Laryngeal cancer is the most common cancer of the upper respiratory tract and can be diagnosed in the
early stages of the disease. Laryngeal cancer can be treated using surgery or radiotherapy. The introduction of the new MRI-LINAC (MRI-Guided Linear Accelerator) technology in Lithuania has made it possible to apply stereotactic ablative radiotherapy treatment by
monitoring tumor movement during the treatment. However, applying this technology several problems remain: the difficulty in defining the target volume of small-sized tumors, the possibility of dosimetric errors in the presence of a magnetic field due to the target interaction with structures of heterogeneous density (laryngeal cartilage, air in the airways, etc.) which may lead to dosimetric errors in the presence of a magnetic field, uncertainties in visualization and tracking of laryngeal cancer in MRI-LINAC system.
This project aims to develop an innovative stereotactic ablative magnetic resonance image-guided radiotherapy (SMART) treatment method supported by machine learning (ML)-based prognostic models that integrate patients’ radiomic and dosiomic markers, clinical parameters and results of personalized phantom dosimetry measurements, and apply it for early-stage laryngeal cancer
treatment in MRI-LINAC modality.
It is expected that the concept of the SMART treatment method will be universal and can be applied to treating other similar cancers.
Project funding:
Research Council of Lithuania, Projects carried out by researchers’ teams
Project results:
Machine learning-based prognostic radiomics and dosiomics models for clinical use.
Stereotactic ablative magnetic resonance image-guided radiotherapy (SMART) treatment method.
Performed method validation based on the results of individualized in vitro dosimetry measurements
Recommendations for early-stage laryngeal cancer treatment in MRI-LINAC modality.
Period of project implementation: 2024-09-02 - 2027-08-31
Project coordinator: Kaunas University of Technology
