To explore the value of histogram analysis of baseline CT portal images before treatment in predicting the response of patients with colorectal liver metastases (CRLMs) to neoadjuvant chemotherapy.
Methods:
Thirty-four patients (a total of 1
32 lesions) diagnosed with CRLM were retrospectively enrolled and underwent contrast-enhanced CT before and after neoadjuvant chemotherapy (FOLFOX
FOLFIRI or CapeOX ). All patients underwent pre-treatment CT baseline scan withinfour weeks for primary tumor assessment and a second CT scan in 2 to 3 months
for response evaluation. Histogram of CT portal images of patients with CRLM was analyzed and response was mainly assessed using Response Evaluation Criteria in Solid Tumors (RECIST) Version 1.1. The texture parameters of the metastatic tumor were analyzed statistically to find the differences in baseline CT histogram parameters between responding group and non-responding group before and after treatment. The receiver operating characteristic (ROC) curves were depicted to characterize each parameter value in evaluating the treatment outcomes. The optimal cutoff value (obtained according to the maximal Youden index = sensitivity + specificity-1)
the corresponding sensitivity
specificity
positive predictive value (PPV)
negative predictive value (NPV) and accuracy were calculated. Regions of interests (ROIs) were manually drawn on the largest cross-sectional area of the primary lesions by two radiologists in consensus.
Results:
Twenty-one responding and 13 non-responding patients were evaluated. The values of mean
variance
skewness and percentile (10th
50th
90th
99th) in responding group were much lower than those in non-responding group (
P
0.05). The kurtosis and 1st percentile values between the two groups had no significant difference (
P
=0.769
P
=0.06
respectively). The optimal cutoff value for the accurate identification of responding patients was 167 for 90th percentile (74.42% sensitivity
95.65% specificity
96.97% PPV
66.67% NPV
81.82% accuracy
and 0.854 area under curve
respectively).
Conclusion:
CT histogram analysis of baseline CT portal images before treatment can help to predict the response of patients with CRLM after neoadjuva
The value of diffusion-weighted imaging-based texture analysis in glioma grading
Prediction of VEGF expression in extrahepatic cholangiocarcinoma based on MRI texture analysis
The value of CT texture analysis in preoperative evaluation of colon cancer
3.0T WBDWIBS with histogram parameters in prediction therapy response of bone metastatic breast cancer: the initial experience
Baseline texture features extracted from dynamic contrast-enhanced magnetic resonance imaging for predicting the pathological response to chemoradiotherapy in rectal cancer
Related Author
ZHANG Hongying
CHEN Hongri
LI Qingrun
WU Liuyang
SHI Huixian
HAN Lei
YANG Chunmei
HUANG Xinqiao
Related Institution
Clinical Medical College, Yangzhou University
Department of Imaging, Northern Jiangsu People&rsquo
Department of General Surgery, Xi&rsquo
Department of Radiology, West China Hospital, Sichuan University
Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of&nbsp