Development and validation of an individualized nomogram to identify occult peritoneal metastasis in patients with advanced gastric cancer

Abstract Background Occult peritoneal metastasis (PM) in advanced gastric cancer (AGC) patients is highly possible to be missed on computed tomography (CT) images. Patients with occult PMs are subject to late detection or even improper surgical treatment. We therefore aimed to develop a radiomic nom...

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Vydané v:	Annals of oncology Ročník 30; číslo 3; s. 431 - 438
Hlavní autori:	Dong, D, Tang, L, Li, Z -Y, Fang, M -J, Gao, J -B, Shan, X -H, Ying, X -J, Sun, Y -S, Fu, J, Wang, X -X, Li, L -M, Li, Z -H, Zhang, D -F, Zhang, Y, Li, Z -M, Shan, F, Bu, Z -D, Tian, J, Ji, J -F
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	England Oxford University Press 01.03.2019
Predmet:	Female Humans Laparoscopy Male Middle Aged Neoplasm Metastasis Neoplasm Staging Nomograms Peritoneal Neoplasms - diagnosis Peritoneal Neoplasms - diagnostic imaging Peritoneal Neoplasms - pathology Peritoneal Neoplasms - secondary Peritoneum - diagnostic imaging Peritoneum - pathology Radiometry - methods Stomach Neoplasms - diagnosis Stomach Neoplasms - diagnostic imaging Stomach Neoplasms - pathology Tomography Scanners, X-Ray Computed radiomic nomogram occult peritoneal metastasis advanced gastric cancer
ISSN:	0923-7534, 1569-8041, 1569-8041
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Abstract	Abstract Background Occult peritoneal metastasis (PM) in advanced gastric cancer (AGC) patients is highly possible to be missed on computed tomography (CT) images. Patients with occult PMs are subject to late detection or even improper surgical treatment. We therefore aimed to develop a radiomic nomogram to preoperatively identify occult PMs in AGC patients. Patients and methods A total of 554 AGC patients from 4 centers were divided into 1 training, 1 internal validation, and 2 external validation cohorts. All patients' PM status was firstly diagnosed as negative by CT, but later confirmed by laparoscopy (PM-positive n = 122, PM-negative n = 432). Radiomic signatures reflecting phenotypes of the primary tumor (RS1) and peritoneum region (RS2) were built as predictors of PM from 266 quantitative image features. Individualized nomograms of PM status incorporating RS1, RS2, or clinical factors were developed and evaluated regarding prediction ability. Results RS1, RS2, and Lauren type were significant predictors of occult PM (all P < 0.05). A nomogram of these three factors demonstrated better diagnostic accuracy than the model with RS1, RS2, or clinical factors alone (all net reclassification improvement P < 0.05). The area under curve yielded was 0.958 [95% confidence interval (CI) 0.923-0.993], 0.941 (95% CI 0.904-0.977), 0.928 (95% CI 0.886-0.971), and 0.920 (95% CI 0.862-0.978) for the training, internal, and two external validation cohorts, respectively. Stratification analysis showed that this nomogram had potential generalization ability. Conclusion CT phenotypes of both primary tumor and nearby peritoneum are significantly associated with occult PM status. A nomogram of these CT phenotypes and Lauren type has an excellent prediction ability of occult PM, and may have significant clinical implications on early detection of occult PM for AGC.
AbstractList	Occult peritoneal metastasis (PM) in advanced gastric cancer (AGC) patients is highly possible to be missed on computed tomography (CT) images. Patients with occult PMs are subject to late detection or even improper surgical treatment. We therefore aimed to develop a radiomic nomogram to preoperatively identify occult PMs in AGC patients.BACKGROUNDOccult peritoneal metastasis (PM) in advanced gastric cancer (AGC) patients is highly possible to be missed on computed tomography (CT) images. Patients with occult PMs are subject to late detection or even improper surgical treatment. We therefore aimed to develop a radiomic nomogram to preoperatively identify occult PMs in AGC patients.A total of 554 AGC patients from 4 centers were divided into 1 training, 1 internal validation, and 2 external validation cohorts. All patients' PM status was firstly diagnosed as negative by CT, but later confirmed by laparoscopy (PM-positive n = 122, PM-negative n = 432). Radiomic signatures reflecting phenotypes of the primary tumor (RS1) and peritoneum region (RS2) were built as predictors of PM from 266 quantitative image features. Individualized nomograms of PM status incorporating RS1, RS2, or clinical factors were developed and evaluated regarding prediction ability.PATIENTS AND METHODSA total of 554 AGC patients from 4 centers were divided into 1 training, 1 internal validation, and 2 external validation cohorts. All patients' PM status was firstly diagnosed as negative by CT, but later confirmed by laparoscopy (PM-positive n = 122, PM-negative n = 432). Radiomic signatures reflecting phenotypes of the primary tumor (RS1) and peritoneum region (RS2) were built as predictors of PM from 266 quantitative image features. Individualized nomograms of PM status incorporating RS1, RS2, or clinical factors were developed and evaluated regarding prediction ability.RS1, RS2, and Lauren type were significant predictors of occult PM (all P < 0.05). A nomogram of these three factors demonstrated better diagnostic accuracy than the model with RS1, RS2, or clinical factors alone (all net reclassification improvement P < 0.05). The area under curve yielded was 0.958 [95% confidence interval (CI) 0.923-0.993], 0.941 (95% CI 0.904-0.977), 0.928 (95% CI 0.886-0.971), and 0.920 (95% CI 0.862-0.978) for the training, internal, and two external validation cohorts, respectively. Stratification analysis showed that this nomogram had potential generalization ability.RESULTSRS1, RS2, and Lauren type were significant predictors of occult PM (all P < 0.05). A nomogram of these three factors demonstrated better diagnostic accuracy than the model with RS1, RS2, or clinical factors alone (all net reclassification improvement P < 0.05). The area under curve yielded was 0.958 [95% confidence interval (CI) 0.923-0.993], 0.941 (95% CI 0.904-0.977), 0.928 (95% CI 0.886-0.971), and 0.920 (95% CI 0.862-0.978) for the training, internal, and two external validation cohorts, respectively. Stratification analysis showed that this nomogram had potential generalization ability.CT phenotypes of both primary tumor and nearby peritoneum are significantly associated with occult PM status. A nomogram of these CT phenotypes and Lauren type has an excellent prediction ability of occult PM, and may have significant clinical implications on early detection of occult PM for AGC.CONCLUSIONCT phenotypes of both primary tumor and nearby peritoneum are significantly associated with occult PM status. A nomogram of these CT phenotypes and Lauren type has an excellent prediction ability of occult PM, and may have significant clinical implications on early detection of occult PM for AGC. Abstract Background Occult peritoneal metastasis (PM) in advanced gastric cancer (AGC) patients is highly possible to be missed on computed tomography (CT) images. Patients with occult PMs are subject to late detection or even improper surgical treatment. We therefore aimed to develop a radiomic nomogram to preoperatively identify occult PMs in AGC patients. Patients and methods A total of 554 AGC patients from 4 centers were divided into 1 training, 1 internal validation, and 2 external validation cohorts. All patients' PM status was firstly diagnosed as negative by CT, but later confirmed by laparoscopy (PM-positive n = 122, PM-negative n = 432). Radiomic signatures reflecting phenotypes of the primary tumor (RS1) and peritoneum region (RS2) were built as predictors of PM from 266 quantitative image features. Individualized nomograms of PM status incorporating RS1, RS2, or clinical factors were developed and evaluated regarding prediction ability. Results RS1, RS2, and Lauren type were significant predictors of occult PM (all P < 0.05). A nomogram of these three factors demonstrated better diagnostic accuracy than the model with RS1, RS2, or clinical factors alone (all net reclassification improvement P < 0.05). The area under curve yielded was 0.958 [95% confidence interval (CI) 0.923-0.993], 0.941 (95% CI 0.904-0.977), 0.928 (95% CI 0.886-0.971), and 0.920 (95% CI 0.862-0.978) for the training, internal, and two external validation cohorts, respectively. Stratification analysis showed that this nomogram had potential generalization ability. Conclusion CT phenotypes of both primary tumor and nearby peritoneum are significantly associated with occult PM status. A nomogram of these CT phenotypes and Lauren type has an excellent prediction ability of occult PM, and may have significant clinical implications on early detection of occult PM for AGC. Occult peritoneal metastasis (PM) in advanced gastric cancer (AGC) patients is highly possible to be missed on computed tomography (CT) images. Patients with occult PMs are subject to late detection or even improper surgical treatment. We therefore aimed to develop a radiomic nomogram to preoperatively identify occult PMs in AGC patients. A total of 554 AGC patients from 4 centers were divided into 1 training, 1 internal validation, and 2 external validation cohorts. All patients' PM status was firstly diagnosed as negative by CT, but later confirmed by laparoscopy (PM-positive n = 122, PM-negative n = 432). Radiomic signatures reflecting phenotypes of the primary tumor (RS1) and peritoneum region (RS2) were built as predictors of PM from 266 quantitative image features. Individualized nomograms of PM status incorporating RS1, RS2, or clinical factors were developed and evaluated regarding prediction ability. RS1, RS2, and Lauren type were significant predictors of occult PM (all P < 0.05). A nomogram of these three factors demonstrated better diagnostic accuracy than the model with RS1, RS2, or clinical factors alone (all net reclassification improvement P < 0.05). The area under curve yielded was 0.958 [95% confidence interval (CI) 0.923-0.993], 0.941 (95% CI 0.904-0.977), 0.928 (95% CI 0.886-0.971), and 0.920 (95% CI 0.862-0.978) for the training, internal, and two external validation cohorts, respectively. Stratification analysis showed that this nomogram had potential generalization ability. CT phenotypes of both primary tumor and nearby peritoneum are significantly associated with occult PM status. A nomogram of these CT phenotypes and Lauren type has an excellent prediction ability of occult PM, and may have significant clinical implications on early detection of occult PM for AGC.
Author	Dong, D Shan, X -H Sun, Y -S Li, L -M Li, Z -Y Zhang, Y Bu, Z -D Wang, X -X Gao, J -B Zhang, D -F Tian, J Shan, F Fu, J Fang, M -J Li, Z -H Tang, L Ji, J -F Li, Z -M Ying, X -J
Author_xml	– sequence: 1 givenname: D surname: Dong fullname: Dong, D organization: CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing – sequence: 2 givenname: L surname: Tang fullname: Tang, L organization: Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Radiology Department, , Peking University Cancer Hospital & Institute, Beijing – sequence: 3 givenname: Z -Y surname: Li fullname: Li, Z -Y organization: Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Gastrointestinal Cancer Center, Peking University Cancer Hospital & Institute, Beijing – sequence: 4 givenname: M -J surname: Fang fullname: Fang, M -J organization: CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing – sequence: 5 givenname: J -B surname: Gao fullname: Gao, J -B organization: Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou – sequence: 6 givenname: X -H surname: Shan fullname: Shan, X -H organization: Department of Radiology, Affiliated People's Hospital of Jiangsu University, Zhenjiang – sequence: 7 givenname: X -J surname: Ying fullname: Ying, X -J organization: Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Gastrointestinal Cancer Center, Peking University Cancer Hospital & Institute, Beijing – sequence: 8 givenname: Y -S surname: Sun fullname: Sun, Y -S organization: Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Radiology Department, , Peking University Cancer Hospital & Institute, Beijing – sequence: 9 givenname: J surname: Fu fullname: Fu, J email: jijiafu@hsc.pku.edu.cn organization: Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Radiology Department, , Peking University Cancer Hospital & Institute, Beijing – sequence: 10 givenname: X -X surname: Wang fullname: Wang, X -X organization: Department of Radiology, Affiliated People's Hospital of Jiangsu University, Zhenjiang – sequence: 11 givenname: L -M surname: Li fullname: Li, L -M organization: Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou – sequence: 12 givenname: Z -H surname: Li fullname: Li, Z -H organization: Department of Radiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming – sequence: 13 givenname: D -F surname: Zhang fullname: Zhang, D -F organization: Department of Radiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming – sequence: 14 givenname: Y surname: Zhang fullname: Zhang, Y organization: Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Gastrointestinal Cancer Center, Peking University Cancer Hospital & Institute, Beijing – sequence: 15 givenname: Z -M surname: Li fullname: Li, Z -M organization: Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Gastrointestinal Cancer Center, Peking University Cancer Hospital & Institute, Beijing – sequence: 16 givenname: F surname: Shan fullname: Shan, F organization: Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Gastrointestinal Cancer Center, Peking University Cancer Hospital & Institute, Beijing – sequence: 17 givenname: Z -D surname: Bu fullname: Bu, Z -D organization: Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Gastrointestinal Cancer Center, Peking University Cancer Hospital & Institute, Beijing – sequence: 18 givenname: J surname: Tian fullname: Tian, J email: jie.tian@ia.ac.cn organization: CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing – sequence: 19 givenname: J -F surname: Ji fullname: Ji, J -F email: jijiafu@hsc.pku.edu.cn organization: Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Gastrointestinal Cancer Center, Peking University Cancer Hospital & Institute, Beijing
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/30689702$$D View this record in MEDLINE/PubMed
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Copyright	The Author(s) 2019. Published by Oxford University Press on behalf of the European Society for Medical Oncology. 2019 The Author(s) 2019. Published by Oxford University Press on behalf of the European Society for Medical Oncology.
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Keywords	radiomic nomogram occult peritoneal metastasis advanced gastric cancer
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Snippet	Abstract Background Occult peritoneal metastasis (PM) in advanced gastric cancer (AGC) patients is highly possible to be missed on computed tomography (CT)... Occult peritoneal metastasis (PM) in advanced gastric cancer (AGC) patients is highly possible to be missed on computed tomography (CT) images. Patients with...
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SubjectTerms	Female Humans Laparoscopy Male Middle Aged Neoplasm Metastasis Neoplasm Staging Nomograms Peritoneal Neoplasms - diagnosis Peritoneal Neoplasms - diagnostic imaging Peritoneal Neoplasms - pathology Peritoneal Neoplasms - secondary Peritoneum - diagnostic imaging Peritoneum - pathology Radiometry - methods Stomach Neoplasms - diagnosis Stomach Neoplasms - diagnostic imaging Stomach Neoplasms - pathology Tomography Scanners, X-Ray Computed
Title	Development and validation of an individualized nomogram to identify occult peritoneal metastasis in patients with advanced gastric cancer
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