CORE
🇺🇦
make metadata, not war
Services
Services overview
Explore all CORE services
Access to raw data
API
Dataset
FastSync
Content discovery
Recommender
Discovery
OAI identifiers
OAI Resolver
Managing content
Dashboard
Bespoke contracts
Consultancy services
Support us
Support us
Membership
Sponsorship
Community governance
Advisory Board
Board of supporters
Research network
About
About us
Our mission
Team
Blog
FAQs
Contact us
research
DCE-MRI perfusion and permeability parameters as predictors of tumor response to CCRT in patients with locally advanced NSCLC
Authors
A Fieselmann
A Mayer
+41 more
A Uneri
AJ de Langen
AR Padhani
AW Anderson
C Ellingsen
C Halle
C Yang
CA Ridge
CR Justus
D Rueckert
EA Eisenhauer
FG Zöllner
GJ Parker
H Cho
H Mamata
H Yabuuchi
HJ Aerts
J Chen
J Gu
JC Cheng
JH Kim
JH Naish
JP O’Connor
JP O’Connor
K Kudo
MA Zahra
MA Zahra
MM Coselmon
O Thews
P McCloskey
PL Choyke
PS Tofts
RJ Kelly
RL Jensen
SJ Ahn
SP Li
W Huang
W van Elmpt
X Li
Y Ohno
YC Chang
Publication date
20 October 2016
Publisher
'Springer Science and Business Media LLC'
Doi
Cite
View
on
PubMed
Abstract
In this prospective study, 36 patients with stage III non-small cell lung cancers (NSCLC), who underwent dynamic contrast-enhanced MRI (DCE-MRI) before concurrent chemo-radiotherapy (CCRT) were enrolled. Pharmacokinetic analysis was carried out after non-rigid motion registration. The perfusion parameters including Blood Flow (BF), Blood Volume (BV), Mean Transit Time (MTT) and permeability parameters including endothelial transfer constant (Ktrans), reflux rate (Kep), fractional extravascular extracellular space volume (Ve), fractional plasma volume (Vp) were calculated, and their relationship with tumor regression was evaluated. The value of these parameters on predicting responders were calculated by receiver operating characteristic (ROC) curve. Multivariate logistic regression analysis was conducted to find the independent variables. Tumor regression rate is negatively correlated with V e and its standard variation V e-SD and positively correlated with K trans and Kep. Significant differences between responders and non-responders existed in Ktrans, Kep, Ve, Ve-SD, MTT, BV-SD and MTT-SD (P < 0.05). ROC indicated that Ve < 0.24 gave the largest area under curve of 0.865 to predict responders. Multivariate logistic regression analysis also showed Ve was a significant predictor. Baseline perfusion and permeability parameters calculated from DCE-MRI were seen to be a viable tool for predicting the early treatment response after CCRT of NSCLC. © 2016 The Author(s)
Similar works
Full text
Open in the Core reader
Download PDF
Available Versions
University of Lincoln Institutional Repository
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:eprints.lincoln.ac.uk:2491...
Last time updated on 17/02/2017
Crossref
See this paper in CORE
Go to the repository landing page
Download from data provider
info:doi/10.1038%2Fsrep35569
Last time updated on 01/04/2019