[Schwannoma of the stomach].

J Med Liban

Published: September 1969

Download full-text PDF

Source

Publication Analysis

Top Keywords

[schwannoma stomach]
4
[schwannoma
1

Similar Publications

Schwannomas commonly occur in the head and neck region but are rarely seen in the gastrointestinal tract; the stomach and small intestine are the most commonly involved sites. These tumors are usually misdiagnosed as gastrointestinal stromal tumors (GISTs) before histopathological confirmation due to radiological similarity. GI schwannomas show positivity for S100 protein and vimentin but are negative for CD 117 and CD 34, which helps in differentiating the tumor from GISTs.

View Article and Find Full Text PDF

Mesocolic schwannoma mimicking gastrointestinal stromal tumor: A case report and review of literature.

Medicine (Baltimore)

November 2024

Gastrointestinal Surgery Medical Center, Weifang People's Hospital, Shandong Second Medical University, Weifang, Shandong, China.

Rationale: Schwannomas are common peripheral nerve tumors originating from Schwann cells, primarily occurring in the head and neck, limbs, and trunk. Schwannomas occurring in the mesocolon are rare and often have no specific manifestations. Abdominal schwannomas need to be differentiated from common abdominal tumors such as gastrointestinal stromal tumors.

View Article and Find Full Text PDF

Purpose: Schwannoma is a rare mesenchymal tumor. In this study, we analyzed clinicopathologically 99 schwannomas.This retrospective study delves into the clinical, pathological, and immunohistochemical dimensions of abdominal schwannomas.

View Article and Find Full Text PDF

Background/aims:  Gastrointestinal stromal tumors are common gastric mesenchymal tumors that are potentially malignant. However, endoscopic ultrasonography is poor in diagnosing gastrointestinal stromal tumors. The study investigated the efficacy of texture features extracted from endoscopic ultrasonography images to differentiate gastrointestinal stromal tumors from gastric mesenchymal tumors.

View Article and Find Full Text PDF
Article Synopsis
  • * Researchers analyzed data from 464 patients and developed classification models using both clinical and endoscopic factors along with digital image analysis.
  • * Incorporating additional factors improved the performance of AI models, with notable increases in AUC values, especially for random forest and K-nearest neighbor models, indicating more accurate diagnoses.
View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!