Xiang Ying, Zhang Yuelang, Li Xiaohui, Xiong Yuhui, Wu Hongmei, Su Xuan, Guo Baobin, He Tuo, Wang Youren, Li Min, He Hao, Zhang Guirong, Ren Xiaoyong
Department of Radiology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
MR Research China, GE Healthcare, Beijing, China.
Quant Imaging Med Surg. 2025 Aug 1;15(8):7392-7405. doi: 10.21037/qims-2024-2564. Epub 2025 Jul 16.
Histogram parameters from synthetic magnetic resonance imaging (SyMRI) may provide more diagnostic information than mean values in differentiating benign from malignant sinonasal tumors. The histopathologic basis of SyMRI in characterizing malignant sinonasal tumors is still unclear. This study aimed to explore the potential value of SyMRI quantitative maps with whole-lesion histogram analysis in the diagnosis of benign and malignant sinonasal tumors and the correlations between SyMRI-derived histogram metrics and histopathologic features in malignant sinonasal tumors.
A total of 76 patients (29 benign and 47 malignant) with sinonasal tumors were enrolled. Nine histogram parameters of the whole tumor were extracted from T1, T2, and proton density (PD) quantitative maps, respectively. Univariate and multivariate analyses were utilized to explore the association between benign and malignant sinonasal tumors. Models based on single, combined quantitative maps, and clinical features were established to evaluate the diagnostic performance. The Spearman correlation coefficient was used to assess the correlation between histogram quantitative metrics of SyMRI and histopathological features.
For SyMRI parameters, 18 histogram metrics showed significant differences between benign and malignant sinonasal tumors (all P<0.05). The combined model based on T2 map (T2-90th percentile, Minimum, and Kurtosis) and clinical features (age and bone destruction) attained the best diagnostic performance in discrimination of benign and malignant sinonasal tumors with the highest area under the curve (AUC) of 0.908, sensitivity of 91.5%, and specificity of 82.8%. Moreover, several histogram quantitative parameters of malignancies were correlated with Ki-67 (r=-0.465 to -0.28), p53 (r=-0.476 to 0.414) and epidermal growth factor receptor (EGFR) status (r=-0.428/0.419). The T2-90th Percentile was independently associated with Ki-67 labeling index (LI) (P<0.05).
Whole-tumor histogram quantitative parameters of SyMRI could further improve the diagnostic performance in differentiating benign from malignant sinonasal tumors and may serve as potential biomarkers in assessing the histopathologic features.
合成磁共振成像（SyMRI）的直方图参数在区分鼻窦良性和恶性肿瘤方面可能比平均值提供更多诊断信息。SyMRI在表征鼻窦恶性肿瘤方面的组织病理学基础仍不清楚。本研究旨在探讨SyMRI定量图谱结合全病灶直方图分析在鼻窦良性和恶性肿瘤诊断中的潜在价值，以及SyMRI衍生的直方图指标与鼻窦恶性肿瘤组织病理学特征之间的相关性。
共纳入76例鼻窦肿瘤患者（29例良性，47例恶性）。分别从T1、T2和质子密度（PD）定量图谱中提取整个肿瘤的9个直方图参数。采用单因素和多因素分析探讨鼻窦良性和恶性肿瘤之间的关联。建立基于单一、联合定量图谱和临床特征的模型来评估诊断性能。采用Spearman相关系数评估SyMRI直方图定量指标与组织病理学特征之间的相关性。
对于SyMRI参数，18个直方图指标在鼻窦良性和恶性肿瘤之间存在显著差异（均P<0.05）。基于T2图谱（T2第90百分位数、最小值和峰度）和临床特征（年龄和骨质破坏）的联合模型在区分鼻窦良性和恶性肿瘤方面具有最佳诊断性能，曲线下面积（AUC）最高为0.908，敏感性为91.5%，特异性为82.8%。此外，恶性肿瘤的几个直方图定量参数与Ki-67（r=-0.465至-0.28）、p53（r=-0.476至0.414）和表皮生长因子受体（EGFR）状态（r=-0.428/0.419）相关。T2第90百分位数与Ki-67标记指数（LI）独立相关（P<0.05）。
SyMRI的全肿瘤直方图定量参数可进一步提高区分鼻窦良性和恶性肿瘤的诊断性能，并可能作为评估组织病理学特征的潜在生物标志物。
