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Combination of clinical information and radiomics models for the differentiation of acute simple appendicitis and non simple appendicitis on CT images.
Zhao, Yinming; Wang, Xin; Zhang, Yaofeng; Liu, Tao; Zuo, Shuai; Sun, Lie; Zhang, Junling; Wang, Kexin; Liu, Jing.
Afiliação
  • Zhao Y; Department of Gastrointestinal Surgery, Peking University First Hospital, Beijing, China.
  • Wang X; Department of Gastrointestinal Surgery, Peking University First Hospital, Beijing, China.
  • Zhang Y; Beijing Smart Tree Medical Technology Co. Ltd., Beijing, China.
  • Liu T; Department of Gastrointestinal Surgery, Peking University First Hospital, Beijing, China.
  • Zuo S; Department of Gastrointestinal Surgery, Peking University First Hospital, Beijing, China.
  • Sun L; Department of Gastrointestinal Surgery, Peking University First Hospital, Beijing, China.
  • Zhang J; Department of Gastrointestinal Surgery, Peking University First Hospital, Beijing, China. junlingzhang1999@163.com.
  • Wang K; School of Basic Medical Sciences, Capital Medical University Beijing, Beijing, China. kexin_wang@mail.ccmu.edu.cn.
  • Liu J; Department of Radiology, Peking University First Hospital, Beijing, China. 4527322@qq.com.
Sci Rep ; 14(1): 1854, 2024 01 22.
Article em En | MEDLINE | ID: mdl-38253872
ABSTRACT
To investigate the radiomics models for the differentiation of simple and non-simple acute appendicitis. This study retrospectively included 334 appendectomy cases (76 simple and 258 non-simple cases) for acute appendicitis. These cases were divided into training (n = 106) and test cohorts (n = 228). A radiomics model was developed using the radiomic features of the appendix area on CT images as the input variables. A CT model was developed using the clinical and CT features as the input variables. A combined model was developed by combining the radiomics model and clinical information. These models were tested, and their performance was evaluated by receiver operating characteristic curves and decision curve analysis (DCA). The variables independently associated with non-simple appendicitis in the combined model were body temperature, age, percentage of neutrophils and Rad-score. The AUC of the combined model was significantly higher than that of the CT model (P = 0.041). The AUC of the radiomics model was also higher than that of the CT model but did not reach a level of statistical significance (P = 0.053). DCA showed that all three models had a higher net benefit (NB) than the default strategies, and the combined model presented the highest NB. A nomogram of the combined model was developed as the graphical representation of the final model. It is feasible to use the combined information of clinical and CT radiomics models for the differentiation of simple and non-simple acute appendicitis.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Apendicite / Apêndice Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Sci Rep Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Apendicite / Apêndice Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Sci Rep Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China
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