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 | N0 (n = 63) | N1-2 (n = 52) | P value |
DWIb=0 | Dissimilarity | 0.018 ± 0.015 | 0.017 ± 0.011 | 0.2182 |
Sum average | 2.099 ± 0.067 | 2.075 ± 0.053 | 0.0451 | |
Difference variance | 0.151 ± 0.145 | 0.146 ± 0.181 | 0.3342 | |
Information correlation | 0.211 ± 0.076 | 0.206 ± 0.063 | 0.0522 | |
Gray level nonuniformity | 1.727 ± 0.623 | 1.559 ± 0.884 | 0.0391 | |
Run percentage | 0.079 ± 0.022 | 0.078 ± 0.021 | 0.0712 | |
Long run low gray level emphasis | 5.943 ± 5.191 | 5.527 ± 4.137 | 0.1222 | |
Run-length nonuniformity | 3.082 ± 0.425 | 3.232 ± 0.493 | 0.0641 | |
SymletL | 8.301 ± 1.159 | 7.945 ± 1.279 | 0.0582 | |
SymletH | 0.487 ± 0.332 | 0.618 ± 0.349 | 0.0251 | |
SymletV | 0.348 ± 0.351 | 0.378 ± 0.346 | 0.7022 | |
SymletD | 0.158 ± 0.124 | 0.181 ± 0.449 | 0.1442 | |
DWIb=000 | Dissimilarity | 0.021 ± 0.022 | 0.019 ± 0.012 | 0.1182 |
Sum average | 2.131 ± 0.075 | 2.098 ± 0.066 | 0.0261 | |
Difference variance | 0.194 ± 0.203 | 0.192 ± 0.183 | 0.2912 | |
Information correlation | 0.221 ± 0.053 | 0.198 ± 0.057 | 0.0351 | |
Gray level nonuniformity | 1.759 ± 0.639 | 1.693 ± 0.836 | 0.0531 | |
Run percentage | 0.081 ± 0.023 | 0.078 ± 0.022 | 0.0672 | |
Long run low gray level emphasis | 9.539 ± 7.4371 | 7.835 ± 5.752 | 0.0172 | |
Run-length nonuniformity | 3.562 ± 0.4327 | 3.210 ± 0.442 | 0.0701 | |
SymletL | 8.837 ± 1.013 | 8.501 ± 1.264 | 0.0552 | |
SymletH | 0.260 ± 0.316 | 0.374 ± 0.339 | 0.0332 | |
SymletV | 0.314 ± 0.339 | 0.327 ± 0.248 | 0.3372 | |
SymletD | 0.101 ± 0.104 | 0.125 ± 0.157 | 0.2362 | |
ADC maps | ADCmin | 0.645 ± 0.347 | 0.606 ± 0.539 | 0.7722 |
ADCmax | 2.642 ± 0.859 | 2.423 ± 0.857 | 0.0111 | |
ADCmean | 1.208 ± 0.515 | 0.910 ± 0.446 | 0.0011 | |
Dissimilarity | 0.021 ± 0.012 | 0.018 ± 0.010 | 0.4352 | |
Sum average | 2.065 ± 0.062 | 2.049 ± 0.046 | 0.1852 | |
Difference variance | 0.199 ± 0.161 | 0.218 ± 0.153 | 0.8132 | |
Information correlation | 0.204 ± 0.483 | 0.182 ± 0.492 | 0.0211 | |
Gray level nonuniformity | 1.665 ± 0.628 | 1.545 ± 0.709 | 0.0721 | |
Run percentage | 0.079 ± 0.023 | 0.076 ± 0.021 | 0.0692 | |
Long run low gray level emphasis | 4.470 ± 4.194 | 4.377 ± 4.385 | 0.5782 | |
Run-length nonuniformity | 3.185 ± 0.387 | 3.317 ± 0.367 | 0.1061 | |
SymletL | 6.902 ± 1.184 | 6.358 ± 1.555 | 0.0411 | |
SymletH | 0.502 ± 0.247 | 0.511 ± 0.245 | 0.9601 | |
SymletV | 0.510 ± 0.337 | 0.578 ± 0.338 | 0.3872 | |
SymletD | 0.270 ± 0.133 | 0.343 ± 0.224 | 0.1421 |
- 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