Shuaitong Zhang1,2, Shengyu Huang3,4, Wei He5, Jingwei Wei1, Lei Huo6, Ningyang Jia6, Jianbo Lin3,4, Zhenchao Tang7, Yunfei Yuan6, Jie Tian8,9,10, Feng Shen11, Jun Li12,13. 1. CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China. 2. School of Engineering Medicine, Beihang University, Beijing, China. 3. Department of Hepatobiliary and Pancreatic Surgery, Tenth People's Hospital of Tongji University, Shanghai, China. 4. Department of Hepatic Surgery IV, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai, China. 5. Department of Hepatobiliary Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, China. 6. Department of Radiotherapy, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai, China. 7. Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shanxi, China. 8. CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China. jie.tian@ia.ac.cn. 9. School of Engineering Medicine, Beihang University, Beijing, China. jie.tian@ia.ac.cn. 10. Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shanxi, China. jie.tian@ia.ac.cn. 11. Department of Hepatic Surgery IV, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai, China. shenfengehbh@sina.com. 12. Department of Hepatobiliary and Pancreatic Surgery, Tenth People's Hospital of Tongji University, Shanghai, China. lijundfgd1@163.com. 13. Department of Hepatic Surgery IV, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai, China. lijundfgd1@163.com.
Abstract
BACKGROUND: Lymph node (LN) metastasis is significantly associated with worse prognosis for patients with intrahepatic cholangiocarcinoma (ICC). Improvement in preoperative assessment on LN metastasis helps in treatment decision-making. We aimed to investigate the role of radiomics-based method in predicting LN metastasis for patients with ICC. METHODS: A total of 296 patients with ICC who underwent curative-intent hepatectomy and lymphadenectomy at two centers in China were analyzed. Radiomic features, including histogram- and wavelet-based features, shape and size features, and texture features were extracted from four-phase computerized tomography (CT) images. The clinical and conventional radiological variables which were independently associated with LN metastasis were also identified. A combined nomogram predicting LN metastasis was developed, and its performance was determined by discrimination, calibration, and stratification of long-term prognosis. The results were validated by the internal and external validation cohorts. RESULTS: Twenty-four radiomic features were selected into the nomogram. The established nomogram demonstrated good discrimination and calibration, with areas under the curve (AUCs) of 0.98 [95% confidence interval (CI) 0.96-0.99], 0.93 (0.88-0.98), and 0.89 (0.81-0.96) in the training and two validation cohorts, respectively. The 5-year overall survival (OS) and recurrence-free survival (RFS) rates of patients with high risk of LN metastasis as grouped by nomogram were poorer than those of patients with low risk in the training cohort (OS 28.8% versus 53.9%, p < 0.001; RFS 26.3% versus 44.2%, p = 0.001). Similar results were observed in the two validation cohorts. CONCLUSIONS: Radiomics-based method provided accurate prediction of LN metastasis and prognostic assessment for ICC patients, and might aid the preoperative surgical decision.
BACKGROUND: Lymph node (LN) metastasis is significantly associated with worse prognosis for patients with intrahepatic cholangiocarcinoma (ICC). Improvement in preoperative assessment on LN metastasis helps in treatment decision-making. We aimed to investigate the role of radiomics-based method in predicting LN metastasis for patients with ICC. METHODS: A total of 296 patients with ICC who underwent curative-intent hepatectomy and lymphadenectomy at two centers in China were analyzed. Radiomic features, including histogram- and wavelet-based features, shape and size features, and texture features were extracted from four-phase computerized tomography (CT) images. The clinical and conventional radiological variables which were independently associated with LN metastasis were also identified. A combined nomogram predicting LN metastasis was developed, and its performance was determined by discrimination, calibration, and stratification of long-term prognosis. The results were validated by the internal and external validation cohorts. RESULTS: Twenty-four radiomic features were selected into the nomogram. The established nomogram demonstrated good discrimination and calibration, with areas under the curve (AUCs) of 0.98 [95% confidence interval (CI) 0.96-0.99], 0.93 (0.88-0.98), and 0.89 (0.81-0.96) in the training and two validation cohorts, respectively. The 5-year overall survival (OS) and recurrence-free survival (RFS) rates of patients with high risk of LN metastasis as grouped by nomogram were poorer than those of patients with low risk in the training cohort (OS 28.8% versus 53.9%, p < 0.001; RFS 26.3% versus 44.2%, p = 0.001). Similar results were observed in the two validation cohorts. CONCLUSIONS: Radiomics-based method provided accurate prediction of LN metastasis and prognostic assessment for ICC patients, and might aid the preoperative surgical decision.
Authors: Xu-Feng Zhang; Yi Lv; Matthew Weiss; Irinel Popescu; Hugo P Marques; Luca Aldrighetti; Shishir K Maithel; Carlo Pulitano; Todd W Bauer; Feng Shen; George A Poultsides; Oliver Soubrane; Guillaume Martel; B Groot Koerkamp; Endo Itaru; Timothy M Pawlik Journal: Ann Surg Oncol Date: 2019-03-29 Impact factor: 5.344
Authors: Gaya Spolverato; Yuhree Kim; Sorin Alexandrescu; Hugo P Marques; Jorge Lamelas; Luca Aldrighetti; T Clark Gamblin; Shishir K Maithel; Carlo Pulitano; Todd W Bauer; Feng Shen; George A Poultsides; Thuy B Tran; J Wallis Marsh; Timothy M Pawlik Journal: Ann Surg Oncol Date: 2015-06-10 Impact factor: 5.344