Introduction: Head and neck cancer (HNC) is a common and diverse group of tumors located in the region from the nasopharynx down to the upper part of the esophagus. Radiotherapy plays a crucial role in HNC treatment. In this thesis the particular focus is on external photon beam radiotherapy. The research is conducted in collaboration with the radiotherapy department of the Leiden University Medical Center (LUMC).
Theoretical background: The quality of a radiation treatment plan significantly affects patient outcomes in radiotherapy. Excessive radiation to organs at risk (OARs) can lead to complications, while insufficient dose to the tumor may increase the risk of recurrence. Automating the treatment planning process has gained attention in recent years, aiming to improve plan consistency, quality, and planning time. This study focuses on the optimization of treatment planning using RayStation’s deep learning autoplanning (DLAP) for patients with HNC.
Method: The study consists of three patient cohorts. The first and largest cohort includes 43 oropharynx patients. The second cohort includes eleven hypopharynx patients and eight larynx patients. The third cohort consists of nine unilateral oropharynx patients. Dosimetric analysis and normal tissue complication probability (NTCP) analysis are performed for both the clinical and DLAP plans in all cohorts. Dosimetric analysis uses parameters from dose volume histograms (DVH), while the NTCP analysis follows the Dutch National Indication Protocol for Proton Therapy for HNC.
Results: An initial sub-study determines the optimal tuning for the DLAP model, which is not only used in this study but also chosen for clinical implementation at the LUMC. In the following comparison study, all patient cohorts demonstrate higher Planning Target Volume (PTV) coverage in the DLAP compared to the clinical plans. The OAR dosimetric parameters show varying results, with DLAP generally demonstrating similar or better sparing of the OARs in oropharynx, hypopharynx, and larynx tumors. However, DLAP show a significantly higher dose in the brain stem core for larynx patients. Furthermore, an increased dose is observed in the mandible across all patient cohorts. Unilateral oropharynx patients treated with DLAP show a significant increase in dose to several OARs, particularly the contra-lateral salivary glands and swallowing muscles. The NTCP analysis does not reveal notable improvements or worsening across all patient cohorts.
Conclusion: DLAP demonstrates promising results for oropharynx patients, raising the question if further improvements in PTV coverage to achieve lower doses in the OARs are necessary. Although the patient cohorts for hypopharynx and larynx are small, the study’s findings indicate the potential for generating adequate treatment plans in these HNC regions. Furthermore, the results also highlight the need for further investigation in unilateral oropharynx cases, as DLAP did not sufficiently spare the contra-lateral side. The divergence in treatment technique suggests waiting for a specifically trained and designed DLAP for unilateral oropharynx patients.