A Master Trial Assessing the Technical Feasibility of First-In-Human Real-Time Image Guided Radiation Therapy Methods

The goal of this clinical trial is to determine whether Real-Time Image Guided Radiation Therapy is a feasible method for radiation therapy delivery for patients with cancer. The main questions it aims to answer are: * Can all fractions per patient which are intended to be delivered with the real-time IGRT method be completed as planned? * Can the beam accurately hit the tumour in ≥85% of fractions? * Are there any unexpected grade \>3 acute toxicities? Participants will not require any additional treatments or preparation procedures above those required for normal radiation therapy treatment, to participate in this study.

Real-time IGRT is a master trial to assess the technical feasibility of first-in-human real-time image guided radiation therapy methods. Real-time image guided radiation therapy (IGRT) methods image the cancerous tumour in real-time, enabling the treatment beam to focus its destructive energy on the patient's cancer, not their healthy tissue. Using a real-time IGRT method available on scarce $10M MRI-guided radiation therapy devices, has halved the incidence of acute grade 2 or greater genitourinary (GU) toxicity for prostate cancer patients. However, \>95% of radiotherapy is given on standard $3M devices. The halving in GU toxicity was confirmed in a study from Memorial Sloan-Kettering using combined kilovoltage and megavoltage guidance. This clinical benefit has led to a global demand: over 70% of centres want better real-time IGRT methods but are limited by resources and capacity. The tipping point is the implementation of real-time IGRT methods on standard devices. The Real-time IGRT trial addresses this unmet need by assessing an array of real-time IGRT methods. To establish real-time IGRT methods, the University of Sydney partner hospitals and cancer centres have been working together across many different cancers, to create a database of images that have been, and are being, used to develop real-time IGRT methods. This development has led to the creation of LEARN, the Learning Environment for Artificial Intelligence in Radiotherapy New Technology, and the associated image acquisition study (https://clinicaltrials.gov/study/NCT05184790). The LEARN study looks at images retrospectively, meaning patients do not directly benefit from their involvement. To achieve benefit for study patients, and ultimately in broader practice, prospective implementation of real-time IGRT methods is required. This umbrella protocol, Real-time IGRT, enables a framework for the safe implementation and evaluation of real-time IGRT methods. Patient dosimetric and geometric targeting benefits will be measured, with the information acquired used to further improve the safety and accuracy of real-time IGRT methods. The technologies being developed are numerous, covering different individual and combinations of imaging methods (surface, kV, MV), are applicable to different cancer sites, use marker and markerless approaches, and track one or more targets and normal tissues. To perform a feasibility study for each single innovation and for each single tumour site is time consuming when using a standard trial protocol. Instead, a master protocol trial comprises one general protocol that includes multiple subgroups and/or multiple interventions. Given this large variety of methods to be tested, a master protocol trial is the most efficient to maximise the safe testing of technologies, and to cease or pause technologies that do not meet the clinical requirements. The master protocol trial aims to increase efficiency in terms of trial infrastructure and protocol administr Покажи пълното описание...

Inclusion Criteria: * Patients 18 years or older to be treated with curative radiation therapy * Patients with brain, breast, head and neck, kidney, liver, lung, pancreas, prostate or spine cancer * ECOG performance status 0-2 * Ability to understand and the willingness to sign a written informed consent document Exclusion Criteria: * Pregnancy, * Patients with any other clinically significant medical condition which, in the opinion of the treating physician, makes it undesirable for the patient to participate in the study or which could jeopardize compliance with study requirements or severe psychiatric illness/social situation * Additional inclusion and exclusion criteria may apply to a specific sub-study