Summary Over 13,000 patients are yearly diagnosed with lung cancer in the Netherlands. Surgery is treatment of choice, but only 20% of patients qualify for a curative resection. About 25% of the patients are diagnosed with locally advanced non-small cell lung cancer (LA-NSCLC). The standard treatment of this stage is concurrent chemoradiotherapy (CCRT) with adjuvant immunotherapy in patients without progression after CCRT. This is an intensive treatment and associated with toxicities, such as dysphagia. Despite the curative intent of CCRT for LA-NSCLC patients, overall survival (OS) is still poor. More personalized treatment is needed, in which treatment outcomes can hopefully be improved and toxicity can be more accurately predicted and reduced. The purpose of this thesis was to evaluate strategies to improve the radiotherapy for LA-NSCLC patients. Focus was on different aspects of the treatment. The specific dose prescription for LA-NSCLC patients was optimized by differentiating the dose to the primary tumor and involved mediastinal lymph nodes to improve treatment outcome and to reduce toxicities. Further, the patient selection for the treatment of oligometastatic disease was analyzed. A clear and practical decision support system was introduced in the clinical practice to optimize the workflow for image guided radiotherapy with ConeBeam-CT (CBCT). Besides, the imaging data of tumor volume regression during treatment detected on CBCT was associated with treatment outcome. Finally, the normal tissue complication probability (NTCP) model to predict the risk of acute esophagus toxicity was optimized.
|Qualification||Doctor of Philosophy|
|Award date||17 May 2021|
|Place of Publication||s.l.|
|Publication status||Published - 18 May 2021|