Application of Intravoxel Incoherent Motion in the Prediction of Intra-Tumoral Tertiary Lymphoid Structures in Hepatocellular Carcinoma.

IF 4.2 3区 医学 Q2 ONCOLOGY
Journal of Hepatocellular Carcinoma Pub Date : 2025-02-22 eCollection Date: 2025-01-01 DOI:10.2147/JHC.S508357
Lidi Ma, Shuting Liao, Xiaolan Zhang, Fan Zhou, Zhijun Geng, Jing Hu, Yunfei Zhang, Cheng Zhang, Tiebao Meng, Shutong Wang, Chuanmiao Xie
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引用次数: 0

Abstract

Objective: To explore the value of intravoxel incoherent motion (IVIM) sequences in predicting intra-tumoral tertiary lymphoid structures (TLSs).

Materials and methods: This prospective study pre-operatively enrolled hepatocellular carcinoma (HCC) patients who underwent magnetic resonance imaging including IVIM sequences, between January 2019 and April 2021. Intra-tumoral TLSs presence was assessed on pathological slide images. Clinical and radiological characteristics were collected. IVIM quantitative parameters and radiomics features were obtained based on the whole delineated tumor volume. By using feature selection techniques, 22 radiomics features, clinical-radiological features (lymphocyte count and satellite nodules), and IVIM parameters (apparent diffusion coefficient (ADC_90Percentile), perfusion fraction (f_Maximum)) were selected. The logistic regression algorithm was used to construct the prediction model based on the combination of these features. The diagnostic performance was assessed using the area under the receiver operating characteristic (AUC). The recurrence-free survival (RFS) was evaluated with Kaplan-Meier curves.

Results: A total of 168 patients were divided into training (n=128) and testing (n=40) cohorts (mean age: 56.83±14.43 years; 149 [88.69%] males; 130 TLSs+). In testing cohort, the model combining multimodal features demonstrated a good performance (AUC: 0.86) and significantly outperformed models based on single-modality features. The model based on radiomics features (AUC: 0.80) had better performance than other features, including IVIM parameter maps (ADC_90Percentile and f_Maximum, AUC: 0.72) and clinical-radiological characteristics (satellite nodules and lymphocyte counts, AUC: 0.59). TLSs+ patients had higher RFS than TSLs- patients (all p <0.05).

Conclusion: The nomogram based on the proposed model can be used as a pre-operative predictive biomarker of TLSs.

Critical relevance statement: The nomogram incorporating IVIM sequences may serve as a pre-operative predictive biomarker of intra-tumoral tertiary lymphoid structure (TLS) status.

体素内非相干运动在肝癌肿瘤内三级淋巴结构预测中的应用。
目的:探讨体素内非相干运动(IVIM)序列在预测肿瘤内三级淋巴结构(TLSs)中的价值。材料和方法:这项前瞻性研究在2019年1月至2021年4月期间,术前入组接受磁共振成像(包括IVIM序列)的肝细胞癌(HCC)患者。病理切片图像评估肿瘤内TLSs的存在。收集临床和放射学特征。基于整个描绘的肿瘤体积获得IVIM定量参数和放射组学特征。通过特征选择技术,选取22个放射组学特征、临床放射学特征(淋巴细胞计数和卫星结节)和IVIM参数(表观扩散系数(adc_90百分位)、灌注分数(f_Maximum))。利用logistic回归算法,结合这些特征构建预测模型。使用接收器工作特征(AUC)下的面积来评估诊断性能。采用Kaplan-Meier曲线评价无复发生存期(RFS)。结果:168例患者被分为训练组(n=128)和测试组(n=40),平均年龄:56.83±14.43岁;男性149人[88.69%];130 tls +)。在测试队列中,结合多模态特征的模型表现出良好的性能(AUC: 0.86),显著优于基于单模态特征的模型。基于放射组学特征的模型(AUC: 0.80)优于其他特征,包括IVIM参数图(ADC_90Percentile和f_Maximum, AUC: 0.72)和临床放射学特征(卫星结节和淋巴细胞计数,AUC: 0.59)。TLSs+患者的RFS高于TSLs-患者(均p)结论:基于该模型的nomogram可作为TLSs的术前预测生物标志物。关键相关性声明:包含IVIM序列的nomogram可作为肿瘤内三级淋巴结构(TLS)状态的术前预测性生物标志物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
0.50
自引率
2.40%
发文量
108
审稿时长
16 weeks
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