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Background: Esophageal squamous cell carcinoma (ESCC) is a prevalent gastrointestinal malignancy associated with significant morbidity and mortality rates. Tumor metastasis leads to a poor prognosis for patients. Intramural gastric metastasis (IGM), is an uncommon pathway of ESCC metastasis, and is more likely to occur when tumor cells show deep infiltration. In this study, we describe the diagnosis and management of two rare cases of T1-stage ESCC with IGM in clinical practice.
Case Summary: Case 1: In this patient, the submucosal tumor-like lesion was initially thought to be a gastrointestinal stromal tumor. T1-stage ESCC was then diagnosed by gastro-endoscopy during subsequent evaluation. The lesion was finally confirmed to be submucosal metastasis of ESCC following pathological analysis. The patient has been receiving treatment for over seven months, with an encouraging outcome. Case 2: In this patient, the initial diagnostic phase showed esophageal and gastric lesions which were classified as two distinct conditions: Early-stage ESCC and a gastrointestinal stromal tumor, respectively. However, postoperative pathology revealed ESCC with IGM. The patient received adjuvant chemotherapy following surgical intervention. Regrettably, the patient was lost to follow-up shortly after surgery.
Conclusion: The occurrence of IGM in T1-stage ESCC is rare. IGM should be taken into consideration when diagnosing submucosal tumor-like lesions to prevent misdiagnosis and missed diagnosis.
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http://dx.doi.org/10.4251/wjgo.v17.i8.110206 | DOI Listing |
World J Gastrointest Oncol
August 2025
Department of Gastroenterology, Tangdu Hospital, Fourth Military Medical University, Xi'an 710038, Shaanxi Province, China.
Background: Esophageal squamous cell carcinoma (ESCC) is a prevalent gastrointestinal malignancy associated with significant morbidity and mortality rates. Tumor metastasis leads to a poor prognosis for patients. Intramural gastric metastasis (IGM), is an uncommon pathway of ESCC metastasis, and is more likely to occur when tumor cells show deep infiltration.
View Article and Find Full Text PDFJ Thorac Dis
August 2024
Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, China.
Background: There is a shortage of reliable predictive models to provide valuable prognostic information for early esophageal squamous cell carcinoma (ESCC) without lymph node metastasis (LNM). We aimed to develop and validate a nomogram using the prognostic factors in T1N0 ESCC patients.
Methods: Patients with pathological T1N0 ESCC who underwent esophagectomy between 2014 and 2021 at three institutes were reviewed.
Clin Transl Med
September 2021
Department of Thoracic Surgery, Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, P.R. China.
BMC Cancer
April 2021
Department of Esophageal Surgery, Tianjin Medical University Cancer Hospital and Institute, Key Laboratory of Cancer Prevention and Therapy, National Clinical Research Center for Cancer, Tianjin, 300060, China.
Background: A nomogram was developed to predict lymph node metastasis (LNM) for patients with early-stage esophageal squamous cell carcinoma (ESCC).
Methods: We used the clinical data of ESCC patients with pathological T1 stage disease who underwent surgery from January 2011 to June 2018 to develop a nomogram model. Multivariable logistic regression was used to confirm the risk factors for variable selection.
Front Oncol
October 2020
Department of Clinical Laboratory, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.
Preoperative prediction of lymph node (LN) metastasis is accepted as a crucial independent risk factor for treatment decision-making for esophageal squamous cell carcinoma (ESCC) patients. Our study aimed to establish a non-invasive nomogram to identify LN metastasis preoperatively in ESCC patients. Construction of the nomogram involved three sequential phases with independent patient cohorts.
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