PMID- 31681593
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20200930
IS  - 2234-943X (Print)
IS  - 2234-943X (Electronic)
IS  - 2234-943X (Linking)
VI  - 9
DP  - 2019
TI  - Prognostic Value of Texture Analysis Based on Pretreatment DWI-Weighted MRI for 
      Esophageal Squamous Cell Carcinoma Patients Treated With Concurrent 
      Chemo-Radiotherapy.
PG  - 1057
LID - 10.3389/fonc.2019.01057 [doi]
LID - 1057
AB  - Purpose: The purpose of the research was to assess the prognostic value of 
      three-dimensional (3D) texture features based on diffusion-weighted magnetic 
      resonance imaging (DWI) for esophageal squamous cell carcinoma (ESCC) patients 
      undergoing concurrent chemo-radiotherapy (CRT). Methods: We prospectively 
      enrolled 82 patients with ESCC into a cohort study. Two DWI sequences (b = 0 and 
      b = 600 s/mm(2)) were acquired along with axial T2WI and T1WI before CRT. Two 
      groups of features were examined: (1) clinical and demographic features (e.g., 
      TNM stage, age and sex) and (2) changes in spatial texture characteristics of the 
      apparent diffusion coefficient (ADC), which characterizes gray intensity changes 
      in tumor areas, spatial pattern and distribution, and related changes caused by 
      CRT. Reproducible feature sets without redundancy were statistically filtered and 
      validated. The prognostic values associated with overall survival (OS) for each 
      parameter were studied using Kaplan-Meier and Cox regression models for 
      univariate and multivariate analyses, respectively. Results: Both univariate and 
      multivariate Cox model analyses showed that the energy of intensity histogram 
      texture (IHIST_energy), radiation dose, mean of the contrast in distance 1 of 26 
      directions (m_contrast_1), extreme difference of the homogeneity in distance 2 of 
      26 directions (Diff_homogeneity_2), mean of the inverse variance in distance 2 of 
      26 directions (m_lnversevariance_2), high-intensity small zone emphasis (HISE), 
      and low-intensity large zone emphasis (LILE) were significantly associated with 
      survival. The results showed that 6 texture parameters extracted from the ADC 
      images before treatment could distinguish among high-, medium-, and low-risk 
      groups (log-rank chi(2) = 9.7; P = 0.00773). The biased C-index value was 0.715 
      (95% CI: 0.708 to 0.732) based on bootstrapping validation. Conclusions: The ADC 
      3D texture feature can be used as a useful biomarker to predict the survival of 
      ESCC patients undergoing CRT. Combining ADC 3D texture features with conventional 
      prognostic factors can generate reliable survival prediction models.
CI  - Copyright (c) 2019 Li, Han, Wang, Zhu, Yin and Li.
FAU - Li, Zhenjiang
AU  - Li Z
AD  - Shandong Cancer Hospital and Institute, Shandong First Medical University and 
      Shandong Academy of Medical Sciences, Shandong Cancer Hospital, Jinan, China.
FAU - Han, Chun
AU  - Han C
AD  - Fourth Hospital of Hebei Medical University, Shijiazhuang, China.
FAU - Wang, Lan
AU  - Wang L
AD  - Fourth Hospital of Hebei Medical University, Shijiazhuang, China.
FAU - Zhu, Jian
AU  - Zhu J
AD  - Shandong Cancer Hospital and Institute, Shandong First Medical University and 
      Shandong Academy of Medical Sciences, Shandong Cancer Hospital, Jinan, China.
FAU - Yin, Yong
AU  - Yin Y
AD  - Shandong Cancer Hospital and Institute, Shandong First Medical University and 
      Shandong Academy of Medical Sciences, Shandong Cancer Hospital, Jinan, China.
FAU - Li, Baosheng
AU  - Li B
AD  - Shandong Cancer Hospital and Institute, Shandong First Medical University and 
      Shandong Academy of Medical Sciences, Shandong Cancer Hospital, Jinan, China.
LA  - eng
PT  - Journal Article
DEP - 20191017
PL  - Switzerland
TA  - Front Oncol
JT  - Frontiers in oncology
JID - 101568867
PMC - PMC6811607
OTO - NOTNLM
OT  - chemo-radiotherapy
OT  - diffusion-weighted magnetic resonance imaging
OT  - esophageal squamous cell cancer
OT  - magnetic resonance imaging
OT  - texture analysis
EDAT- 2019/11/05 06:00
MHDA- 2019/11/05 06:01
PMCR- 2019/01/01
CRDT- 2019/11/05 06:00
PHST- 2019/02/25 00:00 [received]
PHST- 2019/09/27 00:00 [accepted]
PHST- 2019/11/05 06:00 [entrez]
PHST- 2019/11/05 06:00 [pubmed]
PHST- 2019/11/05 06:01 [medline]
PHST- 2019/01/01 00:00 [pmc-release]
AID - 10.3389/fonc.2019.01057 [doi]
PST - epublish
SO  - Front Oncol. 2019 Oct 17;9:1057. doi: 10.3389/fonc.2019.01057. eCollection 2019.