Deep learning based MR Only Radiotherapy for head-and-neck cancer

In the Netherlands about 3000 patients are diagnosed with head-and-neck cancer
each year of which the majority is treated with (chemo)-radiotherapy. As part
of the preparation of the radiotherapy treatment, both a CT scan and a MRI scan
are acquired of the patient in treatment position. The MRI scan is acquired to
clearly depict and delineate the tumor while the CT scan is necessary to plan
the radiotherapy treatment beams. The current preparation procedure has a
couple of disadvantages. First, two patient appointments are required for the
CT and MRI scan. Second due to unavoidable slight variations in patient
position at the time of the CT and MRI, both scans need to be registered. Any
misalignment in registration is at the expense of the treatment accuracy.
Third, delineation of the organs at risk is a tedious manual process that can
takes hours per patient.

Within a European consortium funded by EIT Health we are developing a special
type of MRI sequence that can be used to create a synthetic CT scan. We
hypothesize that using this synthetic CT it will no longer be necessary to
acquire a separate CT, avoiding the problems stated above. Moreover the
consortium develops automated tools for contouring based on deep learning that
could be used to automatically delineate organs at risk, possibly saving
considerable preparation time.

Primary objective: to acquire patient data required to optimize/train a method
to generate synthetic CT scans from MRI scans and to determine the suitability
of the synthetic CT scans for radiotherapy treatment planning.

Secondary objective: To evaluate if the deep learning based autocontouring can
lead to delineations of organs at risk comparable to those delineated by an
expert radiation-oncologist.

Technical feasibility study

The burden consists of a 15 minutes longer MRI scan time than used in standard
workup: 35 minutes instead of 20 minutes scan time. During the scanning, the
patients wear the radiotherapy immobilization mask required for the clinical
scans. There are no risks associated with the intervention. The study does not
affect the treatment.