Yang Liu , Xin Zhou , Xiangxi Meng, Xiangxing Kong, Changzhi Du, Yan Cui, Yitong Liu, Jinyu Zhu, Yuan Yao, Chunxu Cao, Min Wang, Nan Li
{"title":"结合18F-FDG PET/CT播散特征的多参数模型用于预测小细胞肺癌预后的开发和验证","authors":"Yang Liu , Xin Zhou , Xiangxi Meng, Xiangxing Kong, Changzhi Du, Yan Cui, Yitong Liu, Jinyu Zhu, Yuan Yao, Chunxu Cao, Min Wang, Nan Li","doi":"10.1016/j.ejrad.2025.112425","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><div>To evaluate the prognostic value of the tumor dissemination characteristic, metabolic parameters from baseline <sup>18</sup>F-FDG PET/CT, clinical indicators, and pathological indicators in small cell lung cancer (SCLC), and to construct prognostic models.</div></div><div><h3>Materials & Methods</h3><div>SCLC patients who underwent baseline <sup>18</sup>F-FDG PET/CT were retrospectively analyzed and randomly divided into training and validation cohorts (7:3). The tumor dissemination characteristic, metabolic characteristics, morphological features, and clinical and pathological indicators were collected. Cox regression analysis was employed to identify independent prognostic factors. Prognostic models and corresponding nomograms were developed and evaluated using receiver operating characteristic (ROC) curves.</div></div><div><h3>Results</h3><div>303 patients with SCLC were enrolled (including 204 males and 99 females; median age: 62 years, interquartile range: 56–67 years). Multivariate Cox regression analysis identified age, stage, neuron-specific enolase (NSE), and the standardized distance between the two farthest lesions (SD<sub>max</sub>) as independent prognostic factors for progression-free survival (PFS). Area under curve (AUC) values for predicting 6-month, 12-month, and 24-month PFS were 0.790, 0.778, and 0.750 in the training cohort, and 0.778, 0.771, and 0.744 in the validation cohort. For overall survival (OS), age, stage, NSE, whole-body metabolic tumor volume (MTV<sub>wb</sub>), and SD<sub>max</sub> were independent prognostic factors. AUC values for predicting 1-year, 2-year, and 3-year OS were 0.861, 0.830, and 0.799 in the training cohort, and 0.834, 0.801, and 0.787 in the validation cohort.</div></div><div><h3>Conclusion</h3><div>The tumor dissemination characteristic from baseline <sup>18</sup>F-FDG PET/CT is a novel independent prognostic factor in SCLC. Additionally, the models incorporating the dissemination characteristic, metabolic parameter, and clinical indicators demonstrate excellent predictive capabilities in SCLC.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"193 ","pages":"Article 112425"},"PeriodicalIF":3.3000,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Development and validation of multiparametric models incorporating 18F-FDG PET/CT dissemination characteristic for predicting outcomes of small cell lung cancer\",\"authors\":\"Yang Liu , Xin Zhou , Xiangxi Meng, Xiangxing Kong, Changzhi Du, Yan Cui, Yitong Liu, Jinyu Zhu, Yuan Yao, Chunxu Cao, Min Wang, Nan Li\",\"doi\":\"10.1016/j.ejrad.2025.112425\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objective</h3><div>To evaluate the prognostic value of the tumor dissemination characteristic, metabolic parameters from baseline <sup>18</sup>F-FDG PET/CT, clinical indicators, and pathological indicators in small cell lung cancer (SCLC), and to construct prognostic models.</div></div><div><h3>Materials & Methods</h3><div>SCLC patients who underwent baseline <sup>18</sup>F-FDG PET/CT were retrospectively analyzed and randomly divided into training and validation cohorts (7:3). The tumor dissemination characteristic, metabolic characteristics, morphological features, and clinical and pathological indicators were collected. Cox regression analysis was employed to identify independent prognostic factors. Prognostic models and corresponding nomograms were developed and evaluated using receiver operating characteristic (ROC) curves.</div></div><div><h3>Results</h3><div>303 patients with SCLC were enrolled (including 204 males and 99 females; median age: 62 years, interquartile range: 56–67 years). Multivariate Cox regression analysis identified age, stage, neuron-specific enolase (NSE), and the standardized distance between the two farthest lesions (SD<sub>max</sub>) as independent prognostic factors for progression-free survival (PFS). Area under curve (AUC) values for predicting 6-month, 12-month, and 24-month PFS were 0.790, 0.778, and 0.750 in the training cohort, and 0.778, 0.771, and 0.744 in the validation cohort. For overall survival (OS), age, stage, NSE, whole-body metabolic tumor volume (MTV<sub>wb</sub>), and SD<sub>max</sub> were independent prognostic factors. AUC values for predicting 1-year, 2-year, and 3-year OS were 0.861, 0.830, and 0.799 in the training cohort, and 0.834, 0.801, and 0.787 in the validation cohort.</div></div><div><h3>Conclusion</h3><div>The tumor dissemination characteristic from baseline <sup>18</sup>F-FDG PET/CT is a novel independent prognostic factor in SCLC. Additionally, the models incorporating the dissemination characteristic, metabolic parameter, and clinical indicators demonstrate excellent predictive capabilities in SCLC.</div></div>\",\"PeriodicalId\":12063,\"journal\":{\"name\":\"European Journal of Radiology\",\"volume\":\"193 \",\"pages\":\"Article 112425\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2025-09-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Journal of Radiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0720048X2500511X\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Radiology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0720048X2500511X","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Development and validation of multiparametric models incorporating 18F-FDG PET/CT dissemination characteristic for predicting outcomes of small cell lung cancer
Objective
To evaluate the prognostic value of the tumor dissemination characteristic, metabolic parameters from baseline 18F-FDG PET/CT, clinical indicators, and pathological indicators in small cell lung cancer (SCLC), and to construct prognostic models.
Materials & Methods
SCLC patients who underwent baseline 18F-FDG PET/CT were retrospectively analyzed and randomly divided into training and validation cohorts (7:3). The tumor dissemination characteristic, metabolic characteristics, morphological features, and clinical and pathological indicators were collected. Cox regression analysis was employed to identify independent prognostic factors. Prognostic models and corresponding nomograms were developed and evaluated using receiver operating characteristic (ROC) curves.
Results
303 patients with SCLC were enrolled (including 204 males and 99 females; median age: 62 years, interquartile range: 56–67 years). Multivariate Cox regression analysis identified age, stage, neuron-specific enolase (NSE), and the standardized distance between the two farthest lesions (SDmax) as independent prognostic factors for progression-free survival (PFS). Area under curve (AUC) values for predicting 6-month, 12-month, and 24-month PFS were 0.790, 0.778, and 0.750 in the training cohort, and 0.778, 0.771, and 0.744 in the validation cohort. For overall survival (OS), age, stage, NSE, whole-body metabolic tumor volume (MTVwb), and SDmax were independent prognostic factors. AUC values for predicting 1-year, 2-year, and 3-year OS were 0.861, 0.830, and 0.799 in the training cohort, and 0.834, 0.801, and 0.787 in the validation cohort.
Conclusion
The tumor dissemination characteristic from baseline 18F-FDG PET/CT is a novel independent prognostic factor in SCLC. Additionally, the models incorporating the dissemination characteristic, metabolic parameter, and clinical indicators demonstrate excellent predictive capabilities in SCLC.
期刊介绍:
European Journal of Radiology is an international journal which aims to communicate to its readers, state-of-the-art information on imaging developments in the form of high quality original research articles and timely reviews on current developments in the field.
Its audience includes clinicians at all levels of training including radiology trainees, newly qualified imaging specialists and the experienced radiologist. Its aim is to inform efficient, appropriate and evidence-based imaging practice to the benefit of patients worldwide.