Guang-Sen Pan , Xiao-Ming Sun , Fang-Fang Kong , Jia-Zhou Wang, Xia-Yun He, Xue-Guan Lu, Chao-Su Hu, Si-Xue Dong, Hong-Mei Ying
{"title":"基于德尔塔磁共振成像放射组学特征的提名图预测局部晚期鼻咽癌诱导化疗后的长期疗效","authors":"Guang-Sen Pan , Xiao-Ming Sun , Fang-Fang Kong , Jia-Zhou Wang, Xia-Yun He, Xue-Guan Lu, Chao-Su Hu, Si-Xue Dong, Hong-Mei Ying","doi":"10.1016/j.oraloncology.2024.106987","DOIUrl":null,"url":null,"abstract":"<div><h3>Purpose</h3><p>To establish and validate a delta-radiomics-based model for predicting progression-free survival (PFS) in patients with locoregionally advanced nasopharyngeal carcinoma (LA-NPC) following induction chemotherapy (IC).</p></div><div><h3>Methods and Materials</h3><p>A total of 250 LA-NPC patients (training cohort: n = 145; validation cohort: n = 105) were enrolled. Radiomic features were extracted from MRI scans taken before and after IC, and changes in these features were calculated. Following feature selection, a delta-radiomics signature was constructed using LASSO-Cox regression analysis. A prognostic nomogram incorporating independent clinical indicators and the delta-radiomics signature was developed and assessed for calibration and discrimination. Risk stratification by the nomogram was evaluated using Kaplan-Meier methods.</p></div><div><h3>Results</h3><p>The delta-radiomics signature, consisting of 12 features, was independently associated with prognosis. The nomogram, integrating the delta-radiomics signature and clinical factors demonstrated excellent calibration and discrimination. The model achieved a Harrell’s concordance index (C-index) of 0.848 in the training cohort and 0.820 in the validation cohort. Risk stratification identified two groups with significantly different PFS rates. The three-year PFS for high-risk patients who received concurrent chemoradiotherapy (CCRT) or radiotherapy plus adjuvant chemotherapy (RT+AC) after IC was significantly higher than for those who received RT alone, reaching statistical significance. In contrast, for low-risk patients, the three-year PFS after IC was slightly higher for those who received CCRT or RT+AC compared to those who received RT alone; however, this difference did not reach statistical significance.</p></div><div><h3>Conclusions</h3><p>Our delta MRI-based radiomics model could be useful for predicting PFS and may guide subsequent treatment decisions after IC in LA-NPC.</p></div>","PeriodicalId":4,"journal":{"name":"ACS Applied Energy Materials","volume":null,"pages":null},"PeriodicalIF":5.4000,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Delta magnetic resonance imaging radiomics features‑based nomogram predicts long‑term efficacy after induction chemotherapy in locoregionally advanced nasopharyngeal carcinoma\",\"authors\":\"Guang-Sen Pan , Xiao-Ming Sun , Fang-Fang Kong , Jia-Zhou Wang, Xia-Yun He, Xue-Guan Lu, Chao-Su Hu, Si-Xue Dong, Hong-Mei Ying\",\"doi\":\"10.1016/j.oraloncology.2024.106987\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Purpose</h3><p>To establish and validate a delta-radiomics-based model for predicting progression-free survival (PFS) in patients with locoregionally advanced nasopharyngeal carcinoma (LA-NPC) following induction chemotherapy (IC).</p></div><div><h3>Methods and Materials</h3><p>A total of 250 LA-NPC patients (training cohort: n = 145; validation cohort: n = 105) were enrolled. Radiomic features were extracted from MRI scans taken before and after IC, and changes in these features were calculated. Following feature selection, a delta-radiomics signature was constructed using LASSO-Cox regression analysis. A prognostic nomogram incorporating independent clinical indicators and the delta-radiomics signature was developed and assessed for calibration and discrimination. Risk stratification by the nomogram was evaluated using Kaplan-Meier methods.</p></div><div><h3>Results</h3><p>The delta-radiomics signature, consisting of 12 features, was independently associated with prognosis. The nomogram, integrating the delta-radiomics signature and clinical factors demonstrated excellent calibration and discrimination. The model achieved a Harrell’s concordance index (C-index) of 0.848 in the training cohort and 0.820 in the validation cohort. Risk stratification identified two groups with significantly different PFS rates. The three-year PFS for high-risk patients who received concurrent chemoradiotherapy (CCRT) or radiotherapy plus adjuvant chemotherapy (RT+AC) after IC was significantly higher than for those who received RT alone, reaching statistical significance. In contrast, for low-risk patients, the three-year PFS after IC was slightly higher for those who received CCRT or RT+AC compared to those who received RT alone; however, this difference did not reach statistical significance.</p></div><div><h3>Conclusions</h3><p>Our delta MRI-based radiomics model could be useful for predicting PFS and may guide subsequent treatment decisions after IC in LA-NPC.</p></div>\",\"PeriodicalId\":4,\"journal\":{\"name\":\"ACS Applied Energy Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.4000,\"publicationDate\":\"2024-08-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Energy Materials\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1368837524003051\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CHEMISTRY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Energy Materials","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1368837524003051","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
Delta magnetic resonance imaging radiomics features‑based nomogram predicts long‑term efficacy after induction chemotherapy in locoregionally advanced nasopharyngeal carcinoma
Purpose
To establish and validate a delta-radiomics-based model for predicting progression-free survival (PFS) in patients with locoregionally advanced nasopharyngeal carcinoma (LA-NPC) following induction chemotherapy (IC).
Methods and Materials
A total of 250 LA-NPC patients (training cohort: n = 145; validation cohort: n = 105) were enrolled. Radiomic features were extracted from MRI scans taken before and after IC, and changes in these features were calculated. Following feature selection, a delta-radiomics signature was constructed using LASSO-Cox regression analysis. A prognostic nomogram incorporating independent clinical indicators and the delta-radiomics signature was developed and assessed for calibration and discrimination. Risk stratification by the nomogram was evaluated using Kaplan-Meier methods.
Results
The delta-radiomics signature, consisting of 12 features, was independently associated with prognosis. The nomogram, integrating the delta-radiomics signature and clinical factors demonstrated excellent calibration and discrimination. The model achieved a Harrell’s concordance index (C-index) of 0.848 in the training cohort and 0.820 in the validation cohort. Risk stratification identified two groups with significantly different PFS rates. The three-year PFS for high-risk patients who received concurrent chemoradiotherapy (CCRT) or radiotherapy plus adjuvant chemotherapy (RT+AC) after IC was significantly higher than for those who received RT alone, reaching statistical significance. In contrast, for low-risk patients, the three-year PFS after IC was slightly higher for those who received CCRT or RT+AC compared to those who received RT alone; however, this difference did not reach statistical significance.
Conclusions
Our delta MRI-based radiomics model could be useful for predicting PFS and may guide subsequent treatment decisions after IC in LA-NPC.
期刊介绍：
ACS Applied Energy Materials is an interdisciplinary journal publishing original research covering all aspects of materials, engineering, chemistry, physics and biology relevant to energy conversion and storage. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important energy applications.
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