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Background: Patients with advanced gastric cancer (GC) often and can develop simultaneous or sequential duodenal and biliary obstructions resulting in reduced quality of life and significantly a reduction in the survival time. However, palliative management, insertion of biliary and duodenal metallic stents can relief these obstructions and has become a feasible and safe therapeutic strategic option. However, the operation of bimetallic stents placement is much more difficult and challenging, for instance, cannot prevent tumor progression and reemerge obstructions.Case Description: This report describes and elucidates a patient with GC who has complicated duodenal and biliary obstructions. In this case, the patient was already at an advanced stage when diagnosed, and the patient had a past medical history of cardiac and pulmonary disorders, with the poor general condition and no chance of undergoing any form of laparoscopic surgery. Furthermore, this patient developed severe symptoms of duodenal and biliary obstructions which have resulted in having nutritional disorders and liver dysfunctions post chemotherapeutic treatment regimens. In order to get rid of those obstructions, endoscopic photodynamic therapy (PDT) combined with duodenal metal stent and biliary metal stent was utilized for palliative treatment. In addition, such combined strategies can provide a longer survival time (11 vs. 7.6 months reported before) and improve the quality of life for patients with GC at an advanced stage.Conclusions: PDT combined with bimetallic stents is a safe and excellent therapeutic strategy for advanced GC which has complicated duodenal and biliary obstructions.

Background Immune checkpoint inhibitors (ICIs) represent an approved treatment for various cancers; however, only a small proportion of the population is responsive to such treatment. We aimed to develop and validate a plain CT-based tool for predicting the response to ICI treatment among cancer patients. Methods Data for patients with solid cancers treated with ICIs at two centers from October 2019 to October 2021 were randomly divided into training and validation sets. Radiomic features were extracted from pretreatment CT images of the tumor of interest. After feature selection, a radiomics signature was constructed based on the least absolute shrinkage and selection operator regression model, and the signature and clinical factors were incorporated into a radiomics nomogram. Model performance was evaluated using the training and validation sets. The Kaplan–Meier method was used to visualize associations with survival. Results Data for 122 and 30 patients were included in the training and validation sets, respectively. Both the radiomics signature (radscore) and nomogram exhibited good discrimination of response status, with areas under the curve (AUC) of 0.790 and 0.814 for the training set and 0.831 and 0.847 for the validation set, respectively. The calibration evaluation indicated goodness-of-fit for both models, while the decision curves indicated that clinical application was favorable. Both models were associated with the overall survival of patients in the validation set. Conclusions We developed a radiomics model for early prediction of the response to ICI treatment. This model may aid in identifying the patients most likely to benefit from immunotherapy.