부산대학교 도서관

Background: Palliative radiotherapy (PRT) is an effective treatment for managing symptoms of advanced cancer. At least half of all radiation treatments are delivered with palliative intent, aimed at relieving symptoms, such as pain or shortness of breath. Symptomatic patients must receive PRT quickly, therefore expeditious treatment planning is essential. Standard radiation planning requires a dedicated CT scan acquired at the cancer centre, called a 'CT simulation', which facilitates treatment planning (i.e. tumor delineation, placement of radiation beams and dose calculation). However, the CT simulation process creates a bottleneck and often leads to delays in starting treatment. Other researchers have indicated that CT simulation can be replaced by the use of standard diagnostic CT scans for target delineation and planning, which are normally acquired through the radiology department as part of standard patient workup. The goals of this feasibility study are to assess the efficacy, acceptability and scalability of diagnostic-CT-enabled planning, compared to conventional CT simulation planning, for patients receiving PRT to bone, soft tissue and lung disease. Methods: This is a randomized, phase II study, with 33 PRT patients to be randomized in a 1:2 ratio between conventional CT simulation (Arm 1), and the diagnostic CT enabled planning workflow (Arm 2). Patients will be stratified by treatment target volume (bone and soft tissue metastasis vs. primary or metastatic intrathoracic disease targets). The primary endpoint is the amount of time the patient spends at the cancer centre. Secondary endpoints include efficacy (rate of plan deliverability and rate of plan acceptability on blinded dose distribution review), stakeholder acceptability (based on patient and clinician perception of acceptability questionnaires) and scalability. Discussion: This study will investigate the efficacy, acceptability and scalability of a "sim-free" PRT pathway compared to conventional CT simulation. The workflow may provide opportunity for resource optimization by using pre-existing diagnostic imaging and requires minimal investment due to its similarity to current PRT models. It also offers potential benefit to patients by eliminating an imaging procedure, reducing the amount of time spent at the cancer centre, and expediting time to treatment. Trial registration: Clinicaltrials.gov identifier: NCT05233904. Date of registration: February 10, 2022; current version: 1.4 on April 29, 2022. [ABSTRACT FROM AUTHOR]