RESUMO
Radiation therapy plays a crucial role in cancer treatment, necessitating precise delivery of radiation to tumors while sparing healthy tissues over multiple days. Computed tomography (CT) is integral for treatment planning, offering electron density data crucial for accurate dose calculations. However, accurately representing patient anatomy is challenging, especially in adaptive radiotherapy, where CT is not acquired daily. Magnetic resonance imaging (MRI) provides superior soft-tissue contrast. Still, it lacks electron density information, while cone beam CT (CBCT) lacks direct electron density calibration and is mainly used for patient positioning. Adopting MRI-only or CBCT-based adaptive radiotherapy eliminates the need for CT planning but presents challenges. Synthetic CT (sCT) generation techniques aim to address these challenges by using image synthesis to bridge the gap between MRI, CBCT, and CT. The SynthRAD2023 challenge was organized to compare synthetic CT generation methods using multi-center ground truth data from 1080 patients, divided into two tasks: (1) MRI-to-CT and (2) CBCT-to-CT. The evaluation included image similarity and dose-based metrics from proton and photon plans. The challenge attracted significant participation, with 617 registrations and 22/17 valid submissions for tasks 1/2. Top-performing teams achieved high structural similarity indices (≥0.87/0.90) and gamma pass rates for photon (≥98.1%/99.0%) and proton (≥97.3%/97.0%) plans. However, no significant correlation was found between image similarity metrics and dose accuracy, emphasizing the need for dose evaluation when assessing the clinical applicability of sCT. SynthRAD2023 facilitated the investigation and benchmarking of sCT generation techniques, providing insights for developing MRI-only and CBCT-based adaptive radiotherapy. It showcased the growing capacity of deep learning to produce high-quality sCT, reducing reliance on conventional CT for treatment planning.
RESUMO
BACKGROUND: Dual antiplatelet therapy (DAPT) helps prevent ischemic events after coronary stenting but comes with an increased risk of bleeding. Several risk scores have been proposed for the management of patients receiving DAPT, but no standardized tool exists for the purpose. We sought to compare the performance of the new PRECISE-DAPT (Predicting Bleeding Complication in Patients Undergoing Stent Implantation and Subsequent Dual Antiplatelet Therapy), CRUSADE (Can Rapid Risk Stratification of Unstable Angina Patients Suppress Adverse Outcomes with Early Implementation of the American College of Cardiology/American Heart Association Guidelines), and ACUITY (Acute Catheterization and Urgent Intervention Triage Strategy) scores for the prediction of bleeding in Korean patients receiving DAPT. METHODS AND RESULTS: Nine hundred and four consecutive patients who underwent stent implantation received DAPT. One-year bleedings were assessed using TIMI (Thrombolysis in Myocardial Infarction), GUSTO (Global Use of Strategies to Open Occluded Arteries), and BARC (Bleeding Academic Research Consortium). Bleeding events occurred in 154 patients (17.0%) by BARC type ≥3a criteria, 119 patients (13.2%) by the TIMI minor or major criteria, and 80 patients (8.8%) by the GUSTO moderate or severe criteria. In the C statistic analysis, CRUSADE, ACUITY, and PRECISE-DAPT scores showed high area under the curve values for 1-year bleeding (area under the curve 0.73, 0.75, and 0.75 for TIMI minor or major bleeding; area under the curve 0.81, 0.79, and 0.82 for GUSTO moderate to severe; and area under the curve 0.79, 0.81, and 0.81 for BARC type ≥3a, respectively). The discriminate ability of PRECISE-DAPT was similar to CRUSADE and ACUITY in bleeding complications. However, the PRECISE-DAPT score was better at reclassifying the risk of 1-year bleeding compared with ACUITY for the 3 bleeding criteria. CONCLUSIONS: The PRECISE-DAPT score is a simple 5-item risk score that represents a standardized tool for the prediction of 1-year bleeding in Korean patients receiving DAPT, regardless of bleeding definition.
