Towards individualized treatment for esophageal cancer

Abstract

Despite recent improvements in staging, treatment, and perioperative care, esophageal cancer remains a devastating disease with a 5-year overall survival rate of only 15-25%. As prognosis is often poor, multimodality (rather than single modality) treatment approaches are frequently applied to increase the chances of cure. For patients the multitude of burdening treatment modalities are hard to undergo and exhibit substantial risks of serious side effects without knowing whether all components (e.g. chemotherapy, radiotherapy, surgery) contribute to the desired outcome on an individual basis. The studies presented in this thesis aimed to open a window to move towards individualized care for patients with esophageal cancer enabling selection of only those treatments that are best for the individual patient and omission of components that contribute little to (or even deteriorate) the well-being of the patient. In order to enable such tailor-made treatment for the individual patient with esophageal cancer, improvements in the diagnostic work-up, multimodality treatment strategies, treatment response assessment, and the risk prediction, prevention, and management of postoperative complications are indicated. The research projects presented in this thesis contribute to the realization of these improvements through the use of advanced imaging techniques and prediction models for the estimation of individual treatment efficacies and risks. Two exciting developments described in this thesis have shown promising results for allowing individualized treatment for esophageal cancer in the nearby future. First, it was indicated that in the coming years clinicians will likely become able to accurately estimate patients’ individual probability of a certain treatment efficacy after chemoradiotherapy based on MRI-based quantitative imaging parameters. Such an estimation would tremendously help clinicians and patients with informed and shared treatment decision-making. In particular the preoperative probability of a pathologic complete response is of interest for the patient, as this parameter reflects the need for additional surgical treatment. Vice versa, early identification of a high probability of non-response may be reason to modify or stop (toxic) chemoradiotherapy. Second, in this thesis the first steps were taken to develop MRI-guided radiotherapy for esophageal cancer using the MR-linac, which is a treatment modality that is currently transforming the field of radiotherapy. The MR-linac enables physicians to visualize and adapt radiotherapy in real-time during treatment based on detailed MR images. As such, the MR-linac yields unprecedented levels of precision and accuracy for each individual patient resulting in improved treatment efficacy and reduced toxicity. In addition, it implies that in the nearby future standard (rather conservative) total radiation doses –already leading to a complete disappearance of esophageal cancer in approximately 30% of cases– may be safely escalated using the MR-linac. Meanwhile, treatment response could be continuously monitored during treatment using the MRI component. These features are expected to result in a higher proportion of local cure (and good tumor responses) for esophageal cancer with fewer side effects. If so, a more restrained policy towards surgery may be practiced in a significant proportion of patients, while current non-surgical patients (due to advanced local tumor characteristics) may become new surgical candidates.