Magnetic resonance imaging (MRI) with functional features of diffusion weighted imaging (DWI) are advancing imaging technologies that have potential to overcome limitations of conventional staging methods, radiation treatment planning and the assessment of tumor response in esophageal or esophagogastric cancer. This study aimed to explore the value of MRI for the prediction of tumor response to chemoradiotherapy and accurate target volume delineation as compared to CT simulation for patients with unresectable or potentially resectable esophageal or esophagogastric cancer undergoing chemoradiotherapy. The average CT texture features are also extracted before and during treatment to establish a model to predict the prognosis or side effects (e.g. radiation pneumonitis or esophagitis) of patients.
Histologically confirmed squamous cell carcinoma, adenocarcinoma of the esophageal or esophagogastric junction
Unresectable or potentially resectable tumor (cT3-4N0-1M0-M1a, according to AJCC 6th) based on standard primary staging by EUS and CT
Age>18 years
No distant metastasis other than supraclavicular lymph nodes
Contraindication for MRI scanning
Patients with other cancer history except cervical carcinoma in situ and non-malignant melanoma skin cancer
Pregnant or lactating females
Contraindication for radiotherapy or chemotherapy
Single group
MRI and CT
DeviceRatiotherapy
RadiationPaclitaxel, platinum-based drug
DrugTumor response based on MRI and CT simulation
Radiotherapy target volume assessment with pre- and post-chemoradiotherapy based on MRI and CT simulation
Evaluation of tumor heterogeneity with IBEX software
Using the average CT images for texture extraction. Histogram, gradient, cooccurrence, gray-tone difference, and filtration-based techniques are used for texture feature extraction. Models incorporating texture features are established to compare to models incorporating clinical prognostic factors alone.
Overall survival
Progress free survival
Reduction in acute and late side effects based on modified RT treatment volumes with pre- and post-chemoradiotherapy based on MRI and CT simulation
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