The obtained plans were evaluated in the light of current standard of care, based on dose-volume (DVH) optimization approach.

RESULTS

The statistical significance analyses of the results indicated that the doses to normal tissue were between 14% and 45% lower, when Energy-based optimization was used instead of DVH-based optimization.

CONCLUSION

Incorporation of quantitative imaging information, through CT derived density, in the optimization cost function allows reduction of dose to normal tissue for NSCLC cases. Energy-based radiotherapy plans result in lower normal tissue dose and potentially lower complication rates compared to standard of care.

Confirmation of Skin Doses Resulting from Bolus Effect of Intervening Alpha-cradle and Carbon Fiber Couch in Radiotherapy

In this study, we verified the treatment planning calculations of skin doses with the incorporation of the bolus effect due to the intervening alpha-cradle (AC) and carbon fiber couch (CFC) using radiochromic EBT2 films. A polystyrene phantom (25 × 25 × 15 cm3) with six EBT2 films separated by polystyrene slabs, at depths of 0, 0.1, 0.2, 0.5, 1, 1.4 cm, was positioned above an AC, which was ~1 cm thick. The phantom and AC assembly were CT scanned and the CT-images were transferred to the treatment planning system (TPS) for calculations in three scenarios: (A) ignoring AC and CFC, (B) accounting for AC only, (C) accounting for both AC and CFC. A single posterior 10 × 10 cm2 field, a pair of posterior-oblique 10 × 10 cm2 fields, and a posterior IMRT field (6 MV photons from a Varian Trilogy linac) were planned. For each radiation field configuration, the same MU were used in all three scenarios in the TPS. Each plan for scenario C was delivered to expose a stack of EBT2 films in the phantom through AC and CFC. In addition, in vivo EBT2 film measurement on a lung cancer patient immobilized with AC undergoing IMRT was also included in this study. Point doses and planar distributions generated from the TPS for the three scenarios were compared with the data from the EBT2 film measurements. For all the field arrangements, the EBT2 film data including the in vivo measurement agreed with the doses calculated for scenario (C), within the uncertainty of the EBT2 measurements (~4%). For the single posterior field (a pair of posterior-oblique fields), the TPS generated doses were lower than the EBT2 doses by 34%, 33%, 31%, 13% (34%, 31%, 31%, 11%) for scenario A and by 27%, 25%, 22%, 8% (25%, 21%, 21%, 6%) for scenario B at the depths of 0, 0.1, 0.2, 0.5 cm, respectively. For the IMRT field, the 2D dose distributions at each depth calculated in scenario C agree with those measured data. When comparing the central axis doses for the IMRT field, we found the TPS generated doses for scenario A (B) were lower than the EBT2 data by 35%, 34%, 31%, 16% (29%, 26%, 23%, 10%) at the depths of 0, 0.1, 0.2, 0.5 cm, respectively. There were no significant differences for the depths of 1.0 and 1.4 cm for all the radiation fields studied. TPS calculation of doses in the skin layers accounting for AC and CFC was verified by EBT2 film data. Ignoring the presence of AC and/or CFC in TPS calculation would significantly underestimate the doses in the skin layers. For the clinicians, as more hypofractionated regimens and stereotactic regimens are being used, this information will be useful to avoid potential serious skin toxicities, and also assist in clinical decisions and report these doses accurately to relevant clinical trials/cooperative groups, such as RTOG.

A validation of carbon fiber imaging couch top modeling in two radiation therapy treatment planning systems: Philips Pinnacle3 and BrainLAB iPlan RT Dose

BACKGROUND

Carbon fiber (CF) is now the material of choice for radiation therapy couch tops. Initial designs included side metal bars for rigidity; however, with the advent of IGRT, involving on board imaging, new thicker CF couch tops without metal bars have been developed. The new design allows for excellent imaging at the expense of potentially unacceptable dose attenuation and perturbation.

OBJECTIVES

We set out to model the BrainLAB imaging couch top (ICT) in Philips Pinnacle(3) treatment planning system (TPS), to validate the already modeled ICT in BrainLAB iPlan RT Dose treatment planning system and to compute the magnitude of the loss in skin sparing.

RESULTS

Using CF density of 0.55 g/cm(3) and foam density of 0.03 g/cm(3), we demonstrated an excellent agreement between measured dose and Pinnacle(3) TPS computed dose using 6 MV beam. The agreement was within 1% for all gantry angle measured except for 120°, which was 1.8%. The measured and iPlan RT Dose TPS computed dose agreed to within 1% for all gantry angles and field sizes measured except for 100° where the agreement was 1.4% for 10 cm × 10 cm field size. Predicted attenuation through the couch by iPlan RT Dose TPS (3.4% - 9.5%) and Pinnacle(3) TPS (2% - 6.6%) were within the same magnitude and similar to previously reported in the literature. Pinnacle(3) TPS estimated an 8% to 20% increase in skin dose with increase in field size. With the introduction of the CF couch top, it estimated an increase in skin dose by approximately 46 - 90%. The clinical impact of omitting the couch in treatment planning will be dependent on the beam arrangement, the percentage of the beams intersecting the couch and their angles of incidence.

CONCLUSION

We have successfully modeled the ICT in Pinnacle(3) TPS and validated the modeled ICT in iPlan RT Dose. It is recommended that the ICT be included in treatment planning for all treatments that involve posteriors beams. There is a significant increase in skin dose that is dependent on the percentage of the beam passing through the couch and the angle of incidence.

Biological optimization in volumetric modulated arc radiotherapy for prostate carcinoma

PURPOSE

To investigate the potential benefits achievable with biological optimization for modulated volumetric arc (VMAT) treatments of prostate carcinoma.

METHODS AND MATERIALS

Fifteen prostate patient plans were studied retrospectively. For each case, planning target volume, rectum, and bladder were considered. Three optimization schemes were used: dose-volume histogram (DVH) based, generalized equivalent uniform dose (gEUD) based, and mixed DVH/gEUD based. For each scheme, a single or dual 6-MV, 356° VMAT arc was used. The plans were optimized with Pinnacle(3) (v. 9.0 beta) treatment planning system. For each patient, the optimized dose distributions were normalized to deliver the same prescription dose. The quality of the plans was evaluated by dose indices (DIs) and gEUDs for rectum and bladder. The tallied DIs were D(1%), D(15%), D(25%), and D(40%), and the tallied gEUDs were for a values of 1 and 6. Statistical tests were used to quantify the magnitude and the significance of the observed differences. Monitor units and treatment times for each optimization scheme were also assessed.

RESULTS

All optimization schemes generated clinically acceptable plans. The statistical tests indicated that biological optimization yielded increased organs-at-risk sparing, ranging from ~1% to more than ~27% depending on the tallied DI, gEUD, and anatomical structure. The increased sparing was at the expense of longer treatment times and increased number of monitor units.

CONCLUSIONS

Biological optimization can significantly increase the organs-at-risk sparing in VMAT optimization for prostate carcinoma. In some particular cases, however, the DVH-based optimization resulted in superior treatment plans.