Gastric sub-epithelial tumors: identification of gastrointestinal stromal tumors using CT with a practical scoring method.


Journal

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
ISSN: 1436-3305
Titre abrégé: Gastric Cancer
Pays: Japan
ID NLM: 100886238

Informations de publication

Date de publication:
07 2019
Historique:
received: 16 10 2018
accepted: 26 11 2018
pubmed: 12 12 2018
medline: 31 12 2019
entrez: 12 12 2018
Statut: ppublish

Résumé

To determine CT features that can identify gastrointestinal stromal tumors (GISTs) among gastric sub-epithelial tumors (SETs) and to explore a practical scoring method. Sixty-four patients with gastric SETs (51 GISTs and 13 non-GISTs) from hospital I were included for primary analyses, and 92 (67 GISTs and 25 non-GISTs) from hospital II constituted a validation cohort. Pre-operative CT images were reviewed for imaging features: lesion location, growth pattern, lesion margin, enhancement pattern, dynamic pattern, attenuation at each phasic images and presence of necrosis, superficial ulcer, calcification, and peri-lesion enlarged lymph node (LN). Clinical and CT features were compared between the two groups (GISTs versus non-GISTs) and a GIST-risk scoring method was developed; then, its performance for identifying GISTs was tested in the validation cohort. Seven clinical and CT features were significantly suggestive of GISTs rather than non-GISTs: older age (> 49 years), non-cardial location, irregular margin, lower attenuation on unenhanced images (≤ 43 HU), heterogeneous enhancement, necrosis, and absence of enlarged LN (p < 0.05). At validation step, the established scoring method with cut-off score dichotomized into ≥ 4 versus < 4 for identifying GISTs revealed an AUC of 0.97 with an accuracy of 92%, a sensitivity of 100% and a negative predictive value (NPV) of 100%. Gastric GISTs have special CT and clinical features that differ from non-GISTs. With a simple and practical scoring method based on the significant features, GISTs can be accurately differentiated from non-GISTs.

Identifiants

pubmed: 30535637
doi: 10.1007/s10120-018-00908-6
pii: 10.1007/s10120-018-00908-6
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

769-777

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Auteurs

Ming Liu (M)

Department of Radiotherapy, Fudan University Shanghai Cancer Center, Shanghai, China.

Liheng Liu (L)

Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China. liu.liheng@zs-hospital.sh.cn.

Erhu Jin (E)

Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.

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Classifications MeSH