A How-To Compendium for GammaPod Treatments, Clinical Workflow, and Clinical Program at an Early Adopting Institution

Breast irradiation following breast-conserving surgery is an integral part of breast conserving therapy for curative treatment of early-stage breast cancer^1-7. With the recognition that the majority of ipsilateral local relapses following breast-conserving therapy occur at the site of the tumor bed, several trials have since investigated the efficacy of accelerated partial-breast irradiation (APBI)^8-10 as an alternative to the established but less convenient option of daily whole breast irradiation over several weeks. However, the setup uncertainty and inter-fraction movement expected with 3-dimensional conformal radiation therapy (3D-CRT) APBI has generally required the use of larger planning target volume margin expansions, which ultimately results in a larger dose to normal tissues, as well as an association with worsened cosmesis^11-13. A stereotactic partial breast irradiation (S-PBI) approach is needed to allow more precise radiation therapy to the region of the primary tumor. As the GammaPod uses a vacuum assisted breast cup and pump, it allows for smaller CTV margins than 3D-CRT. Here, we describe our methods and workflow for efficient GammaPod S-PBI, as the second institution in the world to go live with GammaPod.

Correlation of treatment time to target volume for GammaPod treatments: A simple second calculation

Purpose

The GammaPod is a novel device for stereotactic breast treatments that employs 25 rotating Co‐60 sources while the patient is continuously translated in three axes to deliver a highly conformal dose to the target. There is no commercial software available for independent second calculations. The purpose of this study is to determine an efficient way to estimate GammaPod treatment times based on target volume and use it as a second calculation for patient‐specific quality assurance.

Methods

Fifty‐nine GammaPod (Xcision Medical Systems, LLC.) breast cancer patient treatments were used as the fitting dataset for this study. Similar to the Curie‐seconds concept in brachytherapy, we considered dose‐rate × time/(prescribed dose) as a function of target volumes. Using a MATLAB (Mathworks, Natick, MA, USA) script, we generated linear (with 95% confidence interval (CI)) and quadratic fits and tested the resulting equations on an additional set of 30 patients.

Results

We found a strong correlation between the dose‐rate × time/(prescribed dose) and patients’ target volumes for both the linear and quadratic models. The linear fit was selected for use and using the polyval function in MATLAB, a 95% CI graph was created to depict the accuracy of the prediction for treatment times. Testing the model on 30 additional patients with target volumes ranging from 20 to 188 cc yielded treatment times from 10 to 25 min that in all cases were within the predicted CI. The average absolute difference between the predicted and actual treatment times was 1.0 min (range 0–3.3 min). The average percent difference was 5.8% (range 0%–18.4%).

Conclusion

This work has resulted in a viable independent calculation for GammaPod treatment times. This method has been implemented as a spreadsheet that is ready for clinical use to predict and verify the accuracy of breast cancer treatment times.

Simplified method for determining dose to a non-water phantom through the use of ND,w and IAEA TRS 483 for the GammaPod

PURPOSE

GammaPod, a breast stereotactic radiosurgery device, utilizes 25 rotating Co-60 sources to deliver highly conformal dose distributions. The GammaPod system requires that reference dosimetry be performed in a specific vendor-supplied poly-methylmethacrylate (PMMA) phantom. The nonstandard nature of GammaPod dosimetry, in both the phantom material and machine-specific reference (msr), prohibits use of the American Association of Physicists in Medicine Task Group 51 (TG-51) protocol. This study proposes a practical method using TRS 483 to make the reference dosimetry procedure simpler and to reduce overall uncertainties.

METHODS

The dose to PMMA (D_PMMA) is determined under msr conditions using TRS 483 with an Exradin A1SL chamber placed in a PMMA phantom. The conversion factor, which converts from the dose-to-water (D_w) in broad-beam Co-60 reference geometry to D_PMMA in the msr small field Co-60 (Q_msr) geometry, is derived using the Monte Carlo simulations and procedure described in TRS 483.

RESULTS

The new conversion factor value for an Exradin A1SL chamber is 0.974. When combined with N_D,w, D_PMMA differs by 0.5% from the TG-21/N_x method and 0.2% from the IROC values. Uncertainty decreased from 2.2% to 1.6%.

CONCLUSION

We successfully implemented TRS 483 reference dosimetry protocols utilizing N_D,w for the GammaPod in the PMMA phantom. These results show not only agreement between measurements performed with the previously published method and independent thermoluminescent dosimetry measurements but also reductions in uncertainty. This also provides readers with a pathway to develop their own IAEA TRS 483 factor for any new small field machine that may be developed.

Reproducibility of a novel, vacuum-assisted immobilization for breast stereotactic radiotherapy

A novel, breast‐specific stereotactic radiotherapy device has been developed for delivery of highly conformal, accelerated partial breast irradiation. This device employs a unique, vacuum‐assisted, breast cup immobilization system that applies a gentle, negative pressure to the target breast with the patient in the prone position. A device‐specific patient loader is utilized for simulation scanning and device docking. Prior to clinical activation, a prospective protocol enrolled 25 patients who had been or were to be treated with breast conservation surgery and adjuvant radiotherapy for localized breast cancer. The patients underwent breast cup placement and two separate CT simulation scans. Surgical clips within the breast were mapped and positions measured against the device’s integrated stereotactic fiducial/coordinate system to confirm reproducible and durable immobilization during the simulation, treatment planning, and delivery process for the device. Of the enrolled 25 patients, 16 were deemed eligible for analysis. Seventy‐three clips (median, 4; mean, 4.6; range, 1–8 per patient) were mapped in these selected patients on both the first and second CT scans. X, Y, and Z coordinates were determined for the center point of each clip. Length of vector change in position was determined for each clip between the two scans. The mean displacement of implanted clips was 1.90 mm (median, 1.47 mm; range, 0.44–6.52 mm) (95% CI, 1.6–2.20 mm). Additional analyses stratified clips by position within the breast and depth into the immobilization cup. Overall, this effort validated the clinically utilized 3‐mm planning target volume margin for accurate, reliable, and precise employment of the device.