{"title":"基于 18F-FDG PET/CT 的放射组学特征在区分结直肠腺癌患者的原发性肺癌和单发肺转移瘤方面的价值。","authors":"Na Wang,Meng Dai,Fenglian Jing,Yunuan Liu,Yan Zhao,Zhaoqi Zhang,Jianfang Wang,Jingmian Zhang,Yingchen Wang,Xinming Zhao","doi":"10.1080/09553002.2024.2404465","DOIUrl":null,"url":null,"abstract":"OBJECTIVE\r\nTo investigate the value and applicability of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) radiomics in differentiating primary lung cancer (PLC) from solitary lung metastasis (SLM) in patients with colorectal cancer (CRC).\r\n\r\nMATERIALS AND METHODS\r\nThis retrospective study included 103 patients with CRC and solitary pulmonary nodules (SPNs). The least absolute shrinkage and selection operator (LASSO) was used to screen for optimal radiomics features and establish a PET/CT radiomics model. PET/CT Visual and complex models (combining radiomics with PET/CT visual features) were developed. The area under the receiver operating characteristic (ROC) curve (AUC) was used to determine the predictive value and diagnostic efficiency of the models.\r\n\r\nRESULTS\r\nThe AUC of the PET/CT radiomics model for differentiating PLC from SLM was 0.872 (95% CI: 0.806-0.939), which was not different from that of the visual (0.829 [95% CI: 0.749-0.908; p = .352]). However, the AUC of the complex model (0.936 [95% CI:0.892-0.981]) was significantly higher than that of the PET/CT radiomics (p = .005) and visual model (p = .001). The sensitivity (SEN), specificity (SPE), accuracy (ACC), positive predictive value (PPV), and negative predictive value (NPV) of PET/CT radiomics for differentiating PLC from SLM were 0.720, 0.887, 0.806, 0.857, and 0.770, respectively.\r\n\r\nCONCLUSION\r\nPET/CT radiomics can effectively distinguish PLC and SLM in patients with CRC and SPNs and guide the implementation of personalized treatment.","PeriodicalId":14261,"journal":{"name":"International Journal of Radiation Biology","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Value of 18F-FDG PET/CT-based radiomics features for differentiating primary lung cancer and solitary lung metastasis in patients with colorectal adenocarcinoma.\",\"authors\":\"Na Wang,Meng Dai,Fenglian Jing,Yunuan Liu,Yan Zhao,Zhaoqi Zhang,Jianfang Wang,Jingmian Zhang,Yingchen Wang,Xinming Zhao\",\"doi\":\"10.1080/09553002.2024.2404465\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"OBJECTIVE\\r\\nTo investigate the value and applicability of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) radiomics in differentiating primary lung cancer (PLC) from solitary lung metastasis (SLM) in patients with colorectal cancer (CRC).\\r\\n\\r\\nMATERIALS AND METHODS\\r\\nThis retrospective study included 103 patients with CRC and solitary pulmonary nodules (SPNs). The least absolute shrinkage and selection operator (LASSO) was used to screen for optimal radiomics features and establish a PET/CT radiomics model. PET/CT Visual and complex models (combining radiomics with PET/CT visual features) were developed. The area under the receiver operating characteristic (ROC) curve (AUC) was used to determine the predictive value and diagnostic efficiency of the models.\\r\\n\\r\\nRESULTS\\r\\nThe AUC of the PET/CT radiomics model for differentiating PLC from SLM was 0.872 (95% CI: 0.806-0.939), which was not different from that of the visual (0.829 [95% CI: 0.749-0.908; p = .352]). However, the AUC of the complex model (0.936 [95% CI:0.892-0.981]) was significantly higher than that of the PET/CT radiomics (p = .005) and visual model (p = .001). The sensitivity (SEN), specificity (SPE), accuracy (ACC), positive predictive value (PPV), and negative predictive value (NPV) of PET/CT radiomics for differentiating PLC from SLM were 0.720, 0.887, 0.806, 0.857, and 0.770, respectively.\\r\\n\\r\\nCONCLUSION\\r\\nPET/CT radiomics can effectively distinguish PLC and SLM in patients with CRC and SPNs and guide the implementation of personalized treatment.\",\"PeriodicalId\":14261,\"journal\":{\"name\":\"International Journal of Radiation Biology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2024-09-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Radiation Biology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1080/09553002.2024.2404465\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Radiation Biology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/09553002.2024.2404465","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOLOGY","Score":null,"Total":0}
Value of 18F-FDG PET/CT-based radiomics features for differentiating primary lung cancer and solitary lung metastasis in patients with colorectal adenocarcinoma.
OBJECTIVE
To investigate the value and applicability of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) radiomics in differentiating primary lung cancer (PLC) from solitary lung metastasis (SLM) in patients with colorectal cancer (CRC).
MATERIALS AND METHODS
This retrospective study included 103 patients with CRC and solitary pulmonary nodules (SPNs). The least absolute shrinkage and selection operator (LASSO) was used to screen for optimal radiomics features and establish a PET/CT radiomics model. PET/CT Visual and complex models (combining radiomics with PET/CT visual features) were developed. The area under the receiver operating characteristic (ROC) curve (AUC) was used to determine the predictive value and diagnostic efficiency of the models.
RESULTS
The AUC of the PET/CT radiomics model for differentiating PLC from SLM was 0.872 (95% CI: 0.806-0.939), which was not different from that of the visual (0.829 [95% CI: 0.749-0.908; p = .352]). However, the AUC of the complex model (0.936 [95% CI:0.892-0.981]) was significantly higher than that of the PET/CT radiomics (p = .005) and visual model (p = .001). The sensitivity (SEN), specificity (SPE), accuracy (ACC), positive predictive value (PPV), and negative predictive value (NPV) of PET/CT radiomics for differentiating PLC from SLM were 0.720, 0.887, 0.806, 0.857, and 0.770, respectively.
CONCLUSION
PET/CT radiomics can effectively distinguish PLC and SLM in patients with CRC and SPNs and guide the implementation of personalized treatment.
期刊介绍:
The International Journal of Radiation Biology publishes original papers, reviews, current topic articles, technical notes/reports, and meeting reports on the effects of ionizing, UV and visible radiation, accelerated particles, electromagnetic fields, ultrasound, heat and related modalities. The focus is on the biological effects of such radiations: from radiation chemistry to the spectrum of responses of living organisms and underlying mechanisms, including genetic abnormalities, repair phenomena, cell death, dose modifying agents and tissue responses. Application of basic studies to medical uses of radiation extends the coverage to practical problems such as physical and chemical adjuvants which improve the effectiveness of radiation in cancer therapy. Assessment of the hazards of low doses of radiation is also considered.