Metastatic lymph node analysis of colorectal cancer using quadruple-phase CT images

Keisuke Bando; Ren Nishimoto; Mikio Matsuhiro; Hidenobu Suzuki; Yoshiki Kawata; Noboru Niki; Gen Iinuma

doi:10.1117/12.2512738

13 March 2019 Metastatic lymph node analysis of colorectal cancer using quadruple-phase CT images

Keisuke Bando, Ren Nishimoto, Mikio Matsuhiro, Hidenobu Suzuki, Yoshiki Kawata, Noboru Niki, Gen Iinuma

Proceedings Volume 10950, Medical Imaging 2019: Computer-Aided Diagnosis; 109503U (2019) https://doi.org/10.1117/12.2512738
Event: SPIE Medical Imaging, 2019, San Diego, California, United States

Abstract

The mortality rate of colorectal cancer in Japan is increasing year by year. The mortality rate is 3rd in males and 1st in death rate in females. However, it is possible to raise the 5-year survival rate to over 80% by discovering and resecting it early. Colorectal cancer is a malignant tumor that spreads and spreads. There are various types of metastasis, but the most important factor in predicting the prognosis of early colorectal cancer patients is lymph node metastasis. Generally, it is said that the greater the lymph node diameter, the higher the possibility of positive for metastasis. However, there are cases where metastasis is also confirmed in those with small lymph node diameters. The purpose of this study is to detect the metastatic lymph nodes using spatiotemporal features of triplet-phase CT images (arterial phase, portal vein phase, equilibrium phase). This method consists of 1) lymph node extraction, 2) metastatic lymph node classification and 3) quantitative assessment of metastatic lymph node. The method was applied to 33 cases of rectal cancer. For quantitative analysis of lymph node metastasis, logistic regression analysis is used to identify the image feature dominant in lymph node metastasis.

Citation Download Citation

Keisuke Bando, Ren Nishimoto, Mikio Matsuhiro, Hidenobu Suzuki, Yoshiki Kawata, Noboru Niki, and Gen Iinuma "Metastatic lymph node analysis of colorectal cancer using quadruple-phase CT images", Proc. SPIE 10950, Medical Imaging 2019: Computer-Aided Diagnosis, 109503U (13 March 2019); https://doi.org/10.1117/12.2512738

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