Reproducibility with repeat CT in radiomics study for rectal cancer.
OBJECTIVE
To evaluate the reproducibility of radiomics features by repeating computed tomographic (CT) scans in rectal cancer. To choose stable radiomics features for rectal cancer.


RESULTS
Volume normalized features are much more reproducible than unnormalized features. The average value of all slices is the most reproducible feature type in rectal cancer. Different filters have little effect for the reproducibility of radiomics features. For the average type features, 496 out of 775 features showed high reproducibility (ICC ≥ 0.8), 225 out of 775 features showed medium reproducibility (0.8 > ICC ≥ 0.5) and 54 out of 775 features showed low reproducibility (ICC < 0.5).


METHODS
40 rectal cancer patients with stage II were enrolled in this study, each of whom underwent two CT scans within average 8.7 days. 775 radiomics features were defined in this study. For each features, five different values (value from the largest slice, maximum value, minimum value, average value of all slices and value from superposed intermediate matrix) were extracted. Meanwhile a LOG filter with different parameters was applied to these images to find stable filter value. Concordance correlation coefficients (CCC) and inter-class correlation coefficients (ICC) of two CT scans were calculated to assess the reproducibility, based on original features and volume normalized features.


CONCLUSIONS
Features are recommended to be normalized to volume in radiomics analysis. The average type radiomics features are the most stable features in rectal cancer. Further analysis of these features of rectal cancer can be warranted for treatment monitoring and prognosis prediction.to modulate two anticancer compounds in well-defined sets of GBM patients.
Department of Radiotherapy, Fudan University Shanghai Cancer Center, Shanghai, China.|Department of Oncology, Fudan University Shanghai Medical College, Shanghai, China.
Panpan
P
Hu
Department of Radiotherapy, Fudan University Shanghai Cancer Center, Shanghai, China.|Department of Oncology, Fudan University Shanghai Medical College, Shanghai, China.
Jiazhou
J
Wang
Department of Radiotherapy, Fudan University Shanghai Cancer Center, Shanghai, China.|Department of Oncology, Fudan University Shanghai Medical College, Shanghai, China.
Haoyu
H
Zhong
Department of Radiotherapy, Fudan University Shanghai Cancer Center, Shanghai, China.|Department of Oncology, Fudan University Shanghai Medical College, Shanghai, China.
Zhen
Z
Zhou
Department of Radiotherapy, Fudan University Shanghai Cancer Center, Shanghai, China.|Department of Oncology, Fudan University Shanghai Medical College, Shanghai, China.
Lijun
L
Shen
Department of Radiotherapy, Fudan University Shanghai Cancer Center, Shanghai, China.|Department of Oncology, Fudan University Shanghai Medical College, Shanghai, China.
Weigang
W
Hu
Department of Radiotherapy, Fudan University Shanghai Cancer Center, Shanghai, China.|Department of Oncology, Fudan University Shanghai Medical College, Shanghai, China.
Zhen
Z
Zhang
D000328:Adult; D000368:Aged; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D012004:Rectal Neoplasms / Q000000981:diagnostic imaging*; D015203:Reproducibility of Results; D014057:Tomography, X-Ray Computed / Q000379:methods*
radiomics; rectal cancer; reproducibility; textural features
Med Phys. 2015 Dec;42(12 ):6784-97
26632036
Radiology. 2003 Jun;227(3):617-22
12773666
Acta Oncol. 2013 Oct;52(7):1391-7
24047337
PLoS One. 2014 Jul 15;9(7):e102107
25025374
Radiology. 2009 Jul;252(1):263-72
19561260
Med Phys. 2015 Mar;42(3):1341-53
25735289
Psychol Bull. 1979 Mar;86(2):420-8
18839484
Med Phys. 2013 Dec;40(12 ):121916
24320527
PLoS One. 2015 Mar 04;10 (3):e0118261
25739030
Nat Commun. 2014 Jun 03;5:4006
24892406