Copyright
©The Author(s) 2020.
World J Gastroenterol. May 7, 2020; 26(17): 2082-2096
Published online May 7, 2020. doi: 10.3748/wjg.v26.i17.2082
Published online May 7, 2020. doi: 10.3748/wjg.v26.i17.2082
Method | Features | T1-2 (n = 31) | T3-4 (n = 84) | P value |
DWIb=0 | Dissimilarity | 0.015 ± 0.008 | 0.018 ± 0.013 | 0.0172 |
Sum average | 2.068 ± 0.043 | 2.095 ± 0.067 | 0.0181 | |
Difference variance | 0.140 ± 0.085 | 0.161 ± 0.192 | 0.1352 | |
Information correlation | 0.185 ± 0.058 | 0.215 ± 0.067 | 0.0162 | |
Gray level nonuniformity | 1.411 ± 0.351 | 1.730 ± 0.811 | 0.0191 | |
Run percentage | 0.075 ± 0.012 | 0.083 ± 0.023 | 0.0092 | |
Long run low gray level emphasis | 4.971 ± 4.897 | 5.840 ± 4.678 | 0.3162 | |
Run-length nonuniformity | 3.266 ± 0.356 | 3.107 ± 0.445 | 0.0301 | |
SymletL | 7.815 ± 1.568 | 8.295 ± 1.153 | 0.3672 | |
SymletH | 0.627 ± 0.4011 | 0.516 ± 0.318 | 0.2211 | |
SymletV | 0.335 ± 0.460 | 0.359 ± 0.298 | 0.8162 | |
SymletD | 0.162 ± 0.158 | 0.177 ± 0.114 | 0.3712 | |
DWIb=1000 | Dissimilarity | 0.018 ± 0.006 | 0.021 ± 0.018 | 0.0602 |
Sum average | 2.098 ± 0.058 | 2.122 ± 0.076 | 0.1211 | |
Difference variance | 0.176 ± 0.105 | 0.198 ± 0.257 | 0.3482 | |
Information correlation | 0.194 ± 0.041 | 0.217 ± 0.058 | 0.0531 | |
Gray level nonuniformity | 1.443 ± 0.370 | 1.773 ± 0.815 | 0.0211 | |
Run percentage | 0.075 ± 0.014 | 0.083 ± 0.023 | 0.0092 | |
Long run low gray level emphasis | 8.801 ± 5.347 | 8.646 ± 7.836 | 0.9802 | |
Run-length nonuniformity | 3.239 ± 0.371 | 3.084 ± 0.461 | 0.0361 | |
SymletL | 8.461 ± 1.329 | 8.749 ± 0.984 | 0.9352 | |
SymletH | 0.318 ± 0.387 | 0.336 ± 0.261 | 0.6962 | |
SymletV | 0.293 ± 0.371 | 0.316 ± 0.249 | 0.5012 | |
SymletD | 0.099 ± 0.124 | 0.118 ± 0.113 | 0.1372 | |
ADC maps | ADCmin | 0.328 ± 0.385 | 0.262 ± 0.367 | 0.7452 |
ADCmax | 2.513 ± 0.855 | 2.704 ± 0.885 | 0.2981 | |
ADCmean | 1.099 ± 0.471 | 1.063 ± 0.521 | 0.7401 | |
Dissimilarity | 0.062 ± 0.008 | 0.021 ± 0.011 | 0.0202 | |
Sum average | 2.049 ± 0.038 | 2.063 ± 0.061 | 0.1712 | |
Difference variance | 0.170 ± 0.122 | 0.218 ± 0.135 | 0.1372 | |
Information correlation | 0.181 ± 0.041 | 0.199 ± 0.052 | 0.0551 | |
Gray level nonuniformity | 1.367 ± 0.334 | 1.675 ± 0.739 | 0.0141 | |
Run percentage | 0.073 ± 0.011 | 0.082 ± 0.021 | 0.0122 | |
Long run low gray level emphasis | 4.006 ± 4.016 | 4.558 ± 4.364 | 0.8602 | |
Run-length nonuniformity | 3.309 ± 0.498 | 3.168 ± 4.328 | 0.0681 | |
SymletL | 6.789 ± 1.253 | 6.607 ± 1.435 | 0.5251 | |
SymletH | 0.443 ± 0.187 | 0.530 ± 0.261 | 0.7911 | |
SymletV | 0.473 ± 0.358 | 0.572 ± 0.350 | 0.1992 | |
SymletD | 0.313 ± 0.224 | 0.301 ± 0.166 | 0.9051 |
- Citation: Yin JD, Song LR, Lu HC, Zheng X. Prediction of different stages of rectal cancer: Texture analysis based on diffusion-weighted images and apparent diffusion coefficient maps. World J Gastroenterol 2020; 26(17): 2082-2096
- URL: https://www.wjgnet.com/1007-9327/full/v26/i17/2082.htm
- DOI: https://dx.doi.org/10.3748/wjg.v26.i17.2082