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Radiomics Features of 18 F-Fluorodeoxyglucose Positron-Emission Tomography as a Novel Prognostic Signature in Colorectal Cancer

 Jeonghyun Kang  ;  Jae-Hoon Lee  ;  Hye Sun Lee  ;  Eun-Suk Cho  ;  Eun Jung Park  ;  Seung Hyuk Baik  ;  Kang Young Lee  ;  Chihyun Park  ;  Yunku Yeu  ;  Jean R Clemenceau  ;  Sunho Park  ;  Hongming Xu  ;  Changjin Hong  ;  Tae Hyun Hwang 
 CANCERS, Vol.13(3) : 392, 2021-01 
Journal Title
Issue Date
18F-fluorodeoxyglucose positron-emission tomography ; colorectal cancer ; prognosis ; progression-free survival ; radiomics
The aim of this study was to investigate the prognostic value of radiomics signatures derived from 18F-fluorodeoxyglucose (18F-FDG) positron-emission tomography (PET) in patients with colorectal cancer (CRC). From April 2008 to Jan 2014, we identified CRC patients who underwent 18F-FDG-PET before starting any neoadjuvant treatments and surgery. Radiomics features were extracted from the primary lesions identified on 18F-FDG-PET. Patients were divided into a training and validation set by random sampling. A least absolute shrinkage and selection operator Cox regression model was applied for prognostic signature building with progression-free survival (PFS) using the training set. Using the calculated radiomics score, a nomogram was developed, and its clinical utility was assessed in the validation set. A total of 381 patients with surgically resected CRC patients (training set: 228 vs. validation set: 153) were included. In the training set, a radiomics signature labeled as a rad_score was generated using two PET-derived features, such as gray-level run length matrix long-run emphasis (GLRLM_LRE) and gray-level zone length matrix short-zone low-gray-level emphasis (GLZLM_SZLGE). Patients with a high rad_score in the training and validation set had a shorter PFS. Multivariable analysis revealed that the rad_score was an independent prognostic factor in both training and validation sets. A radiomics nomogram, developed using rad_score, nodal stage, and lymphovascular invasion, showed good performance in the calibration curve and comparable predictive power with the staging system in the validation set. Textural features derived from 18F-FDG-PET images may enable detailed stratification of prognosis in patients with CRC.
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1. College of Medicine (의과대학) > Dept. of Surgery (외과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Nuclear Medicine (핵의학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Yonsei Biomedical Research Center (연세의생명연구원) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
Yonsei Authors
Kang, Jeonghyun(강정현) ORCID logo https://orcid.org/0000-0001-7311-6053
Park, Eun Jung(박은정) ORCID logo https://orcid.org/0000-0002-4559-2690
Baik, Seung Hyuk(백승혁) ORCID logo https://orcid.org/0000-0003-4183-2332
Lee, Kang Young(이강영)
Lee, Jae Hoon(이재훈) ORCID logo https://orcid.org/0000-0002-9898-9886
Lee, Hye Sun(이혜선) ORCID logo https://orcid.org/0000-0001-6328-6948
Cho, Eun Suk(조은석)
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