Liang Liang1, Rongkui Luo2, Ying Ding1, Kai Liu1, Licheng Shen2, Haiying Zeng2, Yingqian Ge3, Mengsu Zeng4. 1. Department of Radiology, Zhongshan Hospital, Fudan University, and Shanghai Institute of Medical Imaging, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China. 2. Department of Pathology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China. 3. Siemens Healthineers, No. 278 Zhou Zhu Road, Pudong New District, Shanghai, 201318, China. 4. Department of Radiology, Zhongshan Hospital, Fudan University, and Shanghai Institute of Medical Imaging, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China. zengmengsu_zs@163.com.
Abstract
OBJECTIVE: To investigate the relationship between imaging findings and S100A4 overexpression in pancreatic ductal adenocarcinoma (PDAC) and to determine imaging biomarkers of S100A4 overexpression from whole-tumor evaluation with MRI and texture analysis. METHODS: A total of 60 patients with pathologically confirmed PDAC were included in the study. All patients underwent preoperative abdominal contrast-enhanced MRI examination with Magnetom Aera (Siemens Healthcare, Germany, 1.5 T) at our institute. Whole-tumor evaluation including texture analysis was performed. Sections of specimens were reviewed, and the S100A4 expression status was quantitatively evaluated. Univariate and multivariate logistic regression analyses were conducted to find imaging biomarkers that could predict S100A4 overexpression. RESULTS: Twenty-four tumors (40.0%) had negative results for S100A4 overexpression, and 36 tumors (60.0%) exhibited overexpression. After univariate and multivariate analysis, distal pancreatic duct dilatation, T1WI_10th percentile and the enhancement rate difference between delayed phase (DP) and portal venous phase (PVP) were identified to predict S100A4 overexpression in PDAC independently (p = 0.009, 0.012 and 0.044), with odds ratios (ORs) of 0.102, 0.139 and 4.645, respectively. The area under the ROC curve (AUC) values were 0.715, 0.707 and 0.691. The AUC value of the proposed model was 0.877 with a sensitivity of 80.6% and specificity of 75.0%. CONCLUSION: A model including distal pancreatic duct dilatation, T1WI_10th percentile and the enhancement rate difference between the DP and PVP could predict S100A4 overexpression in PDAC as imaging biomarkers.
OBJECTIVE: To investigate the relationship between imaging findings and S100A4 overexpression in pancreatic ductal adenocarcinoma (PDAC) and to determine imaging biomarkers of S100A4 overexpression from whole-tumor evaluation with MRI and texture analysis. METHODS: A total of 60 patients with pathologically confirmed PDAC were included in the study. All patients underwent preoperative abdominal contrast-enhanced MRI examination with Magnetom Aera (Siemens Healthcare, Germany, 1.5 T) at our institute. Whole-tumor evaluation including texture analysis was performed. Sections of specimens were reviewed, and the S100A4 expression status was quantitatively evaluated. Univariate and multivariate logistic regression analyses were conducted to find imaging biomarkers that could predict S100A4 overexpression. RESULTS: Twenty-four tumors (40.0%) had negative results for S100A4 overexpression, and 36 tumors (60.0%) exhibited overexpression. After univariate and multivariate analysis, distal pancreatic duct dilatation, T1WI_10th percentile and the enhancement rate difference between delayed phase (DP) and portal venous phase (PVP) were identified to predict S100A4 overexpression in PDAC independently (p = 0.009, 0.012 and 0.044), with odds ratios (ORs) of 0.102, 0.139 and 4.645, respectively. The area under the ROC curve (AUC) values were 0.715, 0.707 and 0.691. The AUC value of the proposed model was 0.877 with a sensitivity of 80.6% and specificity of 75.0%. CONCLUSION: A model including distal pancreatic duct dilatation, T1WI_10th percentile and the enhancement rate difference between the DP and PVP could predict S100A4 overexpression in PDAC as imaging biomarkers.
Authors: Helmut Oettle; Stefan Post; Peter Neuhaus; Klaus Gellert; Jan Langrehr; Karsten Ridwelski; Harald Schramm; Joerg Fahlke; Carl Zuelke; Christof Burkart; Klaus Gutberlet; Erika Kettner; Harald Schmalenberg; Karin Weigang-Koehler; Wolf-Otto Bechstein; Marco Niedergethmann; Ingo Schmidt-Wolf; Lars Roll; Bernd Doerken; Hanno Riess Journal: JAMA Date: 2007-01-17 Impact factor: 56.272
Authors: Lola Rahib; Benjamin D Smith; Rhonda Aizenberg; Allison B Rosenzweig; Julie M Fleshman; Lynn M Matrisian Journal: Cancer Res Date: 2014-06-01 Impact factor: 12.701
Authors: Christophe Rosty; Takashi Ueki; Pedram Argani; Marnix Jansen; Charles J Yeo; John L Cameron; Ralph H Hruban; Michael Goggins Journal: Am J Pathol Date: 2002-01 Impact factor: 4.307
Authors: Susan Tsai; Beth A Erickson; Kulwinder Dua; Paul S Ritch; Parag Tolat; Douglas B Evans Journal: J Oncol Pract Date: 2016-09 Impact factor: 3.840