Demonstration of simulated annealing optimization for permanent breast seed implant treatment planning

Dosimetric consequences of seed placement accuracy in permanent breast seed implant brachytherapy

PURPOSE

This study quantifies the dosimetric impact of implant accuracy and derives a quantitative relationship relating implant accuracy to target dosimetry.

METHODS AND MATERIALS

A framework was developed to simulate multiple implants for error combinations. Spherical clinical target volumes (CTVs) were modeled with volumes 1.4 cm³, 9.2 cm³, and 20.6 cm³, representing the range seen clinically. Each CTV was expanded 10 mm isotropically to create a planning target volume (PTV).. Random and systematic seed placement errors were simulated by shifting needles from their planned positions. Implant errors were simulated over the range of clinically practical errors in permanent breast seed implant. The relative effect on target coverage was evaluated. Regression analysis was performed to derive relationships between CTV dosimetry and the magnitude of implant accuracy. The validity of the clinically used 10 mm PTV margin for each of the CTVs was assessed.

RESULTS

Introducing practical implant errors resulted in CTV V_90% median (10th and 90th percentile) of 97.7% (85.9% and 100%), 96.2% (86.8% and 99.7%), and 100% (77.8% and 100%) for the typical, large, and small CTV, respectively. All CTVs show similar trends in target coverage. Polynomials were derived relating seed placement accuracy to median (R² = 0.82) and 10th percentile (R² = 0.78) CTV V_90%._. CONCLUSIONS: This work quantitatively describes the relationship between implant accuracy and CTV coverage. Based on simulations, the 10 mm PTV margin is adequate to maintain target coverage. These equations can be used with institutional seed placement accuracy to estimate coverage.

Does inverse planning improve plan quality in interstitial high-dose-rate breast brachytherapy?

Purpose

To investigate the effect of input parameters for an inverse optimization algorithm, and dosimetrically evaluate and compare clinical treatment plans made by inverse and forward planning in high-dose-rate interstitial breast implants.

Material and methods

By using a representative breast implant, input parameters responsible for target coverage and dose homogeneity were changed step-by-step, and their optimal values were determined. Then, effects of parameters on dosimetry of normal tissue and organs at risk were investigated. The role of dwell time modulation restriction was also studied. With optimal input parameters, treatment plans of forty-two patients were re-calculated using an inverse optimization algorithm (HIPO). Then, a pair-wise comparison between forward and inverse plans was performed using dose-volume parameters.

Results

To find a compromise between target coverage and dose homogeneity, we recommend using weight factors in the range of 70-90 for minimum dose, and in the range of 10-30 for maximum dose. Maximum dose value of 120% with a weight factor of 5 is recommended for normal tissue. Dose constraints for organs at risk did not play an important role, and the dwell time gradient restriction had only minor effect on target dosimetry. In clinical treatment plans, at identical target coverage, the inverse planning significantly increased the dose conformality (COIN, 0.75 vs. 0.69, p < 0.0001) and improved the homogeneity (DNR, 0.35 vs. 0.39, p = 0.0027), as compared to forward planning. All dosimetric parameters for non-target breast, ipsilateral lung, ribs, and heart were significantly better with inverse planning. The most exposed small volumes for skin were less in HIPO plans, but without statistical significance. Volume irradiated by 5% was 173.5 cm³ in forward and 167.7 cm³ in inverse plans (p = 0.0247).

Conclusions

By using appropriate input parameters, inverse planning can provide dosimetrically superior dose distributions over forward planning in interstitial breast implants.

Establishing a simulation-based education program for radiation oncology learners in permanent seed implant brachytherapy: Building validation evidence

PURPOSE

The purpose of this study was to establish a simulation-based education program for radiation oncology learners in permanent seed implant brachytherapy. The first step in formalizing any education program is a validation process that builds evidence-based verification that the learning environment is appropriate.

METHODS AND MATERIALS

The primary education task allowed practitioners to use an anthropomorphic breast phantom to simulate a permanent seed implant brachytherapy delivery. Validation evidence is built by generating data to assess learner and expert cohorts according to their proficiency. Each practitioner's performance during the simulation was evaluated by seed placement accuracy, procedural time-to-complete, and two qualitative evaluation tools-a global rating scale and procedural checklist.

RESULTS

The average seed placement accuracy (±SD) was 8.1 ± 3.5 mm compared to 6.1 ± 2.6 mm for the learner and expert cohort, respectively. The median (range) procedural time-to-complete was 64 (60-77) minutes and 43 (41-50) minutes for the learner and expert cohort, respectively. Seed placement accuracy (student t-test, p < 0.05) and procedural time-to-complete (Mann-Whitney U-test, p < 0.05) were statistically different between the cohorts. In both the global rating scale and procedural checklist, the expert cohort demonstrated improved proficiency compared to the learner cohort.

CONCLUSIONS

This validation evidence supports the utilization of this simulation environment toward appropriately capturing the delivery experience of practitioners. The results demonstrate that, in all areas of evaluation, expert cohort proficiency was superior to learner cohort proficiency. This methodology will be used to establish a simulation-based education program for radiation oncology learners in permanent seed implant brachytherapy.

Post-implant analysis in permanent breast seed implant: automated plan reconstruction using simulated annealing

Purpose

Post-implant analysis in permanent breast seed implant (PBSI) brachytherapy is an important component of the quality assurance process that indicates dosimetric quality relevant to patient outcome, indicating salvage therapy if inadequate, as well as providing feedback to the brachytherapy team to improve future treatments. To measure geometric indices on implant quality, plan reconstruction must be performed to correlate each planned and post-implant seed location. In this work, a simulated-annealing-based algorithm is developed to perform this plan reconstruction automatically.

Material and methods

The plan reconstruction algorithm was developed in MATLAB, taking the patient pre-treatment and post-implant (Day 0) plan and associated contours as inputs. For 19 treated patients, a reconstruction was obtained that defined the correspondence between each planned and post-implant seed. The simulated-annealing algorithm was used to reconstruct each patient 10 times to assess the variability in convergence. Manual reconstructions performed by at least two independent observers to obtain consensus were defined as the ground truth; these were compared to the automatic reconstructions obtained by the algorithm. Metrics on seed placement accuracy and needle strand angulation were calculated for the patients.

Results

The algorithm performed reconstructions on 19 patients (1235 seeds) with ground-truth reconstructions, obtaining 97 ± 8% correct matches. This strong performance indicates the ability to incorporate this algorithm into the clinical quality assurance workflow.

Conclusions

The plan reconstruction algorithm developed herein performed very well in a 19-patient cohort. This algorithm can be incorporated into the clinical process to assist in the assessment of center-specific seed placement accuracy and can be used to gather implant metrics in an automated, standardized fashion for future PBSI trials.