Histogram analysis of synthetic magnetic resonance imaging: Correlations with histopathological factors in head and neck squamous cell carcinoma

医学 直方图 接收机工作特性 百分位 曼惠特尼U检验 头颈部鳞状细胞癌 核医学 病理 人工智能 癌症 内科学 头颈部癌 数学 统计 计算机科学 图像(数学)
作者
Fan Yang,Yujie Li,Huizi Lei,Haoran Wei,Qiang Du,Xiaoduo Yu,Xiaolu Li,Yanfeng Zhao,Lin Li,Lizhi Xie,Meng Lin
出处
期刊:European Journal of Radiology [Elsevier]
卷期号:160: 110715-110715 被引量:5
标识
DOI:10.1016/j.ejrad.2023.110715
摘要

To analyse the association between histogram parameters derived from synthetic MRI (SyMRI) and different histopathological factors in head and neck squamous cell carcinoma (HNSCC).Sixty-one patients with histologically proven primary HNSCC were prospectively enrolled. The correlations between histogram parameters of SyMRI (T1, T2 and proton density (PD) maps) and histopathological factors were analysed using Spearman analysis. The Mann-Whitney U test or Student's t test was utilized to differentiate histological grades and human papillomavirus (HPV) status. The ROC curves and leave-one-out cross-validation (LOOCV) were used to evaluate the differentiation performance. Bootstrapping was applied to avoid overfitting.Several histogram parameters were associated with histological grade: T1 map (r = 0.291) and PD map (r = 0.294 - 0.382/-0.343), and PD_75th Percentile showed the highest differentiation performance (AUC: 0.721 (ROC) and 0.719 (LOOCV)). Moderately negative correlations were found between p16 status and the histogram parameters: T1 map (r = -0.587 - -0.390), T2 map (r = -0.649 - -0.357) and PD map (r = -0.537 - -0.338). In differentiating HPV infection, Entropy was the most discriminative parameter in each map and T2_Entropy showed the highest diagnostic performance (AUC: 0.851 [ROC] and 0.851 [LOOCV]). Additionally, several histogram parameters were correlated with Ki-67 (r = -0.379/-0.397), epidermal growth factor receptor (EGFR) (r = 0.318/0.322) status and p53 (r = 0.452 - 0.665/-0.607) status.Histogram parameters derived from SyMRI may serve as a potential biomarker for discriminating relevant histopathological features, including histological differentiation grade, HPV infection, Ki-67, EGFR and p53 statuses.
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