Literature DB >> 19728919

[Correlation of multi-slice spiral CT features to clinicopathologic manifestations of gastrointestinal stromal tumor: a report of 49 cases].

Shao-Han Yin1, Chuan-Miao Xie, Yun-Xian Mo, Zi-Lin Huang, Yan-Chun Lu, Xue-Wen Liu, Yun Zhang, Jian-Peng Li, Lie Zheng, Pei-Hong Wu.   

Abstract

BACKGROUND AND
OBJECTIVE: Gastrointestinal stromal tumor (GIST) is one of the most common mesenchymal tumors of the digestive system. Imaging examination plays an important role in preoperative diagnosis and postoperative evaluation for it. This study was to describe the multi-slice spiral computed tomographic (MSCT) findings and pathologic features of GIST, and to analyze their correlation.
METHODS: MSCT and pathologic reports of 49 patients with 53 pathologically confirmed GIST lesions were reviewed and compared.
RESULTS: Of the 53 GIST lesions, 14 were at very low biological risk, 11 at low risk, ten at moderate risk and 18 at high risk; 36 (67.9%) were found in first visit by CT scans. On CT images, the GIST lesions with maximal diameter of > or =50 mm showed irregular shape, invasive growth, presence of cystic area and heterogeneous enhancement, and most of them were at high risk; the lesions with maximal diameter of <50 mm showed regular shape, expansive growth, and homogeneous enhancement, and most of them were at risk of moderate or below. No lymph node metastasis was found. Only three lesions showed S100-positive, which presented infiltration along the gastric wall or bowel ring on CT images.
CONCLUSIONS: CT examination is helpful in risk prediction for GIST, but it is difficult to detect small lesions (< 2 cm) by CT scans. Due to the infiltrative growth of GIST with neural differentiation (S100-positive), it is difficult to distinguish GIST from gastric cancer on CT images.

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Year:  2009        PMID: 19728919     DOI: 10.5732/cjc.008.10832

Source DB:  PubMed          Journal:  Ai Zheng


  1 in total

1.  Evaluation of risk classifications for gastrointestinal stromal tumor using multi-parameter Magnetic Resonance analysis.

Authors:  Tao Zheng; Juan Du; Linsha Yang; Yanchao Dong; Zhanqiu Wang; Defeng Liu; Shuo Wu; Qinglei Shi; Xiaohan Wang; Lanxiang Liu
Journal:  Abdom Radiol (NY)       Date:  2020-10-15
  1 in total

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