Suppr超能文献

局部区域复发的影像组学生物标志物:来自口腔鳞状细胞癌术前CT扫描的预后见解

Radiomic Biomarkers of Locoregional Recurrence: Prognostic Insights from Oral Cavity Squamous Cell Carcinoma preoperative CT scans.

作者信息

Ren Lei, Ling Xiao, Alexander Gregory, Molitoris Jason, Choi Jinhyuk, Schumaker Lisa, Mehra Ranee, Gaykalova Daria

机构信息

University of Maryland School of Medicine.

Thomas Jefferson University.

出版信息

Res Sq. 2024 Jan 22:rs.3.rs-3857391. doi: 10.21203/rs.3.rs-3857391/v1.

Abstract

This study aimed to identify CT-based imaging biomarkers for locoregional recurrence (LR) in Oral Cavity Squamous Cell Carcinoma (OSCC) patients. Our study involved a retrospective review of 78 patients with OSCC who underwent surgical treatment at a single medical center. An approach involving feature selection and statistical model diagnostics was utilized to identify biomarkers. Two radiomics biomarkers, Large Dependence Emphasis (LDE) of the Gray Level Dependence Matrix (GLDM) and Long Run Emphasis (LRE) of the Gray Level Run Length Matrix (GLRLM) of the 3D Laplacian of Gaussian (LoG σ = 3), have demonstrated the capability to preoperatively distinguish patients with and without LR, exhibiting exceptional testing specificity (1.00) and sensitivity (0.82). The group with LRE > 2.99 showed a 3-year recurrence-free survival rate of 0.81, in contrast to 0.49 for the group with LRE ≤ 2.99. Similarly, the group with LDE > 120 showed a rate of 0.82, compared to 0.49 for the group with LDE ≤ 120. These biomarkers broaden our understanding of using radiomics to predict OSCC progression, enabling personalized treatment plans to enhance patient survival.

摘要

本研究旨在确定口腔鳞状细胞癌(OSCC)患者局部区域复发(LR)的基于CT的影像学生物标志物。我们的研究回顾了在单一医疗中心接受手术治疗的78例OSCC患者。采用了一种涉及特征选择和统计模型诊断的方法来识别生物标志物。两个放射组学生物标志物,即高斯拉普拉斯三维图像(LoG σ = 3)的灰度共生矩阵(GLDM)的大依赖性强调(LDE)和灰度游程长度矩阵(GLRLM)的长游程强调(LRE),已证明能够在术前区分有无LR的患者,表现出极高的检测特异性(1.00)和敏感性(0.82)。LRE > 2.99的组3年无复发生存率为0.81,而LRE≤2.99的组为0.49。同样,LDE > 120的组为0.82,而LDE≤120的组为0.49。这些生物标志物拓宽了我们对利用放射组学预测OSCC进展的理解,有助于制定个性化治疗方案以提高患者生存率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ee2/10854303/ff1cbd68df46/nihpp-rs3857391v1-f0001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验