Literature DB >> 28583627

Resectable pancreatic adenocarcinoma: Role of CT quantitative imaging biomarkers for predicting pathology and patient outcomes.

Christophe Cassinotto1, Jaron Chong2, George Zogopoulos3, Caroline Reinhold4, Laurence Chiche5, Jean-Pierre Lafourcade6, Adeline Cuggia7, Eric Terrebonne8, Anthony Dohan9, Benoît Gallix10.   

Abstract

BACKGROUNDS: Patients with a pancreatic cancer amenable to surgery still have a poor prognosis and high risk of post-operative recurrence. We aimed to assess the value of quantitative imaging biomarkers using computed-tomography (CT) texture analysis to evaluate the pathologic tumor aggressiveness and predict disease-free survival (DFS) in patients with resectable pancreatic adenocarcinoma.
METHODS: We retrospectively performed attenuation measurements and texture analysis on the portal-venous phase of the pre-operative CT scan of 99 patients that underwent resection of a pancreatic ductal adenocarcinoma in two university hospitals. Tumor attenuation parameters included: mean attenuation value of the whole tumor (WHOLE-AV), and of the most hypoattenuating area within the tumor (CENTRAL-AV). Tumor heterogeneity parameters included: standard deviation, entropy, skewness, and kurtosis.
RESULTS: Tumor attenuation parameters showed significant association with the tumor differentiation grade (CENTRAL-AV, Odds ratio (OR) 0.968, 95% confidence interval (CI) 0.94-0.998) and lymph node invasion (WHOLE-AV, OR 0.886, CI 0.823-0.955). Variables associated with early-recurrence were: lymph node ratio (R2=0.15), kurtosis (R2=0.08), and CENTRAL-AV (R2=0.04). Lymph node ratio (Hazard ratio (HR) 1.02), and CENTRAL-AV (HR 0.98) were independently associated with shorter DFS. Patients with CENTRAL-AV<62 Hounsfield units had a shorter 1-year DFS (35% versus 68%, p=0.004).
CONCLUSION: Tumors that are more hypoattenuating on the portal-venous phase on CT scan are potentially more aggressive with higher tumor grade, greater lymph node invasion, and shorter DFS.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  CT attenuation value; Cancer staging; Pancreatic adenocarcinoma prognosis; Quantitative imaging biomarkers; Texture analysis

Mesh:

Substances:

Year:  2017        PMID: 28583627     DOI: 10.1016/j.ejrad.2017.02.033

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  37 in total

Review 1.  White paper on pancreatic ductal adenocarcinoma from society of abdominal radiology's disease-focused panel for pancreatic ductal adenocarcinoma: Part II, update on imaging techniques and screening of pancreatic cancer in high-risk individuals.

Authors:  Naveen M Kulkarni; Lorenzo Mannelli; Marc Zins; Priya R Bhosale; Hina Arif-Tiwari; Olga R Brook; Elizabeth M Hecht; Fay Kastrinos; Zhen Jane Wang; Erik V Soloff; Parag P Tolat; Guillermo Sangster; Jason Fleming; Eric P Tamm; Avinash R Kambadakone
Journal:  Abdom Radiol (NY)       Date:  2020-03

2.  Can physician gestalt predict survival in patients with resectable pancreatic adenocarcinoma?

Authors:  Linda M Pak; Mithat Gonen; Kenneth Seier; Vinod P Balachandran; Michael I D'Angelica; William R Jarnagin; T Peter Kingham; Peter J Allen; Richard K G Do; Amber L Simpson
Journal:  Abdom Radiol (NY)       Date:  2018-08

Review 3.  CT and MRI of pancreatic tumors: an update in the era of radiomics.

Authors:  Marion Bartoli; Maxime Barat; Anthony Dohan; Sébastien Gaujoux; Romain Coriat; Christine Hoeffel; Christophe Cassinotto; Guillaume Chassagnon; Philippe Soyer
Journal:  Jpn J Radiol       Date:  2020-10-21       Impact factor: 2.374

Review 4.  The Role of Endoscopic Ultrasound in Pancreatic Cancer Staging in the Era of Neoadjuvant Therapy and Personalised Medicine.

Authors:  Miguel Bispo; Susana Marques; Ricardo Rio-Tinto; Paulo Fidalgo; Jacques Devière
Journal:  GE Port J Gastroenterol       Date:  2020-09-07

Review 5.  Pancreas image mining: a systematic review of radiomics.

Authors:  Bassam M Abunahel; Beau Pontre; Haribalan Kumar; Maxim S Petrov
Journal:  Eur Radiol       Date:  2020-11-05       Impact factor: 5.315

6.  Hypovascular pancreas head adenocarcinoma: CT texture analysis for assessment of resection margin status and high-risk features.

Authors:  Ameya Kulkarni; Ivan Carrion-Martinez; Nan N Jiang; Srikanth Puttagunta; Leyo Ruo; Brandon M Meyers; Tariq Aziz; Christian B van der Pol
Journal:  Eur Radiol       Date:  2020-01-17       Impact factor: 5.315

7.  CT prediction of resectability and prognosis in patients with pancreatic ductal adenocarcinoma after neoadjuvant treatment using image findings and texture analysis.

Authors:  Bo Ram Kim; Jung Hoon Kim; Su Joa Ahn; Ijin Joo; Seo-Youn Choi; Sang Joon Park; Joon Koo Han
Journal:  Eur Radiol       Date:  2018-06-21       Impact factor: 5.315

Review 8.  Radiomics in stratification of pancreatic cystic lesions: Machine learning in action.

Authors:  Vipin Dalal; Joseph Carmicheal; Amaninder Dhaliwal; Maneesh Jain; Sukhwinder Kaur; Surinder K Batra
Journal:  Cancer Lett       Date:  2019-10-17       Impact factor: 8.679

9.  Development and multicenter validation of a CT-based radiomics signature for discriminating histological grades of pancreatic ductal adenocarcinoma.

Authors:  Na Chang; Lingling Cui; Yahong Luo; Zhihui Chang; Bing Yu; Zhaoyu Liu
Journal:  Quant Imaging Med Surg       Date:  2020-03

10.  Preoperative CT predictors of survival in patients with pancreatic ductal adenocarcinoma undergoing curative intent surgery.

Authors:  Shannan M Dickinson; Caitlin A McIntyre; Juliana B Schilsky; Kate A Harrington; Scott R Gerst; Jessica R Flynn; Mithat Gonen; Marinela Capanu; Winston Wong; Sharon Lawrence; Peter J Allen; Eileen M O'Reilly; William R Jarnagin; Michael I D'Angelica; Vinod P Balachandran; Jeffrey A Drebin; T Peter Kingham; Amber L Simpson; Richard K Do
Journal:  Abdom Radiol (NY)       Date:  2020-09-28
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