Cargando…
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...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Termedia Publishing House
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6431098/ https://www.ncbi.nlm.nih.gov/pubmed/30911312 http://dx.doi.org/10.5114/jcb.2019.83338 |
Sumario: | 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. |
---|