抄録
Aim: To investigate whether liver fibrosis can be predicted by quantifying the deformity of the liver obtained based on computed tomographic (CT) images scanned under respiratory control. Materials and Methods: For dynamic CT of 47 patients, portal venous and equilibrium phases were scanned during inspiration and expiration, respectively. After rigid registration of the two images, non-rigid registration of the liver was performed, and the amount and direction of each voxel's shift during non-rigid registration was defined as the deformation vector. The correlation of each CT parameter for the obtained deformation vectors with the pathologically-proven degree of liver fibrosis was assessed using Spearman's rank correlation test. Receiver operating characteristic curve analysis was conducted for prediction of liver fibrosis. Results: The standard deviation, coefficient of variance (CV) and skewness were significantly negatively correlated with the degree of liver fibrosis (p=0.030, 0.009 and 0.037, respectively). Of these measures, CV was best correlated and significantly decreased as liver fibrosis progressed (rho=−0.376). CV showed accuracies of 66.0-70.2%, and the areas under curves were 0.654-0.727 for prediction of fibrosis of grade F1 or greater, F2 or greater, F3 or greater and F4 fibrosis. Conclusion: The deformation vector is a potential CT parameter for evaluating liver fibrosis.
| 元の言語 | 英語 |
|---|---|
| ページ（範囲） | 1417-1424 |
| ページ数 | 8 |
| ジャーナル | Anticancer research |
| 巻 | 39 |
| 発行部数 | 3 |
| DOI | |
| 出版物ステータス | 出版済み - 3 2019 |
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All Science Journal Classification (ASJC) codes
- Oncology
- Cancer Research
これを引用
Prediction of liver fibrosis using CT under respiratory control : New attempt using deformation vectors obtained by non-rigid registration technique. / Nishie, Akihiro; Akahori, Sadato; Asayama, Yoshiki; Ishigami, Kousei; Ushijima, Yasuhiro; Kakihara, Daisuke; Nakayama, Tomohiro; Takayama, Yukihisa; Fujita, Nobuhiro; Morita, Koichiro; Ishimatsu, Keisuke; Takao, Seiichiro; Yoshizumi, Tomoharu; Kohashi, Kenichi; Li, Yuanzhong; Honda, Hiroshi.
：: Anticancer research, 巻 39, 番号 3, 03.2019, p. 1417-1424.研究成果: ジャーナルへの寄稿 › 記事
}
TY - JOUR
T1 - Prediction of liver fibrosis using CT under respiratory control
T2 - New attempt using deformation vectors obtained by non-rigid registration technique
AU - Nishie, Akihiro
AU - Akahori, Sadato
AU - Asayama, Yoshiki
AU - Ishigami, Kousei
AU - Ushijima, Yasuhiro
AU - Kakihara, Daisuke
AU - Nakayama, Tomohiro
AU - Takayama, Yukihisa
AU - Fujita, Nobuhiro
AU - Morita, Koichiro
AU - Ishimatsu, Keisuke
AU - Takao, Seiichiro
AU - Yoshizumi, Tomoharu
AU - Kohashi, Kenichi
AU - Li, Yuanzhong
AU - Honda, Hiroshi
PY - 2019/3
Y1 - 2019/3
N2 - Aim: To investigate whether liver fibrosis can be predicted by quantifying the deformity of the liver obtained based on computed tomographic (CT) images scanned under respiratory control. Materials and Methods: For dynamic CT of 47 patients, portal venous and equilibrium phases were scanned during inspiration and expiration, respectively. After rigid registration of the two images, non-rigid registration of the liver was performed, and the amount and direction of each voxel's shift during non-rigid registration was defined as the deformation vector. The correlation of each CT parameter for the obtained deformation vectors with the pathologically-proven degree of liver fibrosis was assessed using Spearman's rank correlation test. Receiver operating characteristic curve analysis was conducted for prediction of liver fibrosis. Results: The standard deviation, coefficient of variance (CV) and skewness were significantly negatively correlated with the degree of liver fibrosis (p=0.030, 0.009 and 0.037, respectively). Of these measures, CV was best correlated and significantly decreased as liver fibrosis progressed (rho=−0.376). CV showed accuracies of 66.0-70.2%, and the areas under curves were 0.654-0.727 for prediction of fibrosis of grade F1 or greater, F2 or greater, F3 or greater and F4 fibrosis. Conclusion: The deformation vector is a potential CT parameter for evaluating liver fibrosis.
AB - Aim: To investigate whether liver fibrosis can be predicted by quantifying the deformity of the liver obtained based on computed tomographic (CT) images scanned under respiratory control. Materials and Methods: For dynamic CT of 47 patients, portal venous and equilibrium phases were scanned during inspiration and expiration, respectively. After rigid registration of the two images, non-rigid registration of the liver was performed, and the amount and direction of each voxel's shift during non-rigid registration was defined as the deformation vector. The correlation of each CT parameter for the obtained deformation vectors with the pathologically-proven degree of liver fibrosis was assessed using Spearman's rank correlation test. Receiver operating characteristic curve analysis was conducted for prediction of liver fibrosis. Results: The standard deviation, coefficient of variance (CV) and skewness were significantly negatively correlated with the degree of liver fibrosis (p=0.030, 0.009 and 0.037, respectively). Of these measures, CV was best correlated and significantly decreased as liver fibrosis progressed (rho=−0.376). CV showed accuracies of 66.0-70.2%, and the areas under curves were 0.654-0.727 for prediction of fibrosis of grade F1 or greater, F2 or greater, F3 or greater and F4 fibrosis. Conclusion: The deformation vector is a potential CT parameter for evaluating liver fibrosis.
UR - http://www.scopus.com/inward/record.url?scp=85062615248&partnerID=8YFLogxK
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U2 - 10.21873/anticanres.13257
DO - 10.21873/anticanres.13257
M3 - Article
C2 - 30842177
AN - SCOPUS:85062615248
VL - 39
SP - 1417
EP - 1424
JO - Anticancer Research
JF - Anticancer Research
SN - 0250-7005
IS - 3
ER -