CT多维放射组学联合炎症免疫评分术前预测食管鳞状细胞癌病理分级。

IF 3.8 2区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Academic Radiology Pub Date : 2025-01-13 DOI:10.1016/j.acra.2024.12.030
Shaokun Zheng, Jun Chen, Anwei Ren, Weili Long, Xiaojiao Zhang, Jiqiang He, Ming Yang, Fei Wang
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引用次数: 0

摘要

理由和目的:炎症和免疫生物标志物可促进食管鳞状细胞癌(ESCC)的血管生成和增殖转移。病理分级程度反映了ESCC的肿瘤异质性。目的是开发和验证基于增强CT多维放射组学结合炎症免疫评分(IIS)的nomogram预测低分化ESCC。材料与方法:回顾性研究ESCC患者266例,随机分为训练组(N=186)、验证组(N=80)和完整数据组(N=266),确定总生存期,术后随访。对肿瘤影像进行分割,在CT动脉期和静脉期形成瘤内和瘤周3mm的三维感兴趣体积(VOI)区域,提取3404个放射组学特征。最后,计算肿瘤内动脉期(aInRads)、肿瘤周围3mm (aPeriRads3)和静脉期(vInRads)、肿瘤周围3mm (vPeriRads3)的放射组学评分。采用Logistic回归将四个队列的分数融合形成一个堆叠。此外,还分析了16项炎症免疫生物标志物,包括天冬氨酸转氨酶与淋巴细胞比值(ALRI)、天冬氨酸转氨酶与丙氨酸转氨酶比值(AAR)、中性粒细胞倍γ -谷氨酰转肽酶与淋巴细胞比值(n γ γ lr)、白蛋白加5倍淋巴细胞总和(PNI)等。最后,利用ALRI、AAR、n - γ lr和PNI构建IIS。通过受试者工作特征曲线(AUC)下面积、校准曲线和决策曲线分析(DCA)来评价模型的性能。结果:堆叠和IIS是预测低分化ESCC的独立危险因素(p结论:综合术前炎症免疫生物标志物、瘤内和瘤周CT放射组学的nomogram预测低分化ESCC具有较高且稳定的诊断效能,有望为个体化手术选择和治疗提供指导。数据和材料的可获得性:研究中包含的原始手稿包含在文章中。进一步的询问可直接向通讯作者提出。
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CT Multidimensional Radiomics Combined with Inflammatory Immune Score For Preoperative Prediction of Pathological Grade in Esophageal Squamous Cell Carcinoma.

Rationale and objectives: Inflammation and immune biomarkers can promote angiogenesis and proliferation and metastasis of esophageal squamous cell carcinoma (ESCC). The degree of pathological grade reflects the tumor heterogeneity of ESCC. The purpose is to develop and validate a nomogram based on enhanced CT multidimensional radiomics combined with inflammatory immune score (IIS) for predicting poorly differentiated ESCC.

Materials and methods: A total of 266 ESCC patients from the retrospective study were included and randomly divided into a training set (N=186) and a validation set (N=80), and a complete data set (N=266), and overall survival was determined to follow up after surgery. The tumor imaging was segmented to form intratumoral and peritumoral 3 mm areas of 3D volume of interest (VOI) on CT arterial and venous phases, and 3404 radiomics features were extracted. Finally, the radiomics scores were calculated for arterial phase intratumoral (aInRads), peritumoral 3 mm (aPeriRads3), and venous phase intratumoral (vInRads), peritumoral 3 mm (vPeriRads3). Logistic regression was used to fuse the four cohorts of scores to form a Stacking. Additionally, sixteen inflammatory-immune biomarkers were analyzed, including aspartate aminotransferase to lymphocyte ratio (ALRI), aspartate aminotransferase to alanine aminotransferase ratio (AAR), neutrophil times gamma-glutamyl transpeptidase to lymphocyte ratio (NγLR), and albumin plus 5 times lymphocyte sum (PNI), etc. Finally, IIS was constructed using ALRI, AAR, NγLR and PNI. Model performance was evaluated by area under receiver operating characteristic curve (AUC), calibration curve, and decision curve analyse (DCA).

Results: Stacking and IIS were independent risk factors for predicting poorly differentiated ESCC (P<0.05). Ultimately, three models of the IIS, Stacking, and nomogram were developed. Compared with the Stacking and IIS models, nomogram achieved better diagnostic performance for predicting poorly differentiated ESCC in the training set (0.881vs 0.835 vs 0.750), validation set (0.808 vs 0.796 vs 0.595), and complete data set (0.857 vs 0.823 vs 0.703). The nomogram achieved an AUC of 0.881(95%CI 0.826-0.924) in the training set, and was well verified in the validation set (AUC: 0.808[95%CI 0.705-0.888]) and the complete data set (AUC: 0.857[95%CI 0.809-0.897]). Moreover, calibration curve and DCA showed that nomogram achieved good calibration and owned more clinical net benefits in the three cohorts. KaplanMeier survival curves indicated that nomogram achieved excellent stratification for ESCC grade status (P<0.0001).

Conclusion: The nomogram that integrates preoperative inflammatory-immune biomarkers, intratumoral and peritumoral CT radiomics achieves a high and stable diagnostic performance for predicting poorly differentiated ESCC, and may be promising for individualized surgical selection and management.

Availability of data and materials: The original manuscript contained in the research is included in the article. Further inquiries can be made directly to the corresponding author.

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来源期刊
Academic Radiology
Academic Radiology 医学-核医学
CiteScore
7.60
自引率
10.40%
发文量
432
审稿时长
18 days
期刊介绍: Academic Radiology publishes original reports of clinical and laboratory investigations in diagnostic imaging, the diagnostic use of radioactive isotopes, computed tomography, positron emission tomography, magnetic resonance imaging, ultrasound, digital subtraction angiography, image-guided interventions and related techniques. It also includes brief technical reports describing original observations, techniques, and instrumental developments; state-of-the-art reports on clinical issues, new technology and other topics of current medical importance; meta-analyses; scientific studies and opinions on radiologic education; and letters to the Editor.
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