Jie Kuang, Yanan Chen, Huikang Xie, Hua Hao, Yanlin Zhao, Cui Tang
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引用次数: 0
Abstract
Background: Primary lung adenocarcinoma with duodenal metastasis is relatively rare, and its early clinical symptoms are often insidious, making diagnosis challenging. CT, MR, PET-CT, and gastroscopy can effectively identify gastrointestinal metastatic lesions, providing reliable evidence for definitive diagnosis and treatment planning, which contributes to prolonging patient survival.
Case presentation: This report presents a rare case of duodenal metastasis from lung adenocarcinoma. The patient was diagnosed with lung adenocarcinoma (cT4N3M1c, stage IVb) one year prior. During chemotherapy, the patient gradually developed symptoms of abdominal distension and progressive jaundice. Through analysis of CT and MR imaging changes during the disease course, combined with laboratory test indicators, malignant duodenal tumor causing biliary obstruction and pancreatitis was suspected. Ultimately, endoscopic pathological biopsy confirmed duodenal metastasis from primary lung cancer. The clinical surgeon implemented a PTCD treatment plan, successfully relieving the patient's biliary obstruction.
Conclusions: Primary lung cancer patients presenting with abdominal symptoms and imaging findings suggestive of gastrointestinal tumors should be highly suspected of metastasis. Timely pathological diagnosis is essential to determine the nature and origin of the tumor, thereby facilitating the formulation of individualized treatment plans.
期刊介绍:
Cancer Imaging and Diagnosis is dedicated to the publication of results from clinical and research studies applied to cancer diagnosis and treatment. The section aims to publish studies from the entire field of cancer imaging: results from routine use of clinical imaging in both radiology and nuclear medicine, results from clinical trials, experimental molecular imaging in humans and small animals, research on new contrast agents in CT, MRI, ultrasound, publication of new technical applications and processing algorithms to improve the standardization of quantitative imaging and image guided interventions for the diagnosis and treatment of cancer.