Risultati per: Scoperto bersaglio per il trattamento del cancro al pancreas
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Evaluation of hypofractionated adaptive radiotherapy using the MR Linac in localised pancreatic cancer: protocol summary of the Emerald-Pancreas phase 1/expansion study located at Oxford University Hospital, UK
Introduction
Online adaptive MR-guided radiotherapy allows for dose escalation to pancreatic cancer while sparing surrounding critical organs. We seek to evaluate the safety of delivering hypofractionated five-fraction, three-fraction and single-fraction MR-guided stereotactic ablative radiotherapy (SABR) to the pancreas.
Methods and analysis
This is a single-centre three-arm phase 1 non-randomised safety study. Patients with localised pancreatic cancer will receive either 50 Gy in five (biological equivalent dose (BED10)=100 Gy), 39 Gy in three (BED10=90 Gy) or 25 Gy in a single fraction (BED10=87.5 Gy) MR-guided daily online adaptive radiotherapy. Each fractionation regimen will be assessed as independent cohorts to determine tolerability, assessed continuously using Bayesian conjugate posterior beta distributions. The primary endpoint of the study is to establish the safety of five-fraction, three-fraction and single-fraction MR-guided hypofractionation SABR in localised pancreatic cancer by assessing dose-limiting toxicities. Secondary endpoints include overall survival, progression-free survival, local control rates, overall control rate, resection rates, long-term toxicities and freedom from second-line chemotherapy. This study plans to also explore imaging and immune biomarkers that may be useful to predict outcome and personalise treatment. The trial will recruit up to 60 patients with a safety run-in.
Ethics and dissemination
The trial is approved by the West Midlands—Black Country Research Ethics Committee 22/WM/0122. The results will be disseminated via conference presentations, peer-reviewed scientific journals and submission to regulatory authorities. The data collected for the study, including individual participant data, will be made available to researchers on request to the study team and with appropriate reason, via octo-enquiries@oncology.ox.ac.uk. The shared data will be deidentified participant data and will be available for 3 years following publication of the study. Data will be shared with investigator support, after approval of a proposal and with a signed data access agreement.
Trial registration number
ISRCTN10557832
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Automated Artificial Intelligence Model Trained on a Large Dataset Can Detect Pancreas Cancer on Diagnostic CTs as well as Visually Occult Pre-invasive Cancer on Pre-diagnostic CTs
The aims of our case-control study were – 1) to develop an automated 3D-Convolutional Neural Network (CNN) for detection of PDA on diagnostic CTs, 2) evaluate its generalizability on multi-institutional public datasets, 3) its utility as a potential screening tool using a simulated cohort with high pretest probability, and 4) its ability to detect visually occult pre-invasive cancer on pre-diagnostic CTs.