RASOR sharp:

MRI-based radiotherapy planning using a single MRI sequence

Aim

We propose the development of an MRI-only radiotherapy treatment planning system to improve and streamline minimally-invasive cancer therapy guidance and control, increase treatment accuracy and reduce both patient burden and medical costs.

Background

Radiotherapy is a main pillar in cancer treatment. A crucial step in radiotherapy is radiation treatment planning (RTP), which involves localization of tumor tissue and identification of organs-at-risk (OAR) to facilitate targeted irradiation of the tumor while minimizing dose to these OARs. Prior to treatment, RTP aims to establish an optimally 3D sculpted dose distribution by calculating a sophisticated beam plan that irradiates the tumor from different angles and with different beam shapes. For accurate dose calculations not only geometric information on the tumor and OARs is required, but also on tissue electron densities.

Problem definition

Imaging of the patient is vital for RTP and CT is de facto the standard imaging modality. CT provides easy 3D electron density mapping, localization of implanted fiducial markers and bony anatomy. On the other hand, tumor and soft tissue contrast on CT scans is limited. To compensate for the latter, from the mid 2000s onwards, radiotherapy departments started adding MRI on a routine basis. Its superior soft tissue contrast allows for much better delineation of tumor target volume and OARs. As standard MRI sequences do not allow localization of implanted fiducial markers and assessment of the tissue electron density, patients have to undergo two exams in clinical practice: a CT and a MRI scan. Besides extra patient burden and medical costs, this introduces inevitable geometrical inaccuracies related to interscan differences and image fusion.

Objective 1: Solving the problem for conventional radiotherapy

The first objective is the development of an MRI-only RTP for conventional radiotherapy. This results in a much more streamlined workflow allowing faster start of treatment for patients. Obviously, this reduces both patient burden and medical costs. Furthermore, it improves treatment accuracy by removing the need for multi-modal image fusion eliminating systematic positioning errors related to interscan geometrical differences and the inevitable inaccuracies encountered in image fusion.

Objective 2: Enabling the next step in image-guided radiotherapy

"Seeing what you treat" is where the MRI-linac is about. This radiotherapy system with integrated 1.5 T MRI functionality is a revolutionary system pioneered by our group which is currently a large industrial project of Elekta AB and our project partner Philips Healthcare. This system facilitates simultaneous irradiation and MR imaging and is being prepared for clinical introduction. MR based planning plays a key role for the MRI-linac as new treatment plans have to be calculated prior to each radiation fraction to account for the current state of the patient's anatomy. Basically this is the same challenge as for the objective for conventional radiotherapy. However, now MRI based dose calculations have to be performed while the patient is on the treatment table. Ultimately, also anatomical changes during treatment might be accounted for by near-real-time plan adaptations.

Methods and innovations

In an MRI only RTP workflow several steps typically based on CT imaging should be accomplished MRI-based, including accurate detection of fiducials for position verification and generation of electron density maps for dose planning. The ideal MRI only imaging approach would constitute a single 3D scan with high geometric fidelity and which would facilitate detection of gold fiducials and pseudo CT (pCT) generation. Preferentially, the required acquisition and processing time to generate a pCT should take only a few minutes to allow on-line plan adaptation for the MRI-linac.
The approach we propose constitutes the development of a multi-functional master sequence meeting all these criteria. As a starting point we will build on our recently published RASOR imaging technique. Preliminary results indicate that the RASOR imaging technique features already several of these qualities for prostate: it has a high geometric fidelity, allows for prostate contouring, OAR identification, seed detection and bone visualization and potentially enables pCT generation. Head and neck (H&N) is a more challenging tumor sites due to air cavities and lack of fiducials. Here, we will focus on geometric fidelity and cortical bone visualization to allow position verification based upon registration with cone beam CT. We will validate our MRI-based RTP in a clinical environment by performing 2 clinical studies (prostate and H&N) where we will compare our MRI-based RTP "in the background" with the currently clinical CT-MRI based RTP in terms of dose accuracy and position verification. Additionally, we will evaluate in parallel a pCT approach provided by our industrial partner Philips Healthcare.

Nico (C.A.T.) van den Berg (born 1975) studied Applied Physics at the University of Twente. From 2002 to 2006 he performed his PhD on "Radiofrequency field in hyperthermia and MRI" at the department of Radiotherapy at the UMCU. He is an Associate Professor in the Imaging division of the UMCU. He is the (co) author of 29 peer reviewed papers. His main research themes are RF transmit design and RF safety of ultra high field body MRI (17 papers) and the development of MR imaging for oncology (12 papers). He has been a pioneer in the recent development of travelling wave MR imaging and RF multi-transmit for high field MRI. In 2009 he received a prestigious, personal VENI grant for talented researchers to develop new RF transmit concepts for high field body MR imaging. He is project leader on two ZonMW projects and heads a research group consisting of 5 PhD students and 3 postdocs. He is senior member on the imaging group of the department of Radiotherapy overlooking the development of (functional) MR imaging techniques for various cancers and fast, volumetric image tracking of organ motions during MR-Linac radiation treatment.