Your browser doesn't support javascript.
loading
Virtual biopsy using CT radiomics for evaluation of disagreement in pathology between endoscopic biopsy and postoperative specimens in patients with gastric cancer: a dual-energy CT generalizability study.
Liu, Yiyang; Zhao, Shuai; Wu, Zixin; Liang, Hejun; Chen, Xingzhi; Huang, Chencui; Lu, Hao; Yuan, Mengchen; Xue, Xiaonan; Luo, Chenglong; Liu, Chenchen; Gao, Jianbo.
Afiliación
  • Liu Y; Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
  • Zhao S; Henan Key Laboratory of Imaging Diagnosis and Treatment for Digestive System Tumor, Zhengzhou, 450052, China.
  • Wu Z; Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
  • Liang H; Henan Key Laboratory of Imaging Diagnosis and Treatment for Digestive System Tumor, Zhengzhou, 450052, China.
  • Chen X; Department of Urology Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
  • Huang C; Department of Gastroenterology, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
  • Lu H; Department of Research Collaboration, R&D Center, Beijing Deepwise and League of PHD Technology Co., Ltd, Beijing, 100080, China.
  • Yuan M; Department of Research Collaboration, R&D Center, Beijing Deepwise and League of PHD Technology Co., Ltd, Beijing, 100080, China.
  • Xue X; Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
  • Luo C; Henan Key Laboratory of Imaging Diagnosis and Treatment for Digestive System Tumor, Zhengzhou, 450052, China.
  • Liu C; Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
  • Gao J; Henan Key Laboratory of Imaging Diagnosis and Treatment for Digestive System Tumor, Zhengzhou, 450052, China.
Insights Imaging ; 14(1): 118, 2023 Jul 05.
Article en En | MEDLINE | ID: mdl-37405591
ABSTRACT

PURPOSE:

To develop a noninvasive radiomics-based nomogram for identification of disagreement in pathology between endoscopic biopsy and postoperative specimens in gastric cancer (GC). MATERIALS AND

METHODS:

This observational study recruited 181 GC patients who underwent pre-treatment computed tomography (CT) and divided them into a training set (n = 112, single-energy CT, SECT), a test set (n = 29, single-energy CT, SECT) and a validation cohort (n = 40, dual-energy CT, DECT). Radiomics signatures (RS) based on five machine learning algorithms were constructed from the venous-phase CT images. AUC and DeLong test were used to evaluate and compare the performance of the RS. We assessed the dual-energy generalization ability of the best RS. An individualized nomogram combined the best RS and clinical variables was developed, and its discrimination, calibration, and clinical usefulness were determined.

RESULTS:

RS obtained with support vector machine (SVM) showed promising predictive capability with AUC of 0.91 and 0.83 in the training and test sets, respectively. The AUC of the best RS in the DECT validation cohort (AUC, 0.71) was significantly lower than that of the training set (Delong test, p = 0.035). The clinical-radiomic nomogram accurately predicted pathologic disagreement in the training and test sets, fitting well in the calibration curves. Decision curve analysis confirmed the clinical usefulness of the nomogram.

CONCLUSION:

CT-based radiomics nomogram showed potential as a clinical aid for predicting pathologic disagreement status between biopsy samples and resected specimens in GC. When practicability and stability are considered, the SECT-based radiomics model is not recommended for DECT generalization. CRITICAL RELEVANCE STATEMENT Radiomics can identify disagreement in pathology between endoscopic biopsy and postoperative specimen.
Palabras clave

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Observational_studies / Prognostic_studies Idioma: En Revista: Insights Imaging Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Observational_studies / Prognostic_studies Idioma: En Revista: Insights Imaging Año: 2023 Tipo del documento: Article País de afiliación: China