Jie Gong, Fan Meng, Changhao Liu, Jianchao Lu, Jie Li, Zhi Yang, Hongfei Sun, Xinzhi Teng, Jiang Zhang, Jing Cai, Mei Shi, Lina Zhao
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The independent prognostic features common to both EC and NPC were screened from highly repeatable features using C-index and redundancy analysis.</p><p><strong>Results: </strong>CT-based RFs in NPC and PET-based RFs in EC demonstrated significantly higher repeatability compared to CT-based RFs in EC (median ICC: 0.886 vs 0.806; 0.897 vs 0.806; p < 0.05). While CT-based peritumoral features showed comparable repeatability to tumor features in EC (0.824 vs 0.806, p > 0.05), PET-based peritumoral features exhibited significantly lower repeatability than tumor features (0.819 vs 0.897, p < 0.05). CT-based lymph node features demonstrated significantly lower repeatability than tumor features in NPC (0.863 vs 0.886, p < 0.05). Nevertheless, the effects of bin count, feature class, and filter on repeatability demonstrated consistent patterns across different cancer types, imaging modalities, and pathological regions. Moreover, four common independent prognostic features effectively stratified both EC and NPC patients into high- and low-risk groups with significant survival differences (p < 0.05).</p><p><strong>Conclusions: </strong>RF repeatability might be affected by cancer type, pathological region, and imaging modality, while certain features maintain consistent prognostic performance across different cancer types.</p><p><strong>Critical relevance statement: </strong>The identification of high-repeatable pan-cancer prognostic radiomics features enables noninvasive patient risk stratification to guide personalized therapy, with cross-cancer consistency enhancing their applicability and convenience in clinical practice, thereby accelerating the integration of radiomics into precision oncology clinical workflows.</p><p><strong>Key points: </strong>This study examined RF repeatability and prognostic value specificity. RF repeatability varies across cancer types, regions, and modalities. 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Tumor, peritumor, and lymph node regions were defined as regions of interest. RF repeatability was assessed via perturbation analysis using intraclass correlation coefficients (ICC), with consistency and differences across cancer types, pathological regions, and modalities evaluated. The independent prognostic features common to both EC and NPC were screened from highly repeatable features using C-index and redundancy analysis.</p><p><strong>Results: </strong>CT-based RFs in NPC and PET-based RFs in EC demonstrated significantly higher repeatability compared to CT-based RFs in EC (median ICC: 0.886 vs 0.806; 0.897 vs 0.806; p < 0.05). While CT-based peritumoral features showed comparable repeatability to tumor features in EC (0.824 vs 0.806, p > 0.05), PET-based peritumoral features exhibited significantly lower repeatability than tumor features (0.819 vs 0.897, p < 0.05). CT-based lymph node features demonstrated significantly lower repeatability than tumor features in NPC (0.863 vs 0.886, p < 0.05). Nevertheless, the effects of bin count, feature class, and filter on repeatability demonstrated consistent patterns across different cancer types, imaging modalities, and pathological regions. 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引用次数: 0
摘要
目的:探讨放射学特征(RFs)的可重复性及其预后价值是否具有研究特异性。材料与方法:本回顾性研究纳入234例食管癌患者(对比增强计算机断层扫描(CECT)和氟-18氟脱氧葡萄糖正电子发射断层扫描(PET))和525例鼻咽癌患者(CECT)。肿瘤、肿瘤周围和淋巴结区域被定义为感兴趣的区域。通过使用类内相关系数(ICC)的扰动分析评估RF的可重复性,并评估不同癌症类型、病理区域和模式的一致性和差异性。使用c指数和冗余分析从高度可重复的特征中筛选EC和NPC共同的独立预后特征。结果:鼻咽癌中基于ct的RFs和EC中基于pet的RFs的重复性明显高于EC中基于ct的RFs (ICC中位数:0.886 vs 0.806;0.897 vs 0.806;结论:射频可重复性可能受肿瘤类型、病理区域和影像学方式的影响,而某些特征在不同癌症类型中保持一致的预后表现。关键相关性声明:识别高重复性的泛肿瘤预后放射组学特征,使无创患者风险分层能够指导个性化治疗,跨肿瘤一致性增强了其在临床实践中的适用性和便利性,从而加速了放射组学与精准肿瘤临床工作流程的整合。重点:本研究检验了射频的可重复性和预后价值特异性。射频可重复性因癌症类型、地区和方式而异。常见的高度可重复的射频成像推进了泛癌症生物标志物的精准肿瘤学。
Repeatability and prognostic value of radiomic features: a study in esophageal cancer and nasopharyngeal carcinoma.
Objectives: To investigate whether radiomic features (RFs) repeatability and their prognostic value are study-specific.
Materials and methods: This retrospective study included 234 esophageal cancer (EC) patients (contrast-enhanced computed tomography (CECT) and fluorine-18 fluorodeoxyglucose positron emission tomography (PET)), and 525 nasopharyngeal carcinoma (NPC) patients (CECT). Tumor, peritumor, and lymph node regions were defined as regions of interest. RF repeatability was assessed via perturbation analysis using intraclass correlation coefficients (ICC), with consistency and differences across cancer types, pathological regions, and modalities evaluated. The independent prognostic features common to both EC and NPC were screened from highly repeatable features using C-index and redundancy analysis.
Results: CT-based RFs in NPC and PET-based RFs in EC demonstrated significantly higher repeatability compared to CT-based RFs in EC (median ICC: 0.886 vs 0.806; 0.897 vs 0.806; p < 0.05). While CT-based peritumoral features showed comparable repeatability to tumor features in EC (0.824 vs 0.806, p > 0.05), PET-based peritumoral features exhibited significantly lower repeatability than tumor features (0.819 vs 0.897, p < 0.05). CT-based lymph node features demonstrated significantly lower repeatability than tumor features in NPC (0.863 vs 0.886, p < 0.05). Nevertheless, the effects of bin count, feature class, and filter on repeatability demonstrated consistent patterns across different cancer types, imaging modalities, and pathological regions. Moreover, four common independent prognostic features effectively stratified both EC and NPC patients into high- and low-risk groups with significant survival differences (p < 0.05).
Conclusions: RF repeatability might be affected by cancer type, pathological region, and imaging modality, while certain features maintain consistent prognostic performance across different cancer types.
Critical relevance statement: The identification of high-repeatable pan-cancer prognostic radiomics features enables noninvasive patient risk stratification to guide personalized therapy, with cross-cancer consistency enhancing their applicability and convenience in clinical practice, thereby accelerating the integration of radiomics into precision oncology clinical workflows.
Key points: This study examined RF repeatability and prognostic value specificity. RF repeatability varies across cancer types, regions, and modalities. The common highly repeatable RFs advance pan-cancer biomarker precision oncology.
期刊介绍:
Insights into Imaging (I³) is a peer-reviewed open access journal published under the brand SpringerOpen. All content published in the journal is freely available online to anyone, anywhere!
I³ continuously updates scientific knowledge and progress in best-practice standards in radiology through the publication of original articles and state-of-the-art reviews and opinions, along with recommendations and statements from the leading radiological societies in Europe.
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The journal went open access in 2012, which means that all articles published since then are freely available online.