Postmortem evidence of neuroinflammation in bipolar disorder: a systematic review

Abstract

Permanent breast seed implant (PBSI) is a developing brachytherapy technique for the treatment of early-stage breast cancer. In current practice, PBSI uses manual planning strategies to generate clinical treatment plans. In this work, a simulated annealing-based algorithm is developed to demonstrate the first application of inverse optimization for PBSI.Target, skin, and chest wall muscle contours, exported from a treatment planning system in digital imaging and communications in medicine format, are used as inputs. To optimize, the user defines the dose–volume histogram objectives for the target and specifies a relative weighting for target and skin constraints. A 10-patient cohort of previously treated patients was planned by using the inverse optimization algorithm. Plan quality was compared to the clinically treated manually generated plans using the V90%, V100%, V150%, and V200% for the planning target volume (PTV), V90% and D0.2 cc for skin dose, and PTV conformity indices.For each of the 10 patients, patient-wise paired differences between inverse and manual plans were analyzed and presented in box plots. Comparing inverse and manual planning techniques, a statistical difference was not observed (p > 0.05) in PTV coverage criteria (V90%, V100%) and dose to skin2mm. A statistical difference was observed in the inverse plans as a reduction of the V150% (mean of 6.2%) and increase in conformity index of the 20%, 50%, 90%, and 100% isodose lines.This work presents the first application of inverse optimization used to generate PBSI treatment plans. A 10-patient cohort previously treated with PBSI was retrospectively planned for comparison with the clinically treated manually generated plans.