Nowadays pancreatic cancer is one of the deadliest oncological pathologies. The only effective curative tool is the surgery. Before the intervention, an endoscopic ultrasound is performed on the patient to carry out the biopsy of the main tumor. In this study, the echoendoscopie will be extended to lymph node staging away from the surgical field in order to implement a simple classification of lymph nodes, based on non-invasive ultrasound criteria. This would facilitate the location and qualification of peripancreatic lymph nodes and distant from the tumor, and therefore the staging of the tumor.
Nowadays pancreatic cancer is one of the deadliest oncological pathologies today. Even after curative surgery, considered the only effective curative tool, 5-years survival does not exceed 5%. Before surgery, an endoscopic ultrasound is performed on the patient to carry out the biopsy of the main tumor. However, the evaluation being devoted to the pancreas, this study wishes to extend echoendoscopie to lymph node staging away from the surgical field. The proposed study is based on the hypothesis that the implementation of a simple classification of lymph nodes, based on non-invasive ultrasound criteria, would facilitate the location and qualification of peripancreatic lymph nodes and distant from the tumor, and therefore the staging of the tumor.
At the same time, the video data obtained will be collected in a computer database in order to create an artificial intelligence lesion detection and qualification tool.
This study plans to recruit 45 adult patients, male or female, with a solid or cystic pancreatic tumor and for whom a surgical resection (first line and after neoadjuvant treatment) is planned. The main objective is to estimate the sensitivity and specificity of a simple classification "benign / malignant" of the nodes, established by the endoscopist using endoscopic ultrasound criteria's, compared to the gold standard (anatomopathology).
Condition | Pancreatic Cancer |
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Treatment | Echoendoscopy |
Clinical Study Identifier | NCT04899739 |
Sponsor | IHU Strasbourg |
Last Modified on | 20 April 2022 |
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