Multi-Slice CT Features Predict Pathological Risk Classification in Gastric Stromal Tumors Larger Than 2 cm: A Retrospective Study.

Wang, Sikai; Dai, Ping; Si, Guangyan; Zeng, Mengsu; Wang, Mingliang

Wang, Sikai; Dai, Ping; Si, Guangyan; Zeng, Mengsu; Wang, Mingliang.

Afiliação

Wang S; Department of Radiology, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, No. 182 Chunhui Road, Longmatan District, Luzhou 646000, China.
Dai P; Department of Radiology, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, No. 182 Chunhui Road, Longmatan District, Luzhou 646000, China.
Si G; Department of Radiology, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, No. 182 Chunhui Road, Longmatan District, Luzhou 646000, China.
Zeng M; Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai 200032, China.
Wang M; Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai 200032, China.

Diagnostics (Basel) ; 13(20)2023 Oct 12.

Article em En | MEDLINE | ID: mdl-37892014

Palavras-chave

Armed Forces Institute of Pathology; X-ray computed; gastric stromal tumors; nomogram model; risk classification

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Diagnostics (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

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