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Development of a Novel Multiparametric MRI Radiomic Nomogram for Preoperative Evaluation of Early Recurrence in Resectable Pancreatic Cancer.
Tang, Tian-Yu; Li, Xiang; Zhang, Qi; Guo, Cheng-Xiang; Zhang, Xiao-Zhen; Lao, Meng-Yi; Shen, Yi-Nan; Xiao, Wen-Bo; Ying, Shi-Hong; Sun, Ke; Yu, Ri-Sheng; Gao, Shun-Liang; Que, Ri-Sheng; Chen, Wei; Huang, Da-Bing; Pang, Pei-Pei; Bai, Xue-Li; Liang, Ting-Bo.
Afiliação
  • Tang TY; Department of Hepatobiliary and Pancreatic Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Li X; Zhejiang Provincial Key Laboratory of Pancreatic Disease, Hangzhou, China.
  • Zhang Q; Innovation Center for the Study of Pancreatic Diseases, Zhejiang Province, China.
  • Guo CX; Department of Hepatobiliary and Pancreatic Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Zhang XZ; Zhejiang Provincial Key Laboratory of Pancreatic Disease, Hangzhou, China.
  • Lao MY; Innovation Center for the Study of Pancreatic Diseases, Zhejiang Province, China.
  • Shen YN; Department of Hepatobiliary and Pancreatic Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Xiao WB; Zhejiang Provincial Key Laboratory of Pancreatic Disease, Hangzhou, China.
  • Ying SH; Innovation Center for the Study of Pancreatic Diseases, Zhejiang Province, China.
  • Sun K; Department of Hepatobiliary and Pancreatic Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Yu RS; Zhejiang Provincial Key Laboratory of Pancreatic Disease, Hangzhou, China.
  • Gao SL; Innovation Center for the Study of Pancreatic Diseases, Zhejiang Province, China.
  • Que RS; Department of Hepatobiliary and Pancreatic Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Chen W; Zhejiang Provincial Key Laboratory of Pancreatic Disease, Hangzhou, China.
  • Huang DB; Innovation Center for the Study of Pancreatic Diseases, Zhejiang Province, China.
  • Pang PP; Department of Hepatobiliary and Pancreatic Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Bai XL; Zhejiang Provincial Key Laboratory of Pancreatic Disease, Hangzhou, China.
  • Liang TB; Innovation Center for the Study of Pancreatic Diseases, Zhejiang Province, China.
J Magn Reson Imaging ; 52(1): 231-245, 2020 07.
Article em En | MEDLINE | ID: mdl-31867839
ABSTRACT

BACKGROUND:

In pancreatic cancer, methods to predict early recurrence (ER) and identify patients at increased risk of relapse are urgently required.

PURPOSE:

To develop a radiomic nomogram based on MR radiomics to stratify patients preoperatively and potentially improve clinical practice. STUDY TYPE Retrospective. POPULATION We enrolled 303 patients from two medical centers. Patients with a disease-free survival ≤12 months were assigned as the ER group (n = 130). Patients from the first medical center were divided into a training cohort (n = 123) and an internal validation cohort (n = 54). Patients from the second medical center were used as the external independent validation cohort (n = 126). FIELD STRENGTH/SEQUENCE 3.0T axial T1 -weighted (T1 -w), T2 -weighted (T2 -w), contrast-enhanced T1 -weighted (CET1 -w). ASSESSMENT ER was confirmed via imaging studies as MRI or CT. Risk factors, including clinical stage, CA19-9, and radiomic-related features of ER were assessed. In addition, to determine the intra- and interobserver reproducibility of radiomic features extraction, the intra- and interclass correlation coefficients (ICC) were calculated. STATISTICAL TESTS The area under the receiver-operator characteristic (ROC) curve (AUC) was used to evaluate the predictive accuracy of the radiomic signature in both the training and test groups. The results of decision curve analysis (DCA) indicated that the radiomic nomogram achieved the most net benefit.

RESULTS:

The AUC values of ER evaluation for the radiomics signature were 0.80 (training cohort), 0.81 (internal validation cohort), and 0.78 (external validation cohort). Multivariate logistic analysis identified the radiomic signature, CA19-9 level, and clinical stage as independent parameters of ER. A radiomic nomogram was then developed incorporating the CA19-9 level and clinical stage. The AUC values for ER risk evaluation using the radiomic nomogram were 0.87 (training cohort), 0.88 (internal validation cohort), and 0.85 (external validation cohort). DATA

CONCLUSION:

The radiomic nomogram can effectively evaluate ER risks in patients with resectable pancreatic cancer preoperatively, which could potentially improve treatment strategies and facilitate personalized therapy in pancreatic cancer. LEVEL OF EVIDENCE 4 Technical Efficacy Stage 4 J. Magn. Reson. Imaging 2020;52231-245.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Pancreáticas / Imageamento por Ressonância Magnética Multiparamétrica Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Male Idioma: En Revista: J Magn Reson Imaging Assunto da revista: DIAGNOSTICO POR IMAGEM Ano de publicação: 2020 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Pancreáticas / Imageamento por Ressonância Magnética Multiparamétrica Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Male Idioma: En Revista: J Magn Reson Imaging Assunto da revista: DIAGNOSTICO POR IMAGEM Ano de publicação: 2020 Tipo de documento: Article País de afiliação: China