OpenKBP-Opt: an international and reproducible evaluation of 76 knowledge-based planning pipelines.

Objective.To establish an open framework for developing plan optimization models for knowledge-based planning (KBP).Approach.Our framework includes radiotherapy treatment data (i.e. reference plans) for 100 patients with head-and-neck cancer who were treated with intensity-modulated radiotherapy. That data also includes high-quality dose predictions from 19 KBP models that were developed by different research groups using out-of-sample data during the OpenKBP Grand Challenge. The dose predictions were input to four fluence-based dose mimicking models to form 76 unique KBP pipelines that generated 7600 plans (76 pipelines × 100 patients). The predictions and KBP-generated plans were compared to the reference plans via: the dose score, which is the average mean absolute voxel-by-voxel difference in dose; the deviation in dose-volume histogram (DVH) points; and the frequency of clinical planning criteria satisfaction. We also performed a theoretical investigation to justify our dose mimicking models.Main results.The range in rank order correlation of the dose score between predictions and their KBP pipelines was 0.50-0.62, which indicates that the quality of the predictions was generally positively correlated with the quality of the plans. Additionally, compared to the input predictions, the KBP-generated plans performed significantly better (P< 0.05; one-sided Wilcoxon test) on 18 of 23 DVH points. Similarly, each optimization model generated plans that satisfied a higher percentage of criteria than the reference plans, which satisfied 3.5% more criteria than the set of all dose predictions. Lastly, our theoretical investigation demonstrated that the dose mimicking models generated plans that are also optimal for an inverse planning model.Significance.This was the largest international effort to date for evaluating the combination of KBP prediction and optimization models. We found that the best performing models significantly outperformed the reference dose and dose predictions. In the interest of reproducibility, our data and code is freely available.

Adenosine A2A Receptor Mediates Inhibition of Synovitis and Osteoclastogenesis after Electroacupuncture in Rats with Collagen-Induced Arthritis.

BACKGROUND: This study was to investigate the role of adenosine A2A receptors (A2AR) in inhibiting the effect of electroacupuncture (EA) on osteoclastogenesis in collagen-induced arthritis (CIA). METHODS: Wistar rats were divided into four groups: sham-control group, CIA-control group, CIA-EA group, and CIA-EA-SCH58261 (A2AR antagonist) group. We detected tumor necrosis factor-α (TNF-α), nuclear transcription factor-κB (NF-κB), receptor activator of NF-κB ligand (RANKL), protein kinase A (PKA), and extracellular regulatory protein kinase 1/2 (ERK1/2) in peripheral blood by ELISA. PKA, ERK1/2, and NF-κB in ankle joints were determined by western blotting. We evaluated the arthritis damage by histological examination and determined the number of osteoclasts by tartrate-resistant acid phosphatase (TRAP) staining. RESULTS: EA treatment downregulated the expression of TNF-α, RANKL, PKA, ERK1/2, and NF-κB in peripheral blood but increased the levels of PKA and ERK1/2 in ankle joints. Importantly, EA treatment reduced bone erosion as evidenced by the histological findings and inhibited osteoclastogenesis as revealed by TRAP staining. All these effects of the EA treatment were reversed by combining EA treatment with the A2AR antagonist SCH58261. CONCLUSION: Our data suggest that EA treatment activated A2AR. The effects of the A2AR antagonist SCH58261 suggest that the inhibition of osteoclast formation, the inhibition of TNF-α, RANKL, and NF-κB expression, and the increase of ERK1/2 are all dependent on this EA-induced A2AR activation. It is therefore likely that these pathways with clearly defined roles in inflammation and bone erosion are at least partially involved in the mediation of the inhibition of synovitis and osteoclast formation induced by EA.